ISSN 1880-8468
Technical Report ofInternational Development Engineering
国際開発工学研究報告

TRIDE-2023-02

March 31, 2023

Abstracts of Bachelor Theses Presented
from September 2016 to March 2022

Department of International Development Engineering,
Graduate School of Science and Engineering,Tokyo Institute of Technology
http://www.ide.titech.ac.jp/TR

Preface
This technical report consists of the abstracts of Bachelor theses presented in the
Department of International Development Engineering, Tokyo Institute of Technology,
on August 2, 2016, February 28, 2017, August 1, 2017, February 23, 2018, August 8,
2018, February 22, 2019, August 19, 2019, February 20, 2020, February 18, 2021, August23, 2021, and February 17, 2022.

iTechnical Report of International Development Engineering
TRIDE-2023-02
Table of Contents(Completeng in September 2016)
Parameter Selection of Support Vector Machine with Variable Kernel Function…………..….…………………………….…………………………………… Akira SHIOZUKA 1
Selective Catalytic Reduction by C3H6 over CeO2-ZrO2…………………….……...……………………………………….…………… Takumi KOMORI 3
Microbial Community Analysis in Anaerobic Digestion of Oil-Containing Wastewater...…………..………….………………………………………………………….…… Jou FUJITA 5(Completeng in March 2017)
Prediction of Future Population Distribution of Jakarta on the Basis of Global Warming Scenario……………….…...……………………………………………..…………… Shun TAKAKUWA 7
Exploring the Optimal Number of Days in East China Sea Cruise Tourism from/to Shanghai………………...………………………………….…………………..……… Zhonghui ZHENG 9
Raspberry Pi による低コストな屋内位置推定システムの構築……………..…………………………………………………………………………… 姜 竣銘 11
A System of Extracting Common Form in Multiple Natural Scene Images and Reading Form-Data……….………….…………………………………………………...…………Yuhang HUANG 13
A Study on Travel Behavior and Characteristic of Residential Zone in Satellite Metropolitan Cities
for Urban Function Attraction -Case Study of Kashiwa City and Surrounding Cities……….………………………………………………………………….………… Yiting JIANG 15
高速コンポスト化に寄与する新規な好熱性酢酸分解菌の特定………..…………………………………………………………………...………… 氏家 大祐 17
Clarification of Paratransit Industry and Driver’s Life Satisfaction Analysis Considering Social
Capital in Sri Lankan Cities………….…...…………………………………………………………………….… Yuri SAITO 19
Simulation of Forest Fire using a Coupled Weather-Fire Model WRF-Fire……..……….…………………………………………………...………… Kohei YAMASHITA

21

Design of a Rectangular Patch Antenna for Radio Propagation Measurement…….……….………………….…………………………………………….…………… Xin DU 23
SFM-AKAZE による 3D 点群再構築に関する研究………..………………………………………………………………………...……… 魏 嘉昊 25
ii

Fe 交換ゼオライト触媒による C3H6 を用いた NO 選択還元……..……….………………….……….……………….……….……….…….………… 譚 楊 27
地方自治体の水道事業体の経営効率性と国際活動の関係……..……………………………………………………………………….….……. 山田 優志 29
Concept Study of a Deployable Atmospheric Reentry Vehicle with Waverider Effect…….………..……………………………………………….….………. Tomohiro WATANABE 31
地域特性がエコツーリズムの特徴に与える影響…..……………………………………………………….……….……….……… 海宝 慎太郎 33
Numerical Analysis of Storm Surge Inundation in Tacloban City Caused by the 2013 Typhoon
Haiyan − Analysis of Evacuation and Effectiveness of the Embankment……...……………………………………………..………………………….… Shota KUROBE

35

A Study on Continuity of Utilizing a Closed School for Exchange from the Viewpoint of Travel
Inflow..……...…………………………………………………….….……. Haruyoshi NAGAFUNE 37
Effects of AC Voltage on Asymmetric Capacitor Thruster..……………...………………………………………………….……. Shunnosuke YAMADA 39
Outdoor-to-Indoor Radio Propagation Measurement by using an Unmanned Aerial Vehicle in
2.4GHz band….…...………………………...………………….…..……….……………………. Qiwei FAN 41(Completeng in September 2017)
改良されたクラスタリングによるウェーブレット画像符号化の線形予測...………….…………...…….....…………………………………….……………………. 李 然

43Pretreatment of Feed Oil for Biodiesel Fuel Production…....………………………………………………………………………………… Zhuoheng LI 45
Effects on Landing Aircrafts by Wind around the Hangars at Haneda Airport……………………………………..………….…...…………………………… Yuhei MORITA 47
Effects of Electrode Tip Curvature and Distance between Electrodes on Electric Field……………….……………………………….……………………………..…… Gota NURISHI 49
財務的内部収益率から見た大型ショッピングモールにおける太陽光発電システムの導入可能性；上海（中国）を事例として…………………………..……………………………………………………………… 顧 任遠 51
Analysis of Microbial Flora in Canned Shirasu Heat-Sterilized under Reduced Pressure………………….…………………..……………………………………..…… Tatetsu MAEDA 53(Completeng in March 2018)
iii

Assessment of Technical Feasibility of Jakarta’s Giant Seawall Project…………………….………….…………………………………………………….… Yi XIONG

55

Numerical Modeling for Predicting River Flow in the Mekong Delta…………...…………….…..…..…………………………………………….…… Mizuho ARAI 57
Trial Production of Self-Rechargeable Drone………………………….………………….…………………………...…………… Siqi YUAN 59
日本全域における大気境界層水平風速の年間スペクトル特性…………………………………..…………………………………...………………… 何 暁卿 61
The Effect of Consolidation and Privatization of Ports in Proximity － Case Study in Osaka andKobe Ports －………………………………..……..………….…………………...………… Hoshi TAGAWA 63
Study on Wave Pressure Exerted on Piles Installed in Swash Zone…………………….……………..………………………………………….… Takayuki SUGIU

65

Recovery of Acetonitrile from Pharmacy Factory Wastewater by Distillation Process……………….………………………………....……………………………………… Jierui XU 67
Future Precipitation Prediction Based on Climate Change & Urbanization Scenarios in a Megacity—
Jakarta…………………...…………………………………………….……………….… Yinglan QIN 69
Simultaneous Measurement of Liquid Surface Tension and Contact Angle.…………………………………………….……………………………… Keiichiro HAMADA 71
Design Method of Angle of Beams to Maximize Gripping Force of Multi-Beam Structure…………………………..……………………………………….……… Hiroaki YAMASHITA

73

Utilization of Bio-Oil Derived from Wood Residues in Rubberwood Process…………………….…………………………………..……………………… Haruka TANAKA

75

Feasibility Study of Mars Orbit Insertion by Aerocapture using Solar Sail………………………………..……………………..………………… Yuichiro TSUKAMOTO 77
Global Exploration of Asteroid by Numerous Microlanders….……………………………………………………………………………… Seonghwan YEO 79
Effect of Ions Generated Between Electrodes on Breakdown Voltage………………………….……………………………………….………………… Masaki HIRA 81
Abnormal Tides Caused by Storm Surges in Tokyo Bay………………………………….………………………….…..………… Atsuhei TAKAHASHI 83
Phosphate Recovery using Calcium Silicate Hydrate Synthesized from Coal Fly Ash………….…………………….………………………….…………………………… Yu ANDO 85
Clarification of Public Transport Usage Conditions in Ahmedabad, India…………………………….……………….………………………………… Takashi HIRAIDE 87
iv

3D Model Construction of Indoor Environment using Photogrammetry…………….……..…………………………………..……………………...…… Shan WANG 89
都市におけるミツバチプロジェクトが地域に与える環境・社会的影響…………………..……………………………………………………………...…… 神田 大樹 91
Visualization of Indoor Radio Wave Propagation by using Augmented Reality Technology…………………………………………………………………...……………… Jiayue CHENG 93
Wavelet Based Image Coding via Prediction using Neural Networks…...………………………………………………………………...…… Takuma TAKEZAWA

95

Equilibrium Adsorption of Manganese using Mordenite………...…………………………………………………...………………… Shunya HATTORI 97
オセアニア島嶼諸国における水道事業の効率性分析………………………………………………………………………………….… 国分 絋一郎 99
Influence of Speed of Gate Opening in Dam-Break Experiment………….……...………………..……………………………………… Fumitaka FURUKAWA 101
Characteristics of the Users of Residential Photovoltaic and Energy Storage Systems in Japan………………….……….....………………………………………………… Hiromichi MITANI 103
Possibility of Tethered Aerocapture for Direct Orbit Insertion….……………………………………………………..…………………………..… Saho KATO 105
TIV Application to Simultaneous Multiple Surface Observation………………………….……...…….………………………………………… Yoji ISHIBASHI 107
Phytoremediaton of Aquatic Environment Polluted by Antibiotics…………………….……..…………………………………………………… Shuyang WANG 109
チェルノフ距離に基づく局所フィッシャー線形判別分析…………………………………………………….…………………………………… 湯 韻佳 111(Completeng in September 2018)
Study of GPU Accelerated Computer Vision…….…………………………………………………………….…………………… Shitian NI 113
Nitrogen Oxides Removal using Red Mud…………………………………….…………………………………………………..… Siqi WU 115(Completeng in March 2019)
Study on Mechanism of Potassium Removal from Palm Kernel Shell by Hydrothermal Treatment……………….……………………………………………………………….…… Tsamara Tsani 117
Hydraulic Experiment and Numerical Analysis on Tsunami – Storm Surge Entering through
Breakwater Moundv

…………………………………………………………………….……..… Yoshifumi TAKATA 119
Experiment System to Examine the Effect of Cathode Temperature on Electric Field Intensity at
Breakdown……………………………………………………………………………..…… Ryoji ICHISAKI 121
Image Feature Extraction by Sliding Discrete Fourier Transformation………………………………………………………….……………………...………… Xu SUN 123
食品安全認証の取得有無と日本食品企業の特徴との関係……………………………………………………………………………………...….. 周 温文 125
GPU Acceleration of Initial Search Method for Regional Image Matching…………………………………………………………………………………..…… Moran LEE 127
All-Day Energy Harvesting Power System Utilizing a Thermoelectric Generator……………………………………………………………………………… Yasuki KADOHIRO 129
Liquid-Liquid Equilibria of Terbium and Dysprosium with PC-88A as Extractant…………………………………………...…………………………………… Junki KURIHARA 131
Enhancing NH3 Recovery from Aquaculture Sludge Composting by Inoculation of the Sludge
Solubilizing Bacteria……………………..………………………………………………………… Ryo NAKAGAWA 133
New Activation Functions by Simulating Synaptic Plasticity to Enhance Forgetfulness in Neural
Network…………………………………………………………………….…….………… Xiaochen LIU 135
Recovery of Oil from Spent Coffee Grounds by Solvent Extraction for Biodiesel Production………………………….………………………………………...……………… Thisang PHAM 137
Earth-Moon Transportation System using a Reusable Vehicle and Fuel Stations……………………..…………………………………………………………..… Ayu NUMATA 139
2 次元曲面において熱画像風速測定法(TIV)の結果の表現…………………………………………………………………………………………….. 孫 岳 141
Effect of Pull-Off Angle on Adhesion Force between Side Surface of PDMS Beam and Rigid Body……………………………………………………………………………..… Suguru NORIKYO 143
Application and Comparison of Cooley-Tukey Algorithms for Ocean Rendering with Spectral
Domain Approach………………………….…………………………………………………….…… Eungang SON 145
籾殻灰の有効利用－CA(OH)2 を鉱化剤としたゼオライトの合成に関する研究………………………………………………………………………………………….… 陸 遥 147
インド・アーメダバードにおけるオートリキシャ旅客特性の解明……………………………………………………………………………………….…… 郭 欣 149
Adhesion Model of Side Contact for Elastic Beam with Consideration of Inflection Pointvi

…………………………...……………………………………………………… Saneyuki KATO 151
公共交通指向型開発のための都市成長モデルの開発……………………………………………………………………………………….… 董 思繁 153
Exploring Europa by Plume Breaking……...…………………………………………………………………..…… Juyon YAMAZAKI 155
Development and Calibration of Radio Sensor using Off-the-Shelf Software-Defined Radio for
Location Fingerprinting……………………………………………………………….……………...…… Haichen JIANG 157
Separation of Acetonitrile from Pharmaceutical Wastewater using Solvent Extraction……………………………………………………………………………..…… Kaito SAWADA 159
無線ネットワークセル設計のためのニューラルネットワークを用いた電波伝搬損失予測…………….………………………………………………………………………….. Yongri JIN 161
指向性チャネルモデルに基づく伝搬パラメータからの大型アレーMIMOシステムのチャネ
ル容量評価……………………………………………………………………….………………… 趙 恒偉 163
Development of Channel Sounder for SHF Band Channel Measurement by Virtual Planar Array…………………………………………………………...……………………… CheChia KANG 165
Selection Guidelines Windmill and Generators for Small Wind Power Generation System
Considering Maximum Power Point Tracking…….…………………………………………………………….…………… Honoka HAYASHI 167
Orbital Transfer System for Microsatellites using Laser Propulsion…………...…………………………………………………………...…………… Shun SUZUKI 169
全球情報を用いた都市幾何形状情報作成手法の提案……………………………………………………………………………….……… 富沢 哲郎 171(Completeng in September 2019)
A Study on Separation of Lithium and Cobalt from Mixture Solution………………………………………………………………………..…… Daisuke AKAZAWA 173
サプライチェーンを考慮した東京都市圏物流施設の年類型別立地分析……………………………………………………………………………………………. 衣 然 175
都市近郊における農業の特徴の二時点比較：千葉県を事例として………………………………………………………………………………………. 遠藤 奈美 177(Completeng in March 2020)
Comparative Analysis of Network Transportation Costs for Truck Platooning and Existing Driving………..……………………………………….…………………………………… Hyunsoo LEE 179
vii

Numerical Analysis for Precise Estimation of Wave Pressure and Overtopping around Coastal Dike………………………………………………………….…….………..…… Takumi MIZUOCHI 181
Analysis of Characteristics and Benefits of Sharing Service Users…….……………………………………………….………………....…… Hidehiko MATSUDA 183
ドップライダーで観測された建物後流（ストリーク）の研究…….…………………………………………………………….…….………..…… 桐谷 蒼介 185
GDP と人口によるグローバル都市成長モデルの改良…………………...………………..…..………………….…………….…….………… Zuo HE 187(Completeng in March 2021)
Image Super-Resolution by a Convolutional Neural Network using a Difference Image for Learning…………………...…………………………………………..…….………..… Haruki IKENOUE 189
Effect of pH Regulation on Pig Manure Composting………………………....………………………………………….…….……….. Nobuaki HOJO 191(Completeng in September 2021)
外国人観光客の避難所利用に対する日本人の受容意識…………………...………………………………………………….…….………..…… 厳鮮詠 193(Completeng in March 2022)
Experimental Investigation on Accuracy of Surface Tension Determined by Sessile Drop Shape……...…………….…..…………………………………….…….……..…Yuino MUROZONO 195

􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂
􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂􇀂

viii

Parameter selection of Support Vector Machine with Variable Kernel
Function
Student Number:12_07140 Name:Akira Shiozuka Supervisor:Yukihiko Yamashitak ( x, z )  x ,  y  .

1 Introduction(2)

Then eq.(1) can be written as

Kernel method is a data analysis methodology which has been rapidly developed in the field of computer science in recent years. For example, support vector machines (SVM) based on
on kernel method have demonstrated very highperformance in classification and regression.
The central idea of kernel method is mapping
an original input vector into a high dimensionalfeature space to change the nonlinear classificclassification functions to linear classification
functions. However to realize such excellent
performance, the proper selection of feature
mappings is very important. For the purpose,
The variable kernel method (VKM) was researched. VKF can change the kernel parameter according to the position, although all sample patterns have the same parameter in the standard kernel method.
In this paper, I propose methods to fix parameter for VKF to improve recognition performance. I explain the framework of VKF, VKF-SVM,
and propose a new parameter for selection method and 3 types of sample number selection method. I also show experimental results by using
a toy problem and UCI datasets.

Nd x   w, x    , w   n xn  . (3)
2.3

n 1

Framework for VKF

As an example of kernel method several feature mapping j x   j  1, J  of which inner product can be calculated analytically areprepared.Their kernel functions are denoted byki , j x, y   i x ,  j x  .

(4)

In VKF, nonlinear feature mapping n foreach leaning pattern xn and only one feature
mapping  0 for an unknown pattern x are
prepared. The model of w in eq.(3) can be denoted byNw   n  n  xn  .

(5)

n 1

Then, the discriminant function is given byd x   w,  0 x    ,
N

2

2.1

  n k n , 0  x n , x    .

Framework for VKF

(6)

n 1

Mercer’s Theorem

In VKF, we can change the kernel parameter i of xi according to the distances to theLet xn, yn  n  1, N  be a set ofsample, where each xn is a sample patter andadjacent samplig points.

yn is its label ( ± 1). The inner productbetween x and z is denoted by x, z . In
this paper, a liner discriminant model for abinary problem is discussed. In case of thestandard kernel method, a Marcer kernel
function k x, z  is fixed and the kernelparameter  is constant. The discriminantfunction is given by

3

VKF with SVM
SVM can be summarized as minimizingNw  Cn .
2

(7)

n 1

subject to (for any n  1,2, , N )Nd  x    n k  xn , x    ,(1)

yn d ( xn )  1   n  0,  n  0 .

n 1

where n are coefficients and  is a threshold. From Mercer’s theorem, we can consider
there exists a feature mapping  x  that cansatisfy(8)

where C is a constant
VKF is applied to SVM. It is denoted by VKFSVM. In the previous work, VKF parameter  i
was selected by average of the distances from1

Table 1: Error rates for UCI datasets(DIS-select)(a)SVMNo SNS

Distance

Average

Density

SVM

Ba

10.9±0.6

10.7±0.6

10.8±0.5

10.9±0.7

10.8±0.5He

16.5±3.8

16.4±3.4

16.9±3.6

16.4±3.2

17.8±3.6Th

4.5±2.2

4.0±1.6

4.5±1.6

4.4±2.2

5.7±2.4

Ti

22.3±0.3

22.2±0.4

22.4±0.3

22.3±0.3

22.4±1.2x10.1±0.4

10.1±0.4

10.1±0.4

10.1±0.4

10.2±0.3

Table 2 : Error rates for UCI datasets(Den-select)
No SNS

Distance

Average

Density

SVM

Ba

10.7±0.5

10.7±0.5

10.8±0.4

10.7±0.5

10.8±0.6He

16.5±3.6

16.7±3.717.1±3.7

16.4±3.617.8±3.7Th

4.9±2.8

4.9±2.7

6.1±3.7

5.1±2.7

5.7±2.5Ti

22.4±0.6

22.8±0.923.4±1.522.7±0.6

22.5±1.3

Wa

10.3±0.4

10.3±0.4

10.3±0.4

10.3±0.4

10.3±0.4

and the smallest  i as  0 . From eq.(4), thekernel function for VKF is given by(b)VKF-SVM with Density selection and Area xz 2 
 2 i j 
k i , j  x, z  
exp   22 
 2  2 




j 
i
j 
 i

M

regularFigure 1 : Results of toy problem(12)Then, I apply VKF-SVM to a toy problem and5 types of UCI datasets. For the toy problem,the error rate for SVM is 7.58%. And the rates
for SVM-VKF with DIS-select without SNS ,DIS-SNS, AVE, DEN are 7.20%, 7.18%, 7.20%, and 7.06%. On the other hands the rates for
SVM-VKF with DEN-select under there are
6.20%, 6.21%, 6.14% and 6.00%. DEN-selectwith DEN-SNS is the best with parameter :  0.178, C  178, r  1.005 . Fig.1(a) shows
result with SVM, and Fig.1(b) shows results of
VKF –SVM with the best method. We can see
clearly that Fig.1(b) is more smooth. Tables 1
and 2 show error rates for UCI datasets. From
the tables, we can see VFK -SVMs with SNSsoutperform SVM those no-SNS.

xi to its nearby points (DIS-select).

I propose to decide  i by an inverse densityof nearby points. (DEN-select) In the previous
work , the number of samples for the selection
is fixed. I propose to change it and three sample
number selection (SNS) method. r is a SNS
parameter and di , n is distance from xi tonearest n -th
points.
(1) Distance SNS (DIS-SNS)d n1 d n  r .

(9)(2) Averaged distance SNS (AVE-SNS)

 1 n1   1 n  dl    dl   r .
 n  1 l 1   n l 1 

(10)

5

(2) Density SNS (DEN-SNS) n 1 2 
 d n ! 

4

 n 
 2   r .
 dn 

Conclusion

In this paper, I proposed new parameter andsample number selection methods. For future
work, I have to use a wide range of parameterand propose a new parameter selection method
to suit VKF.

(11)

Experiment Result

References[1] Naoya and Yukihiko Yamashita, ”Simultaneous learn- ing of localized

In the experiment , I used the Gaussian
kernel function (GKF) for a feature mapping

multiple kernels and classifier with,wighted regularization” Structural ,Syntactic and Statistical Pat- tern Recognition, pp,543-362, Springer Berlin2Selective Catalytic Reduction by C3H6 over CeO2-ZrO2Student Number: 09-09638

Name: Takumi Komori Supervisor: Hirofumi HINODE

1. Introduction

2. Experimental

Nitrogen oxides (NOx) is general term for NO,

In this study, CeO2-ZrO2 catalysts wereNO2 and N2O. NOx causes several environmental

prepared by manual mixing method using CeO2

problems, such as photo- chemical smog, acid rain

(JRC-CEO1) and ZrO2 (JRC-ZRO6) as precursors.

and global warming. Main sources of NOx are

CeO2 and ZrO2 were mixed together manuallyfactories,

automobiles.

with ethanol, then dried, and calcined at 550℃ in

Especially more than half of NOx are emitted

air for 4 hours. Then the catalysts were crushedfrom automobiles. So this is important to develop

and sieved to 0.71-1.00 mm [4].

powerplantsandcatalysts for NOx reduction.

The

HC-SCR

activity

experiments

were

Nowadays, three-way catalysts (TWC) are

carried out in a fixed-bed flow reactor. The

generally used to reduce NOx in automobiles.

reactant gas was composed of 1500 ppm NO, 10%

This catalyst can reduce NOx high efficiency at

O2, 1500 ppm C3H6 and He as a balance gas.

specific air to fuel (A/F) ratio. However, theCatalyst was used with a corresponding spacedevelopment of lean-burn engines (A/F = 20~60)

velocitythat have higher fuel economy and cleaner

changed stepwise from 150℃ to 550℃.

of

13000h-1.

The temperature was

emissions requires another type of catalyst forThe

NOx reduction. One common method to reduceanalyzed

NOx

NOA-7000) while CO2 was analyzed using gas

inexhaust gas is

selective catalytic

NO

and

by

NO2

NOx

concentrations
analyzer

were(Shimadzu,

reduction of NO using hydrocarbon as reducing

chromatographagent (HC-SCR of NO) [1].The main reactions ofdetector (GL Science, GC-3200). The catalysts

HC-SCR are the following:

were characterized by TG-DTA, XRD.

2NO+O2 → 2NO2

withthermalconductivity(1)

3. Results and Discussion

3NO+3NO2+C3H6 → 3N2+3CO2+3H2O (2)Previous Studies showed that CeO2-ZrO2
catalysts have potential of HC-SCR [2][3].

Fig.1 shows the results of catalytic activity

However in those studies, catalysts were madetests of each catalyst. By adding CeO2, the peak of

only 1 to1 ratio. Therefore in this study, I decided

the activity shifted to lower temperature. In thisto prepare some CeO2-ZrO2 catalysts by changing

study 30wt% CeO2-ZrO2 catalyst shows thethe ratio, and compare each catalytic activity tohighest activity at 400℃.

reduce NOx.

3

From this test we can see that NO was reduced by
HC-SCR in this study.
XRD patterns of each catalyst are shown in
the Fig.3. It can see that by adding CeO2, CeO2
peaks become stronger and ZrO2 peaks become
weaker. From this figure, it can say that CeO2
exist as crystal in these catalysts.
Fig.1 Catalytic activity of ZrO2 and 10wt%, 30wt%,
50wt%, 70wt% CeO2-ZrO2 for the reduction of NO to N2
using C3H6 as a reductant

Fig.4 XRD patterns of the catalysts

4. Conclusion
Fig.2 Catalytic activity for the oxidation of C3H6 to CO2

In this study, the peak of catalytic activity
Fig.2 shows the catalytic activity of eachshift to lower temperature by mixing CeO2 to ZrO2.

catalyst for the oxidation of C3H6 to CO2. By

And 30wt% CeO2-ZrO2 showed the highest

adding CeO2, the oxidation ability of the catalyst

activity at 400 ℃ in prepared catalysts. And I

became higher. It can be considered that CeO2

made sure NO reduction by HC-SCR, and CeO2

helps oxidation in HC-SCR.

helps oxidation.

Reference[1]R.Burch et al, Appl.Catal.B, 11, (1997)[2]「いまセリウムがおもしろい」, (株)ティー・
アイ・シー,[3]Bantan

初版 (2005)
Furat;

bachelor

thesis,Tokyo

institute of technology (2013)[4]yang wang; master thesis, Tokyo institute ofFig.3 Effect of C3H6

technology (2010)
To make sure HC-SCR, I compared reduction
activity of 30wt%CeO2-ZrO2 in case that there is
C3H6 or not. The result of this test is Fig.3. It
shows that catalyst activity without C3H6 is lower.

4Microbial community analysis in anaerobic digestion of oil-containing wastewaterStudent Number: 12-12767

Name: Jou FUJITA

1. Introduction

Supervisor: Kiyohiko NAKASAKI

O-0, 21-95 with O-25 and day 96-370 with O-50.
For the startup of the experiment, distilled water, 200 mL of
O-0 substrate and 65 g of granular sludge were mixed in twoof the anaerobic sequencing batch reactor (ASBR). These
reactors had a working capacity of 2.5 L, and operated 39℃
with agitation at 100 rpm. In these experiments, 200 mL ofsupernatant was extracted from the reactor and the same
volume of fresh substrate was fed every day.
The pH in the supernatant was measured by the pH meter.
A sample of the exhaust gas was captured into a sampling
bag and gas compositions were measured by GC-TCD. Gas
volume was measured using dry test gas meter.
The microbial community in the sludge was determined bydenaturing gradient gel analysis, and bacterial 16S rRNA
gene fragment was used. Characteristic bands in the DGGE
gel were excised and base sequences of the DNA containedin the bands were determined. Also to determine the
distribution of bacterial community, next generation
sequence method using MacQIIME was used.

Lipid is one of the major organic matters in wastewaterfrom food processing factory. Lipid can be a good substrate
for anaerobic digestion as in theoretical value, 850 mL of
methane gas can be produced from 1 g of lipid, while themethane production from protein and carbohydrate are 500
and 395 mL/g respectively [1]. However, the anaerobic
digestibility of lipid is not satisfactory due to the low
biodegradability. To solve the problems, lipid is often
pre-hydrolyzed by reagent or enzyme. Moreover enzyme
pretreatment is more lower-cost than chemical treatment. So
there is possibility of improving anaerobic digestion frompretreated oil by microorganism producing surfactant.
Anaerobic digestion of organic matter is a complex process
which is governed by distinct microbial community. To
achieve anaerobic digestion of a new substrate, the sludge
needs to be adapted to new substrate. This adaptation
generally involves a significant change in the
microorganisms present in the sludge. An understanding ofthese changes in the microbial community would allow us toknow which microorganisms contribute to higher methane
production during anaerobic digestion, which would allow
the development of system to monitor the presence andabundance of relevant microorganisms.
This study analyzed the changes in the microbialcommunity during the adaptation of sludge to soybean oil
after an increasing the concentration of soybean oil to feed inanaerobic digestion process. Furthermore, the microbialcommunity in the reactor with soybean oil feeding wascompared to the one with pretreated soybean oil feeding.

3. Results and discussion
The pH values of Run A and B are around optimum value,
6.3-7.4 for whole period of fermentation.

2. Materials and methods
An yeast strain, Pseudozyma rugulosa NBRC 10877 wasused to pretreat the soybean oil. The yeast was precultivatedin 20 mL of YM broth at 25 ºC for 2 days 150 spm. Then
yeast was inoculated to 10 mL of Yeast oil broth andcultivated at 25ºC for 7 days. After 7 days cultivation, theculture was supplied to anaerobic digestion reactor.
The mixture of glucose, sodium acetate, lactic acid (GAL)and soybean oil were used as substrates for anaerobic
digestion and two experiments, Run A and Run B wereconducted. In Run A, the reactor was fed with untreated
Yeast oil broth, and in Run B, the reactor was fed withpre-treated oil broth. In both of Run, the ratio of soybean oil
against amount of carbon increased to 0%, 25% and 50%(O-0, O-25 and O-50) for each step. Those substrates were
supplied to each reactor in a stepwise manner: day 0-20 with

Fig. 1 Course of moving average methane gas production of
Run A and Run B

Fig. 1 shows the courses of methane gas volume in Run A
and Run B. During day 1 to 20 of fermentation the gas
productions of both Runs were stable at around 1.07 L.
After changing the substrate to O-25 at day 20, the gas
volume of Run B during day 21 to 95 was almost the same
volume with that before day 21. This result indicated that
pretreated oil could be completely degraded and converted to5

CH4 and CO2 since in total amount of carbon in thesubstrates of O-0 and O-25 were the same. By contrast, thegas volume of Run A decreased to around 0.80 L at day 21.
Then, the gas volume of Run A gradually increased from day
24 and reached at around 1.09 L on day 74.
After changing the substrate to O-50 at day 95, the gas
volume of Run A and Run B decreased to around 0.65 L,
After the pretreatment, O-50 was considered to containhigher amount of long chain fatty acid (LCFA) that was
produced in the degradation of soybean oil than that in O-25.
It is considered that LCFA produced in the degradation ofsoybean oil in O-50 caused decrease of the methane gas
production of Run B.
Around day 155, the gas volume of Run A and Run B
gradually increased and reached to 1.09 L on day 175 that is
almost the same volume observed before day 21. Also afterday 175 we could observe increasing methane gas volume.

Run B after day 96, The disappearance of band 7 wasFig. 3 DGGE pattern for bacteria of Run A and Run B
observed. And the increasing of band 4, 5, 6 and 10 wereobserved in only Run A. Since Run A was fed with untreatedsoybean oil and Run B was fed with pretreated soybean oil, it
is implied that these microorganisms degrade the soybeanoil.

4. Conclusions
The methane production of Run B was recovered after day
120 and Synergistales and Propionibacteriaceae wascandidate of bacteria which can support increasing methane
production.
There is possibility that bands 4, 5, 6, 10 in DGGE pattern
for bacteria of Run A are significantly important
microorganisms.

Fig. 2 Changes of key bacteria in Run A and Run B
The distribution of bacteria and archaea population in Run
A and Run B was analyzed by using next generation
sequencing (NGS). Fig. 2 shows the changes of the key
bacteria which seem striking difference between Run A andRun B. Among the all microorganisms, these bacteria whichclose to Propionibacteriaceae and Synergistales were more
dominant in Run B than in Run A after day 100. And it is
known that Synergistales is obtained from oil-degrading
enrichment [3]. In Fig. 2(A), the population of the
microorganisms in Run A was twice higher than in Run B,
on the other hand in Fig. 2(B), the population in Run A wasalso twice higher than in Run B. The results indicated that in
Run B these two microorganisms played important roles in
LCFA rich environment and supported methane productionin the period when the methane production increase after day
120.
Fig. 3 shows the DGGE pattern for bacteria of Run A and

Reference[1] N. Kataoka et al. : Studies on a Methane Fermentation
Process for Treating Oil and Fat Containing
Food-processing Wastewater, Ebara engineering
review, 212, 3-9 (2006).
[2] I. Angelidaki et al. : Effects of free long-chain fatty
acids on thermophilic anaerobic digestion, Appl
Microbial Biotechnol, 37, 808-812 (1992).
[3] Lisa M. Gieg, Irene A. Davidova, Kathleen E. Duncan
and Joseph M. Suflita : Methanogenesis, sulfate
reduction and crude oil biodegradation in hot Alaskan
oilfieldse, Environmental Microbiology, 11, 3074-3086(2010)Run B. In both Runs, it was observed that the increase ofband 13, which was close to Actinomycetaceae. This
microorganism was considered to be able to degrade LCFA,
because during gradual increase of methane gas in day
120-220 the density of the band 13 also increased and it wasconsidered to be rich-LCFA environment in both Runs. In

6Prediction of future population distribution of Jakarta on the basis of global warming scenario
ID : 13B08154
1.

Name : Takakuwa Shun

Supervisor : Prof. Kanda and Alvin C. G. Varquez

Introduction

Data

such

to Indonesia’s defines the decadal changes of total
as

urban

parametersandpopulation in Jakarta from the present to theanthropogenic heat emissions is necessary in order

future. In this study, two types of SSP were used,

to study future urban climate using meteorological

SSP1 and SSP33). SSP 1 is based on the future

models. It is already known from previous researchassumption that education, governance andthat these data can be derived from the hightechnology are of highest level and the rate ofresolution population distribution of urban.1) In

population increase is restricted. On the other

other words, if the future population distribution

hand, SSP3 is business as usual condition,of urban is known, future urban climate can besuggesting higher rate of population increase andstudied. The objective of this research is to predict

uncontrolled growth. Based on this assumption,

future population distribution in Jakarta based on

SSP1 (SSP3) is paired with Compact (Historical)

two types of SSP scenarios.

Growth.

Then

final

population

distribution

scenarios were referred to "Historical Scenario"
2. Methodology

and "Compact Scenario".

Three inputs are needed to predict future

LandScan𝑇𝑀 provides past and latest (2013)

population

griddedpopulation distribution and was used as a base of

distribution of probability for urbanization derived

population distribution prediction; and to validatefrom an urban growth model. Second is the trend

the estimated population distribution.

of future total population in Jakarta based on a

Future population distribution was calculated

Shared Socioeconomic Pathways Scenario (SSP).

annually from the base year using a discretized

Third is present-day population distribution byform of the logistic function as follows.

LandScan𝑇𝑀

distribution.

First

is

. Using a logistic model which utilizes

Pop𝑡+1𝑖,𝑗 =these inputs, future population distribution can be(A𝑡𝑖,𝑗 + 1)Pop𝑡𝑖,𝑗(Eq. 1)𝑡
1 + B𝑖,𝑗
× Pop𝑡𝑖,𝑗obtained.

𝑡
𝑡+1
Pop𝑡+1𝑖,𝑗 = 10 (Pop𝑖,𝑗 = 0 & Pro𝑖,𝑗 ≥ 0.5) (Eq. 2)

SLEUTH model is a cellular automata model; where𝑡
A𝑡𝑖,𝑗 = 𝑒𝑥𝑝(r𝑖,𝑗)−1which can estimate future horizontal urban growth(Urbanization Probability Map) by using different

𝑡
B𝑖,𝑗
=

input data such as Slope, Excluded region, Urban

A𝑡𝑖,𝑗
K𝑡

(Eq. 3)(Eq. 4)model to predict two types of urban growth,a𝑡 × Pro𝑡+1𝑖,𝑗𝑡
r𝑖,𝑗 = { 𝑡b × Pro𝑡+1
𝑖,𝑗Historicali, j and t refer to the spatial and temporalextent, Transportation, and Hill shade2). I used theandCompact

Growth.

Historical(0 < Pop𝑡𝑖,𝑗 < 100)}
(100 ≤ Pop𝑡𝑖,𝑗 )(Eq. 5)Growth is the urban growth which follows thecoordinates. Pop and Pro refer to the population

historical trend. Compact Growth represents aand urbanization probability. K 𝑡 , a𝑡 and b𝑡 are

restricted urban growth by strict economic andcoefficients obtained by minimizing theurban planning policies.

difference between the estimated population

SSP and the growing ratio of Jakarta’s population

distribution and the actual values from7

LandScan𝑇𝑀 . SSP was used as an additional
constraint,|𝑆𝑆𝑃𝑡 − 𝑠𝑢𝑚(Pop𝑡𝑖,𝑗 )| ≤ 1000 (Eq. 6)
to optimize K 𝑡 , a𝑡 and b𝑡 .
3. ResultFig.1 shows the result of SLEUTH. From Fig.1,

Fig.1 Urbanization Probability Map by SLEUTH

it can be seen that urbanized area is so different

model. Compact Growth (left) ; Historical Growth

between Historical and Compact Growth.

(right)Fig.2, 3, and 4 reveal the future population ofurban area in 2014 :Jakarta. From Fig.2, it can be seen that trends oftotal population are almost the same in Compact
Scenario and SSP1, Historical Scenario and SSP3
respectively. From Fig.3, it can be seen that
future population based on SSP is well distributedby this estimation procedure. In Fig.4, red region
shows population increasing significantly in the
Historical Scenario than in the Compact Scenario.
On the other hand, blue region shows an opposite
condition. From this figure, it can be seen thatFig.2 Trends in the total population of Jakarta.

population is expected to increase at the central
area in the Compact Scenario than in the
Historical Scenario.
4. Conclusion
Future population distribution in Jakarta basedon the SSP scenarios is introduced. This method
can be expanded to other cities, and can potentially
useful for urban planners and weather modelers.

Fig.3 Population distribution of Jakarta in 2050 in"Historical Scenario"

Reference
1)

Manabu Kanda, et al ; A new aerodynamic
parametrization for real urban surfaces

Boundary-Layer Meteorol (2013), vol148 : 357-377
2)

PROJECT GIGALOPOLIS
http://www.ncgia.ucsb.edu/projects/gig/index.html

3)

藤森 真一郎（2011 年 11 月 22 日）; IPCC 第 5 次評価報告書に向けた将来シナリオの検討 日本からの貢献とその意義

Fig.4 Population distribution difference between

http://2050.nies.go.jp/sympo/111122/file/1_fujimori.pdf

Historical and Compact Scenario in 2050

8

Exploring the Optimal Number of Days in East China Sea Cruise Tourism
from/to Shanghai
Student Number: 13_09484 Name: Zhonghui Zheng Supervisor: Shinya HANAOKA, Tomoya KAWASAKI

1.

Introduction

2)
Existing & Fictitious Lines (Orthogonal Design)
Table 2 shows the Existing (fill color) and Fictitious(non color) cruise lines made by orthogonal design.
Price setting refers to the actual price ofCasual/Standard cruise ship ticket; because we only
can cruise to Jeju for a travel within 3 days realistically,
the Day 3 just has 1 line.

In 2015, nearly 1.91M Chinese passengers took a cruise
vacation, growing 66 percent annually since 2012[2].
Shanghai as the main port of the cruise tourism products,
it is developing rapidly in recent years. However,Shanghai in the process of further development of cruise
tourism also met with some bottlenecks, for instance,
how to attract more and more new users and repeaters tojoin cruise tourisms.
According to the survey of International Cruise
Tourism in Shanghai (Costa Cruise 2009), 58% of
people selected the number of cruise days is the mostimportant factor they emphasize when choosing a cruise
tour. Because for Chinese people, the most concentrated
holiday are three Golden Weeks and the longest holiday
is also less then 10 days. For most of the Chinese office
workers, they still have not enough time to participate ina longer voyage cruise travel. Therefore, this study
mainly concentrated on cruise days and other two factors,
destinations and price that the most tightly connectedwith cruise days.
Based on the background, objectives of this study are 1)
Using SP Survey to analyze the main factors influence
tourists’ decision making, and to clarify when theychange how people’s satisfaction change. Also consider
the interaction of other factors with days.2) By using theestimated parameter result to find the utility function andfind out its saturation point. Also, we analyze the changeof maximum utility by the optimum number of days andclarify the characteristics by individual attribute.

2.

Table 2 Existing & Fictitious Cruise Lines

2.2 Mixed Ordered Logit ModelIn this study, StataSE 1.4 is used to analysis Ordered
Logistic Regression for panel data. Because it israndom-effects OLM, methods and formulas are shownas the following:
for i=1,…,n panels, where t=1,…, !! , !! areindependent, identically distributed ! 0, !!! , also called
panel-level random effects and ! is a set of cutpoints,
K is the number of possible outcomes. So derive theprobability of observing outcome k for response !!" as:Methodology!!"# = Pr !!" = ! !, !!" , !!
11
= 1 + !"#(−! + ! ! + ! ) − 1 + !"#(−! + ! ! + ! )2.1 Stated Preference (SP) Survey Design

1)
Overview of Web-based Questionnaire
Table 1 shows the overview of web-based questionnaire.
According to Asia Cruise Trends (CLIA, 2016), Japanand South Korea mixed cruise lines is the most popular
to Shanghai cruise tourists. The ports of call are top 6 ofdestinations most popular to Chinese cruise tourists. The
reason why this study did not consider other factors may
influence people’s decision making is that due tolimitation of vacation time, Chinese tourists will givepriority to consider how long and where they want tocruise to, after that, they consider what kind of service
they want to enjoy and how much is it. Therefore, cruisedays is most concerned at first when choosing cruise
tour.

!

!"

!

!!!

!"

!

Where !! is taken as −∞, !! is taken as +∞.

2.3 Method of estimating the optimal cruise
days

Step 1: Analysis ordered logistic regression for panel
data by using StataSE 1.4, confirm main independent
variables that can influence significantly and using
appropriate coefficients to define the utility function.
Step 2: Differentiate U( !! ) with respect to Day(!" !"#$), plug the known values and check out theextreme point of the function(i.e, when (!" !"#$ )=0,
calculate value of Day).
Step 3: Plot the obtained optimal Days and the days ofexisting & fictitious Lines(line 1~20). Except lines
mentioned in 2.2, other existing lines that provide by
Cruise Company are added into analysis.

Table 1 Overview of Web-based Questionnaire

3.

Result and Discussion

3.1 Overview of Survey Data
Gender: The number of total answerers is 648, female is52.78% (342); male is 47.22% (306). Age: Proportion ofless than 40 years and over 40 years is almost 1:1.
Occupation: 50% are company clerks. Monthly Income:Over 50% are in the range of 5000~15000 CNY.
Experience of cruise tourism: 527 answerers want to joincruise tourism if they have chance. Preferences of Cruise9Days: from figure 1, it can be said that 5 days tour is themost popular without regarding for the influence of priceand ports, the answerers just were asked “ How manydays do you expect to take a cruise? ”

Table 3 Summary of parameter estimation results

3.2 Cross Analysis
In this part, cross analysis include gender (male, female),age groups (18~29, 30~39, 40~49, 50~) and monthly
income (0~8000, 8001~15000, 15001~25000, 25001~,
unit CNY), experience of cruise tourism (yes & no).
Figure 2 and 3: the shapes of curves are almost the same;the peak is 5. Monthly Income (figure 3): the preferenceof cruise days for each group is 5; but for short trip (2~3),
there are some differences that the proportion of the
low-income people is higher than others, maybe because
short trips are not so expensive that they can be able toafford. Age groups (figure 4): age groups shows somedifferences that 18~29 is prefer to 5 days; 30~39 andFor male, it seems that except Days, Price, Day square,
Price*Day, others not affect significantly.
Model 4 and 5 (New user & Repeater): young and newusers more like to cruise, and high-income repeaters
probably prefer join again. Using the result of Model 1,
confirm the utility function and plot:

Figure 1 Preference of Cruise Days

! !2, !"#, !",40~49 are all most expected 5 days; relatively, the most
expected cruise days for old people is longer than young
people. It can be said that because old people (include
retiree) have time and considerable economic condition,
they would like to travel long days for relax [3].

Figure 2 Gender!
!!! !! ! ,!
!!! !"#$!

, !"#!$#"%&

!"
!"#$

=0

Figure 5 Comparison of D and D* , U and U*

From figure 5, When D=D*, it means the days (D) of
choice tourism become the optimal days(U*) and theutility of this choice tourism will be the U* maximum
utility. In this case, D* of choice tourism IV is nearly
5.0677, comparing to other D* of choice tourism, it is
the closest approach. From the figure 4.3.3, it indicatedthat it is better to extend for less than 5 days ofintersection and shorten after 5 days. It is realisticallypossible by adjusting the sailing date, calling area
sightseeing, shopping time etc. If pay attention to themagnitude relation between U and U * for the same
choice tourism, the difference between U and U * ofeach tour increases as the number of days increases andthe rate of increase in utility also increases.

Figure 3 Experience of Cruise Tour4. Conclusion

Figure 3 Age Groups

Age, experience, number of days, price, port of calling
are the main factors for passenger decision making, but
the most important are days, prices, port of call.
Generalization cannot be done because the optimal
number of days is changed according to other factors, but
substituting the estimated optimum days into the utility
function increases the utility.

Figure 4 Monthly Incomes

3.3 Model Estimations
Model 1 (Total sample): according to z-value and signsof coefficient (+&-), it indicated that young people liketo cruise than old people and the probability join thecruise tour of repeater is higher than new user; number ofDays is longer better, but from sign of Day square isnegative, we can obtain maximum value, and people
refer to cheap tours. From sign of Fukuoka is negative, itmeans people not so like to go to Fukuoka for a travel.
Model 2 and 3 (Male & Female): Age influences thefemale satisfaction negatively, but experience is positive;

References[1] Kam Huang James F. Petrick, “Why do you cruise?”, Tourism
Management, No 32, 286-393, pp.4-6 (2011)[2] Cruise Lines International Association (CLIA), “Asia Cruise
Trends”, 2016 Edition, pp.6-13, pp.29-30[3] Kawasaki, T. Todoroki, T. Komatsu, G., “Preferences of the
Potential Cruise Ship Users in Japan, International Association of
Maritime Economics (IAME) 2016 Conference, Hamburg (2016)10

Raspberry Pi による低コストな屋内位置推定システムの構築
学籍番号: 13B04920

氏名: 姜

竣銘

指導教官: 高田潤一、 Azril Haniz

1 はじめに近年、スマートフォンとコミュニケーションネットワークの普及に伴い位置情報サービス（Location based service）の需要が高まってきている。位置情報サービスに用いられている技術は屋外位置推定技術と屋内位置推定技術に分けられている。屋外位置推定技術では、GPS による位置取得が主流である。しかし，GPS 衛星の電波が届かな
い屋内では、取得した位置情報には誤差がある。屋内位
置推定では、研究者は様々な技術を検討しているが、まだ市場に決定打が出ていない状況である。
様々な技術の中に、最近では省電力無線通信である
BLE(Bluetooth Low Energy) が注目されている。BLE は
消費電力が少ないことから長時間稼動に適しており、近年スマートフォンをはじめ BLE 機能を備えているデバ
イスが増えており、屋内位置推定システムとしての利用は期待されている。さらに、低価のシングルボードコン
ピュータである Raspberry Pi は BLE 信号を送信したり受
信したりすることができて、容易に屋内位置推定システ
ムを構築できる。
本研究では Raspberry Pi で BLE 受信信号強度（Received Signal Strength:RSS）に基づいて位置指紋法（Location Fingerprinting）を使いデバイスフリー屋内位置推定システムを提案する。そして、提案したシステムの初期的検証として実験を行い、その結果と考察を報告する。

2 原理
2.1 デバイスフリー位置推定システム
Aly の調査 [1] により、屋内位置推定システムは主に二つに分かれて：デバイス依存システム（Device-based
System）とデバイスフリーシステム。従来のデバイス依存システムはユーザーが無線の端末を持つ必要がある。
しかし、デバイスフリーシステムでユーザーは無線の端末を携帯する必要はなく、ユーザへの負担は軽減できるというメリットがある。
Figure 1 に示したように、デバイスフリーシステムは複数の送信機と受信機により構成される。屋内環境の様々の場所に、送信機と受信機を適切に設置し、複数の送受信機のペアを作る。人が屋内環境に現れる場合、人体による電波の遮蔽や反射により、屋内の電波伝搬環境が大きく変化すると考えられ、送受信機間の通信路も変化する。人が立つ場所によって影響を受ける送受信機のペアが異なり、場所依存性があるため、その特徴を位置推定に利用できる。デバイスフリーシステムの事例として高齢者の遠隔介護支援が挙げられる [2]。

Figure 1: Raspberry Pi を利用したデバイスフリーシステムのイ
メージ

Figure 2: 位置指紋法の全体図を推定する。人体の指紋と同じように、ある場所の指紋がデータベースにある指紋が一致すれば、場所を特定することができる。本研究では信号の特徴量として受信信号強度を利用する。
位置指紋位置検出技術の利点として、マルチパスが多い
屋内環境は適しており、データベース作成時と同じ環境下では高い位置推定精度が期待できることである。しかし、精度を維持するためには環境変化に合わせてデータベースを再作成する必要がある [5]。
Figure2 が示しているのは位置指紋法の全体図である。
RSSIi,j とは i 番目の送受信機ペアの j 番目の計測ポイ
ントにおける RSS であり、RSSIi′ は online phase で測定した i 番目の送受信機ペアの RSS である。n は計測ポイントの個数で,m は送受信機ペアの組合せの数である。
パターンマッチングアルゴリズムとして、本研究ではユークリッド距離を用いた最近傍法を採用した。データ
ベースに各計測ポイントの指紋と Online Phase のユーザの指紋とのユークリッド距離は式 1 で表す。それで式 2によって、ユークリッド距離が最小の計測ポイントを絞
り出し、この点は推測した場所である。

d2j =

m
∑

(RSSIi,j − RSSI target i )2

(1)

ĵ = arg min dj

(2)

i=1

j

2.2 位置指紋法に基づく位置推定技術

3

位置指紋法に基づく位置検出技術は、受信信号の伝搬特性を利用する [3]。Figure1 が示してように、２つの段階があり、一つは「Offline Phase」で、もう一つは「Online
Phase」である。Offline Phase では事前に設定した場所で一定時間に取得した信号の特徴量をデーターベースに格納する。Online Phase では未知の場所で取得した信号の特徴量を利用して、パターンマッチング手法により位置システムの構築

3.1 Raspberry Pi
Figure3 は本研究使っている Raspberry Pi である。Raspberry Pi はシングルポードコンピュータで、LINUX などの OS をインストールすることができる。そして、自分で書いたプログラミングによって、自由に Bluetooth、Wi-Fiなどのハードウェアを操ることができる。BLE USB ド

11

4.2 結果と考察提案した屋内位置推定システムで実験し、結果はユー
ザの実際の位置と推定位置の間の距離（誤差距離：error
distance）で評価する。テストポイントは計測ポイントと同じではないから、理想的な推測位置はテストポイントと空間的に距離が一番近い計測ポイントである。つまり理想的な場合でも、誤差距離はゼロではないわけである。
Fig5 は結果を示した。赤線は理想的な場合の誤差距離
Error Distance(cm)350

Figure 3: Raspberry Pi の写真

ideal result
test result

300
250
200
150
100
50
0
a

b

c

d

e

f

g

h

i

j

Test points

ングルを装着することによって、BLE 信号を送受信することが簡単にコントロールすることができる。本システ
ムでは、コマンドで複数の Raspberry Pi を受信機と送信機の間切り替えて、システムの送受信機関の通信路を変化させる。

Figure 5: 屋内位置推定実験の結果

で、青線は実際の場合の誤差距離である。a,b,d,e,i 点は誤
差距離は１メートル以内であったが、他のテストポイン
トは誤差距離が大きかった。その原因は大きく２つ考えられる。
まず、今回の実験では一つのポイントで２０個の RSSI
データが指紋としてデータベースに格納され、同じく式1 によって計算された。人が立つ場所によって必ずしも全ての送受信機間の通信路に影響を与えているわけではない。例えば、A 点の近くに人が立っても Raspberry Pi♯4と ♯5 の間の通信路への影響は少ない。すべての送受信機
ペアではなく、有効な送受信機ペアのみを適切に選択することで、より高い推定精度が得られると考えられる。
そして、屋内環境における障害物によるシャドウィン
グとマルチパスによるフェージングにより、場所の変動が小さくても、位置指紋の変動は大きい。その問題を解決するために、計測ポイントが多く増やして、データー
ベースにより多くの位置指紋を保存する。それでより高い推定精度が得る事ができると考えられる。

3.2 ネットワークの説明
屋内に各場所で設置した Raspberry Pi の送受信をコントロールしたり、Raspberry Pi が受信したデータをパソコ
ン・サーバーに送信したりするためにネットワークを構築すべきである。本システムは Wi-Fi ルーターによって、ローカルエリアネットワークを構築することで実現した。
サーバーパソコンを使って SSH と VNC(Virtual Network
Computing) プロトコルで Raspberry Pi を遠隔操作する。
UDP 送信プログラムを書いて Raspberry Pi とサーバー間のデータの通信を行う。

4 実験
4.1 実験説明

5

おわりに

今回の研究では、Raspberry Pi で BLE 受信信号強度（RSS）に基づいて位置指紋法（Location Fingerpriting）を使いデバイスフリー屋内位置推定システムを提案した。
検証実験によって、その結果を分析し、その可能性を探った。
今後の課題として、次のようなことに関する研究を進めていく必要がある。提案したシステムにふさわしいパ
ターンマッチングアルゴリズムを研究する。またスマー
トフォンで表示できるリアルタイムな屋内位置推定シス
テムを構築する。

Figure 4: テストベッドの設置

提案した屋内位置推定システムを初期検証するため東工大南６号館２１４室で実験を行った。Figure4 は実験のテストベッドである。５個の Raspberry Pi は一定の順序によって送受信を切り替えて、様々な送受信機の組み合わせを作り、RSSI を測定する。送信側は送信強度が 0dbm
で、送信間隔が 100ms である。実験実施者は各計測ポイ
ントに立ち、受信機は各送受信パターンで 40 秒間の RSSI
データの平均値を記録する。 Offline phase が完了したら、
Figure 2 に示す RSSI のようなデータベースを作る。そのとき m ＝ 20 で、n=16 である。
Online Phase では、１０個のテストポイントを取り（緑のˆ丸）、各テストポイントで受信して Figure 2 に示す RSSIのような行列を作る。そして、式 1 と式 2 を使って、推測位置を決める。

12

References[1] H.Aly and M.Youssef,“An analysis of device-free and devicebased wifi-localization systems”, Ambient Computing and Intelligence(IJACI), vol.6, no.3, January 2014.
[2] 杉野恭兵, 大囿忠親, 新谷虎松: “複数の Bluetooth ビーコンに基づくデバイスフリーな屋内測位におけるキャリブレーションについて”，信学技報， 115(381)， pp1-6, 2015.
[3] 辻広之,“アレーアンテナを用いた屋内外の無線局位置推定の実験的検証” 信学論（B）， vol.J90-B, no.9, pp-784-796, Sep.2007.
[4] 大 槻 知 明,
“位 置 推 定 技 術”,“http://www.ohtsuki.ics.keio.ac.jp/theme/localization.pdf”.

2009:[5] A.Dempster,B.Li,and I.Quader, “Errors in determinstic wireless fingerprinting systems for localization”, 3rd International sysmposium
on Wireless Pervasive Computing (ISWPC), pp.111-115, May 2008.

A system of extracting common formin multiple natural scene images and reading form-data
Student Number：13 05405 Name：Yuhang HUANG Supervisor：Yukihiko YAMASHITA
age qj in test image set Q = {q1 , q2 , . . . , qm |qj , j =1, 2, . . . , m} and extract the result of text region set
With the development of computer, most of tasks of
R = {r1 , r2 , . . . , rm |rj , j = 1, 2, . . . , m} using mask imdata processing are done in computer, although there
age m.
are still many paper forms, such as business reports,business cards, and invoices, which are still being used.
To process both paper-based data and digital data at

1

Introduction

the same time, studies on form document recognition
and understanding based on document images havebeen done, and a method for form-type identificationand form-data recognition was proposed [1].
Nowadays, with the increase of portable camera devices such as camera in smart phone or car, text understanding in natural scene images has become a key taskthat can change our everyday lives by novel applications such as automated vehicle system. With portable
camera and computer processing unit, now people canFigure 1: Flow chart of proposed system
A. Extract template image target tFirstly, we change all the images ik in I to grayprocess data without desktop computer or scanner. A
need of processing document easily from images in nat-scale and execute Scale-Invariant Feature Transformural scene background has appeared in recent years.
(SIFT) [2] to each image ik to get their feature keypoint
To solve the situation where the original form image
descriptors D = {d1 , d2 , . . . , dn |dk , k = 1, 2, . . . , m}.
is lost or form media can not be scanned like car numA matching method of Fast Library for Approximate
ber plate, in this study I propose a system of extractNearest Neighbors (FLANN) is done for feature matching unknown common form in multiple natural scene
ing [2]. By matching i1 to i2 , i2 to i3 , . . . ,in−1 to in ,images by analyzing the diﬀerences of the contents ofand finally in to i1 , we make a matching cycle of theimages to find out the text region and reading forminput image set I, which can provide a map set {f |fk :data.
dk → dk+1 , fn : dn → d1 , k = 1, 2, . . . , n−1}. Secondly,
we pick up the feature points p ∈ Ptargetl which meet2P

= {p|p ∈ d , f◦f◦ . . . ◦ f ◦ f . . . ◦ f (p) =

l l−1
l−2
1
n
l
Form extracting and reading targetlp}, which can find a set of stable features among imsystemages in I. Finally, we group points p ∈ Ptargetl withrectangle as target image region, and find out the best
Ptargetl of which rectangle is the most nearly parallel

The proposed system consists of three parts. A. Exwith horizon, in order to find a good template for text
tract same-form template image target t from input
extracting. And then we clip a template image t fromimage data set I = {i1 , i2 , . . . , in |ik , k = 1, 2, . . . , n}.
the original image il by using the rectangle region.
B. Analyze the diﬀerence between template t and eachB. Mark diﬀerent text regions
image ik and mark diﬀerent text region in mask imAfter process A, we can get the template image t
age m. After processes A and B, template image t
and its original image il . We apply Maximally Staand mask image m are obtained. C. Execute temble Extremal Regions (MSER) method that performs
plate matching between template image t and each im13

well in extracting character candidates [3]. Firstly, we
execute the MSER detector to the template image t
and find the candidates of character. Using geometricproperties of text to filter out non-text regions withthresholds [4], we can get text regions with rectangle boxes. After expanding this bounding boxes andmerging the connected boxes, we finally get text regions. Secondly, we transform the template image t
and the images in image set I to binary images using
the adaptive threshold method. And then we execute Figure 2: Experimental results. A1 and A2:SIFT feaprojective transformation from each image {ik ∈ I, k = ture matching, B1 and B2: text regions after removing
1, . . . , l − 1, l + 1, . . . , n} to template image t. By cal- non-text regions based on geometric properties, B3 andculating the Zero-mean Normalized Cross Correlation B4: text-region mask image m, and C1 and C2: result(ZNCC) coeﬃcients with each block image clipped by image r
text regions after blurring them by a Gaussian function, we can find diﬀerences between template image
t and ik .We remove the text region results if not all

4

calculate qj+1 .

References

Conclusions

In this study, I proposed a system of extracting
the correlation coeﬃcients of the corresponding regioncommon form and form-data from natural scene backamong the images are lower than 0.7. Finally, we saveground text images with portable camera devices. By
all the results of text regions that remain as the mask
experiment, we confirmed that we can extract simple
image m.
form and process form data simply with camera devices
C.Read form-data from test image set Q
in a smart phone.
First, we execute SIFT both to template image t
Performance could be improved, by using other feaand to test images qj ∈ Q, and match each test image
ture extracting method to increase stable matched
qj to template t. Then we calculate the parameters
points in procedure A. Comparing not ZNCC coeﬃof homography and execute projective transformationcient but the contents of text, adding logical structurefrom each test image qj to template t. Finally, we
analysis, and using improved natural scene image text
calculate the ZNCC coeﬃcient between qj and t. If
recognition methods can also improve procedure B.
coeﬃcient is higher than 0.9, we extract the text frommask image m. If not, we turn to the first step to[1] Sako H., Seki M., Furukawa N., et al, ”Form read-3

Experimental Result

ing based on form-type identification and formdata recognition.” Proceedings of the 7th Inter-

We examined the system by setting I with four input

national Conference on Document Analysis andRecognition, Vol.3, pp.926-930, 2003.

images and Q with two test images. We implemented
the procedure A, B and C using Eclipse C++ in Linuxwith OpenCV3.1 library, which contains SIFT feature[2] Lowe,D.G.,”Distinctive

extracting tools. And we implement the algorithm of
ZNCC and MSER text extracting based on [3], [4].

Image

Featuresfrom

Scale-Invariant Keypoints.” International Journalof Computer Vision,Vol.60,No.2,pp.91-110,2004.

The results of procedure A, B and C are shown in
Figure 2.
Even though most of test data sets run successfully,[3] CHEN, Huizhong, et al, ”Robust text detection in natural images with edge-enhanced maximally stable extremal regions.” Image Processing, 2011 18th IEEE International Conference,

we found that error occurs when using ZNCC to measure natural scene images because of lighting and dis-

pp.2609-2612, 2011.

placement, which will get coeﬃcients lower than 0.5
although two images are almost similar. MSER will
miss some candidates. Grouping by margin will group[4] Neumann, L. and Jiri M., ”Real-time scene text localization and recognition.” Computer Vision and
Pattern Recognition, pp. 3538-3545, 2012.

all the form as one region.
14

A study on travel behavior and characteristic of residential zone in satellite
metropolitan cities for urban function attraction-Case study of Kashiwa city and surrounding cities
Student Number: 13B07172 Name: Yiting JIANG
Supervisor: Shinya HANAOKA, Kumiko NAKAMICHI
1 Introduction

survey. Valid response rate is about 24%. Target zone ofthis research is the small zone that includes station in
Kashiwa and surrounding cities. There are 16 small zones
in total.
The methodology is shown as figure1.

In addition to the urban problems caused by rapid urbanization in Japan, a number of new problems has arisensuch as decline of productive population and aging problems. On the other hand, local government will face financial difficulties if they try to maintain all the public facilities especially in sprawl areas. And the quality of resident’s life will also decrease. Therefore, government realized that it is essential to reconsider the urban structure.
According to this background, the Act on Special
Measures Concerning Urban Renaissance was revised,and Location Optimization Plans has been created since
2014[1]. This means that local government should draw
where is resident-attracting districts and where is urban
function area specifically around core area to attract residents and urban functions to promote compact city. There
are about 300 cities starting to set this plan as of 2016.
However, it is risky and unreliable to set Location Optimization Plans without clear current status of each coreareas [2]. To avoid any possible risks, it is essential to evaluate the utilization conditions of each stations and facilities in core areas, which could be achieved by analyzing
the travel behavior of the residents.
This paper aims to analyze the current situation of target
city from residential zone type and resident’s travel behavior from the view of urban function attraction.

.

.

.

.

Figure 1: Flow of travel behavior analysis

3 Results and Discussion

3.1 Results of residential zone typeFigure 2 is the final result of residential zone type.

2 Data and Methodology

2.1 Introduction of the target city
Kashiwa City is one of the satellite cites in the Tokyo
Metropolitan Area. Like other cities around Tokyo, population increased rapidly around stations with the improvement of access to metropolis and housing developments in
Kashiwa since 1970s. Furthermore, with a new train route
opened in 2005, population of such satellite cities as
Kashiwa will still increase in the future, although the population of most of cities in Japan is decreasing now. Under
the financial pressure, local government need to reconsider urban structure and improve convenience of life ofresidents by improving urban function.

2.2 Analysis of residential zones
In order to grasp the basic urban structure of the target
city, all residential districts in Kashiwa were classified bypopulation density, land use regulation type, distance tocity center and distance to the nearest railway station.
Based on the national residential zone type classified byNakamichi et al. (2016) [3], smaller number of zone types
means higher national average value of fuel consumption
per person per day, is used as a reference

Figure 2: Kashiwa residential zone type

2.3 Analysis of travel behaviorth

In this paper, the 5 Person Trip (PT) Survey in Tokyo
Metropolitan Area conducted in 2008 is used to analyze
resident’s travel behavior in small zone unit. 1.4 million
households are randomly chosen from 16 million households living in the Tokyo Metropolitan Area to answer thisThe results showed that most of towns are low-heightresidential district use, especially in southern Kashiwa
and the fuel consumption around Kashiwa Station islower than other stations surrounding the area. There areseveral densely populated areas far from railway stations

15

and fuel consumption showed different tendency, so
travel behavior analysis was used to find out the reason.

area and includes Shinkashiwa Station and Masuo Station.
Figure 5 is also the “Case A” situation. It shows that the
number of OD trips for going home and shopping is muchhigher than other zones such as the zone 42211. Furthermore, share of private car is much higher than 42211 zone.
Figure 6 is an example of a specific analysis of “Case A” in which trips start from 42221 zone. This
figure shows that a majority of the trips are from s
outhern area to northern area. Especially when people go shopping they usually choose nearby places orthe city center.

3.2 Results of travel behavior

500

3.3 Summary

theothersrailway400
300

Car sharing ratio(%)

Trip number

The analysis of two typical zones are shown here.
The first is small zone 42211, which is in the center areaof Kashiwa and includes west side of Kashiwa Station.
Figure 3 is the result of “Case A” that people depart fromtarget zone. Each purpose has two cases, they are innerinner (I-I) trip and inner-outer (I-O) or outer-inner (O-I)
trip. The largest number of trips is the case that people gohome from target zone to the others zones.

bus

200
100
I-O I-I

privatecar
bicyclego tohospital

on foot

0
I-O I-I
go to work

I-O I-I
AttendschoolI-O I-Igo homeI-O I-I

I-O I-I

shopping

daily
activity

Trip purpose

300
250
200
150
100
50
0

Car sharing ratio(%)

the others
railwaybus
othercommercial
facilitysupermarket

company

medical/walfa
re facility

culture facility

educational
facility

Trip number

Figure 3: Case A (Trips from zone 42211 divided by purpose)

private car
bicycleon foot

Facility type

300
200

bus

100
I-O I-I

privatecar
bicyclego tohospital

on foot

0
I-O I-I
go to work

I-O I-I
AttendschoolI-O I-Igo homeI-O I-I
shopping

I-O I-I
daily
activity

Medical/ welfare facility

Tobu Urban
Park Line
Joban Line

42211

42241
42212

42200

TX

42223
42220
0.1
0.2
Facility density(number/ha)

0.3

Syonan area

Figure 7 shows the relationship between facility density
and car share divided by railway line. It shows that areas
along Joban Line have more facilities and lower car share.
The area along Tobu Urban Park Line has lower facility
density and higher car share.

theothersrailway

400

42221
42240
42213
42231
42232

Figure 7: Facility density and private car share

Figure 4 is “Case A-1” that people visit the facility intarget zone and depart from target zone to home eventually.
Use of commercial facilities is the highest in this zone andmost people go home by public transportation or on footfrom this zone.
500

70
60
50
40
30
20
10
0
0

Figure 4: Case A-1 (Trips from zone 42211 for go home divided by type of facility that people last visited)

Trip number

70
Tobu Urban
Supermarket and
60
Park Lineother commercial
50 42240 42221
facility
Joban Line
40
42241
42200
30
42231
TX
42232
20
42211
42213 42220
1042212
Syonan area
42223
0Trip Purpose
0
0.1
0.2
0.3
Facility density(number/ha)

4 Conclusion
People who live around Kashiwa Station and Minamikashiwa Station (Joban Line) are more likely to use
public transportation since the number and frequency ofbuses is much higher than other station. Areas along Tobu
Urban Park Line still need to be equipped with more public facilities especially the area around Sakasai Sation,
most people living in this area drive private cars to othersmall zones for shopping. Takayanagi area has same situation with Sakasai Station area. But it has much fewer bicycle users.
In this research, the relationship between public facility
and travel behavior and usage of each type of facilities ineach core areas was made clear by arranging data from PT
survey with a focus on the type of facilites that people lastvisit before they go home. This methodology could also
be applied to other cities.

Trip purpose
Figure 5: Case A (Trips from zone 42221 divided by purpose)

References[1]

国土交通省―立地適正化計画制度: http://www.mlit.go.jp/en/toshi/ city_plan/compactcity_network.html[2]

肥後洋平，森英高，谷口守:｢拠点へ集約｣から｢拠点を集約｣へ－安易なコンパク
トシティ政策導入に対する批判的検討,都市計画論文集,Vol49, No3,2014

Figure 6: Trip flow from zone 42211 with 3 purposes[3]

中道久美子,呂田子,花岡伸也: 大都市圏及び地方圏都市における住宅地タイプと交通行動特性の変化,土木計画学研究・講演集, Vol.53, 2016.

The second is small zone 42221, which is in the southern

16

高速コンポスト化に寄与する新規な好熱性酢酸分解菌の特定学籍番号：13_02074 氏名: 氏家大祐 指導教官：中崎清彦
2-3 酢酸分解菌の単離
酢酸分解菌の培養には酢酸を唯一の炭素源とする液体および寒天培地 (CH3COOH 1g/L, Na2HPO4 ・12H20

１ はじめに
近年、大量に発生する廃棄物の効率的な処理が大きな関心を集めている。廃棄物の中でも家庭・飲食店等から廃棄される生ごみはコンポスト化処理により有機肥料として有効利用が可能である[1]。しかしながら、生ご
みはコンポスト化の過程で多量の有機酸が発生し、pHが低下することによって微生物の活性が阻害されコンポスト化に長い時間がかかることが知られている。
コンポスト化の過程で有機酸を分解する微生物の研究がおこなわれてきた。40℃付近の中温条件で有機酸を分解する酵母はすでに報告されている[2]。一方で、コンポスト化の高温期にあたる 60℃付近で有機酸を分解する微生物の存在はこれまでのところ知られていなかった。60℃付近で酢酸を分解できれば微生物の活性を促し、コンポスト化の時間を短縮できる。
当研究室の平井は 60℃のコンポスト化で活発な酢酸の分解がおこる事象を偶然に見いだしている（Run D-1）
[3]。本研究では、Run D-1 のサンプル中に存在すると考えられる、高温条件下で酢酸を分解する新規な微生物の特定を目的とした。

12.362g/L, (NH4)2SO4 2.0g/l, KH2PO4 2.0g/L, MgCl2・6H2O
0.34g/L, FeSO4 ・ 7H2O 2.8mg/L, MnSO4 ・ 4H20 2.23mg/L
CoCl2 ・ 6H2O 2.4mg/L, CaCl2 ・2H2O 1.7mg/, CuCl2 ・2H2O
2.8mg/L, ZnSO4 ・ 7H2O 0.287mg/L, NaMoO4 ・ 2H2O
0.242mg/L and agar 15g/L for agar plate) を用いた。Run

D-1 のコンポスト化 8 日目のサンプルを滅菌水で 100 倍希釈し、液体培地 50mL に接種して 60℃, 150rpm で 3日間集積培養した。集積培養の後、培養液 100µL を寒天培地に塗沫して 60℃で 5 日間培養した。その後、寒天培地上に現れたコロニーを純化して好熱性酢酸分解菌を単離した。単離した微生物を液体培地で純粋培養し、HPLC を用いて酢酸の分解能を確認した。
好熱性酢酸分解菌として単離した微生物の解析では357F プライマーと 907R プライマーを用いて 16S rRNAの V3, V4 領域を増幅し、塩基配列を測定した。これにより単離した微生物を同定した。

3 結果と考察

２ 実験方法2-1 コンポスト化操作
モデル的な生ごみはラビットフードと米を乾燥重量比
で 7：3 に混合して調整した。モデル生ごみにおがくずを通気性改良材として、また市販の微生物資材（オーレス
G, (株)松本微生物研究所）を種菌として乾燥重量比で10：9：1 に混合しコンポスト混合原料とした。コンポスト混
合原料を 30L のコンポスト装置中に湿重量で 3 kg 投入
し、底部より通気量を増減させて温度を制御しながらコンポスト化をおこなった。サンプル 15g を経時的に取り出し、コンポスト化過程で変化する温度、CO2 発生速度、pH、含水率、有機酸濃度、微生物濃度を測定した（RunD-1）[3]。
2-2 酢酸分解菌の推定
Run D-1 のコンポスト化過程で経時的に取り出したサ
ンプルに対し ては 2 種類のイン デックスプライ マー(Nextera XT Index 1 (N7xx), Nexteea XT Index 2 (S5xx))を用いて 16S rRNA の V4 領域を増幅して、NGS（NextGeneration Sequence）を用いた解析をおこなうことによりサンプル中に存在する微生物の種類と相対的な存在
度の経時変化を求めた。これをもとに好熱性酢酸分解菌を推定した。

17

Run D-1 ではコンポスト化 6 日目から 9 日目にかけて60℃の高温条件下で酢酸が分解され、pH が 5.2 から
8.6 まで上昇した[3]。
図 1 に NGS を用いた Run D-1 中の菌叢解析の結果を示す。NGS によって 80 種類を超える微生物群の存在が確認され、各微生物群の相対的な存在度が明らかになった。先に述べたように Run D-1 ではコンポスト化 6日目から 9 日目にかけて酢酸が分解されているので、好熱性酢酸分解菌の相対的な存在度はこの時期に高くなっていることが推測される。コンポスト化 6,8 日目の
微生 物 叢では Ureibacillus (#18), Geobacillus (#60),
Symbiobacterium (#57), Bacillus (#4）, Bacillales (#2）
が主な微生物であった。
Geobacillus（#60）の相対的な存在度に注目して Run
D-1 中の酢酸濃度と比較した結果を図 2 に示す。コン
ポスト装置中の温度が 60℃に達した 4 日目以降、Geobacillus（#60）の相対的な存在度は酢酸濃度の増減と同じ傾向の変動をしていた。このような傾向を持つ
微 生 物 は Geobacillus （ #60 ） の み で あ っ た こ と か ら 、Geobacillus（#60）が酢酸を分解することで増殖している、
好熱性酢酸分解菌であることが推定された。
Run D-1 コンポスト化 8 日目のサンプルを接種して得られた液体培地を塗沫した寒天培地の写真を図 3 に示す。この寒天培地から 8 種類の異なるコロニー形状を示

す微生物（uj1～uj8）を単離した。これらの微生物は高温条件下で酢酸を唯一の炭素源とする寒天培地上に増殖したので、好熱性酢酸分解菌であると考えられた。
これらの微生物を液体培地で純粋培養したときの、酢酸濃度の変化のうち uj1 と uj8 を図 4 に示す。uj1 とuj8 は 60℃で酢酸を分解するために、これらは好熱性酢
酸分解菌であることが確かめられた。なお、塩基配列に基づいて uj1～uj8 を同定したところ、uj1 から uj7 はGeobacillus spp. の 近 縁 で あ り 、 uj8 は Aeribacillus
pallidus と相同性が高いことがわかった。
引き続いて、これらの微生物と Geobacillus（#60）の塩基 配 列 を 比 較 し た と こ ろ 、 uj1, uj3, uj4, uj5, uj6 がGeobacillus（#60）に含まれることを確かめた。以上の結果、高温条件下での酢酸分解能を持つ uj1, uj3, uj4,
uj5, uj6 が Run D-1 のコンポスト化においても高温で酢酸を分解するという重要な役割を担っているものと考えられた。

Concentration ofacetic acid (g/L)

図 3 寒天培地上のコロニー

1
uj1

0.8

uj8

0.6
0.4
0.2
0

0

1

2
Time (d)34

図 4 単離した微生物の培養にともなう酢酸濃度の変化

4 結論
60℃のコンポスト化で酢酸が活発に分解されているコ
ンポスト中の微生物叢を NGS を用いて解析することにより、高温条件下で酢酸分解に寄与する微生物として
Geobacillus 属細菌を推定した。また、そのコンポストサ
ンプルから Geobacillus 属細菌を単離し、60℃で酢酸を分解できる新規な微生物の存在を確かめた。

Relative abundance ofGeobacillus (#60) (%)

25

Concentration ofacetic acid (mg/g-ds)

図 1 Run D-1 サンプル中の微生物叢変化

20

5 参考文献(a)20[1] Al-jabi, L. F., Halalsheh, M. M., & Badarneh, D. M.
(2008) Conservation of ammonia during food waste
composting. Environ. Technol. 29, 1067-1073.

15
10
5
0

1

2

3

4 5 6 7 8Composting time (d)9[2] Nakasaki, K., Araya, S., & Mimoto, H. (2013)
Inoculation of Pichia kudriavzevii RB1 degrades theorganic acids present in raw compost material andaccelerates composting. Biores. Technol. 144, 521–528.

10

(b)

15

[3] 平井秀平（2015） 酵母 RB１接種と温度制御による高速コンポスト化 東京工業大学 修士論文.

10
5
0

1

2

3

4 5 6 7 8Composting time (d)9 10

図 2 Run D-1 における (a) Geobacillus（#60）の相対的な存在度および (b) 酢酸濃度18Clarification of Paratransit industry and driver’s life satisfaction analysis considering social
capital in Sri Lankan cities
Student number:13-06110

Number: Yuri Saito

Supervisor: Shinya Hanaoka, Tomoya Kawasaki

1. Introduction
In many developing countries where public transport ispoor, paratransit, which is middle transport mode between
public transport and private transport, have important rolefor people’s life. However, many of them are informal andnot controlled by government and research aboutparatransit industry are not conducted much.
Sri Lanka is one of the countries where public transport
is poor and many paratransit called “3-whleer” (3W) exist.
Although 3W is not only necessary transport mode forpeople but also cause of several problems, research about
3W industry are not conducted much. Therefore, Sri
Lanka is selected as a target country to clarify paratransit
industry in developing country.
First objective of this research is to clarify the 3W
industry in Sri Lanka. From first objective research, it isrevealed that 3W driver’s life is influenced by government
policy and driver’s group. Generally, “social capital” isdefined as features of social organization, such as trust,norms, and networks. In this case, a relationship withgovernment and driver’s group is social capital for 3W
drivers. Therefore, based on first objective results, second
objective is to conduct driver’s life satisfaction analysis
considering social capital and compare the results among
cities. The results help government to keep good
relationship with 3W drivers when they make or introduce
their policy.

Provincial Passenger Authority is provincial level
stakeholder. Western Provincial Passenger Authority are
introducing policy to control 3W in western province.
Municipal Council or Local council make 3W parking
space in a proper area. There are largest 3W authority,called “All Island 3W Drivers and Owner Association”
and provincial 3W trade unions in some area. All Island
3W Drivers and Owner Association is consist of eachprovince’s 3W director and they are able to talk with
political people and present their opinion about nation andprovincial policies. On the other hands in rural area, Police
have responsibility of 3W. They have role to build 3W
parking space, register 3W vehicle and conduct training of3W drivers.

3.2 About 3W drivers
3W drivers form local 3W driver group consisting 20-30
drivers called “Society”. A society provides several
welfare services to drivers and are important role for 3W
drivers. There are two types of 3W drivers, one belongs tosociety (society driver) and the other do not belong tosociety (free driver). Generally, society limit the numberof members by themselves so that free driver is difficult
to belong to society even though they want to belong to it.
Society has their own parking space given by Municipal
Council and wait passengers in a line. Each society havetheir own rules and welfare services. Society drivers are
not allowed to catch passengers except their society’s
parking space. On the other hands, although free drivers
do not have parking space, they can catch passengers
everywhere except society’s parking spaces. The role ofsociety is different among areas. The rate of societies
which have relationship with nearby residents is 37% and
33% in Colombo and Kandy (urban area), respectively.
However, Moratuwa is 53% and Padukka is 60%. In
addition, the rate of societies which have relationship withother societies is only 13%, 14% in Colombo, Kandy andMoratuwa are 20%, respectively. However, Padukka is
77%. From the results, it is revealed that the farther fromcity area (that mean the lower power of provincial
government), the stronger of connection between thesocieties and the area.

2. Methodology
Two field surveys were conducted in this study. First one
is interview survey with stakeholders of 3W industry to
clarify the actual condition of 3W industry in October
2016. The second one is questionnaire survey in target
four cities (Colombo (city area), Moratuwa (urban area),
Padukka (rural area) in western province and Kandy(urban area) in central province) in December 2016. The
questionnaire sheets including personal information,
general social capital questions and 3W driver’s social
capital questions were made. Based on this questionnaire,ordered logit model is developed to clarify the factors
which affect 3W driver’s life satisfaction for each city.

3. The results of Interview survey
3.1 Stakeholders in 3W industry

4. The results of questionnaire survey

National institution, provincial institution, Municipal
Council/Local Council, and 3W association relate to 3W
industry in urban area. Ministry of Transport (MOT),
National Transport Authority (NTC), and Department ofMotor Traffic (DMT) are national level stakeholders.
Under the instruction of MOT, NTC are considering to
replace 3W of electric environmental friendly vehicle in
the future to solve air pollution problems caused by 3W.
DMT are planning to make new 3W driver license
considering age limitation and start stricter 3W driver
training system from 2017 in order to reduce accident rate
related to 3W.

459 samples in Colombo, 457 samples in Moratuwa, 510
samples in Padukka, 500 samples in Kandy, total about
1900 samples were gathered. However, Padukka
questionnaire sheets have many no answer parts. Hencethe models of 3 cities except Padukka are developed. Afterthe descriptive analysis, ordered logit model wasdeveloped. Dependent variable is satisfaction of life (1 isextremely unsatisfied, 10 is extremely satisfied), and highnumber of each independent variable mean highsatisfaction, high trust or strongly agree the question.

4.1 Questionnaire sheet and sample numbers

4.2 City comparison of the analysis results
Table 1 shows significant variables in Moratuwa,

19

Colombo and Kandy. Although worthwhile andsatisfaction of 3W is significant in Moratuwa andColombo, importance of family and friends, which are
general social capital variables, are significant in Kandy.
Therefore, it is revealed that compared to Colombo
Moratuwa, 3W driver job do not have big impact on
driver’s life satisfaction in Kandy. Justification of bribe issignificant in only Moratuwa and Colombo therefore it
might be western provincial specific characteristics.
However, clear characteristics of western province have
not obtained yet, therefore more deeper consideration isneeded.
In Moratuwa, interesting job as a reason to still continue
3W driver job and satisfaction of 3W vehicle is significant.
Therefore, life satisfaction of Moratuwa drivers who canenjoy their job comfortably is high. In Colombo, althoughdriver can earn as he wants and interesting job as a reason
to start 3W driver job are significant, trust of trade unionis significant and coefficient is minus. Generally, 3W
driver trade union take actions since they are not satisfied
with government or provincial government. Therefore,high trust of trade union means low satisfaction withgovernment. In Kandy, the variables which is significant
in 2 cities are not significant. Not only general social
capital parameters but also importance to have friendly
relationship with other 3W drivers and have reliable 3W
driver friends, which are 3W driver’s social capital
parameters, are also significant. Therefore, Kandy driver’s
life satisfaction is influenced by social capital more thanMoratuwa and Colombo.
Table 1 Each city’s significant variables
Independent variables
Moratuwa
Colombo
Average Satisfaction of life
(1Unsatisfied⇔Satisfyied10)

7.00

7.33

Table 2 shows significant variables of society driver andfree driver in 3 cities. In Moratuwa and Colombo,
worthwhile and satisfaction of 3W job is significant in bothdrivers. Monetary variables, which are satisfaction ofsalary and fuel cost, is significant in both society drivers
in Colombo and Kandy. Passenger variables, which areimportance to communicate with passengers and like tocommunicate with passenger, are significant in bothMoratuwa and Kandy. In Kandy, social capital variable ismore significant in free driver than society driver.
Table 2 Significant variables of society driver and free driver
Moratuwa

Colombo

Kandy

S

F

S

F

S

3W driver job is worthwhile and fulfilling

○

○

○

○

Driver are proud of his job.

○

○

○

○

Satisfaction of 3W driver job

○

○

○

○

How much you want to justify bribe?

○

Independent variables

Importance to communicate with passengers○

Satisfaction of Municipal Council andProvincial Government△

3W driver is easy job△○

Satisfaction of salary as 3W driver○

Trust of trade union−○

Driver can earn as he wants

△

8.36

○
○

Trust of press○

Importance of friends

△

△

○

Driver has 3W driver friends who help him
when he faces some trouble○

Driver have reliable 3W driver friends○

3W driver job is worthwhile andfulfilling

○

○

--

Driver are proud of his job.
Satisfaction of 3W driver job
How much you want to justify
bribe?
Satisfaction of salary as 3W driverInteresting job as a reason to still
continue 3W driver job(1: Yes,0: No)
Unsatisfaction of the quality ofyour 3W vehicle

○

○

--

5. Conclusion

○

○

--

○

○

--

△

○

○

○

--

--

−○

--

--

Satisfaction of fuel cost andmaintenance cost.

△

--

--

Interesting job as a reason to start3W driver job (1: Yes,0: No)
Driver can earn as he wants
Trust of trade union
Importance of family
Importance of friends
Trust of dealer
Importance to have friendly
relationship with other 3W drivers

--

○

--

--

○

△

--

−○

--

--

--

○

--

--

○

This study clarifies 3W industry situation by interview
survey and conducted 3W driver’s life satisfaction
analysis by questionnaire survey considering social
capital to clarify factors which affect their life satisfaction.
From interview survey, it is revealed that now 3W industry
is not under control of government and government isintroducing or making new policy in order to control 3W.
3W drivers form local 3W driver groups and make theirown rules and welfare services. From questionnaire
survey, it is revealed that although the same province
cities have common significant variables, different
province city have different significant variables. In
addition, there is different significant variables between
society driver and free driver. As a future work, moremodels should be developed.

--

--

○

--

--

○

Driver have reliable 3W driverfriends----○

Trust of press

--

--

○

References[1] JICA: Urban transport system development project for Colombo
metropolitan region and suburbs:2014[2] Johannes Orlowskil, PamelaWicker: The monetary value of social
capital: Journal of Behavioral and Experimental Economics:2014[3] Amal S. Kumarage, Mahinda Bandara, Darshini Munasinghe:
Analysis of the economic and social parameters of the Three-Wheeler
Taxi service in Sri Lanka: Research in transportation economics:201020○○(○:1% significance level, △:5% significance level)
S: Society driver
F: Free driver(○:1% significance level, △:5% significance level): General social capital parameters: 3W driver’s social capital parameters: Personal information (3W driver)△

Satisfaction of fuel cost and maintenance cost.

Importance to have friendly relationshipwith other 3W drivers

Kandy

○

Importance of family

Driver like to communicate with passengers

FSimulation of forest fire using a coupled weather-fire model WRF-Fire
13B15384 Name : Kohei YAMASHITA

Supervisor : Manabu KANDA

1. Introduction
When fire occurs, it triggers modifications to its
surrounding

meteorology.

In

investigationsofneighborhood-scale fire incidents, it is necessary toconsider the interaction between the fire andweather. Until now, a lot of research of wildland fire
has been condicted internationally. However, thishas never been conducted in Japan. The aim of thisFig.1 Burned area. Dotted line represents actual burned

study is to test the applicability of a coupled weather-firelinemodel in investigating Japan forest fire events.

2. Numerical Setting
2.1 WRF-Fire Model
The regional weather model Weather Research andForecasting (WRF) which is widely used to calculate thewe a t h e r f i e l d i s c a p a b l e o f l o c a l a n d wi d einterconnection by the nesting method. WRF-Fire is anadditional component of the model which couples theweather model with a fire-sread model. WRF calculates
the surface wind field and is inputted to the fire spread

Fig.2 Simulated fire spread (orange area) corresponding

module which calculates spread rate and feedbacks heatto the actual burnt area (white line) in fig. 1. Arrows

flux from the fire (Rothermal, 1972; Coen et al., 2012).

represent simulated 10-m wind velocity.

2.2 Target Forest Fire Event
We applied WRF-Fire to a forest fire incident thatEnvironmental Prediction (NCEP) was used for theoccurred in Japan. Figure 1 shows Takamikurayama

initial and lateral boundaries.

forest fire in Hyogo Prefecture, the center of the nested
domains. The fire occurred early in the morning of

3. Results

January 24th, 2011. 117 ha of forest area was burned.

Fig.2 shows the simulation result of fire spread area.

To determine the fuel category of the forest, 13 fuelThe simulation captured the areal sequence of spread.

model (Anderson 1982) is commonly used. In theFire spread to eastwards following the wind. Fig.3 shows

simulation, the forest was set to a category of 10(timber).

the temperature difference due to latent heat release from

Objective analysis data of the National Center for

fire. Arrows in figures mean wind velocity. Figures show
wind is affected by causing plume at fire front line.

21

In the first simulation, it was found that fire spread rate
was overestimated although the pattern matches with theobserved fire spread. The spread rate was improved bycorrecting the fuel category (from category 10 to 9) andlimiting the fire spread based on fire-fighting activity (i.e.
setting no fuel category to the fire-protected area) (Fig.
4). Simulation result is Fig.5. Simulation result area issimilar to actual burned area.

Conclusion
The result of simulation showed feedback effect from

Fig.3 Change in 2-m. temperature (°C) due to forest fire.

fire. The result of simulation confirms that WRF-Firecan be applied to forest fires in Japan. The next step of
this research is to improve the model to consider urban
fire.

Acknowledgment
This research was funded by Promotion Program for
Scientific Fire and Disaster Prevention Technologies.

Reference
Rothermal, 1972: A mathematical model for predicting

Fig.4 Forest fuel category based on the classification by

fire spread in wildland fuels

Anderson (1982). Yellow and red area corresponds toAnderson, 1982: Aids to Determining Fuel Models For

fuel category 9 (litter) and no fuel category, respectively.

Estimating Fire Behavior
Coen et al., 2012: WRF-Fire Coupled Weather-WildlandFire Modeling with the Weather Research andForecasting Model

Fig.5

New

simulated

firespread(orangearea)

corresponding to the actual burnt area (red line). Arrows
represent simulated 10-m wind velocity.

22Design of a Rectangular Patch Antenna for Radio Propagation Measurement
Student Number: 13B09596 Name: Xin Du Supervisor: Jun-ichi TAKADA
2017/2/21
1

Introduction

3

The antenna is an essential part in the wireless communication systems. A channel sounder is an important equipment to predict performance of advanecd systems such as
MIMO [1]. There are numerous researches about evaluation of propagation mechanism for the MIMO systems at
2.4GHz and 60GHz frequency band [2]. In the next generation 5G systems, higher frequency band will be used andour group is focusing on measurement of the channel characteristics at 5GHz frequency band by using USRP channelsounder systems. Lightweight antenna is desired in a channel sounding equipment. Therefore, a patch antenna with
5GHz center frequency will be designed for both transmitter and receiver of USRP channel sounder.

2

Simulation and Design

The finite integration technique (FIT) based simulator
CST Studio Suite was used in analysis and design. Discrete port, which is used for simple modeling, with 50Ω
impedance is set at P . To adjust center frequency at
4.85GHz, L(= W ) is determined according to the Eq.(1)–Eq.(4) as the initial value. The feed offset P was set by
1.9mm tentatively. L(= W ) is changed to adjust center
frequency and L = W = 13.2mm was determined by thesimulator. Then, L and W are changed individually for finetuning. Figure 2 shows frequency characteristic of reflection coefficient S11 with variations of L (W = 14.0mm).
Fine adjustment of resonance frequency can be controlled
by changing the values L and W . Finally, L = 13.6mm
and W = 14.0mm was determined for the antenna withcenter frequency of 4.85GHz.
Next, the SMA, which is used in the measurement, connector is introduced in the simulation as feed structure tovalidate the discrete port feed modelling. It was foundthat the shift of resonant frequency is negligible. Figure 3
shows frequency characteristic of reflection coefficient S11with variations of P . When P = 2.1mm, the best matching can be realized. The relative bandwidth is 2.45% (for|S11 | < −10 dB) and 4.94% (for |S11 | < −5 dB).

Patch Antenna(a) Perspective view(b) Cross-sectional view

Figure 1: Configuration of a rectangular patch antenna

Figure 1 shows the configuration of a rectangular patch
antenna. Here, an FR-4 substrate with 1.6mm-thick isused. The dielectric constant of FR-4 around 5 GHz is ǫr =4.3. The thickness of the copper is 18µm. The resonancefrequency of a rectangular patch antenna can be approximately expressed by Eq.(1)– Eq.(4) [3].
c0√2Le ǫrpǫre (L)ǫre (W )Le = L(1 + ∆)
ǫr
fr =

∆=

Figure 2: Frequency characteristic of S11 with L

(1)

(2)

h
0.164(ǫr − 1)ǫr + 1L[0.882 ++{0.758 + log( + 1.88)}] (3)
L
ǫ2r
πǫr
h
ǫre (x) =ǫr + 1ǫr − 1h −1+(1 + 12 ) 2
2
2
x

(4)

Figure 3: Frequency characteristic of S11 with P

Where, fr is resonant frequency. c0 is speed of light. L
and W are the length and width of the patch, respectively.

23

In order to make the lightweight patch antenna, it is necessary to miniaturize the substrate size. The simulationshows the influence is not large until substrate size is larger
than 50mm-length square. Therefore 50mm-length square
substrate is used for fabrication. Figure 4 shows gain pattern with lengths of substrate (L = 13.8mm W = 14.0mm
P = 2.1mm). Here, the angle theta (θ shown in Fig. 1) isthe angle from z axis.

and width of the patch will also affect the center frequency. Precision of the dimensions of the patch wasenough. It is difficult to control thickness of substrate withmilling machines while in-plane pattern can be precisely
controlled. The measured thickness of the fabricated antenna was 1.4mm. The simulation was conducted to checkthe influence of thickness of the substrate. Figure 7 shows
frequency characteristic of S11 for two kinds of thickness(1.4mm and 1.6mm). The center frequency of 1.4mm-thicksubstrate is higher than that of 1.6mm-thick one.
Another potential possibility of frequency shift is estimation error of the substrate dielectric constant. In the simulation, dielectric constant of 4.3 is used for the FR-4 substrate. However, it is known that the FR-4 has dispersive
characteristic around GHz band and dielectric constant become small as the frequency becomes higher [4]. For example the dielectric constant of substrate is about 4.0 at
5.94 GHz [5]. Figure 7 also shows that the difference of
frequency characteristic of S11 between two different dielectric constant, 4.3 and 4.0 (h=1.4mm). The center frequency is about 5.1GHz when dielectric constant is 4.0.
There is a high possibility the thickness and dielectric constant factors cause the center frequency shift.

Figure 4: Gain pattern with lengths of substrate (x-z plane)4

Measurement and Results

A CAD software EAGLE and milling machine were used
for fabrication of the antenna. An SMA connector was soldered after drilling and milling the substrate as shown in
Fig. 5.

(a) Front view(b) Back view(c) After soldering

Figure 7: Comparison between different thickness anddielectric constantFigure 5: Fabrication of Patch Antenna

Figure 6 shows the measured and simulation result of
frequency characteristic of S11 . Vector network analyzer
ROHDE&SCHWARZ ZVA 40 was used in measurement.
The shift of center frequency was observed. The measured
center frequency is about 5.1GHz.

5

Conclusion

A rectangle patch antenna was designed for channelsounder at 5GHz band. An antenna was fabricated andmeasured. Frequency shift was observed from simulation.
The frequency shift may due to the estimation error of dielectric constant of the substrate. Frequency adjustment isfuture study.

References[1] Ezio Biglieri, Robert Calderbank, Anthony Constantiniades,
Andrea Goldsmith, Arogyaswami Paulraj and H.Vincent Poor
MIMO Wireless Communications isbn.13-978-0-521-87328-4,
pp.1-7, publisher.Cambridge University Press, 2007.
[2] Tianyang MIN, Kentaro SAITO, Minseok KIM and Junichi
TAKADA
Channel Sounding in 2.4GHz and 60GHz bandfor Multi-band Wireless LAN System IEICE Technical Report
SRW2016-39 pp.37-41, 2016-08.
[3] G. A. Deschamps Microstrip Microwave Antennas 3rd USAF
Symposium on Antennas, 1953.
[4] Shingo INOUE and Futoshi KUROKI Measurement on Dielectric
Properties of FR-4 Substrate at Millimeter-wave Frequency IEICE
Technical Report, vol.111, no.351, MW2011-126, pp.5-8, 2011-12.

Figure 6: Measured and simulated S11

According to Eq.(1)– Eq.(4), the reasons for frequency
shift were considered. The thickness and permittivity of
substrate may cause frequency shift. In fabrication, length24SFM-AKAZE による 3D 点群再構築に関する研究
学籍番号:13B04506

1

名前:魏

指導教員:山下

嘉昊

はじめに

2.2

幸彦

準教授

カメラの外部パラメーター

一般には、世界座標系とカメラ座標系は独立である。
現在、コンピュータービジョンの分野において、複数3D再構築する際には一つの固定した世界座標系と複数の画像から対象物の 3 次元情報を取得する 3 次元再構築のカメラ座標系が必要となる（一般には最初のカメラ座手法に関する研究が数多く行われている。最近は動画像解析（SFM）に基づいた 3 次元情報の取得に関して世界 標系を世界座標系にする）。

の人々が研究を行っている。
XW
XC
SFM では、まず 3 枚以上の複数の画像間の対応点を、
 YW 
 YC 

(4)
各画像の特徴点の特徴量に基づいてマッチングによって探 ZC  = D  ZW 
す。マッチングした対応点からエピポーラ幾何（Epipolar
1
1
Geometry）の理論を用いてカメラの内部パラメーター
外部パラメーターはワールド座標系内のカメラ座標系と外部パラメーターを計算し、Bundle Adjustment 手法
で誤差を抑えることで各カメラの位置及び対象物の 3 次 の位置 t（平行移動 Translation を表す 3x1 ベクトル）と元位置を推定する。本研究では、従来多数の SFM ソフ 姿勢 R（回転 Rotation を表す 3x3 行列）によって決定
トウェアに使われている SIFT（Scale-Invariant Feature できる。R と t を用いて座標間の関係を式で表すと以下Transform）の代わりに、最近注目されている AKAZE となる。ここで、D と 03 は次式で定義される。
()（Accelerated KAZE）の特徴量を用いて対応点をマッチ
R t
ングすることを試みる。
D=, 03 = [0, 0, 0]T
(5)
0t3 1

2

カメラモデル及びエピポーラ幾何
2.3

カメラで撮影した画像は、3 次元空間の物体をカメラを通して 2 次元平面に射影したものである。最終的には、ある物体に対し、行列をかけて 3 次元空間の点から
2 次元平面の点に変換できる。エピポーラ幾何とは、3次元空間に存在する点をステレオ視から観察する際の相対的なカメラ位置や姿勢などの情報を記述できる幾何で
ある。

2.1

カメラ行列

上述のカメラ内部パラメーターと外部パラメーターを合わせた関係式は以下のようになる。







 
XC
XW
XW
u
 YC 
 = KD  YW  = P  YW  (6)s v  = K  ZC 
 ZW 
 ZW 
1
1
1
1

カメラの内部パラメーター
ここで、行列 P はカメラ行列（または新たな透視投影行列）と呼ばれる。世界座標とディジタル画像座標の関係を表す大事な行列である

まず、3 次元カメラ座標系上の点 (XC , YC , ZC )、2 次
元画像平面上の点 (x, y) はカメラの焦点距離 f を用いて、以下の関係を満たす。
(
( )
)
f
XC
x
(1)
=
y
ZC YC

2.4

エピポーラ方程式

仮に、3 次元ワールド座標系のある点 P に対し、p =(x, y, 1)T と p′ = (x′ , y ′ , 1)T は 2 つの画像座標からなる
また、点の位置の次元を一つ上げた同時座標で表す。 同次座標とする。p と p′ は以下の関係を持つ。
すなわち (x, y) の代わりに (x, y, 1) で表す。
p′ = Rp + t(7)
さらに、画像座標 (x, y) からディジタル画像座標 (u, v)への変換が必要である。その関係式は以下となる。
同一平面上の三つのベクトル p、p′ 、t から二つのベク
 
  
トルの外積と残る一つのベクトルの内積は 0 という性質
ku −ku cot θ u0
x
u
kv


v  =  0を用いて以下の方程式が成り立つ。
y
(2)
v
0
sin θ
1
1
0
0
1
p′T [t × (Rp)] = 0(8)
今までの式を以下のようにまとめる。


 
XC
p′T Ep = 0(9)u YC s v  = K (3)
ここで、行列 E は基本行列（Essential Matrix）と呼ZC 
1
ばれる。基本行列はベクトルt の歪対称行列 [tx ] と回転
1
行列 R から構成される。また、上述したカメラ同次座標
ここで、行列 K はカメラの内部行列である。
における点 p、p′ に対する 2 次元画像平面のディジタル25画像座標系の 2 次元点を x = (u, v, 1)T 、x′ = (u′ , v ′ , 1)Tに変換する。関係式は以下のようになる。

4

実験結果

今回の実験は fountain-P11、Herz-Jesu-P8、entry(10) P10 三つの画像データを用いて、SFM-SIFT と SFMAKAZE を比較して、その結果を検討する。
上述したエピポーラ方程式は以下のように変わる。

x = Kp, x′ = K ′ p′p′T Ep = 0
x′T (K ′−T EK −1 )x = 0
x′T F x = 0

Table 1: 実験結果
(11)

fountain

ここで、行列 F は基礎行列 F（Fundamental Matrix）と呼ばれる。基礎行列 F はカメラの内部パラメーター Kと外部パラメーター E 両方を含んでいる。

3

AKAZE 法SIFT 法ではガウシンフィルターの等方性により勾配
強度の大きい方向に対しても平滑化してしまうため、局所的な特徴及び輝度値が曖昧になってしまう。AKAZE
ではエッジを保存するために非線形拡散フィルターを用いる。さらに、AKAZE では特徴記述子として独自の記述子を使用する。

3.1∂L= div(c(x, y, z) · ∇L)∂tc(x, y, t) = g(|∇Lσ (x, y, t)|)1
g2 =|∇Lσ |2
1 + k2

(12)
(13)
(14)

5

AKAZE

11
8188
4.04

11
4497
3.99

8
4501
3.50

8
4431
3.28

10
9936
7.08

10
8570
8.80

1.45

1.95

1.40

1.73

3.88

5.20

36.40

25.05

25.77

18.19

34.66

24.79

5.99

3.80

3.36

2.25

11.09

15.74

47.51

31.15

31.48

22.70

51.09

44.02

参考文献
[1] Alcantarilla, Pablo F., and T. Solutions. ”Fast explicit diﬀusion for accelerated features in nonlinear
scale spaces.” IEEE Trans. Patt. Anal. Mach. Intell
34.7 (2011): 1281-1298.

特徴点検出

特徴点を検出するために、非線形スケール空間におけるフィルタリングされた画像 L の各点で、ヘッセ行列の行列式を計算する。下式は標準化する際に用いる微分演算子である。
2
LiHessian = σi,norm(Lixx Liyy − Lixy Lixy )結論

本研究では、対応点マッチング法の AKAZE 法を用いた 3D 点群再構築手法を提案した。実験の結果、再構
築した点群数は一般の SFM-SIFT 法より少なかったが、時間を短縮できることがわかった。対応点マッチングした後の誤差を減らすステップの改善により再構築する点
群数の増加が今後の課題である。

非線形スケールスペース

拡散フィルターは時間軸で定義されているため、下式でピクセル軸から時間軸へ変換する。
1
ti = σi2 , (i = 0, 1, · · · , N )
(16)
2

3.4

AKAZE SIFT

SFM-AKAZE 法は SFM-SIFT 法より再構築した点群
数が少なかった。しかしながら、計算時間に関しては
SFM-AKAZE 法は SFM-SIFT 法より明らかに短縮できた。リアルタイム 3D 点群再構築や 3D 顔認識などの様々な方面の応用は期待できる。

対数ステップの離散化スケールスペースはオクターブ
o とサブレベル s で書かされ、スケール σ と次式のように対応する。
o+s
σi (o, s) = σ0 2 S
(15)

3.3

entry

AKAZE SIFT

非線形拡散フィルター

AKAZE 法は非線形拡散フィルターを用いることでエッジを保存することができる。

3.2

画像数
合計点数
BA 前 誤差 [pixel]
BA 後 誤差 [pixel]
抽出時間
[s]
マッチ ン
グ時間 [s]
合計時間[s]

Herz-Jesu

SIFT[2] Alcantarilla, Pablo Fernandez, Adrien Bartoli, andAndrew J. Davison. ”KAZE features.” European
Conference on Computer Vision. Springer Berlin
Heidelberg, 2012.

(17)[3] Hartley, Richard, and Andrew Zisserman. Multiple
view geometry in computer vision. Cambridge University press, 2003.

特徴量記述

AKAZE 法は KAZE 法のように各特徴点ごとに半径σi ごとに 6σi までの範囲を探索することで特徴量発見 [4] Perona, Pietro, and Jitendra Malik. ”Scale-space
し、各特徴点の一次導関数 Lx と Ly を特徴点のガウス
and edge detection using anisotropic diﬀusion.”関数によって重み付けする。特徴点の方向は π3 の角度
IEEE Transactions on pattern analysis and maのベクトルの総和になる。その総和のベクトルのオリエ
chine intelligence 12.7 (1990): 629-639.
ンテーションが特徴点の方向となる。
26

Fe 交換ゼオライト触媒による C3H6 を用いた NO 選択還元
学籍番号：13_09159

名前：譚 楊 指導教員：日野出洋文

1 背景
今日、自動車は産業社会や日常生活において不可欠な存在となっている。一方で排気ガスが工場の排煙とともに大気汚染源の一つとなっている。近年、特に発展途上国において
大気汚染問題が深刻で、WHO が PM2.5 など
大気汚染による死者が 2012 年に推計 700 万人超だったとの報告を出した。自動車排ガス

2.実験
本研究ではベータ型ゼオライトに JRC-ZB25(1)を使用した（以下は Beta と呼ぶ）。また
比較的細孔径の大きなメソポーラスベータゼ
オライト（以下 Betameso と呼ぶ）を水熱合成法[3]で合成した。
Beta と水熱合成法により合成した Betameso
をイオン交換法で Fe イオンを導入した。イオ

中の主要な大気汚染物質は、CO、HC、NOX、
SO2、パティキュレート（未燃焼すす）である。
NOX の除去が重要であることが明白である。
NOX 除去の有効な方法の一つは触媒技術で、その中に炭化水素による NOx の選択的接触還元（HC－SCR）がある。これは排ガス中の未燃焼のプロピレンなどの炭化水素または含酸素有機化合物を NOｘの還元剤に使用する技術である。
これまでゼオライト系、金属酸化物触媒、貴金属系触媒において NOｘ選択還元能が見出

ン交換過程での上澄み液を回収し、回収した液をすべて集め、イオン交換量を誘導結合プ
ラズマ原子発光分析（ICP-AES）で測定した。
Fe 交換ゼオライトを乾燥、550℃で６時間焼成し、触媒を調製した。当該触媒を Fe-beta、Fe-betameso とし、また比較として、Beta、
Betameso の選択還元活性を測定した。
炭化水素による NOX の選択還元実験は常圧固定床流通式反応装置を用いた。一回の測定に 0.4ｇの触媒を用い、NO（1500ｐｐｍ）、O２（10％）、C3H6（1500ｐｐｍ）というガス組成されている。ゼオライト特に ZSM-5（MFI）、モ
ルデナイト（MOR）、ベータ（BEA）などに Cu を担持した触媒による HC-SCR を扱った報告が多いが、実用に至っていないのも事実である。
またゼオライト結晶内部での拡散の効果が検討され、細孔内の反応物、生成物、水蒸気な
どの活性抑制物質の拡散が容易であるため、酸素の 12 員環からなる比較的大きな細孔を持つ Co-ベータは、活性が高いことが報告されている[1]。

（バランスガス：He）で実験を行った。空間速度は約 1.3×104h-1 である。
NO と NO2 の定量には NOX 分析計（島津製作所 NOA-7000）を使用した。CO2 の定量にはガスクロマトグラフ（GL Science 社製 GC－3200、TCD detector）を用いた。触媒のキャラクタリゼーションを熱重量分析・示差熱分
析法（TG-DTA）、X 線回折法（XRD）、ICPAES、窒素吸着法（Nitrogen adsorption
method）で行った。

さらに Fe 交換ベータ型ゼオライトは、CO 還元能を有すると共に N２O 分解活性を併せ持つことが報告されている[2]。
本研究では上で述べた既存研究のもとに Fe
交換ベータ型ゼオライトの NO 選択還元活性について検討した。

３．結果および考察
Fig.1 で示したように Fe イオン交換ベータ型
ゼオライト(Fe-beta)は 300℃から 500℃の間で他の触媒と比べて高い活性示した。350℃付
近では一番高い活性（NO 転化率 63.6％）を示した。Fe-betameso は Fe-beta と同じ傾向を示し、350℃で一番活性（NO 転化率 52.6%）を

27

示すも、Fe-beta より低いことがわかった。Fe
イオンを導入していないゼオライト触媒 Beta

比表面積（m2/g）と Betameso はある程度活性を示したが、Fe イオンを導入したものと比べると活性が著しく低い結果となった。

Fe-beta

733.9

Fe-betameso

405.6

Table1 の比表面積の結果から Fe－ｂ
etameso より Fe-beta 比表面積が大きいことが Fe-beta の活性の高いことと一致したことか
ら、比表面積が活性点の分散に影響していることが考えられる。

Fig.1 NO から N2 の転化率[%]

Fig.4 触媒 XRD パータン

Fig.4 に合成したベータ型ゼオライトや Febeta、Fe-betameso の XRD パータンを示した。結果はゼオライトの結晶構造はイオン交換のあとでも保たれ、またイオン交換量が少ない
ため、鉄の酸化物結晶相は検出されなかった。
TG-DTA の結果から各種の触媒は９00℃まFig.2 C3H6 から CO2 転化率[%]

Fig.2 から触媒 Fe-beta と Fe-betameso は300-450℃で高い CO２への転化率を示した。
活性実験で 300-450℃で高い活性がでたことと一致したことから、この温度域で NO 選択還元反応が行われることがわかった。

で熱的に安定しているが確認できた。
ICP-AES でイオン交換量を測定した結果
Fe-beta と Fe－betameso のイオン交換率はそれぞれ 0.69%、1.14%で Fe－beta の交換率（鉄含有量）が低いのにもかかわらず高い活性を
示した。
４．結論
Fe 交換ゼオライト系触媒は HC－SCR で高い活性示した。また比表面積は反応活性に関係していることがかわった。更に、実用化には
水蒸気、SO２などの反応阻害物質の影響と長時間運転時の耐性を検討する必要がある
参考文献：

Fig.3 C3H6 の無い状態の転化率

Fig.3 から C3H6 の無い状態では活性が低いことから還元剤 C3H6 の存在は NO の還元分解に不可欠であることがわかった。

[1]T.Tabata et al.,Catal.Today,27,91[2]M.Rutkowska et al.,Applied Catalysis B(2013)[3]Van Obers et al.Microporous and mesoporous

Table1 触媒の比表面積

Materials120(2009)28

地方自治体の水道事業体の経営効率性と国際活動の関係
学籍番号：13_15556 氏名：山田 優志 指導教官：阿部 直也

定都市の水道事業体、中核都市の水道事業体を対象

1.研究の背景と目的(合計 64)に、各水道局の需要の大きさ[給水人口(人)]、近年、我が国の地方自治体の水道局の一部は、開施設の能力の大きさ[年間配水量(m3)]、技術力の大発途上国における水道事業の運営体制改善や人材育

きさ[有収率(%)]、施設の規模の大きさ[職員数(人)]、成、さらには技術協力などに関して積極的に活動を

水道料金(円)、事業収入(円)、事業支出(円)を知るた

行っている。一方、開発途上国における水道事業は、めに、それらの過去五年間(平成 23 年~平成 27 年)

地域やコミュニティーによっては、依然としてインの平均値をデータとした。まずクラスター分析を行フラとして十分に整備されていない状況があり、イ

い水道事業体の規模と、国際活動の関係性を調べた。

ンフラとして上水道が整備されている地域において効率の面を調べる際には、DEA(BCC モデル)を用い、も、水質・水量ともに不十分な状況がしばしば指摘

変数を DEA に投入する組み合わせを、すべての変されている。具体的には、水道事業を担う組織の不数、技術的な変数、経済的な変数の三通りに分け、十分なマネジメント体制や能力不足により、盗水やどの側面の効率値が国際活動に関係するのかを明白

漏水問題、さらには水質汚染に伴う感染症などが指にした。そこで、国際活動に関係すると判明した側

摘されている。

面の効率値をいくつか求め、クラスター分析を再度

開発途上国の水道局職員の人材育成を怠ると、水行うことで、効率値と国際活動に関係があるかを観道職員は、世界からの ODA により建設された高機察した。

能な水道施設を効率的に使用できない。また、開発

3. 各水道局の規模と効率値

途上国の無収水率は高く、供給した水を料金として効率よく回収できていない。このような問題を解決

前述の全ての変数を投入し水道事業体の規模にするために、現地の水道職員に日本の水道事業のノついてのクラスターを図.1 に挙げた。

ウハウを伝えるべきであると考える。国際活動に関0%する現状は、平成 20 年から平成 27 年の八年間にかけて 2,000 近くある水道事業体の中からわずか 23
18%

事業体と活発であるとは言い難い。さらに、国際活動を直接的にはやっていない水道事業体も国際活動に貢献しようとしている。堺市と仙台市がそれにあたる。堺市水道局は公式に国際活動に乗り出すことを発表しており、仙台市は 2003 年から札幌市水道10%

局の国際活動を一部引き受けている。
以上を踏まえ本研究の目的は二点である。第一に、国際活動の活発度に注目し、水道事業体の規模と経

77%

各
ク
ラ
ス
タ
ー
の
国
際
活
動
に
従
事
し
た
水
道
局
の
割
合

営率性の間に関係性があるかを明らかにする。第二に、国際活動の実績の有無に着目し、水道事業体の100%

経営効率性に差があるのか明らかにする。

図.1 規模のクラスター分析

2. 研究の枠組み
国際活動に従事したことある水道事業体、政令指29

また、クラスターの各変数の平均値を表.1 に挙

4. おわりにげた。

以上より本研究の結論をまとめる。第一に、地方表.1 各クラスターの平均値

自治体の水道事業体による国際活動の活発度に注目

給水人口(人) 年間配水量(m3)有収率(%) 水道料金(円) 事業収入(円) 事業支出(円) 職員数(人)Cluster A

3.65E+05

4.59E+07 8.78E+01

5.18E+09

5.49E+09

4.75E+09 1.28E+02

Cluster B

4.06E+05

5.14E+07 8.85E+01

6.94E+09

7.57E+09

6.75E+09 2.12E+02

Cluster C

3.85E+05

4.47E+07 9.25E+01

6.45E+09

7.02E+09

6.44E+09 1.73E+02

Cluster D

1.10E+06

1.29E+08 9.29E+01

2.09E+10

2.36E+10

2.24E+10 4.45E+02

Cluster E

3.86E+06

4.30E+08 9.24E+01

5.01E+10

5.64E+10

4.98E+10 1.15E+03

すると、水道局の事業規模と技術的効率性の間に正の関係性があることを確認した。第二に、経営効率性の間には、統計的に有意な差を確認できなかった

国際活動に貢献したことがある水道事業体の割が、両者の技術的効率性に注目すると統計的な有意合が多いクラスターほど、各変数の平均値が高いこ差を確認した。

とが見受けられた。ここから、規模が大きいほど国そこから得られる提案として大きな規模かつ高際活動に貢献していることが確認できた。また、

い技術的効率性を持っている水道局は国際活動に貢DEA では、全体の効率値、技術的効率値、経済的効献できる可能性を持っている。前述した仙台市と堺率値を観測した。技術的な変数を入れた時にだけ、市の規模は大きく技術的効率性の高いため、研究結

国際活動に貢献したことある水道局の効率値とそう果に沿った形となった。

でない水道局の効率値に有意性を確認できた(図.2)。

今後の課題として、技術が高い故、国際活動に貢経済的効率値で二つの間に有意性が見られなかった

献しているだけでなく、国際活動を通じて、日本の背景は、国際活動をする際に JICA による財政補助

職員の技術が高まっていることを解明することが挙があり、各水道事業体で国際活動の費用を負担しなげられる。また、実践的な国際活動に貢献する理由

くてもいいことが考えられる。
P<0.01を調べることが挙げられる。規模、効率性と国際活P<0.01動の関係性から、論理的には国際活動に貢献できる

P<0.01

水道局を特定することができる。しかし、実際にメリットがないと多くの水道局は国際活動に踏み出す
入力

給水人口、職員数

入力

給水人口、職員数

入力

給水人口、職員数

出力

総給水量、有収水量

出力

有収水量

出力

総給水量

ことができない。ステークホルダーを整理し、23 の水道局が実際なぜ国際活動を始めたのかをまとめて

図.2 技術的効率値の有意性いくことでより多くの水道局が国際展開していける

技術的な変数をいくつか組み合わせて各々効率と考えられる。

値を出し、クラスター分析を行った。クラスターβとγには国際活動に貢献した水道局の割合が高く

参考文献(α=17%,β=75%,γ=39%)、各々のクラスターの効[1] 東京都水道局(2016),

率値の平均を見ると、クラスターβとγが全体の効

https://www.waterworks.metro.tokyo.jp/

率値の平均よりも高いことを確認した(図.4)。ここか(閲覧日：2017 年 2 月 10 日)ら技術的効率と国際活動にも関係があることを確か[2]各地方自治体の水道局めた。

[3]奥沢英一,濱田篤郎(2000) 開発途上国における水系感染症とその実態[4] 公 益 社 団 法 人 日 本 水 道 協 会 (2016),
http://www.jwwa.or.jp/ (閲覧日：2017 年 2 月 10日)

図.3 各クラスターと全体の平均値30Concept study of a deployable atmospheric reentry vehicle with
Waverider eﬀect
Student Number：13-16478

Name：Tomohiro Watanabe

1Introduction

2

Mission and System concept

Supervisor：Daisuke Akita

The lower surface of the vehicle receives high pressure
by the attached shock wave and results in the increase in
A sounding rocket is an instrument-carrying rocket de- the high lift to drag ratio. This is the Waverider eﬀect.
signed to perform scientific observations during its suborbital flight(50〜1500km). The recovery of the payload on the final stage of the sounding rocket opens
up new possibilities. The recovered equipment can bereusable and it is cost-eﬀective. The Sample-return mission, whose goal is collecting and returning samples fromhigh altitude to ground, also becomes possible.
This paper proposes the recovery of the payload witha deployable reentry vehicle with Waverider eﬀect. The
feasibility is investigated by designing the shape and the
Figure 2: Vehicle Configuration
aerodynamics performance of the vehicle.

3

Trajectory calculation

The motion equations of the vehicle are given in polar
coordinates. The forces on the vehicle are only the Earthgravity force and the aerodynamic force. The equation is numerically calculated by 4th order Runge-Kutta
method. Initial velocity is 0.01[m/s], initial altitude is
180[km], initial path angle is 0[deg], initial longitude is0[deg].
The heat flax q[W/m2 ] is estimated by Detra-KempRiddell equation[1]. The surface temperature of the vehicle is calculated by Stefan-Boltzmann equation using
the result of heat flax. The curvature radius of the leading edge is 2.0[cm].

Figure. 1 shows the mission concept.
1. The sounding rocket carrying the recovery vehicle
on the final stage is launched
2. The rocket reaches the target altitude, releases the
final stage and opens the nose cone. The recovery vehicle separates from the final stage and is deployed.
3. The recovery vehicle controls its attitude. During
on-design Mach number, the lift to drag ratio increases by Waverider eﬀect.
4. The vehicle reaches near the launch site. Before thevehicle falls into the sea, the parachute is deployed.

4

Required aerodynamic characteristics

The vehicle must meet the following three requirements
to realize the mission.
(i) The temperature of the vehicle surface is less than1550[K].
(ii) The downrange of the vehicle is more than 90[km].
(iii) The vehicle can be installed inside the rocket nose
cone of 20[cm] radius.
As the lift to drag ratio is 1.0, the ballistic coeﬃcientis less than 170[kg/m2 ] to meet Req. (i).
The lift to drag ratio was determined by the following
procedure.

Figure 1: Mission Concept
Figure. 2 shows the model of the recovery vehicle. It
is the ”Caret-Wing Waverider”, which has the simplest
shape in all the Waveriders. In Fig. 2, the black line
shows the shape of vehicle and the blue line shows theshock wave attaching the leading edge of the vehicle.

1. The lift to drag ratio gained by Waverider eﬀect isdetermined, and then the vehicle wedge angle θs isdetermined by Eq. (1)[2].

31

L
1
=
D
tan θs(1)

2. On-design Mach number is determined by the trajectory calculation for the long downrange, and theshock wave angle βs is determined by Eq. (2). The
heat capacity ratio κ is 1.4.

θs = tan−1(
2 cot βsM 2 sin2 βs − 1
M 2 (κ + cos 2βs ) + 2)(2) Figure 4: Cross-section drawing of non-deployable vehicle inside the nose cone of sounding rocket

3. In this study, oﬀ-design lift to drag ratio is determined by assuming the shape of the triangular pyramid (triangular pyramidOAA’C in Fig. 2) in the
supersonic flow[3]. Table. 1 shows the height h andthe width w of this triangular pyramid.
Figure 5: Cross-section drawing of deployable vehicle
inside the nose cone of sounding rocket
The condition for maximizing the projected area wasdetermined. The projected area(S = lw) is the functionof only the width.
The length l is calculated by the equation(h =Table. 3 shows the size of deployable and nonl tan βs ).
deployable vehicle which has the maximum projected
area.
Table 1: Triangular pyramid size
Hight h[cm] 20
Width w[cm] 20

As on-design lift to drag ratio is 2.3 and the Mach
number is 5.0, the vehicle meets Req. (i). Table. 2
shows the lift to drag ratio of this vehicle.

Table 3: Size of deployable and non deployable vehicle

Length l[cm]Height h[cm]Width w[cm]Projected area S[cm2 ]Table 2: Aerodynamic characteristics of Waverider
Lift to drag(4.25 ≤ M ≤ 5.75) 2.3
Lift to drag(otherwise)
1.8

Deployable
51.7
28.6
28.0
1449

Non-deployable
54.4
30.0
17.3
941

As the vehicle has the lift to drag ratio such as Tb. 2,
the ballistic coeﬃcient is less than 175[kg/m2 ] to meet
Req. (i).
6 Conclusions
Figure. 3 shows the flight trajectory of the vehicle
This study shows that the recovery reentry vehicle isthat has the aerodynamic characteristics above.
able to withstand the aerodynamic heating and reachnear the launch site. However, the estimation of aerodynamic characteristics isn’t suﬃciently accurate. The
estimation of the aerodynamic characteristics is necessary to model the eﬀect of viscosity and non-linearity of
the compressible flow. The future work is to estimate
the accurate aerodynamic characteristics of the vehicle
by wind tunnel experiments and CFD.

References

5

Figure 3: Trajectory of the recovery vehicle[1] N. H. Kemp, F. R. Riddell ”Heat Transfer to Satellite Vehicles Re-entering the Atmosphere”, Journalof Jet Propulsion, Vol. 27, No. 2, 1957, pp. 132-137

Deployable vehicle and Nondeployable vehicle[2] Goro Kamimoto, Yoshitaka Uenaka, ”Measurementsof the Hypersonic Aerodynamic Characteristics for
Several Kinds of Wave Riders”, The Japan Society
for Aeronautical and Space Sciences, Vol.17, No.184,
1969

Figure. 4 shows non-deployable vehicle inside the nose
cone of the sounding rocket. Figure. 5 shows deploy- [3] L. C. Squire ”A comparison of the lift of flat delta
wings and waveriders at high angles of incidence andable vehicle. The span of this vehicle is maximized byhigh mach number”, Archive of Applied Mechanics,
deployment. The size of the vehicle needs to be large
Vol. 40, Issue 5, 1971, pp. 339-352
to decrease the ballistic coeﬃcient of the vehicle. The
ballistic coeﬃcient is determined by the requirement for
the aerodynamic heating.
32

地域特性がエコツーリズムの特徴に与える影響
学籍番号：13B03599

1.

名前：海宝 慎太郎

研究の背景と⽬的

3.

エコツーリズムとは地域が主導して、⾃然を保護しつつ指導教員：阿部 直也

分析枠組み

本研究は以下の⼿順に沿って⾏われた。

も観光資源として利⽤しようとする新しい形態の観光である（敷⽥・森重 2001）。1970 年代に欧⽶で広まり、⽇本
においては 1990 年代後半から主に地域活性化の⽬的から注⽬を浴びるようになる。欧⽶のエコツーリズムが希少な⾃然を対象とするなど⽐較的統⼀された定義が存在するのに対し、⽇本では広義の定義から狭義のものまで様々あ1)

ヒアリング調査による影響要因の推測

2)

分析対象の⾃治体の絞り込み

3)

地域特性を記述する変数の収集

4)

主成分分析を⾏い変数の情報を縮約5)得られた合成変数を⽤いた階層的クラスター分析
によるエコツーリズム推進⾃治体の類型化る。希少な⾃然のみでなく⾥⼭などの⾝近な⾃然も含み、さらに地域⽂化や農業・漁業のような地域産業も観光対象

分析対象の絞り込みは、環境省が公開するデータベースとしている地域も多く⾒られる。このような「⽇本型エコの中から⾏った。エコツーリズム推進協議会といったネッ

ツーリズム」の多様性は先⾏研究でも指摘されているが、トワーク型の団体を持ち、⾏政として取り組みを⾏う⾃治

定量的な指標を⽤いて説明したものはない。

体であることを条件として 36 ⾃治体に絞り込んだ。次に、エコツーリズムに関連する 6 つの変数区分を定め、それら本研究では、多様性の背景を理解するために、エコツーを表現する変数を集めた。各指標区分を選択した理由は、

リズムの特徴に影響を与える地域特性を明らかにするこ

⼈⼝・財政は都市の持つ⼒を表し、観光はその地域の観光とを⼀つ⽬の⽬的とする。そしてクラスター分析による類発展度を、⾃然・⼀次産業・史跡はエコツーリズムの対象型化で、エコツーリズムの多様性を明らかにすることを⼆となる観光資源の充実性を表すためである。

つ⽬の⽬的とした。

2.

表 2

現状把握のためのヒアリング調査

変数⼀覧
2

どのような地域特性がエコツーリズムの特徴に影響をH%与えるか把握するため、地域特性の異なる 6 件の市町村に

H

%

H

%
%

おいて、⾃治体もしくは観光協会へのヒアリングを実施しHた（表 2）。ただし調査の幅を広げるため、⽐較的広義のエ3

コツーリズムを対象に⾏った。
表 14

ヒアリング調査地域の⼀覧
5
P

6
P

*

5

O

%*H

P

N

P

4.

O

* -2
P

P

8
P

H

01

%

%

01

%

%

01

%

%

01

%

%

01

%

%

01

%

-

,

-

,

データおよび分析結果

O

主成分分析を⾏った結果は表 3 の通りである。各変数

O
O
68

H

%

%

68

O

P

,

%

7
O

の因⼦負荷量から主成分の意味付けを⾏えるものとして

68
1

3

0

第三主成分までを選択した。第三主成分までの累積寄与率
が 58%と低いのは、本研究が着⽬した変数では捉えきれて調査の結果、特に興味深い発⾒としてエコツーリズムをいない特徴がまだ残っている可能性を⽰しており、今後の⾏う⽬的が⾃治体によって様々であることが浮かび上が課題である。第⼀主成分（PC1）は⼈⼝総数、財政⼒指数った。筆者はここから、『エコツーリズムを⾏う⾃治体は経に正の影響を受けるため、「都市度」とした。PC2 は宿泊済的な利益を期待する「観光振興」と地域の外部との交流

業従業者率、昼夜⼈⼝⽐に正の影響を受けるため、「観光発を促進する「地域活性化」の 2 つの⽬的を持ち、優先度の展度」とした。PC3 は史跡を代替的に表す仏教系従事者率

⾼さはもともと観光地であるかどうかに依存する』というに正に影響されるため、「歴史価値度」とした。特に PC2仮説を設定したい。観光地性の⾼さを観光発展度と定義しについては、ヒアリング調査で確認した観光発展度に相当た。ヒアリング調査から知⾒を得て、本研究では特にこのする評価軸であると捉えた。したがって PC2 はエコツー

観光発展度を重要な地域特性として考えた。

リズムの⽬的に影響を与える変数とみなした。

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Numerical analysis of storm surge inundation in Tacloban City caused by the 2013 Typhoon
Haiyan − analysis of evacuation and effectiveness of the embankment
Student Number：12_05514 Name：Shota Kurobe Supervisor：Hiroshi Takagi
We surveyed 38 households, while only 22 ofthese households observed physical damages toproperties outside. Using these survey results,
the calibrated model utilized in the priorresearch in 2014 was verified (Figure1).

1. Introduction
Typhoon Haiyan (referred locally as“Yolanda”) struck the Philippines on 8
November 2013, which induced severe damages
to Leyte, Samar, and several other more islands
and provinces. It was the strongest storm everrecorded in terms of one-minute sustained windspeed [Takagi et al., 2015]. According to the
National Disaster Risk Reduction andManagement Council (NDRRC), it was reported
that 6,300 people died, 28,688 people were
injured, and 1,062 people were still missing byApril 2014.
On November 8, Typhoon Haiyan madelandfall in Leyte, Samar and other islands
causing a catastrophic destruction. According to
the previous studies, a large storm surge
occurred along the coastline of Leyte Gulf,
causing particularly large damages to the sea
front of Tacloban City, which is the biggest city
in Leyte Island located at the north western endof Leyte Gulf.
This paper aims at revealing thecharacteristics of storm surge caused by Haiyan,
focusing on Tacloban City where the largest
number of casualties took place. In order to doso, based on a prior research conducted in 2014,
an analysis of evacuation behavior among local
people and the effectiveness of the newly
proposed coastal embankment were investigated.

Figure 1. Interview result, indicating what theyobserved during TY Haiyan

3. Numerical analysis
The fluid dynamics model Delft3d-FLOW
coupled with a typhoon model [Takagi et al.,2016] was employed for the simulation.
Calculation settings is as below (Table 1).

2. Field survey

Table 1. Calculation settings

In the previous study carried out in 2014, themodel accuracy was calibrated from the flow
velocity at one observation point while the water
depths were calibrated at 14 observation points[Takagi et al., 2016]. However, according toother studies, damage to buildings and structures
are not solely attributed to flood water level but
rather more connected to the water depthvelocity products [Cox et al., 2010]. In thisresearch, a field survey was carried out from
December 13 to December 17, 2015, toinvestigate how accurately water depth-velocity
products can reproduce the actual damages
happened during the passage of the typhoon.
In the field survey, the flow direction of storm
surge was confirmed by the interview survey inwhich the interviewees were asked whether or
not they observed if any humans were being
drifted along with the surge flow. Besides,
analyzing a captured video that shows the storm
surge flow velocity confirmed the findings
through the present study.

OutlineItem

Domain1:Philippines wide area(3000m)
Mesh size

Domain2:Leyte bay area(100m)
Domain3:Tacloban area(10m)Cause of storm surge

Typhoon Haiyan(central pressure895hpa),
50 years period typhoon(Central Pressure 905hpa)

Time stepΔt=0.005 min

Tide level

Mean Lower Low Water

Computation time

Data of sea level

Data of ground level

Roughness coefficient

Domain1

2013/11/8 6:00～2013/11/8 9:40

Domain2・3

2013/11/8 6:00～2013/11/8 9:40

Domain1

GEBCO_08 Grid

Domain2

Chart

Domain3

The data which measured in 2014

Domain1

ASTER GDEM

Domain2

ASTER GDEM

Domain3

The data which measured in 2014

Domain1

Sea area：0.025

Land area：0.06

Domain2

Sea area：0.025

Land area：0.06

Domain3

Sea area：0.025

Land area：0.04

It was confirmed that there is a plan to construct
coastal embankments along the coastline of
Leyte Island in response to the damage from
Typhoon Haiyan. However the detail of theembankment in Tacloban downtown area has
not been decided yet.
35

The simulation incorporating the dyke
construction plan was performed with theassumption that a 2d-weir tide embankment
would be installed (Figure 2), and thereby theeffectiveness of the tide embankments as acoastal protection structure was evaluated.

A report states that evacuation activities
during when the water depth exceeds 0.3 [m/s]or when the water depth-velocity products
exceeds 0.6 [m/s2] would be likely difficult toperform with safety [Cox et al., 2010, Ministryof Land, Infrastructure and Transport, 2012].
Using the index of this report as a basis, the time
for people to safely travel to evacuation areasfrom each observation points was computed.
Calculation revealed that if the embankment was
raised, the margin for a safer evacuate could becreated at a linearly increasing trend. This is dueto the fact that for the case where there is noembankment, flooding in Tacloban City will
start soon after storm surge occurs. On the other
hand, for the case where there is theembankment, the arrival time of floodwater will
be delayed (Figure 5).

Figure 2. Calculation area of downtown Tacloban
and the assumed a thin weir along the coastline

4. Results
It was found that even if the embankment
height is raised, the inundation depth is not
linearly decreased. The water depth waschanging greatly depending on whether theembankment height is above or below the
maximum storm surge height (Table 2, Figure 3).
Simulation results of inundation depth
showed drastic changes if the water levelexceeds the 4.3m-high embankment, whereas
the inundation depth exhibited a constant depth
if the embankment height exceeds 4.9m (Figure
4).

Figure 5. Transition of the time when people haveto start their evacuations in downtown Tacloban

5. Conclusion
If embankments do not have a sufficientheight, a reduction effect on inundation depths
cannot be expected. Nonetheless, a marginaltime for enabling people to get themselves asafer evacuation can be created by constructing
the dykes along the coastline.

Table 2 Classifications of flood damage according
to water depth

References
1)Takagi, H., Esteban, M., 2015.：Statistics oftropical cyclone landfalls in the Philippines
unusual characteristics of 2013 Typhoon Haiyan.
Nat. Hazards.
2)Takagi H., Li S., de Leon M., Esteban M.,
Mikami T., Matsumaru R., Shibayama T.,
Nakamura R. (2016) Storm surge andevacuation in urban areas during the peak of astorm, Coastal Engineering.
3) Cox R.J., Shand T.D.,and Blacka M.J. (April2010)：Australian Rainfall & Runoff Revision
Projects Project10 Appropriate Safety Criteria
for People STAGE1 REPORT,19p.
4) 国 土 交 通 省 (Ministry of land,
Infrastructure and Transport, 2012)：津
波浸水想定の設定の手引き Ver.2.00,P45

Figure 3. Contour figure of water depth.

Figure 4.Distribution of the maximum water depth indowntown Tacloban, classified by dyke heights

36

A STUDY ON CONTINUITY OF UTILIZING A CLOSED SCHOOL FOR EXCHANGE FROM THE
VIEWPOINT OF TRAVEL INFLOW
Student Number: 11_18181 Name: Haruyoshi NAGAFUNE Supervisor: Naoya ABE

1 Introduction

over 65 years old”, “rate of population of primary industries”, “rate of forest area”, and “financial index”. Second, principal componentscores classify 207 zones by cluster analysis
under three regional groups: urban group,
middle group, and rural group. Urban grouphas 54 zones, middle group has 95 zones, andrural group has 58 zones.
207 zones are also classified by the relation
between a travel inflow zone and a top residence zone of travel inflow under three groups:“From urban zone inflow group (UIG)”, “Fromsimilar zone inflow group (SIG)”, and “Fromrural inflow group (RIG)” (Table.1). “From urban inflow group” has 109 zones, “From similar
inflow group” has 77 zones, and “From rural
inflow group” has 21 zones.
52 zones that belong to three metropolitan
areas and a center area of Hokkaido exclude
travel inflow from same that area. So, in 155
zones excluding 52 zones from 207 zones, I also
consider the relation between the amount of TI
and the number of UCSEs, UPY, and years of a
UCSE.

From 2002 to 2013, 2,208 public schools wereclosed and re-used for the other purposes except school. Many re-used schools are forneighbors, but Ministry of Education, culture,
sports, science and technology (MEXT) has recently introduce utilizing closed schools forexchange (UCSEs) (Fig.1), so I think the number of UCSEs will increase in the future.
Compare with utilizing closed schools for theother purposes, UCSEs have three features:
high repairing cost, highly dependence on
support from government and company, andmany users come from far. These three features
show that it is necessary to obtain consensus
from many stakeholders, so it is an important
problem to grasp the amount of travel inflow(TI) in the area of UCSEs.
In order to analyze continuity of UCSEs, I
classify regional zones as similarity and type of
TI, and consider the relation between theamount of TI and the number of UCSEs, users
per year (UPY), and years of a UCSE.

Table 1: The definition of type of travel inflow
From regional group (Top)
Urban

Middle

Rural

To

Urban

SIG

RIG

RIG

regional

Middle

UIG

SIG

RIG

group

Rural

UIG

UIG

SIG

Figure 1: One of the utilizing closed schools

3 Relations(Akitsuno Garten)

I confirm the correlation coefficient and thescatter diagram between TI and the number of
UCSEs, UPY, and years of a UCSE.
In the relation between TI and the numberof UCSEs, there are two weak correlations on“urban group in 207 zones” and “rural group in
155 zones”. In the scatter diagram (Fig.2), “rural group in 155 zones” has few unique zones

2 Classifications
At first, principal component analysis evaluate
207 zones by eight local indexes, which are“population”, “ratio of population increase”,“area”, “rate of under 15 years old”, “rate of37

Travel inflow (thousands)

The number of years of a
UCSE

far from coordinate origin and has many zones
near to coordinate origin.
In the relation between TI and the number
of UPY, there are three weak correlations on“urban group in 207 zones”, “from similar in
207 zones” and “from similar in 155 zones”. In
the scatter diagram (Fig.3), “from similar in
207 zones” has few unique zones far from coordinate origin and has many zones near to coordinate origin.
In the relation between TI and the numberof years of a UCSE, there are two correlations
on “urban group in 207 zones” and “urbangroup in 155 zones”, and four weak correlations
on “rural group in 207 zones”, “rural group in
155 zones”, “from similar in 207 zones” and“from similar in 155 zones”. In the scatter diagram (Fig.4), “urban group in 155 zones” has
one unique zone far from coordinate origin andhas the others close to each other.

50

Zones: 48

3

4

5

The number of UCSEs

The number of UPY

250

r = 0.380

100
50
0
0

Zones: 77

30

60

90

0

30

60

90

120

Travel inflow (Thousands)[1] 文 部 科 学省 , 廃 校施 設活 用 状 況実 態調 査 ,2014.
[2] MinistryofLand,
Infrastructure,
Transport and Tourism Government ofJapan, “2010 Inter-Regional Travel Survey
in Japan”, 2010.
[3] Hideki Nozawa, Gen Taniguchi, Kazuhisa
Tsunekawa, and Eisuke Tabata, “A Studyon The Feature of Regions that Have
Closed Public Schools and Reuse – In caseof Aichi, Gifu, and Mie prefecture -”

300

150

0

References

Figure 2: TI-No. Of UCSE scatter diagram onrural group in 155 zones.

200

10

This study has following conclusions.
In the two relations between TI and thenumber of utilized closed schools, and UPY,
there are a few weak correlations. In the scatter diagram which has the largest correlation,
there are few unique zones far from coordinate
origin and many zones near to coordinate
origin.
In the relation between TI and the numberof years of a UCSE, there are two correlations
and four weak correlations. In the scatter diagram which has the largest correlation, there is
one unique zone far from coordinate origin andare the others close to each other.

r = 0.261

2

r = 0.462

20

4 Conclusions

15

1

30

Figure 4: TI-No. Of YR Of UCSE scatter diagram on “urban group in 155 zones”

20

0

40

Zones: 28

25

10

50

120

Travel inflow (Thousands)

Figure 3: TI-No. Of UPY scatter diagram on“from similar in 207 zones”
38

Effects of AC voltage on Asymmetric Capacitor Thruster
Student number: 13-15496

Name: Shunnosuke Yamada

1.Introduction

Supervisor: Daisuke Akita

2. Asymmetric Capacitor Thruster

Titan is Saturn’s 6th satellite. Presence of somekind of life is expected on titan because of thefollowing factors. [1](1). Titan has dense atmosphere (about 1.5atm)
mainly consists of nitrogen and methane.
(2). Methaneis circulating like water on earth.
(3). There is ammonia water inside the crust.
We think Titan exploration is very important.
But Titan can’t be observed from an orbit due tomethane sol.[2] So we need send a spacecraft
inside Titan atmosphere. Figure 1 is a blimptype explorer proposed by NASA.The reasons to
use a blimp are as follows.
(1). Blimp can observe the atmosphere directly.
(2). Blimp is not affected by terrain, so it canwork also over the lakes.
(3). Titan has dense atmosphere.
We propose a blimp-type probe that is propelledby Asymmetric Capacitor Thruster (ACT)shown in Fig 2, because of the following reasonscompared with the propeller and the motor.
(1). Simple structure and easy to fold anddeploy.
(2). No driving part and high reliability.
(3). High thrust-to power ratio.

The asymmetric capacitor thruster is a simple
thruster, which consists only of hairline wire
and aluminum foil. [4] When a high DC voltage,say 10kV, is applied to the ACT of 20cm span,
the ACT produces a force of a few milli Newtons.
However, to get a sufficient force by the thruster,a high voltage power supply is required. In themost previous works, a DC voltage is applied to
the ACT. In this study, effects of AC voltage on
the ACT is investigated.

3. Experimental method
As shown in
Fig 3, the ACT for thisexperiment is composed of a thin wire electrode(anode) of copper and a planar electrode(cathode) of aluminum foil. The diameter of thewire is 0.05 mm, 0.2 mm, 0.5 mm. The width ofthe electrode is approximately 180 mm, thedistance between the electrodes is 12 mm and
20 mm. Table 1 shows the experimental
conditions.

Table1 Experimental conditions

AppliedVoltageFrequency
Electrodes
DistanceDC

AC(squarewave)

AC(sine
wave)

<15kV

<11kVp13.5kVp－
12 mm,
20 mm

4.3-20kHz
12 mm

5.5kHz
20 mm

The thrust is measured by electronic balance.
The experimental system is shown in Fig 4.

Figure 1 Blimp-type explorer proposed by NASA [3]Figure 3 Structure of AC
Figure 2 Blimp type explorer’s image

39

Figure 7 also shows the applied voltage andthe thrust. The wave shape of the applied AC
voltage is sine.Electrode distance is 20 mm.
The thrust in the case of AC applied is lower
than that of DC applied when the applied
voltage is evaluated as a RMS’s value.

Figure 4 Experimental system

4. Results

Figure 5 shows the applied voltage vs thethrust. Electrodes distance is 12 mm. The wave
shape of the applied AC voltage is square. DC
produces stronger thrust than that of AC. Highfrequency square wave produce stronger thrustthan that of low frequency square wave. Any
gradient in case of AC is lower than that of DC.

Figure 7 voltage vs thrust(sine wave)
5.Conclusions
In this study, the effects of AC voltage on
asymmetric capacitor thruster is investigatedto apply it for Titan exprolation.In all the casesof this experiment, the thrust is increased withthe applied voltages.Basically the thrust andthe thrust-to-power ratio in the case of AC islower than that of DC. Current in the case of
AC is higher than that of DC. The future work
is to investigate the effects of dielecrics aroundthe electrode in the case of AC.
Reference[1] Cassini Celebrates 10 Years Exploring
Saturn[https://www.nasa.gov/jpl/cassini/10-years20140625] access 2017/02/21[2] Kensei Kobayashi,2011“タイタンのアスト
ロバイオロジー探査“ 日本惑星科学会誌
Vol20,No.2[3] NASA Ames Research Center NASA Jet
Propulsion Laboratory[https://www.jpl.nasa.gov/missions/?type=future] access 2017/2/21[4] Francis X. Canning, Cory Melcher and
Edwin Winet, “Assymmetrical Capacitors
for Propulsion”, NASA/CR-2004213312,2004.

Figure 5 voltage vs thrust (square wave)
Figure 6 shows the voltage vs current in thesame case of Fig. 5. The current in the case of
AC-applied is higher than that of DC applied.
The current increases with the applied AC
frequency.

Figure 6 voltage vs current (square wave)

40

Outdoor-to-Indoor Radio Propagation Measurement by using an Unmanned Aerial Vehicle in
2.4GHz bandStudent Number: 13B11890

Name: Qiwei Fan Supervisor: Jun-ichi TAKADA, Kentaro SAITO

1 Introduction
Owing to the wide spread of smart phones and tablet
computers, the user traffic in mobile communication
systems is increasing rapidly. Especially, in the urban environments, it is a significant issue to accommodate many users in office buildings in the network.
Therefore, 3-dimensional(3D) service area planning is
recently investigated. 3D service area planning is amethod to achieve frequency reuse by arranging somemicro cell base stations. Therefore, we need to analyze the radio propagation characteristics in Outdoorto-Indoor(O2I) propagation scenario.
The O2I radio characteristics have been investigatedin [1] [2], and it showed that the dominant penetration loss was the shielding of Fresnel region andthe diffraction of waves by the window of building.
Therefore the spatial relation between the transmitter,and the window position is important to understandthe propagation
However, the variations of actual measurement settings are limited because transceiver is set on the
ground or on the floor of a building. Because surrounding environment and window position in highaltitude is totally different from that on the ground, we
use Unmanned Aerial Vehicle(UAV) to achieve highaltitude environment. Moreover, we can get propagation characteristic while changing the altitude of thetransmitter smoothly by using UAV.

Figure 1: UAV used in measurement

2.2

Transceiver and Measurement course

The transmitter and receiver is introduced in Section 2.1, the detailed information of transceivers are
summed up in Table 1
Table 1: Measurement parameters

2.1 Measurement System

item
Transmitter
ReceiverSoftware
UAV
Height of Receive Antenna
Carrier Frequency
measurement interval
Transmit Course
Receive Course (Distance from window)

The transmitter in the measurement was a WIMAX
Mobile router which was set on the plastic box under an UAV type DJI F550 with NAZA M V2, asshown in Fig.1. During the measurement of O2I radio propagation, the mobile router was placed outside
the building, which acted as the outdoor base station,and the receiver was a laptop with a USB dongle. The
receiver received Beacon signal which is a signal sent
by a wireless hardware regularly to all clients within
wireless network coverage and logged Received Signal Strength Indication(RSSI) data.

The measurement was conducted in the Suzukakedai
campus, Tokyo Institute of Technology, and measurement place was a lawn in front of a tall building. The
horizontal distances between the building and measurement points were 15m. p0 was the starting pointof the measurement as shown in Fig. 2. The distance
between subsequent points was 2m, p11 was the final
snapshot in which it was 22m away from p0.
The receiver was set on the 6th floor of the building,and outside the window there was a metal fence. The

2 Radio Propagation Measurement by using
UAV

41

detailpocket wifi WX02
FUJITSU laptop with IODATA WN-AC876U
Homedale
DJI F550 with NAZA M V2
1.6m (from 6th floor)
2.4GHzone data per second
p0-p11 (distance interval 2m)
Rx1(0.4m), Rx2(2.4m), Rx3(4.4m)

Figure 3: Excess loss of Rx1 in verticalFigure 2: Top view of course outside

receiver was placed at the distance of 0.4, 2.4, 4.4m
away from window which was denoted by Rx1, Rx2
and Rx3. The receiver antenna hight was 1.6m.
2.3 Process of the Measurement
We put the UAV on p0, and used the controller
to make UAV gain altitude. After the UAV height
reached 20m above the lawn, we lowered it down until it landed. During the measurement, we tried tomake UAV’s speed constant. After we finished measurement at p0, we moved UAV to next point, and repeated this process again. When finished measuringp11, we moved the receiver to the next position in order of Rx1, Rx2, Rx3. We took notes of the elapsed
time at three locations: (1) the starting point, (2) at the
maximum altitude, (3) the ending point.

Figure 4: Excess loss of Rx3 in verticalcess loss became higher as diffraction angle increased.

4

3 Results

Conclusion

In this thesis we introduced an O2I radio propagation
measurement system at 2.4 GHz band by using UAV.
The objective of this paper is to use the UAV to send
the signal at a high altitude. The result shows somecharacteristics of diffraction and penetration loss inmeasurement

In Fig. 3, and Fig. 4 , the vertical axis the excess loss
(which means the loss increased comparing to freespace loss), if it is close to 0dB, it means the propagation is almost the same as free space propagation.
The horizontal axis is altitude of UAV.
For Rx1 as shown in Fig. 3, there was a LOS(line-ofsight) while altitude was higher than 10m, and excess
loss increased about 5dB while transitioning to nonLOS(line-of-sight). Moreover, in non-LOS the excess
loss increased following the decrease of altitude.
For Rx3 as shown in Fig. 4, there was a LOS while
altitude was higher than 14m, and excess loss increased significantly while transitioning to non-LOS.
Excess loss in Rx3 is larger than that in Rx1, it can beconsidered as the increase of penetration loss following the increase of penetration distance.
The result is that, the excess loss increased whiletransitioning from LOS to non-LOS scenario, becauseof diffraction loss. In LOS case, the excess loss became higher as the penetration distance increases because of penetration loss. In the case of non-LOS, ex-

References[1] H. Omote, M. Miyashita ”Analysis of Arrival Angle Characteristics between Indoors of Difference LOS Buildings inMobile Communications” , IEICE Society Conference, B1-6, Sept.2016[2] R. Eguchi, D. Furuishi, S. Araki, S. Ichitsubo, ”Frequency
Characteristics of Penetration Loss Caused by Window”,
IEICE Society Conference, B-1-8, Sept.2016

42

改良さ れた ク ラ ス タ リ ン グに よ る ウ ェ ーブレ ッ ト 画像符号化の線形予測
学籍番号:13 16165

名前:李

然

指導教員:山下

幸彦

はじ めに

1

Algorithm 1 k-means ア ルゴリ ズム
ラ ン ダム に k 個の点を 選んで， 中心点初期値と する 。
離散ウ ェ ーブレ ッ ト 変換（ DWT） は， データ や関数
repeatな ど を 異な る 周波数成分に分解する ための方法の一つで1. データ セ ッ ト の各データ を 最も 近い中心点のクある 。 ウ ェ ーブレ ッ ト 画像符号化は， DWT を 用いる 画
ラ ス タ に 割り 当て て ， k 個のク ラ ス タ を 形成する 。
像符号化の方法で， 変換係数を 算出する こ と でデータ 圧
2. 新し く 割り 振ら れた ク ラ ス タ から 中心点を 再計
縮を 実現し て いる [1][2]。 予測符号化は， 予測を 利用し算する 。
て データ 圧縮を 行う 手法である 。 こ の研究では， 予測符
until 中心点が変化し な く な る 。
号化で利用する k-means の計算時間や初期値問題を 解決する た めに ， 従来の k-means の代わり に ， 最近注目

2.3

さ れて いる k-means++[3] を 用い， 更に交差検定に基づ
く アルゴリ ズム でデータ セッ ト に合う ク ラ スタ 数を 算出

こ の研究では， 画像の特徴値を 抽出し ， k-means でク

し ， 時間削減と 予測精度の向上を 試みる 。

2

ク ラ ス タ リ ン グ によ る 線形予測

2.1

線形予測

ク ラ スタ リ ン グによ る 線形予測

ラ ス タ リ ン グし , カ テ ゴ リ ー Ωc (c = 1, 2, ..., C) に 作成
する . Ωc に 対する 予測モデルは以下の通り である 。

q = hac , vi ,こ こ で ac は線形予測の係数ベク ト ルである 。 学習デー

元々 の線形予測は以下の式で表さ れる 。

ŝ(n) =pX

ai s(n − i),(4)

タ vi と qi (i = 1, 2, ..., Nc ) は Ωc に 属し ， ac はク ラ ス
タ 内の平均予測誤差

(1)

Nc
X

i=1

ŝ(n) は実際の信号 s(n) の p 個の信号値の 係数 ai の線|qi − hac , vi i |2 .

(5)

i=1

型結合によ る 予測値である 。 予測値と 実際値の差で生じを 最小に する よ う に 決める 。

た誤差 e(n) は次の式で表さ れる 。

e(n) = s(n) − ŝ(n)= s(n) −pXai s(n − i),(2)3k-means ++と ク ラ スタ リ ン グの改良

3.1

k-means++法

i=1

線形予測係数 ai は, 次の平均予測誤差XE=
e2 (n).

(3)nk-means++法によ り ， ク ラ スタ リ ン グの時間短縮と ク
ラ ス タ 構成の安定化が可能に な る 。 D(x) は各データ 点を 最小に する よ う に 決める 。

から 最も 近い既存のク ラ ス タ 中心と の距離と 定義する 。

2.2

k-means ク ラ スタ リ ン グ

本論文の実験では， 客観的にク ラ スタ 数を 評価する ために， ラ ン ダム要素を 取り 除く 必要性があり ， k-means++
k-means ク ラ ス タ リ ン グは n 個のデータ を 距離に 基法の最初の中心点を データ 数 n を ク ラ スタ 数 k で割っ たづき k 個のク ラ スタ に分類する 方法である 。 こ の実験で nk の整数部分番目のデータ に 固定する 。 k-means++のは， そ の距離に ユーク リ ッ ド 距離を 用いる 。
ア ルゴリ ズム を 以下に 示す。
こ こ で (x1 , x2 , ..., xn ) を データ セッ ト と し ， それぞれのデータ は d-次元の実数ベク ト ルと する 。 k-means のア ルゴリ ズム は以下の通り である 。
43

Algorithm 2 k-means++ ア ルゴリ ズム
ラ ン ダム に 最初の中心点 c1 を X から 選出する 。
repeat
次の中心点 ci は，する 。

表 1: RM SEk の比較 (括弧中の数はク ラ ス タ 数)
実験データ
提案法 (104) 従来法 (64) 従来法 (128)′ 2′
P D(x )
2 を 最大に する x とx∈X D(x)Intersection

9.22

9.67

9.61

Lenna

5.79

6.02

6.30

Barbara

21.30

21.95

22.47

until k 個の中心点が選出さ れる 。
普通の k-means 法でク ラ ス タ リ ン グを 行う 。

た 。 従来手法のク ラ ス タ 数を そ の両側の 64 と 128 と す

3.2

る 。 なお， RMSE は小さ いほど 精度が高いこ と を 意味す

改良さ れたク ラ スタ リ ン グ法る 。 実験結果から ， 本研究の方法で， 予測精度の向上や
ク ラ スタ リ ン グに必要な 時間の短縮， ループ数の消減を

k-means 法の最大の問題点は， ク ラ スタ 数 k を 事前に実現し た。

決めな け ればな ら な いこ と である 。 特に本実験では， ク
ラ スタ 数は線形予測の精度に甚大な 影響を 及ぼす。 こ こ

表 2: ク ラ ス タ リ ン グ時間
手法＼ク ラ ス タ 数
64104で， ク ラ スタ リ ン グ法を 改良する ために， 予め用意さ れた複数の学習画像データ を 使い予測し ， 予測データ と 元

128

データ を 比較する こ と で学習データ に対し て 一番適切なk-means 法

2789.79s

4895.63s

7416.46s

ク ラ ス タ 数を 推定する 。 ク ラ ス タ 数 k の取り 得る 範囲

提案法1372.79s

3156.13s

5951.62s

を {kmin , kmax } と し ， m 個の学習画像データ を 合わせたデータ セッ ト を 二組に 分け、 そ の中で N1 を ク ラ ス タ
リ ン グで利用する データ セ ッ ト と し ， N2 を 線形予測用

表 3: ク ラ ス タ リ ン グ計算に 必要な ループ数
手法＼ク ラ ス タ 数
64
104
128

データ と する 。 最良ク ラ ス タ 数を kbest と 記す。 ア ルゴ
リ ズム は以下の通り である 。

k-means 法

795

965

1075

提案法

331

589

801

Algorithm 3 線形予測に よ る 最良ク ラ ス タ 数の推定
最初のク ラ ス タ 数 k は kmin から 始める 。
repeat1. 普通の k-means++法で N1 を ク ラ ス タ リ ン グ
する 。

5

結論
本研究では， ウ ェ ーブレ ッ ト 画像符号化の線形予測の

2. N1 のク ラ スタ リ ン グ結果で算出し た係数で線形予測用データ N2 を 予測する 。

ためのク ラ スタ リ ン グの改良方法を 提案し た。 実験の結3. 予測結果から ク ラ ス タ 数 k ごと に 平均平方二乗 果， 予測精度の向上と と も に , ク ラ ス タ リ ン グに 必要な時間と ループ数も 短縮でき た。 し かし ， 最良ク ラ スタ 数
誤差 RM SEk を 計算する 。
の算出には， ある 範囲内のク ラ スタ 数の予測誤差を 調べ
4. k = k + 1。
尽く す必要があり ， そのため大量な 時間が必要で， アルuntil ク ラ スタ 数 k が 最大ク ラ スタ 数 kmax に達する 。

ゴリ ズム のさ ら な る 高速化が今後の課題である 。

RM SEk が最小値と な る k を kbest と する 。

参考文献

4

実験結果

[1] Marc Antonini, Michel Barlaud, Pierre Mathieu and Ingrid Daubechies, ”Image Coding Using

今回の実験は画像電子学会が頒布し た JIS X 9201:1995
自然画像から 8 つ の画像データ を 学習データ と し ， そWavelet Transform”, IEEE Transactions on Image
Processing, Vol. 1, No. 2, April 1992.

の中の一番目の画像データ を ク ラ ス タ リ ン グ用データ[2] Dan Wang, Yukihiko Yamashita, ”Wavelet BasedN1 と し 、 他の画像データ を 線形予測用データ N2 と す
る 。 そし て 、 予め用意し た別の画像データ (Intersection,

Image Coding via Linear Prediction and Improved
Clustering”, Master Thesis, Jan 2017.

Lenna, Barbara) を テス ト データ と する 。 従来の方法とク ラ スタ 数と RM SEk と 比較し ながら ， ク ラ スタ リ ン グ[3] D.Arthur, S.Vassilvitskii, ”k-means++: The Ad-「 高精細カ ラ ーディ ジタ ル標準画像 (CMYK/SCID)」 のvantages of Careful Seeding”, Stanford University,
2007.

に必要な 時間と 計算ループ数も 測定する 。 今回のデータ
セ ッ ト で算出さ れた 最良ク ラ ス タ 数 kbest は 104 と な っ44Pretreatment of Feed Oil for Biodiesel Fuel Production
Student ID:13B16171

Name: Zhuoheng LI

Supervisor: Ryuichi EGASHIRA, Hiroaki HABAKI
aqueous phase.

1. Introduction
Biodiesel fuel is a kind of alternative diesel fuels and madefrom renewable biological sources such as vegetable oils andanimal fats. Although biodiesel fuel has attracted much attention
as environmentally friendly fuel, it is difficult to be popularized
due to the high cost of the feed oil and the limitation on feed
supply. The cost of feed oil frequently shares more than 80 % of
its total production cost, and then, low quality feed oils, such as
crude plant oils, used frying oil and so on, have come into
utilization, which generally contain some impurities, such as
phospholipids, free fatty acids (FFA), and so on. The impurities
reduce biodiesel fuel product yields and contaminate biodiesel
fuel products. Therefore, the removal of phospholipids and freefatty acid from feed oil before transesterification is so importantas the feed pretreatments(FP). Whereas the ordinary method to
remove phospholipids in the feed oil by sulfuric acid solution
and water washing was inefficient to remove FFA, the removalof FFA with sodium hydroxide solution could separate FFA andsome parts of phospholipids simultaneously1). On the other hand,
the removal of FFA by sulfuric acid and menthol has
inadequately been studied on the removal of phospholipids.
In this dissertation, the simultaneous separation of thephospholipids and FFA was studied in terms of the phospholipid
reduction and yield of the treated oil.

2.2.2 Sodium hydroxide solution treatment
The experimental conditions of sodium hydroxide solution
treatment (treatment 2) were summarized in Table 23-6). The
neutralization of FFA to form soap by sodium hydroxide solution
was expressed as the following reaction.
RCOOH(org) + NaOH(aq) ⇄ RCOONa(aq) + H2O(1)
The mass fraction of phosphorous of phospholipid in the feed oil
was adjusted to 0 or 0.001, and the mass fraction of FFA in feed
oil was adjusted to 0.15. The specified amounts of feed oil andsodium hydroxide solution were contacted in flask with amagnetic stirrer in the temperature-controlled water bath. Aftercompleting reaction, the mixture was separated into the aqueousand organic phases by centrifuge. The obtained aqueous phases
also were analyzed by ICP-AES to determine the mass fractionof phosphorous in aqueous phase. This method should require nowater washing to remove sodium hydroxide because sodiumhydroxide generally was used as alkali catalyst intransesterification reaction for biodiesel production,
Table 2 Experiment conditions
Feed oil
Phosphorous/Feed oil mass fraction[-] 0.001; 0
FFA/Feed oil mass fraction[-]
0.15
Sodium hydrate solution treatment
NaOH/H2O solution mass fraction[-]
0.095
NaOH aq/Oil molar fraction[-]
1.15
Reaction temperature[k]353Reaction time[h]0.083

2. Experimental
2.1 Feed oil
Triolein (C18:0) was selected as the major component in feed
oil because it was a major component in the vegetable oils
generally used for biodiesel fuel production. Oleic acid andlecithin were added as impurities as model FFA andphospholipids, respectively. Generally, two types ofphospholipids are contained in the plant feed oils, such as
hydratable and non-hydratable phospholipids. Lecithin is one ofthe plant-derived phospholipids, which include both hydratable
phospholipids,
suchasphosphatidylcholine
andphosphatidylinositol, and non-hydratable one such as
phosphatidylethanolamine, respectively.

2.2.3 Sulfuric acid and methanol treatment with water washing
The experimental conditions of sulfuric acid and methanol
treatment with water washing (treatment 3) were summarized inTable 33-6). The esterification of FFA into fatty acid methyl ester(FAME) by methanol with catalyst of sulfuric acid was
expressed as the following reaction.
H2SO4

RCOOH(org) + CH3OH(aq) ⇄ RCOOCH3(org) + H2O(2)
The composition of the feed oil was the same as in the cases oftreatment 2. The specified amounts of feed oil, concentrated
sulfuric acid and methanol were contacted and the reaction was
carried out in a two-necked flask, which was equipped with
reflux condenser, and temperature-controlled water bath. After
esterification, the water washing should be required to remove
sulfuric acid because sulfuric acid may neutralize the alkali
catalyst in transesterification. The water washing with a
specified amount of water was repeated twice. The aqueous andorganic phases also were separated by centrifuge after thetreatment. The obtained aqueous phases also were analyzed by
ICP-AES to determine the mass fraction of phosphorous inaqueous phase.

2.2 Feed oil treatment methods
2.2.1 Sulfuric acid solution treatment with water washing
The experimental conditions of sulfuric acid solution
treatment with water washing (treatment 1) were summarized inTable 11-3).
Table 1 Experimental conditions
Feed oil
Phosphorous/Feed oil mass fraction[-]0.001
Sulfuric acid solution treatment
H2SO4/H2O solution mass fraction[-]0.25; 0.4
H2SO4 aq/Oil mass fraction[-]0.0008; 0.001
Reaction temperature[k]343Reaction time[h]0.33Water washing
H2O/Oil mass ratio[-]
0.1
Reaction temperature[k]343Reaction time[h]0.33Table 3 Experiment conditions
Feed oil
Phosphorous/Triolein mass fraction[-] 0.001; 0
FFA/ Triolein mass fraction[-]
0.15
Sulfuric acid and methanol treatment
MeOH/Oil molar ratio[-]
7.5
H2SO4/Oil mass fraction[-]0.03
Reaction temperature[k]333Reaction time[h]1.5
Water washing
H2O/Oil mass ratio[-]
1.5
Reaction temperature[k]333Reaction time[h]0.33

The initial mass fraction of phosphorous of phospholipid in
the feed oil was adjusted to 0.001. Sulfuric acid was used as
catalyst to convert non-hydratable phospholipids into hydratableones. The reaction was carried out in flask with a magnetic stirrer,
with temperature-controlled water bath. The feed oils weremixed with sulfuric acid and kept at 343K for 0.33 hour. Afterreaction, the hydratable phospholipids were removed byrepeating water washing with a specified amount of water for
total five times. After each water washing, the mixture wasseparated by centrifuge to obtain the aqueous and organic phases.
Then the aqueous phases after each separation were analyzed by
ICP-AES (SPS 7800, Seiko Instruments Co. Ltd.) for
determination of the mass fraction of phosphorous in the

3. Results and Discussion
3.1 Definitions of yields
The fractional removal of phosphorous after k-th time water
washing from the aqueous phases by j operation, YP,j,k, was45

defined as,

methanol treatment and with water washing, treatment 3. In allcases, white colored high-viscous substance was obtained. The
phospholipids should work as surfactant and some emulsion
might be generated. For both cases, YP,j,k increased with Waq,j,k.
In the case of treatment 2, the aqueous solution of sodiumhydroxide could extract phospholipid compounds and YP,j,k
increased less than 0.82. The mass fractions of phosphorous in
the feed oils could be reduced to 0.00018, and still some part ofnon-hydratable phospholipids might have remained in theorganic phase. In the case of treatment 3, YP,j,k attained more than
0.93 at the first time water washing, and YP,j,k raised to 0.99 at thesecond water washing. It meant that treatment 3 could favorably
reduce the phospholipid even if FFA and methanol existed in thesystem. The mass fraction of phosphorous in the organic phase
after water washing could be reduced to 0.00001.

k

YP, j ,k = ∑M aq, j ,l yP, j ,l M org, j ,F xP, j ,F

(3)

l =1

Here, Morg,j,F, xP,j,F, Maq,j,l and yP,j,l indicate the mass of feed oil,mass fraction of phosphorous in the feed oil, mass of the aqueous
phase obtained at the k-th time water washing and mass fractionof phosphorous in the k-th aqueous phase, respectively. The j
stands for the operation of three types treatment methods.
The total mass of obtained aqueous phase until k-th treatment
was defined as,

Waq, j ,k Maq, j , k(4)Here Maq,j,k means the mass of the aqueous phase obtained at thek-th time washing treatment. The j stands for the operation of
three types treatment methods.
The yield of the organic phase by those three types treatment
methods was defined as Yorg,j.

Yorg,j  M org,j M org,F

3.3 Comparison of organic phase yields
Table 4 shows the comparison of Yorg,js by three kinds oftreatment methods. In the case of treatment 1, Yorg,1 increased as
the concentration of sulfuric acid used. The Yorg,js were larger
with the treatment 3 than those with treatment 2. Sodiumhydroxide should react with FFA to be removed as soap. On theother hand, treatment 3 should convert FFA to FAME, to keep
higher Yorg,j than treatment 2. With the feed oils containing
phospholipids, Yorg,js decreased for both cases because
emulsification of the oil phase should be enhanced, as mentioned
above, and the effects of the emulsification must be larger withtreatment 2. Accordingly, FFA and phospholipid could be
removed simultaneously by treatment 3 in the feed pretreatment
with higher oil yield. Thus, this method might have possibility
to simplify the feed pretreatment process. The treatment 3 might
keep the final biodiesel fuel yield high even if the crude plantoils containing phospholipid and FFA by higher level.

(5)

Here Morg,j, Morg,F means the mass of the organic phase obtained
after j operation and the mass of feed oil. The j stands for theoperation of three types treatment methods.
3.2 Removal of phospholipid by different treatment methods

Table 4 Comparison of organic phase yields
Treatment methods

H2SO4/H2O solution
mass fraction [-]Sulfuric acid solution
treatment withwater washing(treatment 1)

0.40

Sodium hydroxide
solution treatment(treatment 2)

Figure 1 shows the plots of YP,j,k against Waq,j,k in the case of
sulfuric acid solution treatment with water washing, treatment 1.
The YP,j,k increased as Waq,j,k. When water containing no sulfuric
acid was used, YP,j,k was more than 0.55 at the first time water
washing and raised to 0.75 after total five time operations. The
YP,j,k with sulfuric acid solution of 0.25 mass frac. was almost
same as that with water washing. The treatment with sulfuric
acid of 0.4 mass frac. enhanced YP,j,k significantly, and YP,j,k was
0.85 after first time water washing and raised to 0.99. The higher
sulfuric acid treatment should effectively convert nonhydratable phospholipids into hydratable ones to enhance YP,j,k,
after water washing the mass fractions of phosphorous in organic
phase could be reduced to 0.00001

Sulfuric acid andmethanol treatment withwater washing(treatment 3)

H2SO4(aq)/Oilmass fraction [-]Phosphorous/Feed oilmass fraction [-]Organic phaseyields [-]

0

-

0.001

0.68

0.25

0.0008

0.001

0.69

0.001

0.001

0.72

0

0.61

0.001

0.41

0

0.93

0.001

0.76

0

≥ 0.98-0.03

4. Conclusion
The treatment of feed oil to remove phospholipid and freefatty acid was studied. In the case of sulfuric acid and methanol
treatment with water washing, the sulfuric acid could effectively
convert non-hydratable phospholipids into hydratable ones. This
treatment could improve the phospholipid removal, even if freefatty acid and methanol existed in the system. Furthermore, thistreatment attainted higher fractional yield of the feed oil.
Therefore, this treatment could be expected to remove
phospholipids and free fatty acids simultaneously with thehigher yield of the biodiesel fuel product.

Literature Cited[1] Sinthupinyo Patima “Comparative Study of Biodiesel Production by
Alkaline Transesterification from Low- valued Feed” Master Thesis, Tokyo
Tech (2007)[2] K. T. Liu, S. Gao, T. W. Chung, C. M. Huang, Y. S. Lin “Effects of process
conditions on the removal of phospholipids from Jatropha curas oil during thedegumming process” Chemical Engineering Research and design, 90 (2012)
1381-1386[3] Hayashi Tomoki “Effects of Operating Conditions in Biodiesel Fuel
Production from Low-valued Feed” Bachelor Thesis, Tokyo Tech (2008)[4]-B. Freedman, E. H. Pryde, T. L. Mounts, “Variables Affecting the Yieldsof Fatty Esters from Transesterified Vegetable Oils.” J. Am. Oil Chem. Soc.,
61, (10), 1638-1643, (1984)[5]-G. Vicente et al. “Integrated biodiesel production: a comparison ofdifferent homogeneous catalysts systems” Bioresource Technology, 92, 297305, (2004)[6]-G. Vincente et al. “Optimization of integrated biodiesel production.”
Bioresource Technology, 98, 1724-1733, (2007)

Figure 2. The effects of Sodium hydrate solution treatment method andsulphuric acid and methanol treatment with water wash method on YP,j,k [-]Figure 2 shows the plots of YP,j,k against Waq,j,k during sodiumhydroxide solution treatment, treatment 2, and sulfuric acid and46

Effects on landing aircrafts by wind around the hangars
at Haneda Airport
Student number : 13_14746 Name : Yuhei Morita

Supervisor : Daisuke Akita

1. Introduction

At Haneda Airport in Tokyo , there’re four
runways. At near the edge of one runway offour, four hangers are placed in parallel to therunway. When wind is going over the hangers,
it can be stirred and after that, it can affect toaircrafts which is landing at the runway.
Details of disposition of these buildings areshown in Fig.1.

Figure 3 Simulation model

3. Results
Although the flow must be turbulent
considering the Re number, turbulence models
are not used in this simulation.
Figure 4 shows a velocity distribution at 15m
high.

Figure 1 Disposition of hangers and runway

Figure 2 shows the details the touchdown
point on the runway and the route of landing
aircrafts.

Figure 4 Velocity distribution

In Fig.4, the angle between the wind and the
runway is 90°. The table 1 shows the windparameters used in the simulation.
Table 1 Parameters

Figure 2 Touchdown point and the route of landing
aircrafts

wind direction
wind velocity
45 deg 90 deg 5m/s 10m/s 15m/s 20m/s

In this paper, I investigate the effects onlanding aircrafts caused by the wind going overthe hangars. In order to simulate the flow fieldaround the hangar, a open source CFD software
called OpenFOAM was used. The validation of
the CFD method was performed throughsimulations of flow field around a cylinder.

The effect on the landing aircraft by wind isevaluated with the following equation [1].
∆𝐿𝐿

2. Simulation Model

=−

2
𝑉𝑎








Figure 3 shows the simulation model.

47

∆𝑢 +

1
𝑉𝐺

∙

1
𝐶𝐿

∙

𝜕𝐶𝐿
𝜕𝛼

∙ ∆w ・・・(3.1)

L: Lift
Va , VG : airspeed, ground speed∆u: a change of tail wind
∆w: a change of vertical wind
CL : coefficient of lift
α: angle of attack

60
50
40
30
20
10
0
-10
-20
-30
-40
-50

20
15
10
5
0
-5
-10
-15
-20
-25
-30

5m/s

10m
/s
15m
/s

0

300

600

900

15m/
s 90°
20m/
s 90°
5m/s
45°
Hangar

0

300

600

900

1200

When the wind velocity is 20m/s, and the
direction is 90°, passengers can feel the
maximum acceleration.
Both maximum and minimum of a change of alift is shown in figure7. The duration is from0[s] to 3000[s]. The wind velocity is 5 m/s andwind direction is 90deg.

Figure 5 Lift change along aircrafts trajectory

In Fig 5, the change in lift increases with thevelocity. Even when the velocity is 5m/s, thelift seems to be drastically changed.
Figure 6 shows the comparison of the winddirection.

15
10

20
15
10
5
0
-5
-10
-15
-20

10m/
s 45°

Figure 7 change of acceleration

1200

Horizontal distance from a point oftouchdown[m]

5m/s
90°

a changeof lift[%]a change of lift[%]

10m/
s 90°

horizontal distance from a point oftouchdown[m]20m/sHangar5m/s
90°change ofaccerelation[%]a changeof lift[%]

Figure 5 shows a change in lift force along the
trajectory of aircrafts. The wind direction is 90
deg to the runway in Fig 5.

5m/s
45°

maxi
mum

5
0

minim
um

-5
-10

10m/s
90°

-15
Hangar

0

300

600

900

0

10m/s
45°

horizontal distance from a point oftouchdown[m]

1200

600

Till an aircraft reaches at the edge of the
runway, a change of lift can be decreased at any
time. But after passing at the edge of the
runway, lift can be increased.

In Figure6, when the angle is not 90°, achange of lift just before touchdown can belower than zero. It means it must be moredangerous because decreasing lift may lead anairplane to touchdown strongly, unsafely.
A change of vertical component of acceleration
was calculated using the following equation[2].







400

Figure 8 a change of lift

Figure 6 Effect of wind direction

∆n =

200

horizontal distance from a point of touchdown[m]4. Conclusion
In this study, the wind flow field around the
hangars was simulated to investigate its effects
on landing aircrafts. The effect on landing
aircrafts is evaluated by change in lift force of
the aircrafts using the simulation results.
Although the hangars are distant from therunway, the lift force of the aircrafts is affectedby the wind behind the hangars. The
touchdown point should be changed for safe
aircrafts operation.

ρVCLα
× ∆w・・・(3.2)
2(W⁄S)

ρ: density of atmosphere[kg⁄m3]
V: ground speed[m⁄s]CLα : lift slope
W⁄S : wing loading[kg⁄m2 ]∆w: a change of vertical velocity[m⁄s]Reference

This change of acceleration stands for how
much passengers can feel the change of lift.
Figure 6 shows the results.

[1] Akira Nakayama, Humio Watanabe, 1981年5月12日に羽田空港に発生したLaw Altitude Wind Shear(LAWS)の解析, 1987
[2] JAPAN AIRCRAFTS ASSOCIATION
https://www.japa.or.jp/wp-content/uploads/2016/05/2010no4.p
df#search=%27%E6%8F%9A%E5%8A%9B%E5%A4%89%
E5%8C%96+%E4%B9%99%E5%AE%A2%27 17/07/201748

Effects of electrode tip curvature and distance between
electrodes on electric fieldStudent number: 12B11325

Student name: Gota Nurishi

1. Introduction

Supervisor: Kunio Takahashi

constant and there is no electric field distribution inside theElectrical breakdown can occur and current can flow

surface. Considering symmetry between anode and cathode,𝑉potentials at anode and cathode are set toThis is called discharge phenomenon. Arc welding and argon

respectively. Electric field in each point of the surface is inplasma therapy are very famous application examples. It is

proportion to voltage under the condition that both electrodeknown that electrode tip curvature greatly effects on electrical

tip curvature and distance between electrodes are constant.

breakdown [1].

So effects of electrode tip curvature and distance between

The problem is that the way to calculate electric field isn’t

2

and −

𝑉

through the air if large voltage is applied between electrodes.

2,electrodes on electric field should be tested with voltage fixed.

accurate although electric field greatly effects on electrical

3. Procedure to calculate electric field

breakdown. Electric field isn’t always equal to voltage over

2N lattice points are arranged on the surface of electrodes ―distance between electrodes. Therefore, charge density on the

Each of anode and cathode has N lattice points. As Fig.2

surface of electrode should be calculated.

shows, (N―5) lattice points are arranged on each curve, but

2. Model treated in this research

the closer to electrode tip, at shorter intervals lattice points

Two parabola-shaped electrodes shown in Fig.1 are treated

are required. On straight lines which correspond to cutting
planes, 5 lattice points each are arranged. N is set to 50 in thisin this research.

research.
[mm]

300 q50 q49 q48 q47 q46
200
100
-10

-q1 -q

0

2

-q3

-100
-10.004

-200
-q4

-300

Fig.1 Model of electrodes-10.008

The electrodes for anode and cathode have a same material
and form. The surface and the interior of them are seen as

0

0.1

0.2

0 10 20 30 [mm]Fig.2 lattice points plotting ― In case that distance between

conductors, so potential on the surface of each electrode iselectrodes is 20mm and radius of curvature is 2mm―

49

Normalized electric field distribution on neutral axis [V/d]Electric field is equal to charge density over permittivity oneach point of surface, so electric field will be clear if charge
density is calculated on each point of surface. Charge density
everywhere can be calculated by using BEM(boundary
element method) and considering that potential on the𝑉surface of each electrode is constant( everywhere at anode,2𝑉and − everywhere at cathode) [2]. Electric field not only on
2

𝑑

𝑑

2

2

electrodes but also on neutral axis(− < 𝑧 < , 𝑟 = 0) will be4

R=0.1dR=0.2dR=0.5d
R=d
R=2d
R=5d
R=10d

3.5
3
2.5
2
1.5
1
0.5

0

0.1

0.2

0.3

0.4

0.5

Normalized vertical displacement from symmetry plane [d]clear if charge density is calculated on each point of surface.
Superposition principle of coulomb’s law enables to solve

1.2electric field distribution on neutral axis easily [3].

1.1
1

4. Simulation Result
2 kinds of diagrams are shown below. Voltage is 1[V].The

0.9

ratio of ‘radius of electrode tip curvature’ (R) to ‘distanceFig.4 Diagram of electric field distribution on neutral axis

between electrodes’ (d) greatly effects on electric field. The

d is fixed in Fig.4. In case that R is small, electric field nearintensity of electric field itself isn’t so significant.

the tip (z≒0.5d) is much bigger than it on symmetry plane. In

0

0.1

0.2

0.3

0.4

0.5

case that R is big enough, electric field is almost constant withrespect to displacement.

5. Conclusion
The ratio of radius of electric tip curvature to distance
between electrodes greatly effects on electric field distribution.
The intensity of electric field can’t be defined as voltage overdistance between electrodes unless radius of electrode tip
Fig.3 The ratio of charge density to electrode tip

curvature is sufficiently bigger than distance between

R is fixed in Fig.3. The smaller d is, the easier it is that theelectrodes. In case that distance between electrodes is bigger

ratio of charge density to the tip decreases with respect tothan radius of electrode tip curvature, electrical breakdown

displacement as Fig.3 shows. Whether d is big or small,doesn’t always occur at electrode tip.

charge density at the place horizontally more than 2R away

6. Reference

from electrode tip is sufficiently smaller than that at the tip.

[1] Japan Welding Society, Vol.12, No.4, 1994 “Phenomena of micro-discharge
across the gap of sub-micrometer” by Hiroshi Maruo, Yoshinori Hirata andKimihiro Ozaki[2] Journal of applied physics, Vol.90, No.1, 2001 “Voltage required todetach an adhered particle by Coulomb interaction for micromanipulation”
Kunio Takahashi, Hideaki Kajihara, Masataka Urago, Shigeki Saito,
Yoshihiro Mochimaru, and Tadao Onzawa[3] “電磁気学” by 浅田雅洋 and 平野拓一

50

財務的内部収益率から見た大型ショッピングモールにおける太陽光発電システムの導入可能性：上海（中国）を事例として
学籍番号：13_05322

氏名：顧

1. はじめに

任遠

指導教官：阿部直也

上海（中国）において、太陽光発電システムを設置「パリ協定」の採択でエネルギー構造の調整が中国しようとする事業者が、所定の条件を満たした場合、受の一大課題となっていた。その中の一つとしては 1950
年代から発展し始まった中国太陽光発電事業であり，近け取ることができる補助金制度は表 2 の通りである。
表 2 上海（中国）における太陽光発電システム設置に

年都市部における太陽光発電システム設置の推進も始ま対する補助金制度(単位：RMB/kWh)っていた。しかしながら，都市部における太陽光発電シ
ステムの設置は場所がないという問題が残されていた。
そこで政府が分散型太陽光発電システム(電力需要側が中央政府から

地方政府から

最大合計

0.42

0.25

0.67

2-2. 日本のショッピングモールにおける太陽光発電

建設し，電圧レベル 35kV かつ容量 6MW 以下であり，自システム普及の実態

己消費を主とする同時に余剰電力を地域ネットワークに本研究では、日本におけるショッピングモールにお輸送する太陽光発電システムが分散型に分類すると中国

ける太陽光発電システム普及の背景を理解するため、関国家電網会社が定義している)の推進を国戦略として提連資料の収集とヒアリング調査を行った（I-M 社を訪問

示し，都市部における太陽光発電の推進を図った。

してヒアリング調査を行った、2017 年）。その結果、ま太陽光発電システムの設置候補施設の中で、日射量ず日本の立地する全 147 箇所のショッピングモールでを確保しやすい屋上面積が広く、自己消費電力量が比較

は、71 箇所が容量太陽光発電システムの設置が行われて的多いショッピングモールは、発電設備の設置施設としいることを確認した。設置の際、どのような基準に基づて望ましい条件を有していると思われる。しかし、中国において、現時点では、分散型太陽光発電システムを設きシステムの設置を判断するのか、I-M 社の担当者に確置しているショッピングモールの事例が大変限られてい否かによって判断しているとのことであったが、特に同る。そこで、本研究は、発電及び施設設置のために比較的好条件を兼ね備える施設と想定されるショッピングモ

社はグループ会社全体として、環境に配慮するポリシーを明確に掲げているため、その点もシステム導入を決めールに分散型太陽光発電システムの設置が必ずしも進んる大きな要因となっていることが確認された。また、政でいない背景を、(1)投資の収益性という観点と(2)日本

策的要因、すなわち、補助金の有無は収益性を大きく左におけるショッピングモールにおける同システムの設置右するため、結果的に政策面の動向も大きく導入を決め方針と比較して検討することを目的とした。具体的にる際に影響を及ぼしていることが確認された。

認したところ、基本的には財務的収益性を確保できるか

は、設備設置を投資とみなし、その財務的内部収益率の視点から，検討を行う。

3. 財務的内部収益率
企業は投資プロジェクトを遂行するか否かを意思決

2. ショッピングモールにおける太陽光発電シ定するために使われる評価指標の一つは、プロジェクト

ステム普及の実態がもたらす費用と便益の時間価値に基づき計算する内部

2-1. 上海（中国）における太陽光発電システム普及

収益率である。内部収益率は、社会的費用と便益も計算の実態と関連制度に入れる経済的内部収益率と純粋にプロジェクトの投資

本研究が着目している上海における太陽光発電シス

費用と収益を計算する財務的内部収益率がある。本論でテムの累積設置容量は確認できなかったが，2016 年に補は，財務的内部収益率を適用した。

助金を受けて設置されたシステムの建設状況は表１の通内部収益率の具体的な概念と算出手順は以下の通りりである。同表からわかる通り、ショッピングモールにである。実施期間が𝑛年のプロジェクトから得られる財

おける設置容量は全体の１％未満である。また、上海に立地するショッピングモール（127 箇所）のうち、太陽務的収益の現在価値の合計と、プロジェクトの為に要する財務的費用の現在価値の合計と等しくなるような割引

光発電システムを導入しているところは、0 箇所であ率と定義されるのが財務的内部収益率である𝐼# を初期投る。(2016 年 12 月 BAIDU 衛星画像で確認した結果)
表 1 上海市分散型太陽光発電システム建設状況概要

資額，𝐶𝐹& を𝑡年度目にプロジェクトから得られる収入にその年の投資費用を引いた数値，𝑟を割引率，𝑛をプロジ(2016 年)

ェクトの想定期間とすれば，
𝐶𝐹/
𝐶𝐹1
𝐶𝐹3
+
+⋯+
𝑁𝑃𝑉 = −𝐼# +
1+𝑟
1+𝑟 1
1+𝑟 3
3

= −𝐼# +
&5/

𝐶𝐹&
=0
1+𝑟 &

この等式が成り立つような𝑟を財務的内部収益率と呼ぶ。本研究ではこれを求める。

51

4-2.

4. 収益分析とシナリオ別の検討

補助金に着目する場合

現在太陽光発電コストがまだ高く，補助金は事業に欠かせない。補助金額が下がる場合，全量売電の時に内部収益率がどのように変化するかに着目した。国の補助金を現在の 0.42(RMB/kWh)、地方の補助金を0.25(RMB/kWh)から計算し始め，0.1(RMB/kWh)刻みとし，0 になるまでの財務的内部収益率の変化に着目した。結果的に内部収益率が 12.66%からそれぞれ 3.51%と10.35%まで減少した。また，両方の補助金が無くなると，財政収支が負になる。
4-3. 買取り価格に着目する場合
中国では太陽光発電事業主が全量売電を選択する場
合，所在地域買取り価格で電力を買取られている。上海の買取り価格は現在 0.85(RMB/kWh)である。買取り価格が下がる場合，全量売電の時に財務的内部収益率がどのように変化するかに着目した。買取り価格を0.85(RMB/kWh)から計算し始め，0.1(RMB/kWh)刻みとし，現在火力発電コストの 0.39(RMB/kWh)までの財務的内部収益率の変化に着目した。結果的に内部収益率が12.66%から 6.25%まで減少した。
4-4. 初期投資費用に着目する場合

図 1 ショッピングモールと太陽光発電システムのビ
ジネスモデル

上海に立地するショッピングモールに太陽光発電シス
テムを設置する場合、どのような費用と便益が発生するのか、関連資料およびヒアリング調査（2016 年 8 月実施）により図示したものが、図 1 である。 この調査では，ショッピングモールのビジネス規模を考察するための各収支データを揃えた。同図にある通り、太陽光発電システムの主な収益は売電収入と補助金であり、主な費
用は O&M 費用と税金である。本論では、太陽光発電シス
テムの収益分析を、全量売電する場合と全量自己消費する場合の二通りに分けて行う。
虚線部分の太陽光発電システムを単独で分析する結果，全量売電の場合内部収益率は 12.66%、全量自己消費の場合は 9.57%になる。また，太陽光発電事業とショッ
ピングモール本来の事業と比較すると，ショッピングモ
ール事業の収入が太陽光発電事業の収入の何十倍もあることが判明し，両者の収入の額が桁違うことがわかった。ここまでの分析結果から二つがわかる：(1)現在シ
ステム全量売電の場合は全量自己消費にするより内部収益率が高い；(2)太陽光発電事業はショッピングモール
本来のビジネスと比べると無視できるほど微々たるである。
太陽光発電事業の収益性は様々な要因で内部収益率が影響される。本論では人間行動、補助金、買取り価格、初期投資費用による内部収益率の変化に着目し、検討した。各シナリオの試算結果は表 3 でまとめている。
表 3 シナリオ別の収益性試算結果（単位：％）
シナリオ

全量売電

人間行動

太陽光発電設備の価格は近年低下傾向にある。初期投資費用が下がる場合，全量売電の時に財務的内部収益率がどのように変化するかに着目する。初期投資費用を現在設定している 750(万 RMB)から計算し始め，10(万RMB)刻みとし，初期設定の三分の二の 500(万 RMB)までの財務的内部収益率の変化に着目した。結果的には財務
的内部収益率が 12.66%から 22.86%までに上昇した。

4. 結論および今後の課題
本論の結論として，以下の 2 点を確認した。(1)現時点中国では太陽光発電事業への民間投資を促進する政策が実施されているため，ショッピングモールにおける太陽光発電事業の投資の収益性がある程度確保できることがわかった。また，(2)政策面と収益性両方が整えている中，現在中国におけるショッピングモールにおける太陽光発電システムの投資の実績は限定的である事実が，全量自己消費

会社全体として環境に配慮するポリシーを明確に掲げて最大 9.57%

いないためと考えられる。

補助金(国)(↓)

12.66%から 3.51%

今後の研究課題としては，ショッピングモールへの補助金(地方)(↓)

12.66%から 10.35%

太陽光発電システムの導入による社会的便益の考察が考

買取り価格(↓)

12.66%から 6.25%

えられる。ショッピングモールのような人が多く集まる

初期投資費用(↓)

12.66%から 22.86%

場所での再生可能エネルギーの導入によって，人々の環

4-1.

境意識はどれだけ喚起されるか，またその際に用いる補

人間行動に着目する場合

助制度はどうあるべきかについて研究が考えられる。

発電することで多少電力を余計に使用しても良いと考え，電力消費量が逆に増える可能性がある。施設利用
者が太陽光による発電電力を過剰に消費した場合，財務的内部収益率がどのように変化するかに着目する。過剰参考文献に消費される電力は総発電量の 1(%)から計算し始め、展“十三五”規劃

1(%)刻みとし、内部収益率が計算できなくなるまで電力消費量を増加した。結果的に人間の過剰電力消費で仮想[2] Antonio Colmenar-Santos et al. (2016) An
assessment of photovoltaic potential in shopping

プロジェクトの財務的収益率が確実に減少する。また，

centres[1]中国国家発展改革委員会（2016）

過剰消費の程度と比例して財務的収益率の減少が激しく[3]蜂谷豊彦・中村博之（2001）

なる。

会計

52

第7章

可再生能源発企業経営の財務と戦略的投資の評価と決定Analysis of microbial flora in canned Shirasu heat-sterilized under
reduced pressure
Student Number: 13-13155 Name: Tatetsu MAEDA Supervisor: Kunio TAKAHASHI

1. Introduction

Shirasu was added in a 200 mL sterilized
trypticase-soy (TS) liquid medium. Each medium

Boiled Shirasu (whitebait) is a highly perishable

was flushed with nitrogen gas at 50 mL/min for 8

food, so that it can be preserved for only up to 4

min to ensure anaerobic environment. The culturedays at 10℃. Therefore, it is necessary to develop

flask was incubated at 10 or 30℃, 120 rpm, for 30

the technologies, such as packing in a can, todays. To confirm the growth of microorganisms,

preserve boiled Shirasu for a long period of time.

turbidity of the medium was observed.

Sterilization is necessary for the long-termpreservation of Shirasu. During heat sterilization

2-2. Microbial community analysis

of canned Shirasu, the internal pressure increases

Total DNA was extracted from microorganisms

and causes dripping, which results in the decreasegrown after enrichment culture, and the DNAof amino acid content by 51 to 60%. Therefore,

region encoding 16S rRNA was amplified by PCR

canned Shirasu is heated at reduced pressure tousing TaKaRa EX Taq® Hot Start Version

avoid dripping. Because canned Shirasu is(Takara Bio Inc., Japan). After confirming the

distributed at 10°C, it needs to be confirmed thatpsychotropic

and/orpsychrophilicamplification, the PCR products obtained weremicro-

purified using Wizard® SV Gel and PCR

organisms do not grow in a can after sterilization.

Clean-Up System (Promega Corp., USA). The

These microorganisms may increase during apurified PCR products were sequenced using

long-term storage period, although the microbial

BigDye® Terminator v3.1 Cycle Sequencing Kit

concentration is low at immediately after the(Perkin Elmer, Applied Biosystems Division,

sterilization. The existence of microorganisms

Japan).

would be examined in a short period of time by
growing the microorganisms under their favorable

3. Results and discussion

growth conditions and by applying molecularbiological

techniques.

The

present

study

3-1. Enrichments at different temperatures

investigated the microbial community of canned
Shirasu heated at reduced pressure, in order toDuringenrichment

cultureunder

anaerobic

confirm the long-term stability of canned Shirasu.

conditions, the growth of microorganisms insterilized canned Shirasu was different depending
on incubation temperatures (Fig. 1). The liquid

2. Materials and methods

medium incubated at 30℃ became turbid within
22-1. Enrichment cultureindicating

the

rapid

growthofmicroorganisms. On the other hand, no microbial

Two cans of Shirasu (Lots 1 and 2) were sterilized

growth was observed at 10℃ even after 30 days.

at 85℃, -20 kPa for 60 min. Microorganisms in

These results suggest that some microorganisms

canned Shirasu were enriched under two different
temperatures.

days,

remain in canned Shirasu after sterilization, but

Approximately 2 g of sterilized

they do not grow at 10℃.

53

Lot 1

Lot 2

4

1
2
3
5

1

Paenibacillus qingshengii
strain S1-9

2

Paenibacillus qingshengii
strain S1-9

3

Bacillus subtilis subsp.
inaquosorum strain BGSC 3A28

4Staphylococcus epidermidis
strain NBRC 100911

5

Bacillus amyloliquefaciens
subsp. plantarum strain FZB42

Fig. 1. Comparison of turbidity in TS liquid media

Fig. 2. DGGE profiles of sterilized cannedenriched at two different temperatures

Shirasu enriched at 30℃

99 Band 4
Band 357

3-2. Microbial community analysis

Aeribacillus pallidus strain DSM 3670
52

100 Bacillus licheniformis strain DSM 13

Paenibacillus odorifer strain TOD45

Figures 2 and 3 summarize the results of100

Band 176 Band 2

Band 54

microbial community analysis of the sterilized

88

Staphylococcus epidermidis strain NBRC 100911
Clostridium butyricum strain LCL 155

canned Shirasu enriched at 30℃. In Lot 1 can,0.02

two kinds of microorganisms were detected;

Fig. 3. Phylogenic tree of the bacteria found in

Paenibacillus qingshengii strain S1-9 and Bacillus

sterilized canned Shirasu enriched at 30℃

subtilis subsp. inaquosorum strain BGSC 3A28.
These identified strains were both spore-forming

4. Conclusions

bacteria [1,2]. In Lot 2 can, a spore-former
plantarum

Three spore-forming bacteria were observed instrain FZB42 [3] was also detected. Their spores

heat-sterilized canned Shirasu after enrichment at

are known to be tolerant against high temperature

30℃, while no microbial growth was observed at

so

10℃. It is suggested that the heating sterilization

Bacillusthat

amyloliquefaciens

they

often

subsp.

surviveafter

heatingsterilization [3]. Thus it was suggested that thedisinfects

psychotropic

and/orspores of these microorganisms survived after

microorganisms of canned Shirasu.

psychrophilic

heating of canned Shirasu at 85℃. On the other
hand, no microorganism was found at 10℃ (Fig.
1),

suggesting

that

the

growthof

5. Referencesthese

microorganisms enriched at 30℃ is very slow at[1] Chen, L., et al., 2015. Int. J. Syst. Evol.

low temperature. From these results, it isMicrobiol., 65, 2161–2166.

suggested that the heating sterilization adopted in[2] Setlow, P., 2005. J. Appl. Microbiol., 101,

this study efficiently disinfects psychotropic

514-525.

and/or psychrophilic microorganisms of canned[3] Rajan, S., et al., 2006. J. Food Prot., 69, 853–

Shirasu.

860.

54Assessment of Technical Feasibility of Jakarta’s Giant Seawall ProjectStudent ID: 14B15849

Name: Yi Xiong

Supervisor: Hiroshi Takagi

1 Abstract

according to NSICD scenarios

Jakarta is the capital of Indonesia. This megacity
is located on the northwest coast of Java, the mostpopulous island in the world. Jakarta metropolitan
area is the second largest urban agglomeration andsecond largest city in the world after Tokyo [1].
However, this megacity is suffered from the flood
almost every year. Jakarta is located at the mouth ofmany rivers which are connected with Jakarta Bay.
The land subsidence caused by overexploitation ofgroundwater makes the city more vulnerable toflood hazard [1]. In order to save the city andthousands of residents against the annual floods
from sea and rivers, Jakarta government decided topromote a project named The Master
Plan ”National Capital Integrated Coastal
Development”, collectively called as NCICD, which
incorporates the multi-phases of a Giant Seawall
and large storage basins. The project activities werechanged several times due to political or economy
reasons. And it will be still changing in the future
considered that the technical feasibility isinadequate [2]. There are a number of grave
concerns relating to such an ambitious project. In
the event that the great seawalls fail to shut out
seawater or the project is suspended or postponeddue to economic turmoil, engineering difficulties,
environmental impact, or political decisions, andassuming that efforts to reduce land subsidence are
not carried out, downtown Jakarta would eventually
become submerged [3].

Land subsidence rate in Jakarta is assumed at
7.5cm/year on average along the coastline [2].
According to Deltares, an independent institute, theworst area’s land subsidence rate in north Jakarta is
up to 18cm/year, urging the government to proceed
the Master Plan promptly. The future land
subsidence rate depends on the decrease in
groundwater extraction and the implementation of
piped water supply as alternative drinking water
source.
The master plan NCICD has three phases
including flood protection and urban development.
Phase A consists of short-term measures forstrengthening the existing coastal dykes (Fig.1).
Phase B includes the western part of outer sea wall
(total length 31km) and land reclamation for urban
development. Phase C is an optional construction ofa sea wall depending on the development on theland subsidence in the eastern part of Jakarta bay.
This paper attempts to find out the feasibility andeffects mainly on flood protection part of Phase A
and B by simulating scenarios using Delft3D Flow.
The following approach was assumed based on
construction schedule of NCICD. For simulation,
every 5 years of time interval has been consideredfrom 2020 to 2050. And the average land
subsidence rate was considered to create eachyear’s depth file in Delft3D. In this study, threesituations have been examined where the dyke’s
height considered as 1m, 3m and 5m, respectively.
Sea level was imposed based on astronomical tidelevel considering an abnormal high tide occurred in2007 [5]. Considering the storage lake that collects
all the flows from many rivers, the sea level inside
the seawall will quickly rise unless discharged water
is released into the sea accordingly. Thus pumpstations need to be constructed in order to lower
sea level inside the sea wall. The capacity andnumber of pump stations need to be determined byconsidering river discharges and other water inflows
to control sea level inside.

It is not clear how the project will look like in the
future. Other studies have concluded that thehuge storage will turn into a receptacle of waste
water if the government does not prioritize a paralleldevelopment of structural treatment of sewage[4].
The effects on the fishery industry cannot be ignored
neither. This study mainly focused on protecting
Jakarta from flood hazard. The aim of this researchis to find out the appropriate height of coast dyke
and discuss the technical feasibility of constructing
the outer sea wall.

Fig. 1

2

The result showed in each case, flooded area wasalmost same. Although 1m high dyke is enough toprotect the city from flood (Fig 2, Fig 3). However, it
should be noted that dyke must be heightened as
the land subsidence continues. It also should be
noted that dyke was not affected by land
subsidence in the simulation. In fact, seabed canalso be affected by land subsidence but not as fast
as coast area. In this study, although the subsidence
rates were assumed to be constant, in real situation
the sea level rise is slightly faster than simulation
condition.

strengthening dykes in northern Jakarta

Numerical

analysisusing

Delft3D

55

Fig.4 Sea level inside with 100m and 300m opening
Fig. 2 Flood area without coastal dykes in 2050

and maintenance costs, should be very expensive.

4 Conclusions
Theoretically, the proposed Phase A of NCICD
can protect Jakarta from flood hazard. According to
the simulation result, the whole system including
pump station, sea wall, dyke, storage basin, land
reclamation and gate system is proved as effective.
However, according to the analysis of this study, inPhase B, free-access sea wall was effective only if
the opening is shorter than 100m. This small
opening should limit the capacity of accessing ships.
As an alternative solution, canal-lock type gate canboth keep sea level from rising and provide a fluent
access for ships. However, expensive cost needs tobe managed by the local government. It also should
be noted that no matter how the sea wall would bebuilt, the massive pump system would continuously
require a plenty of electricity and financial resources.

Fig. 3 Flood area with 1m high coastal dykes in 2050

3 Investigation on Outer Seawall System
References

According to the information from Jakarta’s
government officer, there is a plan to construct a
300m-wide opening on the outer sea wall whichenables ships to access the existing ports. Basedon this information, another simulation scenario has
been carried out. The gate is needed in order tokeep alive fishing activities even after Master Plan isbeing implemented. In this study, two types ofaccess between inner and outer seas have been
considered. One type is free-access opening andthe other is a canal lock type that can keep the waterout of the seawall. The result showed that the giant
seawall might fail to protect the city from flood even
if they can limit the opening part as short as 100m
wide (Fig4). On the other hand, canal locks typegate can prevent the sea level inside the seawall
from rising of water effectively, although theoperation appears to be very complicated and theassociated cost, including construction, operational,[1] NCICD,”Master Plan, National Capital
Integrated Coastal Development”, 2014
[2] Deltares, ”Pump schemes, NCICD Phase A
Retention”, 2016[3] Takagi H., Fujii D., Esteban M., Yi X.
Effectiveness and Limitation of Coastal Dykes in
Jakarta: The Need for Prioritizing Actions against
Land Subsidence. Sustainability, 9, 619, 2017.
[4] van der Wulp, S.A., et al., “Master Plan Jakarta,
Indonesia: The Giant Seawall and the need forstructural treatment of municipal waste water”,
Marine Pollution Bulletin (2016)[5] Takagi H., Esteban M., Mikami T., Fujii D.
Projection of coastal floods in 2050 Jakarta, Urban
Climate, 17, pp.135-145, 2016.
[6] NCICD,

56”Construction strategy stage B”, 2014.

Numerical Modeling for Predicting River Flow in the Mekong Delta
メコンデルタの河川流予測のための数値シミュレーション
Student Number：13B00543

Name：Mizuho Arai

1. Introduction

Supervisor：Hiroshi Takagi

charge that best describes water levels observed by theSouthern Regional Hydro-Meteorological Centre in
Can Tho.

The Mekong Delta is formed by the accumulation of
sediment carried by the Mekong River in southern
Vietnam. It is one of the areas where the influence of
sea-level rise is concerned due to its extremely low
elevation. Major flood events are occurring almost
every year in the Mekong Delta. Especially, in
September 2000, remarkable flood damage whichcaused more than 400 casualties, manifesting lack ofeffective countermeasures against flood issues. Can
Tho, the largest city in the Mekong Delta, is situated
80 km inland where tide has dominant influence on
the river level. In other words, it is clear that rising ofsea surface elevation will increase the risk of floodingin Can Tho. Therefore, it is essential to understandthe combined influence of tide and river discharge inorder to evaluate the flooding risk of Can Tho andother Mekong Delta’s cities. The prediction of riverflows is also important in assessing the flood risk.
However, it appears that the river flow characteristics
and patterns in the delta system have been overlooked
and have not been sufficiently studied in the previous
flood risk studies.
This study attempt to develop a practical procedure
to predict a combined river flow in Can Tho, using ahydrodynamic model, Delft 3D-FLOW.

3. Analysis result and consideration
Figs. 1 and 2 show the reproducibility of the waterlevel and flow velocity in the dry season. Peak values
during maximum and lowest tidal phases are
extracted, and coefficient of determination is calculated by regression analysis. Fig-1 (a) shows thatsimulated water levels overestimate when tidal levelis relatively low (= neap-tide phase), whereas thoseagree well with the observed data during the springtide. Fig-2 shows that the flow velocity in the dry
season can be simulated with relatively high accuracy.
Nevertheless, it is confirmed that in Fig-2 (a) numerical results significantly overestimate particularly
when flow velocity is low. This is likely because theriver flow in this model neglected complex mechanisms of river-flow attenuations due to the tidal
current that travels upward.

2. Num erical M odeling
There is a significant difference in rainfall between
dry season and in rainy season. Therefore, this study
uses two methodologies to examine river flows in Can
Tho, as described in this section.
(1) Dry season（2010/4/15～4/30）
Due to the low-lying nature of the Mekong Delta, thetidal current is dominant in the Mekong Delta during
the dry season. In the dry season when rain rarely
falls, the influence on the river flow from the upstream
is extremely small. Therefore, the dry season model
can ignore the flow rate due to rainfall as well as
freshwater discharging from the upstream river. By
applying tidal constituents along the ocean-sideboundary, river flow and water level in the dry season
can be simply reproduced.

Fig-1 (a), (b) Model verification for high-tide level andlow-tide level in the dry season(2) Rainy season（2009/7/24～7/30）
In the rainy season, the flow from upstream due torainfall needs to be considered in addition totidal-induced currents. Therefore, it is necessary toobtain the flow rate that can reproduce the observation value. For the sake of simplicity of calculation,in this study we assumed an artificial source term,
which reproduces total river discharge in the middle
stream of Can Tho. The discharge at the source point
is determined by a trial method, which finds the dis-Fig-2 (a), (b) Model validation for High-tide velocity andlow-tide velocity in the dry season57

Table 1 shows the coefficients of determination of thewater level and the velocity for three different flow
rates due to total rainfall. Overall, the average flowrate with 18,000 ㎥/s seems to best reproduce velocity
and water level among three assumed discharges.
Table 1. Coefficients of determination of water level andvelocity according to three discharge scenarios
R²

Flow(m3/s)
12,000Velocity
18,00024,00012,000
Water level
18,00024,000n = 0.019
Rising tide Falling tide
0.68730.92050.74380.93260.59520.8786
0.97240.81570.96740.8881
0.96880.9017n =0.025
Rising tide Falling tide
0.71810.973
0.83080.88420.79960.86780.96010.89570.96
0.8671
0.96430.7472

Fig-4 (a), (b) Model verification for high-tide phase velocity
and low-tide phase velocity in the rainy season

Fig-3 (a), (b), Fig-4 (a), (b) show the reproducibility of
the water level and flow velocity in the rainy season
respectively. Peak values of rising and falling tides are
extracted, and each coefficient of determination is
calculated by regression analysis.
From the above results, it was found that the
influence of the tide is dominant to the river flow, andby using a model with high roughness coefficient, it ispossible to predict the maximum water level and flow
velocity which are important for the evaluation offlooding risk in rainy season. On the other hand, inorder to avoid overestimation of the water level in thedry season, it is necessary to evaluate the influence ofriver flow in the dry season on the tidal current.

4. Conclusions
Can Tho is densely populated city in the Mekong
Delta over low land, and is considered to be the world's
most vulnerable region to climate change. This study
constructed a practical simulation model that took into
consideration river discharge as well as tide, andinvestigated the possibility of predicting the river flowin the Mekong River.
As a future task, it is necessary to advance researchon the following things: Improving the proposed
method to be applicable for a longer period of the data.
Considering detailed land geometries to investigate
flooding risks in urban and agricultural areas.

5. References
1)

2)
3)

4)
Fig-3 (a), (b) High-tide phase level and low-tide phase level inthe rainy season58

高木泰士, Tran Van Ty, Nguyen Danh Thao,
Esteban Miguel, 高橋勇人: “メコンデルタ都市の洪水の研究―潮汐と海面上昇の影響―”,土木学会論文
集 B3(海洋開発), 69(2), pp.988-993, 2013.
Mekong River Commission: “Overview of theHydrology of the Mekong Basin”
高木泰士: 途上国防災の現実と課題―土木と国際開発の２つの視点から, 土木技術, 68 (3), pp. 85-88,
2013.
Hiroshi Takagi, Nguyen Hong Quan, Le Tuan Anh,
Nguyen Danh Thao, Van Pham Dang Tri, Tran
The Anh: “Practical modelling of tidal propagation
under fluvial interaction in the Mekong delta(under review)

Trial Production of Self-rechargeable Drone
Student number: 13B02306 Name: SIQI YUAN Supervisor: Kunio Takahashi

1Introduction

Drones(Unmanned aerial vehicle) have been widely usedin multiple different applications[1]. Due to safety reasons,battery has become the main energy source for drones. However the operation time of drone is relatively short[2]. Drones
have to stop for charging, then can continue operating[3].
(a) Boost converter design

Multiple methods have been tried to solve this problem.
One of them is building a charging platform and developing
algorithm to let drones charge as efficiently as possible[5].
However the operation area has been limited by this.
This research focus on designing a system which do not require any additional charging platform and do not need to(b) Equivalent circuit of boost converterchange drone’s original size. Two following method have

Fig. 1: Finding the basic character of solar drone

been used. (1)On-board solar panel that absorb solar energy for powering the drones. (2)Boost Converter to higher
the voltage the drones require.
2

Design of the boost converter

Model of the boost converter have been thought as fig.1[4].
Here by setting RL + RDS + RMP = Ron , and RL + RD +RMP + RDR = Roff , VD + VDR = VC and set VMP as power

Fig. 2: Current combination of the switching circuit

source’s maximum power point(MPP) voltage, IMP set as
MPpower source’s MPP current, RMP = VIMP
, We can figure outdion(t)2VMP − Ron ion(t) = L
dtWhen f → inf, the influence L brings to ioff becomes neg-

(1) ligible.

2VMP − VDR
dion(t)(1 − r)lim E1s = VDR
(7)
(2)
f →∞
Roff
dt
Therefore the general solution for (1) and (2) is shown re- Then we can use the result from [4] that the optimal duty
spectively as (3) and (4). Here C1 and C2 are random con- ratio is shown in eq(8) and the setting is e
g C,D = VDR +VD .
2VMP − Roff ioff(t) − VC = L

VMPstant.

→ 1.
Also need to under the condition that RRoff
on
Ron
2VMP
+ C 1 e− L t
Ron

(3)

Roff
2VMP − VC+ C2 e− L t
Roff

(4)

ion(t) =ioff(t) =dg = 1 −3C= B temperately.
We can set 2VRonMP = A and 2VRMPo f−V
f

e
g C,D

(8)

Experiment

After figuring out the maximum power point by fig.4, in-

I = ion[1] , ioff[2] , ion[3] , ioff[4] , ..., ion[2n−1] , ioff[2n]n = 1, 2, 3, ...

1

sert to eq(8). Assembling design following the fig.1a, and(5)

the model is shown in fig.3. The biggest obstacle of thisEnd current of each period is defined as In . eq(5) shows theresearch was designing a light system. The element whichswitching pattern. fig.2 shows the image of it.

had a significant impact on the total system weight is thelim ioff[∞](t) =n→∞(B − A)(e−Ron TonL− 1) − Roff t
e L +BR T +R T− on on L off off

1−ecoil. Due to the comprehension of the switching circuit(6)

charging system, higher the inductance therefore the higher
59

Fig. 3: Final assembly(a) Out of battery(b) Halogen Lamp for charging(c) Remove Halogen Lamp(d) Start operation

Fig. 5: 4 hours results of in-door simulation charging

Fig. 4: Maximum Power Point Tracking(1)V1 = 1.701V (2)V2 = 1.632V(3)V3 = 1.505V (4)V4 = 1.400V
the current follows through the battery. Therefore higher
the charging power. But to figure out whether by setting a

Fig. 6: The result of four different coils

high frequency will keep the system light, 4 different coils
have been used to calculate the charging power under f =the inductance. This hypothesis have been proved through

400kHz. During 8 hours recording, voltage between test-

the experiment by using different inductance coils. There-

ing resistance and drone battery has been recorded. Even-

fore when aiming to provide a light on-board system, it istually, whole charging system routine have been checked.

found that using lower inductance coil which have a re-

For indoor experiment, Halogen lamp have been used. After

duced weight impact will require setting the frequency tochecking solar panel under Halogen lamp, shown to provide

the maximum frequency PIC available in the system.

average 1.6V(original voltage 1.5V), continued the experiReferences

ment. Experiment drone can fly after 10% charging.
4[1] Jinyong Kim, Jinho Lee, Jaehoon Jeong, Hyoungshick
Kim, Jung Soo Park, and Taeho Kim. SAN: Selfadaptive navigation for drone battery charging in wireless drone networks. Proceedings - IEEE 30th International Conference, pages 248–251, 2016.
[2] Chenchen J. Li and Hao Ling. An Investigation on the
Radar Signatures of Small Consumer Drones. IEEE Antennas and Wireless Propagation Letters, 16:649–652,
2017.
[3] Chiuk Song, Hongseok Kim, Youngwoo Kim,
Donghyun Kim, Seungtaek Jeong, Yeonje Cho, Seongsoo Lee, Seungyoung Ahn, and Joungho Kim. EMI
Reduction Methods in Wireless Power Transfer System for Drone Electrical Charger using Tightly-coupled
Three-phase Resonant Magnetic Field. IEEE Transactions on Industrial Electronics, 0046(c):1–1, 2018.
[4] Masanori Tanaka. Optimization of circuit and control
parameters of a boost converter for energy harvesting.
2010.
[5] Chungki Woo, Sanha Kang, Hojin Ko, Hochan Song,and Jae Ook Kwon. Auto charging platform andalgorithms for long-distance flight of drones. 2017
IEEE International Conference on Consumer Electronics, ICCE 2017, pages 186–187, 2017.

Result and Discussion

The first result shows in fig5d that after 4hours charging,the drone successfully charge the battery from 4% to 13%.
After recording the 8 hours charging power, the hypothesis
which by setting high frequency will weaken the influenceof inductance are found to be true. As is shown in fig6 thecharging power order was found by L3 > L2 > L4 > L1 .
5

Conclusion

In this research, prototype production of self-rechargeable
drone has been completed. By using both solar panel andboost converter, an on-board system successfully enabled
drones to charge. However due to the calculation of thecurrent format, it was found that if setting the frequency
to a high magnitude, the current will be less influence by60日本全域における大気境界層水平風速の年間スペクトル特性
学籍番号：14_03770 氏名：何暁卿 指導教官：神田学
1. はじめにの指数の-2/3 は傾きの値になる。
より低周波数側では、大気流れの水平スケー

スペクトル解析は様々な気象現象の、時空間ス

ルに比べ、鉛直スケールは非常に小さいため、ケールの特性を知るのに役に立つ。過去の長期地

二次元的な流れが支配的になると考えられてお上観測データから、時間スケール約 1 時間の所にり、そのスペクトル強度は周波数の-3 乗に比例スペクトル強度の著しく低いスペクトルギャッ

して減少することが理論的に示されている。

プが存在し、その高周波側については Kaimal ら
によるカンザスでの微気象観測実験から、Monin-

3. データObukhov 相似則に従う普遍的性質を実証されている。一方、スペクトルギャップの低周波側では使用したデータは 2014 年から 2016 年まで、

慣性小領域と似た一定勾配でエネルギーが減少

三年間の日本全国 155 地点の気象官署および特する帯域があることが指摘されているが、観測及別地域気象観測所で観測した風速の 1 分値デー

び解析事例の少なさからよく分かっていない。まタである。これは地域気象観測システム（アメた、この二つのスケール間での相互作用なども検ダス）の一部であるが、データの品質管理が施討されていない。これに対し本研究では、日本全された状態で配布されている。155 地点はほぼ日国に散在する 155 地点の地上気象観測 1 分値デ

本全域をカバーしており、各地方の代表的な風ータを用いて、風速に関する長期スペクトルの低速スペクトルが得られていると考えられる。

周波側の特性について検討した。
4. 結果と考察
2. 理論背景
4.1 地上観測データの長周期スペクトル特性
図 1 は 155 地点で計測された風速スペクトル

スペクトルギャップより高周波数側では地表面の三次元乱流に支配される。慣性小領域におの平均値であるが、いくつかの特性が見られ

いて、Kolmogorov は次元的な考察からる。周期約 4 日に最大値、1 日と半日に帯域の極E(k) = Cϵ2/3 k −5/3

(1)

大値があり、それぞれ移動性の高・低気圧の通という式を導いた。いわば Kolmogorov の-5/3

過、地球の自転及び大気潮汐などによるものと乗則である。E(k)はエネルギースペクトル、C はされている。さらに、周期約 1h~10min の間に定数、ϵは乱流エネルギーの散逸率、k は波数である。空間スペクトルを周波数スペクトルに変化するため、Taylor の仮説
𝑘 = 2π𝑓/𝑢0(2)を用い、f の重みをつけ、下の周波数スペクトルに変換できる。
𝑓𝑆(𝑓) = 𝑎𝑓 −2/3(3)

この式は両軸対数スケールで、直線になり、元

図 1 スペクトル特性

61

5. 結論

スペクトル強度が非常に低い領域があり、これがスペクトルギャップである。以上から、地上 1

地上気象観測 1 分値データを用い、日本全域

分データにおいても地上風速に見られる代表的の 155 地点の風速スペクトルを算出し、スペクな傾向を捉えられることが分かる。

トルギャップの低周波側のスペクトル形状の特4.2 メソスケール領域のスペクトル特性性について検討し、その傾きが局所的な風速、

Kraichnan (1967)によると、メソスケールにあるいは地形の影響により変化することを示し

おいて、二つ領域があり、二つ式で表せる。

た。

一つ目はエンストロフィー慣性領域で下の式
E(k) = C ′ η2/3 k −3(4)′で表す。C は定数、ηはエンストロフィーの散逸率である。前述したように、
𝑓𝑆(𝑓) = a′ 𝑓 −2(5)に変化できる。両軸対数スケールで、-2 の傾きが得られる。もう一つはエネルギー慣性領域であり、式(1)で示され、周波数の-5/3 乗でエネル
ギーが減少する。つまり、メソスケールにおいても次々とより小さなスケールの場にエネルギ
図 2 メソスケールにおける傾きk meso−g とーは受け渡されるエネルギーカスケードが生じ

̅ の関係図年間平均風速Uている。
以上について検討するため、155 地点の風速ス
ペクトルから読み取られる、メソスケールにおけるスペクトル強度の傾きk meso−g と、年間平均
̅ の散布図について見てみた（図 2）
風速U。まず、-2 の傾きは確認できなかった。-2/3 に近いことが分かった。
ただし、この傾きは常に理論の-2/3 になってい̅ と負の相関性を持っていること
るのではなく、Uが分かった。これに加え、世界各地の観測事例の図 3 -2/3 傾きとの差(x%)
𝑘𝑚𝑒𝑠𝑜−𝑔 = (-2/3)*(1±x%)

値もプロットしてみたところ、概ね分布の範囲内に収まっており、同様の風速依存性を見ることができる。この傾きが他の要素に対する依存性を見参考文献たところ、それほど強い相関が見られなかった。

1)野口 (2011) 東京工業大学卒業論文

次にこの傾きの地域性について見てみる。得ら2)Kraichnan R (1967) Phys. Fluids, 10, 1417-

れた傾きの値と-2/3 との差をパーセンテージで表1423

し、日本マップにプロットしたのが図 3 である。

3)Larsen XG et al. (2016) Boundary Layer

図から明らかなように、北海道、太平洋側沿岸、

Meteorol, DOI:10.1007/s10546-016-0129-x

島及び平野のような平坦地では-2/3 に近い値を示

4)Kang S et al. (2017)

̅ も地形影響を受けることから、図 2 のしている。U

J.Geophys.Res:Atmospheres, 121(20),11946-

分布は地形に依存していることが示唆される。

11967,DOI: 10.1002/2016JD025289

62

The effect of consolidation and privatization of ports in proximity－ Case study in Osaka and Kobe ports －14_08683 : Hoshi TAGAWA
1.

Supervisor: Shinya HANAOKA, Tomoya KAWASAKIIntroduction

max 𝛱𝑖 = 𝜇 ∙ (52 ∙ 𝑓𝑖 ) ∙ 𝑒𝑖 𝑔𝑡𝑖 + 𝑟𝑖 − 𝑚𝑐𝑝 𝐾𝑖

In Japan, growth rate of transshipment container
volume and the number of trunk lines are substantiallylower than other East Asian countries. In order tostrengthen the competitiveness of Japanese container
port, Japanese Government launched the policy for“International Container Strategy Port”. The prominent
characteristics of this policy is “consolidation” and“privatization” of container ports in proximity (i.e.
Osaka and Kobe port). However, the effect ofconsolidation and privatization of the ports are not welldiscussed. Thus, this study aims to explore the effects ofthe four cases such as “consolidation or nonconsolidation” and “private or public” for Osaka andKobe ports. These effect is examined by using indicatorssuch as container volume and social welfare estimatedfrom the agent-based model. As a case study,
competition between Hanshin (Osaka and Kobe) andBusan port is analyzed.

2.

𝛱𝑖 is profit of Port management company. 𝑔𝑡𝑖 is gross
tonnage of ship. 𝑟𝑖 is charges of berth lease. 𝑚𝑐𝑝 ismaintenance cost of port. 𝐾𝑖 is capacity of port. 𝜇 isparameter. In the case of public, 𝜇 = 1.
b) private
Port management company is outsourced by local
government. Port management company and local
government are different subject. Port managementcompany decide 𝑟𝑖 to maximize own profit 𝛱𝑖 .
(Equation (3)) In the case of private, 𝜇 = 1⁄10 .
(Interview result)C) Terminal operator
Terminal operator is subject of lease berth andloading and unloading. Terminal operator is private.
They decide port service charge (𝑤𝑖 ) to maximize own
profit. (𝑃𝑡𝑖 )max 𝑃𝑡𝑖 = (𝑤𝑖 − 𝑚𝑐𝑡 )𝑄𝑖 − 𝑟𝑖(4)𝑤𝑖

Methodology

𝑚𝑐𝑡 is marginal cost. 𝑄𝑖 is total cargo in port i.
D) Shipping company
Shipping company is subject of cargo transport by
ship. They decide frequency of ships (𝑓𝑖 ) and freight rate(𝜏𝑖 ) to maximize own profit. (𝑃𝑠𝑖 )𝑦𝑁
max 𝑃𝑠𝑖 = (𝜏𝑖 − 𝑤𝑖 )𝑄𝑖 − 𝜀 ∙ 52𝑓𝑖 𝑖 𝑖 − 52𝑓𝑖 𝑒𝑖 𝑔𝑡𝑖(5)

2.1 Effect of consolidation
By executing the consolidation, “Integrated terminal
management” become possible. As a result, cargos to
North America from Osaka and Kobe are aggregated to
one place. It enables to reduce of waiting time due toconcentration of ships and attain economics of scale.
In the case of private, port management company
aims to maximize own profit. On the other hand, in thecase of public, it aims to maximize social welfare. And
also in the case of private, efficient operations are
possible. Cost is cut by 10% from public.
2.3 Behavior of stakeholders

exp(−𝜃∙𝐺𝐶𝑖𝑘 )𝑄𝑖 = ∑𝑘 𝑄𝑂𝑘 ∑Stakeholders involved to port can be divided into five.
“Local government”, “Port management company”,“Terminal operator”, “Shipping company”, and“Shipper”. Agent-based model can simulate therelations of those five stakeholders.
A) Local government
In Japan, it is decided by Port and Harbor Act that
Port management body is local government. And, local
government must decide “Ship’s harbor charges (𝑒𝑖 )”.
Local government is public, so 𝑒𝑖 is decided tomaximize social welfare. (Equation (1))
max 𝑆𝑊𝑖 = 𝛱𝑖 + 𝑃𝑡𝑖 + 𝑃𝑠𝑖 + 𝐶𝑆𝑖(1)𝑖 exp(−𝜃∙𝐺𝐶𝑖𝑘

𝐺𝐶𝑖𝑘 = 𝛼 [

2

𝑁𝑖
𝑉𝑖

+

𝑛𝑖𝑘
𝑣𝑖

+β∙

(6)

)
7

𝑓𝑖

]+𝛾∙

𝑄𝐵
𝐾𝑖

𝑧𝑛

+ 𝜏𝑖 + 𝑖 𝑖𝑘
𝑠𝑖 𝑣𝑖

(7)

𝑄𝑂𝑘 is total cargo from port k. 𝑄𝐵 is cargo volume atberth. 𝛼 is time value. 𝑁𝑖 ⁄𝑉𝑖 + 𝑛𝑖𝑘 ⁄𝑣𝑖 is total shipping
time. 7⁄𝑓𝑖 is waiting time in berth. 𝑉𝑖 is shipping
speed. 𝑛𝑖𝑘 is distance from port k to port i. 𝑣𝑖 isshipping speed of transship. 𝑧𝑖 is fuel surcharge oftransshipment ship. 𝑠𝑖 is capacity of transshipment
ship. θ,𝛽 and 𝛾 are parameter.
2.4 Solution algorithm

𝑒𝑖

1

𝑉𝑖

𝜏𝑖 ,𝑓𝑖𝑦𝑖 is fuel surcharge of ship. 𝑁𝑖 is distance from port i to
North American port. 𝜀 is parameter.
E) Shipper
Shipper is owner of cargo. They choose using port
based on generalized cost. ( 𝐺𝐶𝑖𝑘 ) Generalized cost is
consist of “frequency”, “lead time” and “freightrate.”(Equation (7)) The choice model are represented in
Equation (6).

2.2 Effect of privatization0𝑡0𝑡
𝐶𝑆𝑖 = ∑𝑘 (𝑞𝑖𝑘+ 𝑞𝑖𝑘)(𝐺𝐶𝑖𝑘− 𝐺𝐶𝑖𝑘)(3)𝑒𝑖

The shipper of hinterland in target 10 ports chooses
using port based on own generalized cost. (𝐺𝐶𝑖 ) Other
stakeholders determine each variables based on eachobjective. In order to solve this calculation, this study
adopt Hooke-Jeeves pattern search. Figure 1 shows thesolution algorithm of this study. (Public-case)

(2)

𝑡
𝑞𝑖𝑘
is total cargo from port k and transship at port i in𝑡year t. 𝐺𝐶𝑖𝑘is generalized cost cargo from port k andtransship at port i in year t.
B) Port management companya) public
Port management company is considered to be same
subject as local government since executive committee
members are comprised by local and central
government officers and stock share of this company ismostly shared by governments.

3.

Case study

3.1 Target cargo
Target cargo is from Western Japan 10 ports toNorth America. MLIT forecasts future cargo volume fortwo cases; middle and high increase. This study

63

C)

transshipment cargo
As for transshipment cargo, transshipment cargovolume of Pri-non is the largest. (Table 3) This isbecause, freight rate is lower than other case. Pri-Non
is effective as a hub port.

simulates the two cases and trend case which is
expected from least squares method.

Table 3 Result of transshipment cargo (high case)

3.3 Competition between Osaka, Kobe and Busan
Table4 shows that changing port style makes it
possible to strengthen international competitiveness.
But, compared with Busan international they are
weaker. Only changing port style cannot get stronger
international competitiveness than Busan.

Figure 1 Solution algorithm (Public)
3.2 Inputs for the simulationA)

trend case
In trend case, total cargo volume are decreasing. As
table 1 total cargo shows, when total cargo is decreasing,the difference in effect between consolidation and nonconsolidation becomes smaller. In 2030, as table 1 shows,the total cargo of Pub-Non are largest and social welfare
is high as well. From this result, in case total cargo will
decrease, Pub-Non is efficient in terms of social welfare
maximization.

Table 4 International competitiveness (high-2030)

Table 1 Result of trend case

4.

Conclusion

This study construct the agent-based model toexplore the effects of the four cases such as“consolidation or non-consolidation” and “private or
public” for Osaka and Kobe ports.
The most efficient management form of port isdifferent from the situation. It is important choose
suitable style to their objective.
Changing the port style makes it possible tostrengthen the international competitiveness, but eventhe most strength style, the competitiveness is inferior
to Busan.
In this study, cost of land transportation andtransshipment are not considered. To make model closer
to real, thinking such things is future work.

B)

middle and high increase caseAs for middle and high increase case, total cargo andsocial welfare in case of consolidation are higher thannon-consolidation case. (Table 2) But, there is little
difference between private and public. This implies thatthe effect of consolidation is higher than privatization.
If total cargo is increasing, consolidation is important toachieve cargo volume and social welfare.

References[1] Matsushima and Takuchi (2014) ‘Port privatizationin an international oligopoly’ Transportation ResearchPart B 67 382–397[2] Hooke, R., Jeeves, T. A., 1961. Direct search

Table 2 Result of high casesolution of numerical and statistical problems,
Journal of the ACM, 8, 212–229[3]渡部富博ら(2011)「国際間の貿易・産業構造を考慮した輸出入港湾貨物量推計モデル構築」国土技術政策総合研究所研究報告(49)64Study on Wave Pressure exerted on Piles installed in Swash Zone
Student Number: 14_07726

Name: Takayuki Sugiu

Supervisor: Hiroshi Takagi

1. Introduction

10m

22m
3.5m

In developing countries such as Vietnam, coastal cities
often experience rapid economic growth because of theirgeographical advances. However, many environemental issues
triggered by the development are left behind. One of such
examples is coastal erosion.
Phan Thiet, which is the city located in southern Vietnam,
is famous as a tourist destination and a number of resort hotels
has been built along the coastline. Recently, many coastal
communities are suffering from severe coastal erosion caused byadjacent coastal development such as land reclamation andjetties. Local people has installed wooden piles by themselves asa coastal-protection countermeasure to prevent the retreat ofcoastline. Although these community-based wooden piles arecommonly installed in a very shallow water, extensive research
has yet to be conducted to investigate e.g. wave pressures exerted
on the piles or characterisitcs of waves in swash zone.
The purpose of this research is to verify the accuracy ofnumerical analysis and thereby discuss the applicability of it forwooden piles design. For this purpose, a physical experiment
was carried out using a wave flume, and it was compared withresults from numerical simulation. Applicability of existing
formulas is also discussed.

4m
0.5m

0.5m 0.5m
ch4

ch2

ch3

ch1

Piles

Inlet Boundary

Absorber

Flat Bottom

B d(0.4m)

Slope

1:25

Flat

1.1m
Experiment
0.09m(Wave Pressure Gauge) Simulation
0m

Fig2. Geometry of experiment and simulation (cross-shore direction)

Fig3. Wave pressure gauge point and the piles

Table1. Numerical settings for each cases
cases①HWL・Ht=10②HWL・Ht=20③MWL・Ht=10④MWL・Ht=20⑤LWL・Hｔ=10⑥LWL・Hｔ=20

Fig.1. coastal erosion in Phan Thiet city, Vietnam (January,06,2012)

2. Experiment and numerical analysis

Initital Water Level [cm]
26
26
16
16
10
10

Ht [cm]
10
20
10
20
10
20

B [cm]
40
55
40
47
55
55

Table2. Calculation settings

In order to reproduce a similar situation as Phan Thiet, an
experiment was carried out using the wave flume at a Vietnam’s
governmental institute, SIWRR. Figs. 2 and 3 show thegeometry of the flume and dimension of the piles installed. The
water-pressure gauge was placed on the surface of the center pile,
9 cm above the bottom. This experiment was carried for six cases,
as shown in Table 1. The condition was determined based on
tidal condition (High Water Level (HWL), Middle Water Level(MWL), and Low Water Level (LWL)) and target wave height(Ht=10, 20 cm). Channel 1, 2, 3, and 4 in Fig.2 indicate thelocations where wave gauges were installed.
Numerical simulation was performed using IhFoam,
which is one of the solvers of OpenFOAM. OpenFOAM is an
open-source software, and IhFoam is a three-dimensional twophase flow solver using Volume of Fluid (VOF) method. Table
2 shows the settings of this model. In order to acquire the samewaves with those in experiment at channel 1, the incident wave
height and the depth of the flume in the numerical model wereslightly modified by trial and error, resulting in the conditions asshown in Table 1.

Item
Mesh size
Time step
Wave period
Wave theory
Turbulance model
LES SGSoutline0.015～0.3m cube mesh⊿t = 0.05sec
T = 2.0sec
Stokes theory
LES model
smagorinsky

3. Previous research
There are many previous research about wave pressure
exerted on objects. In this research, three of them were applied.
Table 3 indicates each of three theories along with assumed
conditions.
Table3. Summary of previous research
ObjectHiroi's Wave pressure
Wave Pressure Distribution by Goda
Small amplitude wave theory

65

pile
wall
-

assumed types of conditions
wave flow breaking wave pressure
〇
〇
〇
〇
〇
-

relatively large gap between experiment and OpenFOAM resultand OpenFOAM estimated lower maximum water pressure bymore than 2500 Pa. This is because in the model of OpenFOAM,
it is much more complicated to reproduce the impulse exerted on
the pile because of the limitation of mesh sizes. In addition,
inaccuracy of reproductively of wave-breaking points also affectwave height.

4. Assessment of wave pressure
exerted on the pile
There are two factors that determine wave pressures. One isflow which occurs subsequently induced by wave-breaking andthe other one is wave height. When wave-breaking occurs, wave
motions turn into mass flows, which are transformed into flow
towards the shore. The closer the wave-breaking points to thepile, the more energy exerts on water-pressure gauge. Figure 4.
shows the comparison between experiment results andcalculation results of the previous research. Figure 5 indicatesratio of errors of each theories to experimental results. In thisexperiment, waves broke before they approach to the piles incase ④ ⑤ and ⑥ . Particularly, wave-breaking can beobserved multiple times immediately in front of the piles in case⑤. As a result, larger pressure was instantaneously exerted incase ⑤ than other cases. When the broken wave stroked thepiles, splash of water rising was observed. In general, after awave-breaking happens, its wave height and velocity of the flow
will be attenuated as the wave proceeds forward. Wave height isthe other factor which is critical to the wave pressure. Thus, incase ④, water pressure is relatively lower even though the wave
broke before it arrived at the pile.
Nevertheless, some of preceding research can predict the valueof the pressure in particular cases, but the limitation of theiraccuracy can be explained as they assume wave ashydrodynamic phenomena. In addition, Hiroi’s and Goda’s
formulas are commonly used for designing constructions, andtherefore they take into account safety factors to incorporate acertain margin into the design.

Fig6. Maximum wave pressure in case HWL

Fig7. Maximum wave pressure in case MWL

Fig4. Comparison between the experimental and three theoretical formulas

Fig8. Maximum wave pressure in case LWL

5. Conclusion
By comparing results of preceding research, a certain levelof analysis could be carried out. Also, by analyzing theexperimental model using OpenFOAM, the limitation and thevalidity of IhFoam were proved. It should be noted that
OpenFOAM tends to underestimate breaking wave impact
pressure in terms of design of wave suppressors piles. Although
it has some limitation in terms of accurate calculation, IhFoam
can reveal better analysis other than previous methods and more
precise data can be observed.

References[1] Takagi H. et al., Coastal Vulnerabilities in a Fast-Growing
Vietnamese City, Coastal Disasters and Climate Change in
Vietnam, Elsevier, pp157-171, 2014[2]広井勇，波力の推定法に就きて, 土木学会誌, 第６巻，第２号, 1920[3]合田良実，防波堤の設計波圧に関する研究，港湾技術研
究所報告書, 第 12 巻, 第 3 号, 1973
[4]合田良実, 砕波指標の整理について, 土木学会論文
報告書, 第 180 号, 1970

Fig5. Ratio of errors of each theories to experimental results

Figure 6, 7 and 8 indicate the comparison of maximum
water pressure observed in experiments and OpenFOAM incases HWL, MWL, and LWL, respectively. In the case of ①
and ③, the results from the OpenFOAM analysis show a good
agreement with the experimental result. However, overall,
Openfoam tends to underestimate wave pressures. This
underestimation can be explained that it is difficult to calculate
an impulse force induced by wave breaking. In case ⑤, there is66

Recovery of Acetonitrile from Pharmacy Factory Wastewater by Distillation Process
Name: Jierui XU

Supervisor: Ryuichi EGASHIRA, Hiroaki HABAKI

1. Introduction

Figure 4 shows vapor-liquid equilibrium of a ternary
system after adding the solvent. It can be seen that as thesolvent concentration increases, the azeotropic
composition increases. And the minimum required
amount of solvent can be calculated from Figure 5.
The process of extractive distillation is shown in Figure
6. It consisted of an extractive distillation(D3) anddistillation for a solvent recovery(D4).
1

0.9

0.8

0.8

0.6

0.7

𝒚_𝒂𝒄[-]

Acetonitrile is one of the important substances in thechemical industry and is widely used in thepharmaceutical industry as a solvent or reactant. Although
it is industrially obtained as a by-product in the productionof acrylonitrile, acetonitrile is demanded more thanacrylonitrile, and recycle method of acetonitrile in thewastewater from pharmaceutical factory has attracted
attention. However, acetonitrile and water form azeotropic
mixture, and it is difficult to completely separate them inordinary distillation. Then, pressure swing distillation[1]and extractive distillation[2] have been studied to separate
acetonitrile and water.
This study aims to propose efficient separation ofacetonitrile and water by pressure swing and extractive
distillation processes. First, the vapor-liquid equilibrium(VLE) was estimated to examine the effects of theconditions on the azeotrope point. Then, the separation
was computationally simulated and energy consumptions
by both processes were compared.

x_ac [-]

Student Number:14B07488

0.4
50kPa

0.2

0.5

100kPa300kPa00

0.5
𝒙_𝒂𝒄[-]

0.6

0.4
0

1

Figure 1 VLE diagram ofbinary system

2. Vapor–Liquid Equilibrium and Distillation
Process

100

200
300
pressure [kPa]

400

500

Figure 2 Azeotropic
composition withdifferent pressure

2.1 Estimation of Vapor–Liquid Equilibrium
Table 1 shows the calculation conditions for the VLE
estimations with binary system of acetonitrile and water,
and ternary system of acetonitrile, water and dimethyl
sulfoxide (DMSO). DMSO was selected as the third
compound because it has been proved that is a suitable
solvent[3]. The UNIFAC model was used to estimate theactivity coefficients in the liquid phase, one of thethermodynamic estimation methods with interaction
parameters between functional groups composing themolecular. Then, the effects of the pressure and DMSO on
the VLE was studied.

50kPa
300kPaFigure 3 Process of pressure swing distillation

2.2 Pressure Swing Distillation
Figure 1 shows vapor-liquid equilibrium of a binary
system. It can be seen that the azeotropic compositionchanged when pressure is changing. Figure 2 showsazeotropic composition with different pressure and it canbe known that the azeotropic composition changes rapidly
when the pressure was around 10kPa to 100kPa andchange slowly when the pressure is rising over 300kPa.
Pressure swing distillation is a distillation method that
relies on the phenomenon that the azeotropic compositionchanges with the change in pressure. The process ofpressure swing distillation is shown in Figure 3,
distillations of D1 and D2 are used as the low-pressure
distillation and the high-pressure distillation respectively.

1𝒙_𝒂𝒄[-]

0.95

0.9

0.85

0.8

0.75
0.1

Figure 4 VLE diagram ofternary system

2.3 Extractive Distillation

67

0.15𝒙_𝒅𝒎𝒔𝒐[-] 0.2

0.25

Figure 5 Normalized
azeotropic composition ofacetonitrile with different
mole fraction of solvent

3.2 Result and discussion
Operating conditions and heat duty for pressure swing
distillation and extractive distillation are shown in Table
3. In this research, heat duty of two reboilers in the process
has been decided as the approximate value of the totalenergy consumption.
Table 3 Condition and heat duty of distillation

Figure 6 Process of extractive distillation
Table 1 Conditions for VLE estimation
Binary system
Pressure
Ternary system
Pressure
Mole Fraction of DMSO

3.

Comparison of Distillation Process

3.1 Simulation Conditions
Table 2 shows the calculation conditions of pressure
swing and extractive distillations. The composition of thefeed consisted of acetonitrile and water and the mole
fraction of acetonitrile was 0.4 because actual factory
wastewater has such a composition. The specification of
the product was that the mole fraction and yield of
acetonitrile was set as 0.999. In the case of pressure swing
distillation, the operating pressure was set at 50kPa and
300kPa. The low-pressure column operated lower than
30kPa should be vacuum distillation and the energy
consumption will increase rapidly. When the pressure ofhigh pressure column is higher than 300kPa, the azeotrope
point changed unremarkably. And from Figure 4, whenthe molar ratio of acetonitrile and water is 4:6, theminimum required amount of solvent can be known. The
process simulation was conducted with the generalprocess simulator of PRO II.

1000
298
40
0.999
0.999

[-]
[-]
[-]
[kPa]
[kPa]
[-]
[-]

10-20
10-20
20-30
50
300
1.0-2.0
0-1.0

[kPa]
[-]
[-]
[-]
[-]
[-]
[-]

100
1-100
1-20
1-100
1-10
0.1-1.0
0.1-1.0Stage
numberFeed-instage

Refluxratio

Heat duty ofreboiler[kJ/mol]

D1
D2
D3
D4

50
300
100
100

15
30
58
19

10
13
52
8

1.8
0.9
0.9
0.1

115.4
58.2
28.8
34.1

4. Conclusion
By making the VLE diagram of binary system andternary system. Conditions of the simulation such as
selection of operating pressure in pressure swing
distillation and minimum required amount of solvent in
extractive distillation can be decided.
After running simulation and optimizing operating
conditions, both pressure swing distillation and extractive
distillation proved that can separate acetonitrile and water
into target concentrations.
Among comparing the energy consumption of two
reboilers in the process, extractive distillation is more
efficient than pressure swing distillation.

Table 2 Conditions of the simulation[kmol/h]
[K]
[-]
[-]
[-]

Pressure[kPa]

The total energy consumption by the reboiler after two
distillations is shown in Table 3. Therefore, extractive
distillation is more efficient than pressure swing
distillation in acetonitrile-water system. The reasonsleading to such results were considered to be related tolatent heat of water. With the data of the overall flow ratein the two processes, in the pressure swing distillation, theflow rate of mixture with water and acetonitrile refluxed
is as high as 822kmol/h, so a large amount of heat isnecessary to evaporate mixture which contains 42.7% ofwater again in distillation column D1. However, in thecase of the extractive distillation, since there is no mixture
except solvent is refluxed, less energy is required toevaporate mixture again. Otherwise, trace amounts ofsolvent may be contained in the product depending on thestate of the distillation facility, so there is a risk ofaffecting quality while using extractive distillation.

acetonitrile, water[kPa]
10-500acetonitrile, water, DMSO
[kPa]
100
[-]
1-30

Feed and ProductFeed Mole Flow rate
Temperature
Mole Fraction of Acetonitrile in Feed
Yield
Mole Fraction of Acetonitrile in ProductPressure Swing Distillation
Feed Stage (D1)
Number of Stages (D1)
Number of Stages (D2)
Pressure (D1)
Pressure (D2)
Reflux Ratio (D1)
Reflux Ratio (D2)Extractive Distillation
Pressure (D3 and D4)
Number of Stages (D3)
Number of Stages (D4)Feed Stage (D3)
Solvent Stage (D3)
Reflux Ratio (D3)
Reflux Ratio (D4)Distillati
oncolumnReferences[1]Zhou Jinbo, Cui Xianbao, et al. Separation of acetonitrilewater mixture by batch extractive distillation[J]. Chemical
Industry and Engineering,26(6):482-486, (2009).
[2]Repke J U, Klein A, et al. Pressure swing batch distillation forhomogeneous azeotropic separation[J]. Chemical Engineering
Research and Design,85(4):492-501, (2007).
[3]Zhang Zhigang, Lv Ming, et al. Isobaric vapor-liquid
equilibrium for the extractive distillation of acetonitrilewater mixtures using dimethyl sulfoxide at 101.3kPa[J].
Chem.Eng.Data,58,3364-3369(2013).

68

FUTURE PRECIPITATION PREDICTION BASED ON CLIMATE CHANGE &URBANIZATION SCENARIOS IN A MEGACITY—JAKARTA
Student Number: 14_07608 Name: Ouran Sinn (Yinglan QIN) Supervisor: Manabu KANDA, A.C.G VARQUEZ(temperature, wind velocity, humidity, geopotential height)
estimated from a GCM (Fig.1). 5 GCMs providing two
Climate change affects the intensity and duration of rainfall climate pathways, RCP2.6 (conservative) and RCP8.5
which is directly related to our daily lives. In climate change (worst-case) scenarios were ensemble and used.
studies, future precipitation is widely investigated using
general circulation models (GCM), or downscaling of
future climate scenarios. Besides climate change, the effect 2.2 Setting of Urbanizationof urbanization to precipitation has also been proven. In
spite this, the effect of future urbanization to the future
precipitation in addition to global climate change is
uncertain. This research aims to understand the effect ofurbanization scenarios in the future to precipitation and themechanisms behind them while experiencing various
climate change scenarios.
This study is a pioneering work initially applied to
Jakarta, Indonesia which is a large developing megacity.
The periods cover months of extreme levels of precipitation,
drought and oversupply months.
Figure 2 Estimate future urbanization

1

Introduction

2

Numerical Setting

2.1

Setting of Climate change

Urban areas in WRF can be represented in more detail by
In this study, we utilized a downscaling method called anthropogenic heat emissions (AHE) and urban parameters
pseudo-global warming (PGW, [3]; see 2.1) to investigate (e.g. average building height, plant area index). According tofuture climate and developed a tool (see 2.2) which can [2], urbanization which considers spatial change of bothconsider social scenarios as inputs to estimating AHE and urban parameters can be estimated using a model
which can predict future population distribution anddistributions of urban morphological changes.
The main model used is a modified version of the empirical relationships between population and the said
Weather Research Forecasting Model (WRF). WRF is a parameters. These changes are added to the present AHE [4]non-hydrostatic weather model initially developed by and urban parameters [5]. The process is showed by Fig.2.
NCAR and was improved to accommodate distributions of To predict both population and AHE distribution, future
urban parameters [1] to show different urban morphology. social conditions (e.g. country-level population, energy
135 by 115 grids were allocated for the final domain to consumption, consumption) are needed as inputs. These
cover Jakarta. Grid spacing was set to 1200 meters. The social pathways can be derived from SSPs. Here, we focus
on SSP1 (compact) and SSP3 (business-as-usual).
same physical settings were used as in [1].

2.3

Cases of simulation

Table 1 Information of current & future cases

The simulation cases are shown in Table 1. RCP scenario
and SSP scenario are paired to indicate both and separate
Figure 1 Future climate downscaling
effects of global climate change and local urbanization.
In PGW, the lateral boundary condition of WRF which RCP2.6 with SSP1 show the best future that haveuses the present climate is modified by adding the environmental awareness and good urban planning. On thetemporal change (2010s to 2050s) of climate parameters contrary, RCP8.5 with SSP3 represents a worst future society.

69

3Results and Discussion

3.2

Future urbanization effect

3.1

Future climate change effectFigure 4 is the subtraction between RCP+SSP case with
RCP case. Increase of urbanization case additionaltemperature change around 0.05~0.07 ℃ than RCP cases.
Urbanization lead to more precipitation around the city.

Figure 5 Extreme value of each cases
In terms of extreme rainfall, levels of urbanization show
various effects depending on the background climate being
considered (Fig. 5). RCP+SSP cases (solid line) have lower
probability than RCP cases (dotted) during the dry season but
the situation is reversed during the rainy season.
Figure 3 Increase precipitation in RCP, RCP+SSP case
Figure 3 shows the difference in precipitation between 4 Conclusions
RCP8.5 case with current case and RCP8.5+SSP3 case withcurrent case. The difference shows the pure effect of The research findings are summarized as follows:background climate change in left side figure and (1) Global climate change trigger precipitation increase.
background climate with urbanization effect in right side
Because of the dominant direction of monsoonal winds
figure. Precipitation increase appeared in west side in dry
shift the rainfall, precipitation increase appears in theseason, but in east side in rainy season. Furthermore,west side of Jakarta in the dry season(August), and east
precipitation increase was found when urbanization wasside in the rainy season(January).
included both in RCP2.6+SSP1 and RCP8.5+SSP3 cases.
Temperature increase caused by global warming is around (2) Urbanization causes additional temperature increase and1.23 ℃ in RCP8.5 case. 1.30 ℃ in RCP8.5+SSP3 case.
evapotranspiration decrease in the city lead toThis temperature increase is also evidence that heating will
precipitation increase. Compare to the pure effect oftrigger more moisture from the surface to advected above
climate change, rainfall increase due to urbanization isleading to more precipitable water vapor in the atmosphere.
more concentrated around the urban area.
The seasonal dependence can also be seen. Dry seasonsshow increase at the northwestern part, while in wet seasons(3) Simulated future extreme rainfall in Jakarta decreased in(RCP 8.5) at the Southwestern side. This is brought about
dry season but increased in rainy season. Extreme
the differences in dominant wind directions (monsoon).
drought events in dry season and flood events in rainyseason could occur in the future.

References[1] VARQUEZ, A.C.G., et al., (2015) “The Effects of Highly
Detailed Urban Roughness Parameters on a Sea-Breeze
Numerical Simulation” Boundary-Layer Meteorol, 154:449–
469[2] VARQUEZ, A.C.G., et al., “Future population distribution of anurban agglomeration given climate change scenarios”, Journalof Japan Society of Civil Engineers, accepted[3] Kimura, F., and A. Kitoh (2007) “Downscaling by pseudo
global warning method” ICCAP final report, 43–46[4] Y. Dong et al., (2017) “Global anthropogenic heat flux databasewith high spatial resolution” Atmospheric Environment,
volume 150, 276-294[5] N.S.Darmanto et al., (2017) “Urban roughness parameters
estimation from globally available datasets for mesoscalemodeling in megacities” Urban Climate, volume 21, 243-261

Figure 4 Increase precipitation by urbanization70

Simultaneous measurement of liquid surface tension and contact angle
Student number：14B11722

Name：Keiichiro HAMADA Supervisor：Kunio TAKAHASHI

1. Introduction

surface. From Laplace pressure equation, theSuper-hydrophilic glass applies the concept offollowing equation consists of curvature radius𝜌𝑚 and angle 𝜀 of a point on liquid surface.

surface tension as one of the important elements
to evaluate the wettability of the solid surface,𝛥𝑝(𝜀) =and improve the function for eliminating dim-𝛾𝑙
= −𝜌𝑔𝑧(𝜀)𝜌𝑚(1)where 𝛾𝑙 is liquid surface tension, 𝜌 is liquid

ness.
Measurement of liquid surface tension isdensity, and 𝑔 is acceleration of gravity. And,

important. In most of wettability phenomena,eq.(1) is result of solving the eq.(2).

contact angle is formed between solid and liquidsurface. Therefore, it’s necessary to measure𝑥(𝑧) =

contact angle for measurement of accurate liquidsurface tension.

1√𝑎( tanh−1 √1 −In present, sessile drop

method is familiar to the measurement. This−tanh−1 √1 −method estimates liquid surface tension bymeasuringthesurface

profile

of

an

𝜌𝑔
𝑎=
,
𝛾𝑙

𝑎𝑧 2
𝑎𝑧 2
− 2√1 −
4
4

𝑎𝑧𝑐 2
𝑎𝑧𝑐 2
+ 2√1 −
)
4
4
𝜃𝑐 +

𝜋
2

spherical

cos
(3)
2
√𝑎
where 𝑧𝑐 is the height, to which the liquid goes up

approximation, and ignored gravitational force.

wet on the solid surface, 𝜃𝑐 is the contact angle.

axisymmetric liquid drop on a solid surface.
However,

thismethoduses

In Bakker’s study, the analytical solution

Thisexists about 2-demensional catenary liquid

is

the

𝑧𝑐 =

2

(2)

analyticalsolutionabout

surface model [2]. From this model, liquid2-demensinal catenary liquid surface profile.
Parameter 𝑎 and 𝑧𝑐 is obtained by fitting thesurface tension and contact angle are calculated

curve of eq.(2) using known 𝜌, 𝑔. Therefore, 𝛾𝑙 ,by measurement of liquid surface profile. Due to𝜃𝑐 is obtained from 𝑎 and 𝑧𝑐 .

the analytical solution, high accuracy calculation

3. Experiment3-1. Experiment apparatus

of liquid surface tension can be expected.

2. ModelA camera equipped with telecentric lens is

Figure 1 shows a model of 2-dimensional

used for observing the reflected light from thecatenary liquid surface made by semi-infinite

target, which is parallel to glass slide as a solid

solid surface and liquid which wet to solid(Figure 2).

Figure 1. 2-demensional catenary
liquid surface model

Figure 2. Equipment apparatus

71Solid material is borosilicate glass (Matunami

Table 1. Fitting Results

glass, C024601), and liquid material is pure

Advancing

Receding

γl

θc

γl

θc

water.
Experiments are done for two types ofmeasurement of liquid profile after a glass slide

No.1

61.31

48.16

74.31

28.70

has moved to advancing or receding enough as a

No.2

31.11

19.12

77.26

9.898

No.3

31.99

20.02

58.37

5.047

No.4

32.02

20.02

63.28

3.054

control experiment.

3-2. Analyze experiment result

𝛾𝑙 (mJ/m2 ), 𝜃𝑐 (°) (Tempreture:17.8℃)

Table 1 shows 𝛾𝑙 , 𝜃𝑐 calculated from the fitted
result. Compared with physical property value ofliquid surface tension：𝛾𝑙 =73.1(mJ/m2 ) at 17.8℃,

each 𝛾𝑙 corresponds to the degree of thephysical property value.
Each measured result of 𝛾𝑙 between
advancing and receding is not almost consistentin each number of data. Since 𝛾𝑙 is thecharacteristic value and is not changed bydifferent operations. It is not considered about
deviation of the z-axis direction occurred in aprocessing picture. It is possible that thedeviation of z-axis direction affect the different
values of 𝛾𝑙 .
There is a tendency that 𝛾𝑙 of data of latter
number is smaller. Experiments are performedin the order of number. It’s considered that
surface tension of water is changed because
water is mixed with the dust in the air.

4. Conclusion
Figure 3. Observation of liquid surface(a)Advancing (b)Receding

Simultaneous measurement of liquid surface
tension and contact angle by 2-demensional
catenary liquid surface model is verified in thisresearch.
It is possible that a deviation of z-axis
direction of processing pictures affects to a
calculated value.
It is considered that physical property is
rapidly changed as time goes by.
Reference[1] 中島章, 固体表面の濡れ性 (2014)[2]G.Bakker, Handbuch der Expeimentalphysik(1928)[3] 小野周, 表面張力 (1980)

Figure 4. Fitting curve representative72

Design method of angle of beams to maximize gripping force of multi-beam structure
Student number：14_15507 Name：Hiroaki Yamashita Supervisor：Kunio Takahashi
1. Introduction
Multi-beam structure, i.e. two dimensional array of
inclined beams, can be used as a manipulation device
since it not only generates adhesion force to grip object
but also absorbs the roughness of object’s surface.
In preceding study, multi-beam structure wasinvestigated [1], and it is found that the geometry of thebeams affects the strength of the gripping force.
However, an optimal angle of beams necessary for
maximizing gripping force has not been clearly studied.
This study investigates the design method of angle ofbeams to maximize gripping force, i.e. gripping stress,
considering the density of beams.

Figure 1. The process of contact between
multi-beam structure and surface of object

2. Gripping force of single beam based on elastic
Figure 2. The model of contact between elastic beams
beam theory
and rigid surface
2.1 Model of the contact between elastic beam andrigid surface
Multi-beam structure is composed of inclined
beams fixed as two dimensional array on rigid substrate
and operated by the process shown in Figure 1. (a) the
multi-beam structure approaches an object by applied
displacement and the edge of the beams contact with theobject’s surface. (b) After sufficiently approaching, thebeams alter to area contact, and the adhesion force
occurs between the interface. (c) the multi-beam
structure is then receded and it detaches the object.
The detaching force is called gripping force.
Figure 2 shows the contact between two elastic
beams and rigid surface, which is the unit model of thisFigure 3. Relation between displacement andstudy. The intervals of the beams are 𝛿𝑥 and 𝛿𝑦 .
gripping force of single beam
The beams have a length 𝐿, a width 𝑊, a thickness 𝐻,an angle 𝜃 (0 < θ < 𝜋⁄2 ), Young’s modulus 𝐸 and 2.2 Relation between displacement and gripping
the geometrical moment of inertia 𝐼. The gripping force,
force of a single beamwork of adhesion, displacement between surface and
The gripping force and deformation of a single
beams, length of the contact area are 𝐹 , 𝛥𝛾 , 𝑑 , 𝑎 , beam are estimated by using elastic beam theory [2].
respectively.
Figure 3 shows the relation between the displacement
Considering maximizing gripping stress of the and the gripping force. According to Figure 3, themulti-beam structure, the beams should be fixed as gripping force occurs when Γ⁄tan 𝜃 > 0.5, where Γ isdensely as possible but they can’t overlap with each introduced asother. Therefore, it is assumed that the beams don’t
𝛥𝛾𝑊𝐿2
Γ = √ 2𝐸𝐼 .
contact each other when the maximal gripping force
occurs during the contact process.
The maximal gripping force of a single beam occurs atline A4 B4 and curve B4 C5 in Figure 3.

73

discussed in chapter 3.1. M1 (M2 or M3) is the point
3. Design method of multi-beam structure
3.1 The area in which parameters for design multi- at which the maximal gripping stress occurs.
Therefore, the angle of beams at M1 ( M2 or M3 )beam structure
should be selected for maximizing the gripping stress ofmulti-beam structure.

Figure 4. The area that allows multi-beam structure to
generate gripping force and absorb surface roughness
Figure 6. Relation between angle of beams andgripping stress of multi-beam structure

The area filled with gray in Figure 4 indicates thearea in which (A) the gripping force occurs, and (B) the
multi-beam structure can absorb the roughness ofobject’s surface. The condition (A) is expressedΓ⁄tan 𝜃 > 0.5 as shown in Figure 3. On the other
hand, the condition (B) explained as 𝛿𝑥 < 𝐿 absorb theroughness better than (C) as shown in Figure 5.
Therefore, the parameters for the design of multi-beam
structure should be determined within this area.
Condition
Multi-beam structure

3.3 Procedure to determine the angle of beams
Angle of beams is determined in the following
process (1)~(2). In this process, it is assumed that thelength L, width W, thickness H, Young’s modulus E,interval 𝛿𝑦 and the work of adhesion 𝛥𝛾 are alreadyknown.
(1) Choose the angle which maximize gripping
stress of multi-beam structure. In figure 6,
gripping stress at the neighborhood of zeroradian or M1 (M2 or M3) is maximized.
(2) Then, choose the angle for absorbing theroughness of object’s surface. According to
Figure 5, M1 (M2 or M3 ) should be used forgripping rough surface.

(B)𝛿𝑥 < 𝐿(C)
𝛿𝑥 > 𝐿
Figure 5. The multi-beam structures which havedifferent conditions of interval 𝛿𝑥

3.2 Angle of beams which maximize the gripping 4. Conclusion
The angle of beams which maximize the gripping
stress of multi-beam structure
The
The gripping stress of multi-beam structure σ is stress of multi-beam structure is estimated.
procedure to determine the angle of beams is obtained.
estimated as
𝐹

𝜎 = max ,Reference[1] Mikhail Salyukov, et al, Development of a MultyBeam Structure by Stacking Comb-Shaped Rubbers",
Mate2018, vol24 pp. 261-264, 2018[2] Yu Sekiguchi, et al., “ Adhesion between sidesurface of an elastic beam and flat surface of rigid body”,
Journal of Adhesion Science and Technology, 26:23,
2615-2626, 2012

𝛿𝑥 𝛿𝑦where 𝐹max is the maximal gripping force of a single
beam and 𝛿𝑥 𝛿𝑦 is the occupied area of the single beam
as shown in Figure 1.
Figure 5 shows the relation between the angle ofbeams and the gripping stress of the multi-beam
structure. The parameters on line 𝛼1 D1 ( 𝛼2 D2 or𝛼3 D3 ) in Figure 5 meet the conditions (A) and (B)74Utilization of Bio-oil Derived from Wood Residues
in Rubberwood Process
Student Number:14-09139 Name:Haruka TANAKA

Supervisor:Ryuichi EGASHIRA, Hiroaki HABAKI
analysis of bio-oil were conducted by MICROCORDER JM10.
Table1 principal conditions for thermal treatment
Feedrubberwood sawdsut
Mass of feed[kg]
0.020-0.030
Atomosphere
N2
Flow rate[L/min]0.5
Temprature[K]
713, 903, 1093
Holding time[hour]
0.5

1. Introduction
Rubberwood furniture manufacturing is an important
industry in Southeast Asian countries, and thesawmilling process has been studied to be improved by
the utilization of wood residue, as shown Fig.1 [1]. The
operations expressed by white-colored boxes wereadditional ones to be proposed. The products from thethermal treatment of the wood residue, such as
pyroligneous acid, activated carbon, and off-gas, wereused as preservatives, adsorbent, and heat energy.
However the utilization of bio-oil has not been studied.
In this study, rubberwood sawdust was thermallytreated, and the yields and characteristics of the bio-oil
obtained under various conditions were examined.
Then, utilization of the bio-oil as heat source in theprocess was studied.

Ice bath temprature [K]275-278
2.2 Result and discussion
The yield of CPA, Char and Off-gas based on the RW,
and those of PA and bio-oil based on the feed CPA were
defined as,
𝑊𝑖
Yi =
(1)
𝑊𝑅𝑊

where WRW and Wi were the mass of the feed RW andproduct i (i = CPA, Char, or Off-gas). YOff-gas wasestimated by material balance.
Fig.2 showed the yield of CPA, Char, and Off-gas ofthermal treatment of RW together with previous data indried condition [2]. TT was temperature of thermal
treatment and TS was the final temperature of the liquid.
The yield of CPA and Off-gas gradually increased withTT, and the yield of Char decreased as TT decreased.
Although these trends were the same as the previous
data, the yield of CPA of this study was a little higher
than those in the previous study.
Fig.3 showed the yield of PA and bio-oil. The yield of
bio-oil increased as TT increased and TS decreased. The
higher TT enhanced yield of CPA and heavier
compounds should be generated more in the higher TT
range.

Fig.1 Current and proposed process of sawmilling:material and energy flow[1]2. Thermal treatment of rubberwood
2.1 Experimental
The rubberwood sawdust (RW), provided frommanufacturing company in Malaysia, was used aspyrolysis feed.
The experimental equipment is as stated in previous
study [1]. Table1 shows the conditions of thermal
treatment. The RW was dried at 373 K for 24 hours
before the treatment. The dried RW was heated by acommercial electric furnace under nitrogen atmospherein a stainless tube (I.D. 0.0384 m × 0.70 m ) andpyrolyzed to crude pyroligneous acid (CPA), char andoff-gas. The sample of off-gas were taken at the exit ofapparatus along time, until the furnace cooled down to313K.
The CPA was collected by the condensation of theeffluent gas. CPA was separated into pyroligneous acid(PA) and bio-oil by simple distillation. The final
temperature of the liquid was varied from 393 K to 433
K. The obtained CPA, PA and bio-oil were analyzed todetermine the moisture content and pH by Karl Fischer
titrator and pH meter, respectively. The elemental

Fig.2 Yield of each component Fig.3 Yield of each component
in thermal treatment
in simple distillation

Fig.4 showed pH of CPA, PA, and bio-oil and Fig.5
showed moisture content of them. Bio-oil had nomoisture content, and pH of each bio-oil was almost
constant to be 2.1. Moisture content of CPA was 0.40

75

is equivalent value to the produced heat of wholeprocess. To evaluate heat energy produced by off-gas
and bio-oil, Heat recovery A, QPH3 was divided therequired heat of whole process, was defined as,
𝑄𝑃,𝐻3Heat recovery A =
(4)
𝑄
+𝑄
+𝑄

and pH of CPA was in the range from 1.9 to 2.4.
Moisture content of PA was 0.70 and pH of CPA wasthe range from 2.1 to 2.3.
Table2 also showed characterization of bio-oil. The
element of composition in bio-oil was almost constant
independently of condition. To determine heating valueof bio-oil, the empirical equation estimate higher
heating value, HHV, of bio-oil derived was reported as[4],
HHV = 35.2xC + 99.4xH + 10.5(xS − xO ) (3)where xi was the mass fraction of element i in the
bio-oil (i is C, H, S or O). Generally plants should
contain S by so low level and it was assumed xs = 0.
Then, the HHV was estimated as 19.8 MJ / kg-bio-oil,and lower heating value, LHV, was as 19.7 MJ /kg-biooil. Here it was assumed that all hydrogen be should be
converted water and the latent heat was taken into
consideration.

𝑅,𝐷𝑦

𝑅,𝑇ℎ

𝑅,𝐷𝑠

Fig.6 showed maximum heat recovery A of only offgas or off-gas and bio-oil when all wood residues wereused in thermal treatment and heat generation2. WhenTT was 697 and 897 K, the heat energy produced bybio-oil was higher than off-gas and The heat quantityof bio-oil was occupied 30% of the required heat at
maximum.

Fig.6 Maximum heat recovery

4. Conclusions
To propose rubberwood process to use bio-oil in thisstudy, and the following conclusions were drawn fromthe results.
The effect of thermal treatment temperature had little
difference the elemental yield of bio-oil.
HHV of bio-oil was decided 19.8 MJ/kg, and LHV of
bio-oil was decided 19.7 MJ/kg by Eq. (3).
The heat quantity of bio-oil occupied 30% of therequired heat at maximum when all wood residue wasused.

Fig.4 pH of CPA, PA, Bio-oil

Fig.5 Moisture content of CPA,PA Bio-oil
Table2.Result of elementary analysis

TT[K] TS[K]

H

C

N

O

Moisture contnent

pH

713
903
1093
713
903
1093

0.059
0.061
0.062
0.062
0.062
0.062

0.485
0.507
0.502
0.545
0.539
0.530

0.001
0.001
0.000
0.001
0.001
0.000

0.398
0.402
0.414
0.385
0.387
0.398

0.00
0.00
0.00
-

2.13
2.15
2.18
-

393
393
393
433
433
433

Acknowledgement
Author would also like to express my gratitude to
Hock Chuan Enterprise for providing rubberwood
sawdust.
References[1] Rizafizah OTHAMAN, Kean Giap LIM, Shunsuke
KONISHI, Masayuki SATO, Nan SHI and Ryuichi
EGASHIRA, “Thermal Treatment of Wood Residues
and Effective Utilization of Its Products to Improve
Rubberwood Manufacturing Process,” Journal ofChemical Engineering of Japan, pp. 1149–1158 (2008)[2] K.G. Lim, Master Thesis, Tokyo Institute ofTechnology, 2004
[3] K. Chaiwong, T. Kiatsiriroat, N. Vorayos, C.
Thararax, Study of bio-oil and bio-char production
from algae by slow pyrolysis, Biomass and Bioenergy,
Pages 600-606, 2013[4] S.A. Channiwala, P.P. Parikh, "A unified correlationfor estimating HHV of solid, liquid and gaseous fuels",Fuel, Pages 1051-1063, 2002
[5] Sayuri MITANI, Bachelor Thesis, Tokyo Instituteof Technology, 2009

3. Heat recovery from bio-oil
Fig.1 showed was proposed to improve the process touse bio-oil. QP,H2, QP,H3, QR,Dy, QR,Dh and QR,Ds were
estimated from the enthalpy of inlet and outlet
materials. QR,Th and QR,DS were the heat energy used inthermal treatment and simple distillation respectively,that RW and water were the inlet materials at room
temperature and AC, CPA, and off-gas were outlet
materials at TT and PA and bio-oil ware outlet materials
at TS. Total heat required heat is the synthesis of theseadded QR,Dy, heat of drying RW. This study was usedprevious data because of getting overall process anddata for thermally treatment process [5]. QP,H3 was theheat energy produced by off-gas and bio-oil, usedprevious data and estimated from Eq.(3) respectively.
QP,H2 was the heat energy combusted wood residues.
Now, it was changed the ratio of residue fromrubberwood feed for thermal treatment, and calculated
each flow rate, when the required heat of whole process76

Feasibility Study of Mars Orbit Insertion by Aerocapture
Using Solar Sail
Student Number : 14_09659

Name : Yuichiro Tsukamoto

Superviser : Daisuke Akita

1. Introduction
One of the problems in manned Mars exploration in the
future is transportation of a lot of payload to Mars. By
conventional propulsion methods, however, only a small
amount of payload mass can be carried in spite of huge total
mass due to the specific impulse (𝐼𝑠𝑝 ).
Solar sail is a space propulsion system, which does not
require propellants and obtains thrust by reflecting
photons. JAXA launched solar sail IKAROS (Interplanetary
Kite-craft Accelerated by Radiation Of the Sun) in 2010
and it has successfully demonstrated photon acceleration.
The solar sail membrane is deployed by centrifugal force
with weights attached to the sail tip. Figure 1 shows theconfiguration of the solar sail IKAROS.

Figure 3 The sequence of Mars orbit insertion by
aerocapture using solar sail (Photon acceleration phase)3.

Trajectory Calculation for Aerocapture

Figure 4 shows the model for calculating the trajectoryduring aerocapture. The motion equation of solar sail isrepresented by Eq. (1).

Figure 1

Solar sail “IKAROS”[1]2. Mission Concept
The solar sail, which has an infinite 𝐼𝑠𝑝 , could be usefulas an in-space propulsion system for an interplanetarylogistics from Earth to Mars. Solar sail can’t produce
impulse propulsion, hence deceleration at Mars is
impossible. In this paper, solar sail is inserted into Mars
orbit by aerocapture. Aerocapture is an orbit insertion
method that the spacecraft is decelerated by drag during
atmospheric entry. For acceleration at apoapsis, photon
acceleration is used. Fig. 2 and 3 shows the mission concept.
In this study, in order to estimate the possibility ofsuccessful insertion into Mars orbit, the flight path angle
range (corridor) is investigated. In current technology it isfeasible if corridor is 0.1 [deg] or more.
In this study, the orbit of the solar sail is calculated until
the second entry into the atmosphere after aerocapture.
The solar sail is square shaped. The parameter are
membrane area, membrane mass, and rotation speed. The
ratio of membrane area density to rotation speed in
IKAROS is used as a reference for the rotation speed andmembrane mass of the solar sail considered here.

Figure 4 Motion equation model
𝑑𝑣 𝜇𝑚
1
1
= 2 sin 𝛾 − 𝜌𝑣 2
𝑑𝑡
𝑟
2
𝛽
𝑑𝛾
𝜇𝑚 𝑣
= ( 2 − ) cos 𝛾
𝑑𝑡
𝑣𝑟
𝑟

(1)

𝑑𝑟
= 𝑣 sin 𝛾
𝑑𝑡𝑡[s]: time from entry𝑣[m/s]: velocity
𝛾[deg]: flight path angle𝑟[m]: distance from the center of Mars𝜌[kg/m2] : density of Mars𝜇𝑚 [m3/s2] : a product of Mars mass
and gravitational constant𝛽[kg/m2] : ballistic coefficient
Equation (1) is numerically calculated by 4th order
Runge-Kutta method with time step of 0.1 [s]. Initial
velocity 𝑣0 is 5.6[km/s]. The initial altitude ℎ0 shown in
Figure 4 is 125[km]. [2]As aerodynamic heating during aerocapture, the heat
flux to the membrane surface is calculated by the Tauber’s
formula. The temperature limit of the membrane surface is660 [℃] which is the melting point of aluminum depositedon the membrane surface, If the membrane surface exceeds
this temperature during aerocapture, it is assumed that thesolar sail is burn out.
Fig. 5 shows the corridor based on each ballisticcoefficient and initial Flight path angle. If the velocity ofsolar sail exceeds the second astrnomical velocity at
Martian altitude of 200 [km], it will escape from the Mars
gravitational zone and can’t enter the elliptical orbit. If the

Figure 2 The sequence of Mars orbit insertion by
aerocapture using solar sail (Aerocapture phase)77

velocity of the solar sail does not exceed the fist astrnomical
velocity at Martian altitude of 200 [km], it will descent tothe surface of Mars. Also, β < 5.0[kg/m2] is necessary tocomplete the aerocapture in terms of aerodynamic heating.

Figure 5

entry into the atmosphere. If the rotation of the solar sail is
stopped, the membrane is deformed by aerodynamic force
during entry. The membrane deformation increases theballistic coefficient and thus keeps the orbit energy. The
altitude at the second entry into the Mars atmosphere isabout 200 [km] and the velocity is about 4800 [m/s].
The corridor with the membrane area is calculated sothat solar sail can insert into an elliptical orbit. The ballisticcoefficient at first entry into the Mars atmosphere is lessthan 5.0[kg/m2], and withstands the aerodynamic heating.
Corridor is 0.1 [deg] or more when the total membrane
area is more than 4,800 [m2] as shown in Fig.6. If the total
membrane area is 4,800 [m2], the rotation speed is 125[rpm] and the tensile load applied to the bridge is 461[MPa]. It is necessary to use a material having a tensile
strength higher than this value for the bridge.

Corridor led by temperature condition andballistic coefficientFree molecular flow calculation is performed for getting
aerodynamic characteristics of the rotating solar sail. In thefree molecular flow calculation, the drag coefficient isdetermined only by the angle of the membrane surface withrespect to the flow, and accordingly the ballistic coefficientduring atmospheric entry changes. The angle of themembrane surface to the flow is calculated from thebalance of forces in the symmetrical cross section of thesolar sail.
For the tensile strength of the membrane, only the
diagonal line component (bridge) is evaluated. The force
acting on the membrane surface of the solar sail isdecomposed into components along this diagonalcomponent and the tensile load is calculated.

4.

Figure 6 Aerocapture corridor with solar size

6. Conclusion
If the solar sail has a total membrane area of 4,800 [m2],the solar sail has a sufficient corridor for aerocapture.
Although there remain tasks in the development of thelarge membrane surface, this study would be the first step
toward the interplanetary logistics using the solar sail.

Trajectory Calculation for Elliptical Orbit

The elliptical orbits after aerocapture is calculated byusing the 4th order Runge-Kutta method. The gravity
range of Mars is considered to be a sphere with a radius of
130,000 [km]. If the solar sail goes beyond that, it isassumed to be affected by the gravity of other objects andthe solar sail can’t return to Mars. It is assumed that the
sun's position, the apoareion, and the periareion are all on
the same axis.
The thrust bythe photon reflection is considered to begiven by the following formula with 1.12 [mN] at 1AU of
IKAROS being regarded as a reference. [4]𝐹𝑠 = 1.12 × 10−3 × 𝑑0 ⁄ (𝑑1 − 𝑥) × 𝑆𝑠 /196
𝐹𝑠 [N]
𝑑0 [km]𝑑1 [km]𝑥[km]𝑆𝑠 [m2]

Reference[1] "Japan Aeronautic Association Aerospace and Culture”,
Available at:< http://www.aero.or.jp/web-koku-tobunka/2017-03-mori/2017-03mori.html>[Accessed 29 January 2018][2] Prasun N(2008), "Entry, Descent, and Landing
Performance of the Mars Phoenix Lander", Journal ofSpacecraft and Rockets, Vol. 48, No. 5, pp. 798-808.

(2)[3] Lobbia Marcus(2003),"A Framework for the Design
and Optimization of Waverider Derived HypersonicTransport Configurations"JPh.D.thesis,University ofTokyo.

: photon reflection thrust of solar sail: distance between Sun and Earth (1AU): distance between Sun and Mars
: distance between Mars and solar sail: solar sail membrane area[4] "JAXA Small Solar Power Sail Demonstrator'IKAROS' Confirmation of Photon Acceleration "Availableat<:http://www.jaxa.jp/press/2010/07/20100709_ikar
os_j.html> [Accessed 29 January 2018]

The membrane surface of the solar sail is assumed to beperpendicular to the velocity vector, and the thrust acts inthe velocity vector direction. At that time, the area
subjected to photon acceleration decreases by change inattitude of the solar sail with respect to the sun. The motionof solar sail is dominated only by Mars gravity until fly tothe apoapsis. After that, photon acceleration is applied
from the apoareion to the regression periareion.

5. Results of Trajectory Calculations
On elliptical orbit, it is judged to be successfully inserted
into Mars elliptical orbit if the energy obtained by photon
acceleration exceeds the energy loss due to the second78Global exploration of asteroid by numerous microlanders
Student Number：14 15884, Name：Seonghwan YEO, Supervisor：Daisuke AKITA

1Introduction

GM m
1
GM m
Asteroids are celestial bodies that have not had much=
mv 2 −(1)
process to become planets and may have primitive subR+h
2R
stances for the solar system formulation. At the same
1
GM m
GM m
m(ev)2 −= −(2)time, ”space guard”, which prepares for the asteroid
2
R
R
colliding with the earth, has significance.
e2 h(Rv 2 − 2)
A lander is a spacecraft which descends toward on(3)h′ =(R(ev)2 − 2)the surface of an astronomical body. In this paper,
I propose a method to disperse microlanders on theLander bounces with the horizontal kinetic energy
surface of asteroids in large quantities. This mission
atthe time of collision and moves horizontally until its
has the merit of being able to explore many points
total kinetic energy can be regarded as almost zero.
simultaneously.

Figure 2: Example of collision situation
The friction coeﬃcient µ is define as shown in Eq.(4).
For expressing the definition of the coeﬃcient of friction in this study by the formula, I denote the dimensionless constant coeﬃcient of restitution e, thedimensionless constant friction coeﬃcient µ, the vertical component to the collision plane of the velocity
before collision Vn,o [m/s], collision velocity before collision Supposing that the horizontal component to thesurface is Vt,o [m/s], the vertical component to the collision surface of the collision velocity is Vn,i [m/s] asshown in Eg.(5).

Figure 1: Mission scenario overview
Figure 1 shows the mission scenario. When a mothership carrying many microlanders runs around the asteroid, it scatters the microlanders and collects dataat that position when the microlaner bounces oﬀ andsends it to the mother ship.
The specification of one exploration lander is assumed as follows.
• Mass：0.01[kg] or less
• Size：0.01[m]×0.01[m]×0.01[m]• Communication：It is possible to communicate
with the mother ship and other landers.

Vt,i
Vn,i

(4)
(5)

In this paper, there are threekinds of collision conditions,which consider two kinds ofdiﬀuse reflection and a specular reflection. In this paper,
two situations of (Diﬀuse reflection 1)(−90◦ , 90◦ ) and (Diffuse reflection 2)(−180◦ , 180◦ ) as
(Min, Max) of the rotation angle around the vertical component against the collision surface
are considered. When examining
Figure 3: Diﬀuse the friction coeﬃcient, the coeﬃreflection
cient of restitution, and the characteristics of the collision condition, each parameter
follows the normal distribution with (-3σ, 3σ) as (Min,Max)(Figure. 3).
I thought four types of possible arrangements thatwere expected when orbiter shots(Figure. ??). Whenexamining other three parameters, initial arrangements
are fixed except for other three parameters not-fixed.

In this paper, we have four types of possible parameter,
such as inital position and initial velocity, coeﬃcient ofrestitution and friction coeﬃcient, collision condition,
initial arragement. In order to evaluate each parameter, those other than the relevant parameter are fixed.

2= (1 − µ) · Vt,o= e · Vn,oPhysical modelingIn this paper, only the gravitational field is considerd, shall ignore the influence of other forces such as
air resistance. Focusing on Lander, the basic operation of a single lander is to let it fall from the mothership, repeat the rebound, and to distribute on the asteroid. According to the law of Conservation of Energy, Eq.(1) and Eq.(2) are established. and h’ can beobtained in Eq.(3). The universal gravitational constant G[m3 /(kg · s2 )], the mass of the asteroid M[kg],the mass of microlander m[kg], the radius of the asteroid R[m], the dimensionless constant coeﬃcient of restitution e, the initial height h[m], the maximum heightafter collision h’[m]793

Evaluation of scattering

For visual evaluation on the plane, I take the obtained
spherical coordinate r, ϕ, θ to find the coordinates A[m]and E[m] as apply map projection. Consider ellipsoid
asteroid. The simulation of this research is done 500
times. Therefore, take the average and perform coordinate transformation from the following equation.
√r(range) =x2 + y 2 + z 2(6)z
θ(azimuth) = arccos ( )
(7)
r
x
) (8)
ϕ(elevation) = sgn(y) arccos ( √r2 − z 2
A = r·θ
(9)
E = r·ϕ(10)4Figure 4: Specular Reflection

Result of simulation

All of the simulation in this paper performed 500 timesof 100 landers. Consider the influence of various initial positions and initial velocity. While changing theinitial position and initial velocity, the arrangementsis (Arrangement1) with an interval of 10[m]. The coeﬃcient of restitution is fixed at 0.9, and the friction
coeﬃcient is fixed at 0.1. The initial velocity is given
from 0[m/h] to 300[m/h] at intervals 50[m/h] in theaxial direction(Table. 1).”Distance of the table means
the distance from the center of gravity of the asteroid.
Table 1: Eﬀect of initial posistion and initial velocity(optimum value)
Velocity[m/h]Coordinate[m] Distance[m](0,0,0)(-9.7, 32.1, 100.7)
106.137(0,0,-50)(-17.9, 44.1, 99.5)
110.297(0,0,-100)(-0.8, 4.4, 103.4)
103.497(0,0,-150)(2.2, -11.0, 104.0)
104.603(0,0,-200)(2.2, -12.0, 105.0)
105.706(0,0,-250)(-21.4, 48.0, 99.1)
112.173(12.8, -21.3, 106.0)
108.874(0,0,-300)

Figure 5: Specular Reflection
Consider three kinds of collision condition influences.
There are three kinds of collision conditions, and consider specular reflection and two kinds of diﬀuse reflection. When the initial position (0, 0, 500) [m], give theinitial velocity (0, 0, -100) [m / h]. The coeﬃcient ofrestitution and coeﬃcient of friction shall be (0.9, 0.1).
The simulation performed 500 times (table .4).
Table 4: Collision condition
Collision condition Distance[m](specular)
33.89221(diﬀuse1)
81.22123(diﬀuse2)
83.43120

From Table. 1, it seems that (50, 0, 0) is the condition that is most diﬃcult to be uniformly, but because
it does not move with respect to the axis, it is diﬃcult
to be even more uniform as a result of moving a little
with respect to the axis (0, 0, 500) [m] to (0, 0, -100) [m/ h] does not exceed the escape speed of the asteroid,
the distance from the center of gravity of the asteroid
is the closest. Understanding with only a single ladder
The best simulation in the future will use the resultsof this condition to examine the characteristics of theother conditions.
Consider the influence of various coeﬃcient of restitution and friction coeﬃcient. When the initial position (0, 0, 500) [m], give the initial velocity (0, 0, -100)[m / h]. For the simplicity (restitution coeﬃcient (average value), friction coeﬃcient (average value)), thestandard deviation is 0.1, (Min, Max) is set to (-3σ,3σ). Possible combinations are (0.3 〜 0.7, 0.7 〜0.3).
Simulation is performed 500 times2, Table. 3).
Table 2: (e, µ) = (0.6,0.7
〜0.3)
(e,µ)
Distance[m](0.6,0.7) 76.62776(0.6,0.6) 73.75840(0.6,0.5) 67.09725(0.6,0.4) 65.79947(0.6,0.3) 69.42426

5

Table 3: (e, µ) = (0.7,0.7
〜0.3)
(e,µ)
Distance[m](0.7,0.7)(0.7,0.6)(0.7,0.5)(0.7,0.4)(0.7,0.3)

Conclusion

In this research, investigated the asteroid exploration
by numerous microlanders. Various problems are obvious in using the conventional Lander’s method. Thus,
I proposed a new asteroid exploration method and explored the possibility.
• Depending on the initial position and initial speed,
there are conditions that are diﬃcult to spread.
• In the case of a spherical shape, it is easier todisperse than in the case of an ellipssoid。
• The eﬃciency decreases when a collision that often
bounces back in the direction of collision occurs
often.
• The higher the coeﬃcient of restitution, the higher
the scattering eﬃciency increases as the friction
coeﬃcient decreases.

References[1] 吉田，浅井： 微小重力環境において跳躍する探査ロボットの設計 , ロボティクス・メカトロニクス講演会 99 講
演論文集 1p206044, 1999.
[2] 吉光徹雄. Musesc プロジェクトと小惑星探査ロボット
minerva 構想 . jSAIRAS 98, 1998.

51.40219
49.22597
54.22401
43.37022
36.78452

80Effect of ions generated between electrodes on breakdown voltage
Student Number:14_12124

Name : Masaki Hira

Supervisor : Kunio Takahashi

1. Introduction
Discharge phenomena is a phenomena inwhich a current flows in gas between electrodes towhich the voltage is added between the electrodes.
Arc welding is one of the applications of thedischarge phenomena. Arc welding uses discharge
as a heat source. As a feature of the discharge
phenomena, the breakdown voltage is higher thanre-ignition and arc voltage [1].
Figure 1 Schematic lustration of measurement

There are various research to lower

experiment system

breakdown voltage. One of the studies suggeststhat ions between the electrodes may lower the
breakdown voltage [2]. However, since these aredischarge start.

speculation,

2.2.2

they

need

to

be

examined

Breakdown voltage
After d was fixed, I

experimentally. In this research, the effect of ionsincreased thegenerated between electrodes on breakdown

voltage between electrodes. Then switch off thevoltage is investigated experimentally.

power at the discharge starts. The voltage at this

2. Experiment Equipment

time is measured as the breakdown voltage. After

2.1 Calibration experiment

the experiment was repeated 5 times under thesame conditions, Change d and repeat thisIoncounter (NKMH-103) is used toprocedure.

measure ion concentration(Number/cc). A dryer(Panasonic) accessories is used as an ionizer. The
ionizer is covered by a glass tube. The ion

3. Experiment Result and discussion

concentration was measured by changing the

3.1 Calibration experiment
Figure 2 shows the relation between the

distance from the inlet port of the ioncounter tothe ionizer.

ion concentration and the distance between

2.2 Experiment of breakdown voltage

the ionizer and the inlet port. According to theElectrode rods used in this study are

figure 2, the ion concentration drops sharply

tungsten containing 2% ThO2. The diameter iswhen the distance exceeds 2cm. Therefore,

1mm. In figure 1, R is the resistor to limit thedi = 3mm , 1cm was selected in this research.

current (1500 Ω ). Ions are blown into the air

3.2 Experiment of breakdown voltage

between the electrodes by the ionizer. E

3.2.1 Voltage-current characteristic

is theFigure 3 shows the measurement of

DC power supply.
Voltage-current characteristic

current flowing between the electrodes and theAfter d was fixed at 1μm, the voltage ofpower supply voltage waveform in case of di = 3mm,

power supply is increased gradually. The current

d =1 μ m, with ions, and no ion. In Figure3,

and voltage are continuously measured until thecurrent flowing between the electrodes was

2.2.1

81

600
Breakdown Voltage (V)600

Breakdown Voltage (V)Ion Concentration (Number/cc)

107
106

500

10

5

400

104

500

400
2

103

4

6

8

10

2

4

6

8

d (m)d (m)(a) d i = 3mm With Ion(b) d i = 3mm No Ion

10

Figure 5 The experimental results of relation
102
0

2

4

6

8

between the breakdown voltage and the distance10

Distance (cm)Figure 2 The experimental result of relation

between electrodes

between ion concentration and distancevariations and the average breakdown voltage islow. On the other hand, the graph on the right

Current flowing between Power-Supply
Voltage (V)the electrodes(mA)

400
400

300

shows

200
200

100

0

50

100

0

150

50

100

150

100

100

ions

50

50

qualitatively

0
50

100

150

0

50

100



Power-supply

voltageaveragegenerated

betweenaffectthetheelectrodes

breakdown

voltage.

measured

beforebreakdown

The effect of the ions generated between theelectrodes qualitatively on the breakdown

Figure 4 Current flowing between the electrodes
and

high

150

Times (s)(b) d i = 3mm No Ion

Times (s)(a) d i = 3mm With Ion

andConclusion

00variations

breakdown voltage. Therefore, it is found that the

0

0

large

voltage was foundIn case of ‘Ionizer on’, it was observed that acurrent was flowing in a region of 150V or less.

observed in the region of 150V or less and wasn’t

It was also found that the current is not theobserved in the region from 150V to the start oftunnel current but the possibility that it is thedischarge. It was found that the current observed

current flowed by the ions generated between

in the region of 150V or less was not tunnel current

the electrodes.

but the possibility ofFor the phenomenon that current does not

the current flowing by the ions generated

flow in the region from 150 V or more to thebetween the electrodes.

start of discharge, the mechanism is unknown

3.2.2 Breakdown voltage

and further research is needed.

Figure 4 shows the relation between the

4. Reference

breakdown voltage and d. The graph on the left

[1] 原雅則,酒井洋輔, 気体放電論. 東京: 朝倉書

shows with ions and the graph on the right shows

店, 2011.

no ions. 〇 and × represent breakdown voltage.

[2] 元木幹雄,小野雅章,上出諭吉”放電加工のギャ◇

represent

averagebreakdown

voltage.

ップ現象”,電気加工学会誌,Vol8,No15,1974

Comparing the graph on the left with the graph on
the right, the graph on the left shows small82

Abnormal tides caused by storm surges in Tokyo Bay
Student Number: 13B08237 Name: Atsuhei TAKAHASHI Supervisor: Hiroshi TAKAGI

1. Introduction
Storm surge is an abnormal rise of water
generated by developed low pressure systemsuch as typhoon, over and above the predicted
astronomical tides. Along with strong wind, low
air pressure system is mainly caused bydifference in air pressure between center oftyphoon and outside the storm center [1]. Japan
is affected by typhoon mostly every year. The
typhoon that caused the most devastating
damage at Tokyo Bay in recorded history was
occurred in October 1, 1917. Number ofcasualties and destroyed houses caused by thistyphoon reached up to 1,301 and 43,083,
respectively [2].
The coastal protection around Tokyo Bay has
been much improved over the last century.
However, excessive ground water use during theperiod of rapid economic growth caused land
subsidence about 4 m, inevitably increasing
flood risks. Also less attention has been paid tothe disaster risk associated with storm surges.
Storm surges are amplified by geographicalfeatures of Tokyo Bay and further complicatedby multiple mechanisms associated with ocean,river, and meteorological dynamics.
The purpose of research is to numericallyinvestigate characteristics of abnormal hightides induced by typhoon storm surges in TokyoBay.

Terrain data

The Geospatial Information
Authority of Japan (GSI)

Roughnesssea area: 0.025
land area: 0.08

Time step
Mesh size
Dyke height
Typhoon Track

0.05 (min)Wide area: 250-1000 (m)Narrow area:25-100 (m)The Breau of Construction,
Tokyo Metropolitan Government
Japan Meteorological Agency (JMA)

Table 1. Calculation settings and Data sources

Typhoon Phanfone and Lan developed as atropical storm on September 29, 2014 andOctober 16, 2017, respectively. Finally they took
similar route to each other and eventually
passed over Tokyo on October 6, 2014 and 23
October 2017, respectively.

Fig 1. (left) Grid area (outer and inner domains)and (right) Typhoon Track

3. Result

2. Numerical Analysis
Fig 2. Calculated and observed abnormal tidal
level at Harumi during Phanfone

In this study, parametric typhoon model
coupled with the fluid dynamics model Delft3DFLOW has been used in order to estimate theextent of storm surges inside Tokyo Bay due tothe passage of recent major typhoons. Nested
grid system where the simulation was firstly
carried out for a wide area which encompasses
coasts of Tokyo, Kanagawa and Chiba
Prefecture. Then, with finer grid, detailed
simulation was carried out for low lying areas ofTokyo bay. Table 1 shows the model settings.
Past typhoons that have been reproduced in thisFig 3. Calculated and observed abnormal tide levelat Harumi during Lan
Figs 2 and 3 compare the calculated andobserved tide level deviation in Harumi tidal
station (St.), Tokyo.

study are Phanfone (2014) and Lan (2017).
83For both cases, the first peak of water-level rise
is well reproduced by the typhoon model,
demonstrating that storm-surge component ispredominant among many others. However,second peak which occurred around six hours
later from the first peak did not show wellagreement with observed value. The reason forthis will be discussed in the following section.

river) with those at tidal station located atHarumi and Chiba. Tidal stations at Harumi
and Chiba both are far away from each other.
Iwabuchi St. is located relatively close toHarumi St., whereas Chiba St. is far away from
Iwabuchi St.. Therefore, water level should also
be different between Harumi and Chiba St. if
there is any significant effect of river discharge.
However, both are almost identical. And
secondary peak observed water level at
Iwabuchi did not match well with secondaryhigh tide during Typhoon Lan.

3.1 Seiche effect in Tokyo Bay
Tokyo Bay is a semi-enclosed bay surroundedby both Miura and Boso Peninsula. As a result,behavior of seawater inside is significantly
confined by the shape of the bay. Therefore, asecondary oscillation called “seiche” can also be
induced by an abnormal atmospheric event. In
general, seiche happens in Tokyo Bay around 6
hours later of typhoon passage [3], and this
could be one of the reasons for secondary hightide found in Fig3.

3.3 Atmospheric pressure and wind velocity
after typhoon passes
In parametric typhoon model, the shape oftyphoon approximates as a circle. Therefore,
after a typhoon passed Tokyo Bay, atmosphericpressures and wind velocity rapidly becomesnormal. But in some cases, even when typhoon
travels far away from Tokyo Bay, low-pressure
system and associated strong winds may
remain. Such wake of meteorological condition
is important in predicting water levels, but it
could not be precisely evaluated by the present
model.

3.2 Effect of river discharge
Generally typhoon brings much rainfall thanany other normal atmospheric conditions. As aresult, water volume in the river system
connected directly with Tokyo Bay should also
increase. There is no available data whichcontains a pure river discharge because river
flow near the river mouth is highly influenced
by storm surges as well as tides that propagatesin the opposite direction of river flow. Thus it isdifficult to estimate accurate water discharge
from the data measured at upstream
observatories. Nevertheless, this study tried to
explain river discharge effect by comparing
available water level information along Sumida
River.

4. Conclusion
This study confirmed that the numerical model
can well predict the first peak of the high tide
during typhoons, which is mainly induced bystorm surges. However, the second peak ofwater level did not necessarily show a good
agreement with observed tide water levels. This
could be explained due to the effect of seiche andresidue of winds and low pressures after thetyphoon, which cannot be precisely model withthe present typhoon model. Second peak of tide
during typhoon period could also be dangerous
if it coincides with high tide. In order toreproduce secondary high tide, further studies
are needed to improve the storm surge model.

Fig 4. Observed water level during PHANFONE

Reference[1] 気象庁 台風に伴う高潮
http://www.jma.go.jp/jma/kishou/know/typhoon/4-1.html[2] 北原糸子ら『日本歴史災害事典』吉川弘文館,
2012[3] 宇野木早苗『東京湾の 6 時間周期の振動』海
洋学会秋季大会講演要旨集, 1987[

Fig 5. Observed water level during LAN
Figs. 4 and 5 compare observed water level at
Iwabuchi St. (23.5km upstream along Sumida
84

PHOSPHATE RECOVERY USING CALCIUM SILICATE HYDRATESYNTHESIZED FROM COAL FLY ASH
Student Number: 14-00701 Name: Yu AndoSupervisor: Hirofumi Hinode, Winarto Kurniawan

1 Introduction
Phosphorus (P) is one of the indispensable elements
for human life. It is used in agriculture as fertilizer, has awide range of applications in industry and is one of themain components in our bones and DNA. Phosphorous
can be sourced from phosphate rocks and at present, therecoverable reserves are decreasing at a fast rate becauseof human consumption. About 70% of the rocks are mined
mainly in 3 countries: China, Morocco, and USA. These
countries impose high tariffs and strict restrictions onexports of phosphate rocks. Japan rely heavily on thisimported resource but about half of the volume that is
imported ends up in waste. Therefore, Japan needs a
viable phosphorous recovery system. Usually, P isremoved from the sewage to prevent eutrophication.
There are two most common methods which can recover
P and converted into some value-added chemical such as
fertilizers: first, in the sewage treatment plant, P isrecovered through precipitation method using chemicals
such as polyaluminium chloride to recover chemical
phosphorus from wastewater and excess sludge. Thismethod needs another process to remove othercomponents and to adjust the pH and requiring large
amount of chemicals; the second method is alkaline
extraction in which P in incineration ash of sludge is
extracted by alkali solution. This method needs hightemperature, therefore initial cost and running cost of thismethod are high. For these reasons alternative P recovery
system which can reduce recovery cost is needed.
Calcium silicate hydrates (CSH) are formed in hyperalkaline, hydrothermal environments with silica andcalcium. CSH have high specific surface area and canadsorb heavy metal ion and anion. In previous study, it
was reported that CSH has high P adsorption andsedimentation ability. Moreover, its ability is not
influenced by CO32-, thus P recovery by CSH do not needdecarboxylation and pH adjustment processes [1].
However previous research used mineral as silica resource
and only recover P from simulated water (SW). There issome hypothesis about this adsorption mechanism but
This was not thoroughly studied. In this research to reduce
the synthesis cost of CSH, CSH was synthesized from coal
fly ash which is industrial waste, P recovery test was doneusing actual sewage and the mechanisms were studied
using by X-ray diffraction (XRD) and FT-IR analysis.
The research objectives in this research are as follows.
1) To synthesize CSH from coal fly ash for phosphaterecovery and; 2) To explain the mechanism of Padsorption on CSH

2Experimental methods

2.1

CSH synthesis

hydrothermal method. After the reaction, the solid phase
was washed by deionized water and dried under vacuum
condition at 60℃. To find the optimum condition for P
recovery, CSH which were synthesized at different
reaction times, reaction temperatures and molar ratios of
Ca/Si were tested. The name of samples are assigned as
X-Y-Z (X: reaction temperature, Y: reaction time, Z: Ca/Si
molar ratio)

2.2

Batch test

Phosphate recovery test was carried out by using
simulated wastewater (SW) which was prepared fromdeionized water and KH2PO4. The final concentration of
P in SW was 150 ppm. 0.112 g of samples was added to
SW and stirred at 300 rpm at 25℃. The contact time was
24 hours. In this study, adsorption isotherm and theinfluence of pH and CO32- was investigated. Actual
sewage recovery test was also conducted by using excess
sludge from ‘‘Naruse Clean Center’’ in Machida, Tokyo.

2.3

Characterization studies

XRD analysis was carried out to identify the crystal
phase. Surface functional groups were identified by FT-IR
analysis. XRF analysis was carried out to identify andquantify the elements on the surface. The properties ofpore of samples were analyzed by N2 adsorption methods.
Chemical compositions and concentrations of the solution
was analyzed by ICP-AES.

3

Results and discussion

CSH samples labelled ② and ③ in the XRD
diagram showed in Fig. 1 exhibited peaks at around 7, 29,
32, 50 and 55°, which are specific peaks of CSH. Samples② and ③ in Fig. 2 also exhibited specific FT-IR peaksof CSH at 500, 650, 970, 1450 and 1640 cm-1[2]. From
this results, it can be concluded that CSH was successfully
synthesized from coal fly ash.
Figure 3 shows the amount of P recovery and theamount of Si release. The adsorption of P is thought to beaccompanied by the release of Si. It is considered that
CSH adsorb P by ion exchange between phosphate andsilicate.
Figure 4 shows influence of pH on P adsorption. Initial
pH of SW was adjusted to around 3.0, 7.0, 9.0 and 11.0
using NaOH and HCl solution. CSH showed high P
recovery ability at low pH and ability stayed almost
constant value at high pH. The amount of P recovery wasin proportion with Si release at pH range of 5.0-11.0.
However, at pH range of 3.0-5.0, the amount of P recovery
was increased in spite of decreasing Si release. This isbecause when pH is high, phosphorus ion is in the form of
H2PO41-, so P could be recovered even with low Si release
compared to high pH conditions when P exist as HPO42-.
Figure 6 shows the result of recovery from actual
sewage wastewater sample. CSH could recover about
90% of P in actual sewage sample[4]. However, comparedto the results of P-recovery from SW, the amount of Si

The coal fly ash used in this research was from Ishinomaki,
Miyagi. To extract silica, fly ash was mixed with 5 mol/Lof NaOH solution and was stirred at 300 rpm for 3 hours
at 80℃. After filtration, Ca/Si ratio was adjusted throughthe addition of Ca(OH)2 and the CSH was synthesized by85

released was lower. In excess sewage, most of P exists asorganic phosphorus or condensed phosphoric acids.
Condensed phosphoric acids has multiple P in an ion so
CSH can exchange multiple P by only one silicate ion.

Figure 5. Adsorption isotherms

Q: Quartz(SiO2), M: Mullite (MgO-Al2O3・2SiO2)
C: CSH, H: hydroxyapatite(Ca10(PO4)(OH)2, A: Ca(OH)2

Figure 1. X-ray diffraction patterns

Figure 6. Result of adsorption from actual sewage
Table 1. XRF results

Figure 2. FT-IR patterns
Table 1 shows the amount of elements (atomic %composition) on the surface of samples by XRF analysis.
This indicates that P was recovered on the surface and theamount of silica on the surface decreased. Therefore, it
can be concluded that P ion exchange occurred on thesurface.

4
Figure 3. Result of adsorption from simulated
wastewater

Figure 4.

Conclusion

CSH was successfully synthesized from coal fly ash
by hydrothermal method and could recover about 90% of
P from actual sewage sample that was studied. Results of
FT-IR, XRD and composition analysis indicated that CSH
recovers P by ion exchange between phosphorus andsilicate. Result of XRD and XRF also indicated that CSH
recover phosphorus as hydroxyapatite on the surface. The
amount of Si released was influenced by ionic phase of P
and the amount of P recovered.
Accordingly, the synthesis of CSH from coal fly ash isconsidered to be a new way to recover phosphate fromsewage.

Influence of pH on P adsorption

References[1] Kenji Okano, et al,’’Novel technique for phosphorus
recovery from aqueous using amorphous calcium silicate
hydrate(A-CSHs)’’, Water Research 47, pp.2251-2259, 2013
[2] Wei Guan, et al, ‘‘Synthesis and Enhanced Phosphate
Recovet Property of porous calcium Silicate Hydrate Using
Polyethylenglycol as Pore-Generation Agent’’, materials
2013,6(7), 28462861[3] Hisao Otake, ‘’リンの事典’’, 朝倉書店, 2017

Sample ④ in Fig. 1 shows hydroxyapatite (HAP) is
crystalized. The sample after P recovery from sewage do
not show peaks of HAP. This is because there are different
forms of P in the actual sewage wastewater sample.
Samples ④ and ⑤ in Fig. 2 shows that after P
recovery, peaks of Si-O (around 500, 650 and 970cm-1)
disappeared and peaks of phosphate (around 450, 560, 600
and 1025cm-1)[3] were generated. This showed thatsilicate in sample was replaced by phosphate by ion
exchange.
86Clarification of Public Transport Usage Conditions in Ahmedabad, India
Student number: 14-12147

Name: Takashi Hiraide Supervisor: Shinya Hanaoka, Tomoya Kawasaki

1. Introduction

particular system with adverse effects and loads. Based onthese assumptions, that models how users not to use apublic transportation with auto is created as Figure1. In
this path diagram, it is assumed the impression of Auto
has influence on the use of Bus service.

The population of Ahmedabad is increasing witheconomic growth, and becomes the fifth largest city inIndia in 2011. The number of registered vehicles has also
increased rapidly and it cause economic loss andenvironmental problems due to the severe traffic
congestion. In order to solve those problems, the bus
transport network Ahmedabad Municipal Transport
Service, AMTS has started since 1947 and Bus Rapid
Transport System, BRTS has also started since 2007.
Nevertheless, these public transport accounts for only
12% of modal share in the city and private vehicle
accounts for no less than 36% in 2011. [1] The traffic
congestion has not been resolved yet and the various
problems are remained. This city has the paratransit called"Auto-rickshaw, Auto”, which is expected to play a role
as a feeder of public transport.
Previous studies on public bus transport services atnational and local levels focused on various contents, butthere is scant literature on residents’ impression of public
transport with its feeder in Indian cities and none for
Ahmedabad. Thus, this study is aimed to clarify
conditions to use public transport of private vehicle user.

Figure 1 Path diagram

Direct path coefficients are calculated by the following
equations.
The measurement equation
𝑥𝑖𝑗 = 𝛼𝑖𝑗 ･𝑦𝑖 + 𝜁𝑖𝑗(1)
The structural equation
𝑦𝑖 = ∑𝑛 𝛽𝑛𝑖 ･𝑦𝑛 + 𝜉𝑖
(2)Where, 𝑥𝑖𝑗 is observed variable, 𝑦𝑖 is latent variable,
𝛼𝑛𝑖 and 𝛽𝑖𝑗 are direct path coefficient, and 𝜁𝑖𝑗 and 𝜉𝑖are error variable. Total effect is the sum of direct andindirect path coefficients. It shows the influence between
observation variables.

2. Methodology
Two field surveys were conducted in this study. First
one is interview survey with stakeholders of urban
transportation in Ahmedabad to clarify the actual
condition of each mode in July 2017. The second one isquestionnaire survey of private vehicle users, who live innorthwest side of the city in December 2017. Survey area
is divided into Area A and B. The former is inside thestation area of the AMTS and outside that of BRTS, andthe latter is within 500m from the BRTS route, whichmeans inside the station area of BRTS. The questionnaire
sheet includes personal information and the impression ofAMTS, BRTS and Auto. Using collected samples, themodel of impression structure towards nonuse of public
transport is developed based on Technology Acceptance
Model 2, TAM2, which is a model for explaining theusage behavior of information systems based on Structural
Equation Modeling, SEM. [2]4. The results of questionnaire survey
4.1 Questionnaire sheet and number of samples
297 samples in Area A and 295 samples in Area B werecollected. Respondents were asked to answer eachquestion, which are the variables of nonuse of public
transport including Auto by 4 point scale. 4 and 1 indicates“strongly agree” and “strongly disagree”, respectively.
After the descriptive analysis, the model is developed
based on TAM2 and analyze it by SEM.

4.2 Results
The results of analysis for each area are addressed. All
the model obtained are less than 0.9 of Root Mean Square
Error of Approximation, RMSEA. Based on developedmodels, the conditions not to use public transport with
Auto are discussed.

3. Model development

4.2.1 Area A AMTS - Auto

The conceptual structure of TAM 2 assumes that the
belief of "perceived usefulness" and "perceived ease ofuse" is fundamentally important in explaining the
behavior of using service. Perceived usefulness is thedegree to which a person believes that using a particularsystem would enhance his/her job performance. Perceived
ease of use is the degree to which a person believes thatusing a particular system would be free from effort. When
thinking about behavior of nonuse of transportation
modes, the degrees to which a person believes that themode has no advantage and that it is needed too much cost
are fundamentally important. It is also needed the degree
to which a person believes that he/she would use aFirst, AMTS in Area A is discussed. Figure 2 shows theamount of total effect of latent variables to the nonuse of
AMTS in Area A. "No advantage" has the greatest
influence on nonuse of AMTS. It means the residents
recognize that owned vehicles are more convenient or
comfortable, and might not take road congestion and air
pollution seriously. Moreover, "The burden to use AMTS"
also has an influence on this means of transport.
According to its observed variables, AMTS is necessary
to make it easy to interchange with other transports and tochoose route. It also shows residents consider theoperating hour and frequency are not appropriate.

87Next, feeder of AMTS is discussed. The impressions
related to Autos also affect AMTS, and "Subjective norm"
has the greatest influence on it. , The decision making of
the surrounding people affects to that of himself/herself
greatly. The influence of "The burden to use Auto" and"Adverse effects and loads" has also great influence onnonuse of Autos. According to their observed variables,
discontent with the performance of the car body and theattitude of the drivers have an influence from them.
0.0

0.2

0.4

0.6

Next, it is noted that the feeder of BRTS is considered.
The impressions of Auto also affects BRTS and “Theburden to use Auto” and "Subjective norm" had great
influence on it. One of the influential latent variables is"The burden to use Auto". According to their observed
variables, it is required to raise the quality of driver’s
service. The impression that Autos are hard to catch is also
making people feel hard to use. "Subjective norm" isinfluential as much as "The burden to use Auto". Thus, thedecision making of the surrounding people is greatly
related to that of himself/herself. The amount of pathcoefficient of "Adverse effects and loads" is also large.
Thus, the residents of Area B are sensitive to the risk ofbeing involved in crimes from this result as well.

0.8

No advantage
The burden to use AMTS
Adverse effects and load
Subjective Norm
Auto

0.0

Figure 2 The amount of total effect of latent variables
to the nonuse of AMTS in Area A

AMTS in Area B is discussed. Figure 3 shows theamount of total effect of latent variables to the nonuse of
AMTS in Area B. The nonuse of AMTS is affected by theimpression of its feeder, rather than the evaluation of itself.
The influential latent variable on the nonuse of Auto is"Subjective norm" as with Area A. "The burden to use
Auto" is also as influential as "Subjective norm".
According to its observed variables, the residents are
dissatisfied with the driver's attitude when making routing
and negotiating fare. It leads to not using Auto and buses.
"Adverse effects and loads" has not a little influence as
well. "Autos tend to get involved in harassments at times."
has greatest influence of this latent variable. In theanalysis of Area A, where the same transport is operated,
the path coefficient toward this observed variable wassmaller than other pass. From these results, it can be said
that the residents of Area B are sensitive to the risk ofbeing involved in crimes. It is convincing, because Area
B has order residents with higher income and educationlevel compared to Area A.
0.2

0.4

0.4

0.6

No advantage
The burden to use BRTS
Adverse effects and load
Subjective Norm
Auto

4.2.2 Area B AMTS-Auto

0.0

0.2

Figure 4 The amount of total effect of latent variables
to the nonuse of BRTS in Area B

5. Conclusion
In this study, the impression on public transportation
with its feeder of owned vehicle user in Ahmedabad isanalyzed. It is revealed from the model that the feeling of‘no advantage to use’ of owners of private vehicles has thehighest effect on non-use of AMTS among the latentvariables, followed by ‘burden to use’ as the second
highest effect. Observed variables of ‘effort to transfer’and ‘effort of route choice’ largely affect latent variable of‘burden to use’. ‘Burden to use’ of ‘auto-rickshaw’ isobserved to have a relatively high effect on non-use of
AMTS. This implies that the improvement of feeder
service i.e. auto-rickshaw and connectivity between autorickshaw and AMTS are important to enhance the use of
AMTS. As for BRTS, ‘burden to use public transport (i.e.
ticketing system)’ and ‘auto-rickshaw’ have the highest
effect among the latent variables. Several negative
impressions towards auto-rickshaw as a feeder service areobserved in both AMTS and BRTS. Particularly,
subjective norms such as ‘family and friends do not use
auto-rickshaw’ is identified as one of the influentialconditions of non-use of public transport.
Those findings would be utilize in the process ofplanning and implementing measures to realize more
efficient and less burdensome city traffic in the future.
Nevertheless, it is unknown how much residents willmodally shift by improving the contents mentioned in thisresearch. Therefore, it is necessary to make policy basedon the results of this research and to conduct ademonstration experiment.

0.6

No advantage
The burden to use AMTS
Adverse effects and load
Subjective Norm
Auto

Figure 3 The amount of total effect of latent variables
to the nonuse of AMTS in Area B

4.2.3 Area B BRTS-Auto
BRTS in Area B is discussed. Figure 4 shows theamount of total effect of latent variables to the nonuse of
BRTS in Area B. “The burden to use BRTS" has thegreatest influence on the nonuse of BRTS. The observed
variables, such as difficultness to purchase tickets, get on
and off the bus, and determine the route has a large
influence from it. Thus, it is required to make it easier to
use the bus for these contents. Furthermore, since thevalue of the path coefficient of "It does not operate in earlymorning or midnight." is also large, residences have theimpression, that the operating hour is not appropriate.

Reference[1] CoE, Urban Transport-CEPT University and Ahmedabad Urban
Development Authority (AUDA), Integrated Mobility Plan for Greater
Ahmedabad Region. 2013[2] 中村雅章 情報システム利用の人間行動モデル-TAM (技術受容モデル) に関する研究-, 中京経営研究 10 (2), p.51-77, 2001-0201

88

3D model construction of indoor environment using photogrammetry
Student Number: 14B02679

Name: Shan Wang Supervisor: Jun-ichi TAKADA, Azril Haniz

1 Introduction
To predict and clarify how radio waves from wirelesscommunication systems propagate in the environment, it
may be useful to perform simulations. Surrounding environment has a great influence in wireless communication
systems, and particularly in indoor environments, the arrangement of the room may be very complex and difficult
to be modeled accurately. However it is not easy to construct a 3D model of a whole room from the beginning using software such as CAD. In order to reduce the cost of
construction, we can use photos to get a rudimentary 3Dmodel by photogrammetry.
Photogrammetry is a technique to obtain geometric characteristics of objects from photos. It is as old as modern
photography. By photogrammetry, we can get information
about 3D coordinates, image coordinates of views and soon [1].

Figure 1: Algorithm of SfM

3

Factors which influence 3D model accuracy

Before constructing a whole room, it is necessary to clarify what factors influence the construction and examine
how accurate the models are. Thus we tested six reasonablefactors: texture, color, number of photos, masking background, quality of photos and camera positions by modeling objects using software Agisoft Photoscan.

The objectives of this research are summarized below:
Examine the feasibility of utilizing photogrammetry toconstruct 3D models of indoor environments. Investigate
parameters which may affect the quality of the constructed
3D models.

Color
The influence of color was investigated by changing
the color of a black box, results show that dark or lightcolor does not influence the construction.
TextureThe influence of color was investigated by wrapping a
black box with newspaper, as distinct texture strongly
helps construction. This is because distinct texture has
many feature points that can be easier found by Photoscan.
Number of photos
The influence of the number of photos was also examined. This is related to the overlapping rate. We foundthat more photos with high overlapping rate helps thematching of feature points.
Masking background
Masking the background may help improve the model
because only the object parts will be used in construction. However, in our experiments, we found thatmasking does not have obvious influence on the results.
Quality of photos
Photoscan can calculate the image quality of photos
by sharpnessm Image quality does not have influenceon the accuracy of modeling but affects the clarity of
texture construction.
Camera positions
Camera positions have great effect on the construction. This is also related to the overlapping rate.

2 SfM
One of the most commonly used techniques of photogrammetrical is called structure from motion(SfM),
where 3D models are generated using overlapping photos
taken from lots of locations and orientations.
The process of SfM can be simply summarized into four
steps. Firstly, detect feature points in each photo. Then,
match feature points in pairs, and estimate camera movement. Next, according to feature points matched and camera movement estimation, construct 3D model. Finally,
optimize to have least error between all matching featurepoints, view point movement estimated with real ones.
To detect feature points, Scale-Invariant Feature Transform(SIFT) is used. SIFT is an algorithm which adds
smoothing filter in different scales, and detect featurepoints according to the difference between smoothed photos. Feature points are matched by each pairs of photos and matching is refined using Random Sample Consensus(RANSAC), which to ignore ostracized samples inmatching. According to pairs of feature points, fundamental matrix can be calculated by Epipolar constraint equation which includes information to estimate camera movement. Finally, model is constructed by using Triangulation
method. Figure 1 shows the algorithm of SfM [2].

89Figure 4: Roughness of the room modelpared to the simple box, it is within 6% error. Figure 4
shows the roughness of the room model. For each point,
the roughness value is equal to the distance between
this point and the best fitting plane computed on its nearest neighbors. Because we do not know the actual surface
roughness, we could not calculate the absolute error. But
the surface of the blackboard is smooth, an its roughness
should be less than 1cm. We can see from the Figure 4that color green indicates the roughness of 1.7cm, which ismuch larger than 1cm. The surface of the blackboard is not
smooth. Thus, the accuracy of the roughness is low.

Figure 2: Flyers put on objects without texture

By photogrammetry, the scale of the room can be constructed accurately, so it can be used in radio wave propagation simulation like ray tracing which will not be influenced by the surface roughness error. But simulations
which are highly dependent on roughness can not be applied. For example, simulations of radio wave scatteringfrom object surfaces, and power attenuation caused by surface roughness. Thus further processing is needed to improve the accuracy of the roughness.

Figure 3: Room model

A quantitative analysis of accuracy was investigated bycomparing the actual dimensions of a simple object withthe modeling results. Results show error within 2%, whichindicates that photogrammetry can achieve high accuracy
on modeling simple objects.

5Conclusion

In this thesis, we examined factors that have influence on
the modeling and we used the findings to build a 3D modelof a seminar room. The results show that for a simple object, the accuracy of model is quite high. For a whole room,
the scale can be constructed correctly, but the roughness
shows large error. Thus the model can be used in simulations that are not influenced by surface roughness, such as
simple ray tracing simulations.

4 3D model construction of seminar room
For the whole room modeling, we divided the room into
two parts and rebuilt each part respectively then connected
them to a whole model. We put flyers on the walls, blackboards, cabinet and other objects without texture like Figure 2. We stood at several positions spaced 20cm along
the middle line of the room, and at every position, we took
photos continuously while rotating the camera 180 degrees.
And about the blind spots like the side part of cabinet,
heaters and others, we took photos focusing on them. Finally, we took 246 photos with average image quality 0.9.
The textured room model is shown in Figure 3. Cabinet
and blind spots could not be modeled well. Places without
texture or flyers were blank especially high places. Floor
has a big hole on the middle. We consider that photos takenfrom blind spots were not continuous with other photos, so
the overlapping rate is low. And the shadow and light reflect of metallic objects influence the construction of cabinet and blind spots.

References[1] W. Elhassan ”3D Modeling of Indoor Building Geometry Using Unmanned Aerial Systems” , Concordia University, March 2016
[2] Linda G. Shapiro and George C, ”Computer Vision. Prentice Hall”,
ISNE 0-13-030796-3, B-1-8, 2001
[3] Joanna A,S “Evaluation of algorithms and tools for 3D modeling oflaser scanning data”,Norwegian University, June 2014 .

About the accuracy of the room model, we compared thedimensions of the blackboard, door and the whole room in
the generated model with the actual dimensions measured
using Cloud Compare. Although the errors are larger com-90

都市におけるミツバチプロジェクトが地域に与える環境・社会的影響
学籍番号：13_04475 氏名：神田大樹 指導教員：阿部直也
1. 研究の背景

ランティア 9 人と実施団体の自由が丘商店振興組合の職

ポリネーターが人類に与える恩恵は様々であるが、近年

員 10 人にアンケート票を配布し、回収を郵送形式で実施の都市の拡大が原因の一つとなりポリネーターの減少がした。本研究のアンケート票では養蜂活動の参加頻度(Q1-

懸念されている。しかし、都市環境内でもミツバチをはじ1)、農業・緑地活動の参加頻度(Q1-2)、参加動機「ミツバめとするハチはポリネーターとしての恩恵を、都市環境内

チの保全(Q2-1)」「環境貢献(Q2-2)」「地域貢献(Q2-3)」「食の植物、都市農業にもたらしうることが多くの研究で確認

べ物づくり(Q2-4)」「地域交流(Q2-5)」、ミツバチとの接触されている (Colla, Willis, & Packer, 2009)。これにより、の頻度(農業緑地活動場所：Q3-1、地域内の公園：Q3-2、

都市内でミツバチを飼育することでハチミツの生産以外

地域の街中：Q3-3)、ミツバチプロジェクトの都市への恩にも、都市農業や屋上緑化の恩恵の向上、都市環境の改善

恵の認識「植生の向上(Q4-1)」「農業・緑化活動の活性化が期待される。実際にニューヨークやロンドンなどの世界(Q4-2)」「地域のブランド化(Q4-3)」「地域の注目度の増加

各都市内で、ビル屋上などでミツバチを飼育しハチミツな(Q4-4)」、ミツバチプロジェクト参加後の意識変化「生物どを生産する養蜂活動が確認されている。日本では趣味養や植物(Q5-1)」「地域の活性化(Q5-2)」「地元で取れた食べ蜂の他にミツバチプロジェクトと呼ばれる「都市域におい物(Q5-3)」を回答してもらい、調査結果を分析した。

て、団体が実施する環境保全活動などの目的を持つ継続的

4. アンケート調査結果並びに分析結果

な養蜂プロジェクト」が確認されている(山田, 曽根, 古谷,

アンケート票の回収結果は 2018 年 1 月 9 日時点で、232011)。この活動は 2006 年に銀座で始まり、日本各地の件であった（回収率：23/37、自由が丘 13、銀座：10）。

都市へ広がりを見せている。

そのうち無効票は 1 件、欠損値が含まれているものは 4 件

2. 研究目的であった。図 1 はアンケート調査結果のうち参加動機の本研究は、第一にミツバチプロジェクトへボランティア

集計結果であるが、図 1 では、ミツバチの保全や環境へ

や会員として参加している社会人、実施団体へのアンケーの貢献が参加を後押ししている動機であると答えた回答

ト調査を通じて、ミツバチプロジェクトへ参加した動機、が多いことが確認できる。このことから参加動機の観点か

ミツバチプロジェクトによる都市への恩恵（環境的影響）、

ら環境的活動の側面が強いことがわかる。またアンケート

参加者の意識変化（社会的影響）を調査し、第二にその実調査結果からアンケート票の各質問事項２つを選択して態を把握するとともに今後新たに発足するミツバチプロ

作成したクロス集計表で、フィッシャーの正確検定を行っ

ジェクトの実施方向性を提示することを目的とした。

たところ、「ブランド化(Q4-3)」が養蜂活動（Q1-1）と農業・緑地活動（Q1-2）の活動頻度、多くの参加動機と強い3. 研究手法

関係性を示し（表 1）、養蜂活動の頻度（Q1-1）と公園や本研究では 2006 年に開始した銀座の「銀座ミツバチプ

街中でミツバチを見ること（Q3-2、Q3-3）が生物や植物

ロジェクト」に参加している同プロジェクトの参加者と実への意識変化（Q5-1）と強い関係性があった(表 2)。図 2

施団体を、2008 年に開始した自由が丘の「丘バチプロジ

は農業・緑地活動の参加頻度(Q1-2)、農業・緑地活動場所

ェクト」の参加ボランティアと実施団体を研究対象としてにおけるミツバチとの接触の頻度（Q3-1）、農業・緑化活

アンケート調査を行った。銀座ミツバチプロジェクトでは動の活性化(Q4-2)を係数とした多重対応分析の結果であ

全会員数が不明であるため 2017 年 12 月 8 日に紙パルプ

るが、他の質問項目と比較して高い農業・緑地活動の参加

会館で行われた菜の花交流会にて集まった会員ならびに頻度（Q1.2.1）、高いミツバチとの接触頻度（Q3.1.1）、実

スタッフ 24 名中 18 名にアンケート票を配布、丘バチプ感を伴った都市農業の活性化（Q4.2.1)が互いに近くにプ

ロジェクトでは 2017 年 12 月 19 日に参加している全ボ

ロットされていることが確認できる。

91

5. 結論96968

ミツバチの保全
環境への貢献地域への貢献
食べ物づくり
地域交流

0

8
9
6
7
4
5

10
2 1
2 1
4
1
2 4

10

15

研究対象としたミツバチプロジェクトでは、第一に、ミツバチプロジェクトへ参加したことによる意識変化において、ミツバチとの接触や養蜂活動への高い頻度の参加が、生物や植物への関心を高めていると解釈できた。また第二20にアンケート集計結果から参加動機においては環境的思強く後押しした

後押しした

どちらともいえない

後押ししなかった考が確認できた、が参加者が認識する恩恵の中で地域ブランドの向上と地域の注目度の上昇が多くの参加動機と有

図 1

参加動機

意な関係性があり、かつ認識する恩恵の中で養蜂活動と活動頻度と有意な関係性、または比較的強い関係性があった

表 1

参加動機とブランド化、注目度の認識のは地域ブランドの向上だけであったことを確認した。こ

変数 1

変数 2

P値

のことから、都市内におけるミツバチプロジェクトが都市

Q1-1

Q4-3

0.08

のイメージや独自性を向上しているといえよう。

Q1-2

Q4-3

0.002

Q2-3

Q4-4

0.02

Q2-4

Q4-3

0.01

商業都市のミツバチプロジェクトにおいて、第一に養蜂

Q2-4

Q4-4

0.005

活動のみならず、都市域でミツバチを観察できる環境を整

Q2-5

Q4-3

0.008

えることで、啓もう的効果をより大きくすることができる。

6. 提言

第二に、都市域においてミツバチプロジェクトは環境的活

表 2ミツバチと生物、植物への意識変化動として開始し、その後地域ブランドに関連する人々が潜

変数 1

変数 2

P値

在的な参加者となることを本研究の提言とする。

Q1-1

Q5-1

0.07

Q3-2

Q5-1

0.04

Q3-3

Q5-1

0.01

謝辞
アンケート調査にご協力居てくださったミツバチプロ
ジェクトの皆様に感謝申し上げます。

参考文献
Q1.2.1

Colla, S. R., Willis, E., & Packer, L. (2009). Can green

Q3.1.1roofs

Q4.2.1providehabitat

for

urban

(Hymenoptera:

Apidae)?

Cities

and

bees

the

Environment (CATE), 2(1), 4.
Riza, M., Naciye , D., & Mukaddes , F. (2012). City
branding and identity. Procedia-Social and

Behavioral Sciences, 35, 293-300.
愛甲哲也, 庄司康, 栗山浩一. (2016). 『自然保護と利用のアンケート調査―公園管理・野生動物・観光のための社会調査ハンドブック―』. 築地書館.

図 2

山田順之, 曽根佑太, 古谷勝則. (2011). 都市域の自然体

多重対応分析の結果

験活動としてのミツバチプロジェクトに関する研究. ランドスケープ研究, 74(5), 585-590.

92

Visualization Of Indoor Radio Wave Propagation By Using Augmented Reality
Technology
Student Number: 14B09889 Name: JIAYUE CHENG
Supervisor: Supervisor: Jun-ichi TAKADA Assistant Professor: Kentaro Saito
2018/2/23
1

Introduction

The wireless communication is playing an essential role in
information transmitting nowadays. While because of theradio wave is invisible, it is difcult for users to estimate theradio wave distribution in the room without device.[1] The
focusing point of this thesis is to visualize the radio wave
by using the mobile device, and enables the user know
about the distribution situation of the radiowave in the surroundings. The augmented technology is utilized in thisthesis. Augmented reality technology overlays the digital
object onto a persons perceived reality, and integrates thevirtual world with reality.[2] In this thesis, an augmented
reality (AR) application is developed to exhibit the radio
wave distribution in the indoor environment. The research
divides into two parts: the establishment of the application,and the conduction of the demonstrate experiment. For theestablishing part, in an indoor environment, the radio wave
propagation is calculated by ray tracing method and thenshow the distribution detail in the vertical view graph. Then
using the result data, and develop an AR application by
Unity 3D software. After the establishment, an experimentis conducted in the S6-102 room in Tokyo Institute Technology University to demonstrate whether the application
is running successfully. Moreover, using augmented reality in the application, accuracy errors may occur. Finding
the accuracy errors in this AR application is another targetof the experiment.

2

Figure 1: Vertical view of the radio wave propagation in room
S6-102

3D model of the object, which does not exist in the environment, to the environment model. This process is theway augmented reality works. To develop an applicationin Unity, though the reality pose of the rays is calculatedby ray tracing method, the information should match to thevirtual information in Unity. To coincide the scale of thevirtual world and the reality, experiments are needed to test
the direction of each axis. As a result of an experiment, it
can be found that in the x-axis, the left is the positive direction, y positive is up direction, and z position is from thereal environment to the camera direction.
Another topic is that in the unity 3D, units is used as ameasurement, but it is reference. [3] However, the positionof the rays needs to be input into the unity in units. So
another experiment is established to test the matching relation between the real distance and virtual distance. In thisexperiment, a sphere is put in the tracking point, and at thesame time an arrow is put in the unity position of (200, 0,0) then conduct the application in room S6-102. The distance between the sphere and the camera is decided to be
3m. The result is showing in Fig.2.
Test the real distance between the sphere and the arrow,and the distance is about 0.46 m. In another word, by calculating, we can found the relation between unity units andmeters is about 1 meter ≈ 434.8 units.

Analysing And Design

The ray tracing method is used in analyzing the radio wave
propagation. The Fig.1 shohws the vertical view of theroom S6-102 in Tokyo Institute Technology University. In
Fig.1 Tx indicates transmitter, Rx indicates the location of
the receiver, and the distance between them is 3m. The
width, length, and height of the room are 4.8m, 7.6m and3.0m respectively. The room S6-102 is considered as asimplied indoor environment with only direct ray and rays
reected once off the walls are considered.
The next step is to establish the AR application byunity 3D. As the invisible radio wave signal propagatesin straight direct rays, arrows can be used to represent therays. The direction of the arrows shows the propagating direction of the rays. Then insert the pose information of the‘rays into the Unity 3D.
The Unity 3D software creates a virtual world in the computer, tracking the characteristic points of the environmentand create a 3D model of the environment. Then add the3

ResultIn the experiment, if the transmitters position is considered as the zero point, the position of the rays (I named93shifting in detail, the shifting data CDF is shown as bellow
Fig.5.

Figure 2: Experiment of reality distance to camera distancethem from 1 to 4)are(1.25, 0, 0.75), (1.25, 0, 2.25), (-1.25,
0, 0.75), (-1.25 ,0 ,2.25) respectively. Using the result fromthe last experiment that 1 meter ≈ 434.8 units, we can decide the virtual position of each ray, the virtual position is
showing in the below Fig.

(a) Unity pose information of rays(a) Receiver shifting CDF after
camera rotation

Figure 5: Receiver shifting before and after the movement of thecameraIn these two attempts of the experiment, it can be foundthat the position of the receiver changes indeed after rotating the camera but 90 percent of the shifting is under
0.12m . However, after the moving of the camera for somedistance, the 90 percent of recevier shifting is under 0.8m,
and which is much bigger than that after the rotation. It canbe conrmed that the movement of the camera influent thestability of the receiver, and the form of the camera movement inuence the receiver shifting in different degree. Thisoccurs because of the usage of the gyro sensor. The gyro
sensor measuring the orientation and react to the rotation of
the camera, while it doesn’t correspond well to the translation.

(b) Names of the rays

Figure 3: Information of rays

Then create the radio wave model(arrow model) in theunity, the name of each ray is shown in the Fig.3.
Finally, main experiment is conducted in room S6-102,
and the result is showing in the Fig.4. below.

(a) Front view(b) Left view

5

Conclusion

An AR application aiming at the visualization of the indoor radio wave propagation is developed. In the final experiment, the radio propagating distribution showed successfully on the screen, but some accuracy errors are observed in the process as well. After the camera moves, theshifting of the receiver can be observed in the application.
Because of the distance between the transmitter and the recevier is 3 m, the shifting after camera movement is so significant and cannot be ignored. In the future, other sensor
like distance sensor can be tried to improve the accuracy of
the application.

(c) Right view

Figure 4: Main experiment result

4(b) Receiver shifting CDF After
camera movement

AnalyseHowever, in the experiment, the rays are not correctly
fixed to the point where it should be. As it said above,accuracy errors occur. When moving around in the environment, the ray model shows the trend of unstable. Afterchanging the direction of the camera to observe the rays
in other angle views and then moves it back towards theoriginal direction, position shifting of the receiver can beobserved in the application. To analyze the phenomenon
further, two attempts are tried to make the phenomenon
concrete. First running the application, and record positionof the receiver, then rotate the camera to other angles, andmove it back, then record the position shifting of the recevier again. Next, try the experiment again after moving thecamera in parallel.
Record the results of the receiver shifting before and after
the camera rotation and movement. It can be found thatthe receiver position changes respectively. To analyze theReferences[1] Cem Sahin, Danh Nguyen, Simon Begashaw “Wireless communications engineering education via Augmented Reality Frontiers”
Education Conference (FIE), 2016 IEEE
[2] H Ridho Rahman, Darlis Herumurti, Imam Kuswardayan “Location
basedaugmentedrealitygameusingKudanSDK” Information CommunicationTechnologyandSystem(ICTS),201711thInternational
Conference on[3] Cem Sahin, Danh Nguyen, Simon Begasha “Unity Technologies
https://unity3d.com/cn/

94

WAVELET BASED IMAGE CODING VIA PREDICTION USING NEURALNETWORKS
Department of International Development of Engineering
Student Number: 14B08878 Name: Takuma TAKEZAWA Supervisor: Yukihiko YAMASHITA

1Introduction

ral animals’ brains. The main goal of ANN is to learn amodel between inputs and outputs. A standard ANN
consists of many simple, connected processors calledneurons, and each produces a sequence of real-valued
activations [3]. Input neurons get activated throughsensors perceiving the environment, and other neurons
get activated through weighted connection from previously active neurons. The learning of ANN is to findweights that make the network exhibit desired behavior.
In this research, ANN is used to predict the true
value of target pixels. That is, the goal of this task
is to make a function which outputs the desired true
value from inputs. In this research, outputs are thevalues of target pixels, and inputs are the values of
their neighboring pixels that have been decoded.
In order to solve this problem, I applied the feedforward neural networks (FNNs). It consists of a numberof neurons and several layers. Each unit among thelayers is connected one by one, and each connection
has its weight. Generally, these units are called nodes.

Recently, by the development of multimedia terminals,
a large amount of information is produced every day. It
causes the problems such as the shortage of memories.
Thus, the methods to reduce the data redundancies
have been investigated. For example, image compression technique such as JPEG and JPEG2000 have beendeveloped.
JPEG is one of the most popular methods for image
compression. It is useful but still has a problem calledblock distortions. As a method to solve the problem,
the wavelet-based image coding was invented. Zhou,
et al. proposed to introduce the predictive coding into
wavelet-based image coding [1]. They used linear prediction with clustering as a prediction method.
In this research, I propose to apply the artificial
neural network to the prediction part and conduct experiments to evaluate the proposed method.

2

Image Coding

2.1

Wavelet Based Image Coding

Wavelet-based image coding is one of the image compression methods using discrete wavelet transform (DWT).
Wavelet transform is a method to analyze signals anddivide them into different frequency components. Because digital images are discrete signals, the DWT isapplied and the amount of data can be reduced by encoding the coefficients.
Since this method treats the target signals as oneof the waveforms, it is usually called waveform coding.

2.2

Predictive Coding

Figure 1: Feedforward neural networks

Predictive coding focuses on the correlations between
adjacent signals. For example in natural images, neighboring pixels tend to be positively correlated because
natural image shapes extend over finite spatial regions[2]. And the goal of predictive coding is to reduce
redundancy by removing the predictable components
from original signals.

2.3

Figure 1 illustrates a feedforward neural network.
In this system, information is inputted from the layerof the leftmost (input layer), and it gets activated withweights in each connection and propagates among thelayers from left to right. The model is validated byerrors between the calculated outputs and desired values. Usually, the error is expressed by so-called loss
function. For the loss function, mean squared error(MSE) or cross entropy error (CEE) is used in general. They are applied depending on the problem to besolved. A learning process is continued until the loss

Prediction using Neural Networks

The artificial neural networks (ANN) is a learning system inspired by the biological neuron structure in natu95

function outputs the desirable results.

3

Experimental Results

I used 3 standard images as test data (Fig 2), and 14
standard images as training data. To evaluate the data
size of compressed images, bit rate, the amount of bits
per one pixel is used. Then, the less the value is, themore effective the method is.

Figure 3: Rate-distortion curve for Lenna

Figure 2: Test Data

Figure 4: Rate-distortion curve for Barbara

For prediction, I extracted blocks of the pixels, whose
size is 6 × 3, from the training images. And I iterated
the calculation 10,000 times for every learning process.
Table 1: Bit rates for different training data
Training Data Lenna Barbara Intersection
w/o Prediction
1.861
2.298
2.169
n1
2.221
2.569
2.334
n2
3.085
3.391
2.947
n3
2.952
3.269
2.862
n4
2.930
3.273
2.889
n5
2.741
3.091
2.731
n6
2.364
2.743
2.480
n7
2.981
3.324
2.916
n8
3.249
3.506
3.012
n1-n8
2.773
3.117
2.705
n1-n14
2.184
2.519
2.277
Table 1 shows the results of this experiment. Thosevalues express bit rates for compressed images when
the same quantized factor is used. And Figs 3, 4 and5 show the coding efficiency. But obviously, the best
result is given by without prediction. It implies thatthe prediction is not precise.
Among the results except without prediction, thebest one is produced when 14 images are used as training data at the same time. That is, by using several
images for learning, the generalizing ability of ANN
was improved.

4

Figure 5: Rate-distortion curve for Intersection

the amount of data by using prediction. However, as aresult, any type of ANN just increased the amount ofdata.
As a future work, it is necessary to enhance thegeneralizing ability of ANN. In order to improve ANN,I considered the following attempts. For example, Ichange the hyperparameter of the network such as thenumber of hidden layers, nodes, and iterations have to
be changed. To confirm the validity of the network,cross-validation have to be applied, more images haveto be used for training data.

References[1] Shiyu Zhou, Yukihiko Yamashita, ”Image Coding
using Discrete Wavelet Transform Decomposition
with Prediction of Half-pixel Line Segment Matching”, Proceedings of Picture Coding Symposium ofJapan, no.27, 2013[2] Yanping Huang, Rajesh P.N. Rao, ”Predictive coding”, Wiley Interdisciplinary Reviews: Cognitive
Science, vol 2, pp.580-593, 2011

Conclusions

In this research, I proposed to use ANN for a prediction
part of wavelet-based image coding via prediction. And
the desired goal of this research was the reduction of[3] Jrgen Schmidhuber, ”Deep learning in neural networks: An overview”, Neural Networks, vol 61,
pp.85-117, 201596mEquilibrium Adsorption of Manganese Using Mordenite
Student Number: 10_18887, Name: Shunya Hattori, Supervisor: Ryuichi EGASHIRA and Hiroaki HABAKI
conditions. It was assumed that there was no change inthe volume of the solution and mass of zeolite before
and after the experiment.
Fig. 1 shows the result of XRD analysis. It was
confirmed that the zeolite used was pure mordenite, andthere was no other component.

1. Introduction
The acid mine drainage is acidic wastewatercontaining heavy metal sulfates, generated through theoxidization of metal sulfides at the surface of mineraldeposit with water or air, and polluting the ecologicalsystems. To improve this environmental issue, thetreatment of the acid mine drainage with naturalzeolites has been studied. However, natural zeolites
generally contained several metal ions and so on as
impurities to make adsorption equilibrium more
complicated. [1] [2]In this study, commercially available synthetic
zeolite of Mordenite was used as adsorbent and theadsorption equilibrium was measured to treat with themodel acid mine drainage containing manganese ion.

2. Experimental
The synthetic zeolite of Mordenite was used,purchased from Wako Pure Chemical Industries (HS690, Powder, Hydrogen Mordenite). To measure thecation exchange capacity (CEC) of the zeolite, 4g ofzeolite was contacted with 30mL of 1M aqueous
ammonium acetate (NH4OAc) solution and shaken for
5 minutes. After phase separation using centrifuge,
fresh 30mL NH4OAc solution was added to the solid
phase and this operation was repeated 10 times, basedon the Method-9801 by the US Environmental
Protection Agency. Table 1 shows the conditions ofadsorption equilibrium measurement. In advance, thezeolite was kept at 383K for more than 24 hrs in orderto dehydrate. The solutions were prepared bydissolving MnSO4 ∙ 5H2O and deionized water. The
specified amounts of zeolite and solution were
contacted at 300 K for 240 hrs to be equilibrated.
The liquid phases were analyzed by pH
meter(Horiba,F-74 ) and ICP-AES(SPS7800, SII Nano
Technology) to determine the pH and metal
concentration, respectively.

Fig. 1 Result of XRD analysis

Table 2 shows the result of CEC measurement.
The CEC of the pure mordenite was lower than that ofBogor natural zeolite. Compared with theoretical CEC
of ideal pure mordeite(23 × 10-4mol/g-zeo),it was
lower too [4]. The zeolitesystem
was originally treated by acidsolutions, and this should lower the CEC of the zeolite[5].
Table 2 cation exchange capacity

Fig. 2 shows the changes in pH before and after
systemadsorption equilibrium measurementof pure mordenite
and Bogor natural zeolite [1] [2]. For the Bogor zeolite,
the pH at equilibrium become 7-8 which was higher

Table.1 Experimental condition of Batch adsorption
pH of feed solution

[-]

2-5

Volume of feed solution[L]

50 × 10-3-4

Initial concentration of Mnsystem[mol/L] 9.1×10 -1.8×10
Mass of zeolite
Contacting time[g]
2.5[hours] 240

Temperature

[K]

-2

300

3. Results and discussion
Material balance of batch adsorption is shown as,
Ci,0V0+qi,0 S0 = CiV+qiS (1)where Ci V, S, and qi are the concentration ofcomponent i , volume of the solution, mass of zeolite
and adsorbed amount of component i per unit mass ofzeolite. The subscript of 0 stands for the initial
Fig. 2 Change of pH at initial and equilibrium97

than initial. For the pure mordenite, the pH atequilibrium become lower than initial when intial pH
were 3 and 5. The pH at equilibrium were almost
constant, ranged from 2.6 to 2.8 in the cases that theinitial pH were 3 and 5. The hydrogen ion in themordenite might have been exchanged with Mn2+ ion
and this made the pH lower. When the initial pH wasset at 2, the equilibrium pH was the same as the initialone. The H+ concentration was so high that the amountof the H+ desorbed was negligible.
Fig. 3 shows the molar concentrations of the metal
ions at equilibrium, desorbed from the zeolite.
Although Na, K, Mg and Ca were detected, theirFig. 5 Adsorption isotherms of manganesethe desorbed ion could not be appropriately calculated.
Fig.5 shows the adsorption isotherms of Mn withmordenite and natural zeolite from Bogor[1][2]. The qi
of Mn increased as CMn and pH increased. The qi of Mn
systemwith mordenite were much
lower than those with Bogor
zeolite. The equilibrium pH was much lower withmordenite and H+ should be competitively adsorbed. In
the cases of low initial pH, adsorption amount of Mn
was lower.

Fig. 3 Concentrations of cations at equilibrium

concentrations were much lower than those of H+ or
Mn2+ and the effects of these ions on H+ or Mn
adsorption must be small.
Fig. 4 shows the charge numbers of the cations
due to adsorbed on and desorbed
system from the zeolite. The
charge numbers of adsorbed ion, Mn2+, were almost
balanced with those of desorbed ions, H+, Na+, K+,
Mg2+ and Ca2+. However when initial pH=2, the charge
numbers were not balanced. This might be because
when initial pH=2, the concentration changes of H+,
Na+, K+, Mg2+ and Ca2+ were so small, the amount of

4, Conclusion
XRD pattern showed that the zeolite was puremordenite and the cation exchange capacity wasmeasured as 6.94×10-4 mol/zeo-g. Mordenite could
remove the manganese in the solution and it lowered
the pH. Manganese in the solution was exchanged with
H+ in the zeolite to reduce the pH. The initial pH of thesolution affected the adsorption of Mn and the amountof Mn adsorbed decreased as pH decreased. The pH at
the equilibrium affect the adsorption of Mn due to thecompetitive H+
References[1]Fernando, master Thesis ,Tokyo technology ofInstitue(2015)[2]Hasegawa, master Thesis ,Tokyo technology ofInstitute(2017)[3]Chapman, H. D.; Chemical and Microbiological
Properties, C. A. Black ed., pp. 891–900, U.S.A. (1965)[4]Nishimura, Journal of the Clay Science Society ofJapan, vol13, No1, p23-34(1975)[5]Sakamoto , The chemical Society of japan,p.874882(1994)

Fig. 4 cation balance of the batch adsorption
98

オセアニア島嶼諸国における水道事業の効率性分析
学籍番号：14B05785

1.
1.1.

氏名：国分 絋一郎序論

指導教員：阿部 直也

としては①一人当たりの水の生産量②接続数③1000 接続当たりの従業員数④水の生産コスト⑤NRW2率を使用

背景

水道事業の整備と運営は世界的に重要なテーマのした。

一つであり、持続可能な開発目標（SDGs）の目標 6「す2.2.

べての人に水と衛生へのアクセスと持続可能な管理を分析の手順

水道事業者の効率性を以下の 3 段階で分析する。①

1確保する」に象徴されている通りである。全ての地域 でと②は定量的に、③では定性的に分析する。

飲み水と衛生施設へのアクセス率が伸びているなか、① 主成分分析（PCA）とクラスター分析を用いて対象とオセアニアの島嶼諸国だけはその状況が悪化している。

なる水道事業者が存在する国を分類

2000 年から 2015 年へ、飲み水へのアクセス率は（56％② DEA を用いて各水道事業者の効率性を算出→52％）低下し、衛生施設へのアクセスは(35％→35％)③ ①と②で得られた結果と各種報告書による社会文

変化していない [1]。オセアニアは島嶼諸国という大き化的側面を組み合わせてオセアニアの水道事業者

な特徴を持っており、一般的な開発途上国とは性質がをより大局的に評価異なる。1 つ 1 つの島が小さいことによる資源や人材の2.3.

不足をはじめ、激しい気候変動による大きな被害、複雑本研究が適用する DEA（Data Envelopment Analysis：

な統治などで、水道事業の整備と運営は様々な困難に包絡分析法）は、複数の入力と複数の出力を伴う財や直面している。近年は IWRM（統合的水資源管理）というサービスの生産・提供事業体(Decision Making Unit：

水以外のあらゆる要素を組み込んだ統合的な水資源管

DMU)の効率性を評価するための分析方法である。各理の枠組みが注目されており、限られた資源を有効にDMU の相対的優位性を取り入れた評価が可能である。

活かしながら人々の水へのアクセスを高める必要がある。

本研究では最も基本的な CCR モデルを使用した。以下

そのため、各島嶼国の水道事業の実態について、相対の分数計画問題を解くことでそれぞれの DMU の効率的な優位性や課題を客観的に把握することが重要にな値が得られる。𝑣𝑖 (𝑖 = 1,2, ⋯ 𝑚)と𝑢𝑟 (1,2, ⋯ , 𝑠)はそれぞっている。

れ入出力につけるウェイトであり、記号 o は n 個の事業

1.2.

体のどれかを指す。式(2)はウェイト𝑣𝑖 と𝑢𝑟 による入出力

目的

上記の背景を踏まえ本論の目的は以下 2 点である。
の比を全ての DMU について 1 以下に抑えるという意味

各島嶼国における水道事業の運営効率性を比の制約式である。

較・評価することmax⁡(𝜃, 𝑢, 𝑣)⁡θ =各国の水道事業の実態を定性的な側面から水道事業の発展に必要な方策を提案すること

制約式

本稿では、主に第一の目的について記載する。

2.
2.1.

DEA について方法

𝑢1 𝑦1,𝑜 + 𝑢2 𝑦2,𝑜 + ⋯ + 𝑢𝑠 𝑦𝑠,𝑜𝑣1 𝑥1,𝑜 + 𝑣2 𝑥2,𝑜 + ⋯ + 𝑣𝑚 𝑥𝑡,𝑜𝑢1 𝑦1,𝑖 + 𝑢2 𝑦2,𝑖 + ⋯ + 𝑢𝑠 𝑦𝑠,𝑖≤1
𝑣1 𝑥1,𝑖 + 𝑣2 𝑥2,𝑖 + ⋯ + 𝑣𝑚 𝑥𝑚,𝑖

式(1)

式(2)

(𝑗 = 1, 2, ⋯ , 𝑛)

分析対象および使用データ

本研究の分析対象はオセアニア 13 か国とそれらの国における 18 の水道事業者である。各国の情報として①𝑣1 , 𝑣2 , ⋯ 𝑣𝑚 ≥ 0

式(3)𝑢1 , 𝑢2 , ⋯ 𝑢𝑠 ≥ 0式(4)水道事業は多くの場合そのコスト削減に関心があるため

面積②人口③一人当たりの GNI④水の普及率⑤一人

本研究では出力を固定した、入力指向型を採用した。

当たりの水の消費量を使用した。各水道事業者の情報
1

国連によって分類された地域分けに基づく。

2

99

NRW(Non-Revenue Water)：収入が得られない水。

3.

結果と考察

〈表 1〉は、各 DMU の効率値とその優位集合を示して対象国を国の規模と水道事業の発展度合いの 2 ついる。フィジーやバヌアツを含む 7 社で効率値 1 を取り、の基準で分類した〈図 1〉。PCA で使用した面積と人口

ミクロネシア 1 は 5 社中最も多い 10 社に優位とされ、次が国の規模を示す軸として、またその他 3 つの要素はそいでフィジー・バヌアツは 7 社に優位とされた。ミクロネシの国の水道事業レベルを示す軸として解釈ができた。

ア 3 とニューカレドニアは 2 社と、あまり優位にされていないことから個性的な DMU であることが分かった。優位集合の共通点としてどの 5 社も NRW 率が良いことが挙げられる。入力においてミクロネシア 1 とフィジーが NRWに強みを示す一方、バヌアツは従業員数でも強みを持っていた。出力においてはフィジーだけが接続数に強みを持っていた。同じ国でも効率値が著しく異なる DMUについて、ミクロネシアは 4 つの州に分かれており、ミク
ロネシア 1 と 4 は同じ州に存在するが、1 のほうが規模の面でははるかに大きい事業である。4 が他者に参照され

図 1 各国の分類ない理由もそこにあると考えられる。2 では水道料金を徴収しておらず、水道メーターの故障も頻繁に見られる。

表 1 各水道事業者の効率値と優位集合
水道事業者

効率値

2 の効率値が低い理由もそこにあると考えられる。

優位集合〈表 2〉は各 DMU をより大局的に見たときの結果であ

フィジー

1.00

-

バヌアツ

1.00

-

る。この表から各 DMU の効率値は国の規模とその国のニューカレドニア

1.00-

水道事業レベルの両方に正の相関があることが分かっ

サモア

0.74

Mic.1,Fiji,Van

仏領ポリネシア

0.32

Van, Mic.1, Fiji

米領サモア

0.56

Van, Mic.1

パラオ

043

Mic.1, Mic.3, Fiji

パプアニューギニ 1

0.57

Van, Fiji, Mic.1

パプアニューギニ 2

0.37

Mic.1, Fiji, Mic.3

ソロモン諸島「0.37

Van, Mic.1, Fiji

マーシャル諸島 11.00-

必要があることが分かった。さらに各社で異なるが、従ミクロネシア 11.00-

業員数、接続数あるいは水の生産量を改善することでミクロネシア 4

1.00-

それぞれの効率値は向上する。DEA 効率値は相対的

ミクロネシア 3

1.00-

ミクロネシア 2

0.33

Van, Mic.1

トンガ

0.25

Van, Mic.1, Fiji

進国と比べれば効率的と言うことはできない。各社はよ

キリバス

0.08

N.C,Mar.1,Mic.1.

り効率的な事業を目指すと同時にオセアニア全体としてマーシャル諸島 2

0.04

N.C

た。理由として面積や人口が大きいと人材や水資源が豊富になることが考えられる。ミクロネシアとマーシャルの効率的な 4 社を除くとその値はより顕著になった。

4.

DEA の結果、全ての水道事業者が NRW を改善するな効率値である。オセアニア内で効率的であっても、先さらなる効率化に努める必要がある。また、水道事業は技術的側面が全てではない。オセアニア地域は社会文

表 2 グループことの効率値の主要値化的な面で他国にはない固有な特徴があり、それが発

平均値

最小値

最大値

A) 規模大・先進

0.81

0.32

1.00

B) 規模小・先進

0.50

0.43

0.56

C) 規模大・途上

0.44
0.59
(0.18*)

0.37
0.04(0.04*)

0.57
1.00(0.33*)

D) 規模小・途上

結論

展の障壁になっていることも事実である。本研究では多くは扱えなかったが、それらを統合したより包括的な分析も必要である。

参考文献[1] WHO., UNICEF. (2017). Progress on Drinking-Water,(*)効率値の高い上位 4 水道事業者を除いたときの値

Sanitation and Hygiene. UN-Water.

100Influence of Speed of Gate Opening in Dam-break Experiment
Student Number: 14_12880

Name: Fumitaka Furukawa

Introduction
The aim of this study is to examine the influence of
speed of gate opening in a dam-break experiment.
“Dam-break” is a simplistic method to generate a rapid
water flow which is induced by releasing water column
in the reservoir being held with a gate. This type ofexperiment is often applied to an experiment with theaim of generating tsunami-like waves. By pulling thegate in a short time, an intensive flow can be generated.
However, little attention has been given to themechanism of the gate in dam-break analysis. In thisstudy, how the gate can affect the flow of water was
examined.

Supervisor: Hiroshi Takagi

1Figure 1 without gate model (unit: m)

Numerical Analysis with OpenFOAM
In this study, two types of gate opening werereproduced using OpenFOAM analysis. The first
method (Case 0) is to make the gate disappear
instantaneously (i.e., without consideration of thetransition of opening), and the second one (Case 1) is tocontrol the rate of gate’s opening in accordance withseven different scenarios as shown in Table 1.
In
OpenFOAM
analysis,interFoam andinterDyMFoam were used as solver for two
incompressible fluids. The interFoam solver is applied tothe model without gate control, while interDyMFoam isapplied to the model with gate control. These two solvers
are made for analysis of two phase fluid and VOF(Volume of Fluid) method is used for tracking andlocating the free surface. The interDyMFoam wasadopted because it enables computational meshes to bemodified as the time step advances, which is suitable forreproducing the transition of gate opening.
Figs 1 and 2 are the schematic diagrams of eachmodels.
The pulling speed of the gate was calculated using
the following sinusoidal function.
2𝜋𝑡𝑣 = 𝑣0 sin⁡( )𝑇

Figure 2 with gate model (unit: m)
Table 1 simulation models
case
w/o gatewith gate(v 0 (cm),T (s))

T gate (s)

case0

-

0

-

case1-A(32.5,1.75)

0.9

21.02

case1-B(30.0,2.0)

0.95

18.52

case1-C(27.5,2.25)

1.05

16.8

case1-D(25.0,2.75)

1.1

14.7

case1-E(22.5,2.75)

1.2

13.15

case1-F(20.0,3.0)

1.25

11.32

case1-G(8.2,6.0)

2.3

4.37

V gate (cm/s)

3
Results
3.1
The gate condition
In Table 1, Tgate indicates the duration for pulling the gatefrom a static condition till a position high enough. The
mean rate of the gate opening, vgate, is calculated by𝑣𝑔𝑎𝑡𝑒 =

𝑥𝑔𝑎𝑡𝑒
𝑇𝑔𝑎𝑡𝑒

(2)

where xgate is the vertical distance over the time of Tgate.
3.2

(1)

Water velocity

Figure 3 shows the peak velocities at 2.5 m and 3 m fromthe front of the water column. The difference of watervelocity among six cases, 1-A to 1-F, is within ±1%,which are remarkably small compared to thosedifferences with case0. Thus it is considered that a slightdifference in the opening speed of the gate does not
significantly cause change in flow velocity in the flume.
However, compared with 1-G whose gate is opened
relatively slow, water velocity of 1-G is about 10% lessthan the other with gate control cases. Furthermore,⁡ ⁡ ⁡ In the simulation for “with gate model”, totally sevencases have been used, and for each case has uniqueparameter v0 and T from (1). The following table shows
the combinations of (v0 ,T).
OpenFOAM was also used to calculate water pressure
and water velocity for all cases.

101

velocities differ considerably between with and without
gate controls. Water velocity of 1-A to 1-F is reduced byabout 15% and that of 1-G is reduced by about 25% incomparison with the scenario without gate control.

Xequal denotes the distance from the front of the watercolumn to the point where the pressure curve without
gate control intersects with a pressure curve with gate
control.
This figure demonstrates a strong relationship between
Tgate and Xequal, which is confirmed by a high value of R2(=0.956). The relationship is represented as
𝑋𝑒𝑞𝑢𝑎𝑙 = 1.4907𝑇𝑔𝑎𝑡𝑒 + 0.2359(3)

Although it should have to do with various otherconditions such as flume geometry, bottom friction, anddischarge volume, these simple fomulas will bebeneficial in carrying out a dam-break experimentbecause water pressures monitored in the experiment canbe converted to those without gate control, which iscommonly assumed in a numerical modelling of dambreak test.

Figure 3 peak of water velocity
3.3
Water pressure
Figure 4 shows the peak of water pressure at every 0.5m
point from the front of the water column. Here thehorizontal axis and vertical axis denotes the horizontal
distance from the gate and the peak water pressure,respectively.
Figure 5 shows the peak pressure without gate control
that intersect those of with gate control, focusing on therange from 1.6 m to 2.3 m in Figure 4. The peak pressureof case 1-A to 1-F intersect that of case 0, but pressure
peak of 1-G does not intersect it as far as observed in this3m geometry.

Figure 6 Tgate-Xequal.
5
Conclusion
It was confirmed that the speed of gate control is one of
the influential factors in a dam-break experiment. If thegate speed is considered, water velocity is reduced byabout 20% and the pressure become larger than that ofwithout gate control.
References[1] J.C.Martin and W.J.Moyce “Part V An Experimental
Study of the Collapse of Fluid Columns on a Rigid
Horizontal Plane, in a Medium of Lower But
Comparable, Density” The Royal Society,1952

Figure 4 water pressure peak[2]松田信彦、千田優、岩本浩明、江口三希子、武田将英“電動式スルースゲートを用いた段波造波
特性”海洋開発論文集 vol.33,2017

Figure 5 peak of water pressure (extract)4
Observation
Figure 6 shows the comparison between Tgate and Xequal.

102

Characteristics of the Users of Residential Photovoltaic and Energy Storage
Systems in Japan
Student Number: 14_14146 Name: Hiromichi MITANI Supervisor: Naoya ABE
1. Introduction

2. Objective

Renewable energy is defined as “Energy derived fromnatural processes (e.g. sunlight and wind) that are
replenished at a faster rate than they are consumed” [1],and solar power, wind power, hydropower, geothermal,
and biomass are common as renewable energy. The
utilization of those energies has become more importantas the importance of combating climate change by
reducing the consumption of fossil oils has become
critical. It is, however, well-know that some of therenewable energy system have their inherent limitationsin terms of stable generation of energy, notably electricity.
For example, photovoltaic (PV) system highly depends on
weather conditions. It is also critical for a grid as a whole
to maintain the balance between demand and supply
simultaneously. Even for a consumer of electricity, it has
become more important to have means to control his/her
consumption pattern of electricity as the retail market has
been liberalized and now there are more and more optionsof how people use electricity. Therefore, while we need todefuse more renewable energy systems in a society, we
also need to implement some measures to keep grids
stable and functional as well as to provide means to
consumer who wish to enjoy more flexibilities of how
they could use electricity.
Energy Storage System (ESS) is a good measure topromote renewable energy because it can make up for
shortcomings renewable energy has. ESS can store
surplus electricity that renewable energy generates
excessively, and it can release the electricity inside when
renewable energy plants cannot generate enoughelectricity. ESS could provide back-up power when the
distribution of electricity is cut due to natural disastersuch as earthquakes. Through those functions, ESS willcontribute to renewable energy diffusion, mainly for PV
systems. However, ESS for households is still too
expensive and it diffusion is still at an early stage. Little
is known about the motivation of the users who havealready purchased or used PV and/or ESS.so that it isimportant to understand who actually purchased and how
they find the systems.

The objectives of this study are,Capacity(PV)(10^3 kW)

グラフ タイトル

1.
2.

For those ends, the interviewees are selected through aninternet-based question, followed by group interviews.

3. Methodology
Internet-based inquiry was sent to the registered tester ofa Japanese marketing firm to recruit the interviewees forthe group interviews to those who have already installed
PV and/or ESS. The flow of the selection of theinterviewees was conducted as shown in Fig.2.

Selection of the interviewees throughinternet-based inquiry (number ofregistered tester: 85,449)
Number of respondents: 3,318
Eligible testers who
own PVs and/or ESS
at detached-house: 72

13 people wereselected and joined
the interviews.
Fig.2: The flow of the selection of interviewees
To clarify the similarity of the invited interviewees,
cluster analysis was conducted for the 72 eligible testers.
Multiple correspondence analysis was also conducted toclarify the common attributes of the interviewees. By
combing the results of the two analyses and the groupinterviews, this study will obtain findings according to theobjectives.

Capacity(ESS)(10^3 kWh)

45,0001,000

40,000900

35,000800
700

30,000600

25,000500

20,000400

15,0004. Findings

300

10,000

200

5,000

100

0

Fig.3 and 4 show the results of cluster analyses of 72
testers who have installed PV and/or ESS system basedon the Internet-based questions, and correspondence
analysis of interviewees of group interviews who haveinstalled ESS based on paper-based questions in Table.1.

0
FY2011 FY2012 FY2013 FY2014 FY2015 FY2016
PV system

to clarify how the users of residential PV and ESS
systems recognize their own systems
to find out any obstacles for further diffusion of PV
and ESS at household level

Lithium ion ESS

Fig.1: Cumulative capacity of PV and ESS system inJapan (Source; [2], [3])103

Table 1: Variables used for analysis
Types of Analysis
Variables used for analysis
Cluster Analysis •Age… (1)•The number of children… (2)•Commute time (one-way)•
Working time per day•
The number of working days
per week… (3)•Annual household income
Correspondence •(Variables above)
Analysis•Economic benefits from
PV/ESS… (4)•Degree of satisfaction toward
PV/ESS… (5)•Awareness of saving
electricity•
Sensitivity to electricity rate
… (6)•Degree of satisfaction towardcurrent life… (7)As a result of correspondence analysis, it was found thatthe degree of satisfaction toward PV system/ESS, age, thenumber of children, and attitude to electricity rate wasplotted nearly and that the degree of satisfaction towards
current life and economic benefits from PV system/ESS
were also plotted nearly.

The general findings of the group interviews weresummarized as in the following. As for economic benefits
from PV/ESS, 9 out of 13 answered they had economic
benefits. As for degree of satisfaction toward PV/ESS, 10
out of 13 answered they were satisfied with their own
system. Regarding awareness of saving electricity andsensitive to electricity rate, younger interviewees
answered they felt it burden more than older interviewees.
As a result of the cluster analysis, the testers wereclassified into three groups. The interviewees of the groupinterviews were circled with colors. Seeing the colored
circle, it is found that the interviewees were scattered into
all groups, not distributed biased. It means that theinterviewees of the group interviews were not so biased
group. Group I is the group that most of the testers are in
the thirties and forties and the average of commuting time
and working time per day is very high among three groups,
and that all of the testers in this group have their PV
system. Group II is the group that the age of the testers inthis group is scattered, and that the average annual
household income is the lowest, the average number ofchildren is the highest of three groups. Group III is thegroup that most of the testers are in their fifties and sixties
and the average annual household income is quite higher
than other two groups.

Fig.4: Result of correspondence analysis

Variables (1), (2),(3), (5) and (6) wereplotted nearly

Variables (4) and (7)were plotted nearly

5. Conclusion
This study obtained the following conclusions.
1.

2.

The users of residential PV/ESS recognized theirown systems as good systems, but the benefits they
can get from ESS were not so well known as thatof PV among those who didn’t have ESS.
It was found that the expectation for PV/ESS was
different from person’s age, life stage, having
children or not, and commuting or not. Thus, forfurther diffusion of PV/ESS, measures taken it into
consideration would be necessary.

References
[1]
[2]
[3]

International Energy Agency. IEA website, FAQs,
Renewable energy.
資源エネルギー庁. (2017). なっとく！ 再生
可能エネルギー 固定価格買取制度 情報公表用ウェブサイト.
一 般 社 団 法 人 日 本 電 機 工 業 会 (JEMA).
(2017). 定置用リチウムイオン蓄電システムの出荷実績 2011 年度～2016 年度

Fig.3: Result of cluster analysis

104

Possibility of Tethered Aerocapture for direct orbit insertion
Student Number：14 04099

1

Name：Saho KatoIntroduction

Payload mass of a spacecraft is limited by performanceof a rocket. The spacecraft has many observation instruments and a lot of fuel to enter into an orbit of planet.
In case of Magellan spacecraft, the fuel and thruster occupied 30% of total mass of the space craft[1].
A new way to enter into an orbit around a planet, in
stead of a thruster system, is Aerocapture has been studied. Aerocapture uses aerodynamic drag to enter into
the orbit. Spacecraft must be equipped with heat shield
to protect the payload from heating and force. However,method needs acceleration at apoapsis.
Tethered aerocapture is an alternative way to enter
into orbit by using atmospheric drag. This system has
an aero-device at the end of tether. In this way, spacecraft needs neither the heat shield nor the thruster.

Figure 2: Motion equation modelµv
Tcos(θt )d2 x= − 2 cos(θ) − Dcos(θv ) −
r
m
dt2

(1)

d2 y
µv
Tsin(θt )2 = − r 2 sin(θ) − Dsin(θv ) −
m
dt

(2)

D=

2

Supervisor：Daisuke Akita

Mission Concept

Figure 1 shows the mission scenario.
1 The aero-device is separated from the orbiter with⃝
deployment of the tether before entry.
2 Deployment of the tether is finished before entry enter⃝
into Venus atmosphere.
3 Aerodynamic force begins to aﬀect the aero-device.
⃝
4 The orbiter is decelerated by tension of the tether.
⃝
5 The orbiter cuts oﬀ tether when the orbiter finishes⃝
deceleration.
6 The orbiter goes on elliptical orbit around Venus.
⃝

ρ(r)v 22β

(3)

T = k(l − L)(l ≥ L)(4)

T =0(l ≤ L or after tether cut oﬀ)

(5)

t [s]
: time from entryv [m/s] : velocity of pointµv [m3 /s2 ] : standard gravitational parameter of Venusr [m]: distance from center of Venusθ [deg] : point angle from the X-axis
γ [deg] : velocity angle from the X-axis
α [deg] : tether angle from the X-axis
m [kg]: mass of pointρ [kg/m2 ]: atmosphere density
β [kg/m2 : ballistic coeﬃcientk [N]: spring constantl [m]: distance between orbiter and aero device
L [m]: initial tether length

The equation is numerically calculated by 4th order
Runge-Kutta method to estimate trajectory of the orbiter and the aero-device. Initial condition of the orbiter
is following values.
Figure 1: Mission scenario
mo [kg]: mass of orbiter, 1000[kg]The purpose of this study is to verify the tethered
Ho [km]: initial altitude of the orbiter, 230 [km]aerocapture for planetary orbit insertion.
vo [m/s] : initial velocity of the orbiter
θo [deg] : initial angle of the orbiter, 90[deg]γ0 [deg] : initial velocity angle of the orbiter
α0 [deg] : tether angle of orbiter[deg]3

Motion Equation and Initial
Mass of the aero-device is md [kg]. Initial γ0 of aerodevice is same one. Initial condition of the aero-device
Conditionis given by L, γ, α . In this study L, γ, α and m are00dMotion of the orbiter and the aero device are consid- parameters.
ered in cartesian coordinate system as shown in Figure
Trajectory Results
2. Venus gravity, aerodynamic force and tension from 4
Characteristics of α0 , L, d and md are evaluated. In
the tether act on the orbiter and the aero-device. The
motion equation of the orbiter and the aero-device are this study, the evaluation criteria are mtotal (tether mass
+ aero-device mass)[kg] and corridor ∆γ. It is preferredgiven by Eq.(1)-(5).
105that mtotal is low and ∆γ is high in their values. In thisstudy, standard parameter are given in Table1.
Table 1: Standard Parameterparameter
value
α0
[deg]
90
L
[km]
40
d
[mm]
2.0
md
[kg]
100
β
[kg/m2 ]1

When α0 =90 [deg], γmin (γmin means requisite minimum path angle) is the lowest. Because apparent tether
length for orbit is the longest when α0 =90 [deg]. It is
used that α0 =90 [deg] in following part.
L is changed from 30 [km] to 50 [km] in this part. ∆γ
increases with increase of L as shown in Figure 3. Because the longer L is, the lowest aero-device can be got
aerodynamic force in initial path angle. But the longer
L is, the stronger aerodynamic force is. So γmax is decrease with increase of L. Compared of decreasing ofγmin and γmax , γmin decreases more than γmax . And∆γ increases with increase of L.

Figure 5: md vs γ and ∆γ:L=50[km]In summary, optimum
point of α0 is 90 [deg]. Lshould be long and d sholud be thick within the limited
total mass. md isn’t eﬀective for getting larger corridor
when L is long.
Three limiting conditions on trajectory calculating are
considered.
• Minimum altitude of orbiter is above 160 [km] [2].
• Total mass(mt + md ) is 363 [kg] or less [1].
• Corridor is 0.1 [deg] or more.
Based on estimation the parameters are set to be
α0 =90[deg],md =0 [kg] . Figure6 shows corridor withchange in L and d. Red area means total mass is above
363 [kg].

Figure 3: L vs γ and ∆γ
d is changed from 1.5 [mm] to 2.5 [mm] in this part.
Figure 6: Corridor with changing L and d∆γ increases with increase of d as shown in Figure 4.
Green area means that corridor is over 0.1 [deg].
Because increasing of d, tether can endure strong tension
in higher initial path angle as shown in change of γmax . Tether mass in Figure6 is the lowest when L=57 [km]When d is low, tether can’t endure tension. So d must and d=1.6 [mm]. Tether mass is 176 [kg] which is below
be high above a certain value. In conclusion, L and d that of thruster system.
must be high for getting larger corridor.

5

Conclusion

It is shown that tethered aerocapture is able to entry orbit around Venus. Tethered aerocapture may provide mass reductions over thruster systems. A problemof this method is aerodynamic heating on tether. The
aero-device could be used as a heat sink to reduce thetemperature of the tether.

References[1] Charles D. Brown. ”Elements of Spacecraft Design
Charles”. AIAA Education Series, 2003, 615p.
[2] Toshio Kawasaki. ” 宇宙航行の理論と技術”. TijinFigure 4: d vs γ and ∆γ
shokan, 1986, 347p.
md is changed from 0 [kg] to 200 [kg] in this part.
When L is high, ∆γ doesn’t increase eﬀectively with [3] Mary Kae Lockwood and Brett R. Starr.
”System Analysis for a Venus Aerocapture
increase of md as shown in Figure5. Because Compared
Mission”.
NASA/TM-2006-214291,
L-19237,of decreasing of γmin and γmax , the change is same. The
https://ntrs.nasa.gov/search.jsp?R=20060010899,
higher md is, the larger S(surface area of aero-device )(cited 2018-1-17)
is. But The higher md is, the stronger tension is. In
conclusion, md isn’t eﬀective when L is longer.
106

TIV APPLICATION TO
SIMULTANEOUS MULTIPLE SURFACE OBSERVATION
Student Number: 14B01327 Name: Yoji ISHIBASHI Supervisor: Manabu KANDA, Atsushi Inagaki
shoot the target from diﬀerent directions. SC5200 and
FSV1100 were installed to validate the TIV velocity
from Lepton 3.
The sonic anemometer MODEL 81000 (R.M. Young
Company) was installed at 3 m above ground and 3 m
downwind from the leeward facet. 13 thermocouples(Type-E) were attached to the center of each surfaces
and floors surrounding the block. Both observations
were recorded at 10 Hz.

1 Introduction
Air flow at the near surface has influence on human
lives in terms of pollutant transport or thermal comfort. It is important to understand how the wind blowsin pedestrian levels or in urban canyons. However,complex urban building structures make the wind fieldso complicated. To observe this spatial wind distribution, several observation methods are developed.
PIV (particle image velocimetry) has great contribution to observe 2D wind structure in the building
canyon.[1] While PIV should disperse small particles
as tracer and using laser to illuminate particles, andit limit to do PIV out or daytime observation.
TIV (thermal image velocimetry) is one of the methods measuring wind field. It can estimate wind velocity at the near surface by tracking the temperature perturbation region from thermal images. Thismethods applied to wind field on the wall of building
or schoolyard covered with artificial turf.[2] Althoughthese observation has great contribute to develop TIV,
air flow structure surrounding the building will be limited by the viewing angle of the thermal camera.
TIV has potential to observe real wind flow in theurban canyons. In order to overcome this, simultaneous TIV measurements should be conducted on multiple surfaces.
Objective of this research is to build an inexpensive
simultaneous observation system, evaluate its applicability, verify the system by comparisons with numerical simulations or previous PIV observation results,
and investigate wind flow around a cube block.

Fig. 1 Appearance of target block in COSMO

3 Analysis Method
3.1 Data preprocessing
Preprocessing multiple thermal infrared images
taken by the thermal cameras were necessary. In
particular, filling lacking data and correcting lensdistortions were conducted.
Temperature data lacking from the Lepton 3 measurements were complemented by linear interpolationof the nearest valid frames. Then, lens distortion due
to close distance from the target was eliminated. Finally, homographic transformation was done to normalize each camera.

2 COSMO Observation
The observations were implemented at the outdoor
urban scale model, COSMO on 13th of December
2017, from 1055 JST. The target block is a cube witha 1.5 − m side and made of concrete and covered
with styrofoam board with 20 − mm thickness(Fig.1).
Styrofoam board make the temperature perturbationon the surface large due to its low heat capacity.
It becomes easier to catch by the thermal infrared
cameras.
The equipments which used in this experiments
were thermal infrared cameras, sonic anemomteterand thermocouples.
The thermal infrared cameras which used in thisstudy were Lepton 3 (FLIR Systems, Inc), SC5200AIT (FLIR Systems, Inc) and FSV-1100-L8 (Apiste
Corporation). In order to obtain several thermal image of target from diﬀerent directions, we need to construct an inexpensive system of thermal cameras, anadded originality of this study. Lepton 3 is a coremodule of infrared camera which adopts uncooled microbolometer. Although it has only lower sensitivity and frame rate than SC5200, it is nuch cheaperand enough for this system. Already tested in TIV,SC5200 adopts cooled Indium Antimonde (InSb) can
provide high sensitinity and accuracy with high frame
rate but it costs much. FSV1100 is mid-grade of two
and it adopts uncooled microbolometer with high resolution. This experiment use 11 Lepton 3 cameras to

3.2 TIV
Multiple thermal infrared cameras provide thermal
images of each surfaces. TIV process can be divided
into two parts; extracting temperature perturbationand correlation analysis. Averaging time to extract
temperature perturbation was set to 0.5 s. Integration
domain size is 7×7px(0.26×0.26 m) and search domain
size is 8 × 8px(0.30 × 0.30 m).

4 Observation Results
The wind was around 3 m s−1 northwesterly at theheight 2H. Stability parameter z/L was around 1.39
derived from the data obtained from sonic anemometer, and it indicates stable.

4.1 TIV Vectors
Temperatrue perturbation at the north-facing surfaces was too little to extract perturbation by wind
because the intensity was almost same as noise. TIV
vectors were derived for southern and top surfaces.
Each surfaces had been taken by two types of thermal infrared camera. TIV wind vectors obtained from
one thermal camera shows good correlation with each107

(a) FSV1100

Fig. 4 w and uw obtained from sonic anemometer(b) Lepton3

Fig. 2 Wind distribution on leeward surface obtained from FSV1100 and Lepton3(a) wSE under Sweep mode (b) wSE under Ejection mode

Fig. 3 Correlation of v and w component at thecenter of leeward surface with 5 s averaging(c) TSE under Sweep mode(d) TSE under Ejection mode

Fig. 5 TIV estimated ensamble averaged verticalmotion and temperature distribution on the leeward surface. The ’x’ marker indicates the point of
the maximum wSE value.

other (Fig.3).
On the top surface, TIV wind velocity tend to correspond to those obtained from the sonic anemometer.
The delay between measurements was about 3 s calculated from cross-correlation. This lag occurs because
observed position diﬀered by 3 to 4.5 m. While mean
wind speed was about 3 m s−1 at the height 2H, different lag times were observed above the block; windspeed changes above the block at 2H propagate surface wind speed with 2 to 3 seconds delay.
On the southeast-facing leeward surface, updraft
motion due to the cavity circulation was observed.
Largest updraft motion was observed almost centerof the surface (Fig.2). According to Uehara[3], under
neutral and unstable condition, it appears at or a little
above the center of the surface. In general, this shows
TIV was successfully implemented using the inexpensive system.

become unstable condition.

5 Conclusions
This study is the first-ever attempt of a simultaneous TIV application across multiple facets. Here, reliability of TIV velocity estimated from multiple qualities of thermal images and its application to instantaneous phenomena around a block were conducted.
In this paper, we discussed about reliability of TIV
velocity from multiple thermal images and instantaneous phenomena.
Multiple thermal images shows similar TIV vectors
and wind speed. Under dim conditions, temeperature
perturbation wasn’t obtained because of the lack ofsensitivity of thermal cameras.
Sweep and ejection motion are caused by the large
structure above urban canopy layer. TIV confirmedthat these motions aﬀect the stability in the cavity.

4.2 Sweep and Ejection
In this section, we discuss two patterns in the cavity
flow observed by the TIV influenced by sweep andejection. Sweep and ejection modes can be detectedusing a sonic anemometer (Fig.4).
Sweep condition (uw < 0 with u′ > 0, w′ < 0)occurs in case wind speed above the block become faster. Under this condition, leeward surface
updraft is enhanced (Fig.5(a)) and surface temperature decreased (Fig.5(c)). Ejection condition(uw < 0 with u′ < 0, w′ > 0) occurs with slower
above wind speed. Updraft motion on the leeward
surface become little slower (Fig.5(b)) and surface
temperature becomes higher (Fig.5(d)).
This is considered that cavity circulation is mainly
dominated by the wind speed above the canyon for
accelarating or decelarating the circulation speed.
Faster circulation enhance heat exchange between theblock surface and the air in the cavity, on the other
hand, slower circulation doesn’t exchange the heatso much, then surface temperature get higher andReferences[1] 瀧本浩史, 森脇亮, 津國眞明, 神田学. 屋外都市スケー
ルモデルにおける piv 計測. 水工学論文集, Vol. 52,
pp. 259–264, 2008.
[2] Atsushi Inagaki, Manabu Kanda, Shiho Onomura,and Hideaki Kumemura. Thermal image velocimetry. Boundary-Layer Meteorology, Vol. 149, No. 1,
pp. 1–18, Oct 2013.
[3] Kiyoshi Uehara, Shuzo Murakami, Susumu
Oikawa, and Shinji Wakamatsu. Wind tunnel
experiments on how thermal stratification aﬀects
flow in and above urban street canyons. Atmospheric Environment, Vol. 34, No. 10, pp. 1553 –
1562, 2000.
108

Phytoremediation of aquatic environment polluted by antibiotics
Student number: 14B02692

1.

Name: Shuyang WANG

Introduction

Hydrolysis was conducted in experiment A, hydrolysis andphoto-degradation were conducted in experiment B. Uptake,hydrolysis and uptake were conducted in Experiment C. Undera condition with light, mechanisms conducted in the removal
will be hydrolysis, photo-degradation and sorption with uptake
by plant. This condition was considered as L group (Light).
As a hypothesis of this research, we consider there is noconnection between these mechanisms. For example, inExperiment B, both hydrolysis and photo-degradation
conducted. The hypothesis means the participation would notaffect the efficiency of hydrolysis.
Therefore, we could calculate the efficiency of eachmechanism by counting the D-value between the remained
concentration. C0 - CA ( mol/L) is the amount that hydrolysis
worked. The rest can be done as the same: CA –CB is the workby photo-degradation, and CB –CC is the work by duckweed.CACD is the work by plant under no-light condition.
Experiment D was set to investigate the effectiveness ofhydrolysis and plant under the condition without light. In thiscase, the mechanisms related to the removal will be hydrolysis,
sorption and uptake under no-light condition(NL group). By
comparing these two groups, we could find out the difference
between the efficiency of duckweed under light and no-light
condition.
All experiments were set triplicate to avoid accidental
mistake, and calculation were based on the average of each kindof data. Relationship between each experiment and themechanism conducted was shown in Table 3.

Various kinds of antibiotics have been widely used for bothhuman beings and animals to get rid of the bacteria. However,in India, pharmaceutical company discharged wastewaterproduced during production process with high concentration
antibiotics [1-4]. This may cause 2 main problems: the increaseof antibiotic-resistant bacteria and the sediment in animals(especially in aquatic animals) and plants through irrigation andsoil [5]. Antibiotics being accumulated in animals and plants
will enter human body and will lead to the ineffectiveness during
a surgery or cure.
Since the last decades, ponds of duckweed(Lemna minor)
has been utilized in the removal of nutrients and organic
compounds successfully. Then, the utilization of duckweed has
been studied in the removal of the organic compounds in water.
This study aimed the treatment of aqueous solution
contaminated by antibiotics with duckweed. First, removal of
antibiotics in the aqueous solution by the duckweed wasmeasured. Then, the effects of operating conditions on the
antibiotics removal was studied to discuss the mechanism ofantibiotics removal.
2.

Experimental

2.1

Experiment materials

Two kinds of antibiotics were selected, ciprofloxacin (CIP),
and sulfamethoxazole (SMX), which are detected in the polluted
water in India. Ciprofloxacin is a member of fluoroquinolonethat share a bicycle core structure related to the 4-quinolone.
Sulfamethoxazole belongs to sulfonamide group. In thisresearch, antibiotics are purchased from Wako Pure Chemical
Industries. Ltd. The structure and other chemical data are shown
as below in Table 1.

2.3 Experiments and analytic methods for the removal
mechanisms investigation
Table 2 Experiment conditions for experiment A~D
Weightof
duckweed(g)Illumination
Antibiotics infeedConcentrationof feed (C0mol/L)
Amountoffeed (mL)
Growthmedium(amount mL)
Time(hrs)

Table 1 Structure and molar mess for each antibiotic
Ciprofloxacin
Sulfamethoxazole
FormulaC17H18FN3 ・HCl・ C10H11N3O3S
H2 O
Molar mass

385.82

Supervisor: Ryuichi EGASHIRA Hiroaki HABAKI

253.28Duckweed were purchased and grown under a specificcondition. Temperature of water was monitored and controlled
at 24±0.5℃(297.15±0.5K). Illumination was supplied by ametal halide lamp (Eye HID LAMP, 400W IWASAKI
ELECTRIC CO. LTD.), which could provide 680 μ mol/m2s.
Illumination was provided 16 hours per day. In order toreproduce duckweed, aeration was provided by an air pump
(4.5W NISSO CORPORATION ) for 24 hours per day.
Duckweed cultures were grown for 4 weeks before experiments.

A

B

×

×

C
3.00

D
3.00

×

○

CIP/SUL○
CIP/SUL×

CIP/SUL

5.00×10-5/1.00×10-5

5.00×10-5/1.00×10-5

5.00×10-5/1.00×10-5

5.00×10-5/1.00×10-5

80

80

80

80

4.00×10-3

4.00×10-3

4.00×10-3

4.00×10-3

168

168

168

168

CIP/SUL

Table 3 Mechanism involved in each experiment and the calculation
method for their effectiveness

2.2

Methods
The wet mass of duckweed was measured after wipe off thesurface of random amount of duckweed. Then the duckweed
was dried in a dryer at 110℃(383.15K) for 24 hours, and thedried mass was measured, too.
Three mechanisms are connected with the remove:hydrolysis, photo-degradation and uptake by duckweed.
Through Experiment A~D we could investigate the efficiencyof each mechanism and the efficiency of duckweed in theremoval process. Experiment conditions were set as describedin Table 2. C0 was the concentration of feed solution. By
scanning the sample from each flask, CA ~CC (concentration of
antibiotic in sample) could be calculated.

A

B

C

D

○

○

○

○

Photodegradation

×

○

○

×

Uptake by
plant

×

×

○

○*

Hydrolysis

3.

109

Results and Discussion

3.1

Table 7 Experiment result (C0=1×10-5mol/L)

Moisture content of Duckweed

The moisture content of duckweed was estimated with thefollowing equation:
𝐷𝑟𝑖𝑒𝑑 𝑚𝑎𝑠𝑠
𝑀𝑜𝑖𝑠𝑡𝑢𝑟𝑒 𝑐𝑜𝑛𝑡𝑒𝑛𝑡 = 1 −Wet mass
Experiment were conducted 9 times. Data is shown below inTable 4.
Table 4 Experiment result for moisture content

Group
1
2
3
4
5
6
7
8
9

Wet mass (g)
5.61
4.15
3.88
4.20
4.01
2.94
3.51
2.66
3.20

Dried mass (g)
0.63
0.43
0.41
0.42
0.43
0.33
0.40
0.33
0.37

Moisture content
0.89
0.90
0.89
0.90
0.89
0.89
0.89
0.88
0.88

3.2

Removal Mechanisms
All results of efficiency is based on the formula described
below.
Table 5 Formula for the calculation of efficiency
Ephoto-E plant

E plant(NL)

degradation

Formula𝐶: − 𝐶;

𝐶; − 𝐶<

𝐶< − 𝐶=

𝐶; − 𝐶>When the concentration of feed (C0) is 5×10-5mol/L, theresult is shown in Table 6.

Table 6 Experiment result (C0=5×10-5mol/L)

L

CIP

SUL

𝐶: − 𝐶;
𝐶: − 𝐶;
𝐶< − 𝐶=

0.51
1.49
1.30

0.00
0.06
1.22

NL

CIP

SUL

𝐶: − 𝐶;
𝐶; − 𝐶>

0.51
2.52

0.00
2.43

CIP

SUL

0.23
0.32
0.19

0.00
0.22
-0.45

NL

CIP

SUL

𝐶: − 𝐶;
𝐶; − 𝐶>

0.23
0.23

0.00
0.33

Ciprofloxacin tends to collapse under hydrolysis and photodegradation, and could be removed by duckweed. Compared toformer experiment, the antibiotic remained in the solution is less,decreased from 0.34 to 0.26. In condition 2, hydrolysis share thesame efficiency with sorption and uptake. But obviously, plantshowed a low efficiency under no-light condition.
The result of sulfamethoxazole at this concentration iscomplex. Again, sulfamethoxazole was stable towardshydrolysis. Sulfamethoxazole collapsed under photodegradation, account for 21% of the sulfamethoxazole been
removed. Data for E uptake could not be calculated, because theconcentration ‘increased’, which is normally impossible. The
reason is that in condition 2, sulfamethoxazole decreased from1 × 10-5mol/L to 0.67 × 10-5mol/L . Based on experience in thisresearch, the ‘increase’ may be considered as no change inconcentration.
There are several reasons for this result. The first reason isabout the metabolite from duckweed during the experiment. As
mentioned in 2.5, to avoid the influence from the metabolite, wehave set a control group. And in the calculation, data from thisgroup were being subtracted from the absorbance of group C.
But still, individual difference of plant may exist. Furthermore,
the spectrometer could only measure the absorbance of sample
but not distinguish compounds in the sample as a Liquid
Chromatography, which means is the sample is a mixture, theabsorbance may lead to a ‘increase’ in the signal and in the data.

By calculating the average of all the moisture content, theaverage moisture content is around 89%.

E hydrolysis

L
𝐶: − 𝐶;
𝐶: − 𝐶;
𝐶< − 𝐶=

4.

Conclusion

In this research, we observed and calculated theeffectiveness for each mechanism in the removal of antibiotics
from water. Ciprofloxacin could be removed by hydrolysis,
photo-degradation and uptake by duckweed in bothconcentration. On the other hand, remove of sulfamethoxazole
is difficult. Because it showed stability towards these 3
mechanisms. Among all the mechanisms, the participation of
duckweed displayed its potential in removing sulfamethoxazole.
However, at feed concentration 1 × 10-5mol/L, effect is stillquestionable, which may need new analytical methods or
different analyze machine based on other theory like LC(liquid
chromatography).

At this concentration, both the ciprofloxacin and thesulfamethoxazole group, part of the duckweed died after 2
weeks. At this concentration, duckweed’s metabolism was
influenced.
In the case of ciprofloxacin, hydrolysis and photodegradation showed their effectiveness in the removal process.
Together, hydrolysis and photo-degradation occupied 60% of
the ciprofloxacin being removed. Uptake by plant did benefit theremoval by taking up 40% of the work.
On the other hand, in the case of sulfamethoxazole,
duckweed showed its effectiveness in the process. Uptake andsorption by plant maintained 95% of the decrease inconcentration. Sulfamethoxazole is stable towards hydrolysis
and photo-degradation but could be removed by plants during aperiod, mainly because sulfamethoxazole has sulfonic acid as apart of it, which can make sulfamethoxazole stable towardshydrolysis.
In condition 2, we could find out no matter what theantibiotics is in the feed, plant could still remove antibiotics
from water. Though the effect is somehow weaker than undercondition 1.
When the concentration of feed is 1×10-5mol/L for both
antibiotic, the result is as described in Table 5.The calculation isbased on the formula described in Table 5, results are showed as
the ratio of work done by each mechanism (D-value) and theconcentration of feed.

References[1] Carolin Rutgersson,
Jerker Fick,∥† Nachiket Marathe,⊥ Erik#Kristiansson, Anders Janzon, Martin Angelin, Anders Johansson,
Yogesh Shouche, Carl-Fredrik Flach, and D. G. Joakim Larsson
Fluoroquinolones and qnr Genes in Sediment, Water, Soil, and Human
Fecal Flora in an Environment Polluted by Manufacturing Discharges[2] Carl-Fredrik Flach, Anna Johnning, Ida Nilsson, Kornelia Smalla,
Erik Kristiansson and D. G. Joakim Larsson Isolation of novel IncA/C and
IncN fluoroquinolone resistance plasmids from an antibiotic-polluted lake
[3] Sivanandham Vignesh, Krishnan Muthukumar, Rathinam Arthur James
Antibiotic resistant pathogens versus human impacts: A study from three
eco-regions of the Chennai coast, southern India[4] Johan Bengtsson-Palme, Fredrik Boulund, Jerker Fick, Erik
Kristiansson and D. G. Joakim Larsson Johan Bengtsson-Palme, Fredrik
Boulund, Jerker Fick, Erik Kristiansson and D. G. Joakim Larsson[5] Xiaoqin Wu, Laurel K. Dodgen, Jeremy L. Conkle, Jay Gan, Plant
uptake of pharmaceutical and personal care products from recycled waterand biosolids: a review

110チェルノフ距離に基づく局所フィッシャー線形判別分析
学籍番号：14 10020

1

氏名：湯韻佳はじめに

指導教員：山下幸彦

ここで，w は特徴ベクトルである。式の分母を小さくすると同時に分子を大きくする w を定める。このことにコンピュータによるパターン認識は，前処理，特徴抽

よって，変換後は，クラスの分離が可能になる。w は，出と識別の 3 つの過程で行われる，その中で特徴抽出とSW と SB に関する一般化固有値問題によって得られる。

は，対象を区別できるような情報を観測パターンから取FDA をベースに CFDA は，誤認識率の定義から提案されたチェルノフ距離を用いて，SW と SB の計算に補正では最も基本な手法の 1 つであるフィッシャー線形判別 項を加えることで FDA に汎用性を与えた。一方，LFDA
分析 (FDA) とその関連研究に基づいて，判別性能を高 は，局所性保存射影のアイデアを取り入れ，S と S にり出す処理である。その方法は多岐にわたるが，本論文Wめる手法を提案する。

B

親和性行列を導入したものである。その効果は，より離局所線形判別分析 (LFDA) は，FDA を局所性保存射れているサンプルのペアはクラス内変動行列 SW により

影 (LPP) と組み合わせることによって，データ構造を小さい影響を与えることであり，多数のクラスターを持保存しながら，FDA の認識率を高めた。しかしながら， つデータも非常に高い精度で分類することができる。しFDA と同様に各クラスの分散共分散行列が異なる場合， かし各クラスの分散共分散行列が異なる場合，識別のた
識別のために最適な特徴を抽出しないという問題が残さめに最適な特徴を抽出しないという問題がある。そのたれている。一方，チェルノフフィッシャー線形判別分析

め CLFDA 特徴抽出モデルを導入することを提案する。
(CFDA) は，FDA に補正項を加え，分散共分散行列の既存のクラス間変動行列 SB とクラス内変動行列 SW
形が異なる場合に，分類の認識精度を高めるための手法 は，データの平均と分散のみを用いて計算されたものでである。論文では，LFDA に，CFDA で使われたチェル あるが，ここでは，それを親和性行列と組み合わせた S˜
B
ノフ距離に基づいた補正項を加えることによって，形が と S˜ に置き換えることによって，同じクラスに所属すW異なる分散共分散行列を持つデータに対して認識精度を るデータを近づけ，離れたデータ間の影響を抑える。た高めることができる特徴抽出法を提案する。そしてそのだし LFDA と CFDA において，平均値と分散の定義の効果を評価するため，トイデーターと UCI データセッ 方法が異なっているため，係数を補正し，変動行列を算トのデータを用いた実験を行う。実験で求めたエラー率 出できるようにする必要がある。
から，その判別性能を既存手法と比較し，評価する。

2

3

チェルノフ局所線形判別分析
フィッシャー線形判別分析とは，多変量に基づく 2 ク

ラスのパターンの分布からこの 2 クラスを識別するために適した 1 次元軸を求めるための手法である。クラスの中の情報を表すクラス内変動行列 SW とクラスの間の関

特徴抽出精度検証のための実験
本節では，提案モデルの有用性を検証するために行った実験について述べる。プログラムによって生成した

AB 型 (図 1) と ABA 型 (図 2) のトイデータと，機械学習のための UCI データ (表 1) を 2 つ使い，4 つの手法

(CLFDA，LFDA，CFDA，FDA) による特徴抽出を行う。そして，認識法として最近傍法を用いて，エラー率
T
SB = (µ1 − µ2 )(µ1 − µ2 ) ，(1) を出力する。さらに，それぞれのデータセットに対して，
SW = Σ 1 + Σ 2 .
(2) どの方法が適する手法であるか検証する。
次に各データとパラメータについて述べる。図 1，2と書ける。ここで µc は，クラス c の平均ベクトル，Σc はトイデータであり，図 1 ではクラスごとのデータ数は
はクラス c の分散共分散行列である。次元を落とした平 100 であり，図 2 では 200 である。交差検定を 100 回行っ
均ベクトル mc と分散共分散行列 σc2 を用いて，FDA に てエラー率を評価し，各データセットにおいて学習のた係を表すクラス間変動行列 SB はそれぞれ：

おけるフィッシャーの評価基準関数を定義すると次のよめに使うデータは全体の 70%とし，テストデータには残うになる。

りの 30%を使った。

w SB w|m1 − m2 |= T.
σ1 2 + σ2 2
w SW w2

argmax w

J(w) =

T(3)
111

トイデータの実験結果を表 2，表 3 で，UCI データの

8

6Class 1
Class 2

表 3: ABA 型データの認識エラー率 (平均 ± 標準偏差)Class 1
Class 2

6

4

4

2

2
0

Data Type

CLFDA

LFDA

CFDA

FDA

O 10.83±0.06

13.85±0.05

33.90±0.06

31.89±1.36
28.08±0.13

0
-2

1

-4

-4

2

O 19.13±0.11

32.14±0.09

28.80±0.16

-6
-4

-6
-10

3

O 27.13±0.13

27.33±0.14

28.84±0.1129.43±0.15

432.33±0.07

O 13.93±0.06

50.10±0.13

50.76±1.89

540.93±0.06

O 9.86±0.05

43.20±0.06

41.48±1.44

-2

-2

0

2

4

-5

0

5

10

表 1: UCI データセットの情報
Data Type

特徴量

データ数

クラス数

使うデータ

Iris

4

150

3

クラス 2，3

Wine

13

178

3

クラス 1，2

Transfusion

4

748

2

1,2

Haberman

9

569

2

1,2

表 4: UCI データの認識エラー率 (平均 ± 標準偏差)

実験結果は表 4 で示す。ただし，各データタイプにおいData Type

CLFDA

LFDA

CFDA

FDA

Iris

14.53±6.9717.47±6.12

O 5.76±3.91

24.35±5.71

Wine11.28±4.237.86±2.13

O 1.41±2.06

1.54±1.82

Transfusion

23.92±0.41

O 19.83±0.47

26.89±2.66

26.44±2.29

Haberman

32.57±4.44

O 31.94±4.1434.39±4.4534.53±4.25ての最もエラー率が低い結果の前に「O」を付けている。
り精度を高めることを目的とした特徴抽出手法を提案し

表 2: AB 型データの認識エラー率 (平均 ± 標準偏差)た。そして認識実験を行い，既存手法と比較し，その有
Data Type

CLFDA

LFDA

CFDA

FDA

用性を調べた。

1

O 14.53±0.1434.07±0.26

27.85±0.19

28.87±0.26

2

O 9.97±0.13

23.90±0.24

14.82±0.17

13.83±0.23

3

O 10.10±0.12

23.08±0.18

19.10±0.12

20.83±0.24

タに対する CLFDA の性能をが安定化手法を開発するこ4

O 11.85±0.19

49.16±0.2225.17±0.27

23.70±0.25と，パターン間距離の評価法を検討することである。

今後の課題は，2 クラス 3 クラスター (ABA 型) のデー

表 2 では，すべてのデータに対し，CLFDA が最も低いエラー率を達成している。そのエラー率は FDA の約

参考文献

1/2 である。表 3 からは，クラスターが 3 つある場合，中心のクラス 2 が両側のクラス 1 と分散が明らかに異なるとき，CLFDA の特徴抽出精度が最も高い。ただし，そうでないときは LFDA の結果が一番良い。原因としては，補正項のモデルは，AB 型分布とデータの形が明らかに異なる場合に適するため，他のデータでは補正項の本来の機能を実現できなかったためと考えられる。最後に表 4 では，CFDA と LFDA が最も良い結果を出している。CLFDA は，2 クラス 2 クラスターのトイデー
タの場合とほとんど変わらず，補正項の機能を実現することができていないと考えられる。すなわち高次元ベク
トルに対する抽出精度は，既存の方法より劣っている。
この問題の解決のためには，パターン間距離の評価法に工夫が必要と考えられる。

[1] 上田修功ほか (1998) 『わかりやすいパターン認識』
オーム社[2] 佐藤真一, 福井和広 (2011)「パターン認識とビジョン」
pp.1-4, 16[3] Yokota, et al., ”Heteroscedastic Gaussian based
Correction term for Fisher Discriminant Analysis
and Its Kernel Extension”Proc. of International
Joint Conference on Neural Networks (IJCNN2013),
no. 1188， pp. 1-3, Aug. 2013[4] Sugiyama, et al.，”Dimensionality Reduction ofMultimodal Labeled Data by Local Fisher Discriminant Analysis”, Journal of Machine Learning Research vol.8, pp. 1029-1036, May. 2007.
[5] X. He, P.Niyogi, ”Locality Preserving Projections”,
NIPS’03 Proceedings of the 16th International Conference on Neural Information Processing System,
pp. 153-155， Dec.2003.

4

おわりに
特徴抽出は，対象を区別できるような情報を観測パ

ターンから取り出す，パターン認識においてとても重要なプロセスである。本論文では特徴抽出法の一種である
局所フィッシャー線形判別分析 (LFDA) をもとに，チェ
ルノフ距離に基づいた補正項を加えることによって，よ112

Study of GPU accelerated computer vision
Student Number: 13 10694

1

Name: Shitian Ni

Introduction

While needs for high computing powers continue
to grow to process the exponentially growing amountof data from smart devices around the globe, Moore’s
law is reaching to its limit. Gordon Moore noted thattransistors eventually would reach the limits of miniaturization at atomic levels.
Cores and threads could be put together to work inparallel to accelerate data processing. Therefore, themarket trend is to use more and more cores.
Intel’s CPU lineup can have up to 72 cores with
Xeon and over 200 when used with dual Xeon Phi coprocessors. On the other hand, Nvidia GeForce GTX
1080Ti has 3584 CUDA cores, Nvidia Tesla V100 has
5120 CUDA cores and 640 Tensor cores, far more coresthan a CPU can have.
GPUs are designed for manipulating computer graphics and image processing, and their highly parallel structure to manipulate image blocks makes them more efficient than CPUs to do matrix computations which arenecessary for modern artificial intelligence deep learning and computer vision tasks.
In this research, we conduct a parallel computing
acceleration of an image recognition algorithm called
GPT via GPU, which achieves a further acceleration of
global projection transform (GPT) enhanced methods
proposed by Zhang et al [2] [3].

2Global Projection Transformation (GPT)A measure of image matching is based on the canonicalized correlation between two normalized images f (r)and g(r) given by (1).
Z
C(f, g) =f (r)g(r)dr,(1)
K

where K is the image area and r = (x, y)T is a position vector. Images need to be normalized to calculate
canonicalized correlation. Normalization for an image
f (r) is defined by the following equations.
ZZ
f (r)dr = 0,
f (r)2 dr = 1.
(2)
K

K

GPT correlation matching which calculates the normalized correlation after GPT is given byZ
CGPT (f, g) =f (r)gK

Ar + b
1 + hc, ri


dr.

(3)

113

Supervisor: Yukihiko Yamashita

The method is proposed by Yamashita and Wakahara [1] to address projection transformation by extending affine-invariant GAT (Global Affine Transformation) correlation matching. Zhang et al. [2] [3] enhanced GPT with sHOG filters and accelerations bytemplates and lookup tables.

3

GPU computing

Although templates and lookup tables significantly
accelerated the computation speed, further improvements are considered. Massive amount of computation involving image pixel matrix calculations has tobe done. In those cases, there would be a ’for’ loop going through all image pixels. Consider an image whichhas 200*200 pixels. If we add value 1 to all pixels, thenwe need to do 40000 times of calculations in serial in
the original code base. But if we use GPU, for example
a 2000 CUDA core GPU and if we can spread the pixels to all CUDA cores, based on a simple calculation,
we just need 20 times of calculations for each CUDA
core being given 20 pixels and do the calculation inparallel.
Notice that tasks performed in parallel should notdepend on each other. That is, order in which the tasks
are performed should not matter the final result. For
example, task 1 is adding 1 to pixel a, task 2 is adding
pixel a to pixel b. Performing task 1 before task 2 andperforming task 2 before task 1 would result in different pixel b values. In this kind of cases, operations are
related to each other, so they should not be performedin parallel. But because many of those operations going through image pixels do the same tasks, GPU acceleration theoretically helps to improve performance.
In the original code of the GPT matching, the following operations are included- Calculation of mean of nearest-neighbor interpoint distances between two images- Determination of optimal GAT components thatyield the maximal correlation value- Calculation of Gaussian weighted mean values- 8-quantization of gradient direction- Projection transformation of the image by bilinear
interpolation- Update of the Gauss window function- Update of correlation
For the parallelizable operations, the followings aresome further CUDA strategies:- Reduce parallel kernel code divergence (if..else..)- Reduce data transfers between different memories- Access neighboring data in memory- Parallel paradigm usage including Map, Stream
filtering, Scan, Scatter, Gather, Reduce

These calculations for each pixel are independent toeach other, so the computing time can be reduced byassigning the independent calculations to GPU threads.
Furthermore, a part of reference table can be loaded
into the device memory as well as shared memory inadvance to reduce the memory access time.
Access to device memory is slower than shared memory which is slower than registers. To use share memory instead of device memory, we divide data to several
blocks, load the blocks to shared memory, then execute
data block calculations separately in parallel.

4

Calculation times differ from execution to executions based on hardware related issues. But that difference is minor, in range between 0.1 to 0.3 seconds.
And calculation time error tends to converge after multiple executions. Besides that, memory copy in GPU
and serial Atomic operation overheads are still obvious.

Figure 1: The template image (170 × 136) and test
images (340 × 272) from Boat dataset

Experimental Results

Figure 1 shows the template image and test images from Boat dataset. Table 1 shows comparisons ofcalculation times required for these matchings between
standard CPU algorithm denoted by Stand. CPU, template and lookup table accelerated CPU algorithm denoted by Accel. CPU, GPU accelerated algorithm andCPU ASIFT algorithm.
The calculation times cost by GPU in Table 1 do
not include the time for copying the template tables
to GPU memory. The calculation times cost by GPTbased methods are the times required for only one subwindow. Accel. CPU costs about one hundredth of thecalculation time required by Stand. CPU, and GPU
significantly reduces the calculation time of Stand. CPU
further to several thousandths of time.
Incidentally, we used Tokyo Institute of Technology
supercomputer TSUBAME 3.0 instance with CPU of
3.47 GHz Intel Xeon-X5690 and GPU of NVIDIA Tesla
P100 in this experiment. The programs of Stand. CPU
were coded in C++. Accel. CPU enhanced Stand. CPUwith templates and lookup tables. The GPU accelerated programs were implemented with CUDA on top of
the Accel. CPU. Accel. CPU and GPU have the same
calculation results which are the image correlation values which are almost the same as the Stand. CPU results. Stand. CPU results are better than ASIFT.
All the programs are available on
https://github.com/shitian-ni/CUDA-GPT
Also, the program of ASIFT-RANSAC using the OpenCV
library were executed on C++ platform on CPU.
To further compare computation times of different
GPU enhancements, we measured calculation times ofsample Graffiti Image 6 again.
Exclude time for parameters initialization and time
for copying initial data to GPU memory,- Accel. CPU calculation time is 5.571 sec- GPU calculation time is 0.467s
If we use CUDA AtomicAdd function to sum elements one by one in serial instead of reduce methodwith shared memory,- GPU elapsed time is 0.490 sec
If time for parameters initialization and time forcopying initial data to GPU memory are included,- Total Accel. CPU calculation time is 7.146 sec- Total GPU calculation time is 1.227 sec
114

Table 1: The calculation times of Boat dataset (second).
Test image
Stand. CPU
Accel. CPU
GPU
ASIFT

5

Image 2102.95
1.82
0.227
7.259

Image 3
96.76
1.64
0.248
6.786

Image 4
86.6
1.86
0.303
5.766

Image 5
84.28
1.85
0.263
5.694

Image 6
82.39
1.82
0.23
5.419

Conclusions

This paper first introduced the GPT correlation
matching method and its variations. Then we introduced GPU programming and its use on GPT. GPU
implementation has the same results as Accel. CPU
and almost the same as Stand. CPU which has thebest correlation values on the experiment datasets. On
the other hand, GPU acceleration reduced the calculation time of Accel. CPU more than ten times and Accel. CPU itself reduces Stand. CPU computation time
to about 1 percent. Future works could be about comparison between GPU accelerated GPT and neural networks. Tests on bigger images could also be done.

References[1] Y. Yamashita and T. Wakahara, “k-NN classification of handwritten characters using a new distortiontolerant matching measure,” Proc. of 22nd Int. Conf.
on Pattern Recognition, pp. 262–267, Stockholm, Aug.
2014.
[2] S. Zhang, T. Wakahara, and Y. Yamashita, “Theoretical Criterion for Image Matching Using GPT Correlation,” Proc. of 23rd Int. Conf. on Pattern Recognition,
pp. 544–549, Cancun, Dec. 2016.
[3] S. Zhang, T. Wakahara, and Y. Yamashita, “Image Matching Using GPT Correlation Associated with
Simplified HOG Patterns,” Proc. of 7th Int. Conf.
on Image Processing Theory, Tools and Applications,pp. 1–6, Montreal, Nov. 2017.

Nitrogen oxides removal using red mud
Student Number: 14_05590

Name: Siqi WUSupervisor: Hirofumi HINODE, Kurniawan WINARTO

1. Introduction

MnO2

Nitrogen oxides (NOx) are considered one of
the most significant air pollutants and it causes
acid rain, ground-level ozone and global
warming. NOx usually relates to NO and NO2.
Half of NOx emitted in the atmosphere comefrom automobiles, and a significant 20% fromelectric power plants. Because of the presence ofO2, NOx cannot be easily removed in the leanburn gasoline or diesel engines using a threeway catalyst. Therefore, selective catalytic
reduction with ammonia (NH3-SCR) or NOx
storage-reduction (NSR) is currently the mostdeveloped technology to reduce the emission ofNOx. However, NH3-SCR requires large amountof additional reductants, and can easily cause
secondary pollution with ammonia.
Red mud, or bauxite residue, is solid waste
generated by the Bayer process in aluminum
industry. This waste product usually contains a
mixture of many oxides. Due to the high pHfrom 10 to 12, and massive volumes of
production of over 20 billion tons a year globally,it has potential impacts on surface and groundwater quality.
In this study, red mud was investigated as
potential material for NO removal in the excessof O2.

3. Results and Discussion

Fig.1 shows the performance of a series ofsamples prepared at different calcination
temperature (The number following “RM”
shows the calcination temperature of thesamples. Uncalcined red mud was named “RM”
only.). Samples calcined at 300℃-400℃ showed
the highest activities. When the calcination
temperature is above 400℃, the performance
significantly decreased. The NO removal for
RM600 drop below 0 at 450℃-500℃, indicating
the removal process of NO was an adsorption,
not a decomposition. At lower temperatures,
NO was adsorbed in these samples, while athigh temperatures, NO was desorbed fromthese samples, resulting in NO concentration
higher than inlet gas.
Fig.2 compares the results of 1st round test
and 2nd round test of uncalcined red mud. As
shown in the graph, the performance of thesamples at 1st round is much better than in the

2. Experimental

Indonesian red mud was used in this study.
The composition of red mud is shown in Table 1.
[1]
Table 1 Chemical composition of Indonesian red mud
Chemical composition

Weight%

Fe2O3

33.36

Al2O3

24.63

SiO2

13.8

Na2O

7.98

TiO2

1.33

CaO

0.57

MgO

0.05

ZrO2

0.03

0.05

A series of samples were prepared bycalcining red mud powder at different
temperatures from 300℃ to 600℃ under air
flow. The powder was put into the tube furnaceand heated for 5 h, then pelletized, ground, andsieved with 1.0 to 1.4 mm particle size.
Using a 6 mm inner diameter quartz glass
tube as fixed-bed flow reactor, the activity of red
mud was measured by passing a reactant gas
consisted of 1500 ppm NO, 10% O2, with He asbalance gas at a flow rate of 4 ml/s with spacevelocity 13000 h-1. The reaction temperatures
were varied from 150℃ to 550℃.
Subsequently, the NO and NO2 concentration
were measured by NOx analyzer (NOA-305A;
Shimadzu Co.). Characterization of samples
was done by X-ray diffraction (XRD) to analyze
crystalline structure and Fourier Transform
Infrared Spectroscopy (FT-IR), for the analysis
of surface functional groups.

115

comparison, adsorption using Al(OH)3 was also
performed. The adsorption capacity of
uncalcined red mud is similar to Al(OH)3, it
indicates Al(OH)3 is the effective component in
the red mud for NOx adsorption at room
temperature. However, the conversion rate in
RM400 reached 100%, perhaps there are othermetal oxides creating synergistic effect with
Al(OH)3 .

2nd round. Therefore，we can conclude that thecomponents affecting catalytic activity are
influenced by calcination temperature, andthese are present in low temperature yet
becomes unstable at high temperature.

50

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

100 150 200 250 300 350 400 450 500 550
RM

RM300

RM550

RM400

RM600
TEMPERATURE (℃)

Fig. 1. NO removal of various RM samples
100%
NO REMOVAL

RM
RM400

NO removal

NO REMOVAL

100%
80%
60%
40%
20%
0%
-20% 0
-40%
-60%
-80%
-100%
-120%

0

80%

100

200

Al(OH)3300

400Time (min)

60%
40%

Fig. 4. NO adsorption test results

20%
300

350

TEMPERATURE(℃)

RM-1 2nd400

RM-2 1st

450

500

1465

RM-2 2ndE
D

Fig. 2. NO removal of RM samples, 1st and 2nd round testH

1558-1506

RM-1 1st

250

1384
1430

200

1558-1506

150

1442 1465 1414

0%

E

D

SiO2
Fe2O3
Al(OH)3
CaCO3

C
B
A

G
F

Fig. 5. FT-IR Characterization. (A)RM, (B)RM300, (C)RM400, (D)RM600, (E)Al(OH)3; Peaks [N2O2]2-: 1442,
1384, NO2- :1506-1558

E
D
C
B

Fig.5 shows the result of FT-IR analysis. The
presence of [N2O2]2- indicates the occurrence ofchemical adsorption during the process.

A

4. Conclusion

Fig..3. XRD patterns of various samples. ((A)RM preexperiment, (B) RM post-experiment, (C) RM300 preexperiment, (D) RM300 post-experiment, (E) RM400
pre-experiment, (F) RM400 post-experiment, (G)RM600 pre-experiment, (H)RM600 post-experiment)

Uncalcined red mud, and red mud calcined at
300℃ or 400 ℃, showed high performances in
NOx removal. Considering the energy
consumption during the production process,uncalcined red mud is more suitable forindustrial use.
In addition, Al(OH)3 accelerates the NO
removal due to its adsorption capability. The
combination of Al(OH)3 with other metal oxides
might generate synergistic effect on the use of
uncalcined red mud for NO removal.

As shown in Fig.3, RM has more components
than RM300, such as Al(OH)3 and otherunknowncomponents.
However,these
components are missing in the post-experiment
RM because Al(OH)3 decomposed to Al2O3 andwater at about 180 °C. Because activity of postexperiment samples decreased, Al(OH)3 might
have effect on the experiment outcome.
To verify the adsorption capacity, theadsorption tests were performed at room
temperature. Fig.4 shows the result and for

Reference[1] A. Wahyudi; Doctor Thesis, Tokyo Instituteof Technology (2017)

116

C
B
A

STUDY ON MECHANISM OF POTASSIUM REMOVALFROM PALM KERNEL SHELL BY HYDROTHERMAL TREATMENT
Student Number: 16B07365

Name: Tsamara Tsani

Supervisor: Fumitake TAKAHASHI

Keywords: Potassium Removal, Hydrothermal Treatment, Palm Kernel Shell (PKS)

1 Introduction
Palm Kernel Shell (PKS) is one of theabundantly available agricultural waste inIndonesia. Palm oil industry in Indonesia yields
5.9 million tons of PKS annually, which is equal
to 54.8 GJ of energy [1]. Despite the energy
potential, the utilization of PKS as biofuel is still
limited.
Pretreatment of PKS is needed to upgrade thebiomass quality in order to achieve an efficientenergy conversion through combustion. There
are several characteristics of desirable solid
biofuel, one of which is low potassium content[2]. At high temperature, potassium content inbiomass reacts with silica and produces a sticky
and mobile phase which causes slagging that
disturb the heat exchange process in the boiler.
Therefore, removal of potassium prior to
combustion is important to be conducted.
Hydrothermal treatment (HTT) has shown
remarkable performance in removing potassium
content from other lignocellulosic biomass, suchas Empty Fruit Bunch (EFB) [3]. A study also
gives a hint toward the utilization of potassiumrich liquid by-product from HTT as liquid
fertilizer [4]. However, the mechanism ofpotassium removal from lignocellulosic biomass
by hydrothermal treatment is not fully
understood yet. The understanding of potassium
existence form in biomass and its removal
process by hydrothermal treatment is importantto further optimize the extraction effort. This
study aims to investigate the potassium existence
form and its removal mechanism fromlignocellulosic biomass (in this case palm kernel
shell) by hydrothermal treatment.

Chart 1 Experiment and analysis flowchart

Hydrothermal treatment was conducted at 100,
140, 180 and 220°C with biomass to water ratioof 1:10 and 30 minutes holding time.
Proximate analysis, ultimate analysis, ash
composition analysis (XRF), SEM-EDX line
profile analysis, crystalline analysis (XRD),
potassium concentration analysis (ICP-OES),
and mass balance analysis were conducted in thisstudy.
Potassium (K) removal rate was calculatedusing the following equation.
K removed (%) ="#$% &"#$'"#$%

𝑥 100%

𝑚𝑠./ = mass of potassium in raw PKS
𝑚𝑠.0 = mass of potassium in HT-treated PKS at t-temperature

In order to check the existence form ofpotassium, line profile analysis and crystalline
analysis were conducted. Elemental mapping
was conducted in prior to line profile analysis.
Particles with high potassium
content were then selected toundergo line profile analysis.
This particle was divided into
4-5 analysis sections shown
Picture 1 Line profilein picture 1.
analysis sections

3 Result

2 Materials and Method

3.1 Potassium Characterization in Raw PKS
Utilizing the data from ICP-OES analysis, it isobtained that potassium concentration in raw
PKS is 1441.621 mg/kg or 0.144 wt%. Raw PKS
also identified to have 30.6% of ash content,
34.24% carbon content and HHV of 12.95 MJ/kg.

PKS sample used in this work is originatedfrom Indonesia. It was received in dried
condition, but mixed with some dirt. The sample
were then water washed and oven dried at 7080°C for 24hr. Experimental and analysis
procedures are shown in the flowchart below.

117Line profile analysis in raw PKS (picture 2)
shows high correlation of Potassium existencewith Si (average r=0.7455) and Al (average
r=0.7077).

These pores absorb back some inorganics
thus resulted in higher ash and K2O content.

Graph 2 Ash (%) in hydrochar and K2O (%) in hydrochar ash

Picture 4 Porous structure of HTT-220

Potassium mass balance analysis was also
conducted in this study (graph 3). It confirms theremoval of potassium from solid biomass toliquid by product.
Picture 2 Line profile analysis in section 1 raw PKS

When Si and Al intensity are plotted to one
another, it also shows high correlation (average
r=0.9437). Therefore, it is predicted thatpotassium inside raw PKS may exists in thealuminum silicate matrix as K 2 cation. The
structure may appear in type of feldspar [6](picture 3). Potassium also shows positive
correlation with Cl (average r= 0.490) and S(average r=0.635). Therefore, potassium is also
predicted to exist as KCl and K2SO4 in raw PKS.

Graph 3 Mass Balance Analysis

XRD pattern of treated PKS at 100 and 140°C
confirm the existence of potassium as KCl andfeldspar group. However, the KCl peak vanish
after treated at 180 and 220°C and left potassium
only in the form of feldspar.

4 Conclusion
Potassium is estimated to exist in PKS in theform of KCl, K2SO4, and feldspar (K(Al,Si)3 O4 )as cation (K 2 ). Due to its existence as cation,
potassium can be removed by ion exchange using
subcritical water in hydrothermal treatment.
Potassium removal rate increases withtemperature to up to 60.11% at 220°C. However,high porosity created at high temperature has
resulted in the slight increase of potassium andash content in HTT-220 hydrochar.
Catalytic hydrothermal using H2CO3 or otherweak acid is purposed for future study to improvethe efficiency of potassium removal. The exact
plan for solid hydrochar and liquid by-productutilization after hydrothermal treatment also need
to be examined thoroughly in the future study.

Picture 3 Orthoclase (KAlSi3O8), one of Feldspar structure

XRD crystalline analysis in raw PKS confirms
the existence of potassium in the form of KCl andfeldspargroup
structures(orthoclase,
anorthoclase and trikalsilite).
3.2 Potassium Removal by Hydrothermal
Potassium removal rate increases withtreatment temperature (shown in graph1). It
reached the highest removal rate of 60.11% at
220°C treatment.

References[1] Prastowo Bambang, “Biomass Resource in Indonesia: Indonesia’s Solid Biomass
Energy Potential”, German-Indonesia Workshop on Biomass, 2011.
[2] P. McKendry, “Energy production from biomass (part 1): overview of biomass”, Bio
resource Technology 83 (2002), pp. 37-46, 2002
[3] Nurdiawati A., Novianti S., Zaini I.N. et al, “Production of Low-Potassium Solid Fuelfrom Empty Fruit Bunches (EFB) Employing Hydrothermal Treatment and Water Washing
Process”, Journal of the Japan Institute of Energy 94 pp. 775-780, 2015.
[4] Novanti S, Nurdiawati A, Zaini Ilman N, et al, “Hydrothermal treatment of palm oil
empty fruit bunches: and investigation of solid fuel and liquid organic fertilizer
applications”, Biofuels, 2016.
[5] Hiroki Kitamura, Dahlan A.V, et al, “Geochemical form analysis of titanium inmunicipal solid waste incineration fly ash particles employing correlation analysis ofelemental distribution line profiles”, Journal of Japan Society of Civil Engineers, Ser. G(Environmental Research). 73, 2017.
[6] David A.C. Manning, “Mineral sources of potassium for plant nutrition, a review”,
Agronomy for Sustainable Development. Springer Verlag/EDP Sciences/INRA, 2010.
[7]Nizamuddin Sabzoi et. al, “Synthesis and Characterization of Hydrochars Produced byHydrothermal Carbonization of Oil Palm Shell”, The Canadian Journal of Chemical
Engineering, November 2015.

Graph 1 Potassium removal rate and potassium mass remained

The ash and K2O content in the hydrochar
also decreased as the temperature increases.
However, both of these content slightly
increased at 220°C treatment (graph 2). This
maybe because hemicelluloses weredegraded at 220-315°C [7], thus creates
porous structure on the hydrochar (picture 4).
118

Hydraulic Experiment and Numerical Analysis on Tsunami – Storm Surge
Entering Through Breakwater Mound
Student Number: 15B08456

Name: Yoshifumi TAKATA

Supervisor: Hiroshi TAKAGIThe average grain diameter of the mound was
11.2 mm, and the void ratio was 40.2%.
A total of 5 different water levels have beentested, and whereby the flow rate through the
breakwater mound was measured.
Moreover, we also conducted a numericalanalysis in order to reproduce the experimental
cases and compared the result from theexperiment (Fig. 3). A computational setting
known as “porous media” was used tocharacterize the rubble mound.
From the comparison, we confirmed that
Ergun’s estimated formula [5] is appropriately
determines the coefficients of non-Darcy law; itshows the relationship between hydraulicgradient and inflow rate when relatively fast
flow occurs in a porous media.
Based on that, we conducted a numericalanalysis on a real scale breakwater model. It
assumed that the average rubble diameter of themound was 50 cm and the void ratio of it was
40%. We tested 16 different water levels
between the front and back of the breakwaterand calculated the flow rate through the
breakwater mound.
Based on our numerical analysis, we derived
the equation (1) that estimates the inflow ratefrom the difference of water level.
(1)𝑞 = 0.393 𝐻

1. Introduction
Installing
floodgates
andmovablebreakwaters such as flap gates on the openingof the port are getting attention as effective
countermeasures against tsunamis and storm
surges [1][2][3]. For instance, a large-sizedfloodgate “View-O” has been constructed at
Numazu port (Fig. 1) in 2004 to prevent thehinterland from tsunamis. It is necessary toassess the inflow of the seawater from the small
gaps of the movable gates [4]. In additionseawater may also intrude into the basinthrough other parts of the port. Especially, thebreakwater consists of impermeable caissonand permeable rubble mound. Hence, there isconcern that tsunamis and storm surges enter
inside the port through the gap op the rocks
when difference in water level exists between
inside and outside the port. However, such arisk has not been clearly recognized to date. As
a result, any practical method for assessing the
inflow rate of tsunami or storm surge throughthe mound has not been established.
This study estimates the inflow discharge
through the breakwater mound by carrying out
a hydraulic experiment and numerical analysis.
The results demonstrate that seawater
inevitably enters inside the port from themound even if the port’s opening can beperfectly enclosed by the floodgate before
arrival of tsunami or storm surge.

𝑞：inflow rate per unit width [m3]
𝐻：the difference of water level [m]Fig. 2 The experimental equipment
Fig. 1 The floodgate “View-O” at Numazu port

2. Hydraulic experimentnumerical analysis

andWe conducted a water flume experimentinstalling a model breakwater composed of anacrylic caisson and a rubble mound (Fig. 2).

Fig. 3 An example of velocity distribution derived bynumerical analysis

119

3. Calculation in the model port
We calculated the changes in water level
using derived Eq. (1) in our model port (Fig. 4).
The model port is composed of a port basin(76000 m2) and a pier (24000 m2). Additionally,a breakwater (760 m) and a floodgate (40 m)
have been placed to surround the port, and thefloodgate is closed before tsunami or storm
surge arrive.
We generated 4 types (amplitude: 3.3 m,
period: 15 min, 30 min, 1 hour and 2 hours) of
long waves and compared the changes in waterlevel inside and outside of the port (Fig. 5).
Therefore, it was recognized that water level
increased in all cases and seawater inflow
through the breakwater mound is not negligible.
Especially, the longer the wave period, themore seawater inflow into the port.

(c)

(d)
Fig. 5 Estimated result (a=period: 15 min); (b=period: 30 min);(c=period: 1 hour); (d=period: 2 hour);

4. Conclusion
The
comparison
betweenhydraulicexperiment and the numerical analysis revealed
that Ergun’s estimated formula is applicable todetermine the coefficient of non-Darcy flow.
Following this observation, we derived theevaluation formula of the inflow rate throughthe breakwater mound when water-level
difference appears between inside and outside
the port occurs. Finally, the numerical analysis
for the model port confirmed that the inflow of
the tsunami and storm surge inside the port isunavoidable for the period range of tsunami
and storm surge.

Fig. 4 Configuration of the model port

References[1] 中島晋, 高山知司, 小原恒平ら: 津波防御に向けた直立浮上式防波堤の性能設計, 土木学会論文
集 B2（海岸工学）, Vol.67, No.2，pp.786-790, 2011.
[2] フラップゲート式可動防波堤開発グループ：フ
ラップゲート式可動防波堤実海域試験（最終報
告書概要版）, 22p., 2013.
[3] Fujii N. et al. Self-elevating Sea Wall Constructedwith Pneumatic Caisson Method, 43rd Conference on
Our World in Concrete & Structures, Singapore,2018.
[4] 高木泰士, 富安良一, 荒木健人ら，浮上式防潮堤の狭小隙間部から流入する津波・高潮流量の評
価手法, 土木学会論文集 B3（海洋開発）, 土木学会, 73(1), 35-42, 2017.
[5] Ergun S. Fluid flow through packed columns. Chem.
Eng. Progress 48(2), 1952.

(a)

(b)

120

Experiment system to examine the effect of cathode temperatureon electric field intensity at breakdownStudent Number: 14_01570 Name: Ryoji Ichisaki
1. Introduction
Research on electric breakdown is important touse discharge phenomena and ensure insulation.
In the research on the re-ignition of plasma phenomena, Omata[1] investigated the relation between
the arc current before interruption and electric field intensity, i.e. applied voltage divided by distance between electrodes, required for re-ignition. He suggested that the field intensity may be determined by
the cathode temperature. However, the actual cathodetemperature was not measured.
Murooka[2] investigated the relation between
electrodes’ temperature and breakdown voltage. However, the change of electrodes’ distance due to thermal
expansion hasn’t been considered. Therefore, it is impossible to measure the field intensity.
The purpose of this study is to design an experimental system capable of changing the cathode temperature and field intensity independently considering
thermal expansion.

Supervisor: Kunio Takahashi

Fig. 1 Schematic illustration of the experimental system

2. Experimental system
2.1 Overview
The schematic illustration of the proposed experimental system is shown in Fig. 1. a pure tungsten
plate (t0.20mm) is used as the anode. A V-shaped filament made of a pure tungsten wire (φ0.10mm) is usedas the cathode, and is heated up to a target temperature
by a constant DC current. Both of the electrodes are
set in an acrylic box, which shielding gas (Ar) is
flowed to (5L/min). The cathode temperature is measured by a radiation thermometer (TR-630) through theacryl. In order to set the field intensity, it is required tochange the voltage and the distance between electrodes. The voltage is applied by a DC power supply(MATSUSADA MR-600-1.7). The distance is set byusing a three-axis micro-stage. A DSLR camera isused for capturing the cathode before and after being
heated to measure the thermal expansion of the cathode.

Fig. 2 Circuit of the constant current power supply(1) Set the initial electrodes’ distance 𝑑int
(2) Take pictures of cathode before and after heating,as shown in Fig. 3(3) Obtain the thermal expansion Δ𝑙 of the cathodefrom the pictures(4) Determine the actual electrodes’ distance 𝑑act by
subtracting Δ𝑙 from 𝑑int (as shown in Fig. 4)
3. Experiment
3.1 Experimental procedure
The experiment is conducted by the following
procedure.
(1) Set the initial electrodes’ distance 𝑑int (0.50 ~1.25mm)(2) Set the cathode temperature (room temperature ~2100℃)(3) Increase applied voltage between electrodes until
breakdown occurs(4) Measure the cathode’s temperature, breakdown
voltage 𝑉B , actual electrodes’ distance at the breakdown

2.2 Constant current power supply
The circuit of the constant current power supply
connected to the filament cathode is shown in Fig. 2.
The current 𝐼 flowing through the filament is controlled to satisfy 𝐼 × R 0 = 𝑉ref by FET switching andOP-amp comparator. The variable resistor is used toadjust 𝑉ref at the output of the three-terminal regulator. Isolation transformers are used to isolate the circuit from the ground level of the high voltage power
supply to prevent damages due to discharged current.
2.3 Actual distance between electrodes
In order to measure the field intensity, the actual
electrodes distance is measured by the following procedure.
121

Fig. 3 Pictures of cathode before and after heating

Before heating

After heating

𝑑int

𝑑act

Fig. 5 Cathode temperature vs 𝑽𝐁

Fig. 4 Relation between 𝑑int, 𝑑act , and Δ𝑙

3.2 Experimental result
Relation between the cathode’s temperature andthe breakdown voltage 𝑉B is shown in Fig. 5. It
shows a trend that 𝑉B decreases as the cathode temperature increases. When the cathode’s temperature
was around 1500℃, breakdown didn’t occur even at
the maximum voltage of the power supply (600V).
The apparent field intensity is obtained by dividing 𝑉B by actual electrodes distance 𝑑act . The relation between the cathode’s temperature and the apparent field intensity is shown in Fig. 6. It shows a trendthat as the cathode’s temperature increases, the apparent field intensity increases under 1500℃, and it decreases over 1500℃.

Fig. 6 Cathode temperature vs apparent field intensitythat the analysis field intensity considering the cathode’s curvature might be determined by the cathode’s
temperature.

5. Conclusion

We proposed an experimental system for independently changing the cathode’s temperature and apparent field intensity in the range written as below.
-Cathode temperature: room temperature ~ 2100 ℃-Apparent field intensity: 0 ~2500 V/mm
Experimental results suggest that the electrodes’
curvature can’t be ignored, and that the actual field intensity may be determined by the cathode’s temperature.

4. Discussion

The actual electrodes’ distance 𝑑act of somepoints are shown in Fig. 6. It shows a trend that thelarger 𝑑act is, the smaller the apparent field intensity
at breakdown is.
According to the research of the effect of electrode-tip’s curvature on the field intensity by Nurishi[3], the theoretically analytical field intensity islarger than the apparent field intensity by the effect of
the curvature. The effect increases as 𝑑act increases.
Therefore, by taking into account the effect of cathode’s curvature in the field intensity, the experimental
points might be compensated upward approaching theanalysis result. The amount of the shift is large as apparent field intensity is small. Thus, it is suggested

6. Reference[1] T.Omata,‘Effects of Arc Current and Voltage between Electrodes on Arc Reignition in DC Arc Discharge”, Mate2017, 23rd Symposium on “Microjoining and Assembly Technology in Electronics”, 2017,
Jan.
[2] Y.Murooka, K.R.Hearne “The Effect of Electrode
Temperature on Spark Brearkdown Voltage” The transactions of the Institute of Electrical Engineers of Japan.A[3] 塗師豪太, 2017 年度学士論文

122

Image Feature Extraction by Sliding Discrete Fourier Transformation
Student’s ID: 15B08321 Name: Sun Xu Supervisor: Yamasita Yukihiko

1

Introduction

3

Diﬀerence of Gaussian to approximate Laplacian of Gaussian

In the fields of computer vision, pattern recognition,etc, object recognition has been intensively studied as
an important research theme. It is realized by associLaplacian of Gaussian is given byating feature points in two images. The corresponding( 2)
feature points in two images must be detected from ax + y2x2 + y 2 − 2σ 2
exp −.
GDD (x, y) = −unique point. The local feature is described with re2πσ 62σ 2spect to the feature point, and they can be associatedbased on the feature.
We denote Laplacian of Gaussian by LoG.
The diﬀerence of Gaussian is given by the diﬀerThere are two important points in feature point deence
between two images given by Gaussian Smoothing
tection. The first is the exact location of a featurewithtwo diﬀerent parameters. Let a smoothed image
point, and the second is high repeatablity. Many feabeL(x,y, σ), then the diﬀerence of smoothed image isture point detection methods have been proposed ingivenbyD(x, y, σ) = L(x, y, kσ) − L(x, y, σ).
order to improve locarization and repeatability. One ofPartialdiﬀerentiation of the Gaussian function withthe detection methods to extract characteristic points
respecttothe standard deviation σ has relationshipthat are invariant against rotation and scale change
with
LoG,
which is ∂G∂σ = σ∆G. Also, by combining
is called ”SIFT”(Scale-Invariant Feature Transformadiﬀerential
approximationof partial derivatives, we cantion), which is provided complete by David Lowe inG(x,y,kσ)−G(x,y,σ)
∂G
have
σ∆G
=
≃
. Then, we know
2004.
∂σ
kσ−σ
(k − 1)σ 2 ∆G ≃ G(x, y, kσ) − G(x, y, σ) can express
In SIFT, feature points are extracted using the difapproximation.
ference of Gaussian that in an approximated methodfor Laplacian of Gaussian. This paper proposes to use
the sliding discrete Fourier transformation (we denote 4
SIFT
it by SDFT) to calculate the diﬀerence of Gaussianand Laplacian of Gaussian, then applies it to SIFT to
SIFT (scale-invariant feature transformation) can bedetect feature points and confirms the eﬀectiveness by separated into 5 parts.
experiment.
The first part is the extreme value detection in scale

2

Mathematical Preparation

Gaussian smoothing is a process of blurring an image
using a Gaussian function. It can be applied to noise
removal, preprocessing of edge extraction, etc.
Let the coordinates of the image before rotation be(x, y), the coordinates of the image after rotation withrotation angle θ be (x′ , y ′ ), then rotation of an image
is defined by the coordinate transformation with
(

x′
y′

)

(
=

cos θ
sin θ

− sin θ
cos θ

)(

x
y

)
.

Scale change in SIFT means that the convolutionof the input image with the two-dimensional Gaussian function with standard deviation σ, that is, Gausssmoothing.

space. We need to use a lot of smoothing parameters
σ to apply to the Laplacian of Gaussian filter. This σ
can be regarded as a scale-parameter. And we often use
the diﬀerence of Gaussian for approximation to search
local extrema of an image over scale and space.
The second part is the localization of key points. We
calculate detailed cordinates of key point candidates.
In SIFT, we use Taylor expansion of the scale space
to obtain an extreme value, and delete the key points
candidates with a certain threshold value. After that,
we use Hessian matrix to delete the key points on edges.
The third part is to calculate the orientations of key
points, because we want to obtain rotate-invariant features. Depending on the scale, we extract the points
around the keypoint, then calculate the magnitude andthe orientation of the gradient in that region. We created a gradient histogram for all directions of 360 degrees with 36 bins, and the maximum direction is taken
as the orientation of the key point.
The fourth part is to describe the features. We extract 16 × 16 areas around the key point. We divide
them into 4 × 4 small blocks. For each small block,
we create a gradient histogram with 8 bins. Then, we

123have 128 values for each key point. A feature vector of
Table 1: Matching and extraction accuracy with 90the 128 values is constructed.
degree-rotated image
The fifth part is matching of key points. In SIFT,
SIFT
SIFT-SDFT
we use distance to match key points one by one.
Matching
99.26%
100.00%
Point extraction 67.59%
82.63%

5

Gaussian smoothing using
sliding discrete Fourier trans- Table 2: Matching and extraction accuracy with 180degree-rotated image
form
SIFT
SIFT-SDFT

According to [2], we can approximately calculate the convolution between Gaussian function, andsecond derivatives of Gauss∑Pfunctions, and an input image by g(n) ≃p=0 ap cp (n), gD (n) ≃
∑P
∑P
b
s
(n),
g
(n)
≃
where
DD
p=1 p pp=0 dp cp (n),cp (n) and sp (n) are coeﬃcients of SDFT of input
f (n), ap , bp , and dp are the coeﬃcients of Fourier
series of Gaussian function and its derivatives. They
can be calculated in advance. In order to calculatecp (n) and∑nsp (n), according to [2], we can use formulasu(n) = k=0 f (k)eiβpk , v(n) = u(n)·e−iβpn , v(n+1) =2 cos (βp)v(n) − v(n − 1) + f (n + 1) − eiβp f (n).

6Experiment

Matching
Point extraction

99.74%
63.47%

100.00%81.71%

Tables 1 and 2 show the accuracies of matching andextracted feature points.
The number of feature points extracted by the proposed method is fewer than SIFT. The reason is thatwhen SIFT extracts feature points, it enlarges the input image size by 2 times in order to obtain more feature points. The proposed method just uses the original size of input image.
The computation time is longer. Because SIFTSDFT needs to calculate Gaussian smoothing and LoG
seperately while SIFT just calculates Gaussian smoothing once and then takes diﬀerence of results of Gaussiansmoothing to approximate LoG.
Regarding to the accuracy of matching, both SIFT
and SIFT-SDFT have a similar high accuracy. However, regarding to the accuracy of extracted featurepoints, the proposed method is about 15% better than
SIFT.

I propose a new feature point extraction method
named SIFT-SDFT. The SIFT-SDFT method changes
the Gaussian smoothing and DoG in SIFT to Gaussian smoothing and LoG by the sliding discrete Fouriertransformation. There is no change in feature description. We will use test images to compare the eﬀect
between the SIFT and SIFT-SDFT. We will compare 7
Consideration
the accuracy of extracted matching and feature pointby using digital photo with rotations.
This paper proposes the method using sliding disIn Figures 1 and 2 we show matching results by two crete Fourier transformation to extract feature points
methods.
of an image. We confirm the matching and extraction
accuracies by proposed method is better than the standard SIFT. Future works are to increase the number ofextracted feature points, and to verify the adaptability
for projective transformation.

References[1] David.G Lowe,”Distinctive Image Features
from
Scale-Invariant
Keypoints”,Computer
Science
Department,UniversityofBritishColumbia,Vancouver, B.C., Canada,January
5,2004.

Figure 1: Matching by SIFT

[2] Yukihiko Yamasita and Toru Wakahara, An initial search method for region-based image matching , Technical Report of IEICE, vol.118, No.219,
PP.119-124, 2018.

Figure 2: Matching by SIFT-SDFT
124

食品安全認証の取得有無と日本食品企業の特徴との関係
学籍番号：15B07340

氏名：周 温文

1． 研究の背景と目的

指導教官：阿部 直也

宣伝し、顧客の購買行動に影響を与えられる。三

食品の安全性を確保し、維持することはどん

つ目は国の食品安全に対する政策の要求に応えな時代においても重要性の高い課題だと考えらられるために、食品安全認証を採用しているか。

れる。現在の日本では、「安心」かつ「安全」にも国や企業の実状によって目的が違うが、日本企業のを食べるのが当然のことである。しかし、大規のことがまた分析されていない。

模食中毒が多発してきた。例えば、1968 年カネミ

２．研究の枠組み

倉庫社製の食用米ぬか油による食中毒事件、ま日本における株式会社東京証券取引所、市場第た 2000 年にも、雪印乳業（現：雪印メグミルク）

一部（いわゆる東証一部）に上場している 73 社のの「雪印低脂肪乳」が原因の黄色ブドウ球菌食中

食品関連企業による「FSSC22000 認証」、「ISO22000

毒事件も発生した。これらの事故の原因となるの認証」及び「HACCP 認証」の得状態について把握

が生産管理の不十分である。多くの研究では、食するために収集・使用いたデータおよびその分析

品の安全性を向上させる方法として、食品安全認枠組みを提示する。東証一部 73 社の会社の 2018

証および管理システム採用に焦点を当てている。

年 IR 情報から、2017 年の売り上げ、営業利益や国際食品安全認証は主に三つがある。一つは、従業員数を取集し、また各会社のホームページか

潜 在的 な危 険が プロ セス を特 定し て管 理する

ら食品安全認証の情報を収集した。

「HACCP 認証」である。もう一つは全てのサプラ

具体的には各社の認証の取得の有無を確認し、イチェーンやフードチェーン（関係者）をカバー

名義尺度の変数とした。また、データの精度を上できる「ISO22000 認証」である。最後に管理シスげるために、食品会社各工場の認証状態を確認し、テムの要件と ISO 技術基準に基づき、特に腐敗し認証を取っている工場が工場全体に占める割合やすい食物のために発行される「FSSC22000 認証」を算出した。そして、まずはクロスター分析をしである。日本では食品の安全を守るために食品委て、データ全体像を把握した後で、より詳しい結

員会、厚生労働省、農林水産省などがそれぞれ担果を求めるために、一元配置分散分析（ANOVA）を当する「リスク評価」、「リスク管理」、「リスクコ

用いて、各種の「食品安全認証」と「会社の収益」

ミュニケーション」の３要素がお互いに働いていとの関連性を分析する。次に、その結果に基づいる。また現在国内の食品安全認証がない。

て関連性のあるデータに対してさらに多重比較
2

現在、一部の日本の食品企業は食品安全認証を行う。またχ 分析を使って、食品カテゴリーにを積極的に取っているが、一部が全く採用しなより分類したデータから、企業が認証を採用する

い。食品安全認証の取得有無と日本食品企業の目的を検討する。

特徴との間にどんな関係があるか。

３．分析の結果及び考察

既存研究のレビューにより、食品企業が食品安全認証を採用する目的は主に三つがある。一つ目

表.１研究データ全体像

はより効率的な生産管理を求めるということである。認証を採用した後で、内部生産のプロセス、手順の定義とモニタリングの改善をできるため、生産効率を向上できる。効率の改善により、企業の生産コストを減らせると考えられる。二つ目は認証の採用により企業の公的なイメージを変えられて販売を促進できるということである。食品
安全認証の力を借りて自社製品の安全性などを125

認証」を採用する傾向がある。理由も同じである。

表.2「利益率」と「HACCP 認証」採用割合の検定
Df

Sum SqMean Sq

F value

Pr(>F)

Performance2

2.838e+08

0.006068

3.474

0.0364

Residuals

70

3.154e+100.001746

表.4「飲料」と「ISO22000 認証」との分析
認証
商品
取り扱わない

なし

あり

23

31

54

「HACCP 認証」を採用する企業の平均利益率は

取り扱う

14

5

19

4.1％であり、「HACCP 認証」に基づいて管理を行

合計

37

36

73

う企業あるいは一部の工場のみ認証を採用する

2

𝜒 結果

合計

0.019

企業の平均利益率は 4.7％であり、また認証を採用しない企業の平均利益率は 7.3％である。つま「飲料」の会社は「ISO22000 認証」を採用す

り、「HACCP」認証を採用しない企業ほうがより高る傾向がない。実は、飲料が長期保存、品質改い利益率を生み出している。

良や酸化防止のためにいろいろな化学添加物が理由が主に二つがあると考えられる。一つ目は加えている。そこで、生産現場の衛生管理や安商品の包装にも「HACCP 認証」の標識を示してい全保障がもちろん重要だが、化学添加物のコンないので、企業は「HACCP 認証」の力を借りってトロールが一番重要なポイントだと考えられ

宣伝するわけではないと判断できる。そこで、企る。サンプル中の「飲料」企業の「ISO9001 認

業は生産の安全性を確保して生産効率を向上さ証」の採用率は 42％であり、この「ISO9001 認

せたいために、「HACCP 認証」を導入したと考えら

証」は食品の品質を確保する認証である。もうれる。また 73 社うちの 5 社は日本国内で、「HACCP

一つの理由としては飲料製品がほとんど個人向認証」を採用していないが、海外工場や支社が認けの商品であり、かつ日本の消費者が第三者の証を採用している。これはやはり海外（特に欧米、

食品安全認証に関心を持っていないので、飲料

アジアの一部の地域）で水産食品や食肉製品など企業が第三者認証を取らない傾向がある。またの製造施設への HACCP の導入が義務化されている。

海外と貿易するために認証をとる視点から、飲これも「HACCP 認証」を導入する一つの理由であ料は基本的に日本国内で売っているので、国際る。

の食品安全認証をとる必要がないと考えられまた検定結果により、「FSSC22000 認証」やる。

4．おわりに「ISO22000 認証」の採用が「企業収益性」と関係がないということが分かった。

本研究では過去日本の食中毒事件を振り替えながら、食品安全認証の重要性を示した。結果と表.3「冷凍食品」と「ISO22000 認証」との分析
認証

なし

あり

合計

商品
取り扱わない36

27

63

第三者安全認証を導入したという可能性が高い

取り扱う

1

9

10

と考えられる。食品安全認証と企業の売り上げや、

合計

37

36

73

従業員数や営業利益と関連性がないということ

𝜒2 結果

0.005

しては日本食品企業は安全性を確保できようにが分かった。最後に企業が海外や国内の食品安全政策に従って食品安全認証を取っている。

「冷凍食品」の会社は「ISO22000 認証」を採用

今後の研究では企業のイメージと食品安全認する傾向がある。冷凍食品は長期保存を目的に冷証の関連性について研究を行う。

凍状態で製造・流通・販売されているために、低温にすることで微生物の活動を抑える。麺粉など

参考文献の商品と比べてより高い生産技術が求められる。

[1]HACCP 認証協会

つまり、会社は安全性を確保できように

https://www.th-haccp.com/haccp/「ISO22000 認証」や「HACCP 認証」を採用してい（閲覧日：2019 年 2 月 1 日）る。

[2] 栗原「肉・海鮮・卵」グループの𝜒 2 結果が 0.06 であ[3] A.Moore.D. (2004). DairyBeef: Maximizing

る。そこで、「肉・海鮮・卵」の会社も「FSSC22000

伸一. (2011). 入門統計学.オーム社
Quality and Profits

126

GPU acceleration of initial search method for regional image matchingStudent’s ID: 15B15829 Name: Moran Lee Supervisor: Yamasita Yukihiko

1

Introduction

be calculated as dq ≃Image matching is applied to object detection andpattern recognition, which is one of the most important
methods in image processing. Therefore, many image
matching methods have been proposed. They can beroughly divided into two types, one is a feature point
matching method as extracting feature points from theimage and evaluating the consistency of the featurepoints, and the other is a region matching method as
evaluating the consistency of a image region.
Furthermore, depending on the spatial relationshipbetween the template image and the input image,
matching can be divided into whole-to-part and wholeto-whole matching. Yamashita and Wakahara proposed a fast initial search method for whole-to-partmatching. GPU can be used to further accelerate themethod for real time computation. In this paper I propose the implementation method and compare it withCPU calculation.

IX (x,y)−iIY (x,y)q
2π(∥I1 (x,y)∥2 +ϵ)

q−1
2. In this case,when rotating the reference direction by θ0 , the coeﬃcients d′q of the rotated histogram can be obtained as
d′q = dq e−iqθ0 .
Using fast calculation of Gaussian convolutional sum
and Q-th order Fourier series of edge direction histogram, the feature value calculation of the initial
search method for regional image matching can be described as follow.

Algorithm 1 Calculate Feature Values of Region
Require: Input Image I, a set of scales Sa , a setof center points for feature values TS , The regularized coordinates of points where histograms are used
(xm , ym ) (m = 1, 2, ..., M )for S ∈ Sa do
Calculate Gaussian diﬀerentiation of I with scale
S/8.
Calculate the edge direction histogram dq .
Calculate Gaussian smoothing of dq in scales S
and S/4.
for (x, y) ∈ TS do
2 Fast calculation of Gaussian
Calculate the orientation(s) of the region withconvolution integral
the smoothed coeﬃcient in scale S.
for θ0 ∈(the set of orientions) do
Gaussian smoothing is a process of blurring an image
Calculate cordinates of points where hisusing a Gaussian function. It can be applied to noise
tograms are used.
removal, preprocessing of edge extraction, etc.
Gaussian smoothing is a convolutionalsum given by
x′m = S(xm cos θ0 − ym sin θ0 ) + x∑K
the following expression O(n) ≃ k=−K G(k)I(n − k).
′ym= S(xm sin θ0 + ym cos θ0 ) + y
Since Gaussian function is an even function, thediﬀerentiated Gaussian function is an odd function.
Rotated edge direction histogram in scale S/4
Therefore, Gaussian function can∑Pbe approximated by
and get M (2Q + 1)-dimensional vector.
the cosine function (G(k) ≃p=0 ap cos (βpk)) andNormalise the obtained vector as its norm is
diﬀerential Gaussian function∑Pcan be approximated by
1 and store it as feature values at the region.
the sine function(Gd (k) ≃ p=1 bp sin (βpk)).
end forWe define the convolutional sum of finite interend forval trigonometric∑functions as the following equaend forKtions, cp [n] =k=−K I[n − k] cos(βpk), sp [n] =∑K
k=−K I[n − k] sin(βpk). Then, we can get a O(P N )The feature values of the target region in the temalgorithm to calculate Gaussian convolutional sum as
plateimage and of regions around sample points are
iβpfollows, [v[n] = e v[n − 1] + I[n], cp [n] + isp [n] =calculated.
Then, the inner product between featurep(−1) (v[n + K] − v[n − K] + I[n − K]).
values in the template image and input image are calculated. The region in input image that maximizes the
3 Initial search method for re- inner products is given as the matched region.

gional image matching4

Calculation by GPU

The edge direction histogram D(θ) is weighted sumof the strength of edges in each edge direction in a cerGPU calculation is a kind of SIMD (single instructain region. It can∑be described by a Q-th order Fourier tion multi data) calculation, which means the sameQ
series as D(θ) = q=−Q dn eiqθ . The coeﬃcients can task is applied to diﬀerent cores to process multiple
127data. GPUs of NVIDIA use warp schedulers to control jobs in the core. Therefore, we need to decrease
the branches (if statement) of calculation to increase
eﬃciency of calculation.
GPUs also use cache memory to accelerate calculation. Therefore, the eﬃciency of calculation can be increased by increasing the cache hit rate. And the best
access pattern is given by Figure 1, where the cache hit
rate is 100%.

At first, I calculate the compute time of CPU calculation (CPU). Secondly, I calculate the normal compute
time of GPU calculation (GPU 1). Thirdly, we calculate the compute time of GPU calculation in whichmemory access is optimized (GPU 2). I calculate compute time of optimized GPU calculation with threescales which can show its eﬃciency in real world application (GPU 3).
Because the hardware spec aﬀects the calculation efficiency, we use two types of computers to collect experiment data.
Table 1: Comparison of Compute Time(ms)940MX(6500U) 1060(7700K)
CPU
742
509
GPU 1
160
66
GPU 2
156
31
GPU 3
136
22

Figure 1: Best memory access pattern
The worst memory access pattern is given by Figure
2, where the cache hit rate is 12.5%.

As we can see, the computation time of CPU is atleast 5 times more than computation time of GPU. Furthermore optimized calculation has a better eﬃciency
than normal one. Also, it can be calculated within 100
ms for the calculation with three scales, and it will enable 10fps in the initial search. Therefore, the propesd
method it can be applied to real-time applications.

Figure 2: Worst memory access pattern

5

Optimization of initial searchmethod by GPU
7

In the initial search method for region-based image
matching, at first, we calculate Gaussian smoothing of
dq in scale S and S/4 at all points. Then we calculate
the feature values for sampling region, and sort to findthe point which matches the region in the template
image best.
Because of the property of the warp scheduler, GPU
is not suitable for sorting. Therefore we use CPU to
do this job. Because of the same reason, we use CPU
to find the point which matches the region best.
Almost all jobs in calculation of all Gaussian smoothing of dq in scale S and S/4 can be calculated in parallel, because the jobs for a point don’t have dependency.
But the calculation of Gaussian convolution integral ata point is dependent of the result at the former point.
Therefore, we divided tasks by rows and tasks for arow is assigned to a core.
But if we assign jobs for a row into a core, the memory access pattern becomes the worst. Therefore I optimize the calculation to increase the cache hit rate.
For the purpose, I store results for a row into a column
memory structure. Then transpose the data for the
next step.

6

Conclusion

This paper proposed to accelerate initial searchmethod for regional image matching and realize realtime computing by GPU. We confirm the accelerationand its practicality for real-time processing by experiments. Future works are to increase the hit rate ofcache memory in read access, which may further accelerates the method.

References

Experiment

I use a standard image Lenna (512px×512px) tocompare the eﬀect between CPU calculation and optimized GPU calculation of the initial search method forregional image matching introduced before.
128[1] John Cheng,Grossman,McKercher,(2015)『CUDA
C professional programming』,(translated by
Sinya Morino) Impress Company, 2015.
[2] Yukihiko Yamasita and Toru Wakahara,”An initial search method for region-based image matching”,Technical Report of IEICE, vol.118, no. 219,
PP.119-124, 2018.

All-day energy harvesting power system utilizing a thermoelectric generator
Student Number: 15B16421

1

Introduction

Name: Yasuki Kadohiro

Supervisor: Jeffrey Scott Cross

Black paint is used as a light absorbing film. A portionof the heat pipe and around TEG are covered by glass
wool in order to reduce the heat loss from System 2.
During the daytime, solar radiation passes throughFresnel lens and is concentrated on the flat aluminumheat pipe 1. The heat transfers from the concentrated
solar radiation to cold water. Temperature differences of
TEG are made by the concentrated solar radiation andcold water. In the experiment, a halogen lamp is used tosupply the light since the solar radiation is unstable andthe halogen lamp has a similar wavelength as solar radiation. The power is set to 11.29W , 14.84W , and 21.17W .
The voltage and water temperature are measured in theexperiment.
During the nighttime, cold water (tap water) is
poured into the water tank 1. The heat transfers fromthe hot water to the cold water via the TEG. The temperature difference generates voltage. Temperatures of hot
water and cold water are measured in the experiment.

After the Great North East Japan earthquake in 2011,
distributed energy systems using renewable energy havebecome popular topics of research [1], and especially, solar power generation systems are being installed worldwide [2]. However, this system has a critical limitationthat it cannot generate electricity during the night whenpeople use the most electricity. Energy demand is increasing year by year and it is considered that the energy
problem will become the first of the humanity’s top ten
problems over the next 50 years [3]. Therefore, the systems which can generate electricity not only in the daytime but also in the nighttime is necessary. Moreover,in building applications, hot water is also in demand in
addition to electricity so the system should produce hotwater too.
Ashwin et al. [4] proposed a system combining solar water heating systems and thermoelectric generator(TEG). A TEG is the device which can generate electricity by utilizing the temperature difference between its
Solar
Daytimetwo surfaces. The temperature difference is made by theconcentrated solar thermal energy and the water stored
in the tank, and the heat transfers to the water. The system is able to generate electricity and produce hot water.
Fresnel lensHowever, the system operates only during the day andWater tank 2 Cold water
Weightcannot generate electricity after the sun goes down.
Pressure
In this thesis, an all-day energy harvesting power system utilizing a TEG was researched in order to generate
Cooling TEG
electricity both day and night. The proposed system is
Heating
based on Ashwin’s model but the difference is that theWater tank 1
Flat aluminum Styrene foam
Flat aluminum
system heats water during the day in order to generheat pipe 2
heat pipe 1
ate electricity at night. Two different systems (System
1 and 2) were designed and developed to investigate the Fig. 1: Schematic of System 2, Daytime (Solar light andbest mechanism for the all-day energy harvesting system. Cold water).
The experimental and analytical study was conducted toinvestigate the system’s potential.

2

Nighttime

Experimental Approach

System 1 was designed based upon Ashwin’s model. The
schematics of System 2 are shown in Fig 1 and 2. In
Water tank 2 Hot water
System 2, two flat aluminum heat pipes (flat aluminum
Cold water
Weightheat pipe 1, 2) are used due to their high heat flux carPressure
rying capacity and each of them is thermally coupled
Heating
to TEG’s upper and lower sides by thermally conductive tapes. Metal weights (3087.5g) are placed on TEG
Cooling
Water tank 1
and flat aluminum heat pipe 1, 2 in order to reduce thethermal resistance between TEG and flat aluminum heatpipe 1, and 2. A portion of the flat aluminum heat pipe 1 Fig. 2: Schematic of System 2, Nighttime (Hot water andin the water tank 1 is covered by a black absorbing film. Cold water ).
129

3Results and Discussion

ble. In terms of thermal efficiency during the nighttime,
it is observed that the thermal efficiency of System 2 isIn the experiment, voltage is measured and from the re- lower when compared to the thermal efficiency of othersults, it is observed that System 1 and 2 can constantly systems during the daytime. The heat loss must be regenerate electricity during the daytime. However, Sys- duced and it is necessary to make the value of thermal
tem 1 cannot generate electricity at all at night. System efficiency more than 60% (near to the thermal efficiency
2 can generate electricity at night but the voltage de- during the daytime). However, System 1 and Ashwin’s
creases over time due to the decrease of the temperature model cannot store heat and generate electricity at nightdifferences across the TEG. Therefore, countermeasures so it is obvious that System 2 has the highest potential
are necessary for System 2 to satisfy potential consumers for all-day energy harvesting.
who use electricity for 3 ∼ 5 hours at night. Comparing
the best case scenarios relating to voltage when there isConclusions
no heat loss, System 2 has an efficiency of 62 ∼ 65% and 4
60 ∼ 65% of the TEG s maximum performance during
Three systems have been compared and the results indithe day and the night, respectively.
Table 1 shows the comparison of the thermal and elec- cate that System 1 or Ashwin’s model is the best system
trical efficiency between System 2 and Ashwin’s model [4] to generate electricity and to transfer the heat during theor System 1. Since Ashwin’s model or System 1 cannot daytime, and System 2 is the best system to generate
generate electricity and the voltage decreases over time electricity and to transfer the heat during the nighttime.
in System 2 at night, the electrical efficiency during the Comprehensively, System 1 or Ashwin’s model cannot
produce hot water and generate electricity during thenighttime is not shown in Table 1.
nighttime so it is considered that System 2 is the bestsystem to generate electricity all-day and to produce hot
Table 1: Comparison of the systems
water. From the study, it is proven that System 2 canstore 60 ∼ 65% of the input solar thermal energy during
Ashwin’s model
Results
System 2
the daytime and it can recover 35 ∼ 50% of the stored
or System 1
thermal energy. Moreover, it is proven that System 2 exηelectrical
0.68% (14.84W)
1.29% (14.84W)
hibits an efficiency of 60 ∼ 65% of the TEG s maximum(Daytime)
0.99% (21.17W)
1.87% (21.17W)
performance during the day and the night, respectively.
(System 1)
However, the electricity generation is not sufficient at
ηthermal
65.3% (14.84W)
57.6% (20W)night due to the voltage decrease over time so System(Daytime)
65.4% (21.17W)
55.0% (40W)
2 must maintain a constant temperature differential as(Ashwin’s model)much as possible to generate higher electricity and toηthermal
48.4% (m1 =1000g)
satisfy potential consumers.
(Nighttime) 37.2% (m =2000g)
1Here, m1 is the mass of hot water in the storage tank.
As mentioned, System 1 has same structure or mechanism as Ashwin’s model. Both systems are concentrating the solar radiation on TEG’s hot side directly. In theabove table, it is observed that System 1 has higher electrical efficiency than System 2. It can be considered thatthe mechanism of System 1 (or Ashwin’s model) has moreadvantages than the mechanism of System 2 to generate
electricity during the daytime. Here, the results of Ashwin’s model are not used since the electrical efficiency
depends on not only the mechanism of the system but
the performance of the TEG. A different TEG is usedin the Ashwin’s model, so System 2 is only comparedwith System 1. In terms of thermal efficiency during thedaytime, it is observed that System 2 has higher thermal
efficiency than Ashwin’s model. It can be consideredthat the heat loss in the proposed systems (System 1
and 2) is smaller than the heat loss in Ashwin’s model.
Since System 1 and Ashwin’s model did not store heat in
the water during the nighttime, the thermal efficiency of
System 2 during the nighttime is only shown in the ta-

References[1] Miguel Esteban, Joana Portugal-Pereira. (2014).
Post-disaster resilience of a 100% renewable energy
system in Japan. Energy, 68, 756-764.
[2] Omar Ellabban, Haitham Abu-Rub, Frede Blaabjerg.
(2014). Renewable energy resources: Current status,
future prospects and their enabling technology. Renewable and Sustainable Energy Reviews, 39, 748764.
[3] Geoff G. X.Wang. (2012). Development of clean energy and environmental technologies to address humanity s top problems. Frontiers of Chemical Scienceand Engineering, 6(1), 1-2.
[4] Ashwin Date, Abhijit Date, Chris Dixon, Aliakbar
Akbarzadeh. (2014). Theoretical and experimental
study on heat pipe cooled thermoelectric generatorswith water heating using concentrated solar thermalenergy. Solar Energy, 105, 656-668.

130

Liquid-Liquid Equilibria of Terbium and Dysprosium with PC-88A as Extractant
Student Number: 15B05506 Name: Junki KURIHARA

Supervisor: Ryuichi EGASHIRA, Hiroaki HABAKI

1. Introduction
Rare earth elements (REEs) are used in various
industrial products, such as, the electric vehicles and air
conditioners, in which Ne-Fe-B magnets containing
neodymium, terbium (Tb) and dysprosium (Dy) areused[1][2]. Since the REEs coexist in the ores and theindustrial products usually contain multiple REEs, theseparation of REEs in the ore or the recovery of themfrom industrial product wastes must be important
technology.
The solvent extraction is commercially used as amethod to separate REEs. Although a number of works
on the separation of REEs by solvent extraction havebeen reported, there are only few studies focusing on
the equilibria in the single element system of Tb or in
the binary element system of Tb and Dy, whose
chemical properties are quite similar, making
separation difficult.
In this work, the extraction equilibria were studied
in the single element system of Tb or Dy, and the binary
element system of Tb and Dy, using PC-88A as an
extractant.

Table 1 Experimental conditions
Initial metal concentration
CM,aq,0 ( M=Tb, Dy )-Single element system-Binary element system

0.005 kmol m-3
0.005 kmol m-3(for each)

Initial pH
pH0

Concentration of extractant
CRH2,org,0Aqueous phase volume
Vaq

Organic phase volume
Vorg

0.0~2.0
0.25 kmol m-3
2.0×10-5 m3
2.0×10-5 m3

Extraction temperature

298 K

Extraction time

12 h

The metal concentration in the organic phase CM,org,eq
at equilibrium was obtained using Eq. (2) with CM,aq,0and CM,aq,eq directly measured. The concentration of
extractant in the organic phase at equilibrium wascalculated as,
CRH2,org,eq =CRH2,org,0 -3CM,org,eq(3)
Using the equilibrium constant (KM ), Eq. (1) can be
rewritten as Eq. (7), where D is the distribution
coefficient, defined as,
D = CM,org,eq / CM,aq,eq(4)

2. Experimental
Chloride salts of Tb and Dy in analytical gradewere used as metal ion sources. PC-88A (2Ethylhexyl-2-ethylhexylphosphonate) was used as an
extractant. Table 1 shows the experimental conditions
for liquid-liquid equilibrium measurement. The feedsolutions containing Tb or Dy for the single metal ion
system, or Tb and Dy for the binary metal ion systemwere prepared. The initial molar concentrations of themetal ion in the aqueous phase and the extractant in theorganic phase were fixed. The initial pH was adjusted
using hydrochloric acid. Kerosene was used as a diluent
to prepare the organic phase. The aqueous and organic
phase of the same volumes were contacted each otherin conical flask and shaken for 12 hours to reachequilibrium. Then, the aqueous phase at initial andequilibrium conditions were analyzed to determine therespective pHs and metal concentrations, using pH
meter (F-74, Horiba) and ICP-AES (SPS7800, Hitachi
High-Tech Science Corp.).

logD-3 log CRH2,org,eq =3pH+logKM(5)Fractional extraction of metal ion EM and solvent free
metal mol fraction in phase j, xM,j were defined as,
EM =CM,org,eq /CM,aq,0(6)
xM,j =CM,j,eq /(CDy,j,eq +CTb,j,eq )where j stands for aq or org.

(7)

Single element system
In all cases, the pH at equilibrium became lower
than that at initial condition since hydrogen of theextractant was released by the extraction of metal ions.
The plots of EM in the single systems against theequilibrium pH are shown in Fig. 2. In the range of low
pH, both REEs were little extracted into the organic
phase.in the range of pH of 0 to 0.5, both elements
started to be extracted. Change of fractional extraction
was significant in the range of pH of 0 to 1, and over
90% of REEs were extracted when pH was higher than1.
The terms of the left hand of Eq. (5) were plottedagainst the pH at equilibrium in the case of the single
metal ion systems, as shown in Fig. 2. According to Eq.

3. Results and Discussion
Reaction equilibrium of the trivalent rare earth
metal ion between aqueous phase and organic phasewith PC-88A, is generally described as,(1)
M3+ + 3(RH)2 ⇄ MR3 (RH)3 + 3H+
where the overbar and (RH)2 stands for thecompound in the organic phase and extractant in dimer,
respectively. The material balance equation was
expressed as,
Vaq,0 CM,aq,0 =Vorg,eq CM,org,eq +Vaq,eq CM,aq,eq(2)131Metal mol fraction xM,j [-]Fractional removal EM [-]pH

pH
Fig. 3 Mol fraction of each REE in each phaseFig. 1 Fractional removal vs. pH at equilibrium
in single or binary element system

The extraction equilibria with the binary system
containing both Tb and Dy ions are shown in Fig. 2,
together with those with the single systems. The resultswith the binary system were approximately the same as
those for the respective metal ions with the single
systems, and no effects of the coexisting metal ionswere found in this measurement range.
Plots on Fig. 3 show the mol fraction of each metalin organic phase. Mol fraction of Dy was higher than
Tb at the lower pH while almost same mol fraction was
obtained at the higher pH. From this result, purification
can be obtained when pH is low, but as Fig. 3 shows,
REEs are not extracted into organic phase at the lower
pH, such as less than 0.5, so the concentrations of bothelements should be low.
The mol fraction of each metal in aqueous phaseis also shown on Fig. 3. In contrast to the result inorganic phase, mol fraction of Tb is higher than that of
Dy and the higher pH made the larger difference of mol
fraction. When pH is higher than 1, although thedifference of mol fraction between the 2 elements was
relatively wide, over 90% of elements were extracted
into organic phase. From the results shown on Fig. 1, it
is declared that batch separation or purification is notenough in this condition, and for the further separation,
multistage process should be considered.

(5), the slope of the line of the plots with each metal ion
should be 3, and it was found that both reactions of Tb
and Dy with PC-88A in the single systems followed Eq.
(1). Then, the reaction equilibrium constants of KTb
and KDy were estimated as 1.34 and 2.99, respectively.
The Dy ion was extracted more than Tb because theheavier REEs should be generally extracted more thanthe lighter ones.
The separation factor between Tb and Dy wereobtained as βDy,Tb =KDy / KTb =2.2. Then, βDy,Tb was
relatively low and the separation between Tb and Dy
was found to be relatively difficult by the solvent
extraction.

logD-3logCRH2,org,eq

Binary element system
pH change was also observed in the binary
element system and the decrease was more significant
than that in the single element system because thelarger amount of REE was extracted.
The plots of EM in the binary systems against theequilibrium pH are shown in Fig. 2. Trend of extraction
was similar to that in the single system.

4. Conclusions
From the experiment on the single element system,
extraction coefficient of terbium and dysprosium andthe separation factor were estimated; KDy =2.99 ,KTb =1.34 , βDy,Tb =2.2 . From the experiment on thebinary element system, extraction trends were clarified.
5. Reference[1] Y. Arai et al., 廃棄物資源循環学会誌, Vol. 22,
No. 1, p. 41-49 (2011)[2] S. Ishihara et al., Chishitsu News, No. 609, p. 418 (2005)
pH
Fig. 2 Slope analysis of terbium anddysprosium in single and binary system132

Enhancing NH3 recovery from aquaculture sludge compostingby inoculation of the sludge solubilizing bacteria
Student Number: 15B10306

Name: Ryo NAKAGAWA

Supervisor: Kiyohiko NAKASAKI

1. Introduction

Aquaculture sludge was obtained from the

The accumulation of aquaculture sludge on thebottom of a shrimp pond in Malaysia. Thisbottom of pond could decrease the quality of thesludge is fresher than the sludge used in ourwater and affect to the shrimp culture. The

previous paper[1], so that it contains almost

efficient strategy to treat aquaculture sludge

double amount of easily degradable organicfrom the pond has not been yet established.

matter compare to that sludge. Lab-scale

Methane fermentation and composting are wellcomposting

known as methods to treat the aquaculture

examinesludge, but their products has low values. Thus,

temperature conditions (50, 60, and 70°C). The

a way to improve the value of the products issludge was mixed with sawdust and commercial

importantseeding material with the mixing ratio of 5: 14:

for

the

improvement

of

the

experiment

the

was

conducted

toNH3 recovery in different

sustainability of aquaculture industry.

1 in dry-weight base. Total nitrogen content of

Our laboratory recently proposed a new

the sludge, and the content of total dissolved

strategy to recovery of NH3 gas from thenitrogen and NH4+-N in compost sample, andaquaculture sludge by using thermophilic

NH3 gas yield were measured to examine thecomposting [1]. NH3 gas is free from pathogen

nitrogen mass balance during composting.

and heavy metals, so that it can be used for
cultivation of high value micro algae. From the2-2. Isolation of protein-degrading bacteria andnitrogen mass balance analysis of the sludge

inoculation for composting materials

composting [1], it was revealed that NH3

Protein-degrading bacteria was isolated fromrecovery reached 16% of the total N content ofcompost sample in this study by using skim

the sludge, but 65% of N was remained as un-

milk agar medium, by selecting colonies which

decomposed organic nitrogen. Thus enhancing

forms clear zone around the colony on thethe solubilization of sludge is required tomedium. The DNA of the isolated bacteria wasincrease the ammonia recovery. The objective of

extracted and analyzed the sequence. To clarify

this study is to enhance the organic nitrogen

its ability to enhance the sludge solubilization,

degradation in the aquaculture sludge by

the isolated bacteria was suspended in 0.9 w/v%

inoculating the microorganism.

NaCl solution and inoculated to the sludge
composting. Lab-scale composting of the sludge

2. Materials and methods

was conducted in a same way with 2-1.

2-1. Composting of shrimp aquaculture sludge

133

3. Results and discussion

inoculated condition were 45.3% and 38.0%,

3-1. Effect of temperature on solubilization ofrespectively. These results revealed that the R2

the sludge

could be a useful microorganism to increase the

The nitrogen mass balance after composting isammonia recovery from aquaculture sludge

exhibited in Fig. 1. The ammonia (NH3 + NH4+-

compostingN) conversion efficiency of dissolved nitrogen atsolubilization.

byenhancingthesludge70°C was lower than 60°C. These results showthat the composting temperature at 60°C is the
optimum condition for NH3 recovery. On theother hand, more than 60% of nitrogenremained in the compost as non-dissolved N.
Therefore, enhancing the solubility of nitrogenis needed for NH3 recovery.
Fig. 1. Nitrogen mass balance before and after

composting at different temperatures (50°C, 60°C,
Fig. 2. Appearance of the clear zone around R2

and 70°C).

isolate on the skim milk agar medium.

70
100

70
100

60

Non-dissolved NIntermediate N

40

NH4+-N

NH3-N

30

50

Nitrogen (%-N)

Nitrogen (%-N)

60
50

20

Non-disolved NIntermediate N

40

NH4+-N
NH3-N

30
20

10

10
0
Day 0

50℃

60℃

70℃

0

Day 0

Fig. 1. Nitrogen mass balance before and after composting at

inoculated

un-inoculated

Fig. 3. Nitrogen mass balance before and after
composting with and without inoculation of R2
isolate.

different temperatures (50°C, 60°C, and 70°C)

3-2. Effect of inoculation of the R2 isolate
The picture of isolated bacteria (R2) is shown

4. Conclusion

in Fig. 2. It was shown that the clear zone

Protein-degradable bacteria was isolated fromappeared around R2 colony on the skim milkthemedium. It is suggested that the R2 could

compostsample.

Furthermore,

NH3

recovery from composting of aquaculture sludge

degrade the protein and has potential to be used

was improved by enhancing the solubilization of

for the inoculation in order to increase thenon-dissolved nitrogen in sludge by inoculation

ammonia recovery in the composting.

of the protein-degrading bacteria.

The nitrogen mass balance of the sludge
composting with or without the inoculation ofReference

R2 is exhibited in Fig. 3. The solubilization[1] Koyama et al..(2018) Bioresour. Technol., vol.

efficiency of non-dissolved nitrogen, which is265, pp. 207–213

obtained by the formula:[2] Nakasaki et al.(2009) Bioresour. Technol., vol.

（(NH3 + NH4+ -N + intermediate N）/ Total N）

100, no. 2, pp. 676–682

× 100, at the inoculated condition and un-

134New Activation Functions by Simulating Synaptic Plasticity toEnhance Forgetfulness in Neural Network
Student Number: 15B15918

Name: Liu Xiaochen

1. Research Background

One of the reasons why these days, artificial intelligence (AI) technologies based on deep learning neural network, can achieve the best result so far in human history might be the neural network somehow
works familiar to the network made of natural neurons
in human or animal brains. Another reason might be
the none liner functions used in neural networks, such
as ReLU, somehow works familiar to such a neuron.
As an attempt to make AI behave like human being, I tried to redesign the popular activation function
ReLU to simulate a biological neuron better, especiallyby simulating synaptic plasticity mechanism. What I
expect on this simulation is that to find a simple way
to simulate and control the forgetfulness of a neuralnetwork.

creases or decreases in their activity [2]. Some widely
accepted hypotheses suggest that activity-dependent
synaptic plasticity is induced at appropriate synapses
during memory formation [3].
Related to synaptic plasticity, typical mechanismsthat can be roughly described as consistent stimulation signals transmitted by synapse can increase or
decrease the strength of the synapse its self [3].
3. Proposed Method
3.1. Proposed Activation Function

To simulate the connection strength variation between
actual neurons, I designed a new activation functionthat is similar to ReLU function, however, with a learnable parameter a which I called activate strength. This
activation function can be described as
f (x) = max(0, ax).

2. Methodology and Theory
2.1. Biological and Artificial Neural Networks

The human brain consists of a tremendous number ofnerve cells or neurons which form into extremely complex networks. Neurons communicate via electricalsignals, and connection between neurons are called
synapses [1].
Each neuron typically receives many thousands ofconnections from other neurons and all signals fromother neurons are integrated or summed together insome way and, roughly speaking, if the resulting signal exceeds some threshold then the neuron will ”fire”
or generate a voltage impulse in response [1].
On the other hand, an artificial neural network is
an interconnected assembly of simple processing elements, units or nodes, whose functionality are loosely
based on the animal neuron [1].
The key effort to simulate the behaviour of biologicalneuron is to find a mathematical switch function, which
can be turned on and off depending on the value of
input. One of the most popular approach is an activation function called Rectified Linear Units (ReLU),
which can be described as
f (x) = max(0, x).

Supervisor: Yukihiko Yamashita(2)

where a is the activate strength. Combined with the
newly designed parameter updating method which
mentioned in Section 3.2, I call this activation function
as variable ReLU (vReLU).
3.2. Parameter Updating Method for vReLU

Because the tradition way for parameter updating, gradient descent [5], is not appropriate for synaptic plasticity mechanism simulation, I designed a new algorithm to update the parameter, which can be described
as Algorithm 1.

(1)

Algorithm 1: vReLU 1
Data: Input: x
Old parameter: aResult: Updated parameter: a
Set vr = 10−5 (for example)
if x > 0 thena = a + vr
else
a = a − vrend
a = max(0, x)

where x represents the input signal, and f (x) represents the output signal.
Algorithm 2 is an alternative algorithm I designed
However, ReLU can’t provide further simulations of which works similar to Algorithm 1, but much more efany other important behaviour of a biological neuron, ficient.
such as synaptic plasticity, for lack of learnable pa3.3. Implementation by PyTorchrameters.
In this research, I use PyTorch [4] to implement the
newly designed activation functions and the newly de2.2. Synaptic Plasticity
Synaptic plasticity is the ability of synapses to signed parameter updating method which was destrengthen or weaken over time, in response to in- scribed in Section 3.1 and Section 3.2. However, since135

5. Result and Analysis

Algorithm 2: vReLU 2All experiments show similar results. Figure 2 shows
the recognition accuracies of label-removed data,
which is a typical experiment result. Although therecognition accuracy of a typical CNN model use
ReLU also drops during training, the recognition accuracies of models with the proposed vReLU1 andvReLU2 activation functions drop faster. Then we canknow that both newly designed activation functions
the newly designed parameter updating method works can speed up forgetting.
different from the default way of PyTorch, gradient descent [5], I find a solution to keep the implementations
are compatible with PyTorch default libraries.
Concretely, I implemented each version of the activation function and parameter updating function algorithm into automatic differentiation functions [4], vrelu1
and vrelu2. Because the algorithm used here is not
related to differentiation, instead of computing the differentiation of activate strength (a), I implemented thecode that outputs
Data: Input: x
Old parameter: aResult: Updated parameter: a
Set b = 10−5 (for example)1)
a = 2a · Sigmoid(bx): (Sigmoid(x) = 1+exp(−x)

dif = (aold − anew )/lr .

(3)where dif is the fake ’differentiation’ of a and lr is the Figure 2: Forgetfulness of CNN with various activation functions onlearning rate of a typical gradient descent like param- MNIST Data
eter updating algorithm, such as mini-batch gradientdescent and Adagrad [5]. PyTorch will later updating
6. Conclusion
a automatically by
In this thesis, I proposed two new activation functions
anew = aold − dif · lr .
(4) used in deep learning neural network based on ReLU,
including new learnable parameters and other paramor another result near this value, which turns out to be eters. These activation functions use none-gradientdescent method to update learnable parameters andthe correct result we want.
After that, I packed these differentiation functions were designed to simulate synaptic plasticity mechinto higher-level standard modules, vReLU1 and anism. Experiments shows both of these activation
functions can speed up the forgetting of typical CNNs.
vReLU2, which can be easily used in PyTorch.
For future works, I want to explore real world situ4. Experiment Models
ations that suitable to apply new activation functions,
All experiments start by training a basic convolutional and find better ways for evaluating the effects on neuneural network (CNN) model with complete data, ral network models by the new activation functions.
which means the data contains all kinds of labels. Furthermore, we have to research on different kinds
Then use transfer learning method to train the pre- of neural network and optimize method for parameter
trained CNN model (all parameters are kept, ReLU updating.
layers are replaced by vReLU layers or not) by incomplete data, which means one certain kind of label is References[1] K. Gurney. An introduction to neural networks.
removed from the data on purpose.
CRC press, 2014.
[2] J. R. Hughes. Post-tetanic potentiation. Physiological reviews, 38(1):91–113, 1958.
[3] S. J. Martin, P. D. Grimwood, and R. G. Morris.
Synaptic plasticity and memory: an evaluation of
the hypothesis. Annual review of neuroscience,23(1):649–711, 2000.

a: MNIST modelb: CIFAR10 model
Figure 1: Architecture of CNN[4] A. Paszke, S. Gross, S. Chintala, G. Chanan,
E. Yang, Z. DeVito, Z. Lin, A. Desmaison,
L. Antiga, and A. Lerer. Automatic differentiationin pytorch. 2017.

An overview of gradient deFigure 1 shows the architectures of CNN used in [5] S. Ruder.
scent optimization algorithms.
arXiv preprint
experiments, while Figure 1a shows CNN for MNIST
arXiv:1609.04747, 2016.
data and figure 1b shows CNN for CIFAR10 data.
136

Recovery of Oil from Spent Coffee Grounds by Solvent Extraction for Biodiesel Production
Student ID: 15B12334

Name: Thisang PHAM

Supervisor: Ryuichi EGASHIRA, Hiroaki HABAKI
hexane was used as solvent and the extraction was
carried out 10 times (n=10). Then, the overall yieldof the oil extracted from VCG and SCG were
determined. Second, the solvent extractions wereconducted under different extraction conditions in
the cases of n=1. Hexane, methanol, toluene wereused as solvents and the extraction temperature waschanged at 300K, 310K and 320K. Then theinfluences of solvents and extraction temperature on
the yield of the extracted oil were investigated.

1. Introduction
Coffee is the second most consumed beverage in theworld after water [1] and a huge amount of spentcoffee grounds (SCG) is generated after brewing
coffee. The amount of SCG generated from theinstant coffee industry in the world was estimatedabout 6 million tons per year [2] and various
approaches to utilize SCG have been developed,
such as fertilizer, wood powder, absorbent and so on.
In spite of these applications, most of the SCG are
still discarded as waste and the effective utilizationof SCG is being studied. Although the utilization of
the SCG in the biofuel production was expected as apromising application because of its great sugar
content and lipid content, the production method has
not been fully studied.
This study aims to apply the solvent extraction
technique to the recovery of oil from the SCG for
biodiesel production. Then, the overall yield of theoil recovered from SCG was determined and effectsof the solvents and extraction temperature on therecovered oil were studied.

S1
F

1

Sk

V R, 1
*

R1

1

R1

Rk-1

E *k

*

E 1

k

V E,1

Sn

VR,k
*

Rk

k

Rk

Rn-1

n

n

Rn

*

V E,n

n
En

Ek

E1

Rn

E n

VE,k

k

1

VR,n
*

k : Batch extraction
k : Removal of solvent in R*k
k : Removal of solvent in E*k

2. Experimental
The SCG used in this study were provided in theform of frozen state from AJINOMOTO AGF, INC.,
and the moisture was firstly removed by leaving thesample at 383K for more than 24 hours. Afterremoving the moisture, the pretreated SCG wereused as the feed for the solvent extraction
experiments.
The
coffeegrounds
from
AJINOMOTO AGF, INC., were purchased and usedas the virgin coffee grounds (VCG) for the solvent
extraction experiments without any pretreatment.
As solvents, hexane, toluene and methanol wereused. Hexane was one of the common solvents
commercially used to extract food plant oils.
Toluene or methanol was selected as an example ofaromatic or alcohol compounds. These chemicals
were in analytical grade and purchased from
Fujifilm Wako Pure Chemical Co.
The procedure of multistage crosscurrent extraction
by batchwise operation and experimental conditions
are shown in Figure 1 and Table 1, respectively.
The feed coffee grounds of VCG or SCG wereintroduced to the 1st stage as feed, F.
The F was mixed with 100 mL solvent S1 and the
mixture was shaken in isothermal bath in 24 hours,
under the specified temperature. Then, the mixture
was separated into the liquid E*1 and the wet solid
R*1. The solvent contained in E*1 or R*1 was removed
by heating at the specified temperature and the solid
R1 and extracted oil E1 were obtained. R1 was usedas feed for the 2-nd extraction. The same amount ofsolvent Sk was added in the k-th extraction. First,: Solid phase flow
: Liquid phase flow
: Gas flow

Figure 1 Multistage crosscurrent extraction
procedure
Table 1 Experimental conditions
Materials
Coffee Grounds
VCG             SCG
Solvent
Hexane, methanol, toluene
Extraction conditions
Mass of sample, F
[kg]
[m3]
Volume of solvent, Sk
Extraction time
[hr]
n
[–]
Extraction temperature, T [K]0.025
1.0×10-4241, 10300, 310, 320

Conditions of solvent removal in R*k E*kTemperature[K] 353(methanol, hexane)
383(toluene)Time[hr] 10(hexane, methanol removal in E*k)14(toluene removal in E*k)48(solvent removal in R*k )3. Results and discussion
3.1 Definition of oil yield
The yield of the oil extracted after k-th extraction
was defined as,


 

 


137



where, Ei and F were the oil extracted at the i-th
extraction and the mass of the feed coffee grounds.
3.2 The yield of oil recovered from VCG and SCG
The provided SCG were dried in the atmosphere at
383K and the mass became constant after more than
24 hours. The ratio of the dried mass to the initial
wet mass was obtained as 0.26 kg-dried/kg-wet andthe SCG pretreated for more than 24 hours wereused as the extraction feed in all cases.
Figure 2 shows the plots of Yk against the stage
number of extraction k with VCG and SCG. In thecase of VCG, the solvent extraction was conducted
twice. Yk increased gradually from 0.056 to 0.111
while k ranged from 1 to 8 and had nearly no changewith k >8. Y10 was 0.111 while the yield of oil
extracted at first time Y1 was more than 0.058, it
meant 0.52 of total oil was recovered at the first time
extraction. In the case of SCG, the solvent extraction
was also conducted twice and their results were
mostly the same. Yk increased gradually from 0.056
to 0.093 (run 2) or 0.089 (run 1) while k ranged from
1 to 8 and had nearly no change with k >8. Y10
ranged between 0.089 and 0.093 while the yield of
oil extracted at first time Y1 was more than 0.056, it
meant more than 0.60 of total oil was recovered at
the first time extraction.
The total recovered oil of VCG is 0.11 higher thanthat obtained of SCG (0.093). Although the SCG
were not obtained from the VCG used in this study
and the reason was unclear, some parts of oil might
have been taken at the brewing step.
Yk of VCG and Yk of SCG were mostly the same at
k=1 and different with k 2. Although the solubilityof oil in hexane was not determined in this study, atthe first time extraction (k=1) the solubility limit ofoil in hexane might have been exceeded.

showed the highest Y1 followed by toluene andmethanol. Y1 in the cases of hexane and toluene werecomparable and Y1 in the case of methanol wasmuch smaller.
This trend was also reported inprevious study [3]. The main components of oil musthave been triglycerides of free fatty acid C16 or C18
therefore they were soluble more in non-polar
solvent. The yield of oil Y1 increased slightly as
temperature increased. Although the effects were
insignificant in this measurement range, thesolubility increased as the temperature increased.
0.08

Y1 [-]

0.06

0.02

n=1

290

Yk[-]

0.06
SCG run 1
CCG run 1
CCG run 2
n = 10 Solvent: Hexane
Extraction temperature 300 K

0
3

4

5 6
k [-]

7

8

9

320

330

5. References[1] Angellina., “Cofee, the second most populardrink in the world Eastwest, 2016 January.
[2] T. Tokimoto et al., “Removal of lead ions indrinking water by coffee grounds as vegetablebiomass”, Journal of Colloid and Interface Science,
281, 56-61, 2005.
[3] Ioannis et al., “Influence of solvent selection andextraction temperature on yield and composition oflipids extracted from spent coffee grounds”,
Industrial Crops & Products, 119, 49–56, 2018.

SCG run 2

2

310
T [K]

4. Conclusions
From the experiment on removing moisture fromthe provided SCG, the ratio of the dried mass to theinitial wet mass was obtained as 0.26 kg-dried/kgwet. From the experiment on determining the overall
yield of the oil recovered from VCG and SCG, Y10
of VCG was 0.111, Y10 of SCG ranged between
0.089 and 0.093. From the experiment on
investigating influences of solvents and extraction
temperature on the yield of oil, hexane showed thehighest Y1 followed by toluene and methanol. Y1
increased slightly as extraction temperature
increased.

0.08

1

300

Figure 3 Influences of solvents and extraction
temperature on the yield of oil

0.1

0.02

   

0

0.12

0.04

0.04

10

Figure 2 Yield of oil extracted from VCG and SCG
3.3 Influences of solvents and extraction
temperature on the yield of oil
Figure 3 shows the influences of solvents andextraction temperature on the yield of oil Y1. Hexane138

Earth-Moon Transportation System
Using a Reusable Vehicle and Fuel Stations
Student Number : 15_11197

Name : Ayu Numata

1.
Introduction	  In the future, new space missions such as deep space
exploration and construction of the base will advance more.
These developments lead various missions and a large
amount of transportation. Actually, the ratio of the mass of
payload in the launch rocket is about 1%. Therefore, thetransportation cost for the space mission would be increased
more than ever.
OTV (Orbital Transfer Vehicle) Network, using R-OTV(Reusable-Orbital Transfer Vehicle), is proposed as a futureinterplanetary transportation system. This network system
consists of orbital fuel stations and R-OTV. The R-OTV isfueled at the station. R-OTV transports the cargo among
the orbits. A previous research [1] shows that the cost of
OTV network between the Earth orbits is lower thanconventional method.
The objective of this study is to construct a model ofEarth-Moon OTV network, clarifying the characteristics andsuperiority of the system with IMLEO (Initial Mass of Low
Earth Orbit) and cost assessment.

Supervisor : Daisuke Akita

Model 1: E-OTV / no fuel station
Model 2: R-OTV / fuel station at LEO
Model 3: R-OTV / fuel station at LLO
Model 4: R-OTV / fuel station at LEO&LLO
Assumptions are as follows.
•
Transport 136 ton cargo per year.
•
R-OTV can be fueled fuel at only the station.
•
R-OTV can be used 100 times repeatedly.
•
𝐼!" of OTV propulsion is 450s.
•
All the orbits are on the same orbital plane.

3.

Transportation System Model

Cost assessment needs the mass budget of each model.
The mass of OTV is calculated using HASA [2] as shown
below.
                    𝑀!"!#$ =    𝑀!"#! +    𝑀!"# +    𝑀!"#$"! +    𝑀!"#

2.

Mission concept	  Four transportation models between the low earth orbit(LEO) and the low lunar orbit (LLO) are considered in thisstudy. Model 1 is conventional model using E-OTV(Expendable-OTV). On the other hand, model 2-4 uses
R-OTV. Figure 1 shows the mission scenario of the model
2.

!

(1)

∆!

𝑀!"#! = 𝑀!"!#$ 1 − e !!" ∙!

(2)

𝑀!"#$"! =   0.0.76 𝑇!"!#$ + 0.00033 𝑇!"!#$ 𝐴!"#$% !.! +   130    [𝑙𝑏](3)

𝑀!"# =    𝑅! ×𝑀!"#!

(4)

𝑀!"!#$ [kg] : total mass of OTV
𝑀!"#! [kg] : propellant mass
𝑀!"# [kg] : OTV payload mass
𝑀!"#$"! [kg] : engine mass
𝑀!"# [kg] : propellant tank mass
𝑇!"!#$ [lbf] : engine thrust in vacuum
𝐴!"#$% [-] : expansion ratio of rocket nozzle (=100)
𝑅! [-] : ratio of tank mass / propellant mass
In this study, payload of E-OTV is assumed to be 8 ton,and the total mass of R-OTV is calculated to be the same asthat of the E-OTV. The mass of the fuel station is set to be
50 ton by reference to previous research [1].

4.

Cost model

Cost is calculated as the sum of the fabrication cost(𝐶! ) and the operation cost (𝐶! ), excepts the developmentcost. Operation cost excludes other launch operation cost, but
fuel cost. In this study, the 𝐶! of E-OTV is set to be unit.
(dimensionless quantity).
Other costs are relatively
evaluated based on 𝐶! of E-OTV. Operation cost of
R-OTV is proportional to consumed fuel mass, and is
calculated as Figure 1. The parameter of this study is thelaunch cost to investigate its effect.

Figure 1: Example of mission model (Model 2)139

R − OTV  𝐶!   =(R − OTV  𝑀!"#$   )×(E − OTV  𝐶!   )(E − OTV  𝑀!"#!   )

2500	
  

(5)

Model	  1	  (E-­‐OTV	
  /	
  no	
  Sta.)	
  Model	  2	  (R-­‐OTV	
  /	
  Sta.	
  at	
  LEO)	
  Model	  3	  (R-­‐OTV	
  /	
  Sta.	
  at	
  LLO)	
  Model	  4	  (R-­‐OTV	
  /	
  Sta.	
  at	
  LEO-­‐LLO)	
  

Cost	
  [-­‐]	

2000	
  Table 1: Cost Parameter
OTV
Model 1Model 2~4𝐶!

𝐶!

1 (= Standard)
10

0.01
(5)

Fuel Station
𝐶!
𝐶!

10

Launch𝐶! +𝐶!

-

1500	
  

1

1000	
  

500	
  

5.

Result of calculations
Figure 2 shows IMLEO breakdown for the 20 years.
Figure3 and Figure 4 show the result of cost assessment ofModel 1~4.
In Figure 2, there is no large difference between the
IMLEO of Model 1, 2 and 4. However, the IMLEO of
Model 3 is five times as large as others because the R-OTV
is required to carry all the fuel to the station on LLO in
Model 3.
In Figure 3, the cost of Model 2 and Model 4 (R-OTV /the fuel station at LEO) are lower than that of Model 1(E-OTV), because R-OTV can be used repeatedly.
However, the R-OTV is more expensive than the E-OTV in
the first year because of the initial setup cost for the reusable
system.
It is found that the cost of Model 3 is drastically large asshown in Figure 4. That is because the total launch cost is
proportional to IMLEO in this study, and the IMLEO of
Model 3 is extensively larger than other models. That is
because the R-OTV is required to carry all the fuel to thestation on LLO in Model 3. Figure 3 also indicates thatmost of total cost is launch cost. In the near future, thelaunch cost could be reduced with more inexpensive launchvehicle and the reusable launch vehicles, which are underdevelopment around the world. The system proposed hare
has potential to reduce the mission cost considerably.
Among the Model 2, 3 and 4, using R-OTV, Model 2 (Sta.
only at LEO) has the lowest cost. That is because, in thisstudy, the mission models are considered for the one way
transportation only from the earth to the moon. In the
future, new missions which take something back to the earth
will be necessary.
Investigating the superiority of
construction of the LLO fuel station in would be necessary
such a mission.

0	
  
0	
  

5	
  

10	
  

Year	
  [y]	

15	
  

20	
  

Figure 3: Trend of Total System Cost

Model	  4	  Model	  3	  OTV_FabricaJon	  	
  Model	  2	  OTV_OperaJon	
  Fuel	
  Sta._FabricaJon	
  Fuel	
  Sta._transportaJon	
  Model	  1	  Total	
  Launch	
  

0	
  

500	
  

1000	
  

1500	
  

2000	
  

2500	
  

Cost	
  [-­‐]	

Figure 4: Accumlated Cost Budget for 20 years

6.

Conclusions
Cost assessment in this study indicates that R-OTV/fuelstation system has lower cost than conventional method of
E-OTV. And it is revealed that decreasing the fabrication
cost of R-OTV and launch cost are dominant factors to
reduce the total mission cost. Future works are as follows.
•
The effect of constructing the fuel station on orbits
other than LEO and LLO (e.g. Lagrange point)•
The effect of the LLO station for the transportationfrom the moon to the earth•
Transportation to other plants (e.g. Mars)

Model	  4	  Reference[1] Shinichi Nakasuka, Toru Tanabe, Naoko Sumino (1993),“Fuel Station-Based Transportation Network as a FutureSpace Infrastructure”, Journal of Space Technology and
Science, Vol.8, No.2, pp.22-37[2] ]Gary J. Harloff and Brian M. Berkowitz(1988), “HASA– Hypersonic Aerospace Sizing Analysis for the Preliminary
Design of Aerospace Vehicles”, NASA Contractor Report
182226

Model	  3	  Payload	
  of	
  OTV	
  Model	  2	  Total	  Structure	
  mass	  of	
  OTV	  Fuel	
  Sta._mass	
  Propellant	
  mass	
  to	
  transport	
  Fuel	  Sta.	
  Model	  1	  Propellant	
  mass	
  to	
  transport	
  the	
  Payload	  	
  Propellant	
  mass	
  to	
  transport	
  Fuel	  0	
  10000	
  Figure 2:20000	
  30000	  IMLEO	
  [t]	

40000	
  50000	  IMLEO Breakdown of the 20 year140

2 次元曲面において熱画像風速測定法(TIV)の結果の表現
学籍番号：15B08315

氏名：孫 岳指導教官：神田 学

デルと組み合わせることにより，TIV の結果

1. はじめにを 2 次元曲面上に表現することが目的である．

流れは我々の日常生活に大きく関わってい2. 観測概要

る．しかし，普段の流れは複雑な空間構造を有して透明であり，そのままの観測は困難で本実験で，東京工業大学大岡山キャンパスある．流れ,特に気流の可視化を達成するため

石川台 4 号館の屋上で，黒い発泡スチロールに，計測法として粒子画像流速測定法(PIV)，

製のマネキンと発泡スチロール製で黒く塗っ

シミュレーション法として数値流体力学

た直径 300mm，高さ 400mm の円柱体を対象(CFD)が大きく発展している．PIV は，レーに，サーモカメラによる熱画像を撮り，TIV

ザーシートにより，ある平面における微小な解析を行う．同時に超音波風速計により環境

粒子の動きを追跡し，流れ及び速度分布を計

風の風向風速の測定を行う．

算する．その結果はレーザーシートの平面に

3. 解析手法

制限されている．CFD はコンピューター上でモデルを作り，流れを数値解析・シミュレー

TIV の結果を 2 次元平面へ表現するため，ションする手法．高いレイノルズ数や複雑な結果の風速ベクトルを２次元から 3 次元まで形状を持つ物体の乱流解析の応用には困難で拡張することが必要である．結果を格納するある．

座標系は熱画像左下を原点とし，元の熱画像の XY 座標系を右手系になるように新たな Z

以上の点を踏まえて，PIV のアルゴリズム

軸を定義する．

を利用し，新たな観測手法である熱画像風速
測定法 (Thermal Image Velocimetry ,TIV) が空気が物体表面を流れるときに乱流が生提案された．この手法は粒子の代わりに，対じ，その乱流によって表面に温度変化の不均象物体表面の熱画像を利用し風速を計測する

一性が発生する．TIV はサーモカメラによりため，直接物体表面の風速場の計算ができ

物体表面の温度情報を撮り，さらに時間・空る．この手法は非接触的，安価，安全などい間スケールにおいて解析を行いその変動を求

くつかの利点があり，シミュレーションと比めることで風速ベクトルを計算する．熱画像

べ実在する大きく複雑な表面がある物体の観しか使わないため，風速ベクトルの結果は熱測も可能である．この手法によって，垂直壁

画像平面への投影である．この結果へピクセの上昇流や地表面の塵旋風(ダストデビル)など

ルの Z 座標情報を持ち込み，３次元の風速ベ観測事例があった，これらの観測事例の対象

クトルを作ることができる．
これを達成するために，対象物体の 3D モデ

面は平面であり，カメラの角度によリ射影変ルを作り，モデルの座標と熱座標の座標が対換を行い，結果を一つの平面に整理した．
本研究では，発泡スチロール製の円柱体及応できるように座標変換を行う．それから自びマネキンを対象とし．その表面の自然状態

作したプログラムにより，ピクセルごとの Zでの流れを TIV で捉え，更にそれらの 3D モ

座標を計算する．最後に，風速ベクトルの値

141

は整数に限らないため，その終点の座標を周のベクトル．円柱体の表面において，流れのりの加重平均で計算する．この速度ベクトル

剥離の現象が確認された．

と始点の座標を組み合わせ，再描画すること

超音波風速計による風速は 1m/s 以上であで，TIV の結果を対象物体の 2 次元曲面で表り，TIV 手法により計算された風速は主にすことができる

0.1m/s 以下である．この原因は対象物体のスケールが小さいと考えられる．

4. 結果及び考察

5. 結論

Z 座標を計算するときに正射影を採用するので，モデルの境界部分で誤差が生じる．

TIV の結果を２次元表面へ表現することに成功した．その結果を異なる角度から観察することで１つの角度では気づきにくい変化も発見しやすくなる．しかし，この手法で TIVの精度が上がったことはなく，境界部分でのベクトルは計算に使う情報量は少ないため，定量的な分析には不向きである．

上面図

将来もっと大きいスケールの物体へこの手法を運用し，風速の検証を行うことに期待する．また，複数のサーモカメラによる同時観
測で境界部分での誤差を減らすことも期待する．

参考文献[1] Ch Brücker. Digital-particle-image-velocimetry

側面図(dpiv) in a scanning light-sheet: 3d starting flow

正面図

around a short cylinder. Experiments in Fluids,

図 1 マネキンの表面温度変動及び風速ベクトルの19(4):255–263, 1995.

三面図[2] Atsushi Inagaki, Manabu Kanda, Shiho
Onomura, and Hideaki Kumemura. Thermal image
velocimetry. Boundary-layer meteorology, 149(1):1–
18, 2013.
[3] Kumemura H. Thermal image velocimetry (tiv)and application to a building wall. 土木学会論文集,

側面図68(4):I1753–I1758, 2012.

正面図[4] Zhang Y. Application of thermal image

図 2 円柱の表面温度変動及び風速ベクトルの正面

velocimetry to dustdevil. 東京工業大学修士論文,

図と側面図

2012.

TIV の結果を２次元表面へ表現することで，異なる角度から結果を見ることができ[5] 稲垣厚至. 熱画像風速測定法 (tiv) による風のた．正面で確認しにくい変動も，他の角度か

空間分布計測. 水文・水資源学会誌, 29(3):186–

ら見ると明らかになる．例えば，図１のモデ

195, 2016.

ル頂上部分のベクトルや，図２のモデル左側

142

Effect of pull-off angle on adhesion force between side surface of PDMS beam and rigid bodyStudent Number: 15B11346 Name: Suguru Norikyo

Supervisor: Kunio Takahashi

1. Introduction
The gripping device imitating a fine structure of gecko
foot-hair is considered to be able to adhere to roughsurface even in vacuum. The device’s grip and release
performance can be gained by controlling tangential force.
Mikhail has demonstrated a prototype of the device madeof multiple-PDMS-beam structure, and experimentally
evaluated its function [1].
Shimahara conducted an experimental study on therelation between pull-off angle and maximum adhesion
force of a gel beam contacting with a rigid body [2].
However, Shimahara’s experimental results didn’t meetthose predicted by a theoretical model [3], in which aperfect elastic beam was assumed.
Fig. 3In this study, a PDMS beam (assumed as elastic beam)is used for experimental study of effect of pull-off angle
on adhesion force between side surface PDMS beam andExperimental system

3. Results
When the pull-off angle 𝜑 = 118.0(°), the normal force

rigid bodyis shown in Fig.4. The beam detached from the rigid

2. Experimentbody after the adhesion force is maximum, and the

In order to clarify the effect of pull-off angle on

beam form a new adhesion area. The normal force

adhesion force between side surface of a PDMS beam andincreases while fluctuating. Finally, adhesion contact

rigid body. It is necessary to measure the normal force

between the beam and the rigid body changes from area

𝐹𝑛 (Fig.1), the tangential force 𝐹𝑡 (Fig.1), the displacement

contact to line contact, and the beam comes to peel off.
These behavior can be observed in the range of pull-of an edge of the beam 𝑑, and the length of non-contact

off angle 𝜑 : 101.6～146.2(°).

area 𝑙, experimentally.
We use the experimental system as shown in Fig. 3.

0.2

The elastic beam is made of a PDMS (Sylgard 184, Dow
Corning). The beam is 30 (mm) in length, 15(mm) inwidth, 5(mm) in thickness, and 10(°)in setting angle.

0.1

body.
At the start of the experiment, the slide glass waspressed

to

the

beam

vertically

until

a

certaindisplacement and displaced horizontally until tangential
force being 0 (N) (Fig.2). Then, the slide glass was
unloaded with pull-off angle constant (Fig.3).

Normal force (N)Slide glass (S9213, Matsunami Glass) is used as rigid

0

-0.1

-0.2

-0.3

Maximum adhesion force
-5

-4

-3

-2

-1

0

Normal displacement (mm)Fig.4

Normal force 𝐹𝑛 (𝜑 = 118.0°)

F
Fig.1

Loading process

Fig.2

Unloading process

143

0.3

Measured force
Calculated force

0.2
-0.1

Normal force (N)Maximum adhesion force (N)

0

-0.2

10° 9° 8°0.1 7°0 6°

-0.1
-0.2

-0.3

-0.3
80

100

120

-0.4

140

-2

-1.8 -1.6 -1.4 -1.2
-1
Normal displacement (mm)Pull-off angle (°)

Fig.5

relation between pull-off angle and

Fig.6

-0.8

Experimental result and analysis result

Maximum adhesion force(𝜑 = 118.0°)

4. Discussion

difference between the length of the beam 𝐿 and thelength of adhesion area ,which is calculated by the

The relation between the pull-off angle 𝜑 and the
maximum adhesion force for each pull-off angle 𝜑 isadhesion area divided by the width of the beam. Young’s

shown in Fig.5. As shown in Fig.5, the maximum

modulus 𝐸 is estimated to be 1.73 (MPa) by previous

adhesion force is nearly 0 (N) when the pull-off angle isresearch [4].
When setting angle 𝜃 = 10(°), the calculated normal

less than about 80 (°). The maximum adhesion forcechanges as the pull-off angle changes between about 80

force is larger than measured normal force. Fig.6 shows(°) and about 120 (°). The maximum adhesion force isthat calculated normal force decreases as setting angle

certain when pull-off angle is larger than about 120 (°).

𝜃 used for calculating decreases. It is suggested that thesetting angle 𝜃 decreases during unloading.

The maximum adhesion force depends on thetangential force. However, the tangential force does not

5. Conclusions

exceed a certain force by the adhesion area slipping.

The range of pull-off angle when the maximum

Therefore, in the previous experiment [2], it is suggested
that the range of pull-off angle when the maximum

adhesion force is changed exists.
It is suggested that setting angle 𝜃 changes during

adhesion force is unchanged exists like the result of thepeeling by comparing the calculated normal force withexperiment (Fig. 5).
According to previous research [2], when thenormalized tangential force is positive, the normal forceof the model is obtained as

the measured normal force.

References[1] Mikhail Salyukov, et al, “Development of a Multy-𝐹̃𝑛 =Beam Structure by Stacking Comb-Shaped Rubbers”,

𝐹̃𝑡 2√3𝐹̃𝑡 sinh (2√3𝐹̃𝑡 𝑙̃)Mate2018, vol24 pp.261-264,2018

2 − 2 cosh (2√3𝐹̃𝑡 𝑙̃) + 2√3𝐹̃𝑡 𝑙̃ sinh (2√3𝐹̃𝑡 𝑙̃)× (𝑑̃ −

1 − cosh (2√3𝐹̃𝑡 𝑙̃)2√3𝐹̃𝑡 sinh (2√3𝐹̃𝑡 𝑙̃)[2] Shimahara,S, ”Effect of tangential force on adhesion
between an elastic beam and rigid body”, Master thesis

tan𝜃)

where, the displacement, the length of non-adhesionarea, and the force are normalized as 𝑑̃ = 𝑑/𝐿, 𝑙̃ = 𝑙/𝐿,
𝐹̃ = 𝐹/(12𝐸𝐼/𝐿2 ) in the same manner as Shimahara’s
expressions [2].
As shown in Fig.6, we focus on the force curve of Fig.
5 from the beginning of unloading until the detachment,of Tokyo Institute of Technology, 2016[3] Imai,Y, ”弾性梁と剛体平面の接触における梁の長手方向の変形が凝着力に与える影響”, Master thesis of Tokyo
Institute of Technology, 2018[4] Mai Ngoc Trung, “The prototype of side-contact typeelastic multi-beam using PDMS”, Bachelor thesis ofTokyo Institute of Technology, 2016

and apply measured parameters to Shimahara’s
theoretical model.
The length of non-adhesion area 𝑙 is described by the144Application and Comparison of Cooley-Tukey algorithms for Ocean Rendering with Spectral
domain approach
Student Number:15_08290

1

Name: Eungang SON

Supervisor: Hiroshi TAKAGI

converts a finite sequence of equally-spaced samples of afunction in a same-lengthy sequence of equally-spaced
samples of the discrete-time Fourier transform, which is acomplex-valued function of frequency.

Introduction

Due to the ocean`s highly dynamic behavior, from a silent
sea to an intense ocean, it is hard to understand and explain
its mechanisms. Representing this visual complex
phenomenon is a challenge, and related fields have evolved
to deal with this problem. Since 1980, a large number ofbreakthroughs have emerged in the Ocean Rendering Field.
The major idea is to define its phenomenon based on therelative water depth to wave length: deep water andshallow water. The former type of waves is generally used
to describe longer wave phenomenon in deep sea, whereas
later one illustrates shorter wind waves subject to breaking
waves at a nearshore location.

𝑁−1

2𝜋𝑖

𝑋(𝑘) = ∑ 𝑥(𝑛) ∙ 𝑒 − 𝑁 𝑘𝑛
𝑛=0

s. t. ∀𝑘 ∈ {0, … , 𝑁 − 1}, ∀𝑛 ∈ {0, … , 𝑁 − 1}
𝑁 is the data size.
Depending on pure signal input, DFT represents
symmetricity.

Even symmetric
Ocean rendering can be classified into two: spatial/spectral
methods incorporated in marine and oceanic flow models,and physically based model which take approximate
solutions of the Navier-Stokes Eqauation (NSE) toreproduce the complex dynamic behavior of ocean surface.
For rendering, the optical property of the ocean surface isalso need to be considered. In rendering stage, several
phenomena such as agitation, bubbles, diffraction, andrefraction must be calculated. For ocean rendering, theseshader techniques are also essential for realistic description.

𝑥𝑛 ∈ 𝑅, ∀𝑛 ∈ {0, … , 𝑁 − 1} → 𝑋𝑘
∗
= 𝑋−𝑘
𝑚𝑜𝑑 𝑁

∀𝑘 ∈ {0, … , 𝑁 − 1}, 𝑋 ∗ = 𝑋̅
Also, DFT represents periodical property by input data size
N.
2𝜋𝑖

2𝜋𝑖

Thanks to the properties above, DFT algorithm can bedivided into the algorizms, known to be butterfly
computation, which can contribute to decreasing
computation cost than that of ordinary DFT. DFT algorithm
which is optimized by symmetricity is called radix based
FFT. All radix based algorithms represent similarly
distinguish butterfly computation structural differing onlyin the core computation of twiddling. We chose thefollowing six types of Cooley-Tukey algorithms for the
spectral transform: Radix-2, Twisted Radix-2, Radix-4,
Twisted Radix-4, Radix-8, and Split Radix.

The advent of Virtual Reality (VR) provides new
possibilities in an ocean rendering field. While thetraditional rendering can be differntiated into two
incompatible types according to its purpose: For accurately
focused purpose: such as movie CG, Meteorologicalresearch, and expeditiousness focused purpose such as
game. VR simulation requires both accuracy and
expeditiousness simultaneously. This paper presents acomparison of the frame per second (FPS) of Fourier
domain approaches by using Microsoft 4-Dimensional
Perlin noise data optimized by various Cooley-Tukey
algorithms in VR prerequisite conditions in real-time
domain.

22𝜋𝑖𝑒 − 𝑁 𝑘𝑛 = 𝑒 − 𝑁 𝑘(𝑛+𝑁) = 𝑒 − 𝑁 (𝑘+𝑁)𝑛2.2 Ocean Rendering
There are mainly two kinds of method are considered inocean rendering: Deep water rendering, Shallow water
rendering and Mixed method . Deep water rendering use
theoretical models in marine/ocean science and/or
experimental observation data to represent ocean surface.
There exist three categories, namely a spatial domain
approach, spectral domain approach (Fourier domain
approach), and hybrid approach which is combining the

Methodology

2.1 Cooley-Tukey Algorithm
The basic principle of most Cooley-Tukey algorithms
based on the symmetry properties of a complex exponential
term in the Discrete Fourier Transform (DFT). DFT

145

Figure 1 Rendered Result

two. Spatial domain describes its surface directly in spatial
domain by height map which is composed of periodical
functions arise from the model oceanic science model. On
the other hand, the spectral approach requires wave
spectrums to describe its domain and use Fast Fourier
Transform (FFT) to transform into the spatial domain.
Hybrid methods, which is the combination of the two,generate convincing easily animated surfaces.

50

FPS

40
30
20

SPRDX
TRAD2
TRAD4

10
0
9

Shallow water rendering use NSE to describe ocean surface.
There are two methods exist to discretize the NSE in Ocean
Rendering. Firstly, Eulerian focus on a 2D or a 3D gridwhere the fluid moves from cell to cell. On the other hand,
Lagrangian approaches focus on each particle which isrepresenting small fluid volumes. Like deep water
rendering, Hybrid technics, also developed for strengtheach virtue by combining these two techniques.

12

13

14

15

Figure 2 FPS-resolution graph
800

Spectral Domain Approach

Spectral domain approach uses Fourier Transformation ofexperimental/observed data which have transformed into
the spatial domain. Mastin et al. (1987) proposed the basic
concept of spectral domain approach based on PiersonMoskowitz spectrum theory (1964). Premose andAshikhmin (2000) used JONSWAP spectrum (1973) which
is an revised version of the Pierson-Moskowitz spectrum.
Tessendorf (2001) used Phillips spectrum to describe
surface of wind waves which was used for scenes of Titanic
movie CG. We have used Phillips spectrum for spectral
domain rendering.

3

11

RESOLUTION OF INDEX OF 2

FRAME TIME(MS)

2.3

10

RAD2
RAD4
RAD8

SPRDX
TRAD2
TRAD4

600

RAD2
RAD4
RAD8

400
200
0
9

10
11
12
13
14
RESOLUTION OF INDEX OF 2

15

Figure 3 Frame time-resolution graph

4

Conclusion

We investigated FPS spectral domain approach for
rendering of specific prepared input data which are
optimized by various Cooley Tukey FFT algorithms. The
fastest Cooley-Tukey algorithm: Split radix DIF FFT
displayed 8 FPS in 4K resolution, which is lower than theminimum requirement(60fps) in VR environments. The
result demonstrates the limitation of the technology for thegeneration of realistc wind waves in VR for now.

Experimental Result

We have tested FPS and FT (Frame Time) in bytransforming prepared 4 dimensional Perlin noise data fromthe NDVIA corporation into the spatial domain using 8point Cooley-Tukey algorithms in Philips spectrum (Fig 1)
and investigated by the resolution (Figs 2 and 3). (CPU :Intel(R) Core™ i7-4712MQ CPU @ 2.30GHz, 8GB Ram,
GPU : NVIDIA GeForce 820M)

References[1] Soni M. and Kunthe P., “A General Comparison Of
FFT Algorithms,” Soni2011AGC, 2011.
[2] Darles E., Crespin B., Ghazanfarpour D., Gonzato J.C..
A Survey of Ocean Simulation and Rendering Techniquesin Computer Graphics. Computer Graphics Forum,
Wiley, 2011, 30 (1), pp.43-60. <10.1111/j.14678659.2010.01828.x>. <hal-00587242>[3] Tessendorf J.: Simulating ocean waters. In SIGGRAPH
course Notes (Course 47) (2001).

146

籾殻灰の有効利用－Ca(OH)2 を鉱化剤としたゼオライトの合成に関する研究
学籍番号：15B15887

名前：陸 遥

指導教員：日野出 洋文, Winarto KURNIAWAN

1. 背景

がら、one-step アルカリ水熱合成法[2]を用いて反応温度 90 ℃で、実験を行った。

稲は世界の重要な穀物であり、毎年米の副産物である籾殻は約 1.5 億トンであると報告され

2.2 キャラクタリゼーション

た(2014)[1]。これは利用可能なバイオマスであ生成物は XRD で結晶強度と結晶構造を確認

り、バイオマス発電に利用されている。発電のし、SEM で表面構造を観察した。CEC は酢酸

固形廃棄物となる籾殻灰はそのまま埋め立て

ナトリウム法[3]を用いて、ICP でナトリウムイ

るか、土壌改良、セメント製造の原料などの低オン測定し、算出した。

価値の方法に利用されている。近年、籾殻灰は2.3 吸着実験

約 9 割という高いシリカ含有量のため、ゼオラ

吸着剤 1g/L で 100 ppm の Cd 溶液で生成物の除去平衡時間を確認した。30, 50, 100, 150,

イト合成への応用が注目された[2][3]。
ゼオライトは結晶性のある多孔質アルミノ

200, 300, 400 ppm で 除 去 実 験 を 行 い 、

ケイ酸塩の総称であり、負電荷の骨格があり、Langmuir モデルを適用し、生成物の Cd に対

その負電荷を打ち消すため、アルカリ金属又はする飽和吸着量を推定した。AAS で吸着実験に

アルカリ土類金属イオンを含む。それらの陽イ

おける Cd 濃度を測定した。

オンは交換可能なため、ゼオライトは陽イオン

3. 結果と考察

交換能をもち、重金属陽イオン吸着に応用されている。

P Zeolite P

重金属のカドミウム(Cd)はかつて日本のイタイイタイ病を引き起こした。今でも、中国や

P

P

P

CaCO3

Al(OH)3

Ca(OH)2

Ca3Al2(OH)12P

24h

タイ国を汚染しているため、本研究で Cd を重金属除去の対象物質とした。

12h

既存の研究[2][3]で籾殻灰からゼオライトの合
成中、NaOH が鉱化剤として使われている。ゼ3h

オライトの結晶強度や結晶構造は原料だけで24h

なく、鉱化剤にも依存している。本研究では
Ca(OH)2 を鉱化剤として、籾殻灰からゼオライ

12hトの合成実験を行い、ゼオライトの結晶強度と結晶構造そして陽イオン交換容量(CEC)と Cd

3h

除去能について調べることを目的とした。

3h

2. 実験
2.1 合成実験
本研究に使用した籾殻灰は籾殻を 600 ℃で

図 1. 生成物の XRD パターン

4h 加熱して得た。籾殻灰、Ca(OH)2、NaOH、

Ca/Na＝1/0

Al(OH)3 を一定の割合で混合し、Ca(OH)2 と図 1 から、
Ca/Na が 1/0 の場合、Ca3Al2(OH)12

NaOH の質量比(Ca/Na)及び合成時間を変えなが主生成物であることが分かった。これは原料

147

Ca/Na＝2/1

Ca/Na＝1/2

となる Al(OH)3 と Ca(OH)2 から生じた生成物

図 4 から多くの球状と八面体の結晶が観察できと考えられる。また、未反応の Ca(OH)2 も観測る。参考文献[3][4]により、球状結晶は Zeolite P、された。Ca/Na が 2/1 と 1/2 の場合、3h と 12h八面体結晶は Zeolite X と考えられる。

に未反応の Al(OH)3 が観測され、Al(OH)3 の反表 1. 生成物の CEC

応が遅いことが分かった。24h の時、Ca/Na が2/1 の場合は明らかな生成物がなく、Ca/Na が1/2 の場合は Zeolite P が生成した。また、すべて の 生 成 物 に は CaCO3 が 存 在 し 、 こ れ はCa(OH)2 が水熱合成で容器内の CO2 と反応し

表 1 から、Zeolite P の CEC は Zeolite X&P

たものと考えられる。

X

P X P

PX P

より低い値であることが分かった。
P

Al(OH) P Zeolite
X P

X Zeolite

24h

X

X

X

X

12h

3h
図 5.

Zeolite P と Zeolite X&P の Langmuir 吸着等温線

吸着剤 1g/L、100 ppm の Cd 溶液の場合、
図 2．Ca/Na＝0/1 の場合の生成物 XRD パターン

Zeolite P と Zeolite X&P の吸着平衡時間はそ

図 2 から、3h の時と 12h の時は Al(OH)3 観

れぞれ 30 と 60 min である。図 5 から、Zeolite

測できるが、12h の時 Zeolite X が生成したとP と Zeolite X&P の Cd 飽和吸着量はそれぞれ分かった。24h の時、成長した Zeolite X が観

120.9 と 126.8 mg/g であり、CEC より低いた

測され、Zeolite P も生成した。これは Ca(OH)2

め、Cd の吸着は陽イオン交換によるものだとを鉱化剤とした場合に比べて、Zeolite X が生成考えられる。

し、その生成し始めた時間もより短いと分かっ

4. 結論

た。Zeolite P の回折強度は、Ca/Na が 0/1 の場

Ca(OH)2 を鉱化剤とし、籾殻灰から Zeolite P

合が高いことが分かった。

を合成した。生成物の CEC は 316 mEq/100g、Cd 飽和吸着量は 120.9 mg/g であり、NaOHの場合より CEC の値が低く、合成時間も長い
が、Cd に対する吸着速度がより速く、飽和吸着量もほぼ同じである。
参考文献
図 3. Zeolite P の SEM 画像 図 4. Zeolite X&P の SEM 画

図 3 と図 4 は Ca/Na=1:2, 24h (Zeolite P) と

[1] FAOSTAT, Data.
[2]H. Katsuki, et al. J. Solid State Chem. 182 (2009)

Ca/Na＝0:1, 12h (Zeolite X&P) の SEM 画像[3]C. Santasnachok, et al. J. Envr. Chem. Eng. 3 (2015)である。図 3 から少量の球状の結晶が観察でき、[4]A. Moirou, et al. Clays & Clay Mine., 48, 5, (2000)

148

インド・アーメダバードにおけるオートリキシャ旅客特性の解明
学籍番号:15B03625

氏名: 郭 欣 指導教官: 花岡 伸也, 川崎 智也

1. はじめに較し、どの質問の結果が auto user と non-autouser の間で違いとがあるのか、また関係があるのかを T 検定とカイニ乗検定を R で計算した数値から判明した。private vehicle user と BRTS user の場合も同じように R で計算を行った。また、計算結果が異なるため、関係がある質問の結果に関して、各グループの特性を更に対照図形式によって分析した。

インドの急速な発展に伴い、全国範囲における都市化が素早く進んでいる。インドの都市の人口は2008 年の 3 億 4,000 万人から 2030 年までに 5 億
9,000 万人に増加するのが推定できる。[1]このような都市人口の増加につれ、人々が交通移動の自由の必要性は高まる一方である。しかし、公共交通の発展が経済の発展に追いつかず、そのためオートバ
イや自動車を含む自家用車の増加がみられている。
それに伴い、交通渋滞や大気汚染などの深刻な問題が引き起こされ、人々の日常生活に影響を及ぼしている。特に、大都市では交通問題が手を焼く社会問
題となっている。
本研究は、インドの Gujarat 州で最大の都市、アーメダバードを注目する。アーメダバードでは現在
自動車数の増加が市民にとって大きな負担となり、アーメダバードのバスシステムとオートリキシャを含む公共交通機関に解決策を求めるべきだと考えられる。[2]
本研究の目的は 4 つがある。最初の目的はオートリキシャを BRTS のフィーダーサービスとして使っている旅客の特性を把握することで、 2 つ目は、BRTS ユーザー全般の特性を把握することである。
3 番目の目的は人々が BRTS とオートリキシャを使う理由を知ることにより、最後の目的は BRTS とauto に対する改善点を把握することである。
前述の目的を満たし、今後アーメダバードでオー
トリキシャの活用に役立つことを期待している。

3.アンケート調査の結果と考察
3.1 アンケート調査のサンプル数
２日間のアンケート調査の結果より、310 サンプルの auto user、300 サンプルの non-auto user、合計 610 サンプルの BRTS user が収集された。
3.2 カイニ乗検定と T 検定の結果
表１ カイニ乗検定の結果①

2. 研究手段
２０１８年１１月に、アーメダバードにおいてア
ンケート調査を行った。回答者全員を２つのグループにわけ、１グループはオートリキシャを BRTS のフィーダーサービスとして使う auto user であり、もう１グループは他のフィーダーサービスを使ってBRTS 駅に行く non-auto user である。auto user とnon-auto user の全体は BRTS user であり、平出駿氏が２０１７年の研究でのアンケート調査のサンプ
ルは private vehicle user である。
質問票では年齢や教育背景や収入など一般的な個
人情報だけではなく、交通モード BRTS とフィーダーサービスに関する質問もアンケート票に記載されている。その中には、交通モードを使う時間帯や利用する理由や改善点などが含まれた。それに、BRTSとオートリキシャに関するコメントに対して５段階
評価で 1 が全く同意していない、５が同意している、と設定されている。
アンケート調査の結果から各質問の結果が違うグ
ループわけに従い、auto user と non-auto user、
また private vehicle user と BRTS user の間で比

auto user &non-auto user

BRTS user & private
vehicle user

Age

◯

▲

Gender◯▲Family member◯/

Private vehicles◯/

Employment status◯▲

Educational background◯▲

Household income(monthly)◯▲

Transportation cost(monthly)◯/

Frequency of using BRTS▲/

Time periods of using BRTS
(or private vehicle)◯▲

Trip purpose◯◯

Usage of public
transportation app◯/

Usage of smart card Payment◯/( ◯ :p value > 5%, ▲: p value < 5% ,/ : no data)

上の表１カイニ乗検定の結果①で示すように autoを使うかどうかが BRTS の使用頻度との関連性が示されている。更にこの二つのグループの対照図を作り、non-auto user が auto user より BRTS を使う
頻度が高く、時間帯が幅広いことが判明された。
そして、private vehicle user と BRTS user の計算結果では自家用車と BRTS を選択したのは年齢と性別、また雇用状態と月収入、教育背景および出かける時間帯と関係があると表した。この二つのグループの対照図を作り、そこで判明したのは BRTS 旅

149

客の年齢層が１０代と２０代が多く、女性と正式に雇用された人、および月収入が高い人と高学歴を持
つ人が自家用車を使う人より少ない。BRTS 旅客がBRTS の利用時間帯が分散である一方、自家用車を使う人たちの出かける時間帯がラッシュアワーに集中することが分かった。

上記の表３が示すように、auto user のアクセス
時間と BRTS に乗る時間、および全体のトリップ時
間は平均的に non-auto user より長いことが判明できる。今回調査時に聞いた時間は待ち時間が含まれたので、オートリキシャを探すときドライバーとの値段交渉や経路決定などにかける時間がこの時間差が生じた原因だと考えられる。目的地までの距離が短いことにより BRTS を使ったのはイグレスで時間差がない原因だと考えられる。
3.3BRTS とオートリキシャを使う原因と改善点
BRTS を利用する原因として一位となったのは「安い料金」（64.３％）であり、「速度が速い」（55.
７％）と「家から行きやすい」（40.８％）のは２位、３位である。他には「居心地が良い」や「家から近い」や「BRTS が安全」などもある。
オートリキシャに関して、auto user にオートリ
キシャをフィーダーサービスとして使う原因、また
non-auto user に使わない原因を聞いた結果、「駅から遠すぎ」（81.６％）と「駅から近すぎ」（85.
３％）は各質問の答えで一位である。そこで、駅からの距離の遠近がオートリキシャを BRTS のフィーダーサービスとして使うかどうかの一番の原因だと考えられる。
BRTS の改善点に関して、「バスの頻度」を選択した人が一番多く、37.５％である。オートリキシャの場合では「高い料金」が一番で３７％である。しかし、この二つの答えの中ではが「改善点がない、今のままでいい」と答えた人も少なくない。

表２ カイニ乗検定の結果②
MeanComments about BRTS

Auto
users

Non-auto
users

P
value

1

People around me including family,
friends and colleagues usually use
it.

3.72

4.08

▲

2

Request to operate in early morningand midnight.

3.27

3.55

▲

3

Difficult to get on and off the bus
station.

2.28

2.29

◯

4

Ticketing system is complicated.

2.18

2.18

◯

5

I feel safe to use it.

4.18

4.23

◯

Comments about auto

6

People around me including family,
friends and colleagues usually use
it.

3.62

3.61

◯

7

It tends to get involved inharassments.

1.86

2.08

◯

8

It is frequently available.

3.51

3.46

◯

9

Auto drivers have bad attitude.

2.83

2.89

◯

10

It is small inside, I feelcongested.

2.14

2.14

◯

3.94

3.88

▲

11 I feel safe to use it.

4.終わりに
この調査では、アンケート調査から、オートリキ
シャを BRTS のフィーダーサービスとして使う人の特性分析を行い、オートリキシャがアーメダバードの公共交通での役割を解明した。調査結果により、
private vehicle user と BRTS user の間では顕著な差が存在することが判明できた。BRTS 旅客の中に学生の割合が顕著的に高く、自家用車を使う人たちの中で雇用された人が多い。しかし、auto userと non-auto user の間に個人特性に関する明らかな差がなく、BRTS を使う頻度だけに関係あるのを示した。この結果から、公共交通利用者のフィーダー
サービスの選択が公共交通と繋がり、将来的に公共交通の進展に伴い変動する可能性が予測できる。

( ◯ : p value > 5%, ▲: p value < 5%)

上の表２カイニ乗検定の結果②で示すように autoを使うかどうかが１番目、２番目と１１番目の三つのコメントに対する態度の違いと関係がある。平出駿氏の研究により private vehicle user が公共交通を使わないことに 1 番大きな影響を与えていた項
目“Subjective norm”であった。周囲の人々の意
思決定が本人の意思決定に大きくかかわっていることがわかる。[3]１番目のコメントが示すように、平出駿氏の研究結論は BRTS の旅客でも証明できた。２番目のコメントは non-auto user が BRTS を
広い時間帯で利用するのが推定でき、３番目のコメントを通し auto user がオートリキシャへの信頼性が non-auto user より高いことが判明できた。

参考文献：[1] McKinsey Global Institute: India’s urban awakening:

表３ 交通時間 T 検定の結果

Building inclusive cities, sustaining economic growth:2010

Auto(min)Non-auto(min)P value

Access time

mean: 8.56 median: 7

mean: 7.21 median: 5▲

Egress time

mean: 7.42 median: 5

mean:6.77 median: 5◯

BRTS time

Mean: 30.9 median:25

Mean :27.5 median:25▲

total travel
time

mean: 46.9 median:42

mean: 41.4 median:38▲[2] AKSHAY MANI, MADHAV PAI,RISHI AGGARWAL: Sustainable
Urban Transportation in India: Role of the Auto-rickshaw
sector:2012[3] Hiraide, T., Kawasaki, T. & Hanaoka, S.,
Clarification of public transport usage conditions in
Ahmedabad, India. WIT Transactions on the Built
Environment, 182, WIT Press, 2018.

( ◯ : t value > 5%, ▲: t value < 5%)150Adhesion model of side contact for elastic beam with consideration of
inflection point
Student Number:15 03938

1

Name:Saneyuki KATO

Introduction

In the research field of manipulation, the developmentof a grip-and-release device has been focused. Mikhail
has developed such device using a two dimension array of side-contact elastic (PDMS) beams[1]. He designed the device by setting every single beam with afixed tilting-angle and experimentally studied its function. The adhesion force of the device[1] could be controlled by changing tangential force. However, theoretical model required for designing work is still not
clear.
On the other hand, an adhesion model of side contact
for inextensible elastic beam was proposed [2]. Thismodel assumed the adhesion between an elastic beam
and a rigid surface and considered the bending deformation of the beam. According to the experimental
results of Mikhail [1], it was observed that inflection
point exists during the beams’ deformation, which thisphenomenon can not be predicted by the previous analytic model [2]. Thus, I propose an adhesion model
for side-contact elastic beam with the consideration of
inflection point. This study is thought to be a guideline required for designing grip-and-release device using
side-contact elastic beams.

2

Supervisor:Kunio TAKAHASHI

Modeling

The proposed adhesion model, as shown in Fig. 1, assumes the contact between a side of an elastic beam
and a rigid surface. The beam with length L, width
W , moment of inertia of the (rectangular) cross-section
I, is assumed as Bernoulli-Euler beam. It partially adheres to the surface, so that the non-adhesion length(referred to as non-adhesion area) is defined as l. In
this model, a pure bending deformation is assumed
without any axial deformation, and no deformation occurs in the adhesion area. The boundary between the
non-adhesion area and adhesion area is perpendicular
to the rigid surface, and the angle θ of the beam baseis constant.
By considering bending deformation, the deflection
angle φ of the beam within the non-adhesion area
caused by the force F applied to the beam can be calculated as,√
dφ(1)= ±2 F̃ {cos(φ − α) + C},ds̃
√
where, F̃ = F/(∆γW ), s̃ = s/ 2EI/∆γW , are thenormalized force and (neutral axial) length, respectively. E is Young’s modulus of the beam, ∆γ is thework of adhesion, and C is a curvature parameter tobe determined from boundary condition.

Fig. 1: Schematic image of the contact between sidesurface of an elastic beam and a flat rigid surface
The total energy UT of the contact system, definedas the sum of bending energy, surface energy and potential energy of external force, can be expressed as,∫ŨT = 2F̃ cos(φ − α)ds̃ + (F̃ cos(α) − 1)(L̃ − ˜l) + F̃ C ˜l(2)√where, ŨT = UT / 2EI∆γW , L̃, ˜l are the normalizedenergy, total length, and non-adhesion length of thebeam, respectively. It is assumed that the beam movestatically. Here, we can obtain the equilibrium equation of the contact system as
∂ ŨT
∂ ˜l
= {1 − F̃ cos(α) − F̃ C}
= 0.
∂C
∂C

(3)

Since the total energy of the system is stable if secondorder diﬀerential value of the total energy is positive.
Eqs.(1) and (3) yields√
dφ= ±2 1 + F̃ {cos(φ − α) − cos(α)}.
(4)
ds̃The non-adhesion length ˜l, horizontal displacementx̃ and vertical displacement ỹ of the beam base areexpressed as follows.

151

˜l = 1
2

x̃ =

1
2

1
ỹ =
2

∫

dφ
±√
1 + F̃ {cos(φ − α) − cos(α)}∫

cos(φ)dφ

±√

(5)

(6)

1 + F̃ {cos(φ − α) − cos(α)}∫±√− sin(φ)dφ
1 + F̃ {cos(φ − α) − cos(α)}(7)

Consequently, for the beam without inflection point,
the integration interval is from 0 to θ, whereas for the
beam with inflection point, the integration interval isfrom 0 to φc and φc to θ. φc is the deflection angle atthe inflection point.

3

Result and discussion

Fig.2 shows the relation between the total energy of thebeam and the curvature parameter. ∆ŨT , as shown in
Fig.2, denotes the gap between the total energy of thebeam when it deforms with an inflection point comparing to that in equilibrium without an inflection point.
When the energy gap ∆ŨT is zero, the beam exhibitsa fransition from its deformation without an inflection point to that with an inflection point. But thebeam detaches from the object afterward since no energy equilibrium exists. When the energy gap exists,
the beam does not exhibit the fransition. Therefore,
as long as a constant force applied, a transition would
not happen from the beam without an inflection point
to that with an inflection point. In this paper, sincedetachment from grip is of our interest, we only discuss
the beam without inflection point.
When the tangential force F̃t is kept constant, themaximum value of the normal force F˜n becomes the
maximum adhesion force as long as the system is atequilibrium. Consequently, the maximum adhesion
force can be controlled by the tangential force, and forthis device, griping and detaching performances can beachieved by manipulating the tangential force.
We have also examined the relationship between the
maximum adhesion force and the angle of the beambase θ, as shown in Fig.3. It is observed that as θ decreases the maximum adhesive force increases. Therefore, the smaller the angle of the beam base is, theheavier object the beam can grip. However, when the
beam length L is suﬃciently long, the influence of thebeam base angle on the adhesion force become less as
the tangential force increases. Or in other words, therelease range becomes larger as the base angle of a sufficiently long beam becomes larger. Consequently, thebeam can grip and release objects of various weights byselecting appropriate value of the base angle. However,
we should be careful that the maximum adhesion force
would decrease when the base angle is large, and thebeam length is short. Therefore, the larger the beambase angle is, the longer the beam length is required.
The smaller the beam base angle is, the more heavy
object the beam can grasp. On the other hand, thelarger the beam base angle is, the lighter object thebeam can release. But, when the beam length is sufficiently long, the influence of the beam base angle on
grip and release becomes less as the tangential force
increases.

4

Fig. 2: Total energy equilibrium depends on curvatureparameter

Fig. 3: Maximum adhesion force depends on angle ofbeam basestudied with considerations of its inflection point. The
beams with and without inflection point were carefully
analyzed, and the results showed that there is no transition from the beam without inflection point to thatwith inflection point. The relationship between the adhesion force and the angle of the beam base was also
discussed, and concluded that the smaller the beambase angle is, the more heavy object the beam cangrasp and, the larger the beam base angle is, the lighter
object the beam can release.
The proposed model is required for designing a gripand-release device using an array of side-contact elastic
beams.

References[1] M. Salioukov et.al., Mate vol.24 pp. 261-264,
2018, Jan.

Conclusion

An adhesion model utilizing a side contact of an elastic
beam was proposed, and the behavior of the beam was
152[2] L. W. He et.al., Journal of Applied
Physics,vol.112, no.1,pp.013516- 1-6,Jul. 2012.

公共交通指向型開発のための都市成長モデルの開発
学籍番号：15_09852

氏名：董 思繁 指導教員：花岡 伸也, Alvin Christopher Galang Varquez

1. はじめに国際連合が発表した「世界都市人口予測・

い入力レーヤーとして加えて, 道路に沿う開2018 年改訂版」により, 2018 年の世界都市人発より駅周辺の都市成長に優先させるの二つ

口率は 55%であり, 2050 年に 68%増加すると予の手法で SLEUTH モデルを再開発する。

測されている。そのうちの 90％近くがはアジア

2. 研究手法とアフリカに発生すると予測されている。急激

本研究では, TOD の典型例と考えられるつくな都市化により, 都市部の森林、緑地の減少,

ばエクスプレス線の中の茨城県にある 6 つの汚染, 交通渋滞などいろいろ問題が起こって駅を研究エリアとして, 1997, 2006 ,2009 ,2014

いる。これらの問題を避けて, より持続可能な年のデータから 2014〜2050 年の都市成長状

都市発展を求めるために, 都市成長モデルを況を予測した。

用い, 将来都市の成長状況と土地利用転換の傾向を把握する必要性がある。
SLEUTH モデル(Clarke.K.C,1997)はその背景に応じて開発された都市成長シミュレーショ
ンモデルである。SLEUTH モデルは過去のデータから将来の都市成長パターンを把握できることを前提し, 6 つの入力レーヤー(斜面, 土
図 1.   研究エリア(35.94°~∼36.09°,  139.99°~∼140.12°)  地利用, 排除, 都市, 交通, 陰影)は全て研究エリアの過去の地図から得る GIF イメージと

2.1 排除レーヤーの最適ピクセル値を発見要求されているため, 地域の要因に制限され排除レーヤーはピクセルの値により海、川のなく, 世界範囲で広く使える特性がある。モデ

ような都市化不可能な地域を定義する役割がルは今まですでに世界で 100 個以上の都市ある。 新しい排除レーヤーはもとのデータのに利用され, パフォーマンスを検証された。し上に駅の地図を加え, 駅の影響を考慮するたかしながら, モデルの交通レーヤーの入力はめに, 駅エリアを一番都市化される可能性高道路の地図だけがあり, 道路発展の都市成長

いようにピクセル値に 0, 川部に 100 を与え,への影響しか考えていない。これは持続可能

その他の地域の値は 0〜70 の間に 5 を間隔とな都市開発に足りないと考えられるため, 本研

して 15 回繰り返してモデルを実行した。

究では公共交通機関の発展を考慮し, 公共

2.2 新しい入力レーヤーを作る

交 通 指 向 型 開 発 (Transit

Oriented

SLEUTH モデルの中に既存のシミュレーショ

Development, TOD) の下の都市成長を予測

ンルールに基づいて, もともとの道路に沿う都できるように,

1) 排除レーヤーで TOD が反市発展より駅周辺の成長を優先させる。また,映できる最適なピクセル値を探る; 2) 駅を新し駅の開業による都市開発は駅を中心として駅

153

周辺に発散する特徴があるため, 円型で拡散

数え, 全体の都市ピクセルに対する比率を計する成長に工夫をした(図 2)。

算した結果, 新モデルの駅周辺都市比率は0.0226 で, オリジナルモデルのほうは 0.0220であった。さらに, 新モデルとオリジナルモデ
ル両方の 2014 年のアウトプットを用いて精度検証した結果, それぞれの精度は 84.92%と84.67%であった。

4. おわりに図 2. 道路と駅の都市成長の特徴

3. 結果

結果によって, 排除レーヤーにおいてのピ

3.1 排除レーヤーの最適ピクセル値を発見

クセル値はそれぞれ川部 100, 駅エリア 0, そ異なるピクセル値を持つ新しい排除レーヤの他の地域 50 の時に, TOD の影響を一番大ーを用いてシミュレーションした 2014 年の結果

きく体現できると考えられる。また, 駅レーヤー

を実際の土地利用状況と比べて, それぞれのを加えた新 SLEUTH モデルにおいて, 都市の精度を検証した (図 3)。その他の地域のピク

発展はオリジナルモデルと比べてより駅に集セル値が 50 のとき, モデルの精度が一番高い

中することが実現できた。さらに, TOD 影響をと見え, 86.04%と検証された。

考慮した後に, より精度高い予測ができると考えられる。
本研究では駅周辺の都市成長に優先性を与えることによって SLEUTH モデルを公共交
通指向型の都市開発に発展した。この結果を用いて, 研究エリアの将来の都市発展の成長

図 3. ピクセル値が異なるときのモデルの精度検証

可能性と起こりうる問題が見込まれ, 持続可能また, 2050 年の都市成長確率アウトプットかな都市を作るために参考になると考えられる。

ら, 15 つのケースの間に, ピクセル 50 の場合

排除レーヤーでピクセル値の与えにより駅エリに駅周辺の成長率とほかの地域の成長率のアの発展に加重をしたことと新しい入力レーヤ差が一番大きく見える(図 4)。

ーを作ったことから SLEUTH モデルの柔軟性とポテンシャルを検証できた。また, 公共交通システムの発展は将来の都市成長に関わる重要な要因と考えられているため, これからの研究において, TOD の影響を表す数式モデルを
SLEUTH に結合し, より精度が高いシミュレー
ションを求めることに工夫をするべきである。

図 4. ピクセル値 50 のときの 2050 年都市成長率結果

3.2 新しい入力レーヤーを作る

参考文献

駅を考慮した新モデルと駅考慮しない旧モデル両方を実行し, 2050 年の土地利用状況の[1] United Nations, 2018, 2018 Revision of World

結果を比べた。駅エリアの都市ピクセルの数を

Urbanization Prospects

154Exploring Europa by Plume Breaking
Student Number: 15_15137

Name: Juyon Yamazaki

Supervisor: Daisuke Akita

1. Introduction

3. Modeling Plume

Beneath the icy surface of Jupiter’s moon Europa is perhaps themost promising place to look for present-day environments suitable
for life. Due to Europa’s eccentric orbit, heat created by tidal flexing is
considered to cause the ice to melt and form a huge amount of salty
ocean. Therefore, many missions have proposed to explore Europa tofind out its habitability. Since image captured by Hubble Space
Telescope revealed water vapor erupting from near south pole, it now
brings us great opportunity to study the characteristics of Europa’s
subsurface ocean without digging thick icy surface anymore.
However, this phenomenon is yet poorly understood that the locationof the vent is not precisely known and is difficult to predict thissporadic event.

The model we considered are shown in Fig.3. Vents are consisted ofmultiple narrow vents, and each vent erupts water vapor by angle of2𝜃.

2. Mission Concept
It is impossible to land near the vent by detecting the plume unlessthe phenomenon is well known. Therefore, we propose a mission that
detects the plume by using numbers of a small size lander.
Fig.1 shows the mission scenario and the concept of the lander. In
order to detect plume, lander is injected to the polar orbit all of which
cover the area (latitudes between -80~ -50 [deg] and longitudes
between 120 ~ 250 [deg]) [1] where the vent is known to be foundroughly from mothership orbiting Europa. When a lander
encounters(detects) plume, it would decelerate due to the force ofplume that flight trajectory would change dynamically (We call this“Plume Breaking”). The mothership would track the lander andreveals plume’s characteristics by using radar in the meantime. Lander
is supposed to be very light to get enough deceleration not to crash.
Our mission considers the lander’s ballistic coefficient near 0.1[kg/𝑚" ]. Zylon is used for heat protection and high elastic metal isused to keep its body. Payloads should be light enough.
Our goal is to estimate the feasibility of this mission which is,•
Is it possible to make the lander encountering plume get enoughdeceleration by plume force and touch down on surface under
the speed 200 [m/s]?
•
Can the lander touch down inside the area of the plume oroutside but not far from the area?
•
How many landers are required for this mission?
Unknown for the characteristics of the plume, modeling the plumeis necessary.

Fig.2 Plume model
We assume the flow is compressive and isentropic, only the gravityof Europa works as the force. The initial state gives,(1-1)
𝑎 = 2𝑛 − 1 𝐿 + 2𝑛𝑤-./01
6" "3 𝑆3 = 2𝜋𝑤𝑛𝑎 − 𝜋𝑤𝑛 𝑛 − 1 𝑙 − 𝜋𝑤 𝑛 = 𝑆-./01 (1-2)
The equation of mass flow and energy conservation gives,𝑚 = 𝜌𝑆𝑣 = 𝑐𝑜𝑛𝑠𝑡.
?
"

"

𝑢 −

/A

+

E GH

I EF?

EF? IH IH
BCDI
𝑃 = 𝑃K ( )EG

(1-3)
= 𝑐𝑜𝑛𝑠𝑡.

(1-4)
(1-5)

H

Isentropic flow gives Eq. (1-5). As shown in Fig.2, plume will spreadin a circle whose radius is the tangent of the height, however the area
can be solved in a different way between certain height from thiscalculation.
𝑆 = 2π𝑛" 𝑙 + 𝑤 {ℎtan𝜃 + 𝑤/2}
𝑆 = π(𝑎 + ℎtan𝜃 + 𝑤/2)"(2ℎtan𝜃 ≤ 𝐿) (1-6)(2ℎtan𝜃 ≥ 𝐿) (1-7)

We used the initial state of the plume’s velocity and area as 𝑣K as 560[m/𝑠 " ][2], 𝑆K =𝑆-./01 =1.5×10[ [𝑚 " ][2], the mass flow for 7.0×
10] [kg/s] [2], and the width of each ring 𝑤-./01 as 10 [cm] [3]. 𝑎,
𝜃 , 𝑚 are the parameter of this model because these depends on
Europa’s activity which is impossible to predict.
𝑎[m]: radius of plume area
𝑛: number of ring𝐿[m]: distance between ring
𝜃 [deg]: eruption angle
𝜌 [kg/𝑚 ] ]: density of plume𝑆3 [𝑚 " ]: the area of k’s ringv [m/s]: velocity of plumeS [𝑚 " ]: area of plume𝛾: Specific heat ratio of plume r [m]: radius of Europa
𝜇a [𝑚 ] /𝑠 " ]: Europa’s gravitational constant numberh [m]: height𝑚 [kg/s]: mass flow

4. Motion Equation
Motion of the lander is considered in polar coordination shown in
Fig.3. The Force taken into account for the motion is the gravity ofEuropa and air force of plume. The motion equations of the lander are
given by Eq. (2-1~4)

Fig.1 Mission Scenarios, Lander Concept
155

bE
bc
bg
bc
be
bc
bj
bc

d

g

e
dA

e

= ( Af − )𝑐𝑜𝑠𝛾
=

ef

"?

"

i

𝑠𝑖𝑛𝛾 − 𝜌𝑣= 𝑣𝑠𝑖𝑛𝛾=

the surface. This case brings worse mission scenarios. However, we
can obtain the characteristics of plume by tracking the trajectory oflanders using the mothership.
Fig.5 shows the lander’s distance from plume area and the last
speed when 𝑚 = 7000×100 [kg/s]. Fig.6 reveals what Fig.5 reveals
that the smaller the radius of the plume area, the closer landers can land
from the area of the plume and the greater landers get the reduction of
speed. We should pay attention to the speed that this differs from
Fig.5’s. In some conditions, landers can manage to soft-land andconduct some scientific mission sending results to the mothership.
This case brings preferable mission scenarios.
From Fig.6, we can estimate the number of landers its needed for toachieve mission succeed. 𝑎 = 2.4 [km] is the maximum which
satisfies the condition of last speed. Since the area where plume vents
are supposed to be has 1758 [km] to be covered, the required numberof landers for the case of Fig.6 is roughly 370. If 𝑎 ≥ 2.4 [km], it
would become hard for soft-landing even though we can get thecharacteristics of plume with fewer landers. If 𝑎 ≤ 2.4 [km], morenumbers of landers are needed to fully cover the area though landers
can soft-land and conduct scientific missions.

(2-1)

?

(2-2)
(2-3)

gklmE

(2-4)

e

Fig.3 Motion equations model𝑡 [s]: Time from Plume entry𝑣 [m/s]: velocity
𝛾 [deg]: flight path angle
𝜃 [deg]: Longitude
𝜌 [kg/𝑚] ]: density of plume𝑟 [m]: distance from the center of Europa
𝜇a [𝑚 ] /𝑠 " ]: Europa’s gravitational constant𝛽 [kg/𝑚 " ]: ballistic coefficientEq. (2-1~4) is numerically calculated by 4th order Runge-Kutta
method with time step of 0.01 [s]. 𝜌 is given by solving Eq. (1). 𝛽 ,𝑟 are the parameter of the trajectory. It should be noted that the lander
may perhaps not be in the plume and at that time, the air force ofplume should not be taken into account. This happens when the lander
has flown away from the area of plume or when the height of thelander satisfies Eq. (1-5) and the lander in the position surrounded byplume (See position 2 shown in Fig.4).

Fig.5 Distance and Touch down speed (𝑚 = 7000×1 [kg/s].)

Fig.5 Distance and Touch down speed (𝑚 = 7000×100[kg/s].)

6. Conclusion

Fig.4 Position of the lander

Recently found plume in Europa gives us great opportunity for
scientific discoveries however not yet understood. We suggested themission that can help finding plumes and even land near or inside theplume area by simple and cheap way.When mass flow is given as
7000×100 [kg/s], provided that more than 370 landers were broughtfor the exploration, landers can detect plume and land near the area ofplume in some conditions. Regadless of the characteristics of plume,
we can obtain it. However, the model and the assumption would makethe result shown above uncertain. There is still room for improvement
if we take into consideration more precisely to model plume.

5. Trajectory Results
From chapter3 and chapter4, there are five parameters to simulate
the lander’s trajectory. However, 2 parameters from chapter4 can becontrolled manually. Therefore, 𝛽 =0.1, 𝑟=500 [m] are chosen since
the smaller ballistic coefficient gives more plume force to break(plume breaking) from Eq. (2-1), and the lower height gives thicker
plume from Eq. (1-4) which then results to above.
From Eq. (1-1,5,6), if height is low, the radius of plume area affects
much more than the angle of eruption. However, the mass flow is thestrongest to affect plume. Hence, we assumed the lander’s touch down
speed and the distance from the plume area is affected by the mass
flow and the radius of plume area.
Fig.5 shows the lander’s distance from plume area and the last
speed when 𝑚 = 7000×1 [kg/s]. Fig.5 reveals that the larger theradius of plume area, the further the lander would land from the area ofplume area. though if it is small, the lander would not land in the areaof plume but land far. In this case, we cannot make landers to land
inside the plume. The speed is poorly reduced that it would crash into

7. References[1] Alyssa R. Rhoden (2015) “Linking Europa’s plume activity totides, tectonics, and liquid water”, Cornell University[2] Lorenz Roth (2014) “Transient Water Vapor at Europa’s SouthPole”, Science Vol.343, Issue. 6167-10[3] Jurgen Schmidt (2008) “Slow dust in Enceladus’ plume fromcondensation and wall collisions in tiger stripe fractures”, Nature
Vol.451, Issue. 685-688
156

Development and Calibration of Radio Sensor using Off-the-shelf
Software-defined Radio for Location Fingerprinting
Student Number:15B05127

Name:Jiang Haichen

Supervisor:Jun-ichi TAKADA, Azril Haniz

1 Introduction
Recently, with the fast spread of wireless local area
networks (WLANs) and mobile devices, localization
systems have become significantly important by the increasing needs of location based services (LBS). Global
Positioning Systems (GPS) is usually used to provide
precise location of subjects in open area. On the contrary, Indoor localization systems can not use the satellite signals due to complex influence of many obstacles
inside buildings [1].
Fingerprint positioning technology, one of the popular positioning technologies for indoor localization systems, utilizes specific signal characteristics such as received signal strength (RSS) with specified reference
locations as the offline database. In practice, the target’s location fingerprints are matched with the closet
offline location fingerprints to estimate its location. In
order to enable students and amateurs to apply thisapproach, a cheap and easy-to-use device which cancollect a variety of different fingerprint values is necessary [2].
In this thesis, LimeSDR, an off-the-shelf softwaredefined radio (SDR) with flexibility and low cost, will
be introduced and researched for the stability and reliability of collecting particular signal characteristics
which is needed for indoor localization systems.
The objective of this thesis is to figure out whether
LimeSDR can be used in measuring specific location
fingerprints accurately based on the measurement result after calibration.

Figure 1: Block diagrams for LimeSDR to process Rx
signals.
Figure 1 shows the block diagrams of LimeSDR as asignal receiver. Firstly RF signals are received by twoantennas, and then are amplified with low noise amplifiers (LNA). In the next stage, the signals are fed into
mixers with another signal generated from the local
oscillator to convert the signals into baseband signals
and then passed through low pass filters (LPF). Thenthe analog baseband signals are converted into digital IQ signals by Analog-to-Digital Converters (ADC),
and then finally processed by a transceiver signal processor (TSP). In the TSP, the received signal is further
adjusted by applying IQ imbalance, gain and DC offset
correction. Finally, I (In-phase) and Q (Quadrature)
data of baseband signals is transferred to a computerby a USB3.0 connection and processed by software like
GNU Radio Companion (GRC) or LimeSuite which
also can set the configuration of LimeSDR [3].

2 Development environment of
LimeSDR
The radio sensor which is used to measure the location fingerprint is constructed using LimeSDR and
GNU Radio.

2.1 Architecture of LimeSDRLimeSDR is a cheap and powerful SDR with tworeceiver and transmitter channels receptively which
offer great flexibility compared to other SDRs with
only a single receiver and transmitter channel. In thisresearch, since only the development of a receiver isconsidered, we will omit explanation regarding thetransmitter, this section will explain how LimeSDR
receives signal data from two channels which can beutilized for fingerprinting collection.

Figure 2: LimeSDR

2.2 GNU Radio
GNU Radio is a free and open-source software development toolkit that provides signal processing blocks
to implement software radios. In this research, theLimeSDR source block was employed to control someparameters like RF frequency, RX gain, and also receive samples from the LimeSDR. Then, the File Sink
block was employed to store the received raw IQ data
into a binary file for further processing.

157

3.2

Measurement result

The measurement results are shown in Table 2, including phase difference between RX channels, output
power of two RX channels and IQ phase difference ofindividual channel.
Figure 3: Operating layer of GNU Radio

Table 2: Average measured results with original configuration by LimeSDR

3 Measurement and evaluation

Frequency
2.402GHz
2.426GHz
2.480GHz

3.1 Measurement Method by LimeSDR
To make sure LimeSDR could be used for indoor localization system, we have to ensure that it can accurately measure the location fingerprint from received
signals which are transmitted from a commercial device. In this research, two types of fingerprints, RSS
and phase-difference fingerprint are considered. RSS
represents the power of the received signal, and phasedifference fingerprint is calculated by taking the phasedifference between two receiver channels. Therefore, itis necessary to evaluate the accuracy in measuring RSS
and phase-difference in this research.
As shown in Figure 4, a Sine wave with various
value of power and frequencies in Bluetooth low-energy(BLE) channels will be generated by a Signal Generator (SG) and divided into two separated signals by apower splitter. Then LimeSDR receives two individual signals and convert them into digital IQ data for
laptop to process into the desired fingerprints. Here,the signals were converted into 0.5MHz low IF (Intermediate Frequency) signals instead of baseband signals
by setting corresponding RF frequency in GNU Radioto avoid the DC offset error, and the sampling frequency of the LimeSDR was set to 2.5MHz. Each typeof measurement was conducted for 20 times consecutively, and the whole process was repeated twice tocheck reproducibility.

Output Power
Output Power
Phase differencein channel1(dBm) in channel2(dBm) between channels(degree)-56.48-56.4332.50-56.29-56.2033.74-55.67-55.63
36.75

The measurement results showed that there were significant errors in the measured power and phasedifference, which should ideally be 30dBm and 0degrees, respectively.

4

Calibration and conclusion

In order to calibrate the system and eliminate the errors, we performed the following steps. Firstly, we employed the automatic IQ calibration function in GNU
Radio to reduce the IQ phase difference for each channel. Then the transmission loss due to the power splitter and cables was measured by a vector network analyzer (VNA) and subtracted from the measured data.
We also applied a fixed phase-offset to channel2 basedon the first measurement results to eliminate the phasedifference between channels. The result is shown in the
Table 3.
Table 3: Average Measured results after calibration
Frequency
2.402GHz
2.426GHz
2.480GHz

Output Power
Output Power
Phase differencein channel1(dBm) in channel2(dBm) between channels(degree)-29.97-29.960.15-29.95-29.990.24-30.03-30.040.28

Compared with Table 2, the results with calibration
was more accurate, which proves that collecting fingerprint values with calibration is necessary. Therefore,
in this work, LimeSDR was successful in accurately
measuring location fingerprints, and will be utilized asradio sensors in indoor localization systems as future
work.

References
Figure 4: Measuring Environment

Table 1: Setting of configuration of input sine signal
from SG
Frequency
Power2.402GHz
2.426GHz
2.480GHz-30dBm[1] Y. Gu, A. Lo and I. Niemegeers, ”A survey of indoor
positioning systems for wireless personal networks,” inIEEE Communications Surveys & Tutorials, vol. 11,
no. 1, pp. 13-32, First Quarter 2009.
[2] H. Liu, H. Darabi, P. Banerjee and J. Liu, ”Survey ofWireless Indoor Positioning Techniques and Systems,”
in IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 37, no. 6,
pp. 1067-1080, Nov. 2007.
[3] LimeMicro, LMS7002M Datasheet. [Online] Available:
https://wiki.myriadrf.org//LimeMicro:
LMS7002M\_Datasheet\#RXTSP\_structure158

Separation of acetonitrile from pharmaceutical wastewater using solvent
extraction
Student Number: 15B06836

Name: Kaito Sawada

1. Introduction

Supervisor: Ryuichi Egashira, Hiroaki Habaki

Table 1 experimental conditions
Shaking[h]48
Settling[h]
1
Shaking temperature[K]
298
Acetonitrile aq.
[-] (mass fraction) 0.1~0.9
Solvent (Heptane: Toluene)
1:0, 3:1, 1:1, 1:3, 0:1
Solvent/Feed ratio[-]
1
Mass (respectively)[kg]
2.0×10-2

Acetonitrile is an important compound in the chemicalindustry, especially used in the pharmaceutical industry,
and is generally produced as a by-product ofacrylonitrile. Since the price of acetonitrile is unstable
due to demand fluctuation of acrylonitrile and most ofacetonitrile used in the pharmaceutical industry has
been discharged, the recovery and recycle ofacetonitrile is recently attracting much attentions. On
the other hand, acetonitrile forms an azeotropic mixture
with water [1] and it is impossible to separate themixture by the ordinary distillation. Then, someseparation methods have been studied, such as pressure
swing distillation [2], extractive distillation, solvent
extraction [3], and so on.
In this study, the application of the solvent extraction
to recovery of acetonitrile from pharmaceuticalwastewater was studied. Then, the liquid-liquid
equilibrium was experimentally measured withhydrocarbons as solvent and the recovery ofacetonitrile was investigated.

3. Results and Discussion
In Water-Acetonitrile-Heptane-Toluene ternary andquaternary system, basically it forms liquid-liquid 2
phases. But three liquid phases are formed whensolvent is heptane 50, 75 ％ , feed is higher thanacetonitrile mass fraction 40 ％. Since it is said thatindustrial operation is difficult if it becomes threephases, these samples in three phases are not measured
in this study. In addition, these didn’t form emulsion,
therefore it is easy to separate them. From these results,
it was found that separation operation is possible.
Component i, j contains Water, Acetonitrile, Heptane
and Toluene as W, A, Hp and T respectively. materialbalance is given by

2. Experimental#" 𝑥" = 1

Heptane and toluene were selected from alkane andaromatic compounds, respectively, and used as solvents.
The experimental conditions of liquid-liquid
equilibrium measurements were listed in Table 1. In
advance, the aqueous solution at the specified massfraction of acetonitrile and the mixture of heptane andtoluene at the specified ratio were prepared, and they
were contacted in the conical flask at 298 K in theisothermal bath for 48 hours to be equilibrated. The
mass ratio of the feed and solvent was fixed at unity.
After equilibration, both phases were analyzed by gas
chromatograph GC2010 and Karl Fischer titrator 758
KFD Titrino to determine the compositions of bothphases. In cases of analysis of the aqueous solution by
Karl Fischer titrator, it was occasionally difficult todetermine the mass fraction of water, and then it wascalculated using the mass balance relationship.

(1)#" 𝑦" = 1

𝑅( 𝑥",( + 𝐸( 𝑦",( = R𝑥" + 𝐸𝑦"

(2)
(3)

where, E, R is each mass of extract phase and raffinate
phase after extraction. E0, R0 is mass of feed solution
and solvent. xi is mass fraction in raffinate phase. yi ismass fraction in extract phase. xi,0 is initial massfraction in feed, about component i.
Water in raffinate phase is calculated by equation (1).
Regarding the extract phases, the mass fraction ofacetonitrile are adjusted so that the total is 1, using
equation (2). Using equation (3), Data is out of thisequation a lot is removed.
Distribution coefficient mi about component i,
Separation selectivity βi,j of component i relative tocomponent j is given byymi = i
xi

(4)

mi
mj

(5)

βi, j =

159

()*+,-.+/.0*1234415/3)+.,-1678'

Fig. 3 shows separation selectivity of acetonitrile
compare to water with solvent of mixture heptane andtoluene. For heptane 100％ solvent, when xA,0 is 0.1
and 0.2, the mass fraction of water reached 10 ppm
order, so it cannot measured.
The more Heptane mass fraction is in solvent, thehigher βA, W is. Moreover, Any solvent βA, W decrease
as xA,0 rises. It is thought that the reason for thosefeatures is the large effect of the distribution coefficientof water.

Azeotropic composition
Key Solvent!"&

HeptaneToluene!"%!"$4. Conclusion!"#

From the results, it was found that acetonitrile could
be separated from water using solvent extraction.
The distribution coefficient of acetonitrile increased as
the polarity of solvent increased.
On the other hand, the selectivity of separation ofacetonitrile against water decreased as the polarity ofsolvent increased.

!
!

!"#

!"$

!"%

!"&

'

9,0:*-+1234415/3)+.,-1678
Fig. 1 Phase Diagram of Liquid-liquid equilibrium
ternary system

5. Reference
Fig. 1 is phase diagram of Water-Acetonitrile-Solvent
liquid-liquid equilibrium. In Water-AcetonitrileHeptane ternary system, it is found that it has solubility
for heptane and acetonitrile, heptane and water. In
Water-Acetonitrile-Toluene ternary system, It is foundthat only toluene and water have solubility. In addition,
the azeotropic composition in the case of removing thesolvent is indicated by a black solid line in the figure.
It was suggested that it is possible to exceed theazeotropic composition after the extraction operation
with any solvent.
Fig. 2 shows effects of Initial feed mass fraction ofacetonitrile to the distribution coefficient of acetonitrile
with solvent of mixture heptane and toluene. The more
Toluene mass fraction is in solvent, the higher mA is. It
is thought that the reason for this is that toluene has ahigher polarity than heptane, acetonitrile also relatively
high polarity, so more acetonitrile moves extract phase.
And, effect of xA was not clear.

[1] J. Gmehling, J. Menke, et al. Azeotropic Data for
Binary Mixtures, (1994).
[2] Repke J U, Klein A, et al. Pressure swing batch
distillation for homogeneous azeotropic separation[J].
ChemicalEngineering
ResearchandDesign,85(4):492-501, (2007).
[3] Acosta J, Rodríguez I, et al. Recovery of acetonitrile
from aqueous waste by a combined process: Solvent
extraction and batch distillation Sep. Purif. Technol.
2006, 52, 95– 101, (2006)

!""""
10
104

10
#!

!' ()*+

10
#0

10-1
!"#

mass fraction
Solvent of Heptane

Hp

1

Hp+T

0.75

Hp+T

0.5

Hp+T

0.25

T

0

10-2
!"!#
!

!"$

!"%

!!
+,-)
'()*
'()*

Key

100
!"""
103

10-1

!""
102-2
"

!"&

"#$

"#%

"#&

" '++()*+""''))+,-)

Fig. 2 Distribution coefficient of acetonitrile

Fig. 3 Separation selectivity of acetonitrile comparewith solvent of mixture heptane and toluene

to water with solvent of mixture heptane and toluene

160

無線ネットワークセル設計のためのニューラルネットワークを用いた電波伝搬損失予測
学籍番号: 15B05044

1

氏名: Jin Yongri

指導教官: 高田 潤一、 齋藤 健太郎
ことで, 式 1 から 送信点から受信点における伝搬損失がはじめに求まる. PT は送信レベルで, PR は受信レベル,P L は伝搬

近年移動通信分野におけるデータトラフィックが急速損失をデシベル (dB) で表している.

に増加している. Cisco 社の調査によると世界のデータト
ラフィック量は 2021 年には 2016 年の 7 倍に達すると予測されている [1]. また将来は Internet of Things (IoT) シス

P L = PT − PR

テムの普及により様々な無線通信機器が利用されるよう

本シミュレーションでは表 1 のようにダイポール型のになると考えられており， 効率的な無線ネットワークのアンテナを使用し, 周波数は 5.2GHz に設定した上, 無線構築が重要になってきている. 無線ネットワークを構築す

局の送信電力は 200mW, 送信アンテナと受信アンテナのるにはエリア内の各地点の伝搬損失を把握する必要があ

高さはそれぞれ 1.5m に設定した.

るが，既存の伝搬損失推定式は市街地や屋内環境など複(1)

表 1: レイトレーシングシミュレーションの設定

雑な特徴を持つサイトの伝搬損失を予測する事に向いていない．一方で，実験によりあらゆる地点の伝搬損失を

電波周波数

5.2 GHz

測定するのは労力やコストの観点から困難である．そこ

送信電力

200mW

TxRx 高さ

1.5m

アンテナー種類

ダイポール

で本稿では，エリア内で離散的に得られた伝搬損失デー
タから Artificial Neural Network (ANN) を用いてエリア全
体の伝搬損失特性を予測する手法を提案する．屋内環境

2.2 ニュートラルネットワーク

でレイトレーシングのシミュレーションを行い，得られたシミュレーション結果からエリア全体の伝搬損失特性を予測する実験を行った．提案手法による予測の平均絶対偏差は約 7dB であった．今後は提案手法の無線ネット
ワーク設計への利用が期待される．

2

ANN を用いた電波伝搬損失予測手法

2.1 レイトレーシング (RT)

図 2: 計算に用いた ANN のモデル

本提案手法は図 2 で示すように 2 項分類用と回帰用のANN からなる. 2 項分類用の ANN はエリア内かエリア外を予測し, 回帰用の ANN は伝搬損失を推定する.

RT シミュレーションでは反射, 回折の回数などの拘束条
図 1: 電波伝搬

件により, 二種類の伝搬損失結果が得られる. 得られた結レイトレーシングシミュレーションとは電波を光に見果の一つは受信点で電波の受信ができた時の連続的な値

立て, 幾何光学的原理に基づき, 反射点を幾何学的に捜索で, もう一つは受信電力が閾値以下の場合もしくは有効伝するイメージング法, 送信点から全角度に均一に出射さ搬経路が発見されなかった時の離散的な値である. よっれるレイを幾何学的に軌跡をトレースするレイラウンチて ANN 回帰分析モデルをそのまま用いることはできなング法を用いてレイを追跡する方法である [2] . 図 1 のよい. RT シミュレーションの伝搬損失の結果に基づき, 電

うに伝搬の過程で生じる反射, 透過, 回折などをフリスの波が届いた連続的な結果にはエリア内, 電波を感知でき伝達公式より求まる自由空間伝搬損, フレネルの反射係なかった離散的な結果にはエリア外というラベルをつけ

数,UTD からの回折係数から計算し, 受信レベルを求めるることでもう一つのデータセットを作成する.

161

先ず Tx, Rx の座標とエリア内もしくはエリア外のイン
ディケーターでできたデータセットから教師あり学習をさせることで, 二項分類 ANN モデルの学習を行う. 次に Tx と Rx の座標とその間の伝搬損失で構成したデータセットを用いて, 教師あり学習をさせることで, 回帰用のANN モデルを作る. そして伝搬損失を知らない任意の二点の間で二項分類用の ANN を用いて伝搬が届くかどうかを予測する. 電波が届くと予測されたら, 回帰分類モデ
ルを使い, 二点間の伝搬損失を予測することができる.

3

実験
図 4: 二項分類結果の分布図

搬損失分布が求まる. 図 5 から廊下の角等を曲がる事で急激に伝搬損失が大きくなり，また通信エリア外の領域が現れる事が分かる．

(a)

(b)

図 3: 無線局の配置

シミュレーションの環境は東京工業大学西 9 号館の一階のロビーを想定した. シミュレーションでは電波を受信するレシーバー (Rx), 電波を送信するトランスミッター(Tx) 両方の機能をもつトランシーバーを用いた. 本研究では構造計画研究所により開発された Raplab ソフトウェ
ア・ツールを用いて RT シミュレーションを行った. 図 3で示すように 2m × 2m 間隔でトランシーバーをエリア
内に均一に配置し, レイトレーシングシミュレーションに5

よって異なる二点間の伝搬損失サンプルを 101904 セッ
ト得た.

まとめ

図 5: 伝搬損失分布図

本研究ではレイトレーシングシミュレーション結果を

結果の 80%を用いて ANN モデルをトレーニングし, 残用いてニュートラルネットワークをトレーニングし, そりの 20%を用いて ANN モデルのパーフォマンスを検証の ANN モデルを使い, エリアにおける任意の二点間の伝した [3].

搬損失を予測することができた. このモデルを更に活用4することで, 効率的に無線ネットワークの構築ができると結果と考察考えている.

二項分類用 ANN モデルでは, トレーニングにおいて今後の課題として, ANN モデルから予測する伝搬損失

97.5%, テストにおいては 97.3%まで正確率上げることがを実測値と比較することで, リアル環境でのパフォーマできた. 回帰用のモデルでは平均絶対偏差はトレーニン

ンスを検証する必要がある.

グで 7dB, テストサンプルでは 6.7dB のパフォーマンスが参考文献得られた. 両モデルにおいてトレーニングとテスト二種[1] Cisco. ”Visual networking index: Global mobile data traffic forecast,”
update 20142019, white paper.

類のサンプルセットでほぼ同じパフォーマンスが見られることから, 過剰適合は起きず, 汎化能力を持っていると[2] Z, Yun and F. Iskander , ”Ray Tracing for Radio Propagation Modeling: Principles and Applications,” in IEEE Access, vol. 3, pp. 10891100, 2015.

言える.
一つの例として無線局を座標 (20,10) においた場合, 二[3] A. Nielsen, ”Neural Networks and Deep Learning” Determination
Press,pp. 34-59,2015.

項分類モデルを用いれば図 4 で示しているように各場所
において電波を受信できる確率分布が得られる. 受信率[4] Yao Yiyun.”Path loss prediction by using machine learning for wireless LAN site planning” 東京工業大学環境社会理工学院 修士論文
[未公開]. Feb, 2017.

が 50%以上のエリアのみ抽出し, 回帰用のモデルにインプットすることで, 図 5 で示すように各場所における伝162

指向性チャネルモデルに基づく伝搬パラメータからの大型アレー MIMO システムのチャネル容量評価
学籍番号: 15B09438

1

氏名: 趙 恒偉

指導教官: 高田 潤一、 齋藤 健太郎
アンテナと周波数のサンプル点の番号である。
" 4
#
L
X
Y
(r)
yk1 ,k2 ,k3 ,k4 =sl
ejµl (kr ) + nk1 ,k2 ,k3 ,k4

はじめに
近年、ネットワークを利用した様々なアプリケーション

l=1

サービスの普及に伴い、高速移動無線通信システムに対す

(1)

r=1
(r)

る需要が高まっている。そのようなシステムにおいて、高また、sl は位相基準点間の複素伝達関数、µl

いデータレートの実現を目的とした Multi-Input Multiput-

遅延、nk1 ,k2 ,k3 ,k4 はガウスノイズである。sl と µl

は位相

(r)

はそ

Output (MIMO) 伝送が主要技術の 1 つとして注目されて れぞれ以下のように表される。
いる。更に、次世代通信規格である第 5 世代においては、
sl = αl fdep (Ωldep ) farr (Ωlarr )(2)2π
マッシブ MIMO と呼ばれる大型アレーアンテナによる指(1)µl (k1 ) =(k1 − 1) ∆dx sin θT,l cos φT,l(3)λ向性合成も導入される。一方、MIMO チャネルの評価に2π(2)用いられている双角度 (double directional) チャネルパラ
µl (k2 ) =(k2 − 1) ∆dy sin θT,l sin φT,l(4)
λ
メタは、アレーアンテナの素子間隔を半波長以下として2π(3)µl (k3 ) =k3 ∆dRx sin θR,l cos φR,l(5)
測定する必要があるため、比較的小型のアレーアンテナ
λ


N4
(4)
となり角度分解能が制約されることから、大型のアレーµl (k4 ) = 2π k4 −
∆f τl
(6)
2
アンテナに適用できるとは限らない。そこで、本研究でfdep , farr は送受に用いるアンテナの複素放射電界
は、小型アレーアンテナで測定した角度パラメタを用いて大型アレーアンテナのチャネル応答を予測し、実際に大パタン、αl は伝搬利得である。また、Ωldep ,型アレーアンテナで測定した結果と比較することによっ以下のように定義される。

て、予測可能な範囲を評価することを目的とする。

2Ωldep ≡ [φT,l , θT,l ] , Ωlarr ≡ [φR,l , θR,l ]MIMO チャネル構成Ωlarr は(7)

ここで、以下のようなパラメータを定義し、式 1 で表されるデータをベクトル化する。ここで、A ∈ C N ×L
はマルチパス応答ベクトルで、L はマルチパスの数である。また、記号 ⋄ は列ごとのクロネッカー積を示し、N =N1 N2 N3 N4 である。
 h (r)
iT
(r)
(r)
(r)
a µl
= ejµl (0) ejµl (1) . . . ejµl (Nr −1) ∈ C Nr
(8)

 h 


i
(r)
(r)
(r)
Nr ×L
A µ
= a µ1 · · · a µL
∈C
(9)








A = A µ(1) ⋄ A µ(2) ⋄ A µ(3) ⋄ A µ(4) ∈ C N ×L

図 1: URA x ULA MIMO チャネルモデル(10)

図 1 において、送信アンテナ URA では x 方向に ∆x
間隔で N1 素子、y 方向に ∆y 間隔で N2 素子、受信アン

3

テナ ULA では x 方向に ∆Rx 間隔で N3 素子がある。ま

3.1 測定諸元

た、アンテナにおいてはそれぞれ L 個の狭帯域平面波が本研究では、石垣市で実施した屋外伝搬測定によって放射・到来するとし、各波は図 1 に定める [2] 放射方位取得された実測値を使用する。測定諸元及び測定環境を

角 φT,l 、放射天頂角 θT,l 、到来方位角 φR,l 、到来天頂角

それぞれ表 1, 図 2 に示す。また、本研究の全測定は同じ

θR,l 、伝搬時間 τl 、伝搬における複素振幅の変化を持つ
αl (1 ≤ l ≤ L)。さらに、中心周波数を fc として ∆f 間

測定環境で測定した。図 2 は Tx と Rx の測定位置を表している。さらに、パラメータ推定のために小間隔円形隔で全 N4 点の伝達関数のサンプリングを行う。このとアレーアンテナを用いて測定を行った。また、推定されき測定される伝達関数 yk1 ,k2 ,k3 ,k4 は以下のように表される。ただし、0 ≤ kr ≤ (Nr − 1)

屋外 MIMO チャネル測定

たパラメータ [3] を用いて、測定で使用した大間隔 URA(1 ≤ r ≤ 4) は送受信

x ULA の MIMO チャネルを構成し、構成後の結果と実際に大型アレーアンテナで測定した場合の結果の比較を行う。
163

表 1: チャネルサウンダの詳細
パラメータ
キャリア周波数
信号帯域幅
送信電力
波長
周波数間隔 (∆F )サブキャリア数 (N )遅延分解能 (∆τ )最大遅延 (τmax )アレーアンテナ

値
11 GHz400 MHz
10 mW
2.73 cm
195.31 KHz
2048
2.5 ns5.12 µs
Tx: 12 素子 (二重分極)
Rx: 12 素子 (二重分極)
高さ: Tx:3m, Rx:8m(a)

図 2: 測定において Tx と Rx の位置
表 2: 測定の設定
測定
URA x ULA
測定

Tx
URA:12 素子
高さ:3m
間隔:5.46cm(b)

Rx
ULA:12 素子
方向:南南西 200◦
間隔:5.5cm

図 3: 全サブキャリアにおける各固有値の CDF グラフ

物の表面と平行であり、建物の表面近くの敷設材によって LoS のレベルが変わる可能性が考えられる。

3.2 結果と考察

4

小型アレーアンテナを使用して測定したデータに対しおわりにてパラメタ推定を行った結果を使用し、大型アレーアン

本研究では、小型アレーアンテナを用いて測定した伝

テナのチャネル応答を予測した結果を、実際に大型アレー

搬路パラメタを利用し、大型アレーアンテナのチャネルアンテナで測定した結果と比較した。なお、チャネル特応答を予測し、その結果を実際の測定結果と比較した。

性の合成に当たっては、素子アンテナの校正用指向性デー

比較の結果、今回予測した事例においては、両者は十分タがないため、遅延電力スペクトルのピークが実測値とによく一致しており、推定されたパラメタを用いたチャ

一致するようにスケーリングを行った。更に、両者の比ネルモデルがアンテナの大きさをある程度大きくしても較は固有値分布を指標として行う。はじめに全 2048 サブ

適用可能であることが明らかになった。

キャリアにおいて計 12 個の固有値を算出する。その後、サブキャリア毎に各固有値の CDF を求めることにより評価を行う。結果を図 3 に示す。なお、実線は測定データ、
破線は推定結果を表している。
図 3 より、測定データと合成データの固有値分布はおおむね一致していることが分かる。また、低い固有値

今後、他の観測点でも比較評価を行う。

参考文献[1] Dwi Joko Suroso, Kentaro Saito, Jun-ichi Takada. ”On Investigation of Directional Channel Model for Large Spacing Array MIMO:
Eigenvalues Comparison of Measurement and Channel Synthesis”.
IEICE Technical Report, pp.1-6, Feb. 2018.
[2] Kentaro Saito, Yunyi Yao, Jun-ichi Takada. ”Parameter estimation refinement of MIMO propagation channel by nonlinear conjugate gradient approach”. IEICE Communications Express, vol. 7, no. 9, pp.
328-333, Sep. 2018. DOI:10.1587/comex.2018XBL0083.

の分布は、測定データと合成データでほぼ同じ傾向がある。しかし、図 3 では、2 番目と 3 番目の固有値分布において、測定データと合成データの間に少し 1 ∼ 1.5dB の[3] Minseok Kim, Jun-ichi Takada, Kentaro Saito. ”Multi-dimensional
Radio Channel Measurement, Analysis and Modeling for High Frequency Bands (invited)”. IEICE Transactions on Communications,vol. E101-B, no. 2, pp. 293-308, Feb. 2018.

差がある。その原因は多分 LoS の方向性によるものである。図 2 に示した Tx と Rx の位置では、LoS の方向は建164

Development of Channel Sounder for SHF Band
Channel Measurement by Virtual Planar Array
Student No. : 15B05713 Name: Kang CheChia

1

Introduction

In the 5th generation mobile communication system(5G), the wide range of frequency bands from 2GHz to60 GHz is expected to be utilized for mobile communication to increase the network bandwidth drastically.
However, because the radio propagation characteristics signiﬁcantly depend on the frequency band, it isindispensable to clarify the dependency through a comparable measurement campaign for system design. In[1], SHF band channel characteristics was investigatedby the virtual uniform circular array (UCA) method.
However, it had the limitation of the degree of freedom of the array structure. In this paper, I developed
a virtual array measurement system by using a threedimensional positioner. The developed system has theadvantage that the arbitrary structure of arrays can beformed for the channel measurement. 3-dimensional
channel measurement was conducted in 12 GHz bandin an indoor environment and the measurement accuracy was investigated.

2

Signal Model of Virtual Array
Channel Sounding[2]The signal model received by the VA based channelsounder is shown as follows. In the measurement, thepositioner changes the receiving antenna position at M
points, and the frequency transfer function is measured
at each point. Assuming the number of frequency sample is N, the measured data is a MN×1 vector.
For an incident wave from Direction of Arrival (DoA)
θ, the propagation length diﬀerence dm (θ) from thereference point in position m is:dm (θ) = −(⃗u(θ) · r⃗m )(1)where ⃗u(θ) is the incident wave vector of DoA θ, andr⃗m is the position vector of the m-th antenna position.
Assuming that incident waves are plane waves, theideal array response, and the ideal signal distributionof the antenna array is:aa (θ)am (θ)= [a1 (θ), a2 (θ), ..., aM (θ)]T=e−j2πfndm (θ)C

Supervisor: Jun-ichi Takada, Kentaro Saito
where a(θ, τ ) represents the theoretical receiving signal
when the plane wave arrives with DoA θ and propagation delay τ , which is the product of aa (θ) and ad (τ ).
ad (τ ) is the united complex amplitude of antenna array with propagation delay τ . ⊗ here denotes the kronecker product. xmn is the received signals of the ith
antenna, j th frequency sample. As PBF (θ, τ ) is swept
over all candidate DoA θ, and delay of arrival τ , itwill reach peaks while the candidate approaches theobserved parameters.

3

Development of Virtual Array
based Channel Sounder

Figure 3 shows the structure diagram of the VA system composed by SURUGA SEIKI positioner and R&S
vector network analyzer (VNA) with a personal computer as it’s host. The PC and positioner is connectedby the serial port, and LAN cable was used to connect
the PC to the VNA. Both antennas are connected to
the VNA by a coaxial cable while the receiver is ﬁxed
on the positioner with an acrylic holder. The accuracyof the positioner is 10µm and the position repeatability
is ±3µm space[3].
To perform the measuring campaign automatically,
the software of this work is designed in C++ language
to hold control of the system.The PC ﬁrst should establish a serial communication with the positioner, anda control library for instruments called VISA is used toconnect with the VNA, then the transmit parameters
for the positioiner were set e.g. the number of antenna
elements, spacing distance, and center coordinate, andparameters for the VNA e.g. sweeping band, number ofsubcarriers, and transmit signal power. For each measurement position, the PC sends moving and trigger
commands to both devices, and collects data after themeasurement at that point is completed. The data is
named accordingly based on the position information.

(2)
(3)

where aa (θ) is the array response of the antenna array with DoA θ with its elements ai (θ), fn is the nthsubcarrier frequency of estimating signal, and C is the
speed of light. Array response represents the theoretical receiving signal of the array.
Then in the beamforming (BF) algorithm, assume theevaluation function PBF (θ, τ ) as follows
PBF (θ, τ )a(θ, τ )ad (τ )x====|aH (θ, τ )x|2
aa (θ) ⊗ ad (τ )[e−2πf1 τ , ..., e−2πfN τ ][x11 , x12 , ..., xmn , ..., xMN ]T

(4)
(5)
(6)
(7)
165

Figure 1: Structure diagram of VA system.

Measurement Experiment

4.1

Measurement setup[3] SURUGA SEIKI. ”Standard Type：SXM30.”
Internet: https://jpn.surugaseiki.com/products/series/SXM30,
2018[Feb. 12, 2019].
(Window)(Window)

4.48m

2.37m

N

Table 1: Measurement parameters
Frequency band
12.80 GHz to 12.95 GHz
Frequency points
201
Virtual Array
Cubic array (10 × 10 × 10)
with element spacing 10mm
Antenna
Horn antenna (10dBi)
10 dBmTransmit power

5.07m

4.2

Tx
(h: 1.19m)

4.72m

1.95m

(Door)(Door)

Figure 2: Top view of cubic array measurement.

Data processing

LOS

Using the channel transfer function (CTF) output by
VNA with the BF algorithm, the DoA power spectrum
can be obtained as Figure 3, in which not only LOS
but also several signals were detected. For the signals
traveled 12 m more than LOS signal did, it’s known as
the mix of double-bound reﬂect rays.

5

3.42m

2.53m

Rx
(h: 2.15m)

1.42m

Table 1 shows the basic data of measurement. This
research measured DoA azimuth and elevation, and delay spectrum of both axes with virtual cubic array system and 2 horn antennas. Tx site was 1.19 m awayfrom the ﬂoor, and the center height of Rx site was
2.15 m. To keep LOS within the main lobe of antenna,
Tx antenna pointed northward while Rx pointed southward. Figure 2 shows the top view of whole environment, where DOA= 0 is westward,i.e., the plus direction of Rx’s X-axis. Tx antenna was located 3.42m
apart from the Rx antenna, at the direction whose azimuth was 110◦ and elevation was −17.25◦ . It took 10
seconds to suppress the vibration of antenna holder.
The surroundings was a room full of small objects.

1.63m(Door)

4

Conclusion

Reflected signals

Figure 3: DOA estimation with cubic array.

The VA system was successful in distinguishing incident EM wave form LOS in 12.8 GHz band. However, the reﬂected waves wasn’t distinguishable form
the sidelobe of LOS wave with matched ﬁltered result.
To deal with the problem, measuring with more antenna elements again could be helpful in angle domain,
extending the measuring bandwidth is eﬀective in delay domain on the other hand. This two solutions deﬁnitely take more measuring time, so, it’s important for
future usage measuring 32 GHz band to reduce vibration suppressing time.

References

LOS

Reflected signals

Figure 4: DOA estimation with cubic array.

[1] W. Fan, I. Carton, J. O. Nielsen, K. Olesen, and G.
F. Pedersen, Measured Wideband Characteristics
of Indoor Channels at Centimetric and MillimetricBands, EURASIP Journal on Wireless Communications and Networking. vol. 2016(1), p. 58, 2016.
[2] Andreas F. Molisch. ”Channel Sounding” in Wireless Communications, 2n d ed, Chichester, U.K.:
IEEE., 2011, pp.145-164.
166

Selection guidelines Windmill and Generators for Small Wind Power Generation
System Considering Maximum Power Point Tracking
Student Number: 15B11754 Name: Hayashi Honoka Supervisor: Kunio Takahashi
UNIPULSE). The I-V characteristic of generator
changes depending on the load resistance shown in
Table.1. We measure the torque, rotational speed, andvoltage while varying resistance, wind speed andblade number, as shown in table 1. The current value
divides the measured voltage by the load resistance.
Measurement was continued for over 10 seconds.
Measurements are repeated twice.

１．Introduction
Movement to make small-scale wind power
generation system has been increasing. There is a needfor maximum power point (MPP) tracking with lessconsuming electric power, because one unit of smallscale wind power generation system generates only asmall amount of energy. small-scale wind power
generation system consists of windmill, generator,
boost convertor, and electric storage device. The boost
convertor performs MPP tracking (MPPT) andefficiently stores electricity while boosting up thevoltage. Prototype of autonomous boost converter forsolar power generation has been made [1]. By scanningI-V characteristics of solar cell, boost converter
automatically detects and tracks MPP. However, since
windmill takes time to reach a steady state 対象, themethod of using scanning is not suitable. The relation
among the wind speed, the rotation number of the dragtype windmill and the torque was experimentallyinvestigated [2]. However, since there is only one
generator, generator dependency cannot be verified.
Also, experiment apparatus is a possibility that thewind tunnel is too small to keep wind speed. Therefore,
there is a possibility that experimental result could not
be reproduced. Therefore, this paper experimentallyinvestigates the relation of wind speed, electric current,
voltage of small wind power generation system byusing sufficiently large wind tunnel and several
generators, and consider selection guidelines Windmill
and Generators for Small Wind Power Generation
System Considering Maximum Power Point Tracking

Table. 1 Various elements
Number of blade
8,12,16,20
Rated voltage of generator
Wind speed U
Load resistance R

7.2[m/s],6.0[m/s],4.8[m/s],
3.6[m/s],2.4[m/s],1.2[m/s]5M[Ω]over, 5080[Ω],1980[Ω], 1000[Ω], 488[Ω],198[Ω], 101[Ω],74[Ω],51[Ω],32[Ω],22[Ω],16[Ω],10[Ω],5.3[Ω],3.6[Ω],1.2[Ω]3. Results and discussions
3.1. I-V characteristic depending on type of windmill
Fig.2 shows I-V characteristic depending on
the type of windmill at the wind speed of 6.0m/s. The
I-V characteristics is linear when 20 blades. As thenumber of blades decreases, in the region where theload resistance is low, it is not linear.
Fig.3 shows relation between torque andvoltage depending on the type of windmill at windspeed of 6.0m/s. The relationship between voltage andtorque is linear when 20 blades, and as the number of
blades decreases, in the region where the resistance islow, it is not linear.
These shows the same trend. It can beconsidered that when the number of blades of thewindmill becomes small, windmill becomes impossible
to output torque enough to rotate the generator stably.

2. Experiment apparatus
A schematic diagram of the experimental
apparatus is shown in Fig.1. We prepare the same
shape of windmill with different number of blades.
The projected area varies depending on the number of
blades. And also prepare a commercial wind turbine(SMG-1001). Wind tunnel has a cross sectional areaof 50cm × 50cm which has sufficient size forwindmill of diameter 10cm to 20 cm. Three power
generators with equivalent output power and different
rated voltages have been prepared. Torque applied forgenerator is measured by the torque meter (UTMII,

Fig. 1

3,7,13[V/1000rpm]

3.2.

I-V characteristics depending on wind speed
Fig.4 shows the I-V characteristic of the 16
blades due to wind speed. The I-V characteristics islinear when U=7.2m/s. As the wind speed decrease, in
the region where the resistance is low, I-V characteristic
is not linear. When the wind speed decreases, the torqueoutput by the windmill decreases.
Fig.5 shows relation between torque andvoltage of the 16 blades due to wind speed. The
relationship between voltage and torque is linear when,wind speeds is 7.2 m/s and as wind speeds decrease, in
the region where the resistance is low, it is not linear.
Therefore, when the wind speed decreases,
sufficient torque can’t be output to rotate the generator,
possibly causing the output current to drop.

Experimental apparatus

167

0.5

2.0

0.01

0

5

10
15
Voltage V[V]U=7.2[m/s]U=6.0[m/s]U=4.8[m/s]U=3.6[m/s]

1.0

10
20
Voltage V[V]Fig. 4 I-V characteristic
depending on wind speed

Fig. 2 I-V characteristic
depending on windmill

0.2

0

0.5
V/Vopen[V]1Fig. 6 P-V/Vopen characteristics of thecommercial wind turbine

U=7.2[m/s]U=6.0[m/s]U=4.8[m/s]U=3.6[m/s]3.0Torque T[10-3Nm]

0.3

0.1

0

20

Gene
Gene
Gene
U=7
U=6
U=4
U=3

0.4

Power P[W]

20
16
12
8

Current I[10-2A]

Current I[A]

0.02

2.0

1.0

0

Fig. 3 Relation between Torque and voltage
depending on windmill

1020
Voltage V[V]Fig. 5 Relation between Torque andvoltage depending on wind speed

a method that takes half the voltage of Vopen. In such acase, it is necessary to re-select the number of blades of
the windmill and the generator.

3.3. P-V characteristics depending on type of generator
The open voltage is represented by Vopen. The
rated voltages of the generators prepared this time aredifferent. For the reason the output voltage of eachgenerator was normalized by Vopen. Fig.6 shows the PV/Vopen characteristics of the commercial windturbine. By setting the normalized voltage on thehorizon axis and the output power on the vertical axis
and plotting the experimental result of each generator,
the profiles appear to be the same. Since the profiles
are the same, MPP has the same value. So, MPP does
not depend on the rated voltage.
Therefore, there is a possibility that thegenerator can be selected according to the voltage
targeted by the boost convertor or the storage element.

4.Conclusion
・ In a drag type wind turbine, the output torqueincreases as the number of blades increases
・If the torque output from the windmill is large enoughto rotate the generator, the I-V characteristic of thegenerator can be linearly approximated・We suggest possibility if I-V characteristic can belinear approximation, MPP tracking with low power.

5.Acknowledgement
I would like to thank Prof. Chihiro
Yoshimura for providing the wind tunnel. Also I would
like to thank Prof. Atsushi Inagaki for his corporation
on measure wind speed.

3.4. I-V characteristics and MPP
If I-V characteristics can be approximatedlinearly, the voltage of the MPP(VMPP) is expressed by
the following equation with the open voltage(Vopen).
1
𝑉MPP = 𝑉open
2This suggests that when the I-V characteristic is within
the range which can be linear approximation, MPPT
can be performed by measuring Vopen and taking half ofVopen. This can be realized with lower power than themethod using the scan of reference [1].
If I-V characteristics can’t be approximatedlinearly, VMPP is not half of Vopen. Therefore, if the I-V
characteristic is nonlinear, MPPT cannot be done with

6.References[1] R.Asami, Master's thesis, Tokyo Institute ofTechnology, “Prototype of an autonomous energy
harvesting system using boost converter”[2] Y. Tokuda, Graduation Thesis, Tokyo Institute ofTechnology, “the Relation between Wind Velocity,
Rotation Speed and Torque of Drag Type Wind
Turbine for Small Wind Power Generation

168

Orbital Transfer System for Microsatellites using Laser Propulsion
Student number: 15-07830

Name: Shun Suzuki

1. Introduction

Supervisor: Daisuke Akita

2. Mission concept

Microsatellites, say less than 100 [kg], are being
actively developed by universities and enterprisefor the cost-effective space-based observation or
telecommunication. Figure 1 shows the increase in
the number of the microsatellite launches.
However, it is often launched in a piggybackmanner with a primary large satellite in order toreduce the launching cost as shown in Fig. 2.
Therefore, the microsatellites generally cannot
choose the date & time and launching orbit. In
addition, microsatellites are difficult to have a
propulsion system.
Laser propulsion is expected as a method of
promoting spacecrafts of the future because of thehigh-efficiency propulsion, which is realized by aremote laser system separated from theaccelerating target satellite. However, the lasersatellite with a sufficient power to propel usual
satellites have not been put into practical use.
This study shows the capability of an orbitaltransfer system for the microsatellite by a spacebased laser propulsion.

Figure 3 to 5 show the mission concept. In thisstudy, a space-based ablative laser propulsion is
selected not to require high performance for thelaser station as shown in Fig. 3.
1. A Laser Station is launched to an orbit of 400[km] altitude.
2. Laser is irradiated from the laser station to
the ablator attached to the acceleratingtarget satellite.
3. An ablation jet is generated from the surfaceof the ablator and propelled by its reaction
force.
Figure 4 and 5 show the two cases of orbitaltransfer mission supposed in this study, altitudechange mission and orbital inclination change
mission, respectively.
This study investigates the followings.
1. Required power and number of the laser
station.
2. Orbital transfer capability and applicablesatellite scale.

Fig. 3 Mission concept
Fig. 1 Increase in number of microsatellites [1]Fig. 2 Piggyback satellites inside rocket fairing[2]

Fig. 4 Altitude change mission

1694. Results

Figure 6 Shows relationship between thenumber of laser stations and duration for thealtitude change mission. The number of the laser
station is assumed to be proportional to the laser
power. In this case, considering changing fromaltitude of 400 [km] to 800 [km], altitude changes
are made only by Hofmann transfer. Altitude oflaser station are arranged at regular intervals.
Laser power is the minimum value that gives thenecessary ΔV. The total mass of the laser station
decreases with the number of them. However, it
slow down at the number of station of about 7.
Figure 7 shows relationship between Cm and fuelconsumption in the case of Fig. 5. The change in
the inclination angle is 30 [deg]. It shows that themission could be completed with a reasonable Cm
and fuel consumption.

Fig. 5 Orbital inclination change mission

3. Modeling of Laser Propulsion
The orbital transfer by the laser propulsion is
calculated using the equations below.

𝐶 =

(1)

𝐼

(2)

∙𝐶 = ∙η

ΔV = g ∙ 𝐼
∆V =

∙ ln

∙ ∆𝑡

(3)

Fig. 6 Number of stations vs. mass of total laser
stations and mission period(4)

Cm [N/MW]: Momentum coupling coefficient.
f[N]: Thrust.
Plaser[W]: Incident laser optical power.
Isp[s]: Specific Impulse.
g[m/s2]: standard acceleration of gravity.
ηAB

Δt
m

: Ablation efficiency.
[s]: Irradiation time.
[kg]: Satellite mass

Fig. 7 Cm vs. period and fuel consumption

The most important parameter for laser
propulsion is the momentum coupling coefficient
Cm. In principle, Al powder and POM powders canbe mixed in proportions to obtain Cm values
desired in the range 30 < Cm < 770 [N/MW]. ηAB isthe energetic efficiency of the ablation process,ordinarily 50 [%]. Table 1 shows the nominal
parameter setting. The laser power is a control
parameter.

5. Conclusion

This study shows the capability of the laser
propulsion for the microsatellite. The laser
pointing accuracy would be the most difficult point
to realize a practical space-based laser propulsion.

References[1]”Nanosatellite & Cubesat Database| Missions, constellations, companies,
technologies, and more”.
https://www.nanosats.eu/#info (acessed 2019-0228)

Table 1 Nominal Parameter setting

Cm [N/MW]ηAB [%]
Initial mass [kg]Initial altitude [km]Irradiation time [sec]

100
50
100
400
500

[2]”STP-1-eoPortal Directory-Satellite Missions”
https://earth.esa.int/web/eoportal/satellitemissions/s/stp-1 (acessed 2019-02-28)

170

全球情報を用いた都市幾何形状情報作成手法の提案
ID : 13B09805

Name : 富沢哲郎

Supervisor : 神田学, Alvin C. G. Varquez

1. 序論
近年、発展途上国を中心に人口増加に伴う都市全球整備可能な高解像度都市幾何形状情報(個化が急速に進んでおり、人口 1000 万人以上のメ

別建物高さ情報、平均建物高さHave 、最高建物高

ガシティの 34 都市のうち 28 都市が発展途上国圏

さHmax )作成を試みた。

に集中している。そのような急速な都市化に伴い、① 地図情報から得た建物占有面積情報

大気汚染や熱中症といったような、人体を害するOpen Street Map (OSM) からダウンロードし数々の気象的な問題が生じていることがた建物占有面積情報

Grimmond S. (2007)により報告されている。その② ステレオマッチングにより得た数値表層モ

ような問題の対策のためにも、ウェザーモデルをデル(DSM)

用いて都市の気象シミュレーションを行う必要

商用の 50cm 解像度衛星ステレオ画像、NASA

性は都市に関わらず高まっていると考えることにより無償で提供されるステレオマッチンができる。

グツールである The Ames Stereo Pipeline

都市の気象シミュレーションに都市幾何形状(ASP) を用いて DSM を作成した。

を考慮することは、WRF に代表されるメソスケー③ 汎用衛星情報である数値標高モデル(DEM)

ルモデルや LES に代表されるマイクロスケールモ

ALOS World 3D-30m (AW3D30) 及び Global

デルのどちらにおいても重要である。例えば、居Multi-resolution Terrain Elevation Data

石ら(2018)は、LES を用いて 2m の高解像度で都市2010 (GMTED2010) を用いた。

街区の 3 次元的な空間構造を考慮した気象場の解

まず、DSM と地図情報から得た建物占有面析を行い、その数値解析の結果は観測で得られた積情報から、25ｍバッファーポリゴンを作成

値とおおよそ分布が一致していることを報告ししバッファーポリゴン内の DSM の最小ピクセている。しかし、建物情報を得るためのコストのル値Hminimum を ArcGIS のゾーン統計ツール高さから、都市幾何形状情報は一部の先進国の大を用いて算出し、その値を建物が設置する地

都市に限られている。

形の DTM と推定した。また、同様に建物占有

本研究の目的は、全球配備された情報を用いた

面積情報ポリゴン内の DSM の平均ピクセル値

低コストでの高解像度都市幾何形状情報推定のHaverageを計算し、平均ピクセル値Haverageかための手法の確立である。都市気象学の技術をグら最小ピクセル値Hminimum を差分すること

ローバルに展開するために、グローバルに入手可

で建物占有面積ポリゴン毎の建物高さ情報

能な情報を用いて、価格や手間の観点で低コスト

Hbld を算出した。

であることを目指した。また同時に、メソスケー

しかし、本研究で作成した DSM には、高層

ル、マイクロスケールのどちらの研究にも対応で建物であると、左右画像間の視差が大きすぎ

きるよう高解像度であることにも重きを置いた。

ることや、太陽光線によるハレーションによまた、上記の手法に基づいて、人口 1000 万人以る影響が大きく、標高データを算出できない上の世界 30 メガシティの25km2の領域における、都市の幾何パラメータを算出することも目的と問題が生じた。
上記の問題を打開するため、DSM が計算さした。

れない建物においては、汎用衛星情報である

2. 手法

数値標高モデル(DEM)を用いて建物高さの推本研究では以下に示すいずれもグローバルに定を行った。具体的には、DSM である AW3D30

入手可能な 3 種類の情報を組み合わせることで、から、地物の影響が良く排除されている

171

参考文献

GMTEDmin を差分することで建物高さの推定[1] S. Grimmond: Urbanization and Globalを行った。
以上をまとめた、本研究で提案する手法のEnvironmental

フローチャートを図 1 に示す。

Change:Local

EffectsofUrban Warming (2007)

3. 結果と考察[2] A. Manuel et al: Generation and Quality

東京とジャカルタの研究対象地域にて、前Assessment of Stereo-Extracted DSM From

述の手法により得られた個別建物高さ情報に

GeoEye-1 and WorldView-2 Imagery (2014)

関して、商用の個別建物高さ情報との比較及[3] A. Abdalla et al: Comparison of Matching

び検証を行った。

Algorithms for DSM Generation in Urban

図 2,3 に得られた散布図を示す。いずれのAreas from Ikonos Imagery (2010)

結果からも本研究で提案した手法では、強い[4]居石ら: 全球・都市の将来シナリオを考慮し相関があるが、建物高さを過小評価している

た都市街区の温熱環境予測 (2018)

ことが分かった。DSM を作成する際に、ステレ
オマッチングでは建物による急激な高度変化に対応できず、地形標高データを高く見積もってしまう Smooth effect のためであると考
えられる。
4. 結論
商用 50cm 高解像度ステレオ衛星画像と無償のステレオマッチングツールによるステレ
オマッチングで作成した DSM 及び、汎用衛星

図 1 提案する手法の全体像

情報から得られる DEM や無償公開されている
建物占有面積情報、いずれもグローバルに入手可能なデータを用いて高解像度な都市幾何
形状情報を低コストで作成することができた。
提案した手法を基に、メソスケールの気象シミュレーションだけでなく、LES に代表されるようなマイクロスケールの都市気象シミュ
レーションに最新の都市の幾何形状を含んだ研究が可能になることが期待出来る。
個別建物高さ情報に関しては、領域ベース
法以外のマッチングアルゴリズムを試みるこ

図 2 個別建物高さの比較とで DSM 向上を図り、個別建物高さ情報の更なる精度向上が期待される。
建物占有面積情報に関しては OSM のみを使用した場合、都市によってデータ量の差が出てしまうため、Google Map のような他の地図情報の使用や、衛星画像から画像分類で算出
により更なる向上が期待される。
図 3 平均建物高さの比較

172

A study on separation of Lithium and Cobalt from mixture solution
Student Number : 15_00153

Name : Daisuke AKAZAWA

Supervisor : Hirofumi HINODE, Winarto KURNIAWAN
done by stirring 20 mL of the solution and zeolite-A in

1. IntroductionofErlenmeyer flasks for 3 hours in 25℃ of water bath. The

rechargeable batteries and are used in mobile devices andzeolite was then filtered and the concentration of Co andelectric or hybrid cars. The cathode of this battery contains

Li were measured using ICP-AES.

Lithium-ion

batteries

are

the

major

type

cobalt (Co) and lithium (Li). Cobalt is a kind of rare metals

The zeolite-A used in this research contains Na+ ions.

because only few countries have the resources. Moreover,

Zeolite-A was pretreated to replace Na+ with NH4+ and H+

lithium is valuable metal because future rechargeable

ions which are reportedly easier to separate from thebattery will also use lithium. Both elements are predicted

solution after ion-exchange.

to have a shortage in 4-6 years. Currently some companies

2.3 NH4+ exchanged Zeolite Ion-Exchange test

recycle cobalt and lithium by organophosphorus solvent

NH4+ exchanged zeolite was prepared by mixing 1.0 g

extraction. Around 80% of cobalt is recycled, however,of zeolite-A and 2.0 g of ammonium sulfate in 40 mL ofrecycling lithium is not feasible because the system isdeionized water in Erlenmeyer flask for 3 hours. The

complex and expensive .

process is repeated 3 times. Then, the ion-exchange

1)

Other simple recovery methods such as adsorption andexperiment similar to zeolite-A was done.

chemical precipitation were reported. Researchers tried to

2.4 H+ exchanged Zeolite Adsorption test

separate cobalt and lithium using natural zeolites, however

H+ exchanged zeolite was prepared by heating NH4+

both metals were not adsorbed 2). Though the use of

exchanged zeolite at 350℃ for 120 mins. Then, the ion-synthetic zeolites (zeolite-A) in cobalt and lithium recovery

exchange experiment similar to zeolite-A was done.

has not been reported, zeolite-A, which has higher cation

2.5 Precipitate Recovery Test

exchange capacity can be promising. Research has been

The mixture solution of Co2+ (1000 ppm) and Li+

done utilizing sodium hydroxide to precipitate cobalt, and(1000 ppm) were made by dissolving their respective

then remaining solution was passed through an ion-sulfates salts. Then, as shown in Fig.1, about 200 mg of

exchange resin to separate lithium and sodium 3). They

potassium hydroxide pellets were added into 40 mL of the

could recover 99% of cobalt, but they had to concentrate

mixture solution, stirred, followed by filtration. The

lithium to recover it.

precipitate was recovered, dried, and analyzed using XRD.

The research objective of this study is to develop theThen after which, the precipitate was dissolved in nitric

low-cost recycle methods by using synthetic zeolite oracid and hydrogen peroxide and the analyzed using ICP-

precipitation. Potassium hydroxide (KOH) and potassium

AES.

periodate (KIO4) were used to precipitate Co and Li,

For other set of experiment, 0.288 M of KIO4 solution in

respectively.

20% KOH was prepared. The filtrate and KIO4 solution

2. Experimental

were mixed at 2:5 volume ratio, heating it in the oven at
90℃ for 30 mins. Then, the solution was filtered by Teflon

2.1 Zeolite-A Elemental Analysis

membrane filter. The precipitate was dissolved in nitric

Determination of the elements contained initially inacid and hydrogen peroxide, then analyzed using ICP-AES.

zeolite-A was done by X-ray Fluorescence (XRF). To

Co2+ & Li+ mixture solution 40 mL

measure lithium content in zeolite-A, 50 mg of zeolite-A
and 1.5 g of ammonium sulfate were mixed in 20 mL of

KOH pellets 200 mg (approximate)deionized water for 3 hours, followed by filtration. Lithium
Filter Li+ & K+

content was determined from the filtrate analyzed using
Inductively

CoupledPlasma-AtomicPrecipitate Co

KIO4 0.288M in 20% KOH solution 100 mL

Emissionin oven at 90℃ for 30 mins

Spectrometry (ICP-AES).
2.2 Zeolite-A Ion-Exchange Test

Filter K

Preparation of the mixture solutions of Co2+(100 ppm),
Li+(100 ppm) and NH4+(0/50/100 ppm) were done by+

Precipitate Li

Fig.1 The process of the precipitation test

solving their respective sulfates salts. Ion-exchange test was

173

(Co(OH)2). Table 2 shows the mass ratio of the cations in

3. Result and Discussion
Fig. 2 shows the mass ratio of lithium and cobalt

the precipitation by KOH. The precipitation have highadsorbed to zeolite-A, and Fig.3 shows NH4+ exchanged

purity, which means that cobalt was successfully recovered.
Table 2 also shows the mass ratio of the cations in thezeolite and H+ exchanged zeolite.

precipitation

According to the elemental analysis, zeolite-A has Na

+

by

KIO4.

Althoughlithiumcanbeas exchangeable cation. Fig.2 shows almost all Co2+

concentrated, the precipitation still has much amount ofadsorbed by zeolite-A, while less than 20% of Li+ adsorbed.

potassium. Further research on method to minimize

Addition of NH4+ into the solution resulted in lower

potassium content is still needed.

separation performance. From this result, it can beconcluded that zeolite-A can separate cobalt and lithium,
however Na+ are released to the solution. Na+ is difficult toseparate from Li+, so NH4+ and H+ exchanged zeolites wereused because they have easily separable cations.
However, as Fig.3 shows, NH4+ exchanged zeolite hasless selectivity and H+ exchanged zeolite has low capacity
for both Co2+ and Li+. NH4+ exchanged zeolite may have a100%

adsorbed

Mass ratio ofpotential to separate without releasing interrupting ions.
02-1094> Co(OH)2 –Cobalt Hydroxide (Main ingredients)

Fig.4 The XRD result of precipitation by KOH.

50%
Li

Table 2 The mass ratio of the cations in precipitation

Co

0%
0ppm

NH4+ Concentration
Fig.2 Zeolite-A adsorption testCoK

By KOH

<1%

>99%

<1%

By KIO4

16%

<1%

84%

4. Conclusion
Zeolite-A was able to separate cobalt and lithium from100%

adsorbed

Mass ratio ofLi

50ppm 100ppm

a simulated mixture solution, but it releases Na+, which is
hard to separate. NH4+ exchanged zeolite has less

50%
0%
NH4+

H+

exchanged

exchangedLiselectivity, but it may have the potential to separate cobalt

Coand lithium without releasing interrupting cations. H+
exchanged zeolite has low capacity so it cannot be used forrecycling cobalt and lithium.
KOH precipitation method can recover almost 100%

Fig.3 NH4+ and H+ exchanged zeoliteof cobalt in the form of cobalt hydroxide. In KIO4
precipitation method, we can recover 88% of lithium,

Table 1 shows the recovery ratio by precipitation

however the precipitation contains high amount ofmethods. Almost all of cobalt and 88% of lithium werepotassium. To obtain pure lithium precipitation, further

recovered. This recovery rate is enough for recycling.

research is needed.

References

Table 1 Recovery ratio by precipitation method

1)JOGMEC, ‘EV 電池および電池材料（Ni, Co, Li）の市場動向‘,

Li

Co

Precipitated by KOH

0%

99%

Precipitated by KIO4

88%

<1%

Wirawan・Hirofumi Hinode, ‘The Development of Lithium Ion

Loss

12%

<1%

Recovery Method by Activated Carbon and Natural Zeolite-based

2019, http://mric.jogmec.go.jp/reports/current/20190604/113521/
2)Chandra Wahyu Purnomo・Endhy Kesuma・Sang Kompiang

Adsorbent’, 20173) 吉塚 和治・西浜 章平, ‘有価廃棄物からのレアメタルの統合

Fig.4 shows the XRD result of precipitation by KOH.

的抽出分離回収システムの開発‘, 2012

The peaks show that the precipitate is cobalt hydroxide174サプライチェーンを考慮した東京都市圏物流施設の年類型別立地分析
Transition of logistics facilities’ location choices considering supply chain in Tokyo Metropolitan Area
学籍番号: 15_00756 名前: 衣然 指導教員: 花岡伸也
１．背景と目的
東京都市圏は、東京都区部を中心とする都市圏であり、世界最大の人口と経済規模を持っている。一般に交通調査において定義される東京都市圏に含まれる１都６県（茨城県、栃木県、群馬県、埼玉県、千葉県、神奈川県、東京都）
は、面積は全国の 8.6%に過ぎないが、人口は 33%、実質県内総生産と実質最終消費支出は全国の約 38%を占める
1)。このような圏域において、産業・経済や人々の暮らしと密接に関係がある物流を把握することが重要である。また、一般的に中流施設は短期的に立地が変化するため立地誘導施策の影響を受けにくい一方で、特に工場等の上流施設は、歴史的な経緯で立地している等、物流効率や用地確
保以外の要因で立地している可能性がある。施設の創設年で分けて立地選択分析を行うことも重要である。
近年、物資流動調査などの集計データで物流施設の立地問題をモデル化することで、物流施設の立地傾向を分析し、立地促進政策に示唆を与える研究が多数存在する 2)3)4)。さらに東京都市圏を対象には物流施設をサプライチェーン
上の位置で分類した研究 5)や、物流施設の立地選好とサプ
ライチェーン上の位置との関係を分析し、実際に上流・中流・下流で分類した施設によって立地が異なることを示した研究 4)もあるが、施設創設年で分けた分析は行われていない。
。
本研究では、第五回東京都市圏物資流動調査のデータを用いて、サプライチェーン上の位置によって分類した物流施設を年類型別で再分類し、立地選択モデルを構築する。
さらに、構築したモデルの推定結果を用いて年類型別に物流に関連する施設の立地選好とサプライチェーン上の位置との関係を解明することを目的とする。
２．研究手法中道ら 4)は、第 5 回東京都市圏物資流動調査から物資流
動 origin-destination（以下 OD）の搬出先あるいは搬入元の情報を用いて搬出搬入票の中で「店舗」、「飲食店・宿泊・
娯楽施設」、「住宅・文教施設等」、「工事現場」を最終消費者と定義し、「倉庫」、「集配送センター・荷捌き場」、「トラックターミナル」、「その他の輸送中継施設」、「物流施設（詳細不明）」を物流施設と定義し、「工場」を工場と定義し、「事務所施設」を事務所と定義した。主な搬出先が最終消費者である施設を下流施設と定義し、ほかに工場及び主な搬出先が工場である施設を上流施設と定義し、ほかに主に物流施設に配送している施設を中流施設と定義し、主に事務所に配送している施設をサプライチェーン分類と立地研究の対象外にした。
選択肢であるメッシュの効用は式(1)に表す
𝑉𝑖,𝑗 = ∑𝑘 𝛽𝑘 𝐿𝑖,𝑘(1)𝑟𝑒𝑥𝑝(𝑣𝑗 +𝑙𝑛 𝑀𝑖 )𝑃𝑖𝑟 = ∑

𝑟𝑗 𝑒𝑥𝑝(𝑣𝑗 +𝑙𝑛 𝑀𝑗 )𝑒𝑥𝑝(𝑉𝑖𝑟 )=∑𝑟𝑗 𝑒𝑥𝑝(𝑉𝑗 )(2)

𝑉𝑖,𝑗 :施設 j に対するゾーン𝑖の観測可能な効用
𝑃𝑖𝑟 : セグメント r の物流施設がゾーン（3 次メッシュ）iを選択する確率𝑣̅𝑗 𝑟 ：ゾーン i 内の立地可能な敷地ロットの平均効用とそのばらつきを表す効用関数（確定項）
𝑉𝑖𝑟 ：ゾーン i の効用関数
以上によって、式 5 のロジットモデルの効用関数は、以下のように定式化される。
𝑉𝑖𝑟 = ∑𝑘 𝛽𝑘𝑟 𝑥𝑘𝑖 + 𝑙𝑛𝑆𝑖
(式 3)
𝑥𝑘𝑖 ：ゾーン i 内の敷地の平均的な立地効用を表す k 番目の変数（立地要因変数）
𝛽𝑘𝑟 ：パラメータ
このモデルのパラメータ推定においては、規模変数の項
𝑙𝑛𝑆𝑖 の係数を 1 に固定し、𝛽𝑘𝑟 を通常のロジットモデルと同様に推定している。本研究では、第 5 回東京都市圏物資流動調査の調査範囲である茨城県南部中部、栃木県南部、群馬県南部、千葉県、神奈川県、東京都の１都６県の中で可住地面積０以上の三次メッシュを研究範囲とする。三次
メッシュ数は合計 19844 個である。
中道ら 4)は推定ソフトウェア(R)の能力、及び作業効率を175

考慮し、物流施設の立地している区画とそれ以外のメッシ
ュを無作為に 199 区画を抽出し、合計 200 区画の要素を有する部分選択肢集合を抽出し、選択肢としたが、兵藤・坂井・河村(2015)6)によると、メッシュ総数 17961 のモデルであったが、R のマトリックス計算機を用いることで、全選択肢を扱っても標準的な PC で、十数秒で問題なくパラメータ推定が行えたということのため、本研究では全メッシ
ュ(19844 個)をモデルの選択肢としてモデルの構築を試みる。本研究では、中道ら 4)で採用していた説明変数を参考に選定を行った。本研究は、全メッシュを選択肢とし、サンプルごと配送先重心を計算するには計算量が膨大になるため、意思決定者の配送先重心への距離を除き、それ以外を説明変数とした。
３．結果と考察
年類型の定義について、15 年ずつ等間隔で分類することにしたが、空港、港のような数十年前から位置変更がほぼない変数以外の統計データについて、例えば人口データの場合、公表されている人口のメッシュ統計は 1970 年からであり、さらに前の年代は 1970 年の人口を使用せざるを得ない。一方、新しく立地した物流施設の分析はより重要となり、さらに、1985 年以降は日本の景気循環 7)を考慮する必要がある。そのため 1985 年以降の年類型は 10 年間隔とした。
表１．年類型とサプライチェーン分類別の物流施設サンプル数

1955 年以前の施設から 2005 年以降の施設までモデルを立ち上げ、パラメータ推定を行った。表 2 と表 3 は物流施
設のパラメータ推定結果の一部である。本研究は中道ら 4)と同じように、R 言語の GLM 関数を使用し分析を行った。
主に参考するパラメータは、推定値、p 値、AUC、尤度比である。0.05 以上の p 値を持つ変数に帰無仮説を採択し、物流施設の立地選択に無相関と判断する。
各変数の物流施設に対する相関性は以下の通りである。
・人口：1970 年から 1995 年までの上流施設に対し少ないほど立地しやすく、1955 年以前の上流施設と下流施設に対し多いほど立地しやすい 1995 年以降ほぼ立地に影響はない。
・通勤圏内労働人口：1970 年以降の上流施設と 1995 年
以降の中流施設と 1970 年から 1995 年までの下流施設に対し多いほど立地しやすく、1955 年以前の上流施設と下流施設に少ないほど立地しやすい。
・素材系業界への接近性：すべての上流施設に対し立地選択要素の一つである。素材系業界の付近に上流施設を立地誘導すべきである。
・加工組立関連への接近性：1995 年以前の上流施設に立地選択要素の一つである。1985 年から 1995 年までの中流施設に対し離れて立地する傾向がある。
・生活関連業界への接近性：1970 年から 1985 年までの上流施設と 1995 年から 2005 年までの中流施設に対し立地選択要素の一つである。
・全製造業への接近性：1970 年前と 1985 年から 2005 年までの上流施設と 1985 年から 1995 年までの中流施設
に対し正の相関を持つ。加工組立関連、生活関連業
界、全製造業はそれぞれ物流施設に重要視とされる時期があったが 2005 年以降はほぼ有意性を持たない。
・卸売業市場への接近性：1970 年以降の下流施設と 1955
年後の中流施設に対し正の相関を持つ。下流や中流施設は最終消費者を主な搬出先とするためと考える。
・業務地接近性：すべての施設に対し接近するほど立地しやすい。
・最寄 IC への距離：1995 年から 2005 年までの上流施設と 1955 年から 1970 年までと 1995 年以降の中流施設に対し近いほど立地しやすい。

過去の傾向を参考し立地誘導することが難しいと考える。また、“遠いほど立地しやすい”という結果はあるが、実際わざと港湾や空港に離れる場所に立地する理由は考えられないので、ほかの要素に影響されていると考えられる。
・住宅地域割合：1955 年から 2005 年の上流施設と 1985年から 1995 年までの下流施設に対し割合が低いほど立地しやすい。物流施設は住宅地域と離れて立地してきたが、近年、こういう傾向がなくなっている。
・商業地域割合：1955 年以降の上流施設と 1970 年から
2005 年までの中流施設に対し割合が低いほど立地しやすい。
・準工業地域割合：2005 年以降と 1970 年前の上流施設とすべての中流施設と 2005 年以降と 1955 年以前の下流施設に割合が高いほど立地しやすい。
・工業地域割合：1995 年以降と 1985 年以前の上流施設と 1970 年から 1995 年までの中流施設と 2005 年以降と1955 年から 1985 年までの下流施設に対し割合が高いほど立地しやすい。
・工業専用地域割合：1995 年以降と 1985 年以前の上流
施設と 1985 年から 1995 年までの中流施設と 2005 年後と 1970 から 1985 年までの下流施設に対し割合が高いほど立地しやすい。用途地域は物流施設の立地選択にとって重要な参考である。
・地価：2005 年以降の下流施設に対し高いほど立地しやすく、2005 年以降と 1970 年から 1985 年までの上流施設に対し安いほど立地しやすい。工場などの上流施設
は利益を上げるために、地価の安いところに立地するのに対し、下流施設は地価が高いが最終消費者が多い場所に立地すると考えられる。
・臨海部ダミー：1985 年から 1995 年までの中流施設と1955 年前の下流施設に対し臨海部に傾向がある。
・郊外部ダミー：2005 年以降と 1985 年から 1995 年までの上流施設と 1985 年から 1995 年までの中流施設と1970 年から 1995 年までと 1955 年以前の下流施設に対し郊外部に立地する傾向がある。
・工業団地ダミー：1955 年以降の上流施設と 1995 年以降と 1955 年から 1985 年までの中流施設と 1970 年以降の下流施設に対し工業団地に立地する傾向がある。
4．結論
推定結果から、以下の結論が得られた。
(1) 工業団地や用途地域との相関性は年類型別に異なる傾向を示し、最近の施設は、すべての施設に対し有意性を持つため、立地誘導の時重点的に考慮する必要がある。
(2) 上流施設と下流施設の立地誘導に、地価を考慮する必要がある。
(3) 同じサプライチェーンの位置の施設でも各業種への近接性は年類型によって異なる傾向を示すことから、現時代の需要に適応する施策が必要となる。
(4) 最近の中流施設は空港の近くに立地する傾向がある
ことから、中流施設の立地誘導政策に空港を考慮する必要がある。
本研究は、グループ数が過多にならないように物流施設
を FF 施設、FL 施設 4)のような搬入搬出先で分類していない。今の段階ではまだ工場、多機能事務所など具体的な施設種類に立地に言及することができない。今後の課題としては、物流施設を搬入搬出先で分類し、正確に当時の施設の特徴を表す適切な年類型別で立地選択分析をする必
要がある。
参考文献

表２．施設創設年が 2005 年以降の施設の推定結果

表 3．施設創設年が 1985 年から 2005 年までの施設の推定結果

・最寄空港への距離：1955 年から 1985 年までの中流施設と 1955 年から 1970 年までの下流施設に対し遠いほど立地しやすく、1995 年以降の中流施設に対し近いほど立地しやすい。
・最寄港湾（東京と神奈川湾）への距離：1995 年から2005 年までの上流施設に対し遠いほど立地しやすく、
1955 年から 2005 年までの中流施設と 1955 年から 1970
年の下流施設に対し近いほど立地しやすい。
・最寄港湾（千葉湾）への距離：1995 年から 2005 年ま
での上流施設と 1985 年から 2005 年までの下流施設に遠いほど立地しやすい。
・最寄港湾(ひたちなか湾)への距離：1995 年から 2005
年までの中流施設に対し遠いほど立地しやすく、1985
年から 1995 年までの下流施設に対し近いほど立地しやすい。
・道路延長：1970 年から 1995 年までの上流施設と 2005
年後の下流施設に長いほど立地しやすい。交通系の変数の各年類型の推定結果は一致しないものが多数で、

1)
2)
3)
4)
5)

6)

7)

176

東京都市圏交通計画協議会：東京都市圏の望ましい物流の実現に向けて, 2015.
萩野保克・遠藤弘太郎(2007)：立地選択モデルを用いた東京都市圏における物流施設の立地ポテンシャル分析」，土木計画学研究・論文集，No.24pp.103-110.
篠原丈実，福田大輔，兵藤哲朗：Spatial Sample-Selection Model を用いた物流施設の立地先・立地量の同時決定行動の分析，土木計画学研究・講演集, Paper No. 7311.
中道久美子・川崎智也・花岡伸也・呂田子：サプライチェーンを考慮した東京都市圏
物流施設の立地分析, 土木計画学研究・講演集, Vol.57, 2018.
中道久美子・川崎智也・花岡伸也・渡邊雄太郎：東京都市圏におけるサプライチェーンの観点からの物流施設分類とその品目別分析, 土木学会論文集 D3, Vol.74, No.5,
pp.1005-1018, 2018.
兵藤哲朗・坂井孝典・河村和哉：東京都市圏物資流動調査による空間相関を考慮した物流施設立地選択モデルの検討, 土木学会論文集 D3, Vol.71, No.4, pp156-167, 2015.
内閣府：景気基準日付.

都市近郊における農業の特徴の二時点比較：千葉県を事例として
学籍番号：15_02494

遠藤奈美

1.

背景・目的
近年の日本が抱える少子高齢化や人口の都市集中による農村地域の空洞化などの影響から、農村地域
において人手不足が叫ばれていることは周知の事実である。事実、農林水産省の農業構造動体調査（[１]）によると日本の総農業経営体数、農業従事者数はともに年々減少し続けている。
一方で、農業の組織経営体数は年々増え続けており、また最近では都市内やその近郊における農業の役割や重要性について注目が集まっている。
本研究の目的は、これらの新しい話題に注目しな
がら、最新のデータの分析結果および既存研究を用いて、二時点での地域の状況を比較する事により近代農業の流れを明らかにする事である。
研究対象地域とした千葉県は、東京に隣接した都
市的地域、都市から離れた農村地域など様々なタイ
プの農業があり、農家個数は年々減少しているものの産出額はキープされており、各々の地域での近代農業事情に合った変化を観測することができる。
2.
関連情報と既存研究
2-1. 都市近郊農業
都市農業は都市化地域とその近郊で行われている
農業のことであり、兼ねてから循環型社会におけるその働きは注目されてきた。近年は、その立地の良さを生かした販売方法、地産地消が注目されている。
図２は農林水産省の 2011 年、2001 年の東京都における農産物の販売ルートである。10 年間で農協経由
でない市場外流通の割合が大幅に増えている事がわ
かり、農家の販売ルートとしての農協依存度が減少していることを表している。このような変化に伴い、自己販売経路を確立している都市農家では野菜を中心とした作物の多様化が進んでいる。

図１、東京都農業の販売経路（[２]）
2-2. 農村地域の構造変化
農村地域における高齢化や後継者不足などによる空洞化から、作業委託や借地経営が増えている。こ

うした状況に対処するため、各都道府県に設置された農地中間管理機構に依る農地の集積転売は同機構発足時の 2014 年からわずか 3 年で 7.7 倍にもなっている。具体的事例として、かつて集落が盛んだった新潟県上越市三和区での大規模借地経営への移り
変わりについて細山（2011）は言及している（[３]）。

2000
1500
1000
500
0
2014

2015

2016

2017

図２. 農地集積機構の実績(100 万 ha)
3.

研究手法、データ研究手法ならびにデータは比較対象の既存研究（[４]）を参考に、データは農林水産省の統計データである農林業センサスの 2015 年のものを用いた。
また、分析対象とした区分は、千葉県の昭和 25 年
当時の市区町村区分に従った 341 旧市区町村とした。
具体的な分析方法は、第一に、同県内の各地域の農業の特性を表す 15 の変数（表 1）を用いた主成分分析を行い、その後に主成分スコアを用いたクラス
ター分析を行い類型化した。その上で、各知育区分
における農業形態の変化の有無を、既存研究の成果と照らし合わし、地図上の比較検討を行なった。
表１. 分析に用いた変数
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

177

指導教員：阿部直也

本業農家（65 歳未満農業専業、主業農家）戸数
総経営耕地面積
本業農家率
同居後継者いる農家率
１戸あたり経営耕地面積
経営耕地面積 3ha 以上農家率
経営耕地面積 3ha 以上農地シェア
販売金額 1,000 万円以上農家率
60 歳未満農業就業人口率
雇用（常雇用、臨時雇用）農家率
販売金額 1 位が稲作の農家率
販売金額 1 位が野菜の農家率
販売金額 1 位が畜産の農家率
水田流動化係数（借地、全作業委託、収穫委託の割
合）
水田率

4.

分析結果と考察成したマップとも照らし合わせながら比較した。特徴的だったのは、都市的地域を中心とした小規模野菜特化農業以外のほぼ全ての地域で農地の集約が見られたこと、また野菜特化度の上昇した都市的地域、および農地集積の流れが見られた農業最活性化地域
における 1,000 万円以上販売農家率の増加である。
概ね同様の地域を含んでいたグループ１、２に関しては、どちらも停滞地域ではあるが、農地集積が進んでいるデータが得られた。ただ、変化の大きさには差が見られ、グループ２の方が大きかった。
グループ５からグループ６に移った地域に関して
は、野菜特化度合いが大きく増加し、都市農業的傾
向通りの変化を遂げていることが確認された。

クラスター分析で類型化された各地域区分(341 区分)のグループについて 2005 年と 2015 年の２時点
間の比較をした結果、各グループの変数に対する値の平均値がそれぞれ大きく異なり、それぞれのグループに農業的特徴が見られた。

5.
結論、今後の課題
5-1. 結論
本研究の目的であった「農地集積、法人化、都市農業などによる近代農業の変化の流れを明らかにする」という事に対しては、農業活性化地域地域での農地集積やその規模増加に伴う販売金額 1,000 万円
以上農業経営体率の増加、また都市的地域での野菜特化傾向（都市農業に適した作物）及び販売金額
1,000 万円以上農家率の増加から農地集積や大規模経営化、都市的地域における都市農業的特徴を持った農業経営体の増加を観測し、街頭地域における近代農業の流れを明らかにした。一方で、後継者不足、や平均年齢の増加にも関わらず近代農業的変化の見られない農業停滞地域があることも明らかにした。

図２. 既存研究による色分け（文献[５]70 頁より抜粋）

5-2. 今後の課題
今回の比較研究では、２時点間データをそれぞれのグループごとに比較したので、千葉県における農業の地域特性および変化の大まかな流れを把握することはできたが、一つ一つの市区町村を対応させて逐次比較をすることはできず、各グループに含まれる地区町村が異なる事による誤差が生じることは避けられなかった。そこで、さらなる研究としては土地を対応させた平均値を含めた考察が挙げられる。

＜参考文献＞[１]農林水産省、農業構造動体調査、令和元年 6/28
公表
http://www.maff.go.jp/j/tokei/kouhyou/noukou/ind
ex.html[２]農林水産省「都市農業をめぐる情勢について」、
平成 28 年 10 月
http://www.maff.go.jp/j/nousin/kouryu/tosi_nougy
o/attach/pdf/t_gaiyo-2.pdf[３] 細山隆夫、「大区画圃場地域における大規模借地経営の存立状況と農地団地化」、農業経営研究第 3号、2011[４] 溝田俊之、農山村地域の農業構造分析と施策への提言、平成 20 年度地域活性化のための農業集落
データ分析委託事業報告書、65 頁、2009
http://www.aafs.or.jp/sogo/h20_itaku.pdf

図３. 本研究による色分け

既存研究との対応を図る為、主成分 1 が表す 65歳未満就業者立や販売金額 1000 万以上などの農業活性化度に応じてグループ１から７までを昇順に並べたところ、グループ１、２は概ね合致していたが、グループ５の一部がグループ６になるなどの変化も見られた。
各グループにおける各変数の平均値を算出し、作178

Comparative analysis of network transportation costs
for truck platooning and existing driving(トラック隊列走行と単独走行のネットワーク輸送費用の比較分析)
Name : Hyunsoo LEE Academic advisor : Shinya HANAOKA, Tomoya KASAWAKI

Student ID : 13B00715

1. Introduction

transportation distance [km], α:average of fuelsavings, dab:transportation distance in platoon [km],p:unit price of fuel [yen/ℓ], c:fuel consumption per
km [ℓ/km], uh:usage fee for highway per unit
[yen/unit], ci:insurance money [yen], ct:tax [yen],
cm:vehicle maintenance cost [yen], cx:consumable
goods [yen].

Truck transportation plays a key role in Japan'slogistics transportation because it accounts forabout 90% on a ton basis [1]. However, the shortageof drivers and soaring fuel costs has become serious
recently [2]. And, truck platooning is one means forsolving the problem because it is effective in
reducing fuel consumption and labor costs [3]. However,many studies on it have so far focused on the effects
of introduction and there are few studies on detailedtransport cost comparative analysis. Therefore, theobjectives of this study are as follows. (1) Compare
and analyze the transportation costs of the virtual
network of existing driving and truck platooning(Analysis 1). Verify with actual highway data
(Analysis 2). Next, truck platooning will be
explained. It means that many trucks form a platoon
and travel while maintaining the distance between
vehicles while sharing the driving situation via
communication [4]. And, platooning operated by only
one driver and no driver in the following trucks iscalled autonomous truck platooning. In case ofexisting driving, transportation is performed
directly between each logistics base. However, incase of truck platooning, trucks form or releaseplatooning at platooning center and move in a platoon
between platooning center.

2-2. Comparative analysis (Analysis 1)
Next, this model will be used to calculate theboundary conditions and write a graph while changing
variables. Fig 1 shows the boundary conditions(difference between Case0 and Case1, Case0 andCase2) in a graph. In this graph, Db means average
distance between logistics bases [km].
tw[h]
Case2

Case1

Db[km]

Fig 1. Boundary conditions
And, the boundary conditions are compared.

2.Analysis
A model based on the virtual network is created.
Next, transportation costs are compared to find out
the boundary conditions and a comparative analysis
is made on the way to operate, number of trucks, andvehicle separation distance. Finally, verification
on an actual highway is performed by adapting themodel.

n=2
tw [h]
4
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2
1.8
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1.3
1.2
1
0.8
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0.5
0.3
0.2
0

2-1. Model
There are three cases like existing driving (Case0),
truck
platooning(Case1),
autonomoustruck
platooning (Case2). The model for the cost is asfollows.

CASE0-CASE1

n=2
tw [h]

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4
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0

1122334455667788991111111
0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 0 1 1 2 2 3 Db
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 5 0 5 0 [km]0000000s=6
tw [h]
4
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1.5
1.3
1.2
1
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0.2
0

Tm:sum of all driver’s driving hours [h],tw,twr:waiting time for matching (forming/releasing
platooning) [h], tf,tr:time for forming/releasing
platooning [h], n:number of trucks, cl:driver’s
labor cost per hour [yen/h], Dm:sum of all truck’s

CASE0-CASE1

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1122334455667788991111111
0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 0 1 1 2 2 3 Db
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 5 0 5 0 [km]0000000s=6
tw [h]

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1122334455667788991111111
0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 0 1 1 2 2 3 Db
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 5 0 5 0 [km]0000000

179

CASE0-CASE2

0

4
3.8
3.7
3.5
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3.2
3
2.8
2.7
2.5
2.3
2.2
2
1.8
1.7
1.5
1.3
1.2
1
0.8
0.7
0.5
0.3
0.2
0

CASE0-CASE2

0

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1122334455667788991111111
0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 0 1 1 2 2 3 Db
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 5 0 5 0 [km]0000000

Fig 2. Comparison of boundary conditions
This is example figure in which the comparison of
the boundary conditions was performed with thenumber of trucks(n) or the vehicle separation
distance fixed. The meaning of each color is on the
top of Fig 2. s means vehicle separation distance.
As a result of fixing n (2,3,4 vehicles) and s(6,12,49m), there are 6 results. For example, in caseof two trucks and 6m of s are presented in Fig 2.

2-3.Verification (Analysis 2)
From now on, actual data will be used to verify
whether platooning is actually effective or not on
actual expressway. This verification is performed
based on the calculation results of Hirata(2019) [5].
This study was based on actual data to determine how
many platoons(maximum) could be formed between Tokyo
and Aomori on the Tohoku Expressway. (Inbound:2043
vehicles, Outbound:1550 vehicles). However, since
the trucks form a platoon on the road while drivingin this data, the calculation was conductedaccording to this study(Gather at the platoon centerto form or release a platoon). The total cost
reduction is calculated from the difference between
the cost of existing driving and truck platooning.
In addition, because this data calculates the
maximum number of trucks that can form platooning,it may include the possibility that the cost will
increase due to platooning. Therefore, verificationis performed in the following two cases. (1) If thetrucks are disadvantage when forming platooning, it
is assumed that they do not form platooning(Verification 1). (2) All trucks that can form
platooning form platooning (Verification 2). The
result of verification 1 means that the profit
obtained by platooning is maximum. At vehicle
separation distance(s) is 6 m, which is vehicle
separation distance based on minimum safety time for
platooning communication, where the profit ismaximum, the result of verification 1 is shown in
Fig 3.

Fig 4. Result of verification 2

3. Conclusion
According to the purpose of the study, theconclusions are as follows. First, under theconditions in the area under each of the graphs in
Fig 1, it is likely that the cost of transportation
becomes lower when truck platooning than existing
driving. Next, Case1 is sensitive to s because thegraph changes drastically due to changes in s (toreduce s is important), Case2 is sensitive to n(toincrease n is important). However, Case2 is much moreadvantageous than Case1. Then, it is considered that
there is a high possibility that the cost oftransportation becomes lower when truck platooning
than existing driving on the Tohoku Expressway
between Tokyo and Aomori. Because, significant total
cost reduction can be obtained when tw is smallenough (especially in Case2, total cost reduction ismore than about 10 times of Case1). In particular,
it is important to focus on adjusting the tw withproper scheduling and introducing autonomous truck
platooning that is quite effective. Finally, Futureissues are explained. As the number of trucks
increases, tw is expected to increase, so reflectthat change. Also, it is considered that there wasa possibility that the accuracy of the calculation
was slightly reduced due to a difference in thecalculation method in the verification (On the roador Platooning center). Therefore, the model isimproved so that it can be calculated even on theroad.

References[1] 全日本トラック協会 (2018)., 日本のトラック輸送産業現状と課題
2018., pp.4.
[2] 国土交通省 (2015)., 物流をめぐる状況～物流の現状及び物流政策の取組状況等～., pp.34.
[3] Watanabe (2019)., ヨーロッパにおける大型貨物車を利用した貨物輸送に関する取組の実態と課題., 2019 年ＩＢＳフェローシップ発表会.
[4] European Automobile Manufacturers' Association (2017)., Whatis truck platooning?.

Fig 3. Result of verification 1
Next, Similarly, at s is 6 m, the result of
verification 2 is shown in Fig 4.

[5] Hirata, Abe (2019)., 都市間物流データを活用したトラック隊列走行の車両マッチングポテンシャルの推計～東北自動車道を対象として～.,
日本物流学会誌., 27., 91-98.

180

Numerical Analysis for Precise Estimation of Wave Pressure and Overtopping
around Coastal Dike
Student Number: 15_13747 Name: Takumi Mizuochi Supervisor: Hiroshi Takagi

1. Introduction

shows that, at shallow water depth, the temporal changes andminimum and maximum pressures are almost similar. However,as the water depth becomes deeper, difference in wave pressure
between the simulated and experimental value increased.
This difference in this results may be associated with energy
loss in the porous body. And another reason for this difference isthat the larger the wave height, the more complicated the flow
turbulence occurs in front of the breakwater. In this study, theanalysis did not use a particular turbulence model, so it may not
be possible to reproduce these complicated flow.

Dike is a part of coastal protection system that are constructedalong coast to protect human lives and assets from storm surges,
tsunamis, and waves. The design standard for coastal structures
requires wave pressures and overtopping flow rate being below
the allowable magnitude during the lifetime of the structure. A
number of estimation formula and diagram have been proposed
to date, which are mostly determined by hydraulic experiments.
However, in recent years, a sophisticated CFD (computational
fluid dynamics) is attracting attention in analyzing wave
pressures and overtopping rate. This study attempts todemonstrate the validity of CFD analysis results for wave
pressure and overtopping flow comparison with experiments.

Numerical analysis

Experiment

0.70

2. Wave Pressure
Pressure(kPa)The author performed the CFD and compared the results withthe previous experimental data (Takagi and Nakajima, 2007),
which measured wave pressures acting on an upright breakwater.
Figure.1 shows the geometry and the breakwater model
considered in this experiment and numerical analysis. In theexperiment the rubble mound was a porous structure, whereas innumerical analysis this part was treated as an impermeable body.
Three different wave conditions (Table.1) were posed from theoffshore inlet boundary. Waves mostly reflected on the dike,while a slight water mass overtopped the crest of the structure.
Wave pressure is measured by three pressure gauges, installed at
depth of 6, 10, 14cm on the front surface of the dike. In bothexperiments and numerical analysis, the input wave height andperiod were first determined under the case without any
structures in order to examine how high wave passes the locationof the breakwater. An open source software OpenFOAM wasused for the computation and a solver called interFoam wasadopted to solve two-phase flow using VOF (Volume of Fluid)
method.

0.20
-0.30

0

1

-0.80

2

3

4

5

Time

Numerical
analysis/ExperimentFig.2 Example of pressure in numerical analysis andexperiment (Case No.1, pressure gauge sets 6cm depth)

2
1.8
1.6
1.4
1.2
1
0.8
6cm
H6T1

10cm
14cm
Depth of Pressure gauges
H8T1

H10T1.4

Fig.3 Comparison between wave pressure in experimentand numerical analysis

4. Flow rate of the Overtopping wave

Fig.1 Geometry of experimental and numerical analysis

A comparison was made between the flow rate derived from theovertopping wave diagram by Goda et al. (1975) as shown in
Figure.4 and that obtained by numerical analysis for the uprightdike. Numerical analysis performed using interFoam. Figure.5
show the geometry of numerical analysis for the wave
overtopping test. The flow rate is estimated by measuring thevolume of the water phase stored in the reservoir behind the dyke.
The wave height and period of incident wave were adjusted in
the condition without the slope and dike, resulting in the values
shown in Table.2. Figure.6 shows the example of change inTable.1 Incident wave
Case No.

Period (s)Height (m)

1

1.0

6.0

2

1.0

8.0

3

1.4

10.0

3. Wave Pressure comparison
Figure.2 shows the example of pressure in experiment andnumerical analysis, and Figure.3 shows comparison between
wave pressure in experiment and numerical analysis. These data181

volume per unit width of liquid phase stored in the reservoir.

overtopping flow was small because the wave broken and thewave height of the reflected wave did not occur.
In case No.4~9, it was confirmed that the overtopping amounttends to decrease as the wave height decreases.
All cases show higher flow rate compare to flow rate
overtopping wave between numerical analysis and diagram(Goda et al., 1975).

Fig.4 The diagram of flow rate of wave overtopping(Goda et al., 1975)

Fig.1 Geometry of experimental and numerical analysis
Fig.7 comparison of overtopping rate between numericalanalysis and diagram in Goda et al., (1975)

Table.2 Input wave and water depth detail
Case No.
Period (s)Wave height (m)Depth h (m)
0

2.92

0.160

0.50

1

2.47

0.114

0.557

2

2.18

0.089

0.589

3

1.97

0.073

0.609

4

1.81

0.062

0.623

5

1.58

0.047

0.641

6

1.50

0.042

0.647

7

1.43

0.038

0.652

8

1.31

0.032

0.660

9

1.21

0.028

0.666

6. Conclusion
By comparing results of the previous experiment and research,wave simulation by OpenFOAM, incorporating interFoam
solver, demonstrates the ability to estimate wave pressures andovertopping around upright dike at a reasonable accuracy.
However, OpenFOAM tends to overestimate the wave pressure
acting on upright dike. The flow rate of overtopping wave also
tends to be overestimated by 3~5times.
In this study, all numerical analysis were carried out without aturbulent model due to a numerical stability problem. If asophisticated turbulent model is incorporated, the accuracy ofthe estimation is expected to improve.
It is also expected that more accurate analysis will be possible
by expanding from the two to the three dimensional numericalanalysis.

References
[1]

[2]

Fig.6 example of change in volume per unit width of liquid
phase stored in the reservoir (Case No.5)[3]

5. Flow rate of the Overtopping wave
comparison
Figure.7 shows comparison flow rate overtopping wave
between numerical analysis and diagram in Goda et al. (1975).
Case No.0~3, the calculation doesn’t converge, so the flow rateof the overtopping wave couldn’t set to a sufficient wave number.
But, before the wave hit dike when the landing water depth was
smaller than the wave height it was confirmed that the182

Goda Y. et al., Laboratory Investigation on theOvertopping Rate of Seawalls by Irregular Waves, Reportof the port and harbor research institute Vol.14, No.4,
pp3-44, 1975 (in Japanese)
Takagi H. and Nakajima C., Estimation error in theanalytical prediction of standing wave pressures acting
upon breakwaters, Journal of Hydraulic, Coastal andEnvironmental Engineering, JSCE, Vol.63, No.4, pp291294, 2007 (in Japanese)
岩垣雄一，山口正隆，Stokes 波とクノイド波の適用限界について，海岸工学講演会講演集，第 14 巻，
pp8-16，1967

Analysis of characteristics and benefits of sharing service users
Student No.: 15_13411 Name: Hidehiko MATSUDA
Supervisor: Naoya ABE

1.

1.1.

Introductionof people who use sharing services is not enough.
In recent years, widely recognized sharing
Based on these, this research aims at theservices such as Uber (mobility hailing), Times
following two(car), Airbnb (accommodation), AirCroset- To identify trends in what life stages(clothing) have gotten social popularity and its
people share with what types of sharing.
penetration into society looks certain to some- To understand the relationship between
extent. There are three factors for the trend, 1.
personal characteristics and the benefits ofincreasing demand for community participation; 2.
using sharing services.
internet penetration; 3. global recession (Botsman& Rogers, 2010). The sharing services are often 2. Methodology
categorized into two types (Belk, 2010). The first
type is conventional reuse or recycle of goods, 2.1. Data & Sample
Data collection was done using online-based
involving the transfer of ownership from one toquestionnaire survey platform SurveyMonkey®
other. This type with transfer of ownership meansfrom 30-31 January 2020. The questionnaire
mainly used goods trading. Therefore, trading insurvey was distributed to a total of 502
a thrift shop or flea market is included in this type.
respondents which are residents of Kanto region,
In Japan, the market for flea market apps has
Japan. The summary of demographic
grown rapidly in recent years with the advent of
information of the respondent is shown in Table
flea market apps such as Mercari. The second
1. And table2 shows the correspondence table oftype is access-based consumption (ABC) without
two type of sharing services.
having the ownership of goods and/or services.
ABC is a consumption behavior that involves
Table 1. Demographic summary of the respondents (n = 502)
using goods or services for a certain period of time
Respondentand paying for them, which is also known as aFrequency
Percentage (%)
Profileservice of subscription. Therefore, rental services,
Male
249
49.7
Gendercar sharing services and Airbnbʼs services fall into
Female252
50.3
this type.
Age
<18
5
1
According to a previous study (Benoit et al,
18-29
115
23
30-44
155
31
2017), people use these sharing services for five
45-60
165
33
reasons, for saving money, communicating with
>60
61
12
other people, experience extraordinary, reduction
for risk and responsibility, environmental
Table 2. Two types of sharing and sharing services
protection. But less studies have been conducted
Typewith transfer of ownershipin Japan for the same argument.
Research objectives
In previous studies, classification andpositioning of economic behavior as sharing andmotivation that people share are mainly
discussed. But discussion on the characteristics

183lTrading at recycle shop (off-line)lTrading at flea market app. (on-line)

Type with access-based consumptionl

Car sharing (ex. Times , Uber)lSpace sharing (ex. Airbnb )3.

Result & Discussion

judgement. Many people feel both time andmoney benefit through car sharing andusing ”Minpaku” But “Minpaku” providers differ
in economic benefits. It will be a difference
whether they are successful as an inn.
And from the point of view of the relationshipbetween personal characteristics and benefits ofsharing services, in both sharing, car sharing andusing “Minpaku”, people whose income isrelatively low fell the benefit financially, while
high-income individuals benefit from time. And
housewifeʼs benefit from the time, perhaps
because they can quickly find betteraccommodations when choosing a family vacation
inn. There may be many attractive lodgings forfamilies registered in the private lodging service.

Fig1. Respondentʼs characteristics and usage of sharing services

4.

Conclusion
The study revealed the relationship between
personal characteristics and the use of sharing
services, and the relationship between personal
characteristics and benefits.
In conclusion, it was found that age, income, thepresence of children, and the presence of elderly
people affect people's values for things, and theusage and benefits of sharing services.
As a future task, mobility sharing services such as
Uber are not major in Japan, so it will be necessary
to analyze sharing in overseas countries wheresuch mobility sharing services are widespread.

5.

References
1. Belk, R. (2010). Sharing: Table 1. Journal ofConsumer Research, 36(5), 715‒734.
https://doi.org/10.1086/612649
2. Botsman R, Rogers R. 2010. Whatʼs mine isyours: the rise of collaborative consumption.
Harper Business: New York, NY.
3. Benoit, S., Baker, T. L., Bolton, R. N., Gruber,T., & Kandampully, J. (2017). A triadic
framework for collaborative consumption(CC): Motives, activities and resources &capabilities of actors. Journal of BusinessResearch.
https://doi.org/10.1016/j.jbusres.2017.05.00
4(correspondence analysis)

Fig 2. Subjective time and monetary benefits recognized by either
sharing services users or provider

Fig1 shows the relationship between personal
characteristics and sharing usage. This figure
reveals four main findings. First one is that people
who having a child (0~6years) tend to actively try
to sharing and are expected to do “Minpaku” orcar-sharing in their 30~50s.
Second one is that people who use other sharing
services (e.g. “Minpaku”, car-sharing, thingsshare) frequently.
Third one is that “rationalists” relatively use carsharing and space-sharing.
And fours one is that people who want to own
things exclusively are expected to do car-sharingor “Minpaku” in their 70s.
Fig2 shows the time and economic benefits ofsharing services from the userʼs subjective184

ドップラーライダーで観測された建物後流(ストリーク)の研究
学籍番号 : 15_05191

氏名 : 桐谷 蒼介

指導教官 : 神田 学

稲垣 厚志

1. 始めに
地表付近における大気の流れは、人工排熱や汚染物質の輸送・攪拌という重要な役割を担っている。
そのため、近年都市域で頻発している環境問題には
大気の運動が深く関わっており、その仕組みを解明することは必要不可欠である。
大気の流れ場の空間構造をモニタリングするには、

図 1：ストリーク例 (a)有り (b)無
風向を矢印で示す。

ドップラーライダーが極めて有効である。都市では
図 1 のようなストリーク構造(筋状の弱風域が一定

3. 解析手法

間隔で並ぶ構造)が頻繁に観測される。また、八木ら(2011)が東京都目黒区東京工業大学に設置されたド本研究では目視による観察と分類によってストリ

ップラーライダーを用いて行った研究では、高層ビークを分析し、特徴をまとめた。最初に 2 時間おき

ル群後流域に最大で観測領域 8km 全域に渡ってスのスキャンからストリークの有無(図 1)を分類し、ストリークが伸びているのが確認された(図 1a)。

トリークの出ているものに対してストリークの挙動、

このようなストリークは、風の収束による局所的長さなどについてさらに分類をした。

な上昇流が地表付近の遅い流れを輸送することで形

4. 結果と考察成される。そのため物質輸送にも関係し、またこのような建物後流のストリークによって他のストリー

ストリークの発生頻度には、風が強い時ほど発生

クの位置も決定されている可能性がある。都市で普しやすい傾向にあった(図 3)。ストリークが発生して遍的に見られるストリーク構造の研究はこれまで多いるスキャンを時系列で見ていくと、そのストリー

く行われてきたが、建物から伸びるストリークの分

クのほとんどは図 4 に示すように、数分程度の周期

析は行われてこなかった点で本研究は新しい。

で左右交互に蛇行して伸びていくような構造を持っていた。振動する流体現象の非定常性を表す無次元

2. 観測概要

量ストローハル数 St は、式(1)のように定義される

東京工業大学に設置されたドップラーライダー

が、大気におけるカルマン渦(チェジュ島等)においの、2011 年 8 月 19 日から 2013 年 2 月 3 日までにては St=0.15 となる(参考文献[4])。ストリークの波観測された PPI スキャン(観測半径 4275m、視線方長(λ)と水平風速から計算した時間スケールと、向分解能 50m、スキャン速度 3 degrees/s、俯角 0.5°

St=0.15 から逆算した振動周期を比較すると(図 5)、で全周を水平スキャンする)のデータを用いた。観測

大気が安定な夜間におけるストリークで両者の値が領域の南西縁(武蔵小杉周辺)には、高さ 160~190m

比較的一致している。

の高層ビル群があり、そこから伸びるストリークがストリークは、風速場全体の揺れに合わせて更に頻繁に観測される。本研究ではこの建物から発生す長い周期で揺れることがある。日中はほとんどの場

るストリーク(図 1a)を対象に分析を行う。

合で揺れが見られ、2 本のストリークが合流する挙185

動(図 6a)がよく見られた。逆に夜間は、揺れが見られないことの方が多く、30 分間の平均場においても、
観測領域 8km 全域に渡ってストリークが伸びる(図6b)こともあった。
𝑆𝑡 =

𝐷
𝑈𝑇

式(1)

D は流れの代表長さ、U は水平風速である。
(a)ストリークの合流 (b)非常に長いストリーク
図 6：30 分間(１５スキャン分)の平均場

5. まとめ建物後流ストリークを観察すると、蛇行しながら伸びていく様子が確認でき、夜間のストリークはカルマン渦の周期と比較的一致していた。都市域の流れ場にもカルマン渦のような流れが存在することが示唆されたと言える。今後の課題として、画像認証
図 3.風速に対するストリークの頻度分布技術の導入などによるストリークの定量的な評価や、さらなる大気パラメーターとの関連性を検証して行
きたい。

参考文献
[1] 八木綾子, 稲垣厚至, 神田学, 藤原忠誠, 藤吉康
志. ドップラーライダーによる都市上空の流れ分類.
土木学会論文集 B1(水工学), Vol. 69, No. 4, pp. I
1753–I 1758, 2013.
図 4 蛇行するストリーク[2] 八木綾子, 稲垣厚至, 神田学, 藤原忠誠, 藤吉康
志. ドップラーライダーを用いた筋状乱流構造の間隔に関する研究. 土木学会論文集 B1(水工学), Vol.
71, No. 4, pp. I 415–I 420, 2015.
[3] 坪木和久，若浜五郎. 1台のドップラーレーダーを用いた風速場の測定法:最小二乗法を用いたVAD
解析.低温科学 物理篇, Vol.47:73 – 88 1989
[4] Ito, Niino. Atmospheric Kármán Vortex Shedding

図 5. St=0.2 における各スキャンの振動周期

from Jeju Island, East China Sea: A Numerical Study

186

GDP と人口によるグローバル都市成長モデルの改良
学籍番号：15B03536

氏名：HE ZUO

Smoothing(U- ) = U-01 ×0.25 + U- ×0.5 + U-81 ×0.25

1. はじめに式1

3.2 国レベル GDP、人口データ使用の妥当性

20 世紀後半、人間社会は高度成長の時代を迎えた。急速な都市化によって、人間社会は地球温暖化、生物多様性の減少、ヒートアイランドなど、様々な環境問題に直面している。都市化がもたらす
気候変動などの問題に対する緩和策、対応策を練る
ため、グローバルな時空間都市成長分布予測はとても重要であるが、まだ難しい問題と見られている。

北京、ロスアンゼルスにおいて、都市レベルと国レベルの GDP、人口成長率それぞれを[0,1]の範囲に正規化した成長曲線がほぼ一致している。つまり都市レベルと国レベル成長率の比は不変である。各対象都市において、この比例が常に一定値を保つと仮定すると、比例係数は 3.3 節で使用する重回帰式の係数 Coef に考慮されるため、国レベルデータの使用は妥当である。

2. 既存研究と本研究の目的
都市成長予測モデル SLEUTH(K.Clark et al. [1])は、傾斜、土地利用、除外地域、都市地域、交通
網、山岳、六つのローカル空間的情報を用いて、都市化の時空間分布を予測する。さらに Zhou etal.[2]は、SLEUTH に基づいた全球時空間都市成長
確率を予測する手法 GUSPS を提案したが、欠点として、将来の経済社会発展方向を考慮できない。
GDP、人口は都市成長過程を制御するマクロな指標だと考えられるため、本研究は GDP と人口が都市成長に与える影響を探究し、GUSPS の空間分
布予測を、共通社会経済経路(SSP)から抽出する
GDP 人口予測によって修正して、それから空間分
布を再調整することを目的にしている。(図 1)

図 2 北京の 左)GDP 右)人口 成長を正規化した曲線

3.3 重回帰モデルの作成
以下の制約に従い、114 個都市それぞれを対象に重回帰分析を行なう。
• 都市面積成長率を従属変数にする• GDP 成長率、人口成長率を独立変数にする• GDP 成長率と都市成長率は負でない相関がある• 人口成長率と都市成長率は負でない相関がある• GDP が増加しない、かつ人口が増加しない場
合、都市面積は一定値を保つ
次に、時間スケールが変数の相関に影響する可能性を考慮し、timestep を設置する。任意の𝑋が(𝑖 −𝑡𝑖𝑚𝑒𝑠𝑡𝑒𝑝)年から𝑖年までの成長率d(X - )を式 2 で定義する。従って、任意の timestep に対して、回帰式は式 3 となる。

図 1 本研究のフロー

3.

指導教官：神田 学、 Alvin Varquez

GDP と人口が都市成長に与える影響d(X - ) =3.1 過去の時系列データ

BC 0BCDECFGHEGIBCDECFGHEGI

式2𝑑 𝑈𝑟𝑏𝑎𝑛- = 𝐶𝑜𝑒𝑓STU ×𝑑 𝐺𝐷𝑃- + 𝐶𝑜𝑒𝑓UYU ×𝑑 𝑃𝑂𝑃-

データセット LandScan は 30 秒の空間解像度
2(約 1km )で空間的人口分布を提供している。本研
究は、LandScan で人口が 1000 を上回る格子を都市格子と定義し、過去の都市面積を算出する。
World Bank Open Data は世界銀行より公開されており、過去の国レベル GDP、人口データを提供している。
LandScan から過去の都市面積を抽出する際、年ごとの変動が大きい。そのばらつきを抑えるため、𝑖年の都市面積𝑈について式 1 で平滑化を行なう。
従って 2001 年から 2016 年まで、16 年分のデー
タを準備した。なお、小さい都市の成長は政策に敏感に反応するため、分析対象を全球から抽出した合計 114 個大都市圏や首都にする。

(ただし 𝐶𝑜𝑒𝑓1 ≥ 0,

𝐶𝑜𝑒𝑓] ≥ 0,

式3

𝑃𝑂𝑃は人口)また、成長率が負にならないように、都市面積、GDP、人口の成長率を正規化線形関数(ReLU) で処理しておく。Li et al. [3]、Mertes et al. [4]などの研究でも負の成長の解消を勧めた。

3.3 重回帰分析の結果
一つの対象都市に対して、timestep が 1 から 12まで、12 回重回帰分析を繰り返し、最も高い決定係数を持つ式をその都市に対する最適解とする。一部の結果を表 1 で示す。
切片を 0 にする制約によって、28 個対象都市は負の決定係数を示した。係数 Coef が 0 の場合、その都市において該当の変数が都市成長に与える影響が微小だと思われる。

187

都市名

timestep

決定係数

𝐶𝑜𝑒𝑓STU

𝐶𝑜𝑒𝑓UYU

北京

9

0.32

0.11

0

東京

8

0.63

0.21

3.32

0.38

0.33

0

ロサンゼルス

4
表1

4.

まず、2016 年から 2050 年まで、全対象都市の総合都市面積成長率について、GUSPS は 43%の成長率を示した。SSP1~5 を利用した回帰モデルはそれぞれ 47%、39%、37%、33%、63%の成長を示した。これは適切な範囲だと考えられる。
つぎに、トップ 20 位までの都市(図 5)を見てい
くと、GUSPS から飛躍的な成長を予測された都市において、回帰モデルでは控えめな成長になっている。一方で、8 個の都市において GUSPS から全く成長が認められないものの、回帰モデルからは多少成長すると予測された。
特に注目したい点は、インド人口上位５位までの都市すべてにおいて、GUSPS はまったく成長しないと示唆した。インドの首都 New Delhi でさえ、都市化確率が閾値の 50%を超える格子が現れなかった。かわりに、周辺都市の Lunkaransar から飛
躍的な都市拡張が予測された(図 6)。つまり、
SLEUTH モデルから見るインドの都市成長は主に小さい都市で進めると思われ、大都会に偏るような都市集積効果は認められていない。回帰モデルの方は、それでも現在の大都市は成長すると予測した。
上述の結果を踏まえて、本研究の回帰モデルはGUSPS と比べ、折衷的な予測だと考えられる。

重回帰分析結果の一部

SSP シナリオによる修正

共通社会経済経路(SSP)は将来社会経済発展の可能性を、緩和策、適応策の困難性に応じて５種類に分類した。そのうち、SSP1 は最も良いシナリオ、
持続可能な開発を代表している。SSP3 は最も悪いシナリオ、地域の分断を代表している。
第 3 章で求めた回帰式に SSP1、3 の GDP、人口データを代入した予測結果の例を図 3 で示す。
GUSPS データセットから都市格子を判定する都市
化確率の閾値を 50%に設定した。次に 2050 年
GUSPS データセットの予測結果を再分布する例を
図 4 で示す。

6.

本研究はトップダウンの手法で、まず全球主要な都市それぞれを対象に、GDP、人口が都市成長に与える影響を条件付きの重回帰分析で求めた。
本来、都市レベルデータを入手できなければ、それに基づいたモデル作成が難しい。本研究は、都市レベルと国レベルの GDP、人口成長率の比が各対
象都市において不変であると仮定したことによって、数多くの都市に回帰分析を応用できた。
しかし、この仮定が成り立たない都市について、回帰モデル予測精度の低下が予想される。他に、回帰モデルに様々な制約を設けた結果、決定係数が低くなり、特に切片を 0 にする制約は、負の決定係数に導いた。
GUSPS データセットの改良手法として、本研究は既存の大都市圏で適切な結果を得たものの、全地域の改良はまだ未解決である。

図 3 北京の予測結果

図 4. 北京(a) GUSPS (b) SSP1 による再分布

7.
図 5.

考察と結論

参考文献

[1] K C Clark et al.

2016~2050 年トップ 20 位まで都市の成長率[%]予測“A Self-Modifying Cellular Automaton Model ofHistorical Urbanization in the San Francisco Bay Area”[2] Zhou Yuerong et al. “High-resolution global urban growth

projection based on multiple applications of the SLEUTH urban
growth model”[3] Li Xuecao et al. “Projecting Global Urban Area Growth Through2100 Based on Historical Time Series Data and Future Shared
Socioeconomic Pathways”

図 6.

5.

GUSPS データセットから見る New Delhi とその周辺[4] Mertes et al. “Detecting change in urban areas at continental

最終結果

scales with MODIS data”

188Image super-resolution by a convolutional neural network
using a diﬀerence image for learning
Student number：14 00990

1

Introduction

2

Image interpolation

Name：Haruki Ikenoue

Supervisor：Yukihiko Yamashita

interpolation method, but the amount of calculation increases. It also has the property that the edges may be
As the performance of information processing terminals blurred. The Lanczos-n method is a method of referencimproves, the resolution of displays is increasing. On the ing and weighting pixels with a distance of not greater
other hand, since the resolutions of images and videos than n around the target pixel to interpolate them.
produced in the past are low, the outline blurring is conspicuous when the processing to increase the resolution
is not performed. In order to improve this visibility, theimage super-resolution (SR) is used to restore the edges 3
Convolutional neural networkof a low-resolution (LR) image as clearly as possible toobtain a high-resolution (HR) image. In recent years, image SR by a convolutional neural network has been used. The convolutional neural network [3] is a technique to
The methods have been devised, and researches are be- improve the accuracy of image recognition by performing conducted to obtain a more accurate restoration by ing convolution processing using a movement-invariant
adjusting the number of layers and the structure of the ﬁlter as the weight of the neural network. By performing
network. The amount of calculation using deep learn- the convolution process, it becomes possible to perform
ing increases as the structure of the network becomes image processes such as edge detection and image levelmore complicated. In this research, I try to improve the ing inside the network. Since it also has the function to
restoration accuracy by using a pre-processed LR image detect features similar to the features of the ﬁlter fromas an input image for Super-Resolution Convolutional the input image [4], it is possible to perform the image
Neural Network (SRCNN) [1], which has a relatively sim- super-resolution by combining a LR feature extraction
ple structure among convolutional neural networks. As ﬁlter and a HR feature extraction ﬁlter.
a result, the accuracy is improved without complicating
the network structure.

4

The basic method of generating an image with a large
number of pixels from an image with a small numberof pixels is based on interpolation. [2] There are various image interpolation methods and each of them has
its own characteristics. The nearest neighbor method is
an interpolation method in which the pixel value of the
input image closest to the position of the pixel to beinterpolated is used for it when interpolating the input
image. While its calculation is simple, there is a problem
that jaggies are likely to occur. The bi-linear method isa method by calculating with linear interpolation using
4 pixels around the target pixel. Although the processing by the bi-linear interpolation method is less likely tocause jaggies on the contour than the nearest neighbormethod, the edges may be blurred. The bi-cubic interpolation method is an interpolation method that uses 16
pixels around the target pixel and performs interpolation by a cubic expression. The bi-cubic interpolation
method can obtain a sharper image than the bi-linear

Network learning using diﬀerence images

In this research, in order to improve the accuracy of the
convolutional neural network, I propose to simply extract the features from the enlarged low-resolution image and perform learning using it. As a method to obtain the amount of features, the diﬀerence between the
LR enlarged images obtained by using diﬀerent enlargement methods is used. The diﬀerence image obtained bythis method contains many high-frequency componentsthat are easily lost when the image is enlarged. On thecontrary, the low-frequency component that is easily restored does not contain very much. Figure 1 visualizes
the diﬀerence between the original image and the interpolated image, and the diﬀerence between the images
interpolated by diﬀerent two methods. A gray ﬁlter wasused to improve visibility. It can be seen that the difference between the diﬀerent interpolation methods issimilar to the diﬀerence between the original image andthe interpolated image.

189

Figure 1: Comparison of diﬀerence images

Figure 3: result of super-resolution
can be considered that the features of the bi-cubic andLanczos-4 methods used in case 3 were the worst because
the restorations of high-frequency components were superior to other interpolation methods. As a result of
the experiments, good results were obtained from thesuper-resolution using the convolutional neural network
Figure 2: Learning resultwith the proposed method. However, case 4 does notprovide the best result. Regarding the Lenna image, theprediction result of case 4 was lower than that of the con5 Experimentventional SRCNN. This is because the feature extraction
I conduct experiments to compare SRCNN, which is was not successful.
trained using the training data of diﬀerence between LR
images and HR images, and SRCNN, which used the 6Conclusion
training data of LR diﬀerence images and HR images,
which is the proposed method. The images used for In this study, I proposed to train the convolutional neurallearning were 800 data from the DIV2K dataset, and network using the diﬀerence image to improve the accucalculations were performed up to 100000 epoch. Table racy of SR without changing the structure of the convo1 shows Method A and Method B used for image upscal- lutional neural network. It was conﬁrmed that the proing. Case 5 is a network that inputs a LR enlarged image posed method improves the accuracy of super-resolution
and predicts the diﬀerence. Figure 2 shows the learning by experiments.
Since it is not preferable that the accuracy of the prediction result and the training result diﬀer depending on
Table 1: Upscaling methods
the method, we have to improve the method to generate
Method A
Method B
the diﬀerence image so that the method to acquire thecase1 4x bi-cubic 4x nearest neighbor
diﬀerence image can stably retain the features.
case2 4x bi-cubic
4x bi-linear
case3 4x bi-cubic
4x Lanzcos-4
case4 4x bi-cubic
8x bi-cubic
References
result, and Figure 3 shows the result of super-resolution.
The vertical axis of Figure 2 shows the improved ratioof MSE between HR image and SR result to the MSE
between HR image and the LR image by the bi-cubic
method. From the results, the learning using the difference image increases the gradient of accuracy at theinitial stage of learning and the prediction accuracy after
learning. It is considered that the gradient at the initialstage of learning by using the diﬀerence image is large
because the low frequency components are not uselessat the stage. Regarding the improvement of accuracy
after learning, the proposed methods other than case 3
generally provide good results. Therefore, we can saythat the diﬀerence between blurred images with similar
properties is an excellent feature for super-resolution. It
190[1] Chao Dong, Chen Change Loy, Member, IEEE,
Kaiming He, Member, IEEE, and Xiaoou Tang,
Fellow, IEEE ”Image Super-Resolution Using
Deep Convolutional Networks”, arXiv:1501.00092v3[cs.CV], 31 Jul 2015[2] Masanao Koeda, Etsuko Ueda, Takayuki Nakamura”Introduction to Image Processing with OpenCV”,
Kodansha, 2014 (in Japanese)[3] Atushi Fujita ”Deep learning learned in C++”, Excite Japan Co. Ltd., 2017 (in Japanese)[4] Takayuki Okatani ”Machine Learning Professional
Series - Deep learning”, Kodansha, 2015 (inJapanese)EFFECT OF PH REGULATION ON PIG MANURE COMPOSTING
Student number: 14_12986 Name: Nobuaki HOJO

Supervisor: Kiyohiko NAKASAKI❽

１．Introduction
Composting is a biotechnology to effectively utilizes
organic waste by converting it to the compost and recycle
to farmland. Among organic wastes, livestock manure isconsidered to be particularly suitable for composting
because it does not contain impurities that are not suitablefor composting, and does not contain toxic substancessuch as heavy metals. For this reason, most of the
livestock manure has been treated by composting, but pig
manure is difficult to compost because of its acidity. As acountermeasure, neutralization with alkaline agent such as
lime has been applied. However, there are regulations that
do not recognize agricultural products as "organicallygrown product" if they are grown using compost that has
been neutralized with chemicals. Therefore, there has long
been a need to develop a new method for composting ofacidified pig manure. The aim of this study was to confirm
whether a new method of inoculating organic aciddegrading microorganisms can promote composting of
pig manure.

❻
❺

❶
Air

❷

❸

❼
❹

❶ Flow meter❷ CO2 trap (NaOH)❸ Bubbler❹ Silicon plug
❺ Stainless screen❻ Mini-reactor❼ Gas bag
➑ Incubator

Silicontube

Fig. 1. Experimental devices
60℃ at a rate of 2.5℃/ h and then maintained at 60℃.
By contrast, in Run B and D, the temperature wasmaintained at 30℃ for 3 days and 4 days after the start ofcomposting respectively, to wait for the growth of the
inoculated microorganism. Thereafter, the temperature
was raised to 60℃ in a same matter with other Runs. The
composting period was 10 days in all runs. The exhaustgas from the mini-reactor was collected in a 10 L gas bag,and the CO2 concentration was measured every 24 hours.
The CO2 evolution rate was measured from the CO2
concentration and the aeration rate, and the conversion ofcarbon, which corresponds to the degree of organic matterdecomposition, was calculated from the cumulative value.

２．Materials and Methods
2.1. Preparation of Composting material
For the raw materials of composting, pig manure, sawdust,
and Alles G were mixed at a dry weight ratio of 5:14:1.
For the organic acid-degrading bacteria, yeast Pichia
kudriavzevii RB1 strain and filamentous fungus TR1strain isolated in the laboratory were used. Yeast RB1
strain was cultured on potato dextrose (PD) agar medium
at 30 ℃ for 2 days, and one colony was picked andsuspended into liquid PD medium and cultured at 30℃
for 2 days before composting experiment. The
filamentous fungus TR1 strain was cultured in PD liquidmedium at 30℃for 3 days. After culturing, the cells were
washed with physiological saline and then inoculated.
There are four composting experimental Runs: Run
A using the composting material itself, Run B inoculatedwith yeast RB1 strain as the composting material, Run C
with lime added to the composting material, and Run D
inoculated with the filamentous fungus TR1 strain. The
inoculation concentrations of the cells in Run B and Run
D were adjusted to 109 CFU/g-ds and 1.94 mg/g-ds,
respectively, and the lime in Run C was added so that the
pH of the raw material was 9.

2.3.
Measurementofphysicochemical
andmicrobiological properties
The pH of the compost was measured using a pH meter;
samples were prepared as water-soluble extracts using
distilled water at a 1:9 ratio and treated with ahomogenizer. The moisture content (%) was measured
after drying at 105 °C for 24 h in a dry oven. Organic acidconcentration of the compost was analyzed by using
HPLC. The bacterial cell densities were determined usinga Real-time PCR. The bacterial DNA was extracted fromthe compost sample and the bacterial community was
analyzed by next generation sequencing (NGS).

３．Results and discussion
3.1. Courses of CO2 evolution rate and conversion ofcarbon during composting
Figure 2 shows the time course the CO2 evolution rate andconversion of carbon. In Run A, CO2 was not generated
indicating no organic matter degradation. By contrast,
CO2 evolution was vigorous in Run B, C and D from day
1. Conversion of carbon at day 10 was almost 0 in Run A,
while around 50% in other Runs. This result clearly
indicates that the organic matter degradation of inoculated
Runs (Run B and D) was as high as lime-added Run (RunC). Therefore, the effectiveness of microbial inoculation
was confirmed.

2.2. Composting operation
The composting device was shown in Fig. 1. Distilledwater was added to the compost raw material to adjust the
moisture content to 55%, and 12 g of the raw material was
put into a mini-reactor to start composting. The air flowrate to the mini reactor was 5.5mLmin. For Runs A and C,
the composting temperature was raised from 30℃ to

3.2. Courses of concentration of pH and organic acidconcentration

191

The time course of pH in composting is shown in Fig. 3.
In Run A and C, only the initial and final values are shown.
In Run A, the pH remained unchanged from the initialvalue of around 5.5. In Run C, lime was added at the
beginning to adjust the temperature to around 9, but evenat the end of composting, a weak alkaline condition of 8.5
or more was maintained. These results corresponded wellto the fact that organic matter was not degraded at all in
Run A and was vigorous in Run C. In both Run B and C,
the pH increased after the start of composting, but the rateof increase was particularly fast in Run B, which is notshown in detail here, but yeast is a filamentous fungus. It
was considered that the growth rate was faster than that ofyeast. In both Run B and C, the pH finally became a weakalkaline value around 8. The pH rose faster in Run B as
compared with Run C. The reason for this maybe yeasts
grows faster than filamentous fungi, although the details
are not given here.

alkaline condition, although it should not rise above
neutral level only by the removal of organic acids. This isprobably due to the accumulation of ammonia as a resultof protein degradation in the pig manure.
30

Concentration

Lactic acid Run B

10

CO2 evolution rate x 103 (mol/d)log CFU/g-ds

Conversion of carbon(%)

10

9.5

30
20

9
8.5
Run B

8

Run D

7.5

10

7
0

0

0

2

4

6

8

10

Time(d)

9

Run B
Run D

8
7
6
5
4

0

2

4

6

8

4
6
Time(d)810Although details are not shown here, microbialcommunity analysis showed that the abundance ofBacillales rapidly proliferated after 4 days, suggests that
this microorganism has high organic matter degradation
activity in high temperature. Clostridiaceae also showed
high abundance throughout composting, but this sporeforming bacteria was also abundant in raw material underroom temperature conditions. Therefore, the role ofClostridiaceae in pig manure composting is stillquestionable and needs further investigation to clarify it.

10
Run A
Run C

2

Fig. 5. Courses of concentration of total bacteria duringcomposting.

Fig. 2. Courses of CO2 evolution rate and conversion ofcarbon during composting.

pH

8

10

Run A
Run B
Run C
Run D

40

6

3.3. Courses of bacterial cell density and microbialcommunity during composting
Figure 5 shows the time course of total bacterial celldensity during composting of Run B and D. In allcomposting, the cell density reached a maximum value
around day 2 or 3, and then decreased in the latter half ofthe composting period. However, a high value of
109CFU/g-ds or more was maintained throughout thecomposting period, confirming that organic matter
degradation was active.

60
50

4

Fig. 4. Courses of concentration of organic acid duringcomposting.

082

Time(d)10

46Time (d)Propionic acid Run D
10

0

Run A
Run B
Run C
Run D

2

Propionic acid Run B

0

20

0

Lactic acid Run D

20

10

Time(d)Fig. 3. Courses of pH during composting.

4.

Conclusion

The yeast strain RB1 and filamentous fungus strain TR1
used in this experiment were effective in degradingorganic acids, increasing pH, and maintaining the activityof composting microorganisms when inoculated in theearly stage of pig manure composting. The promotion
effect was as high as lime addition. Since lime cannot be
used to compost for the production of organically grownvegetables, these microbial inoculants was found to beeffective for composting of acidified raw material insteadof lime addition.

Figure 4 shows the course of the organic acidconcentration during composting of Run B and C. Lactic
acid and propionic acids were observed while acetic acidand butyric acid were not detected in all Runs. At the
beginning of composting, the concentration of lactic acidwas remarkably higher than propionic acid. The
concentration of both organic acids quickly decreased in
the early stage of composting. This is probably owing tothe organic acid degradation by the inoculated
microorganisms. The change in organic acidconcentration corresponded well with the increase of pH
values. It should be noted that the pH reached to the weak192

外国人観光客の避難所利用に対する日本人の受容意識
学生番号：15B03482 氏名：厳 鮮詠（オム ソンヨン） 指導教員：花岡 伸也の社会的接触などアンケート調査項目と有意性を調べるためにクロス集計とカイ二乗検定法を用いる。

１．はじめに日本は島国で、地震や水害などの多くの自然災害の影響を受けた国である。過去における災害の中で、たくさんの高齢者や外国人の被害が報告されている。災害への影響を最小限に抑えるために、災害リスク管理が重要である。日本は 2011 年に 621 万人に止まっていた訪日外国人数は、2019 年には約 5 倍増の 3188 万人を記録した。その背景にはビザ緩和、航空運賃の低価格化、日本文化・商品への高い関心などがある。［１］訪日外国人の急増に伴い、災害に対する十分な備えが必要である。しかしながら、過去の災害事例から外国人への対応の課題が挙げられている。例えば、「言葉が分からずどこに行けば良いか分からなかった」など
言語の問題で外国人の避難が遅くなる可能性がある。
外国人に対する情報提供の取り組みをして、外国人の視点で避難所利用しやすくする必要である。また、訪日
外国人観光客は、自国における被災経験や防災教育の有無などにより、日本人の特徴と異なり、災害対応
時の情報収集と対応行動が日本人と異なる。それで、避難所で外国人と日本人避難者とトラブルになる可能性がある。［２］
そこで、本研究では外国人観光客の避難所利用に対する日本人の受容意識を分かるため、アンケート調査を行い、調査結果を分析と考察をする。

コンジョイント分析とは、製品またはサービスが持っている要因に、回答者が与える価値いわば効用値を求める。また、求められた効用値で複数の要因間の相対重要度の把握できる手法である。３０年以内に首都直下地震が発生する可能性が高いと言われてる。首都直下型地震が発生して、避難所に避難するシナリオを想定する。本研究では、避難所選択の相対重要度を分かる
ためコンジョイント分析の手法を用いる。避難所の要因
は避難所まで移動時間、間仕切りの有無、 外国人避難者の有無の３つである。要因の各水準は２つで移動
時間は 10 分以内と 10 分以上、間仕切りの有無はありとなし、外国人避難者の有無はいるといないである。求めた各要因の水準の効用値が正の値のものは回答者から好まれているであり、負の値のものは好まれていないことを示す。これを見ると、それぞれの水準が回答者によってどのように評価されているのかを分かる。コ
ンジョイント分析の中で、本調査では選択型コンジョイ
ント分析を用いて分析する。選択型コンジョイント分析
は、二つの選択肢が提示され、そこから良いと思うものを１つ選ぶ方法である。

２．クロス集計とカイ二乗検定

４．調査結果の分析

クロス集計はアンケート調査の２つ質問項目の関係を調べる手法である。回答数の交差頻度を通して、統計的有意性を検証する。カイ二乗検定は二つ変数間の関係が相互独立関係なのかを検証する方法である。実際に出た観察頻度と統計的に期待できる期待頻度の間でどれだけの差があるかをカイ二乗検定を通して、統計的に検証する。期待頻度は行と列の各頻度の和を掛け合わせた上で総頻度数で割ったものである。カイ
二乗値は観察頻度と期待頻度の差を二乗した後、期待頻度で割った値である。カイ二乗値は期待頻度より観測頻度が大きいほど大きくなり、カイ二乗値が大きいほど p 値は小さくなり、二つの変数間の関連性は高くなる。
そこで、仮説を設定できる。
帰無仮説（𝐻0 ＝二つの変数は相互独立関係である）
対立仮説（𝐻1 ＝二つの変数は相互独立関係ではない）
カイ二乗値に応じた p 値によって、帰無仮説を棄却し、対立仮説を採用するか、対立仮説を棄却して帰無仮説を採択するかを決める。帰無仮説を棄却すると二つの変数は相互独立関係ではないことだと判断される。
本研究では、外国人に対する認識と避難所選択の多方面から分析したくて、外国人に対する認識と外国人とアンケート調査は避難所に避難した経験がある日本
人３００人、避難所に避難した経験がない日本人３００人を対象で２０２１年１月２２日から２５日までＷＥＢ調査を実施した。設問項目は基本情報、避難所選定の重要度、避難シナリオ上避難所選択、自分のコミュニティで外国人の受け入れに同意、外国人との社会的関係、人生に対する満足度、外国人専用の避難所を設置する
必要などを設問した。そこで、日本人が外国人に対する認識を分かるために自分のコミュニティで外国人の受け入れに同意するかしないかの結果と外国人との付き合うがあるかの外国人との社会的接触に有意性を調べるために、調査結果をクロス集計とカイ二乗検定を行う。
自分のコミュニティで外国人の受け入れと外国人との付き合いの有無連関性を調べるためにクロス集計を実
施した。

193

３．コンジョイント分析

表１．クロス集計とカイ二乗検定の結果

効用値で避難所の要因の重要度を分かる。重要度を見ると避難所の選択で重要だと思うことを分かる。間仕切りの有無が５２．４％で一番高かった。回答者は避難所を選択するときに自分の空間があるかプライベートが守られるかを重視する。理由として、災害で住むどこ
ろがなくなって自分の家のようなどころが必要だと思う。
避難所で外国人の有無の重要度を見ると１９．１％で低かった。
クロス集計の結果で外国人との関係有無と外国人の認識は連関性があるだと判断されたから外国人と付き合いがある人と付き合いがない人と分けてコンジョイン
ト分析をすると重要度の変化があるか調べる。

外国人との付き合いの有無
あり
なし
全体
38
91
129
同意
(29.5%)(70.5%)(100%)
しない(6.3%)(15.2%)(21.5%)
自分のコ
ミュニテ
どちら
90
194
284
ィで外国 といえ(31.7%)(68.3%)(100%)
人の受ない(15%)(32.3%)(47.3%)
け入れに
100
87
187
同意
同意
(53.5%)(46.5%)(100%)
する(16.7%)(14.5%)(31.2%)
228
372
600
全体
(38%)
(62%)
(100%)
27.805(0.001∗∗∗ )𝑥 2 (𝑝)∗∗∗∗∗∗𝑝 < 0.05, 𝑝 < 0.01, 𝑝 < 0.001

表４．外国人との付き合いによる避難所選択の重要度
外国人との
外国人との
付き合いがある 付き合いがない
移動時間
29.2％
28.2％
間仕切りの有無
54.6％
51.2％
外国人の有無16.2％
20.6％
表 4 を見ると、外国人との関係がある人は避難所の外
国人有無の重要度が 16.2％で低くなる。外国人との関係がない人は 20.6％で高くなる。この結果で外国人と社会的接触が高いほど外国人に対する認識も高いことを分かる。避難所で外国人の有無に気にしないである。

表１によると、自分のコミュニティで外国人の受け入れに同意しない人は外国人と付き合いがないのが一番高い頻度を見せた。分析結果、カイ二乗値は 27.805、ｐ値
は 0.001 である。有意水準 0.05 でｐ値により、帰無仮説
棄却し、対立仮説が採択する。従って、外国人の受け入れと外国人との付き合いの有無は相互独立関係ではないから連関性があると判断される
上記の３で述べた避難シナリオ上避難所選択の調査
結果を選択型コンジョイント分析を通して、回答者の避難所選択の選好度を調べる。

５．おわりに

表２． 避難シナリオ上避難所選択肢
間仕切りの
外国人の
移動時間
有無
有無
避難所１
10 分未満あるいない
避難所２
10 分未満ないいる
表２は、避難所選択肢の一つの例である。避難所の要因を移動時間、間仕切りの有無、外国人の有無である。
各要因を見て、自分が選好する避難所を選べる。
タグチ直交表を用いて避難所の選択肢を最適化した避難所の４つを比較する６つのシナリオの結果をコンジョ
イント分析をする。
コンジョイント分析を通して属性の効用値を求められる。
表３．コンジョイント分析の結果
答え
効用値
重要度
10 分未満0.5766
移動時間
28.5％
10 分以上-0.5774ある
1.0601
間仕切りの
52.4％
有無
ない
-1.0609いる-0.3846
外国人の
19.1％
有無
いない
0.3839
表３は、回答者の６００人が６つのシナリオで避難所選
択の結果をコンジョイント分析の結果である。効用値が正数の場合は回答者が選好することで負数の場合は選好しないことである。移動時間は短い方で自分の近い避難所を選好する。間仕切りの有無はある方を選好
して、避難所で自分だけの空間とかプライベートを重視する。最後に避難所で外国人の有無については外国人がない方を選好する。

外国人観光客の避難所利用に対する日本人の受容意識を分かるため今回のアンケート調査と調査の結果を分析をした。クロス集計の結果で外国人との社会的接触が高い人、すなわち外国人との付き合いがある日
本人は自分のコミュニティーで外国人を受け入れることに同意していることが分かった。
人々は避難のとき避難所を選ぶ際に自分のプライバシーを重視して外国人観光客の受容については重要度が低かった。クロス集計の結果を用いて、外国人と社会的接触の高い人の避難所選択のコンジョイント分
析の結果を見ると、外国人たちと避難所で一緒に暮らすことを理解する。

参考文献［１］日本政府観光局（JNTO）「訪日外国人旅行者統計」
https://www.jnto.go.jp/jpn/statistics/since2003_visitor_arrivals.pdf．
［２］Rajarshi Dasgupta, et al.：A rapid indicator-based
assessment of foreign resident preparedness in Japan
during Typhoon Hagibis, International Journal ofDisaster Risk Reduction 51 (2020) 101849．
［３］真城 知己：「SPSS によるコンジョイント分析」, 東
京図書 (2001)．
［４］John R. Hauser：Note on Conjoint Analysis, MIT
Sloan Management (2015) 2-18．
［５］宮城県農業・園芸総合研究所情報経営部：マーケ
ティングに活用される分析手法-選択型コンジョイント分
析 (2014) 27-39．

194

EXPERIMENTAL INVESTIGATION ON ACCURACY OF SURFACETENSION DETERMINED BY SESSILE DROP SHAPE
Student Number: 15_14445 Name: Yuino MUROZONOSupervisor: Kunio TAKAHASHI

1 Introduction
The wettability of liquid to solids, such as wax,
solder and surfactants, is evaluated by contact
angle and surface tension. The contact angle ofliquid is measured by the sessile drop and thesurface tension is often measured by the pendantFigure 1Model of sessile drop and definition ofdrop. But, the surface tension is easily affected bycoordinates [1]atmosphere and impurities. So, we need a method

Variables with a length dimension are

to determine the surface tension and contact angle

nondimensionalized as 𝑧̃ = 𝑧/𝑙+ using 𝑙+ =simultaneously from a sessile drop observation.

-.

A theoretical method to determine the surface,/0, where 𝛾2 and 𝜌 are the surface tension andtension from the shape of a droplet on a planethe density of the liquid, respectively. And 𝑔 issurface using a diagram has been proposed [1]the gravity acceleration. The liquid shape depends[2], but the applicability of this method has noton the nondimensionalized curvature at the top of
the liquid 𝜃6̇ . If we measure 𝑟, 𝑧 and 𝜃 ofbeen sufficiently investigated.

7

determining the surface tension from the shape ofarbitrary point on the liquid surface, we candetermine 𝜃6̇ from 𝑧/𝑟 and 𝜃 using a figure,a droplet on a plane is experimentally investigated

we can determine 𝑧̃ from the 𝜃6̇7 and 𝜃 using

using photographs of the droplet.

another figure, and finally, we can determine theIn this study, the accuracy of the method [2] for7

9 <surface tension as 𝛾2 = 𝜌𝑔 89:; . The details of

2 Surface tension determined bysessile drop shape

this method are expressed in Refs.[1] and [2].

A droplet on a solid plane is assumed to be

3 Experimental investigation on
accuracy of surface tension
determined by sessile drop shapeaxisymmetric, as shown in Figure1. The vertex of
the droplet on the axis of symmetry is the origin(O), the 𝑟-axis is perpendicular to the axis ofsymmetry, and the 𝑧-axis is in the direction ofgravity of the axis of symmetry. Take the 𝑙-axis

3.1 Observation or droplet shapealong the droplet surface from the origin (O), andA plate of PTFE (polyethylene

let 𝜃 be the angle with the 𝑟-axis at any point P

terephthalate) is cleaned up with pure wateron the droplet surface. The coordinates of point P

and completely dried up. It is placed on a

can be expressed by 𝑧 and 𝑟.

vibration isolation table, so that the surface ofthe plate is horizontal. Micro-ruler sheets are
pasted on the side-surface of the plate. A

195

droplet of pure water is placed on a cleansufficiently useful for evaluating the wettability ofsurface of the PTFE plate. A camera is put

a liquid.

about 20cm aside of the droplet, so that the

Other liquids of medium and small volumes

optical axis of the camera is also horizontal.

were also considered. As a result, the error in theaccuracy of the surface tension measurement was

3.2 Surface tension measurement results andaround 10%, indicating its usefulness.
The data of 𝑧/𝑟 and 𝜃6̇ for all 𝜃 are plotted

discussion of their accuracy

7

Image data taken by the camera are imported

on the figure used in the method [1,2]. The
evaluated values of 𝜃6̇ are all in a narrow range.

to a drawing software. Grid lines are

It suggests that the surface tensions are

introduced on the image adjusting to the scaleof the ruler. After the image is locked, anothersuccessfully determined for these 𝜃. However,for smaller 𝜃, the deviation of the evaluated 𝜃6̇

line is introduced on the image

seems increased. The effect of the error in the

independently, whose tilt angle is 𝜃. By

measurement on the evaluation is investigated bymoving the tilt line to contact on the liquid

giving an intentional error of 0.025 mm for 𝑧

surface, the contact point is sought. 𝑟 and 𝑧

and 𝑟. The effect is found not so critical for theof the contact point are listed for some 𝜃 indetermination of the surface tension in the

Table 1. The surface tension is determinedmeasurements of the present study.

using the method [1,2] and listed also in the

Since the experiments carried out in the present

table.

study are limited, further investigation would be

Figure 2 shows the image of the droplet.

77required for more detailed discussion.

4 Conclusion
The accuracy of the surface tension values
obtained by the method [1,2] is examined. The
error was around 10%, and it is found that theaccuracy is sufficiently useful for the evaluation

Figure 2 Side view photograph of sessile drop.
Table 1 Surface tension measurement resultsof wettability.

𝜽

𝒓

𝒛

𝒛/𝒓

𝜸l

𝟑𝟎

4.675

1.025

0.219

65.5014

References

𝟒𝟓

5.625

1.725

0.307

66.7205[1] ⾼橋、他、「⼤体積の平⾯上液滴の形状情報

𝟔𝟎

6.125

3.400

0.385

68.0744から液体の表⾯張⼒を決定する⼿法の提案とそ

𝟕𝟓

6.300

2.825

0.448

56.2697の 適⽤性の検討」, 溶接学会論⽂集 38 巻

𝟗𝟎

6.425

3.550

0.553

67.0948(2020), pp.193-198

Mean

64.7322[2] ⾼橋、他、「重⼒下の平⾯上液滴 (Sessiledrop) 形状から図を⽤いて表⾯張⼒と接触⾓を同Since the ideal surface tension of pure water is

時 決定する⾮反復的⼿法」, 溶接学会論⽂集 39

about 72 [mN/s], the error is about -10.1%. Since

巻 (2021), pp.32-38

the surface tension of a liquid is reduced by dust
and other contaminants, this method is196