ISSN 1880-8468
Technical Report ofInternational Development Engineering
国際開発工学報告

TRIDE-2016-04

May 9, 2016

Abstracts of Bachelor Theses
Presented in Feburary 2016

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

Preface
Bachelor theses of Department of International Development Engineering, Tokyo Instituteof Technology were presented successfully on August 4, 2015 and February 29, 2016,
respectively. This technical report consists of the abstracts of those theses.

TECHNICAL REPORT OF INTERNATIONAL DEVELOPMENT ENGINEERING
TRIDE-2016-04

TABLE OF CONTENTS(COMPLETING IN SEPTEMBER 2015)
INDOOR RADIO PROPAGATION PREDICTION UTILIZING DIFFUSE SCATTERING
MODEL....................................................................................................... HAITAO PANG 1
DEVELOPMENT OF ADHESION FORCE MEASUREMENT APPARATUS FOR GLASSGLASS POINT CONTACT....................................................................................................... MIKHAIL SALYUKOV 3
SELECTIVE CATALYTIC REDUCTION OF NITROGEN OXIDES WITH PROPENEOVER NB/TIO2 CATALYST SUPPORTED BA....................................................................................................... TAKUYA YONEDA 5(COMPLETING IN MARCH 2016)
THERMAL ANALYSIS OF LITHIUM EVAPORATION PROCESS TO FABRICATELITHIUM-DRIFTED SILICON DETECTOR FOR A DARK-MATTER SEARCH PROJECTGAPS....................................................................................................... YOSEI INOUE 7
APPLICABILITY OF A 3D NUMERICAL MODEL FOR ASSESSING THE
EFFECTIVENESS OF WOODEN PILE BREAKWATERS....................................................................................................... SHOYA SEKIGUCHI 9
IMAGE MATCHING USING AFFINE-INVARIANT GAT CORRELATION METHOD....................................................................................................... TIANSHENG JIN 11
SEPARATION OF NITROGEN HETEROCYCLIC AND HOMOCYCLIC COMPOUNDSCONTAINED IN ATMOSPHERIC RESIDUE BY SOLVENT EXTRACTION....................................................................................................... AKIRA HASEGAWA 13
SCALE-UP THE PRODUCING OF FUNCTIONAL COMPOST AND EXAMINE THE
DISEASE SUPPRESSING EFFECT....................................................................................................... TAKUYA MITSUHASHI 15
INITIAL PARAMETER SETTING IN THE PROPAGATION ESTIMATION BASED ON
EM/SAGE ALGORITHM....................................................................................................... TOKIO MIYAKE 17

全球高解像度人工排熱データベースの構築....................................................................................................... トウ ゲツ 19
FEASIBLE STUDY OF SPACE DEBRIS REMOVAL BY USING ELECTROMAGNETIC
FORCE....................................................................................................... JUN MITANI 21
EFFECT OFMICROBIAL PRETREATMENT FOR OIL IN METHANE FERMENTATIONFROM WASTEWATER CONTAINING SOYBEAN OIL....................................................................................................... TAKUYA MAEKAWA 23
大域的射影変換相関法を用いたテンプレートマッチング....................................................................................................... チョウ イセイ 25
INFLUENCE OF CURING WATER CONTAINING VARIOUS IONS ON PERMEABILITY
OF CONCRETE AND ITS APPLICATION TO WATER SUPPLY CURING METHOD....................................................................................................... KAZUKI ISHIHARA 27
RELATIONSHIP OF AUTOMOBILE USE WITH URBAN RESIDENTIAL ZONESCLASSIFICATION AND THE TRANSITION....................................................................................................... TIANZI LU 29
NUMERICAL ANALYSIS OF TSUNAMI OVERFLOW BEHIND COASTAL DYKES....................................................................................................... TOMOYA NAKAMURA 31
EFFECTS OF ARC CURRENT AND VOLTAGE BETWEEN ELECTRODES ON ARC REIGNITION....................................................................................................... TADAYUKI OMATA 33
ANALYZING LINKAGES BETWEEN SOLID WASTE MANAGEMENT AND OTHERURBAN DEVELOPMENT SECTORS IN DEVELOPING COUNTRIES: THE CASE OFDHAKA CITY, BANGLADESH................................................................................................. SHINNOSUKE SAWAMURA 35
東アジア域内におけるバルク貨物コンテナ化の要因分析....................................................................................................... 米澤 祐介 37
APPLICATION OF NON-LINEAR CONJUGATE GRADIENT METHOD INEXPECTATION MAXIMIZATION METHOD FOR THE PERFORMANCEIMPROVEMENT OF RADIO CHANNEL PARAMETER ESTIMATION....................................................................................................... YUNYI YAO 39
CONCEPT STUDY OF A NANO MARS LANDER WITH EXTENDABLEAERODYNAMIC DEVICE....................................................................................................... YUTA IMAI 41
IMAGE CODING BY SLANT VECTOR EMBEDDED DISCRETE COSINE TRANSFORM....................................................................................................... KENTO ITAI 43

A PROTOTYPE OF ENERGY HARVESTING EQUIPMENT FOR COMPOST HEAT....................................................................................................... KOOMOK LEE 45
LIQUID-LIQUID EQUILIBRIUM OF SODIUM WITH ORGANOPHOSPHORUS ACID AS
EXTRACTING AGENT....................................................................................................... NOBUYOSHI MORI 47
FACE RECOGNITION UNDER VARIOUS LIGHTING CONDITIONS USING RELATIVEKARHUNEN–LOÈVE TRANSFORM....................................................................................................... ミョウ ゲツ 49
INFLUENCE OF WATER CEMENT RATIO, INITIAL CHLORIDE CONTENT AND
CHLORIDE FIXING ADMIXTURE ON CORROSION OF STEEL BAR IN MORTAREXPOSED TO MARINE ENVIRONMENT....................................................................................................... KOKI HASHIZUME 51
ENVIRONMENTAL STRATEGIES OBSERVED IN ENTERPRISE COOPERATION IN
JAPANESE AUTOMOTIVE INDUSTRY....................................................................................................... KYOSUKE TANAKA 53
THE PROTOTYPE OF SIDE-CONTACT TYPE ELASTIC MULTI-BEAM USING PDMS....................................................................................................... MAI NGOC TRUNG 55

Indoor Radio Propagation Prediction utilizing Diffuse Scattering
Model
Student ID: 11_22001
Name: Haitao PANG
Supervisor: Junichi TAKADA, Kentaro SAITO	  	 direction (𝜃, 𝜑), so integrating the above equation over all
directions gives the energy density
4𝜋𝐼
(3)
𝑊=
𝑐

1. Introduction
In wireless communication systems designs, it is important to
identify the characteristics of multipath effect, which resultsfrom myriad reflections and diffractions from walls, people andsmall objects in the propagation channel. The power delay
profile (PDP) is the intensity of a signal received as a functionof time delay. The PDP gives the time-domain signal spread in
the multipath radio propagation, and it is important for thedesign of wireless communication system.
There are many existing techniques for predicting such
multipath characteristics. For example, ray-tracing models basedon geometric optics, finite-difference time-domain (FDTD)
models, method of moment (MOM) models are among the
popular ones. Although these models are proved to be accurate
to some extent, they are time-consuming and they require
specific inputs such as detailed geometry and accurate
electromagnetic (EM) properties, which are not easy to get andthus quite unreliable sometimes.
On the other hands, the confinement of an indoor
environment and the resemblance between room acoustic androom electromagnetics suggests applicability of existing
methods in acoustics to indoor EM propagation. In [3] and [4],some of established acoustic knowledge is tested for EM
scenarios. In this paper, we introduce a model for calculating
PDP for an enclosure, which requires only three parameters:
volume of the room, the surface area of the room and the overall
equivalent absorption rate of the room surfaces. Experiment wasalso performed to verify the effectiveness of such an model.

Assuming only a fraction 𝛼 of overall incoming intensity isabsorbed by indoor surface area A. Again knowing that 𝐼(𝜃, 𝜑)is independent on any direction, the total absorbed power 𝑃!"#
is!!

𝑃!"# = 𝛼𝐼𝐴

!/!

𝑑𝜑
!

𝑐𝑜𝑠𝜃𝑠𝑖𝑛𝜃𝑑𝜃 = 𝛼𝐴𝜋𝐼
!

𝛼𝐴𝑊𝑐
=
4

(4)

Under the law of conservation, the energy emitted inside theroom is either dispersed into the room volume or absorbed by
the indoor surfaces.
𝑑𝑊 𝛼𝐴𝑐(5)	
  𝑆(𝑡) = 𝑉
+
𝑊	
  
	
  
𝑑𝑡
4
	
  
	
  
When the source is turned off 𝑆(𝑡) = 0 , then the above
homogeneous differential equation can be solved as
𝑊 𝑡 = 𝑊! 𝑒 !!!" ,  
(6)
𝑐𝛼𝐴
4𝑆
𝑤𝑖𝑡ℎ    𝛿 =, 𝑊! =8𝑉
𝑐𝛼𝐴This is also called as Sabine's equation. It describes the indoor
power delay as a log linear function.
2.2 Free mean path and in-room PDP (IPDP) model
The free mean path 𝑙! between reflections is the total path
length divided by the number of wall collisions N during time t.
According to [1][4], 𝑙! can also be derived as relative to total
volume V, total surface A and some constant F. F is dependentof the room shape. For simplicity we use 4 for typical rooms [4].
𝑐𝑡 𝐹𝑉 4𝑉
(7)
𝑙! = ≡≡𝑁
𝐴
𝐴

2. Theories
2.1 Sabine's formula
Back to the beginning of the 20th century, W.C. Sabine has
conducted various experiment and proposed an equation forindoor acoustics [1][2][3]. This equation is valid under two
assumptions: total diffuse (or isotropic) field and energy
conservation. Consider a narrow ray tube in direction (𝜃, 𝜑),the rays of intensity is	  (1)𝑑𝐼(𝜃, 𝜑) = 𝐼(𝜃, 𝜑)  dΩThen the characteristic time 𝑡! that a given set of rays makes
one reflection is𝑡! 8𝑉
𝑡! = 2 =
(8)	
  
𝑐𝐴
𝑐

The corresponding energy density at a point is found by theintensity divided by the velocity of EM waves, equals to the
speed of light𝐼(𝜃, 𝜑)
(2)
𝑑𝑤 =
𝑑Ω
𝑐

Consider the overall average power reflection coefficient
𝛾 =1−𝛼(9)	
  Then the average power level of a bundle rays after n reflections
is approximated by𝛾!
𝑃! = 𝐷 !
𝑑!
(10)	
  

Since the field is fully diffuse, the intensity is independent of

D is a function of the transmitting and receiving antennas and

11The center frequency is set to 5 GHz. And for the purpose of
maximizing delay domain resolution, the bandwidth is 1 GHz(4.5 GHz to 5.5 GHz) for this experiment.

the transmitted power.
By normalizing the power to 𝑃! and initializing the delay timeto 0 s, the power delay levels can be approximated by
𝑃𝐷𝑃! = 1                                    𝜏 = 0,                      𝑓𝑜𝑟  𝑛 = 0𝛾!
𝑡!
𝑃𝐷𝑃! = !           𝜏 = (2𝑛 − 1), 𝑓𝑜𝑟  𝑛 ≠ 0	
  4𝑛2

3.2 Data processing
Since the data output for delay of the VNA is in frequency
domain, we calculated the channel impulse response of eachmeasurement point using inverse Fourier transform (IFT). Then
we average the 9 experiment data around each receive antenna
location to suppress phasing effect to obtain delay profile foreach pair of antennae BA, BC and BD. Then we use the delay
profile between 100 ns and 160 ns to calculate the decay rate2𝛿 of the log linear function with least square method. It isfound to be 0.19 dB/ns. From the calculated data and with use of
the volume of the room V and the inner surface of the room A
we can calculate the overall equivalent absorption coefficient, in
this experiment it is found to be 0.47.
𝑐𝛿𝐴
𝛼=
(12)	
  
8𝑉

(11)	
  

2.3 The proposed model
In previous researches, the Sabine's equation predicts an log
linear power decline and the experiment did show the sametendency in the late reflections but it failed to predict the power
profile of early reflections [4]. Dunens and Lambert havesuggested that reverberation described by Sabine's equation only
occurs after several reflections, or more exactly after 8𝑙! /𝑐  𝑠 to
10𝑙! /𝑐 s [5]. On the other hand the IPDP model's prediction
does not match well when there are many reflections. So we
propose a model that combines two models, with a line-of-side(LOS) component, early reflections (before 5𝑙! /𝑐 s) withpiece-wise power profile predicted by IPDP model, and latereflections (after 9𝑙! /𝑐 s) with log linear power decline
predicted by Sabine's equation. The model are given as
following

Then with 𝛼, V, A and the detected LOS component, we cancalculate the overall PDP with the formulations given by the
proposed model. Figure 1 shows the predicted and detected
outcome for the experiment of BA.

𝑃𝐷𝑃! 1 − 𝛼 !
𝜆 !
, 𝑃𝐷𝑃! =
    
4𝜋𝑑!
4𝑛!
𝑑!
𝑡!
,
𝜏! = (2𝑛 − 1) + 𝜏!
                    𝜏! =𝑐2
with the above parameters, the power profile is
𝑃𝐷𝑃! = 𝑃! 𝐺! 𝐺!

0        , 𝑓𝑜𝑟  𝜏 < 𝜏!

4. Conclusion

𝑃𝐷𝑃! − 𝑃𝐷𝑃!
(𝜏 − 𝜏! ), 𝑓𝑜𝑟  𝜏 > 𝜏 ≥ 𝜏!
𝜏!
𝑃𝐷𝑃! − 𝑃𝐷𝑃!
(𝜏 − 𝜏! ), 𝑓𝑜𝑟  𝜏! > 𝜏 ≥ 𝜏!
𝜏!
𝑃(𝑡) =
𝑃𝐷𝑃! − 𝑃𝐷𝑃!
(𝜏 − 𝜏! ), 𝑓𝑜𝑟  𝜏! > 𝜏 ≥ 𝜏!
𝜏!
𝑃𝐷𝑃! − 𝑃𝐷𝑃!
(𝜏 − 𝜏! )  , 𝑓𝑜𝑟  𝜏! > 𝜏 ≥ 𝜏!   
2𝜏!
4𝑆 !!!"#
𝑒 !!     , 𝑓𝑜𝑟  𝜏 ≥ 𝜏!
𝑐𝛼𝐴

In analogy to applied acoustic theories, we proposed a
prediction model for indoor radio propagation. Experiment was
conducted to verify the model and the results showed wellagreement between the model's prediction and the detected data.
Still as part of the future work experiment conducted in moreother rooms are needed. Although in the EM case polarization isimportant, in this research it is considered as vertical-verticalpolarized. Therefore we need further consideration regarding topolarization in future works.

3. Experiment

Reference

3.1 Experiment backgroundThe experiment was conducted in a room full of small objects.
The width, depth, and height is 6.34 m, 5.65 m, and 3.46 m
respectively. Two bi-conical antennae were used as transmitting
and receiving antenna. The directivity of both antennae isomni-directional in both horizontal and vertical plane. Bothantennae are set to be 1.2 m above ground. The transmitting
antenna is located in the center of the room described as point B.
And the receiving antenna is located at point A, C and D, withthe distance to point B is 1.7 m, 2.2 m, 3 m respectively. In
order to suppress the effect of rapid phasing, the measurement
for each point was conducted at the measurement grid, which
consists of 9 points within the 20 cm, by 20 cm square. A vector
network analyzer (VNA) model No. VNB 8 produced by Rhode
Schwarz is used as signal generator and also spectrum analyzer.

[1] H.Kuttruff, Room Acoustics, Fifth Edition, Spon Press[2] W.C.Sabine, Collected Papers On Acousitcs, 1923, Harvard
University Press[3] J.B. Andersen et al., Room Electromagnetics, Antennas andPropagation Magazine, IEEE (Volume 49, Issue: 2)[4] C.L. Holloways et al., A Model for Predicting the Power Delay
Profile Characteristics Inside A Room, IEEE Transactions On VehicularTechnology (Volume 48, No.4, July 1999)[5] E.K.Dunens and R.F.Lambert, Impulsive Sound-level Response
Statistics in A Reverberant Enclosure, Journal Acoustics Society
America (Volume 61, No.6 pp.1524-1532, 1977)

Acknowledgments
I want to express my gratitude toprofessor Takada, Dr. Saito and other lab members, without
whose support and encouragement I would be unable to finish
this research.

22

Development of adhesion force measurement apparatus for glass-glass point contact
Student Number: 11B11718 Name: Mikhail SALYUKOV Supervisor: Kunio TAKAHASHI
1 Introduction
Understanding of the adhesion behavior between two
solids is important in various fields of engineering, especially in designing the micro manipulation devices. JKR
theory [1] explains the adhesion phenomena in a point
contact between two solids by the work of adhesion. TMO
theory [2] expands JKR theory by taking into account theeffect of stiffness of the measurement system. Both theories are based on assumption of energy minimum condition, thus the path of the force curve during the contact
process can be uniquely determined. However, the loading-unloading paths of the force curve are different in thepractical contact system. Researches on adhesion hysteresis in the point contact using polymeric materials havebeen done to determine the main factor of the phenomena,and factors related to the properties of polymer materials
are identified to influence the adhesion hysteresis[3-7].The experiments on adhesion hysteresis using
non-polymeric materials are also needed to be conducted
to know if the adhesion hysteresis is induced only by theproperties of polymeric materials. In this paper, we developed the adhesion force measurement apparatus forglass-glass point contact i.e. contact between a convex
glass lens and the plane parallel glass plate, by adjusting
the parameters of the apparatus to achieve high measurement resolution ability and linear elasticity under highload conditions, which are the requirements for the apparatus that is capable of observing the adhesion hysteresis
in the point contact between the non-polymeric materials.

Fig.1

Schematic illustration of the TMO Point Contact
Model

2 Preliminary Estimations
For consideration of the requirements for the apparatus,
we used the TMO point contact model (Fig.1) to estimate
the range of the force curve and the required load resolution for its measurement. In the model, the force F working between two objects is obtained by eq.(1) as a functionof contact radius a and gross displacement Zt. The maximal adhesion force can be obtained by eq.(2).
F


2kEa
a2 
  Z t 22Ea  (1   )k 
3R 

Fadh  

3R
2

Fig.2

Schematic illustration of the apparatus

stiffness k must be decreased in order to decrease thechange of load per unit displacement, and by that increase
the load resolution of the apparatus. To obtain the necessary load resolution, we designed a plate spring mechanism with a spring constant of ks=9882[N/m] and set theparameter of stiffness to this value.

(1)

(2)

3 Experimental
Based on the Preliminary estimations as above, adhesion
force measurement apparatus for glass-glass point contact
was developed as shown in Fig.2. An optical plane parallel
glass plate (BK7,SIGMAKOKI Co.) was fixed in the center of a plate spring mechanism. Glass lens (BK7,SIGMA
KOKI Co.) was set on a stage under the glass plate. ForceF was measured using three load cells (LUB-B-10N,KYO
WA Co.) set under the table with the lens. Motorized stage
with a resolution of 0.73μm per step was used for manipulation of the gross displacement. The speed of the stage
was set to 1step per sec. and the waiting period between
steps to 5 sec. in order to minimize the dynamic influence.
The contact experiment of two glass objects was conducted three times each for four different values (73μm,
146μm, 365μm, 730μm) of the maximal gross displacement Ztmax, within the linear elasticity of the apparatus. An
optical microscope was used to observe the contact areaand measure the contact radius a through an observation
window on the upper side of the plate spring. Both param-Among all the constant parameters in eq.(1) and eq.(2),curvature radius of the lens R and the stiffness of themeasurement system k can be adjusted by the design of
the apparatus. Considering the high load conditions of theexperiment, pressure applied to the contact area must be
lowered, to ensure the linear elasticity of the apparatus.
The maximal adhesion force must be enhanced, taking
into account the finite load resolution of the apparatus.
From eq.(1) and eq.(2), it can be assumed that the curvature radius R must be increased to satisfy these conditions.
Thus, the parameter of the curvature radius was set to
R=2[m]. Using this value of curvature radius R and thephysical properties of the glass (Δγ=0.03[J/m2]), The
maximal adhesion force can be calculated from eq.(2) to
be Fadh= -0.28[N]. Thus, the load resolution of the apparatus needs to be no less than 0.01[N] to accurately measure the maximal adhesion force. Considering the installation of a motorized stage with a finite displacement resolution to control the gross displacement of two objects,

3eters F and a were measured simultaneously in the contact
process.

4 Results and Discussions
The required load resolution of the apparatus wasachieved by the proper design of the glass lens and theplate spring. Adhesion force was observed and measured
with an accuracy of 0.01[N] in the point contact experiment of two glass objects, as demonstrated in Fig.5.
Measured Fadh could be assumed to have dependence on
Ztmax, as shown in Fig.5. The observation of the contact
area was done throughout the experiment, and the Newton’s rings (i.e. a concentric interference pattern created by
the reflection of light between two surfaces) were observed. As shown in Fig.6, the contact radius a was measurable as a radius of a dark reflection spot at the center ofthe pattern, when the force F was relatively large. In caseof when the force F was small (e.g. at the beginning of thepoint contact), the contact radius a could not be measured
due to the bright fringe formed in the center of the Newton’s rings. This phenomenon could be attributed to theexistence of the substances such as sub-micron sized particles on the surfaces of the two glass objects.

Fig.4

Load resolution of the apparatus (Ztmax=730μm)

5 Conclusions
Adhesion force measurement apparatus for glass-glass
point contact was developed using the TMO Point contact
model for estimation of the necessary values of the parameters R and k, in order to achieve the high load resolution and linear elasticity under the high load conditions of
the experiment. The maximal adhesion force Fadh wasmeasured under four different maximal gross displacement Ztmax. From the results of the adhesion force measurement experiment, the apparatus was confirmed to havethe load resolution required to measure the adhesion force
in the glass-glass point contact. From the experimental
results, the maximal adhesion force Fadh is suggested tohave dependence on the maximum gross displacement
Ztmax. The contact radius a was measurable within the highload conditions, as a radius of the center of the Newton’srings. Effect of the sub-micron size particles on the surfaces of the two glass objects is considered to explain theinability to measure the contact radius a under a low load.

Fig.5

Relation between maximal gross displacement Ztmax
and maximal adhesion force Fadh

References[1] K. L. Johnson, K. Kendall and A. D. Roberts: Proc. R. Soc.
London A 324 (1971), pp. 301-313.
[2] K. Takahashi, R. Mizuno and T. Onzawa: J. Adhesion Sci.
Technol., Vol. 9, No. 11 (1995), pp. 1451-1464.
[3] K. L. Johnson: Tribology International, Vol. 31, No.8 (1998),
pp. 413-418[4] G. Y. Choi, S. Kim and A. Ulman: Langmuir, Vol. 13, No. 23(1997), pp.6333-6338[5] H. She, D. Malotky and M. K. Chaudhury: Langmuir, Vol. 14,
No. 11 (1998), pp.3090-3100[6] Z. Wei, M. He and Y. Zhao: J. Adhesion Sci. Technol., Vol.
24, No. 6 (2010), pp. 1045-1054.
[7] H. Kesari, J. C. Doll, B. L. Pruitt, W. Cai and A. J. Lew:
Philos. Mag. Lett., Vol. 90, No. 12 (2010) pp. 891–902

Fig.6 Newton rings observed at the contact surface
under the low load (left) and high load (right)

4

Selective Catalytic Reduction of Nitrogen Oxides with Propene over Nb/TiO2
catalyst supported Ba
Student Number: 11-27027

Name: Takuya Yoneda

1. Introduction

Supervisor: Hirofumi HINODE

In the MM method, BaO (WAKO) is used prior to
mixing with Nb/TiO2 prepared earlier. The mixing was
carried out by hand using a mortar and pestle with a little
amount of ethanol. Finally, the catalysts were crushed
and sieved to 0.71-1.00 mm [4]. The catalyst preparedby MM method was designated BaO+ Nb/TiO2.
The HC-SCR activity experiments were carried out
in a fixed-bed flow reactor. The reactant gas wascomposed of 1500 ppm NO, 10% O2, 1500 ppm C3H6and He as a balance gas. 0.8~1.2 g catalyst was usedwith a corresponding space velocity of 13000 h-1. The
temperature was changed stepwise from 150℃ to 550℃.
NO and NO2 concentration were analyzed by NOx
analyzer (Shimadzu, NOA-7000). N2O, CO2 and CO
were analyzed by gas chromatograph (GL Science, GC323w for N2O; GL Science, GC-390 for CO2 and CO).
The catalysts were characterized by TG-DTA, XRD,
and N2 adsorption (Autosorb 1MP/TSU, BET analysis).

Nitrogen oxides (NO, NO2 and N2O) are major
sources of atmospheric environmental problems such as
photochemical smog, acid rain, ozone depletion andgreenhouse effects. Furthermore, presence of nitrogenoxides in the atmosphere can cause problems to humanhealth. Most of the NOx comes from automobiles(48.5%) and power plants (46.2%) using fossil fuels [1].
Nowadays, three-way catalysts (TWC) are generally
used to reduce NOx in automobiles. This method can
reduce NOx with high efficiency at specific air to fuel(A/F) ratio. However, the development of lean-burnengines that have higher fuel economy and cleaner
emissions requires catalyst for NOx reduction that canfunction also at higher A/F ratio which cannot be
achieved using TWC only. One potential method to
reduce NOx in exhaust gas is selective catalytic
reduction of NO using hydrocarbon as reducing agent(HC-SCR of NO) [2]. Previous study showed that TiO2
supported Nb catalyst was effective in HC-SCR of NO[3]
Therefore, in this study, the catalytic activities of BaNb/TiO2 catalysts prepared by two different methods,
impregnation (IM) and manual mixing (MM), were
investigated for HC-SCR of NOx using propene as
reducing agent.

3. Results and discussion
Figure 1 shows the conversion of NO to N2 overTiO2, Nb/TiO2, 10wt% Ba/Nb/TiO2 10wt%
BaO+Nb/TiO2 (BC and AC) catalysts. Nb/TiO2 catalyst
shows the highest activity at 350℃.

2. Experimental
Nb/TiO2 catalyst was prepared by impregnated method
using TiO2 (JRC-TIO-7) and C4H4NbO9 ・(H2O)5(ALDRICH) as precursors with the objective molar
ratio for Ti and Nb[4]. First, C4H4NbO9 ・(H2O)5 wasdissolved in 300 ml deionized water with continuous
stirring and TiO2 was added to the solution and mixed.
The resulting mixture was filtered, dried at 100℃ for 8
h and calcined at 550 ℃ in air for 5 h. The catalyst
prepared by IM method was designated Nb/TiO2.
In the case of consecutive IM method, Ba(NO3)2(Wako) was dissolved in 300 ml of deionized water andmixed with Nb/TiO2. Then the mixture was stirred atroom temperature for 24 h and dried at 100℃ for 12 h.
The catalyst prepared by consecutive IM method was
designated Ba/Nb/TiO2.

Fig.1. Catalytic activity of TiO2, Nb/TIO2, 10wt%Ba/Nb/TiO2,
10wt%BaO+Nb/TiO2 BC, 10wt%BaO+Nb/TiO2 AC for the reductionof NO to N2 using C3H6 as a reductant.

Figure 2 shows the conversion of NO to N2 over
BaO+Nb/TiO2 catalysts by MM method with Ba

5

loading levels from 0-20 wt%. Catalyst with 0% BaO
showed the highest catalytic conversion at 350℃
followed by 1% and 5%. However, further increase of
Mo loading to 10% and 20% showed a decrease inactivity as compared to the bare Nb/TiO2 catalyst.10%
and 20% showed the negative conversion at 400℃. BaO
has a storage capacity for any gas.[5] It was thought thatat lower temperature, NO was adsorbed to BaO, whichthen be released at 400 ℃ and caused negative
conversion.
Fig.4. Catalytic activity of BaO+Nb/TiO2 MM method
catalyst for the reduction of NO to N2 not using C3H6 as a
reductant.

Figure 4 shows the conversion of NO to N2 over all
catalysts by IM and MM method with Ba loading levels
from 0-20 wt%, without C3H6. It can be seen that there
are much lower catalytic conversion compared to result
using C3H6 for almost all catalysts except 20% MM
method prepared catalyst. The result shows that theaddition of C3H6 is necessary for the catalytic
conversion of NO to N2 oxidation-reduction reaction
while a decrease in the conversion to NO2.
..
Fig.2. Catalytic activity of BaO+Nb/TiO2 MM method catalyst for
the reduction of NO to N2 using C3H6 as a reductant.

4. Conclusions
The catalyst prepared by MM method BaO+Nb/TiO2
catalyst showed catalytic activity towards selective
catalytic reduction of NO to N2 with C3H6 as reducing
agent. Compared to the consecutive IM method, MM
method exhibited higher activity and showed highstorage capability. The addition of BaO with MM
method reduced the activity of catalyst.

References

Fig.3. Catalytic activity of BaO+Nb/TiO2 MM method catalyst forthe conversion of NO to NO2 using C3H6 as a reductant.

Figure 3 shows the conversion of NO to NO2 over
BaO+Nb/TiO2 catalysts by MM method with Ba
loading levels from 0-20 wt%. It can be seen that there
is a sharp increase in the conversion of NO to NO2 inwhich the conversion of NO to N2 decreases (Fig. 2)
with 20% MM method prepared catalyst convert NO to
NO2 starting at a lower temperature than bare Nb/TiO2.
The result shows 20% MM method prepared catalyst
has a storage capability for NO2.

[1] Norio Arai Techno-System Corp (1997)[2] R.Burch, T.C.Watling, Appl.Catal.B, 11, 207 (1997)[3] Megumi Makii; Master Thesis, Tokyo Institute ofTechnology (2007)[4] Yang Wang; Master Thesis, Tokyo Institute ofTechnology (2010)[5] Naoki Takahashi; Doctor Thesis Nagoya University(2007)

6

Thermal Analysis of lithium evaporation process
to fabricate lithium-drifted silicon detector
for a dark-matter search project GAPS
Student Number：12 01717

1

Name：Yosei Inoue

Supervisor：Daisuke Akita

Introduction

It is said that in our universe a substance called dark
matter exists in addition to normal substance.
Various theoretical models of dark matter have been
proposed. Cold Dark Matter (CDM) , such as supersymmetric neutralino, is a candidate and is expected
to generate antideuterons via pair annihilation or decay. GAPS project currently persued by JAXA andseveral institutes in Japan and US aims to search for
antideuterons originated from CDM by using lithiumdrifted silicon semiconductor detectors.[1]In order to get a high antideuteron sensitivity, it isnecessary to enlarge the detector fiducial volume while
ensuring the performance of the detector. Among thedetector manufacturing process, it is known that theuniformity of the heated temperature of silicon wafer
during the lithium evaporation process in vacuum is essential to ensure good detector quality. Also, it is known
the smaller the diﬀerence of the temperature between
the heat source and the silicon wafer are, the shorter
the production time of the detector becomes. To realize
stable mass production of the detector, it is important tounderstand the heat transfer mechanism of the heating
device and specify the factors to uniform the temperature and reduce the diﬀerence of temperature between
the heat source and the silicon wafer.
In this paper, I conducted a numerical modeling and athermal analysis of the heating device and compared thecalculated temperature with the actual measured datain order to consider the heat transfer mechanism. The
temperature measurement was conducted by Shimazdu
Co., Ltd., which co-develops the silicon detector for the
GAPS project.

Figure 1: Evaporation system

when they are piled up, there must be some non-contact
area with a tiny gap. Heat transfer in the contact area
is dominated by the conduction heat transfer, and thenon-contact area must be dominated by the radiation
heat transfer. So, I anticipated that these mappings influence the nonuniformity of the temperature.
In the thermal analysis, the contact area and the contact conductance per unit area must be assumed. However, it is diﬃcult to evaluate them accurately. In thispaper, the contact area is simulated by a model, and thecontact conductance is treated as a parameter in a realistic range between 80 and 2000 W · m−2 · K−1 .[3] Fourcases of 80, 100, 1000, 2000 W · m−2 · K−1 , called simulation (1)〜(4), are assumed, respectively. The Model
1 in Figure 2 shows the assumed contact area. In order
to confirm it is correct, it must be verified the Model1 reproduces experimental result and the Model 2 andthe Model 3 in Figure 2 do not reproduce experimantal
result.
At 1 atm environment, there is gas in the small gap of
the non-contact area. Gas in the small gap couples theheat transfer between the both surfaces that can be ap2 Thermal Analysis
proximated by direct contact heat transfer in the whole
The thermal analysis was conducted by using a thermal area (equal to Model 2 in Figure 2). The simulated temanalysis software, Thermal Desktop, which uses the fi- perature was compared with the experimental results at
nite diﬀerence method and the Monte Carlo method.
1 atm, too.
In vacuum, heat transfer is dominated by conduction
heat transfer and radiation heat transfer. To reproduce
the nonuniformity of the temperature at the silicon sur- 3
Results
face, I focused on the diﬀerence of the heat flux between
conduction heat transfer and radiation heat transfer. Figure 3 shows the comparison of the simulated temperGenerally, it is known that the heat flux of conduction atures of Model 1, 2, and 3 with the experimental results
heat transfer is much larger than that of the radiation of silicon wafer in vacuum. Futher, simulation (2) andheat transfer. Figure 1 shows a conceptual diagram of (3) of Model 2 and 3 are omitted because simulation (2)and (3) must be placed between simulation (1) and (4).
the evaporation system.
The experimental data locate between simulaion (2)The heating device consists of a hotplate, a holder,a silicon wafer, and a cover. All of their surfaces are and (3) for Model 1. Therefore, the simulated tempermachined flat but are not completely flat. Therefore atures reproduce the experimental data well. On the7Figure 4: Comparison of the simulated temperature
Figure 2: Assumed contact area and compared contact with the experimental data about the silicon wafer temarea (wafer diameter : 4 inch)
perature at 1 atmother hand, the experimantal data locate out of simulated range for Model 2 and Model 3. Therefore, thesimulated temperatures don’t reproduce the experimental data. From the above, the validity of Model 1 isshown.
Focused on simulation (2) and (3) of Model 1, the temperature distribution at silicon surface is in the range of±0.70 ∼ 2.07 K. Also, the diﬀerenece of the temperarure between hotplate and silicon wafer is about 100
K.
Figure 4 shows the comparison of the analysis resultswith the experimental data of silicon wafer at 1 atm.
The experimental data locate between the simulation(2) and (3). So the entire surface contact model reproduces the experimental data at 1 atm well. This result
corroborates the validity of the numerical model.
Focused on simulation (2) and (3), the temperature
distribution at silicon surface is in the range of ±0.21 ∼0.58 K, and we can find it is improved compared with
it in vacuum. Also, the diﬀerence of the temperature
between hotplate and silicon wafer is about 20 K, andwe can find it is improved compared with it in vacuum.
From the above, the major factor of the nonuniformityof the silicon temerature and the diﬀerence of temperature between hotplate and silicon wafer is considered
to be the existence of the non-contact area between theparts. Also, we can improve them if we can make athermal condition corresponding to 1 atm in vacuum.

4

Conclusions

In this paper, I conducted a modeling and a thermal
analysis of the heating device for the lithium evaporation
process to produce lithium-drifted silicon detectors, andcompared the simulated temperature with experimental
data. As a result, the followings can be concluded:• The experimental data are well reproduced by theheat contact model shown by Model 1 in Figure 2.
• The major reason which causes the nonuniformityof the silicon temperature and the diﬀerence of temperature between hotplate and silicon wafer is considered to be the existence of the non-contact area
between the parts.
• Reproduction of the experimental data at 1 atm by
the entire contact model also confirms the validityof the model.
• The nonuniformity of the silicon temperature andthe diﬀerence of the temperature between hotplateand silicon wafer can be improved if a thermal condition corresponding to 1 atm in vacuum is realized.

Acknowledgments
I would like to thank Dr. Hideyuki Fuke, and Dr. ShunOkazaki, JAXA/ISAS and Mr. Minoru Yamada, Shimazdu Co., Ltd. for their instructions for this study.

References[1] Hideyuki Fuke. Report of the current state of acosimic ray antiparticle search project GAPS by apolar patrol balloon. Balloon Symposium2015[2] T.Aramaki. Antideuteron Sensitivity for the GAPS
Experiment. 2015. [pdf] Available at:⟨ http://
arxiv.org/pdf/1506.02513.pdf ⟩ [Accessed 18
February 2016].
[3] David G. Gilmore ed. Spacecraft Thermal Control
Handbook Volume 1: Fundamental Technologies

Figure 3: Comparison of the simulated temperaturesusing Model 1, 2, 3 with the experimental data about
the slicon wafer temperature in vacuum8Applicability of a 3D Numerical Model for Assessing
the Effectiveness of Wooden Pile Breakwaters
Student Number: 11_13752 Name: Shoya Sekiguchi Supervisor: Hiroshi Takagi
1.

each pile” and (5) “Thin vertical wall instead of piles”. Figures 2 and 3
show the case of “20.0cm spacing between each pile”. Table 1 indicate
the settings used in the numerical simulation.

Introduction

In developing countries, coastal cities often experience rapid
economic development because of their geographical advantages.
However, some detrimental effects from these developments are often
ignored. One of these negative effects is coastal erosion. Coastal
erosion is a process which occurs when beaches are approaching its
disequilibrium profile. If the beach receives less sand than outboundsand volume, an erosion likely occurs, causing an increase in coastal
vulnerability. In Phan Thiet, local people have installed wooden piles toprevent coastal erosion as a wave-breaking countermeasure. However,these piles are randomly placed and there has been no extensive
research conducted about the effects of these wooden piles. Therefore,
the purpose of this research is to develop the methods with a 3D
numerical model to assess the effectiveness of wooden pile
breakwaters.

+3.5m

∇
＿ 0.0m

- 0.4m60m

7.0m

Fig2. Geometry of simulation (cross-shore direction) and Wooden pilemodel assumed in Case 3 (alongshore direction)

Fig3. Observation points around the pile
Table1. Calculation settings

Coastal erosion in Phan Thiet

Item
Mesh size
Time step
Wave height
Wave period
Wave theory
Turbulence
LES SGS

Phan Thiet is a coastal city located in southern Vietnam. It is a
popular tourist spot with numerous resorts and hotels near the beacharea. Recently, the coastal areas of the city have been suffering fromsevere coastal erosion problems caused by coastal development such as
land reclamation and jetties. In Duc Long, a small coastal community
in Phan Thiet, several dozens of houses have been destroyed by serious
erosion problem and still a number of houses are on the verge ofdisappearance. According to the 2001 and 2010 coastline, the beachappears to have retreated towards the shore by about 40m. According to
Takagi (2014), the coastline would retreat by more than 30m as it
gradually approaches its equilibrium beach profile. The community has
set up wooden piles and sandbags to break waves and prevent erosion
but this has not showed any significant effects.

3.

+1.0m

+0.9m

-2.1m

Fig1. Coastal erosion in Phan Thiet city, Vietnam (January, 06, 2012)2.

Wooden Pile

4.

Outline3.47～100cm cube mesh
⊿t=less than 0.01sec
H=1.0m
T=8.0sec
Cnoidal theory
LES model
Smagorinsky

Assessment of wooden pile

This research proposes three criteria to evaluate the performance ofwooden pile breakwaters. The first criterion is the wave run-up height.
Figure 4 shows that the run-up height tends to decrease as the spacing
between piles is reducing. The second criterion is the maximum
bending stress acting on the pile. In Figure 5, the “Wall” case has thelargest bending stress and the stress is much larger compared to othercases. Figure 5 indicates that the bending stress acting on the pile tends
to increase as the spacing between the piles is reduced. One of thereasons for this result is that an increase of the spacing between piles
releases wave energy by passing it through between the piles. Given thebending strength of Larch with a diameter of 10.1~13.8cm is about
36~57 MPa, however, the pile would not snapped by the impact ofwaves considered in this study. On the other hand, the vertical wall issubjected to high bending stresses because the structure receives theentire wave energy.

Numerical analysis

In this research, numerical analysis was carried out using IhFoam
which is a solver of OpenFOAM, which is an open-source software.
IhFoam is a three-dimensional two-phase flow solver using VOF
method. Figure 2 shows the geometry of this simulation which wasderived from the measured bathymetry of Duc Long. The simulation
was carried out for five cases: (1) “No pile”, (2) “Single pile”,(3) ”20.0cm spacing between each pile”, (4) “10.0cm spacing between

9

6.0m

The velocities were observed at five points in Figure 3. Figure 7 shows
the result of calculation and the length of vectors is the amount ofdimensionless sediment transport Φnet . According to Figure 7, atPoint3 and Point4 the “Wall” case has a large effect in transporting thesand offshore. This can be explained by considering that the waves,which are mostly reflected by the wall, intensify wave-induced flows
towards offshore. Moreover, it is apparent that when the spacing
between piles becomes narrower, the sand is more likely transported
offshore. Finally, both of the “20.0cm spacing” and the “10.0cm
spacing” cases have a significant effect on transporting the sandoffshore at Point 5. One of the reasons for this result is that the spacing
between piles accelerates the velocity of waves which passes throughbetween the piles.

Fig4. The run-up heights and incline distances of the waves

Fig5. The maximum bending stress
The third criterion is the sediment transport around the piles based on
the velocities of the bottom flow inputted into the dimensionlesssediment transport calculation formula as suggested by Dibajnia and
Watanabe (1992). Inui et al. (1995) and Yamashita et al. (1996)
extended this formula asΦnet =

qnet (1−λ)
w0 d

Γ=

= 0.0023 ∙ sign(Γ)|Γ|0.5

3′3
uc Tc (Ω3c +Ω′3t )−ut Tt (Ωt +Ωc )(uc +ut )TT
u2c = ∫0 c u2 dt
Tc
2

,

T
u2t = ∫T u2 dt
Tt c2Fig.7 The amount of dimensionless sediment transport

(1.1)
(1.2)

5.

(1.3)

By coupling with the 3D numerical analysis, this research
proposed three criteria to assess the performance of wooden pile
breakwaters that aim at mitigating coastal erosion. The difference inwave run-up and velocity around the structures were clearly observed
according to the difference in the pile arrangement. This research
proved that the methodologies proposed in this study can be used todesign wooden pile breakwaters.

Ωj = 0if ωj ≤ ωcr { ′2w0 TjΩj = ωj ∙d

if ωj ≥ ωcr {
{
ωc =

1

u2c

2 sgw0 Tc

Ωj = (ωj − ωcr ) ∙Ω′j = ωcr ∙, ωt =

1

2w0 Tj(1.4)

d

2w0 Tjd
u2t

2 sgw0 Tt

Conclusion(1.5)

Referenceswhere Φnet is the dimensionless sediment transport, q net is thesediment transport volume per unit time and unit width, λ is the void
fraction, w0 is the sedimentation rate of sand, d is the particle size ofthe sand, s is the water specific gravity of sand, g is the accelerationof gravity, T is the wave period and ωcr , the function related in thesediment transport system, becomes 0 at the time of sheet flow. The
individual waves are defined by the zero-upcrossing method and j in Eq.
(1.4) will be replaced by c or t.

[1] Takagi H. et al., Coastal Vulnerabilities in a Fast-Growing
Vietnamese City, Coastal Disasters and Climate Change in Vietnam,
Elsevier, pp.157-171, 2014
[2] Dibajnia, M. and A. Watanabe, Sheet Flow under Nonlinear Waves
and Currents, Proc. 23rd Int. Conf. on Coastal Eng., ASCE, pp.
2015-2028, 1992
[3] 乾ら, 細粗混合砂のシートフロー漂砂量の算定式について,
海岸工学論文集, 第 42 巻, 1995
[4] 山下ら, 不規則波浪下でのシートフローによる漂砂量算定式,
海岸工学論文集, 第 43 巻, 1996
[5] 徳島県立農林水産総合技術センター森林林業研究所, すぎ(間伐) 丸太の強度, 技術情報カード, No.47, 2003

Fig6. The definitions of the symbols (Yamashita et al., 1996)10

Image matching using affine-invariant GAT correlation
methodStudent Number: 10B07895 Name: Tiansheng Jin Supervisor: Yukihiko YAMASHITA

1Introduction

Let f (x) and g(x) be an input image to be transformed
and a target image. Let fA (x) be the transformed
image of the input image f (x). Then we have

Image matching refers to a process of recognizing a
specific object in an image. Template matching is atechnique in image matching for finding small partsof an image which match a template image. A basic
method of template matching is the normalized crosscorrelation (NCC). NCC has qualities such as highaccuracy, high adaptable, and strong anti-jamming.
However it is sensitive to the deformation of images.
To this issue, the validity of a method using the global
affine transformation (GAT) correlation has been reported. In this study, an experiment using an improved
GAT correlation method in the image matching has
been performed. And the validity of the method is
examined.

2

Global affine transformation
correlation

2.1

Normalized cross-correlation

1fA (z) = pf (A−1 (z − b)),|A|which is different from the conventional fA (x) =1−1(z −b)). The reason why I apply the root de|A| f (Aterminant term is to insure the variance of transformed
image to beRone. Therefore, the correlation is given by
C(fA , g) = K √1 f (A−1 (x−b))g(x)dx. However, A|A|and b are directly embedded in the variable of function
f , it requires exhaustive trials and errors to determine
optimal A and b. To eliminate this step, I change thefunction by using the Gaussian function, let A and b
appear only in the Gaussian function. Furthermore, inorder to achieve a higher process speed, I introduce a
new edge direction function
0 (||v||) = 0)q(v) = n (||v||) > 0π(n−1)− π8 ≤ arg(v) < π(n−1)+ π8 )
4
4

Consider there are two images, the input image F
and the target image G, which are represented bygray level function f (x) and g(x) respectively, as F =f (x), and G = g(x), x ∈ K, where x denotes a 2D
location vector defined in the bounded 2D domain ofK. By using the theory of definite canonicalization:ZZ
f (x)dx = 0,g(x)dx = 0,
KKZZ
f (x)2 dx = 1,
g(x)2 dx = 1,
K

(3)

As a result, it reinforces the contribution of steep regions or edges to correlation for matching while suppressing or neglecting the contribution of flat regions
or grounds. Finally the criterion for GAT correlation
is given byK

we obtain the matching measure of normalized crosscorrelation simply given by:
Z
C(f, g) =f (x)g(x)dx.
(1)

JGAT

=

ZZZZ

G(Ax1 + b − x2 )δ>0 (q(∇f (x1 )),pq(∇g(x2 )))f (x1 )g(x2 ) |A|d2 x1 d2 x2 .(4)K

However, there is still the problem that the correlation measure in itself cannot compensate for geometricimage distortion such as affine transformation.

2.2

3

Global affine transformation correlation

Successive iteration bethod
for optimal GAT determination

GAT is a uniform affine transformation as applied to an
3.1 Optimization
input gray-scale image F. A 2D affine transformationfrom vector x to x′ can be expressed by
Following the necessary condition of maximization
x′ = Ax + b(2) yields both derivatives of JGAT equal to zero with re11
1

spect to each element of A and b. By defining
F (x1 , x2 )= G(x1 − x2 )δ>0 (q(∇f (x1 )),

1

=

x1

=

x2

=

x1 xT1=x2 xT1=q(∇g(x2 )))f (x1 )g(x2 ),(5)ZZZZ
F (x1 , x2 )d2 x1 d2 x2 ,(6)ZZZZ
F (x1 , x2 )x1 d2 x1 d2 x2 , (7)ZZZZ
F (x1 , x2 )x2 d2 x1 d2 x2 , (8)ZZZZ
F (x1 , x2 )x1 xT1 d2 x1 d2 x2 ,(9)ZZZZ
F (x1 , x2 )x2 xT1 d2 x1 d2 x2(10).

and substituting it into the differential equations, we
have

 

x1 x1 Tx2 x1 TA x1 xT1 −− x2 xT1 −
−
/1
1
σ2
1A−1 = O. (11)2Define




T
x1 T
P = x1 xT1 − x1/1
, Q = x2 xT1 − x2 x1 1 ,2(12)

To solve eq.(12), I used the Newton Raphson’s method.

3.2

Successive iteration method foraffine-invariant correlation determination
5

The successive iteration method provides the iterative
procedure for optimal GAT determination and calculation of the affine-invariant correlation. It first calculates the inital value of C0 = C(f, g) between theoriginal input and target images. Next determine the
GAT components of A and b, generate the transformed
image F∗ , and substitute F∗ into the input image F.
Next calculate the update value of C1 = C(f, g) between the renewed F and G, and compare C1 with C0 .
If the correlation value increases, substitute C1 into C0 ,and repeat the process, otherwise, output the value as
the GAT correlation.

4(b)Target(c)GAT(d)proposed GATFigure 1: Images of experiment(Image no.: 3)

and R = rI = σ2 1I. The equation is written as
AP − Q − rA−1 = O.

(a)Original

Image
number1
2
3
4
5

Table 1: Correlations
Original
GAT correlation
correlation Conventional Proposed
0.863265
0.947115
0.969616
0.753867
0.931570
0.9641430.701449
0.923636
0.953321
0.772810
0.899374
0.933814
0.783496
0.860661
0.905002

Conclusions

In this study, I conducted an experiment of templatematching by using the conventionial and the proposed
GAT correlation. By the proposed criterion, GAT correlation has been more accurately calculated. In thealgorithm I stop the process when C1 is smaller thanC0 . However if continue the calculation, a higher value
appeares sometimes. To get a more accurate correlation, we could use the maximal value among calculation
results. Strong practicality might be considered in recognizing areas while the computation speed becomes
higher. Also, in order to apply to perspective transformation, GAT and PPT are needed to be conbined.

Experiment

References

In the experiment, by using five photos of an object
with gradually changed visual angles and matchingwith the previously taken reference image, we can evaluate the performance of the GAT correlation methods.
Then I contrast the correlation values between the conventional GAT and the proposed edition. The correlation is indeed enhanced, however very limited.
The two GAT correlation methods have high accuracy than the original correlation. We can see the affine
transformation is more completed in the proposed version.

[1] T.Wakahara, Y.Kimura, A Tomono, “AffineInvariant Recognition of Gray-Scale Characters
Using Global Affine Transformation Correlation,”
IEEE Transactions on pattern analysis and machine intelligence, Vol 23, No.4, pp.384-395, 2001.
[2] T.Wakahara, Y.Yamashita, “Acceleration of GATcorrelation for distortion tolerant image matching,” ICPR 2012, November, 11-15, pp.746-749,
2012.

12
2

Separation of Nitrogen Heterocyclic and Homocyclic Compounds Contained in
Atmospheric Residue by Solvent Extraction
Student Number: 12B11555

Name: Akira HASEGAWA

Supervisor: Ryuichi EGASHIRA, Hiroaki HABAKI

Table 3. These heavy fractions mainly contained
cyclic compounds and the contents of alkanes werequite low. The content of nitrogen compounds in AR
was much higher than that in VGO. The content of
nitrogen compounds with shorter side chain and morearomatic rings was higher.
A major part of AR dissolved in heptane, nonpolar solvent to form the liquid extract, and the othersmall part remained as solid residue. The distribution
ratio of component i, m′i, in the non-polar solvent
extraction was defined as,
m′i = zi ∕ y′i(1)
where zi was the mass fraction of component i in thesolid residue ,and y′i was that in the liquid extract.
Figure 1 shows the effects of the number of carbon
atoms in side chain and that of aromatic rings on m′iin the extraction of AR by heptane. The m′idecreased, as the side chain lengthed and the numberof aromatic rings decreased. There was not clear
difference of m′i between nitrogen heterocyclic andhomocyclic compounds. However, since the nitrogencompounds contained in AR was those with shorterside chain and more aromatic rings as mentioned
above, the content of the nitrogen compounds in total

1. Introduction
The demand for heavy petroleum fractions havebeen shrinking recently, so that it is desired toconvert these fractions into lighter fractions, forwhich the demands are relatively high. This
conversion can be achieved by catalytic cracking [1].
Before this catalytic reaction, it is necessary andfavorable to remove nitrogen heterocyclic
compounds and polycyclic aromatic hydrocarbons inorder to avoid catalytic poisoning etc. In this thesis,
the solvent extraction using non-polar and polar
solvent[2-6] was applied to the separation of theabove compounds contained in the atmosphericresidue, a petroleum heavy fraction obtained from thebottom of atmospheric distillation tower in therefinery.
2. Experimental
Table 1 shows the conditions of the extraction
using non-polar solvent. The feed was atmosphericresidue (AR), whose boiling range was 623 K~.
Heptane etc. were used as non-polar solvents. Afterthe feed and solvent were equilibrated under
specified conditions, the liquid extract (solvent
phase) and solid residue were separated from eachother by filtration[2].
The conditions of the extraction by polar solvent
are summarized in Table 2. The following mixtures
were used as feeds: AR; the liquid extract from nonpolar solvent extraction (Table 1) of AR (DAAR);
heptane solution of vacuum gas oil (VGO) as a modelfor DAAR (MDAAR); etc. The VGO is the lighter
fraction of two obtained from the vacuum distillationof AR, of which boiling range was 623~823 K. In
some runs with polar solvent, the additive, such as,aluminum chloride, was used in the solvent in orderto enhance the extraction [3]. After equilibration of
feed and solvent phases, separatory funnel was used
to separate the raffinate and extract.
The samples of the feed, extract, solid residue,
and raffinate were analyzed by FT-ICR MS, chemical
luminescence (JIS-K 2609), potentiometric titration.
In FT-ICR MS analysis, more than ten thousands ofheterocyclic and homocyclic compounds contained in
AR or VGO were identified and quantified. The
contents of total nitrogen and total basic nitrogenwere determined by chemical luminescence andpotentiometric titration, respectively.

Table 1

Experimental conditions
non-polar solvent

Feed
Mass of feed
Solvent
Mass ratio of solvent to feed
Temperature
Time

in

extraction

byAR
0.02 kg
heptane etc.
5
303 K
48 h

Table 2

Experimental conditions in extraction by polar
solvent
Feed
AR, DAAR*, MDAAR**, etc.
Mass of feed
0.13 ~ 0.24 kg
Solvent
aqueous solution of methanol
Additive to solvent
aluminum chloride etc.
Mass ratio ofsolvent to feed
1
Mass fraction of
methanol
0.9
Mass fraction of
additive
0, 0.027
Temperature
303 K
Time
48 h

* The extract from non-polar solvent extraction of AR.
** Heptane solution of VGO as a model for DAAR. The massfraction of VGO in MDAAR was 0.33.

Table 3Composition of AR and VGO (in mass fraction)
heterocyclic
homocyclic
compounds
compounds
N
NS
S
AR
0.0332 0.048 0.556
0.3421
VGO 0.0072
00.45950.459

3. Results and Discussions
The compositions of AR and VGO are given in

13

Fig. 1 m′is of nitrogen heterocyclic andcompounds in AR extraction by heptane

were not obvious. The mis of nitrogen heterocyclic
compounds were larger than those of homocyclic
compounds. The effects of aluminum chloride
addition to the solvent on the mis of total and basic
nitrogens in the MDAAR extraction are shown in
Table 4. The mi of basic nitrogen with AlCl3 in thesolvent was higher than that without AlCl3, while thatof total nitrogen was not affected by AlCl3 addition.
The high affinity of aluminum ion with the lone pairof nitrogen atom in the basic nitrogen compound
would enhance the dissolution of the nitrogencompound into aqueous solvent phase [3].
Based on the above experimental results, thefollowing process was suggested. The AR is, first,
extracted by non-polar solvent to remove nitrogen
heterocyclic and homocyclic compounds with shorter
chain and more aromatic rings as solid residue and tolower the nitogen compound content in the liquid
extract to some extent. In the second, this liquid
extract from the non-polar solvent extraction is
extracted again by polar solvent to remove lightnitrogen compounds. The raffinate after this polar
solvent extraction mainly contains homocyclic
compounds with longer side chain and less aromtic
rings without nitrogen, which is an appropriate
fraction for the downstream catalytic reaction.

homocyclic

4. Conclusions

Fig. 2 mis of nitrogen heterocyclic and homocyclic
compounds in MDAAR extraction by aqueous
solution of methanol

The nitrogen heterocyclic and homocyclic
compounds with shorter side chain and morearomatic rings contained in atmospheric residue
could be removed and, thus, the total content of
nitrogen compounds could be lowered by non-polar
solvent extraction. The polar solvent could extract thenitrogen compounds selectively from the liquid
extract obtained in the non-polar solvent extraction.
According to these results, it was suggested to extract
atmospheric residue with non-polar and polar
solvents to provide an appropriate fraction for thedownstream catalytic reaction operation.

Table 4

Effect of aluminum chloride, AlCl3, addition topolar solvent on mi of total and basic nitrogens
mi [–]
without AlCl3 with AlCl3
Total nitrogen
0.4
0.4
Basic nitrogen
0.03
0.23

was reduced from 0.0813 in AR to 0.0796 (solventfree) in the liquid extract. The compounds withshorter side chain and more aromatic rings could be
removed and the content of nitrogen compounds intotal was lowered by non-polar solvent extraction ofAR.
While it was difficult to conduct the direct
extraction of AR by aqueous solution of methanol,
polar solvent, in the range of this work, the extractionof DAAR, MDAAR, etc. could be carried out
satisfactorily. The distribution ratio, mi, was writtenas,mi = yi ∕ xi
(2)
with the mass fraction in the extract, yi, and that in
the raffinate, xi, in the polar solvent extraction. In
Figure 2, the mis are plotted against the number ofcarbon atoms in side chain with the various numbersof aromatic rings, where MDAAR was extracted byaqueous solution of methanol, polar solvent. The mis
decreased with number of carbon atoms in side chain.
The effects of the number of aromtic rings on mis

Nomenclaturemi = distribution ratio of i in polar solvent extraction,m′i = distribution ratio of i in non-polar solvent extraction,
xi = mass fraction of i in raffinate phase in polar solvent
extraction, yi = mass fraction of i in extract phase in polar solvent
extraction, y′i = mass fraction of i in liquid extract in non-polar
solvent extraction, zi = mass fraction of i in solid residue in nonpolar solvent extraction<Subscripts>
i = component i
References[1] 石油学会 ; 石油精製プロセス ，第五章，接触分解 ，pp.125-138[2] Hasegawa, H., 東京工業大学2014年卒業論文[3] Chris, S., 東京工業大学2000年度卒業論文[4] Kodera, Y., et al., Fuel, 70, (6) 765 (1991)[5] Nagai, M., 東京工業大学1999年卒業論文[6] Masuda, T., 東京工業大学2015年度卒業論文

14Scale-up the producing of functional compost and examine the disease suppressing
effectStudent Number: 12_13940 Name: Takuya MITSUHASHI Supervisor: Kiyohiko NAKASAKI

contained in the oil cake. Compost samples wererecovered on day 0, 3, 6 and 12 in the primary
fermentation and subjected to secondary fermentation.
The values of pH of the composts were adjusted to 6
using 20% sulfuric acid. Strain GM-21 was inoculatedwith the initial DNA concentration of 10 ng g-1 DS
and secondary fermentation was carried out for 5 days
at 30oC. The compost samples were withdrawn fromthe mini reactor at 0, 1, 3 and 5 days and subjected tophysicochemical analyses, cell density of mesophilic
bacteria and DNA concentration of strain GM-21
analyses.

1 Introduction
In recent years, many researches about the biologicalpesticide that prevent plant disease utilizing
microorganisms instead of chemical pesticides werereported [1]. However, the steadily effective
biological pesticide has not been produced yet. The
failure of the production of biological pesticide isthought to be caused by a lack of nutrient source forthe activity to suppress bacteria in the soil. If thedisease suppressive microorganism grows in thecompost, nutrient for the microorganism is fertilized
simultaneously with biological pesticide to the soil.
Therefore, the compost containing the diseasesuppressive microorganism is expected to be theeffective biological pesticide. In this experiment,strain GM-21 [2] which can suppress bottom rot
disease of pak-choi was used as the diseasesuppressive microorganism.
The objective of this study is to produce functional
compost that can suppress the plant disease using oil
cake as raw material.

2-2 Bench scale production of functional compost
Functional compost was produced using thebench-scale reactor. Raw compost mixture was sameas mini scale production, but the temperature was left
self-heating. Sterilized compost sample after the
primary fermentation for 10 days was used for
production of functional compost.
2-3 Assessment of the suppressive effect offunctional compost
Plant growth assay was subjected to ascertain the
disease suppressive effect of functional compost.
Three test plots were subjected. Run A was without
the inoculation of strain Pak-choi 2 as the pathogen;
Run B was with the inoculation of only the pathogen;
Run C was with the fertilization of the functional
compost and inoculation of the pathogen. The mixtureof the soil, compost and pathogen was put into
polycarbonate pot and 15 surface-sterilized Pak-choi
seeds were planted to the mixture in the pot. The pots
were placed in a growth chamber and incubated at
25°C for 3 weeks with continuous illumination. The
disease severity was rated on a scale from 1 to 5 bycalculating a percentage of the number of diseased
seedlings over the total number germinated 3 weeks
after sowing. The soil samples were withdrawn fromthe pot at 0, 1, 2 and 3 weeks, and subjected to themeasurement of DNA concentration of strain Pak-choi
2.

2 Materials and methods
2-1 Mini scale production of functional compost
Functional compost was produced by the primary
fermentation for the degradation of organic matter andthe secondary fermentation for the propagation ofstrain GM-21.
The experimental system is the same as that in theprevious paper [3]. The oil cake, sawdust and seeding
material were mixed at a ratio of 15:4:1 on dry weightbasis to create a raw composting mixture. At the startof primary fermentation, the pH level was adjusted to
8 by the addition of slaked lime, and the moisture
content was adjusted to 50% by adding distilled water.
Twelve grams of composting mixture was put into thereactor. Reactor itself was placed in an incubator to
regulate the composting temperature. The temperature
was raised from room temperature to a set point of
60oC at a constant rate of 2.5oC h-1, and then, kept at
the set point until 12 days. The exhausted gas from thecomposting reactor was introduced into a 10 L plastic
bag for 24 hours and the total gas volume and theconcentration of CO2 is analysed. The conversion ofcarbon (Xc), corresponding to the degree of organic
matter decomposition, was taken as a molar ration of
the carbon loss as CO2 to the decomposable carbon

2-4 Real-time PCR
The concentrations of the DNA of strain GM-21 andPak-choi 2 in the soil samples were evaluated by thereal-time PCR method using the DNA extracted fromthe soil samples as a template. The primers specific tostrain GM-21, 25F, 5’- gtgttgcatgtagctgcctcctc -3’ 52R,
15

5’- tgacgcgagagttatccagacctac -3’ , and specific tostrain Pak-choi 2, ST-R1F, 5′- agtgttatgcttggttccact-3’, and ITS4(R), 5′- tcctccgcttattgatatgc -3’ were
designed and used.

Disease severity (%)(n=3)

3 Results and discussion
3-1 Mini scale production of functional compost
The courses of concentration of strain GM-21 in thecompost samples are shown in Fig. 1. When theconversion of carbon was too low (primary
composting for 0 day) or high (primary compostingfor 12 days), strain GM-21 couldn’t grow in thecompost. It was revealed that the optimum conversionof carbon for strain GM-21 to grow was around 75%.

102
101

10-2

0% (0d)40% (3d)75% (6d)
92% (12d)

0

1
2
3
4
Secondary fermentation time (d)5Fig. 1 Courses of concentration of strain GM-21
during the secondary fermentation.

Concentration of
GM-21 (ng/g-DS)

0
1
2
Plant growth assay time (week)

3

(n=3)

104

Run B
Run C

103
102
101
100
10-1

0

1
2
Plant growth assay time (week)3

4 Conclusions
Optimal composting conditions for strain GM-21
were investigated. The bench scale production offunctional compost succeeded. Plant growth assay was
performed using the functional compost which was
produced in this experiment and it was revealed thatstrain GM-21 could significantly suppress thepathogen.

(n=3)

4

20

Fig. 4 Courses of concentration of strain Pak-choi 2
during the plant growth assay.

3-2 Bench scale production of functional compost
The concentration of strain GM-21 in the compost
samples is shown in Fig. 2. Strain GM-21 also could
grow in bench scale composting.
10

40

Fig. 3 Courses of disease severity during the plant
growth assay.

103

10-1

60

0

(n=3)

100

Run A
Run B
Run C

80

Concentration of
Pak-choi 2 (ng/g-DS Soil)

Concentration of
GM-21 (ng/g-DS)

104

100

3

10

2

10

References

110[1] Seiber N. J, Coats J., Duke O. S., Gross D. A. 2014.
Biopesticides: State of the art and future
opportunities. J. Agric. Food Chem. 62:
11613−11619.
[2] Nakasaki K., Saito M., Suzuki N. 2007. Coprinellus
curtus (Hitoyo-take) prevents diseases of vegetablescaused by pathogenic fungi. FEMS Microbiol. Lett.
275: 286-291.
[3] Nakasaki K, Nagasaki K, Ariga O. 2004.
Degradation of fats during thermophilic compostingof organic waste. Waste Manage Res 22: 276-282.

0

10

0
6
Secondary fermentation time (d)Fig. 2 The concentration of strain GM-21 in thecompost samples.

3-3 Assessment of the suppressive effect offunctional compost
Courses of disease severity during the plant growth
assay are shown in Fig 3, Courses of concentration ofstrain Pak-choi 2 during the plant growth assay isshown in Fig. 4. In Run B, disease severity was almost
100% on 3 week after sowing and DNA concentrationof strain Pak-choi 2 increased.
However in Run C, disease was significantly
suppressed and DNA concentration of strain Pak-choi
2 didn’t increase.

16

Initial parameter setting in the propagation estimation basedon EM/SAGE algorithm
Student ID : 12B14068 Author : Tokio MIYAKE
Supervisor : Prof. Jun-ichi TAKADA Asst.Prof. Kentaro SAITO

1Introduction

where xl is received signal from l-th path, n is additive white Gaussian noise, µl is vector notion of
propagation parameter τ, φT , θT , φR , θR of l-th path,
B is angular frequency response of array antenna,and γl is polarized path weight γHH , γHV , γV H , γV V
of l-th path. Since n follows complex normal distribution, we can get likelihood function of µl , γ. By
simplifying of that likelihood function, we obtainnext formula, which is called correlation function.

Multiple-Input Multiple-Output (MIMO) transmission in the higher frequency band above 10 GHz
is expected to be future mobile communication
method. MIMO is the method to improve the capacity of network by using multiple transmitter andreceiver antennas.
The performance of MIMO transmission in highfrequency is strongly depends on the radio channel
condition because of the fading and the scattering.
Spatial Channel Model (SCM)[1] proposed by 3GPP
has been widely used, and it is based on the raybased channel model. This method needs propagation parameter. Space-Alternating Generalized Expectation (SAGE) algorithm[2] is one of the propagation parameter estimation method from the measurements.
This algorithm is iterative algorithm which is
known that the accuracy heavily depends on the initial parameters. Successive Interference Cancellation (SIC) parameter estimation[3] is one of the initial parameter estimation method. This algorithm,
however, has searching problem and can’t estimate
the propagation parameter on the specific condition (see subsection of related works). This paper
propose new initialization method of SAGE algorithm by improving SIC parameter estimation using
Single-Input, Multiple Output (SIMO) data.

2

Related works

2.1

Signal model and SAGE algorithmc(µl |xl ) = xl H B(µl )(B(µl )H B(µl ))−1 B(µl )H xl(2)
By maximizing this correlation function, we maximize likelihood of parameter and get l-th path propagation parameter. Eq. (2) can be used on the condition that xl is known. SAGE algorithm estimatesxl by using initial propagation parameter.

2.2

Since SAGE algorithm is iterative algorithm, the initial parameter estimation of SAGE algorithm is important part. SIC parameter estimation is a algorithm which estimate initial parameter by maximizing correlation function. Since the parameter searchis the 5-dimensional optimization problem, the calculation complexity becomes very large. Therefore, SIC parameter estimation divide this calculation into 4 steps for calculation reduction. Assuming l-th path estimation, we set temporary parameter to the propagation parameter of (l − 1)-th pathestimation result. By using this temporary propagation parameter, we estimate propagation parameteras shown below

In this paper, we define the received signal of
MIMO transmission as frequency response. Assuming plane wave, we can introduce propagation path, which is identified by 9 parameters
τ, φT , θT , φR , θR , γHH , γHV , γV H , γV V . τ is the propagation time from the transmitter to the receiver,
φT , θT is azimuth and elevation of Angle of Departure(AoD), φR , θR is azimuth and elevation of Angleof Arrival(AoA), and γHH , γHV , γV H , γV V is polarized path weights. This paper ignore Doppler shift
for simplicity and assume received signal as superposition of plane waves. The received signal x of L
of plane wave is expressed in vector notation as
x=

L
X
l=1

xl + n =LX

B(µl ) · γl + n

SIC parameter estimation(a1 , a2 , a3 , a4 , a5 ) = (τ̂l−1 , φ̂T,l−1 , θ̂T,l−1 , φ̂R,l−1 , θ̂R,l−1 )τ̂l = arg max c(τ̂l , a2 , a3 , a4 , a5 )τl(φ̂T,l , θ̂T,l ) = arg max c(τ̂l , φT,l , θT,l , a4 , a5 )φT ,l ,θT ,l(φ̂R,l , θ̂R,l ) = arg max c(τ̂l , φ̂T,l , θ̂T,l , φR,l , θR,l )φR,l ,θR,l(3)

3

Proposed method

SIC-parameter estimation reduce the amount of calculation. However, SIC-parameter estimation uses
temporary parameters which are unreliable. The

(1)

l=1

17
1

result of SIC parameter estimation is not accurate
when the temporary parameter is different fromtrue propagation parameter.
To solve the problem, in this paper, we proposed
the SIMO(Single-Input, Multiple Output)-based initial parameter estimation method. In our proposal,
MIMO channel matrix is decomposed into the set of
SIMO channel matrices. Since SIMO channel matrices don’t have Tx-side information, the dimensionof parameter estimation problem is reduced from 5
to 3. The estimated SIMO parameters are then used
as input to the correlation function. Then the remaining two parameters of correlation function are
estimated.

4

Figure 1: CDF plot of error function (SNR=-10 dB)

Results
Figure 2: CDF plot of error function (SNR=10 dB)

We evaluated our proposed method through simulations. The simulation data were generated byfollowing table condition. The propagation parameter is generated to follow normal distribution.
Table 1: Simulation data condition
Number of path
10 pathDelay τ2.5 ≤ τ ≤ 100 ns
AoA azimuth φR0◦ ≤ φR ≤ 359◦
AoA elevation θR30◦ ≤ θR ≤ 150◦
AoD aimuth φT0◦ ≤ φT ≤ 359◦
AoD elevation θT30◦ ≤ φT ≤ 150◦
Path weightγHH , γHV , γVH , γVV = 1
SNR-10, 10, 30 dB
Center frequency
11 GHzBandwidth
400 MHzTx/Rx antenna array 12 elements Cylindrical Array||x − s||2||x||2condition that SNR is bad and temporary parameter is not correct, conventional method lose correlation function peak and can’t estimate propagation
parameter. Proposed method is designed not to use
temporary parameter. This result shows the validityof that idea.

5

We conducted parameter estimation of 30 simulation data. We evaluate obtained result by using next
error function P .

P =Figure 3: CDF plot of error function (SNR=30 dB)

Conclusion

In this paper, we propose new initial parameter estimation of SAGE algorithm. This paper shows proposed method improve accuracy of initial parameter estimation of simulation data in comparison
with conventional algorithm. For future work, wewill conduct propagation parameter estimation byusing proposed method.

(4)

where x is original simulation signal which doesn’t
include noise, and s is estimated signal. This error
function evaluates the difference of estimated signal
and original signal. The smaller value of the error
function means the better estimation result. Fig.1,
Fig.2 and Fig.3 show the result of 30 runs of SAGE
results by using initial parameter estimation.

References[1] v7.0.0 3GPP, TR 25.996. Spatial channel model
for multiple input multiple output(mimo) simulations (release 9), 2009.
[2] Jeffrey A Fessler and Alfred O Hero.
Space-alternating generalized expectationmaximization algorithm. Signal Processing, IEEE
Transactions on, 42(10):2664–2677, 1994.

These results show that proposed method isbetter method in comparison with conventional
method. We can also say that the result difference between the proposed method and conventional method become bigger when the SNR is bad.
The conventional method can estimate propagation
parameter when the SNR is large enough even if thetemporary parameter is not correct. However, in the[3] V. H. Pham. Radio channel parameter estimation using sage algorithm. Master’s thesis,
Tokyo institute of technology, 2014.

182

全球高解像度人工排熱データベースの構築
学籍番号: 12_10001

氏名：トウゲツ1. はじめに指導教官：神田学

Energy Agency (IEA)から得られた。人口デー タ は LandScan Global 2013 Population
Database を使用した。

都市化の拡大に伴い、ヒートアイランド現象が顕著となる。その形成要因の一つとして、人間活動に伴うエネルギー消費による 排 熱 、 即 ち 、 人 工 排 熱 (Anthropogenic
Heat Emissions, AHE)が挙げられる。人工
排熱は都市部の気温変化のみではなく、局地豪雨を促進，大気境界層高度を上昇させるなど、気候・気象面での影響が指摘されている。特に、AHE の影響で夏季の気温が上昇すると、冷房によるエネルギー消費が増加し、更に多くの熱量が排出されるというフィードバック機構も指摘されている。

各グリッドにおける年平均 AHE(𝑄𝑓−𝑦 )は、エネルギーロス（一次エネルギーと最終エ
ネルギーの差）の排熱(𝑄𝐿 )、産業・農業部
門の排熱(𝑄𝐼𝐴 )、商業・家庭・運輸部門の排熱(𝑄𝐶𝑅𝑇 )、人間代謝熱(𝑄𝑀 )という四つの成分に分けて求めた。𝑄𝐿 はエネルギーロスを国全域に、𝑄𝐼𝐴 はその部門のエネルギーを居住人口のある地域に、一様に配分して計算した。𝑄𝐶𝑅𝑇 について、既往研究では人口密度分布によって配分する手法が一般的であるが、通常の居住人口と昼間の都市人口には大きな隔たりが存在するため、都市部の排熱を正確に把握できない。そこで、夜間の経済活動やエネルギー消費をよく表現できる、NOAA のナイトライトデータで人口密度を補正する手法を提案した。ナイトライ
トと人口密度の相関に着目すると、両者の線形関係から逸脱したグリッドは昼夜の人口差が著しく大きいオフィス街と住宅地となる。ナイトライトと人口密度の線形関係に基づき、外れ値の人口データを補正した。
補正後の人口データを用いて、商業部門など都市の活動と密接に関連しているエネル
ギー消費量を配分して 𝑄𝐶𝑅𝑇 を求めた。𝑄𝑀については、Sailor et al.(2015)が提案した代謝率を用いて、LandScan の人口密度によって算出した。

AHE の時空間分布の推定について、既往研
究ではボトムアップとトップダウンの二種類の手法がある。前者は現地調査を通じ、詳細な地理情報と局地的なエネルギー統計値を用いて AHE を定量化する手法である。
しかし、このようなデータは現地で個別に収集する必要があり、広域又は全球について同様の手法を適用することは困難である。
それに対し、後者は国ごとの年間エネルギ
ー総量をより細かい時空間解像度へ配分させる手法である。この手法はグローバルに展開できる一方で、解像度と精度の制限が問題となる。本研究は広域への適用可能性を前提として、高解像度且つより正確に都市のエネルギー消費の分布を再現できるトップダウン手法を開発し、全球の人工排熱データベース(空間解像度:30 arc-seconds,
時間解像度:1hour)を構築することを目的とする。

年平均から月平均を求めるために、AHE に関する気温感応度を提案した。平成 15 年環
境庁の調査および米国の AHE データセット(Sailor et al,2015)を見ると、都市別の月
平均 AHE は、おおよそ20℃を境にして(分岐気温点)V 字型となる傾向が示されている。
各都市のプロットに対して、回帰直線の傾きを用いて、年間平均の AHE に対する気温が分岐気温点より 1℃上昇または低下による増分の比率、即ち気温感応度(%/℃)を算出した。これらを元に AHE の気候感応度に関する経験式を見積もり、グローバルに一般

2.人口排熱時空間分布の推定
本研究では、国別の一次エネルギー消費量が最終的に全て熱フラックスとして排出されると仮定し、年間エネルギー消費から
地域別(空間分布)の年平均 AHE を算出する。
また、年平均から月変化と日変化（時間分布）を推定する。グローバルなエネルギー
統 計 デ ー タ は U.S.Energy Information
Administration (EIA)および International19化させることで、AHE の月変化を求めた。一方日変化については、東京二十三区の AHE
データセット(Moriwaki et al., 2008)を参照すると、月平均気温に対応した四つのパターンがあることが分かり、それに基づき
一日の時間別 AHE を見積もった。

度の補正と、都市別の気候感応度を導入することで、都市の排熱分布および時間変化
が大幅に改善した。これにより高空間解像度のグローバルな AHE データベースを構築することができた。本研究成果を気象シミュレーションの境界条件として応用することで、人工活動が気候に及ぼす影響について検討することが今後可能となる。

3.全球人口排熱のデータベースおよびバ
リデーション
前述のトップダウン手法を用いて全球の人口排熱データベース(2013)を構築した(図1)。グローバル平均の AHE が 0.13 W/m2であり、いくつかの大都市では AHE の値が100 W/m2 以 上 と な っ た 。 最 高 値 は493 W/m2 (香港)である。時間変化に関して、12 月から 2 月までの期間は年間を通して最も大きい人工排熱がなされる時期となった。都市に注目すると（図 2、東京の例）、
ナイトライトで補正した結果、都市中心部と周囲の住宅地区の空間的偏差がよく表現されている。

図１全球における年平均 AHE の空間分布図

本研究の結果を、既存の地域スケールのデータセット(ボトムアップ手法)およびグロ ー バ ル ス ケ ー ル の デ ー タ セ ッ ト (LUCYmodel、トップダウン手法)と比較し、東京、ロンドンと米国 52 大都市について検証を行っ た 。 空 間 と 時 間 の 両 方 に お い て 、 LUCY
model よりボトムアップ手法で再現したデー
タと一致する傾向となった。特に、気候感
応度による補正を適用することで、ボトムアップ手法で解析したローカル AHE の月変
化を LUCY model より精確に再現できた。その一方で、ナイトライトによる補正は東京では顕著であったが、ロンドンでは同様の補正効果は得られなかった。その原因として、ナイトライトの感度は地域差があるた
め、グローバルに展開する際には、ナイト
ライトの感度に関するパラメータを都市ごとに考慮すべきである。

図 2 東京 23 区における AHE の空間分布図

参考文献[1] 平成 15 年度 都市における人工排熱抑制によるヒートアイランド対策調査 (国交省・東京
都 ・ 環 境 省 ) http://www." env. go.
jp/air/report/h16-05/index. html (15).
[2] Sailor, D.J., Georgescu, M., Milne, J.M. andHart, M.A. (2015) ‘Development of a national
anthropogenic heating databasewith anextrapolationforinternational
cities’,Atmospheric Environment, 118, pp. 7–18. doi:
10.1016/j.atmosenv.2015.07.016.

4. おわりに本研究では、グローバルなエネルギー統
計データと衛星画像を用いて、全球人口排熱の時空間分布を推定するトップダウン手法を開発した。ナイトライトによる人口密[3] Moriwaki, R., Kanda, M., Senoo, H.,

Hagishima, A. and Kinouchi, T. (2008)‘Anthropogenic water vapor emissions in Tokyo’,
Water Resources Research, 44(11), p. n/a–n/a.
doi: 10.1029/2007wr006624.

20

Feasible study of Space debris removal by using electromagnetic force
Student number: 12-13904

Name: Jun Mitani

1, Introduction

3, Required deceleration for debris

Space debris is trash in orbit. As a result of
space activity, a large number of space debris
is left in orbit around the earth. We canobserve and track big debris. And can protect
satellite from small debris collisions withshield. But for 1cm to 10cm debris, we cannot
observe them, and cannot protect thesatellites from their collisions. The feasible
solution for the space debris has not beenfound out yet.
Table 1 shows the number of space debris by
its size.
Table 1: Number of space debris[1]
Size
~1cm
1cm~10cm >10cm
Total
0.15
0.65
22
Numbers
billions millions
thousands
Numbers
under
2,000km Alt

1.6
millions

0.27
millions

14
thousands

Shield○××

Observation

×

×

○

Supervisor: Daisuke Akita

Forces on the space debris are modeled asshown in Fig 2.Equations of motion are
written as below.
debrisFigure [2]:Calculation model during
atmosphere entrydv
𝐶 𝑆= − 𝐷 𝜌𝑣 2 + 𝑔𝑠𝑖𝑛𝜃
dt
2𝑚
dθ

(1)

𝑣2

(2)

v dt = (𝑔 − 𝑟 ) 𝑐𝑜𝑠𝜃2, Mission concept

𝜃 :Flight path angle 𝐶𝐷 : Drag coefficient.
r:Distance from the center of the Earth.
𝜌:Atmosphere density. m:Mass.
S:Frontal area.
The time to remove a space debris at 400km
altitude is shown in Fig 3.At least 60 m/s isthe needed to remove the debris in areasonable time.

Figure 1 shows the mission concept
1. A satellite is launched to an orbit of
400km Altitude.
2. The satellite produces a magnetic fieldaround its own self.
3. Space debris fly by the satellite withrelative orbit velocity.
4. Electromagnetic induction induces acurrent inside the debris.
5. The debris is declare by a Lorentz forceof the induced current and the magnetic
field.
6. The decelerated debris re-enter the
Earth’s atmosphere and finally burn up.

Time to re-enterstmosphere[min]45This study investigates the followings.
1. Required V for debris to re-enter theatmosphere.
2. Model of a induced current inside a debris
and a Lorentz force acting on it.

40
35
30
25
20
50

70

90

Required deceleration[m/s]

Figure [3]:Time to remove space debris vs. Δv

Figure [1] :Mission concept

21

110

4, Lorentz force on debris

In Maxwell equations, the charge density
inside a debris is assumed to be zero. For the
conductive material as below.

⃗ =

(3)

Introducing a vector potential 𝐴 of ⃗ , we
can write [3].
⃗ = × 𝐴
(4)
Using equation(4) and Faraday’s law, we cancalculate an induced electro field by
numerically solving.
2

𝐴=

⃗
𝜕𝐵
𝜕𝑡

(5)

Equation (5) is solved by SOR method, An
induced current is calculated using⃗J = σ⃗(6)⃗
Finally, A Lorentz force F is obtained by.

Figure[5]:Induced current dencity distribution⃗F = 𝐽 × B⃗(7)
E: Electro field B: Magnetic flux density: Dielectric constant of vacuum
𝜌 Charge density σ ∶Electric conductivity
J: Current density
F:Lorentz force

Fig[6] shows the vector of decelation in
the whole motion. I confirm the induced
Lourentz force always decelarates debris.
Furthermore, I confirm the induced
Lourentz force is three–demensional
power.

I simulated a situation shown in Fig 4.Space
debris go through a magnetic flux density
field that produced with a magnet. The
velocity of space debris is 10km/s.

Figure[6]:The vector of decelate in the whole
motion4, Conclusion

This study showed an artifical magnetic
field can decelerate the space debris, in orbit.
However, we have to investigate the optimal
magnetic field distribution. To obtain asufficient deceleration for the space debris
removal.

Figure [4] :Space debris goes through B field
The indeed current distribution inside thespace debris is shown in Fig[5].
The current flows to counteract the changeof magnetic field inside the debris.
Integrating the current density, we could
obtain a Lorentz force that decelarates the
soace debris.

References[1]He Ping,” Feasibility on Removal of Space

Debris by an Artificial Magnetic Field,”
p6 ,2009[2]SeiyaFuruki “Titan Aero capture
Saturn Orbit Insertion,” p14 ,2011

for[3]Kenzo Miya “Analysis Electromagnetismand Electromagnetic structure,” YOKENDO,
pp,179-199,1995
22Effect of microbial pretreatment for oil in methane fermentation from wastewater containing soybean oil
Student Number: 12-13229

Name:Takuya MAEKAWA

1. Introduction
Fat is one of the major organic matters in wastewater fromfood processing factory. Fat can be a good substrate formethane fermentation as in theoretical value, 850 mL of
methane gas can be produced from 1 g of fat, even though
500 mL of methane gas can be produced from 1 g of protein,and 395 mL of methane gas can be produced from 1 g ofcarbohydrate [1]. So methane fermentation of wastewatercontaining fat is desired.
However, fat contained in the wastewater is usually
separated and discarded as the industrial waste before thebiological treatment stage because it is known that the
production of the methane from fat is difficult. Fat is
separated from aqueous phase and is hardly biodegradable.
To solve the problems, oil is generally hydrolyzed by reagentof acid-base solution or enzyme. But there is few research ofmethane fermentation from pretreated oil by microorganism
producing surfactant.
In this study, pretreatment of the soybean oil by the
microorganism was applied in the methane production fromthe wastewater containing fat and the effectiveness of the
pretreatment depending on the amount of oil wasinvestigated by the methane fermentation using soybean oil.

Supervisor: Kiyohiko NAKASAKI

substrates were supplied to each reactor in a stepwisemanner: day 0-20 with O-0, 21-95 with O-25 and day
96-232 with O-50.
For the startup of the experiment, 1545 mL of distilledwater, 200 mL of O-0 and 65 g of granular sludge from foodprocessing factory that had been already acclimated with O-0
were mixed in two of the anaerobic sequencing batch reactor(ASBR). These reactors were made of Pyrex glass and had aworking capacity of 2.5 L. These reactors were flushed with
5 L of N2. The temperature in the reactors was maintained at
39 ºC by water jacket, and the solution in the reactors wasagitated with a stirrer at 100 rpm. In these experiments, 200
mL of supernatant was extracted from the reactor, and thesame volume of fresh substrate was fed every day.
The value of pH was measured by the pH meter. A sampleof the exhaust gas was captured into a sampling bag and gas
compositions were measured by GC-TCD. Gas volume wasmeasured using dry test gas meter. The concentration of
GAL and organic acids in culture of Run A and Run B
during day 0-20 was measured by HPLC.
O-0
12.5
6.25
6.25

O-25
9.38
4.69
4.69

O-50
6.25
3.13
3.13

Glucose (g/L)
Sodium acetate (g/L)
Lactic acid (g/L)
Soybean oil contained
0
3.05
6.1
in the substrate (g/L)
Table 1 Composition of the O-0, O-25 and O-50

2. Materials and methods
An yeast strain, Pseudozyma rugulosa NBRC 10877 wasused to pretreat the soybean oil. P. rugulosa was known as a
producer of a surfactant, MEL [2]. MEL has no toxic effecton microorganism [3]. The yeast was precultivated in 20 mL
of YM broth at 25 ºC for 2 days 150 spm. After thecultivation, 1 mL of the preculture was centrifuged and theyeast was rinsed with Yeast oil broth that was composed of
20 g/L of soybean oil, 3 g/L of yeast extract and inorganic
nutrients. Then, 50 µL of Yeast oil broth containing the yeast
was inoculated to 10 mL of Yeast oil broth and cultivated at
25ºC for 7 days. After 7 days cultivation, the culture was
supplied to methane fermentation.
Glucose, sodium acetate, lactic acid (GAL) and soybean
oil were used as substrates for methane fermentation and two
experiments, Run A and Run B were conducted. In Run A,
the reactor was fed with untreated Yeast oil broth, and in Run
B, the reactor was fed with Yeast oil broth pretreated by yeast.
Three kinds of the substrate with different mixing ratio of
Yeast oil broth, glucose, sodium acetate and lactic acid,designated as O-0, O-25 and O-50, were prepared. But
amount of carbon of O-0, O-25, O-50 were same. The
compositions of those substrates are shown in Table 1. Those

3. Results and discussion
The pH value of Run U and Run P is around optimum
value, 6.3-7.4, for whole period of methane fermentation.
Fig. 1 shows the courses of gas volume of CH4 and CO2 in
the fermentation of Run A and Run B. During day 1 to 20 of
fermentation the gas productions of both Runs were stable ataround 1.07 L. As was not shown here, GAL and organicacid were not detected and were considered to be completelydegraded.
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 toCH4 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.

23

The results suggest that immediately after the oil was
supplied, oil was not available for microorganisms. Then, thegas volume of Run A gradually increased from day 24 andreached at around 1.09 L on day 74 that is almost the same
volume with that observed before day 21. It is consideredthat during day 24 to 74, some microorganisms wereacclimated to utilize oil in the O-25.
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 fat than that in O-25. It is
known that more than 0.1 g/L of oleic acid causes theinhibition against microorganisms [4]. When the oil in the
O-50 is completely degraded, concentration of oleic acidproduced from is estimated at 0.15 g/L that is higher than theconcentration of 0.1 g/L causing inhibition of microbialactivity, and it is considered that LCFA produced in the
degradation of oil in O-50 caused the decrease of the gas
production of Run A and 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.This result
suggests that some microorganisms have been acclimated tohigh concentration of LCFA and could degrade LCFA.
Fig.2 shows the DGGE pattern for bacteria in the methane
fermentation process of bacteria of Run A and Run B. There
were some characteristic bands, band 1-7 in Fig.2. Among
those bands, only the DNA sequence of Band 5 could bedetermined. Light intensity of band 5 and band 6 of increasedin the period of day 155-232 which coincided with theincrease in the methane production in Run A and B. DNA
sequence of band 5 was close to that of Segniliparus
rotundus. The results indicated that Segniliparus rotundus
could degrade LCFA.

Fig. 2 DGGE pattern for bacteria of Run A and Run B

4. Conclusions
It was revealed that the microbial pretreatment of oil could
keep the organic matter degradation in methane fermentationfrom wastewater containing oil at the oil content of 3.05 g/L
and when the content of oil was set at 6.10 g/L, it wassuggested that the pretreatment was not sufficient for themethane production.
Gas volume of Run A and Run B was recovered in the latestage of fermentation and a bacteria, Segniliparus rotundus,
was identified as the candidate of LCFA degrading bacteria.
The possibility of enhancement in the methane production
from high content of oil by employing Segniliparus rotundus
was suggested in this study.

Reference[1] Noaki. 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] Tomotake Morita, Masaaki Konishi, Tokuma
Fukuoka, Tomohiro Imura, Dai Kitamoto,
Discovery of Pseudozyma rugulosa NBRC 10877
as a novel producer of the glycolipid
biosurfactants,mannosylerythritol lipids, based on
rDNA sequence, Appl Microbiol Biotechnol, 73,
305–313, (2006)[3] 福岡 徳馬, 森田 友岳, 井村 知弘, 北本 大, 酵

Methane gas production [L/d]

2.5
Run A

2

Run B

1.5
1
0.5
0

母が作り出す高機能界面活性剤（バイオサーファクタント）の開発, 化学と工業, 83, 103-110, (2009)
0 20 40 60 80 100120140160180200220240
Fermentation time [d][4] Irini Angelidaki et al. : Effects of free long-chain fatty
acids on thermophilic anaerobic digestion, Appl
Microbial Biotechnol, 37, 808-812 (1992).

Fig. 1 Courses of CH4 gas production of Run A and Run B

24

大域的射影変換相関法を用いたテンプレートマッチング
学籍番号：12_09653

1

学生氏名：趙偉成

はじめに指導教員：山下幸彦

式 (3) では，未知成分 A, b が画像の中にあり，計算することが難しい、そのため，2 次元ガウス関数

テンプレートマッチングとは，テンプレートと呼2√(4)G(x) = γe−γ∥x∥
ばれるパターンが，テスト画像全体の中に存在するかどうかを調べるコンピュータビジョンの一手法でによる近似と，エッジ方向の同一性を導入し，次のある。この技術は対象物体の位置検出，部品の位置
目的関数を定義する。
決め等広い分野で応用されている。テンプレートマッ∫ ∫チングの基本原理は画素どうしの比較によって，類 J˜GAT =G(Ax1 + b − x2 )(5)
D D
似度が一番高い位置を見つけることである。類似度
δ(∇f (x1 ), ∇g(x2 ))f ′ (x1 )g(x2 )dx1 dx2としては，正規化相互相関 (NCC)，輝度差の二乗和(SSD) または輝度差の絶対値和 (SAD) が代表的であ
ここで，δ(∇f (x1 ), ∇g(x2 )) はクロネッカーデル
る。そのうち，正規化相互相関法には照明変動など タであり，2 つの画像の勾配ベクトルが同方向であ外乱に対する耐性が高いという利点がある。しかし， る場合に 1，異なる場合に 0 となる。
それらの手法にはアフィン変換や射影変換による影GAT 相関法では，A と b に対する J˜GAT の微分が響を受けやすいという問題がある。
0 となる時に最大値を取る。その条件から得られる方
そのため，画像の線形変換や平行移動に頑張な大 程式を近似的に解いて A と b の値を得る。この計算
域的アフィン変換 (GAT) 相関法 [1,2,3] や射影変換に で得られたアフィン変換で入力画像を更新して，こ拡張した大域的射影変換 (GPT) 相関法 [4] が提案さ の操作を相関が最大になるまで繰り返す。
れた。しかしながら，今までの GAT/GPT の実験では入力画像とテンプレート画像の画像サイズが同じ場合だけで実験が行われていた。本論文では入力画 3 GPT 相関法
像が大きくその中からテンプレートを効率的に探し
2 次元画像の射影変換は次式のように与えられる。
出すアルゴリズムを提案し，実験を行う。
Ax + bx′ =(6)
1 + ⟨c, x⟩

2 GAT 相関法

ここで，x は 2 次元座標を表す 2 次元ベクトルで′2 次元画像のファフィン変換は次式で与えられる。 あり，x は射影変換されたベクトルである。また，
２次元画像の部分射影変換 (PPT) を次式で定義する。
′
x = Ax + b
(1)
x
x′ =
(7)
1 + ⟨c, x⟩
ここで，x は 2 次元座標を表す 2 次元ベクトルであ
上式により，射影変換はアフィン変換と部分射影
り，x′ はアフィン変換されたベクトルである。A と変換の組み合わせで表すことができることがわかる。
b はアフィン変換を表す (2, 2)-行列と 2 次元ベクトルである。定義域が D である画像 f (x) に対し，式 (1) したがって，GPT 相関法を部分射影変換 (PPT) とアのアフィン変換で変換した画像を f ′ (x) とおけば， フィン変換 (AT) の２つの部分に分けて計算する。部
分射影変換での目的関数を次式で定義する。
1
)
(
∫ ∫
f (A−1 (x − b))(2)f ′ (x) =
x1
|A|
− x2
(8)
JP P T =G
1 + ⟨c, x1 ⟩D Dが成立する。その時，2 つの画像 f (x) と g(x) の GATδ(∇f (x1 ), ∇g(x2 ))f ′ (x)g(x)dx1 dx2
相関値は次式の目的関数を A, b を変化させた時の最
これを最大にする c を 1 次近似を用いて求める。
大値で定義される。
∫
アフィン変換と部分射影変換を交互に計算し，入力
JGAT =f ′ (x)g(x)dx(3) 画像を変形させたものを新しい入力画像として，相D関値が収束するまで繰り返す。最後に得た最大の相関値を GPT 相関と定義する。

1
25

4

GPT 相関法によるテンプレート
マッチング

表 1: 正規化相互相関及び GPT 相関法による相関値

本論文で提案するアルゴリズムは，テスト画像の各位置で抽出した画像の類似性を評価して，閾値を超えた位置で GPT 相関法を適用し，GPT 相関が最大になる位置を検出することである。第ｍ回目の繰り返しにおいて，射影変換 Am ，bm ，cm を用いて入力画像からテンプレート画像と同じ大きさの画像を切り出す。次に，線形方程式を解いて A′ ，b′ ，c′を計算する。そして，新しい射影変換 Am+1 ，bm+1 ，
cm+1 を次式で計算する。

Am+1= A′ Am + b′ cT
m
′

′

bm+1

= A bm + b

cm+1

′
= AT
m c + cm

縦 1.3 倍拡大
縦 1.1 倍拡大
縦 0.8 倍縮小
縦 0.5 倍縮小
10◦ 回転20◦ 回転30◦ 回転10◦ せん断20◦ せん断30◦ せん断c = (0.003, 0) 射影変換
c = (0.005, 0) 射影変換
c = (0, 0.003) 射影変換
c = (0, 0.005) 射影変換
射影変換とせん断

正規化相互相関0.772618
0.799914
0.739234
0.535498
0.669099
0.547836
0.467166
0.641445
0.660606
0.583002
0.576191
0.445867
0.583002
0.639396
0.492940

Org
0.772618
0.450031
0.291620
0.478905
0.548039
0.499562
0.368555
0.555850
0.581996
0.555452
0.544649
0.445867
0.515562
0.478628
0.282011

GPT 相関0.997546
0.997078
0.993366
0.985412
0.993027
0.990889
0.957391
0.996402
0.996544
0.922667
0.990156
0.988551
0.995552
0.990321
0.913418

(9)
(10)
(11)

この変換により画像を切り出し，相関値が最大になるまで線形方程式を解くことと変形を繰り返す。

5

実験結果

図 1: 変形されたテスト画像

本論文では，大域的射影変換 (GPT) 相関法で射影変換やアフィン変換により変形したテスト画像の中で，参照画像の位置を検出する実験を行った。そして，GPT 相関法の結果と正規化相互相関法の結果を
[a]
[b]
[c]
比較して考察した。表 1 に最大正規化相互相関値，GPT 相関法で検出された位置の初期相関値，検出された位置の GPT 相関値を示す。図 1 は c = (0, 0.005)の射影変換と 30◦ せん断変換で変形したテスト画像
[d]
[e]
[f]
である。図 2 はそれぞれテンプレート画像，輝度差の二乗和 (SSD) による検出位置の画像，輝度差の絶 図 2: テンプレート，検出位置の画像及び変形画像
対値和 (SAD) による検出位置の画像，正規化相互相関法による検出位置の画像，GPT 相関法による検出
位置の画像，GPT 変換した後の画像である。
参考文献
表 1 及び図 2 により，GPT 相関法はアフィン変換
や射影変換に対する耐性を持ち，正規化相互相関法 [1] 若原 徹, 小高 和己, 大局的アフィン変換を用いた形状マッチング, 信学技報, PRMU96-2, May,より相関値の高い画像位置を検出でき，GPT 相関値
1996.
が 0.9 以上に向上したことがわかった。
[2] 若原 徹, 木村 義政, 山下 喜義, GAT 反復を用いたアフィン変換不変の濃淡文字相関法, 信学
技報, PRMU99-31, June, 1999.
6 おわりに[3] Toru Wakahara, Yukihiko Yamashita, “Accelera本論文では，GPT 相関法をテンプレートマッチン
tion of GAT Correlation for Distortion-tolerant Imグに適用することを提案し，その有効性を計算機実
age Matching”, Proc. of ICPR 2012, pp746–749,
験によって確認した。今後の課題は，計算精度の向Tsukuba, Dec. 11-15, 2012.
上と，計算速度を上げることである。

226

Influence of curing water containing various ions on permeability of concrete andits application to water supply curing method
Student Number: 12-01232 Name: Kazuki Ishihara Supervisor: Prof. Nobuaki OTSUKI(3) Reverse T-type specimens assuming theactual structure
Two sizes of cylinder cores were taken from theactual wall φ7.5cm×10cm cylinder cores wereused for compressive test. φ10cm×10cm cylindercores were used for carbonation test and chloride
ion penetration test .
The mix proportion is shown in Table 2.
2.2 Measurement items(1) Compressive strength(2) Carbonation rate coefficient
Concrete specimens has been exposed underCO2 10% condition. Except exposure side
(underside in construction), surface of concrete issealed by epoxy. Results is conversed into air
environment by using Uomoto formula2).
(3) Chloride ion diffusion coefficient
Salt water (NaCl 3%) was sprayed at 50℃
environment. Except exposure side (underside inconstruction), surface of concrete is sealed by
epoxy.
2.3 Kinds of solution and curing method
Table 3 shows kinds of solution and curingmethod.
As solution, seawater, bittern (Table 4) andmagnesium acetate solution were selected
expecting magnesium hydroxide deposition which
colud cover surface on concrete.
Natto bacteria, sodium carbonate (Na2CO3) andsodium hydrogen carbonate (NaHCO3) solution
wasselected
expectingdensificationbycarbonation.
Natto bacteria need nutrient and O2. So,
solution in natto bacteria contained a material(Table 5), and it was pumped air.
Curing of mortar specimens and concrete
specimens cured in under each solution. Curing of

1. Introduction
Curing is known to affect the quality of concrete,especially durability, that is closely related topermeability.
The solution used for curing must not containharmful amounts of substances affecting thesurface of the concrete, such as oil, acids and salts.
Thus, it is possible to use various solutions forcuring.
However, investigation on the effect of the typeof curing water on performance of concrete is veryfew.
One of the curing method used in the actual
construction is water supply curing method1). If
the effects obtained in water supply curingmethod are almost equal to the results of those inunderwater curing, it can be applied to the actual
construction.
In this study, the purposes are following two.
(1) To clarify influence of various ion in curing
water on material permeability of concrete.
(2) To clarify the applicability of water supply
curing method with using various solution.

2. Experiment outline
2.1 Specimens(1) Mortar specimens
Cylinder specimens were used for compressive
test (φ5cm×10cm) .Prism specimens were used
for Carbonation test and chloride ion penetration
test (4cm×4cm×16cm) . The mix proportion isshown in Table 1.
(2) Concrete specimens
Cylinder specimens were used for compressive
test (φ10cm×20cm). Prism specimens were used
for Carbonation test and chloride ion penetration
test (10cm×10cm×40cm) .
The mix proportion is shown in Table 2.

Table3, solution and curing method
No. name

Use solution

1 Tap water
2 Seawater
3 Bittern
4 Natto bacteria
5 Na₂CO₃6 NaHCO₃

Table1, mix proportions of mortar
specimens
W/C(%)

S/C

55

2

7 (CH₃COO)₂Mg1
8 (CH₃COO)₂Mg0.1

C（Kg/㎥） S（Kg/㎥） W（Kg/㎥）
612.5

1224.99 (CH₃COO)₂Mg0.01

319.9

Tap water
Artificial seawater
Bittern
Natto bacteria
sodium carbonate
1.0mol/l
sodium hydrogencarbonate
1.0mol/l
Magnesium acetate
1.0mol/l
Magnesium acetate
0.1mol/l
Magnesium acetate
0.01mol/l

Cement
type

OPC

slump
(cm)

air
content(%)

12.0±2.5 4.5±1.555

sandaggre
gate
ratio
s/a
(%)
44

quantity of material per unit volume of concrete（kg/m ）Cement

W
169

C
307

sand S
S1
547

S2
245

Atmosphericcuring after
7days curinginunderwater

item
3

water

1 day

Table5, nutrient of natto bacteria

curing after
demoulding

Reagent nameconcentration (g/l)

glucose：C6H12O6

20

Ammonium chloride：NH4Cl

7dipotassiumhydrogenphosphate：K2HPO4

0.5

Magnesium Sulfate
Heptahydrate：MgSO4･7H2O

0.5

Ferrous chloride
tetrahydrate：FeCl2･4H2O

0.031

Calcium chloride dihydrate：
CaCl2･2H2O

0.15

Manganese(II) sulfate
hydrate：MnSO4･H2O

0.1

D-Biotin：C10H16N 2O3S

0.0005

Table4, bittern

Table2, mix proportions of concrete and reverse T-type spacemen
watercement
ratio
W/C
(%)

demoulding

gravelchemical
admixture

G
1038

Ad.
3.28

27

Analysis value

Magnesium chloride:MgCl2

12.70%

Sulfate:SO4
Bromide:Br
zinc:Zn
calcium:Ca
sodium:Na
potassium:K
heavy metal:As Pb
arsenic:As2O3

3.00%
2.5% or less
70μg/g0.1% or less
2.60%
1.00%
5μg/g or less
1.0μg/g or less

Photograph 1,
water supply curing method

60
40

20
0

25.0
20.0

15.0
10.0
5.0

Cylinder specimen

Figure 2, carbonation rate coefficient andchloride ion diffusion coefficient
Chloride ion diffusion coefficient(cm2/year)

carbonation rate coefficient(mm/week0.5)

30.0

Chloride ion diffusion coefficient

0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0

Prism specimen

35.0

0.0

Carbonation rate coefficient

Figure 1, compressive strength of mortar
specimens

Compressive strength(N/mm2)

80

180
160
140
120
100
80
60
40
20
0

No data100

No data

Value compared with the tap water(%)

Value compared with the tap water
(%)

120

Core specimen

Figure 3, compressive strength of Cylinder
specimens and core specimens

18
16
14
12
10
8
6
4
2

0

Prism specimen

Figure 4, carbonation rate coefficient of prism
specimens and core specimens

Core specimen

Core specimen

Figure 5, chloride ion diffusion coefficient ofprism specimens and core specimens

reverse T-type specimens used water supply
curing method as shown in the photograph 1.

Trend is the same in underwater curing andwater supply curing method. It is considered thatwater supply curing method can be applied about
durability to carbonation.
3.4 Chloride attack

3. Results and discussion
3.1 Select of solutions by using mortar
specimens
Figure1 shows the result of the compressive testof Mortar specimens. Figure 2 shows the result of
the carbonation test and chloride ion penetration
test of Mortar specimens.
According to Figure 2, the result of carbonation
rate coefficient and chloride ion diffusion
coefficient cured in seawater, bittern and natto
bacteria is better than that cured in tap water.
The most effective concentration of magnesium
acetate to material permeability is 0.1mol/L.
Compared with sodium carbonate and sodiumhydrogen carbonate, sodium carbonate is better
than sodium hydrogen carbonate.
It is found that the best concentration ofmagnesium acetate is 0.1mol/L .
It is found that sodium carbonate is effective inthe solution containing carbonate ions.
3.2 Compressive strength
Figure 3 shows the result of the compressive testof concreate specimens and core specimens.
According to Figure 3, compressive strength ofcylinder specimens cured in all solution except
bittern is equal to that cured in tap water.
However, compressive strength of core specimens
cured in bittern is equal to that cured in tap water.
It is considered that surface affected by the curing
is only one in water supply curing method.
3.3 Carbonation
Figure 4 shows the result of the carbonation testof concreate specimens and core specimens.
Carbonation rate coefficient of prism specimens
cured in all solution is better than that cured intap water, particularly seawater, natto bacteria
and magnesium acetate is good.

Figure 5 shows the result of the chloride ion
penetration test of concreate specimens and core
specimens.
Chloride ion diffusion coefficient of prism
specimens cured in all solution except magnesium
acetate is better than that cured in tap water.
Chloride ion diffusion coefficient of prism
specimens which cured in natto bacteria solution
is the lowest. However, chloride ion diffusion
coefficient of core specimens cured in seawaterand sodium carbonate solution is the lowest.
It is found that effect about durability to chloride
attack is not necessarily the same in underwater
curing and water supply curing method.

4. Conclusions(1)Compressive strength cured in solution
containing various ions by water supply curingmethod is almost equal to that cured in tap water.
(2) Carbonation rate coefficient cured in seawater,
natto bacteria and magnesium acetate is smaller
than that cured in tap water.
(3) Chloride ion diffusion coefficient cured inseawater, sodium carbonate and natto bacteria issmaller than that cured in tap water.
(4) Water supply curing method can be appliedwith little advantages compared to underwater
curing.

5. Reference
1)

2)

28

Hazama Ando Corporation: Water Supply Curing
System of Concrete Structure, “Aqua Curtain”;2013.4
K.Uomoto・Y.Takada: The effect of carbon dioxide
concentration on the neutral rate of concrete,
Production research, Vol.43,No.６, pp.35-pp.38, 1991.6

Relationship of Automobile Use with Urban Residential Zones Classification and the Transition
Student Number: 12_16096 Name: Tianzi LU

Supervisor: Shinya HANAOKA, Kumiko NAKAMICHI

3. Methodology

1. Introduction

3.1 Per capita automobile gasoline consumption [3]This study targets car single trips and the mixed tripsof car and walking. The targeted trips constitute themajority of car using trips (97.5%). It’s a reasonableproxy for the amount of the car use. The automobile
gasoline consumption for each unit distance on weekday
was calculated using Eq.(1) and Eq.(2) in considerationof traffic congestion etc. using car velocity. 𝑆𝑆𝑐𝑐 and ��
was calculated by ratio of car and walking in every trips.
829.3
FC=
-0.8572vc+0.007659vc 2 +64.9(1)

Outflow of population from rural areas causes
population increasing in metropolitan area which resultsin wider and wider range of living area. As urban area
spread chaotically to suburbs, where transportation
facilities, especially public transportation are not in place,residents have high dependence on automobile. As aresult, motorization was progressed rapidly that caused
higher environmental load. Moreover, Japan is facing
problems of population decreasing and aging, especiallyin local area, which makes urban center declining. Since
the city is sprawled with low population density, thewhole city is no longer efficient for infrastructure
management and welfare care.
Compact city is considered as an efficient andecological urban structure with the concept of highpopulation density, mixed land use and residential zones
linked by public transportation[1]. In April 2014, Japan
modified “Act on Special Measures concerning Urban
Reconstruction”, which makes local government
formulate “Location Optimization Plans” and decide“UrbanFunction-attracting
Districts”
andResident-attracting Districts” along public transportation
corridors, in order to promote compact city policy. While
determine Location of the Urban Function-attracting
Districts and the Resident-attracting Districts, there is aneed of database reference that based on the latest urban
data on scale of residential zones which corresponds actual
scale of urban development plans. To begin with, it’s
important to clarify the transition of residential zone types
in the past based on nationwide data. Though Hashimoto
et al.[2] focused on change of population density, analysis
for other characteristics of residential zones is required.
The objective of this study are 1) to clarify transitionof characteristics of residential zones and the relationshipwith automobile use, 2) to make new residential zones
classification based on the latest data considering resultsof objective 1).

vc

GC=FC*𝑆𝑆𝑐𝑐(2)
FC: Gasoline consumption per kilometer
vc: Automobile speed.
Sc: Distance by automobile
3.2 Residential zones classification model
For objective 1), comparison of residential zones types
in 1992 and 2010 was based on existing residential zones
classification[4].
For objective 2), five characteristics (Table 1) thathave high relation with the concept of compact city are
decided as classification criteria. Compared with existingclassification[4], non-city planning area is added as one
land use regulation type.
Table 1 Residential zone characteristics used for classification
Items

Categories
Central City in Metropolitan Area (CM)Satellite City in Metropolitan Area (SM)City type
Central City in Local Area (CL)
Local City in Local Area (LL)
1: < 50 (persons/ha)
Population
2: 50 ~100 (persons/ha)density
3: 100~150 (persons/ha)
4: ≥150 (persons/ha)
25% ~50% (UCA-1)
Urbanization
50% ~75% (UCA-2)
control area
≥75% (UCA-3)
Low-height residential ≥90% (LR-1)
60%-90% (LR-2)
use
Residential
High,medium-height ≥90% (HR-1)
type
residential use
60%-90% (HRGenertal residential use ≥60% (GR)
Neighbourhood
Commercial≥60% (C-1)
commercial use
Land use
type
Commercial use≥60% (C-2)
regulation≥60% (I-1)
Industrial Ligh industrial use
Ind.and exclusively
type≥60% (I-2)
ind.useResidential-commercial mixed type (RCM)
Mixed-use residential (M-R)
Mixed use
Mixed-use commercial (M-C)
type
Mixed-use indurstrial (M-I)
Non-city
Non-city planning area>urban planningplanning area
area (NCP)
Distance to the
1:<1 (km)nearest station
2:≥1 (km)1: <1.6 (km)Distance from
2: 1.6~<5 (km)city center
3: ≥5 (km)2. Data Collection and Target
The National Person Trip Surveys (NPTS) in 1992 and2010 are used for gasoline consumption calculation andresidential zones classification. Population density iscollected from the National Population Census bycorresponding to each district to survey zone of NPTS.
The ratio of each land use regulation area is calculated
by overlapping municipal map, district map andurbanization control area map from the National Land
Numerical Information (NLNI) with using GIS. The
latitude-longitude of zones’ center, stations and city centerof every city are collected from NLNI and changed into
rectangular coordinate, in order to calculate distance from
center of zones to city centers or the nearest cities.
Research target of objective 1) are zones investigatedin NPTS in both 1992 and 2010 (except Tokyo). Zones
of NPTS in 2010 are used for objective 2). Since survey
target and zone names of NLNI and NPTS are different
from each other, zones could not be found in both ofthem are excluded. In order to ensure accuracy of
average gasoline consumption, zones with less than 5
persons are excluded. As a result, 1,878 zones in 69
cities were analyzed in this study.

Fig.1 shows the classification process. Correlation
coefficient (r) of characteristics with gasoline
consumption are criteria for classification. r is significant
when |r|≥1.9407*x-0.498 (Eq.(3)). Eq.(3) is cumulative
approximate of r when p=0.05, x=sample number. For
criteria 3 and 4, categories were decided based on Table
1, but categories were merged when difference of29average gasoline consumption was less than 200cc.

UCA-1
UCA-2
UCA-3
LR-1,2
HR-1,2
GR
C-1
C-2
I-1
I-2
RCM
M-R
M-C
M-I

Step1: Set city types as criteria 1, and land use regulation as criteria
2
Step 2: Calculate coefficient correlation of gasoline consumption
with remaining items
No relation

End

Step 3: Choose item with highest
significant |r| as criteria 3

Step 4: Determine categories of criteria
3Choose criteria 4
for each category
with same method

Fig.1. Process for classification of residential zones types

4. Results and Discussion
Among 601 common investigated residential zones in1992 and 2010, 53 zones (22/135 residential zones types)
disappeared and 10 types of them are residential type. Byplotting residential zones with more than 5 zones
changed to, we found many residential zones was
belonged to residential land use types changed tomix-use land use types (Fig.2). There is no big change inresidential zones belongs to commercial type. Changesof land use regulation occurred in 300 zones. When land
use regulation changed into residential-commercial
mixed use from other land use regulation, gasoline
consumption decreased remarkably.
Based on residential zones data in 2010, 1,878 zones
are classified into 119 types. Table 2 shows theclassification result of CL. In CL, gasoline consumption
depends on location of zones in that city. Gasoline
consumption of zones in CM and SM is low and has highrelation with population density. Zones in LL generally
have high automobile use and low population density,and relation of gasoline consumption with urban layout
is weak. As for land use regulation, residents living inzones that contain commercial areas tend to have lower
gasoline consumption.

Fig.2 1992-2010 change of residential zones types(CM)
Table 2. Classification result of CL
Zone
types
CL1
CL2
CL3
CL4
CL5
CL6
CL7
CL8
CL9
CL10
CL11
CL12
CL13
CL14
CL15
CL16
CL17
CL18
CL19
CL20
CL21
CL22
CL23
CL24
CL25
CL26
CL27
CL28
CL29

5. Conclusion
This study analyzed 1,878 residential zones of 69
cities which can cover all existing residential zones inJapan and calculated automobile use of each zone type.
Zone types of 66.7% of common investigated zones
changed from 1992 to 2010, especially many specificresidential land use regulation districts changed tomix-use land use districts.
This study shows urban layouts affects automobile use,
but the zone characteristics that affects automobile use
differs a lot in case of land use regulation and city types.
Many residents in local area are living in zones belong to
non-city planning area with high automobile use.
Therefore the “Location Optimization Plan” needs to bepromoted in local areas. This study analyzed
characteristics of residential zones and how it affects
automobile use by residential zone type classificationand the results proved compact city urban layout isefficient in reducing automobile use.
For further study, analysis of residents attributes suchas age and household type in every zone types could
show patterns of residents flow needed in every
residential zone types. That will be an indicator of ideal
house moving which has high relation with urban
function location.

Population
Distance Distance to Gasoline
No. ofdensityfrom citynearestconsumpt
zones(persons/ha) center (km) station (km) ion(cc)
<1.6
521.8
UCA-1
5
1.6~5
911.8 23UCA-1
≧51208.7 17UCA-1<50
1092.9 21
UCA-2<1
938.4 12UCA-3
≧11184.7 60
UCA-3
838.9 63
RCM
<1.6
828.2
LR-2
1
≧1.6
1034.1 25
LR-2
<100
≧1
1017.5LR-1
5<100933.4 24
HR-2
<50
<1.6
<1
854.3
HR-1
2
<100
≧1.6
<1
520.7
HR-1
3
≧1
916.6
>1.6
3
HR-1
<5
<1
702.5 41
GR
<100
<5
≧1
855.0 21GR
≧51108.2
7
GR
≧5
574.2
C-1
7
<5
704.2 26
C-2
<1.6
564.8
I-1
3
≧1.6
776.5
7
I-1
<100
<5
<1
907.6
I-2
4
<50
<5
800.3 42M-R
≧51155.8
<100
8
M-R
<100
824.9
M-C
8
≧100
<1
509.3
2
M-C
<100
<1
893.7 11M-I
≧11139.5
<100
4
M-I
≧5
1019.0 36
NCP
Land
use

:Criteria 3:Criteria 4

References[1]OECD: Compact City Policies, A comparative assessment, OECD
green growth studies, OECD publishing, 2012[2] 谷口守, 松中亮治, 橋本晋輔: 公共交通整備状況と地区人口密度からみた都市拡散の関連分析, 都市計画論文集, No.44-1,
pp.117-123, 2009.
[3]平野全宏, 中道久美子, 谷口守, 松中亮治: 都市別自動車 CO2
排出量の定量化とその経年変化分析, 環境システム研究論文集,
Vol.36, pp.19-26, 2008.
[4]中道久美子, 谷口守, 松中亮治: 交通環境負荷低減に向けた都市コンパクト化政策検討のためのデータベース「住区アーカイブ」の構築, 土木学会論文集 D, Vol.64, No.3, pp.447-456, 2008.

30

Numerical Analysis of Tsunami Overflow behind Coastal Dykes
Student Number: 12B10811

Name: Tomoya NAKAMURA

Supervisor: Hiroshi TAKAGI

1. Introduction
The 2011 Great East Japan Earthquake and Tsunami
caused devastation of sea dykes, exacerbated by
overflow and scouring behind the structure. In the courseof the reconstruction from the disaster, the Committee
for Technical Investigation on Countermeasures for
Earthquakes and Tsunamis of Cabinet Office emphasizedthat coastal protection facilities need to be more resilient
so that a moderate structural performance which
contributes to a reduction in tsunami impacts could besustained even after the dyke has been partiallydestroyed. In order to put this into practice, themechanisms on how a coastal dyke has been devastatedneed to be more understood. Particularly, the influenceof the shape of coastal dykes on the tsunami overflow
should be investigated.
This study, took the following steps: (1) conducted afield investigation to measure the dimensions of thecoastal dykes; (2) verified the numerical model bycomparing with previous experimental data; and (3)evaluated the tsunami overflow behind a coastal dyke in
Ishinomaki using a hydraulic model.

Fig.2 The coastal dyke under construction in
Ishinomaki City (photo taken on Sep 2015)

3. Numerical analysis
In this research, ANSYS FLUENT (Ver.16.1) wasapplied to investigate the tsunami overflow passing thecoastal dyke. Firstly, the comparison with experimental
data [1] was made in order to confirm the suitability of
the numerical analysis. Secondly, numerical analysis of
tsunami overflow using the three types of dyke was
performed.
Table.1 Calculation settings for vertical 2D simulation

Investigatingtsunamioverflow
L17m×H1.5m L500m×H49m
0.5cm ~ 5cm
0.1m ~ 1.0m
0.001sec
0.01sec
120sec150secTsunami-like
Cyclic waves
wave
Water surface elevation at theoffshore boundary andtransmitted wave condition at theinshore boundary
Navier-Stokes equation,
Continuity equation
Model
verification

2. Field Investigation

Domains
Grid space
Time increment
Total duration

The authors conducted a field investigation to measure
the dimensions of new coastal dykes using ahigh-precision GPS and leveling staff in Ishinomaki Cityand Sendai Plain. The shapes of coastal dykes aredifferent between Ishinomaki City and Sendai Plain, andthus three different shapes of coastal dikes were analyzed
in this research:
1) Type A: Thin rectangular wall with 5-m height (thedyke type in Ishinomaki before the 2011 event);
2) Type B: Trapezoidal shape with 1:2 slope and 5-mheight (the dyke type in Sendai Plain after the event);3) Type C: Trapezoidal shape with one sloping side with
1:2 slope (inward) and one vertical side with 7.5-m
height (seaward) (the dyke type in Ishinomaki after
the event).

Wave type
Boundary
conditions
Basic equations
TurbulencemodelFree surface
analysis model

3.1
Ishinomaki City

Standard k-εVolume of Fluid Method

Validation of the model from theexperimental data

The model validation was conducted by comparing thewater pressures measured from the experiment, in whicha vertical breakwater was placed as shown in Figure 3.
Input wave is a cyclic wave with a period of 1s and wave
height of 10cm. The data of experiment and the result of
numerical analysis measured at 6cm below the water
surface were processed by a bandpass filter (0.5~20Hz).
The comparison of the results is shown in Figure 4.
Despite the minor differences being observed, the resultsof numerical analysis fitted well the experimental values.

Sendai Plain
Fig.1 The locations of the coastal dikes
investigated in the current study

Pressure sensors

Fig.3 The breakwater installed in the experiment31

Numerical analsys

Pressure(kPa)

0.5

Experiment

0.3
0.1-0.1 0
-0.3
-0.5

2

4

6

time(s)Fig.4 The result of comparison between numericalanalysis and experiment

3.2 Flow characteristics around dykes
3.2.1 Settings of numerical analysis

Fig.8 Velocity around dykes

Numerical analysis was performed under the settings
shown in Table 1. The dimensions derived from the field
investigation were used for the three models. The heightof the dike for all models was set to 7 meters. Velocity
and water level was measured at 25m, 50m, 75m and
90m points behind the dyke. In order to avoid the effectof unrealistic wave reflections from the offshore
boundary, relatively short-period tsunamis were used as
input wave as depicted on Figure 5. Therefore, it is notedthat this study focuses on the maximum velocities andwater levels, rather than the time-history of tsunami
overflows.

3.2.3 Water level behind the dykes
Figure 9 shows the results of relation between water
depth and tsunami. Four cases of incident tsunamis with
6m, 7m, 8m and 9m-height were used. To obtain theflow rates, the authors multiplied the maximum value ofvelocity and water depth for each case. The result showsthat Type B produced the largest flow rate. This may be
attributed to the shape of the dyke where the sloping side
facing the sea causes weak reflection waves. Figure 5
shows that Type A and Type C induce higher waterlevels than Type B due to reflection from the dyke.
water depth(m)type-A

type-B

type-C

3
2.5
2
1.5
1
0.5
0
5

6

7

8

9

10

height of tsunami(m)Fig.9 Water depth and tsunami heightflow rate(㎡/s)

Fig.5 Input wave (offshore wave height 9m) andwater levels simulated 150m off the dyke

Fig.6 Cross-section of the domain with Type A dyke

5

3.2.2 The velocity behind the dykes
Figure 7 shows that Type A dyke produced the least
velocity values, which may be attributed to the strong
turbulence generated behind the dyke as shown in Figure
8.
Velocity(m/s)

9.5

9

10

The numerical model was validated through thecomparison with the previous experimental data.
Furthermore, the effects of the difference in dyke shapeto velocities and water levels behind the dykes wereconfirmed.

type-B1078height of tsunami(m)type-C

4. Conclusion

type-A

10.5

6

type-B

Fig.10 Flow rate and tsunami height

11.5
11

type-A

35
30
25
20
15
10
5
0

type-C

9
20

40
60
80
Distance from dyke(m)References

100[1] 高木泰士，中島ちひろ (2007):“防波堤に作用する重複波圧の推定精度の定量的評価に関する研究”，土木学会論文集 B，Vol.63，No.4，
pp291-294，2007

Fig.7 The relationship between velocity anddistance from the dyke

32Effects of arc current and voltage between electrodes on arc re-ignition
Student Number:12_03640

Name: Tadayuki Omata

Supervisor: KunioTakahashi

time, which is time that arc current is stopped, is controlled byoutput of PIC.

1 Introduction
Arc discharge is an electrical breakdown of a gas that
produces a plasma discharge, resulting from a current throughnormally nonconductive media such as noble gas. Arc
discharge is applied to welding because it has hightemperature around seven thousand to twelve thousand degree.
The breakdown voltage usually ranges from a few kV to tens
kV. But arc re-ignition voltage is lower than the breakdown
voltage. The arc re-ignition is same to the voltage needed tohold arc discharge, usually around tens voltage.
In arc welding, anode has higher temperature than cathodebecause of emission of energy which is equivalent to work
function of anode. This causes problems because the amount ofmelt effects on strength and shapes of welded part. So it isimportant to control arc re-ignition, which means it is possible
to stop arc among intended time and re-ignite arc discharge in
the arc holding voltage. To do so, it is needed to know themechanism of arc re-ignition at lower voltage. In this research,
the effect of arc current before the re-ignition and voltage
between electrodes on the re-ignition is investigated.

R1

③
②

①

Fig.2 electrodes and arc discharge circuit
Fig.3 shows how voltage between electrodes is controlled. I isampere of current flowing in R1. Ic is an ampere of controlledcurrent before the current is interrupted. U is voltage between
electrodes. τ is arc-less time. FET on or off in Fig.3 means thegate source voltage of FET is high or low. Re-ignition in Fig.3
means start of arc re-ignition after arc current is interrupted.
Before arc current is interrupted, I=Ic, U is determined bycurrent-voltage characteristic. When arc current is interrupted,
I and U is zero. After the end of arc interruption, U become
same to Vc, because electrical voltage of drain source of FET
and R1 is zero. So U is controlled by controlling Vc after theend of arc interruption

2 Experimental Equipment
Electrode bars are used in arc re-ignition experiment. The
electrodes for anode and cathode have a same material andform. The material is W containing 2% ThO2. The diameter is
1mm. The electrodes is covered by a glass tube and Ar is flowed
into the tube for preventing oxidation. The flow is around
0.17m3 /min. The distance of electrodes, d, is controlled by amicrometer connected to the anode.

Fig.3 image of U control system after arc-less time

3 Experiment Result
When FET control or stop arc current, certain amount ofvoltage is generated at Vds, which is drain source voltage of
FET. So, in order to know current control is worked, Vds ismeasured in the arc re-ignition experiment. The schematic
illustration of waveform is shown in Fig.4. Vds is determinedby amount of interrupted current and voltage. In arc-less time,
Vds increases to Vc, therefor U is zero and arc current isinterrupted. After arc-less time, Vds is zero because current is
not interrupted. When I start to increase and reaches certain
amount of ampere, current control also starts. Therefor Vds
starts to increase.
At first, re-ignition experiment is done in case that Ic=0.8～
1.4A, U=30～60V, d=5.0mm, 10.0mm, and τ=700μs. In Fig.5, I
showed results of success of the re-ignition in each of theconditions. ○ is in case of d=5.0mm. □ is in case of
d=10.0mm. △ means success rate is from 30% to 70％ in caseof d=5.0mm. White means success and black means failure.
Field intensity is calculated by U/d.

Fig.1 schematic illustration of electrodes
Arc current and voltage between electrodes are also controlled
by the experimental circuit. The circuit is shown in Fig.1. The
circuit contains three differential amplifiers, non-converting
amplifier, FET and a capacitor. The capacitor is used as aconstant power supply and the capacitor is charged by transfer.
When arc current flows, the current control system is started.
Increasing current in the resistance R1 shown in Fig.1, The
output of ① increases. The difference between output of ①
and another output of ③ is output of ②. Then non-converting
amplifier adds output of ② to gate source voltage of FET. So,
the more there is electric potential in R1, the less gate source
voltage is. Therefor arc current is controlled.
When there is output from PIC, the input to differential
amplifier of ① is zero. Then voltage of output of ① is below
zero. So, gate source voltage of FET is also below zero and FET
is off. So, arc current flowing in R1 is stopped. Therefor arc-less33

U=50V

○

○
U=40V
U=30V

Fig.4 schematic illustration of waveforms of current, U, andVds in the arc re-ignition experimentFig.7 a part of current waveform in case of different U

4 Discussion
In Fig.5, it is found that both of arc current and electric
intensity affect success of the arc re-ignition. It is shown that
if distance between electrodes were not same, the success of the
re-ignition is expected by measuring the arc current and field
intensity calculated by U/d.
On the process of breakdown between electrodes, there is a
vibration of arc current having certain amount of time period.
The increase of current with the vibration would be concernedwith 𝛾𝑝ℎ and 𝛾𝑖 effect as shown in Fig.8.
The effect happens when electrons collide with anode, and theenergy is released as photons. Some photon makes ions near
the anode. The ions go across electrodes and collide withcathode and electrons are released. That is called for γi effect.
Other photons released in anode collide with cathode directly
and make the cathode to release electrons. That is called for
γph effect. These electron would be measured as current with
two type of vibrations having certain amount of time period
which is when electron and ion cross the electrodes.

Fig.5 Results of arc re-ignition in case that Ic=0.8～1.4A, U=30
～60V, τ=700μs, and d=5.0mm,10.0mm
Fig.6 is a part of current waveforms in case that Ic=0.8A, 1.0A
and 1.2A, U=30V, d=5.0mm, τ=200μs. The time range of Fig.6
is from 200μs to 350μs. The zero point is start of τ. Verticallines are drawn at the points when Vds is 1V in each conditions.
Current control is not started before the intersections ofwaveform and vertical lines, because 1V is low compared with
U. ○ in Fig.6 are points of intersection of the current
waveform and vertical line.
In Fig.6, all waveform succeeded arc re-ignition. There arevibrations at waveform of Ic=0.8A and 1.0A. The time period is
60μs and 40μs. Looking more detail, it is found that there arevibrations having another time period ranging from 220μs to250μs at the waveform of Ic=1.0A and ranging from 330μs to340μs at the waveform of Ic=0.8A.

Ic=1.2A○

Fig.8 image of α, γph and γi effect

Ic=1.0A○

5 Conclusion○

Arc current and field intensity affects success of arc reignition. The waveform of current of arc re-ignition isinvestigated and it is shown that it is different how arc current
or field intensity affect arc re-ignition. There is a possibility
that 𝛾𝑝ℎ and 𝛾𝑖 effect works in arc re-ignition.

Ic=0.8A

Fig.6 a part of current waveforms in case of different Ic
Fig.7 is a part of current waveform in cases that
Ic=0.8A,U=30V, 40V, and 50V, d=5.0mm, and τ=200μs. The
time range is from 200μs to 230μs, and the zero point is whenarc current is interrupted.
In each of waveforms, the rate of increase of arc current isdifferent. The more U is, the higher rate of increase is. There
are vibrations of arc current in case of U=30V and 40V. Each of
the time periods is 3μs and 60μs.

6 References
1:Masanori Hara, Yousuke Sakai, “KITAIHOUDENNRONN”
Asakurasyoten 2015

2:Orimo “the Effect of Arc Current andDistance between Electrodes on Reignition Executable Timein DC Arc Discharge” bachelor thesis, Tokyo Institute ofTechnology, 201534

Analyzing linkages between solid waste management and other urban development
sectors in developing countries: The case of Dhaka City, Bangladesh
Student Number: 12_07105

Name: Shinnosuke SAWAMURA

Supervisor: Naoya ABE

1. Introduction
Globally more people live in urban areas than in rural
areas, with 54% of the world’s population residing inurban areas in 2014 [1]. Particularly developing
countries are experiencing much faster urbanization thanwere ever experienced by today’s developed countries.
Due to this situation, cities in developing countries havenumerous problems in various sectors such as solid
waste management (SWM), water supply, sewerage,
drainage, air pollution, slum, and transportation.
Recently inclusiveness for urban development has been
more emphasized by Sustainable Development Goals,
which includes “Make cities and human settlements
inclusive, safe, resilient and sustainable” as Goal 11,
indicating that managing city sustainably is indeed a
global challenge.
On the other hand, various government organizations
are commonly approaching such urban problems
individually. However, these urban problems are often
inter-linked with each other. For example, if solid waste
is uncontrolled, scattered waste could block drains in thecity, worsening flood. Therefore, linkages between
SWM and other urban development sectors need to beclarified within the overall framework of urban
development.
Dhaka city is one of the cities being rapidly urbanized.
The city has a population of 8.91 million and an area of
316 sq. km [2], and is divided into North and South parts.
The city also has multiple urban problems, and there arealso various government organizations such as Dhaka
Water Supply and Sewerage Authority (DWASA),
Capital Development Authority (RAJUK), Dhaka North
City Corporation (DNCC) and Dhaka South City
Corporation (DSCC), approaching them. In addition,
multiple donor agencies have implemented numerous
projects to assist such organizations in specific sectors.
Figure 1 shows past implemented projects for Dhaka city
development. However, coordination among theseorganizations is quite weak [3]. Therefore they need tobe more coordinated but it hasn’t been discussed enoughin which linkage public entities should enhance thecoordination. So inter-sectoral linkages occurring in thecity and their priorities should be clarified.

Fig.1: Numbers of ODA for Dhaka city (2003-2014)

3. Methodology
Semi-structured interviews were conducted with a helpof a local waste management expert in September 2015.
The numbers of respondents are summarized in Table 1.
Table 1: Numbers of respondents
Position

R

DNCC
N

R

DSCC
N

Chief Waste Management
Officer (CWMO)
0111
Zone Waste Management div.
Assistant CWMO
5545Conservancy Officer
1
2~5
2
2~5
Conservancy Inspector
8
30~40
10
30~40
Cleaner/labor
0 3,000~
0
3,000~
Total
14
17
Note. R: number of respondents N: number of populations

Three questions were mainly raised in the interview:priorities of SWM components, priorities of urban
development sectors except SWM, and significant
linkages between prioritized urban development sectors
and SWM components. Respondents were asked to
select highest, 2nd-highest, and 3rd-highest of thecomponents and the sectors respectively, and also toanswer any significant linkages as an open question.
As for the data analysis, this study evaluated priorities
of inter-sectoral linkages by two criteria: the number of
responses, and the priorities of related SWM
components and urban development sectors. As for thenumber of responses, the more officers answered thelinkage, the more prioritized it can be. Then three
things—related SWM components, related urban
development sectors except SWM, and influence
direction between former two things—characterize alinkage. There are two cases of influence direction. One
case is SWM components have a negative influence on
the sectors, and the other case is an opposite one. A
linkage can be also prioritized if related
components/sectors
influenced
by
the
other
sectors/components are highly prioritized. To evaluatepriorities of SWM components and urban development
sectors, correspondence analysis and cluster analysis
were conducted.

2. Objective
The objective of this study is to clarify linkages
between SWM and other urban development sectors andthese priorities recognized by officers at waste
management department (WMD), DNCC and DSCC
(DCCs). This objective was designed in order to clarify
inter-sectoral linkages between problems occurring in
the city. This study in particular focuses on SWM sector
due to its high visibility in many Asian cities.
The officers working at WMD, DCCs know thissituation very well as practitioners of SWM. Theyfrequently communicate with players relevant to SWM
such as citizens and other related governmentorganizations. So they have wider perspective on SWM
in the city.

35

4. Results

As a result, the linkages marked with stars are found as
particularly important and have much higher priorities.
Also, all mentioned linkages have some common
features and could be classified into four groups.

The results of the analyses for priorities of SWM
components and urban development sectors are shown in
Figure 2 and 3. Based on numbers of responses andevaluated priorities of components/sectors, linkages
were evaluated as shown in Table 2. Table 2 shows only
the linkages mentioned by more than eight respondents.

5. Discussion
As for urban planning, there is Dhaka Metropolitan
Development Plan (1995-2015) prepared by RAJUKwith assistance from UNDP/UNCHS. However, it
doesn’t consider SWM at all.
As for legal enforcement against illegal waste practices,
police doesn’t adequately play its role and duties but
DCCs substantially supplement the police’s role without
its legitimacy of regulation. The legal responsibility
against construction waste is unclear neither.
As for drainage and SWM sectors, both of them haveserious problems: weak drainage function due to too olddrainage facilities and quite low waste collection rate.
As for transportation, still serious traffic congestion
frequently occurs in the city, even though multiple
projects to improve transportation have been conducted.
These are the reason why four major linkages of urban
problems written in Table 2, occurring in the city.

Fig. 2: Priorities of SWM components

6. Conclusion
Four critical inter-sectoral linkages among urban
development sectors are found in this study, namely
those between urban planning and SWM, legal
enforcement and SWM, drainage and SWM, andtransportation and SWM respectively. Thus those four
linkages should be prioritized for better and sustainable
development of Dhaka city in the future.

References[1] United Nations. (2014). World Urbanization
Prospects The 2014 Revision, United Nations: New
York, U.S.A.
[2] Bangladesh Bureau of Statistics. (2011). Population& Housing Census 2011.
[3] SENES Consultants Ltd. (2007). Dhaka Metropolitan
Development
Plan
Strategic
Environmental
Assessment, The World Bank: Washington, D.C.

Fig. 3: Priorities of urban development sectors

Table 2: Evaluation for priorities of linkages between SWM and other urban development sectors
Related SWM
Influence
Related urban
Linkagesna
componentsb
direction
development sectorsb
Group A: Lack of consideration for SWM by Urban Planning★ No space secured for secondary collection
17
Secondary Collection (3)←Urban Planning (4)Group B: Legal Enforcement against Illegal waste practices★ Little observation of relevant laws by citizens
14 Road & Drain Cleaning (1)(illegal dumping. illegal land possession,
Public Involvement (4)←Institutional Arrangement (3)etc.)
Legal Aspect (2)Inappropriate construction works (illegal
9Road & Drain Cleaning (1)←Institutional Arrangement (3)dumping, illegal construction, etc.)
Legal Aspect (2)Group C: Interdependency between SWM and Drainage★ Blockage of drains by solid waste
14
Primary Collection (4)Road & Drain Cleaning (1)→Drainage (3)Public Involvement (4)Legal Aspect (2)Insufficient drain cleaning and management
9→
Drainage (3)Road & Drain Cleaning (1)by other organization, particularly DWASAInstitutional Arrangement (3)←Waste scattered by water-logging
8
Road & Drain Cleaning (1) ←Drainage (3)Group D: Traffic congestion obstructing SWM★ Traffic jam obstructing secondary collection
14
Secondary Collection (3)←Transportation (2)Note. an is the number of responses. bThe numbers in parentheses mean 4: much higher, 3: higher, 2: slightly higher, 1: lower.

36東アジア域内におけるバルク貨物コンテナ化の要因分析
学籍番号:12_15955 氏名:米澤 祐介 指導教員:花岡 伸也
1.

はじめに1960 年代のコンテナ革命以降，海上貨物に占める国間貿易のコンテナ化率を推定するモデルを構築し，どのような要因が影響するのかを明らかにする．二段階最小二乗法は，同時方程式による偏りを避けるために用いられる手法である．本研究では，総輸送量がコンテナ化率を推定する際に用いる説明変数であると同時に，コンテナ化率を算出する際の分母ともなっているため，二段階最小二乗法により同時方
程式バイアスを避ける必要がある．
一段階目の重回帰式(1)では，操作変数𝑲𝒊 とコンテ
ナ化率𝑌𝑖 の外生変数𝑳𝒊 を用いて二国間貿易の総輸送量𝑋𝑖 を推定する．二段階目の重回帰式(2)では，得られた推定値𝑋̂𝑖 と外生変数𝑳𝒊 を用いてコンテナ化率𝑌𝑖を推定する．
コンテナ化率・総輸送量を算出する際に，性質上コンテナ化ができない品目は除いた．分析対象とする航路は，陸続きとなっている二国間航路を除いた
東アジア域内の航路とする．

コンテナ貨物の重量ベースの比率(コンテナ化率)は上昇を続けてきた．しかし，2000 年代後半になるとコンテナ化率は停滞し，2015 年にいたるまで大きな変動がない．また，コンテナ輸送が抱える問題の一つとして，インバランスによる空コンテナの返送がある．バルク貨物のコンテナ化は空コンテナの返送
費用削減のための有効な解決策の一つと考えられている．
特に東アジア域内では，2015 年までコンテナ取扱量そのものは増加し続けているのにもかかわらず，
コンテナ化率は 2000 年代後半からむしろ減少傾向にある．また，域内には経済発展度や貿易タイプの点で様々な国が存在することから，多角的な分析が可能である．
以上の背景を踏まえ，本研究では東アジア域内におけるバルク貨物コンテナ化の要因を明らかにすることを目的とする．

2.

手法と結果

(1) 品目別分析
品目別分析では，ｋ-平均法を用いて７つの変数を基に東アジア域内で輸送される品目のグループ化を行い，どのような特性を持った品目でコンテナ化が進んでいるのかを分析する．
コンテナ
化率平
均 (%)

単価
平均
($/kg)

総輸送量
平均(十万ﾄﾝ)

コンテナ
輸送変化(十万ﾄﾝ)

バルク
輸送変化(十万ﾄﾝ)

1(21)

15.04

-0.09

92.70

3.66

9.9

5.6

-0.8

2(19)

0.75

-0.47

25.53

1.92

21.0

3.2

8.4

3(4)

11.03

1.44

44.39

1.08

310.6

102.9

86.2

4(8)

32.85

3.65

56.34

0.76

20.1

12.8

-2.7

5(3)

-5.38

-0.10

5.14

0.14

183.5

-4.3

159.2

6(1)

0.00

-0.27

64.98

179.34

0.14

0.1

0.1

7(7)

11.43

-1.71

30.40

0.69

110.5

34.1

38.8

8(66)

3.60

-0.78

87.68

7.98

9.1

5.6

0.8

9(4)

6.55

12.79

51.06

0.45

6.7

2.6

-1.3

13.13

-23.37

75.81

0.75

22.6

(2)

一段階目の操作変数と結果

F-statistic

コンテナ化
率変化
20082014(%)10(3)

𝑌𝑖 = 𝛽0 + 𝛽1 𝑋̂𝑖 + 𝛽2 𝑳𝒊 + 𝛿𝑖
① 一段階目

表2

クラスター分析結果

コンテナ化
率変化
20002007(%)

クラスター
(品目数)

(1)

一段階目の重回帰式の結果を，表 2 に示す．F 値
が 10 を超えているため，弱相関操作変数の問題はないと考えられる．
また，総輸送量に影響を与え，コンテナ化率に影響のない操作変数として，輸出国 GDP，輸入国 GDP，二国間の主要港の航路距離を用いた．

本研究では，以下の三つの分析を通してコンテナ化率の要因を明らかにする．

表１

𝑋𝑖 = 𝛼0 + 𝛼1 𝑲𝒊 + 𝛼2 𝑳𝒊 + 𝜀𝑖

16.9

14.34

操作変数

単位

平均

標準偏差

輸出国 GDP

Trillion $

1.22

1.80

輸入国 GDP

Trillion $

1.22

1.80

海里

1563

772

主要港湾間の距離② 二段階目
二段階目の重回帰式に用いた説明変数と予測される符号を表 3 に示す．

表3

7.5

表１より，クラスター番号 1,8 を見ると，コンテ
ナ化率平均がそれぞれ 92.70%，87.68%と高く，また 2008 年以降のコンテナ化率が停滞している．これにより，工業製品や生鮮食品に分類される品目に関して，2007 年までにコンテナ化が高い割合まで進んだために，それ以降のコンテナ化率が停滞していることが明らかになった．またクラスター番号２を見ると，コンテナ化率平均が 25.53%と低く，2000
年以降ほとんどコンテナ化が進んでいない．これにより，ドライバルク貨物に分類される品目は近年コンテナ化が進んでいないことが明らかになった．しかし，以上の要因は品目別分析では特定できなかっ
た．

輸出国
特性

輸入国

予測符号

単位

+

百万 TEU

30.90

43.2

取扱量
地上インフラ

+

-

3.55

0.5

整備
生鮮食品

+

%

3.73

2.9

工業製品

+

%

74.28

14.2

コンテナ取扱量+

百万 TEU

30.90

43.2

取扱量
地上インフラ

+

-

3.55

0.5

整備
生鮮食品

+

%

2.94

1.3

工業製品

+

%

64.44

10.9

総輸送量

-

百万ﾄﾝ

4.23

4.8

単価平均

+

$/kg

5.70

6.0

インバランス

-

千 TEU

5.84

240.5

特性

二国間
特性

二段階目の説明変数

コンテナ取扱量

説明変数

平均

標準偏差

重回帰式の結果を表 4 に示す．なお，輸出国の工業製品割合とインバランスは有意と表れたが，予測符号と異なっており，他の説明変数間との相関が考えられるため，それらの変数を除いたものを最終的(2) 航路別分析
航路別分析では，二段階最小二乗法を用いて，二37

な結果とした．

表４

二段階目の結果

説明変数
コンテナ取扱量
輸出国
特性① 特定の品目による影響

地上インフラ整備
生鮮食品

係数

t-value

0.0000000018

4.40***

0.08832.03**

0.016246

2.50**

0.00000000058

1.22

生鮮食品

0.0106

1.91*

工業製品

0.0024

2.11**

二国間

総輸送量-0.0000000089-1.93*

特性

単価

0.0084

3.98***

コンテナ取扱量
輸入国
特性

誤差の大きい航路で輸送される品目を細かく見ると，コンテナ化されやすい品目として分類されているが，実際にはそのコンテナ化率が高くない品目があった．一つが香港発日本向き航路における金属
スクラップ，もう一つがフィリピン発航路におけるバナナである．これらの製品はそれぞれ工業製品，
生鮮食品に分類されているが，そのコンテナ化率は非常に低いものであった．
これらの品目のコンテナ化率が低い理由として，
どちらも単価が非常に低いことが原因の一つと考えられる．また，バナナに関してはその輸送量が非常に大きいため，バルク船を利用するニーズが高いことも原因と考えられる．

0.39

修正済み決定係数

Note: ***１％有意, **５％有意，*１０％有意② 単価による影響
コンテナ化率が実際よりも高く推定されたフィリピン発ベトナム向き航路，ベトナム発インド
ネシア向き航路に共通する性質として，著しく低い

この結果より，輸出国の特性として地上インフラ
整備，コンテナ取扱量，また貿易タイプとして生鮮食品，輸入国の工業製品の割合，二国間特性として，
総輸送量と単価が重要な要因であることが明らかになった．なお，コンテナ取扱量はその国のコンテナ
港湾設備の代理指標として用いている．
しかし，予想に反して二国間のインバランスは符号が異なる結果となった．理由として，東アジア域内
での航路は比較的短いものが多く，コンテナ運賃を大きく引き下げるほど空コンテナの返送費用が大きくないことが考えられる．
また輸入国の地上インフラ整備・コンテナ取扱量も重要な要因とは示されなかった．地上インフラ整備に関しては，以下の理由が考えられる．一般に工業部品や金属などのバルク貨物を受け入れる荷主の工場などは港の近くにあることが多く、港からの陸送距離は長くない．そのため地上のインフラ整備が重要な要因とならなかった可能性が考えられる．
コンテナ取扱量に関しては，以下の理由が考えられる．一般にコンテナ輸送では，輸出国はコンテナ
貨物を大きなコンテナ船に積み込み，途中のトラン
シップ港でコンテナ貨物を小さいコンテナ船に積み替えて輸入国へ運ばれることが多い．そのため，輸出国側では積み込みを行うために大規模なガントリ
ークレーンなどの設備が必要であるが，輸入国側は大きな港でなくても積み下ろしを行うことができる
ことから，輸入国側でのコンテナ取扱量が重要な要因とならなかった可能性が考えられる．

(3)

平均単価があった．これにより，単価が著しく低い
航路においては，荷主はコンテナ化する利点を享受できない可能性が考えられる．

3.

詳細分析

詳細分析では，航路別分析で構築したモデルとの誤差が大きく表れた航路を分析し，特定の航路に影響を与えている要因を明らかにする．表 5 は，残差分析により誤差が有意に大きいと特定された航路と，実際の航路のコンテナ化率とモデルで推定されたコンテナ化率を表したものである．

表5
輸出国

誤差の大きい航路
輸入国

推定された
コンテナ化率

実際のコンテナ化率Philippines

Vietnam

57.2%

24.2%

Philippines

Hong Kong

75.3%

46.5%

VietnamIndonesia

50.7%

25.0%

Hong Kong

Japan

66.4%

44.6%

Hong Kong

Vietnam

65.6%

87.7%

Indonesia

Hong Kong

61.0%

85.3%

結論

本研究では，東アジア域内におけるコンテナ化率の要因を明らかにするため，三つの分析を行った．
品目別分析では，生鮮食品・工業製品がコンテナ化されやすい特性を持つ品目であることが特定された．
航路別分析では，コンテナ化率に影響を与える要因
として，輸出国のコンテナ取扱量と地上インフラ整
備，二国間の総輸送量と単価を示した．また，コン
テナ化率を進める要因であると考えられてきたインバランスが，航路の短い域内においては重要にはならない可能性を示した．さらに特定の航路において，コンテナ化されやすい性質の品目のコンテナ化が進んでいないことを明らかにした．また著しく平均単価が低い場合において，モデルの推定ほどにコンテナ化が進まない可能性を示した．
今後の課題として，別の地域におけるコンテナ化率の分析により，本研究で明らかにした要因の検証が必要である．

38

参考文献[1]MartinStopford: “Maritime economics”, Routledge,

2009．
[2]松田琢磨，川崎智也: “バルク貨物コンテナ化の決定要因について－北米/韓国・台湾航路における金属スクラッ
プ輸入の分析－”, 海運経済研究，No.47，pp.65-73,
2013．
[3]Jean-Paul Rodrigue and Theo Notteboom: “Looking
inside the box: evidence from the containerization ofcommodities and the cold chain”, Maritime Policy &Management，Vol. 42，No. 3，pp.207-227, 2015．

Application of Non-Linear Conjugate Gradient Method in Expectation Maximization Method for the
Performance Improvement of Radio Channel Parameter Estimation
Student Number: 12B15688 Name: Yunyi Yao
1

Introduction

Supervisor: Jun-ichi TAKADA

2.2 Parameter Estimation and Obejective of this work
MIMO Channel Matrix, which is dependent on transmitted signal and recieved signal,can be modeled by eq(1).

Recently, demands for high-speed and wide-band wireless communication system have been increasing significantly,and thesesystems are occupying most favorable electromagnetic spectrum
for wireless communication (below 6 GHz band). Natrually, next
generation mobile radio networks (5G) requires research toward
the characteristics of channels at higher frequencies where we
could occupy a larger bandwidth. Takada lab are focusing on
11GHz center frequency with 400MHz bandwidth which is acandidate carrier wave in next generation.
In the other hand, MIMO transmission is a powerful techniqueto improve the quality of wireless link transmission. Therefore,
researh on performance of 11GHz based MIMO transmission
becomes our motivation. However, the performance of MIMO
communication systems is strongly dependent on propagation
environment which is uncontrollable, so it is necessary to build
an accurate MIMO channel model to evaluate the performance.
To build such a model, propagation parameters of channels mustbe figured out accurately at first. EM-SAGE is well known asparameter estimation algorithm but its estimation performanceis limited by resolution and huge computation. The aim of thisresearch is to apply a gradient-base algorithm in parameter estimation in order to improve the accuracy and convergence speed.
Super-high accuracy parameters estimation algorithm will help
us to have better understanding of relationship between propagation environment and transmitted wave.

H(f ) =

LX
l=1

aR,l (ϕR,l , θR,l , f )·Γl ·aTT,l (ϕT,l , θT,l , f ) e−j2πf τl(1)where H(f ) ∈ CMR ×MT , Γl ∈ C2×2 represents tensor form ofpath weight. L is total number of paths considered, and MR , MTis number of antennas elements at transmitter and receiver side,
aR,l , aT,l are array response function of anttenna at transmitterand reciever with respect to the all propagation parameters mentioned above and a certain frequency f . Since we are considering
a wide-band with multi frequency bin, then eq(1) needs to be expanded as follow.
s = vec {H} = B(µ) · γ ∈ CMR .MT .Mf ×1(2)

where Mf is number of sampling points in frequency domain.
B(µ) ∈ CMR .MT .Mf ×4L is a description to structure of thewhole radio channel.γ ∈ C4L×1 is vectorization of Γ. Noticethat matrix µ ∈ CL×5 and γ now contains all groups of pathparamters. And this 2 parameter matrix is the target that wewant to estimate from measured channel transfer function. Eq(3)shows us how to estimate this 2 matrix which is based on Maximum Likelihood Estimation [3].
hiHµ̂ = arg min (x − s) (x − s)
(3)
µ

2

where x ∈ CMR .MT .Mf ×1 is exactly the data of measured MIMO channel transfer function. Therefore, according
to this formular, parameter estimation evantually became 5Ldimensional optimization problem. SAGE [3] is a popular algorithm to optimize multi-dimensional discrete function which
is very appropriate to be applied in this problem. Because inreal measurement, array response aR,l , aT,l are not continous
function but discrete data-base with respect to all sampling angle
point and frequency point which causes the structure of wholeradio channel B(µ) can only be changed discretely. The basic
concept of SAGE is, first decompose the measured data x into
L part which represent information of L paths, then estimate parameters path by path through optimizing likelihood function ofeach path. However, SAGE faces problem that estimation accuracy and convergence speed are limited by given number ofsampling points of array response which we can call resolution
level. Above all, we come to our objective which is applying a
gradient-based algorithm instead of SAGE in order to improve
performance of MIMO channel parameter estimation.

Over view of Parameter Estimation

2.1 Propagation Parameters
Fig.1 descirbes what are propagation parameters. In Ray-based
MIMO channel model [1], transmitted signal is modeled by thesuperposition of multi paths, every path is unique and can be
desribed by a group of parameter, Direction of Departure (DoD),
Direction of Arrival (DoD), Time delay of Arrival (ToA), andDual-polarized Path Weight, l represents path ID. We can define a parameter vector to put them together except path weight.
µl = τl θT,l ϕT,l θR,l ϕR,l ∈ R5×1

3

Proposal

3.1 NLCG alogrithm

Figure 1: Propagation Parameters

39

Non-Liner Conjugate Gradient method is one of the most efficient methods on optimizing multi-dimensional continous function. The basic concept of NLCG is to minimize a multidimensional continous function L(µl ) by constructing a series

NLCG Estimation Result-8
Estimated Value
Modeled Value

τ(ns)

80

-8.2
-8.4

60

-8.6

40

-8.8

20
0

|γ VV|2(dB)

100

-9

0

50

100

150

200

250

300

350

DoDazm[deg]NLCG Estimation Result

-8

100

Estimated Value
Modeled Value-8.2(b) Step-length-searchτ(ns)(a) Search direction

-8.4

60

-8.6

40

Figure 2: Geometric interpretation of NLCG in 2D space

-8.8

20
0

|γ VV|2(dB)

80

-9

0

50

100

150

200

250

300

350

DoAazm[deg](a) Proposal result
SAGE Estimation Result-8100
Estimated Value
Modeled Value

-8.2
-8.4

60

-8.6

40

-8.8

20

(a) Case 1(b) Case 2

0|γ VV|2(dB)

τ(ns)

80

-9

0

50

100

150

200
DoDazm[deg]

250

300

350

SAGE Estimation Result-8
Estimated Value
Modeled Value

100

-8.2
-8.4

60

-8.6

40

-8.8

20
0

-9

0

50

100

150

200

250

300

350

DoAazm[deg](c) Case 3(b) SAGE result

Figure 3: Geometric interpretation of SW condition based
step-length-search(k+1)
position vector µl

Figure 4: Simulation result under same initialization condition

call effective aperture. Another advantage is we can get derivative at same time because NLCG must require derivative of thetarget function.

(k)µl + α(k) d(k) until the function(k)=converge at minimizer. where dis search direction(vector)
in each iteration, and it is defined by what we call conjugate
garadient which is constructed by gradients. α(k) is called steplength(scalar) that determine how long should it travel along thesearch direction in each iteration to make function decrease significantly. This method has been introduced in parameter estimation before [2]. but in [2], optimazation result is limited
by step-length-search procedure which causes exactly the sameproblem as SAGE which is resolution limitation. The geometric interpretation of minimum search procedure by [2] is showed
in Fig2. In this Fig, we simulated a very simple case, there are
only two parameter Azimuth at Tx (ϕT )and Azimuth at Rx(ϕR )in total, so the target function L(µ) we want to minimize is only
2-dimensional.

4

Simulation and Evaluation

Fig4 shows the estimation results by both Proposal and SAGE
under simulated propagation environment. In this modeled channel, there were 10 paths with 10 group of modeled randomparamters. And we gave SAGE and NLCG the same initialization condition, every initial value in delay domain are set into(0)(0)
τl =< τlmodeled >. In angular domain, ϕT,l =< ϕmodeled
>
T,l
(0)

±4[deg], and ϕR,l =< ϕmodeled> ±4[deg]. <> means nearest
R,linterger.

5

Conclusion

In this paper we proposed a gradient-based method to improve
performance of radio channel parameter estimation. Compare to
SAGE algorithm, this proposal do have advantage on accuracyof estimated results and convergence speed.

3.2 SW condition based step-length-search method
To remove resolution limitation of parameter estimation using NLCG, we introduce a efficient non-resolution based steplength-search method named Strong Wolfe condtions based steplength-search method [4]. Strong Wolfe condtions help us to define what kind of step length we need to take. And step-lengthsearch method help us to find such a step length. The search
procedure can be visualized in Fig3.

References[1] Calcev, G. and Chizhik, D. and Goransson, B. and Howard, S. and Huang,
H. and Kogiantis, A. and Molisch, A. and Moustakas, A. and Reed, D. andXu, H., ‘A wideband spatial channel model for system-wide simulations,”
IEEE Transactions on Vehicular Technology, pp. 389-403, 2007.

3.3 EADF of Array Response[2] Shizhi ZHANG, “11Ghz indoor MIMO Channel Parameter Estimation Using Gradient Method,” Master Thesis, Tokyo Institute of Technology, 2014.

The neccessary condition for removing resolution out of estimation is to make array response continous. Because of limitationof given sampling angle and frequency points, all we can do is tointerpolate the information between every sampling points, andcreat a continous function instead of discrete data-base to describe array response. Effective Aperture Distribution Function
method [5] is the way we did to the data-base. EADF can be considered as multi-dimensional Fourier series expansion of the discrete data-base. An advantage of this approach is that the EADF
typically is concentrated to a very small support area which we[3] B. H. Fleury, M. Tschudin, R. Heddergott, D. Dahlhaus, and K. I. Pedersen, “Channel parameter estimation in mobile radio environments using the
SAGE algorithm,” IEEE J. Sel. Areas Commun., vol. 17, no. 3, pp. 434-450,
1999.
[4] Jorge Nocedal and Stephen J.Wright, ”Numercal Optimization”, ed. Peter
Glynn Stephen M. Robinson,isbn: 0-387-98793-2, pp. 100-132, SpringerVerlag New York, 1999.
[5] M. Landmann and A. Richter and R. S. Thoma, ”DOA resolution limits in MIMO channel sounding”, International Symposium on Antennas
and Propagation and USNC/URSI National Radio Science Meeting, Monterey,CA, pp. 1708-1711, 200440

|γ VV|2(dB)

τ(ns)

80

Concept study of a nano Mars lander with extendable aerodynamic device
Student Number: 12-01775 Name: Yuta IMAI Supervisor: Daisuke AKITA
1 Introduction
1. ConceptThis paper proposes a mission that entries
Mars’ atmosphere and lands on Mars’ surface
with a nano size lander. The nano lander has
two merits that are cost effective and mission
flexible.

position of
spacecraft
D
h

mg

L
γ

r

θ

v

O
Mars

Fig. 3 Motion equations model

(1)

(1)

Fig. 1 Mission model𝑡 [s]: Time from entry𝑣 [m/s]: velocity
𝛾[deg]: flight path angle𝑟 [m] ∶ distance from the center of Mars𝜌[kg/m3 ]: density of atmosphere𝜃[m]: longitude
𝜇𝑚 [m3/s 2]: a product of Mars mass
and gravitational constantβ [kg /m2 ]: ballistic coefficient
L/D[−]: lift − to − drag ratio

Figure 1 shows the mission scenario. The
lander is separated from a mother ship before
Mars entry. The extendable aerodynamic device
is deployed before the Mars entry. The
extendable aerodynamic device reduces the
aerodynamic heating during atmospheric entry.
The lander withstands aerodynamic heat andland on Mars’ surface.
As the extendable devise, bi-convex is used.
Bi-convex which has a shape like a combinationof two steel tape measures are able to be storedby winding as shown in Figure 2.Theextendable aerodynamic device is attached to
the lander as shown in Figure. 1.

The equation is numerically calculated by 4thorder Runge-KuttaMethod to estimate a
trajectory of the lander. Initial v is 5.6[km/s].
Initial height as shown Figure 4 is 125 [km],Initial flight path angle is 10[deg].
3 Requirements of aerodynamic characteristics
Four requirements ①~④ shown in Fig. 1
come down to requirements of aerodynamic
characteristics, which refer to ballisticcoefficient and lift-to-drag ratio in this study.
Temperature of surface of the lander have tobe less than 900[℃] to protect the payload.
The heat flax [W/m2 ] is estimated by Tauber’sequation. Temperature of lander is given by
Stefan-Boltzmann law using the heat flax given
by Tauber’s equation.
The result of aerodynamic heating calculation,
ballistic coefficient is required to be less than
9.10[kg/m2 ].
For requirement ② , maximum dynamic
pressure acting on the lander is needed to
below 100[Pa] .To meet this dynamic pressure
requirement, aerodynamic characteristics are

Fig. 2 Bi-convex
This lander has four requirements shown infigure 1.
2. Motion equations and entry trajectory
Motion of the lander is considered in polar
coordinates as shown Figure 3.
Forces acting on the lander are only the Mars
gravity and the aerodynamic force. The motion
equations of the lander are given by Eq. (1).

41needed to be inside of blue area in figure 4.
To obtain 10[km] controllable down range, L/D
is required to be more than 0.27.Since thelanding velocity should be less than 43[m/s] toprotect the payload. Result of trajectory
calculations, the ballistic coefficient is required
to be less than 3.08 to meet the requirement.
These
consideration
shows
that
the
requirementsfortheAerodynamics
characteristics are 𝛽 < 3.08 and L/D > 0.27.

Fig. 6 range of ∅ and Lb/Lt
Fig. 4 requirement of aerodynamic
characteristics for dynamic pressure condition
4 Estimation of aerodynamic characteristics
The aerodynamic characteristics are
estimated by Newtonian impact theory. This
theory gives 𝛽 /m [1/m2 ] andL/D. m is the total mass of thelander.
Aerodynamic characteristics ofthe lander are evaluated for theangle ∅ and Lb/Lt shown in
Figure5.

Fig.7 minimum mass model
References[1]Shunsuke Tanaka: “An environment of
re-entry spacecraft flight”, JAXA-RR-04-056
6-2., 2005

Fig.5 model for Newtonian
impact theory
Total mass is estimated fromthe cross sectional shape of
Bi-convex. 𝛽 /m is given by
Newtonian impact theory.
Figure 6 shows a range ofangle ∅ and Lb/Lt those meet the requirements
when Lb is 3.0[m]. Red shaded area shows
feasible design parameters. Figure 7 shows aminimum mass model.

[3]Lobia Marcus:“A Framework for the Design
and Optimization of Waverider-Derived
Hypersonic Transport Configurations”,
Ph.D.thesis.University of Tokyo ,2003

5. Conclusion
It is shown that nano size lander is able toarchive landing on Mars’ surface. A shape of thelander is shown Fig.6, and mass is 2[kg]. Thislander has only small capability of payload, but
it has potential to active research Mars.

[4] Michael J. Grant∗ and Robert D. Braun:”Analytic Hypersonic Aerodynamics forConceptual Design of Entry Vehicles”, 48th
AIAA Aerospace Sciences Meeting Including
the New Horizons Forum and Aerospace
Exposition4 - 7 January 2010, Orlando, Florida[2]Akihiro Tamura: “Analytical solution of thebending of a bi-convex boom”, MechanicalEngineering Journal, Vol.2, No.6,201442

Image coding by Slant Vector Embedded Discrete Cosine Transform
Student Number:08 02231

Name:Kento Itai

Supervisor:Yukihiko Yamashita

It can be approximated by using K(≤ M ) basis func-

1 Introduction

tions {Φ2k+1 }K
k=1 .

DCT (Discrete Cosine Transform) is an orthogonal

K−1∑transform which is the most frequently used in im-

αk Φ2k+1 .

(6)

k=0

age coding, because DCT has the energy compaction

I difine KK-dimensional ventors φ0 , φ1 , ..., φK−1 byproperty. It can approximate the Karhunen-Loévetransform when the correlation between neighbor pix-

φ0 (j)= αj{
1 (i = j)
φi (j)=
0 (i =
̸ j)els are very high [1]. However, basis vectors of DCT
are cosine funtions so that DCT is not suitable forencoding a gradiation area where pixel values varies(7)

for i = 1, 2, ..., K − 1 and j = 1, 2, ..., K − 1.

linearly. For that reason, Yamada et. al proposed toI orthogonalize them. It would be better not to mix

selectively use ST (Slant Transform) instead of DCT

higher frequency components to lower frequency com-in a gradation area [2]. In this paper, I propose a moreponents because of the energy compaction property ofsimple method. I embed a slant vector to DCT. I call

DCT. Therefore, I propose a modified Gram-Schmidt

it SVEDCT (Slant Vector Embedded Discrete Cosine

orthonormalization. I denote the orthogonalized vec-

Transform). I show its advantage by experiment.

tors by φ′0 , φ′1 , ..., φ′K−1 . First, let φ′0 = φ0 . The
two dimensional vector (φ1 (0), φ1 (1)) is orthogonal-

2 Overview of SVEDCT

ized to (φ′1 (0), φ′1 (1)) by using the original Gram-

I discribe how to embed a slant vector to DCT. Let

Schmidt orthonormalization. Then, I pad zeros tox be an N -dimensional signal in RN . Let Φ(i)/(i =φ′1 (j). Next, (φ2 (0), φ2 (1), φ2 (2)) is orthogonalized to0, 1, ..., N − 1) be the i-th DCT basis function. DCT(φ′0 (0), φ′0 (1), φ′0 (2)) and (φ′1 (0), φ′1 (1), φ′1 (2)). I pad

is given by the inner products between x and Φi .
X (i) = ⟨x , Φ(i)⟩.

zeros to φ′2 (j) similarly. Let U be a (K, K)-matrix of(1)which (i, j)-component is φ′i (j). Since DCT has fastalgorithms, I can get SVEDCT by applying U to theIts inverse transform is given by

first, third,...(2K-1)-th DCT coeﬃcients.
x=

N
−1
∑

X (i)Φi .

2.2

(2)

For image coding SVEDCT should be extended to

i=0

2.1

2D-SVEDCTSVEDCTa 2D transform. In this paper I propose two exten-

I difine a slant vector s by
s(n) = √∑

N −1
2 −n
N −1 N −12i=0 { 2 − i}sion methods. The first method applies SVEDCT separately to horizontal and vertical directions. I call.

(3)

this method 2DS-SVEDCT (2D separable SVEDCT).
However, this method has a disadvantage, since many

Because of the symmetry of DCT, s is expressed bytransform coeﬃcients are diﬀerent from those of DCT.

basis vectors of which orders are odd. Therefore, I

These diﬀerences may make the performance worse

define αk (k = 0, 1, ..., M − 1), M ≡ ⌊N/2⌋ by
αk = ⟨s, Φ2k+1 ⟩.

because of the energy compaction property of DCT.
(4)

The other method is to apply SVEDCT to the DC coeﬃcients of DCT for the other coordinate. I call thisThen, I have
s=

M
−1
∑

αk Φ2k+1 .

method 2D-SVEDCT. In this method, diﬀerences of(5)

coeﬃcients are less. Therefore, it will be possible to

k=0

43

reduce the impact on the energy compaction propertyof DCT.

3 Experiments
I examined the performance of SVEDCT. Fig.1(a) Gradation, 2DS(b) Gradation, 2D(c) Lenna, 2DS(d) Lenna, 2D

shows original images. I compress these images byusing DCT, 2DS-SVEDCT, and 2D-SVEDCT. Fig.2
shows the results of image coding. I use the baseline
JPEG coding scheme and apply the same quantization
factor for all coeﬃcients. The vertical and horizontal
axes show the PSNR and the bit rate, severally.

Fig.3: Rate distortion relations for K=2, 3, and 4

2DS-SVEDCT and 2D-SVEDCT outperform DCT
for the artificial gradation image. For the three natural images, the results by respective transforms arealmost the same. Fig.3 shows rate distortion relations for K=2, 3, and 4 at (6). The results by 2DS(a) Gradation(artificial)

SVEDCT (K=2) are worse than those by K=3 and(b) Lenna

4. For artificial gradation image, the results by 2DSVEDCT (K=2) inferior to others. The results by
2D-SVEDCT (K=2, 3, and 4) are almost the same fornatural images. In all cases, the performances of K=3
and those of K=4 are almost the same. Therefore I
can use K=3 to reduce of the amount of calculations.
(c) Barbara

4 Conclusions(d) Peppers

I proposed the SVEDCT and two types of 2-

Fig.1: Original images

dimensional SVEDCT. Then, I compare performancesof SVEDCT among K=2, 3, and 4. I show the advantages of SVEDCT over DCT and the most suitablevalue of K by experiments. For future works, I haveto conduct experiments with larger image block forexample 16 × 16 (K=2, 3, ..., and 8).

References[1] N.Ahmed, T.Natarajan, and K.R.Rao, ”Discrete(a) Gradation(b) Lennacosine transform,” IEEE Transactions on computers, vol.C-23, no.1, pp.90-93, (1974)[2] Yoshihisa Yamada, Shuichi Yamagishi, and Michihiko Minoh: ”High quality image coding method for
gradation areas by using slant transform”, Journal
The Institute of Image Information and Television(c) Barbara

Engineers vol.65, no.11, pp.1594-1602 (2011)(d) Peppers

Fig.2: Rate distortion relations

44

A PROTOTYPE OF ENERGY HARVESTING EQUIPMENT FOR COMPOSTHEATStudent Number: 12-00706 Name: Koomok Lee Supervisor: Takahashi Kunio
The result shows that the TE module has
constant internal resistance.

1. Introduction
The quantity of waste heat with a lowtemperature is vast amount. For effective use ofunutilised energy, technologies for recovering
waste heat have been investigated andthermoelectric module (TE module)Bi-Te based
alloys as a thermoelectric material is expected to
be used to recover waste heat under 150℃[1].
Among those heat sources, compost heat is
expected to be recovered by using TE module.
Compost has been used as a soil conditioner andis made when organic materials are decomposedby microorganism in aerobic condition. Duringcomposting, the temperature of compost reaches
up to 60~70℃ and lasts up to 2 weeks depends
on the characteristics of compost[2].Previous
studies have investigated the reuse of compost
heat as a water heater by designing water pipe
inside the composting facility[3]. This paper
aims to widen the use of compost heat as a
power generation by designing a prototype ofenergy harvesting equipment using TE modules.
By giving temperature gradient across the TE
modules using water, this prototyped equipment
is devised both as a water heater and power
generation. Also, the performance of theequipment was evaluated by the amount ofrecovered heat energy from water and electricalenergy stored in capacitor through energy
harvesting experiment.

2.3. Prototype of Energy harvesting equipment
Figure 3 shows the prototype that was designedin this study. 15 TE modules were used, i.e. 5
modules were connected in series and 3 of each 5
module in parallel, sandwiched between two
copper plates. The prototype is intended to put
on top of the compost to have one face heated by
the compost, whereas the other face is cooled bywater supply. The electrical energy is finally
boosted up by a boost converter with tracking
the Maximum Power Point (MPPT) of TE
module[4], and then stored into the capacitor.
Temperature of the compost inside the reactor ismonitored and recorded, while the electric
potential generated by the prototype is recorded
to a logger.

Fig.2: Inside the reactor

2. Materials and Method
2.1. Composting materials
Compost reactor (φ:323mm, height:323mm) in
Nakasaki lab was used for composting andenergy harvesting experiment. As a compostingmaterial, oil cake, saw dust and Aurace G weremixed. The mass of compost was 3kg.
2.2. TE module and its I-V characteristic
TE module(9500-127-085B,Ferro tech) is used
to convert compost heat to electrical energy. By
applying
temperature
gradient
using
temperature controller and heat sink across theboth sides of the modules, the I-V characteristicof the module was examined to investigate theperformance of the module. Current and voltage
were measured by varying resistors(1~15Ω).

Fig.3: Assembled prototyped equipment
2.4. Experimental description
The energy harvesting experiment was done for3 times and each experiment was started when
the initial temperature of top and bottom side of
the compost ranges 60~75 ℃ . Heat energy
recovered by water, accumulated electricalenergy in capacitor and heat of combustion by
microbial activity was calculated during theexperiment. Air flow rate(30L/h),temperature ofair, inlet/outlet temperature of water, water flow
rate, accumulated voltage in capacitor, volume
percent of 𝐶𝑂2 in exhaust air were measured
and monitored to calculate recovered energy.
Through each experiment ① , ② , ③ ,few
parameters were modified as shown below to

Fig.1: Results of I-V characteristic

45

investigate the energy recovery efficiency bywater and electrical energy and in an attempt tomaximise the temperature gradient across themodules.
①:Water flow rate kept at 30mL/s②:Water flow rate kept at 15mL/s③:Water flow rate kept at 30mL/s+pipes covered
with polystyrene foam to insulate heatexchange between water and compost heat.
Also, the temperature change of top and bottomof the compost was monitored to investigate theeffect of the equipment during the experiment.

compost heat recovery, using water + power
generation, the slower the water flow, the moreheat energy will be recovered.
From the experiment ①，③,the result showsthat 𝑄𝑤 ① > 𝑄𝑤 ③ , by insulating the heatexchange between 𝑄𝑤 and 𝑄𝑚 so that ③𝑇𝑡𝑜𝑝
cooled faster than ①𝑇𝑡𝑜𝑝 . Since the quantity of
𝐸𝑐 is small amount than that of 𝑄𝑤 , it isdifficult to judge the energy efficiency between
𝐸𝑐 ① and 𝐸𝑐 ②.

3. Results and discussion
The results of each experiment ①,②,③ wereshown below.

Temperature[℃]70

4. Conclusion
This prototyped equipment was made in an
attempt to widen the use of compost heat both asa water heater and power generator using TE
module. And it is confirmed that through energy
harvesting experiment, compost heat will berecovered more efficiently using water than as aelectrical energy using TE module. Although theaccumulated electrical energy was small amount,
it is expected to acquire electrical energy
proportional to the increase of the quantity ofcomposting materials. For that, further energy
harvesting experiment is needed where the heatof combustion by microbial activity is larger
than heat energy loss by water within thecomposting system.

①Ttop

65

②Ttop

60

③Ttop

55

①Tbottom50②Tbottom

45
0

5

10

15

20

③TbottomTime[min]Fig.4: Temperature change on top and bottom of
the compost
Table.1: Heat energy recovered by water (𝑄𝑤 )
①
②
③
unit
𝑄𝑤
673.40971.00544.56kJ

References[1]Shindo
Takahiko,Nakatani
Yujiro,Oishi
Takashi, Thermoelectric Generating System for
Effective use of unutilized energy, Toshibareview,Vol.63,No.2,(2008)[2]Nakasaki Kiyohiko, "微生物利用のエコテクノ
ロジー -コンポスト化- ",静岡県資源環境技術研究会,Jun.1997.
[3]G. Irvine, E.R.Lamont, B.Antizar-Ladislao,
Energy from Waste: Reuse of Compost Heat as a
Source of Renewable Energy, International
Journal of Chemical Engineering, Vol.2010,(2010)[4] Asami Ryushi,Prototype of an autonomous
energyharvesting
systemusing
boost
converter,Tokyo Institute of Technology, masterthesis,(2014

Table.2:Accumulated
electricalenergyincapacitors (𝐸𝑐 )
①
②
③
unit
𝐸𝑐
148.9
107.6
152.1
J
Table.3: Heat of combustion by microbialactivity during experiment(𝑄𝑚 )
①
②
③
unit
𝑄𝑚
1.41
2.16
1.25
kJ
3.1. Recovered energy and temperature of thecompostFrom the experiment ① , ② , ③ , 𝑄𝑤 is muchbigger than 𝐸𝑐 and 𝑄𝑚 .It means that energy
from compost heat is considered to be recovered
more efficiently using water compared to as anelectrical energy and it is expected that compost
will be cooled below 40℃ using the equipmentin this composting system. It is necessary tomaintain the temperature of compost heap
above 50℃ for sterilisation within compost[2]. It
is desirable to use large quantity of compost
during composting when recovering compost
heat using water.
From the experiment ①,②, it is considered that,higher the water flow rate, the more electricalenergy will be generated. But in terms of whole46

Liquid-Liquid Equilibrium of Sodium with Organophosphorus Acid as Extracting Agent
Student Number: 12B14499

Name: Nobuyoshi MORISupervisor: Ryuichi EGASHIRA, Hiroaki HABAKI
Table 1

Experimental conditions in solvent extraction of
sodiumFeedaqueous solution of
sodium, Na (NaCl)
Volume, Vaq [m3]2.0×10−5+
Concentration of Na ,CNa,aq,0 [kmol m−3]0.25 ~ 1
pH, pH00 ~ 14(adjusted by HCl, NaOH)
Solvent
kerosene solution of
PC-88A
Volume, Vorg [m3]2.0×10−5
Concentration of PC-88A,
CRH2,org,0 [kmol m−3]
0.25
Temperature [K]298Time [h]121. Introduction
Solvent extraction is one of the important
methods to separate metals, such as rare earth
metals [1], where the metals are distributed between
aqueous phase and organic phase containing
extracting agent. Organophosphorus acid, e.g., 2ethylhexyl-2-ethylhexylphosphonate (PC-88A) for
rare earth metal extraction, is widely used as an
extracting agent. In the extraction, the metal isexchanged with hydrogen in the extracting agent as,
jMn+ + (x+jn)/2 (RH) 2 ⇄ M j R jn (RH) x + jnH+ (1)where Mn+ is metal ion in aqueous phase and (RH) 2
is the extracting agent dimer in organic phase. Thistransfer of hydrogen into aqueous phase reduces themetal extraction degree. In order to avoid thisunfavorable hydrogen transfer, the extracting agent issaponified with any appropriate me tal, such as,
sodium, in the practical extraction process[2,3,4]. In
this thesis, liquid-liquid equilibrium of sodium withorganophosphorus extracting agent was studied forrare earth metal extraction.

Table 2

Experimental conditions in solvent extraction ofneodymiumFeedaqueous solution ofneodymium, Nd(NdCl3 6H2O)
Volume, Vaq [m3]2.0×10−5
3+Concentration of Nd ,CNd,aq,0 [kmol m−3]
0.005
pH, pH00 ~ 2.0(adjusted by HCl)
Solvent
kerosene solution of
PC-88A
w/ or w/o saponification
Volume, Vorg [m3]2.0×10−5
Concentration of PC-88A,
CRH2,org,0 [kmol m−3]
0.25
Temperature [K]298Time [h]12

2. Experimental
Neodymium was selected as a rare earth metal.
Sodium chloride or neodymium chloride hexahydrate
was the source of the metals. The pH of the aqueous
phase was adjusted with hydrochloric acid or sodiumhydroxide at initial. The organic solvent phase was
kerosenesolutionof
2-ethylhexyl-2ethylhexylphosphonate (PC-88A). All materials wereused without further purification. Tables 1 and 2
show the experimental conditions. The specified
amounts of aqueous and organic phases were brought
into contact in a conical flask. These phases in theflask were shaken in the constant temperature bath tobe equilibrated. After equilibration, settling, andphase separation, both liquid phases were analyzed
using ICP-AES (SPS7800, Hitachi High-Tech
Science Corporation) and pH meter (F-52, Horiba).

At pHeq higher than 5, white turbidity in the
aqueous phase was observed and the turbidity was
kept even after the settling at pHeq=5. This might
result from the surface active effect by the extracting
agent saponified with sodium [6]. In the range ofhigh sodium concentration, heterogeneous threephases were formed at equilibrium. The results of
sodium extraction are shown in Figure 1. Figure 1(a)shows the comparison between the initial andequilibrium pHs, pH0, pHeq. While, in the range ofpH0<3, pHeq was almost the same as pH0, pHeq
decreased after equilibration, where 6<pH0.
The Eq.(1) is rewritten for Na+ as,
jNa+ + (x+j)/2 (RH) 2 ⇄ Na j R j (RH) x + jH+ (5)The equilibrium constant of Na+, KNa, is, thus,
represented with DNa as,
KNa = DNa CH,aq,eqj/(CNa,aq,eqj-1 CRH2,org,eq(x+j)/2)(6)
Based on this equation, log[DNa/(CNa,aq,eqj-1
CRH2,org,eq(x+j)/2)] was plotted over log(1/CH,aq,eq)=pHeq
in Figure 1(d), which is so-called slope analysis.

3. Results and Discussion
The material balance of the metal is written as,
Vaq CM,aq,0 + Vorg CM,org,0 = Vaq CM,aq,eq + Vorg CM,aq,eq(2)
The concentration of metals in organic phase wascalculated using this equation with that in aqueous
phase. The extraction yield, EM, and distribution
ratio, DM, of the metal were defined as,
EM = CM,org,eq Vorg/(CM,aq,0 Vaq)
(3)
DM = CM,org,eq/CM,aq,eq(4)47

reaction formula with j=1, x=3, and KNd=0.0136,
which was much higher than that of sodium,3.12×10−6. The saponification of extracting agent
with sodium did not affect the neodymium
equilibrium, whereas neodymium enhanced thesodium extraction as shown in Figure 1(b).

Fig. 1 Results of sodium, Na, extraction ( ◇ -withoutsaponification, ○-with saponification): (a) pH change;(b) slope analysis under CNa,aq,0=2.5×10−1 kmol/m3

Fig. 2 Results of neodymium, Nd, extraction (-withoutsaponification, -with saponification): (a) pH change;(b) extraction yield; (c) slope analysis

In the range of 5<pHeq, these plots gave straight linewith j=1, x=1, and KNa=3.12×10−6. Shono et al.
reported j=2 and x=2 for sodium extraction with bis(2-ethylhexyl) hydrogen phosphate (D2EHPA), when
pHeq was higher than 4.0[5]. Where pHeq was lower
than 5, log[DNa/(CNa,aq,eqj-1 CRH2,org,eq(x+j)/2)] was higher
and almost constant over pHeq. Although this was
qualitatively attributed to the effect of chloride ion
and it was reported that the chloride ion mightenhance the extraction of metal by forming complex
with metal [7, 8], further study is required.
Figure 2 presents the results of neodymium
extraction with and without sodium. Figure 2(a)shows the pH change by neodymium extraction. The
pHeq was the same as or lower than pH0 without
sodium. The addition of sodium could prevent the pH
reduction as mentioned above. Figure 2(b) shows theextraction yield of neodymium. Neodymium was
extracted into solvent phase. The yield increased with
pH0 and exceeded 0.9 at higher pH0. The yield
could be improved by the addition of sodium aspredicted. Figure 2(c) shows the slope analysis forneodymium extraction with,
jNd3+ + (x+3j)/2 (RH) 2 ⇌ Nd j R 3 j (RH) x + 3jH+
(7)
The experimental results could be well fitted by this

4. Conclusions
The liquid-liquid equilibrium of sodium with theextracting agent of PC-88A was clarified. It was
confirmed that the extraction of neodymium was
improved by the saponification of extracting agent
with sodium.
References[1] 塩川二朗，足立吟也，希土類元素の化学，49, (1981)[2] Man-Seung Lee et al. Separation Purification Technology 46(2005) 72-78[3] I.Kojima et al. Journal of Inorganic and Nuclear Chemistry 31(1969) 1815-1820[4] Isao Komasawa et al. Journal of Chemical Engineering og
Japan 16 (1983) 210-217[5] 庄野厚 ほか 化学工学論文集 24 (1998) 609-614[6] Hailong Hou et al. Chinese Journal of Chemical Engineering
24 (2016) 79-85[7] F.J.Alguacil et al. Revista de Metalurgia Madrid 35 (1999)
255-260[8] Thomas Charles Owens Retrospective Theses andDissertations Iowa State University (1967)

48

Face Recognition under Various Lighting Conditions Using
Relative Karhunen-Loéve Transform
学籍番号: 12B14163

1

名前: ミョウ

ゲツ
(i)

概要

指導教員: 山下幸彦

(i)とし ϕj を λj に対応する固有ベクトルとすると，次式で与えられる。

近年，バイオメトリックス認証やロボットビジョン等の実現を目的として，人間の顔を認識する手法が多数

P (i) =

研究されている。しかし，認識する顔画像の撮影条件

M
∑

(i)

(i) T

ϕj (ϕj )(2)

j=1と，学習用の顔画像の撮影条件が異なる場合，例えば照明等の変動成分が認識画像に含まれる場合，認識性

式 (1) から分かるように，CLAFIC 法は自分のカテゴ能が劣化するという問題が残されている。

リーのパターン集合に関する類内特徴を抽出するもの

パターン認識のための代表的な類内特徴抽出法の一である。しかし，自分のカテゴリーだけ着目している

つに CLAFIC 法 [1](CLAss-Featuring Information Com-

ため，他のカテゴリーと区別するために適した特徴とpression) がある。CLAFIC 法は，自分のカテゴリーのは言えない。即ち，あるカテゴリーに多く含まれる特パターン集合に関する Karhunen-Loéve Transform 変換

徴が他カテゴリーにも含まれる場合，そのような特徴(KL 変換) によって入力パターンから各カテゴリーに関を抽出しても類内特徴量の上では差が生じない。

する類内特徴を抽出し，そのノルムが最も大きくなる

3 相対 KL 変換法

カテゴリーにパターンを識別する。しかし，CLAFIC

識別に適した類内特徴量抽出は，自分のカテゴリーだ法には特徴空間内で近接したカテゴリーの間で誤認識けに含まれる特徴を抽出し，他カテゴリーにも共通にが生じやすい欠点がある。この欠点を改善するため相含まれる特徴や，自分のカテゴリーに含まれない特徴

対 KL 法 [2][3] を提案され，手書き数字認識実験でのを抑制するものであると考えられる。次の評価基準 J2

有効性が示されている。

を与える。
[
]
J2 X (i) =本論文では，相対 KL 変換法を使って顔認識実験を行う。本実験により相対 KL 変換法は CLAFIC 法より照明変動による性能劣化を克服できるか検証する。そし2E ∥f − X (i) f ∥ +αf ∈Ω(i)∑2

ωj E ∥X (i) f ∥j̸=if ∈Ω(j)う場合，相対 KL 変換法の方が認識性能が高いかどう(3)
J2 の第 1 項目は自分のカテゴリーの平均 2 乗近似誤差，第 2 項は他カテゴリーの類内特徴量の平均を表す。

か調べる。

パラメータ α は他カテゴリーの抑制度を表している。

て，学習データとテストデータの照明条件が大きく違

2

評価基準 J2 を最小にする作用素 X (i) を用いて上に述

CLAFIC 法

べた類内特徴抽出することができる。

CLAFIC 法は，パターン認識のための代表的な類内特徴抽出法としてよく知られている。CLAFIC 法で4 実験

は，カテゴリーの KL 変換を用いて類内特徴抽出を行

本実験の目的は次の 2 つである。相対 KL 変換法はう。カテゴリーの総数を K ，特徴空間の次元を N とする。カテゴリー i(i = 1, · · · , K) の KL 変換 P (i) は

CLAFIC 法より照明変動による性能劣化を克服できるか検証すること，学習データとテストデータの照明条

rankP (i) = M (M ≦ N ) という条件で以下の評価基準式
J1 を最小にする線形作用素 P (i) として定式化される。

件が大きく違う場合，相対 KL 変換法の方が認識性能

J1 [P (i) ] =2

E ∥f − P (i) f ∥f ∈Ω(i)が高いかどうか調べることである。
照明問題を扱うための顔データベースとして Yale 大(1)

学の Extended YaleFace B が公開されている。このデー
タベースは，38 個人を 576 条件 (9 姿勢、64 照明方向)

ここで，f は N 次元パターン，Ω(i) はカテゴリー i に属するパターンの集合， E

f ∈Ω(i)で撮影した計 5760 枚の画像で構成されている。64 照は Ω(i) に関する平均を表す。

明方向はカメラの光軸と光源とのなす方位角と仰角かKL 変換 P (i) は，カテゴリー i に属するパターンの相関(i) (i)(i)
行列 R(i) の固有値を λj (λ1 ≥ λ2 (i) ≥ · · · ≥ λN ≥ 0)

らなる座標で定められる。本論文では，姿勢を正面に限定し，最初の 30 人のデータを使用した。

1
49

4.1

α を用いて認識実験を行った。作用素のランクを９に実験 I固定した。パラメータ α と認識率の関係を図 1 に示す。

データベースから 1 人あたり 60 枚の画像 (計 1800 枚)を学習データとしてランダムに取り出した。残りの 4
つの照明方向に対応する画像データ（計 120 枚）をテ

1
No.1
No.2
No.3
No.4
No.5

ストデータとした。作用素のランクは今回の学習デー
タに対して最良の認識率を与える値を用いた。相対 KL

0.8

Recognition Rate

変換法のパラメータ α は，予備実験において高成績を収めた 0.01 とした。認識実験 I の結果を表 1 に示す。
認識率は CLAFIC 法では 87.5%，相対 KL 変換法では94.2% であった。

0.6

0.4

表 1: CLAFIC 法と相対 KL 変換法による認識率
0.2

認識率

CLAFIC 法

相対 KL 変換法

87.5%

94.2%

0
10 -4

10 -3

10 -2

10 -1

10 0

10 1

α

4.2

実験 II

図 1: 認識率とパラメータ α の関係

実験 II では，学習データとテストデータの照明方向
実験結果から，学習データとテストデータの照明条件の違いが大きい場合の性能を，相対 KL 法と CLAFIC

が同じ場合，相対 KL 変換法は CLAFIC 法より認識性法で比較した。方位角が 70◦ より小さい座標に対応す

能が高いことが示された。しかしながら，学習データ

るすべて 40 枚の画像を学習データとして，方位角がの照明条件とテストデータの照明条件が大きく異なる

70◦ より大きい座標に対応する画像データから，方位角が 70◦ ，80◦ ，110◦ ，120◦ ，130◦ の画像データから一つずつランダムに取り出した，計 150 枚の画像をテスト場合，相対 KL 変換法及び CLAFIC 法の両方とも認識性能が低かった。また，相対 KL 変換法でも，CLAFIC
法よりあまり高い認識率が得られなかった。

データとした。作用素のランクを 10 に固定して実験し5 結論た。相対 KL 変換法のパラメータ α は，予備実験において高成績を収めた 0.00005 とした。認識実験 II の結相対 KL 変換法と CLAFIC 法の照明変動による性能劣果を表 2 に示す。認識率は CLAFIC 法では 76.0%，相化に関して検証した。学習データとテストデータの照対 KL 変換法では 76.7% であった。

明条件が同じ場合は，相対 KL 変換法が優れていたが，表 2: α = 0.00005 の場合の認識率

大きく異なる場合は両方法とも性能が低いことが示さ

CLAFIC 法

相対 KL 変換法

No.1

100%

100%

今後の研究としては学習データとテストデータの照明

No.2
No.3
No.4

100%
80%
63.3%

100%
80%
66.7%

条件の違いに対して頑健な認識法を開発すること，及

No.5

36.7%

36.7%

れた。

び他のカテゴリーを考慮する重みを個別に変える方法に関して研究を進めていく必要がある。

6 参考文献相対 KL 変換法のパラメータ α が小さいほど，相対参考文献

KL 変換法は CLAFIC 法に近づくため，少し大きな値である 0.01 を用いたときの結果を表 3 に示す。

[1] S.Watanabe and N.Pakvasa, Subspace method in pattern recognition. Proc. 1st International Joint Conference on Pattern Recognition, Washington DC,

表 3: α = 0.01 の場合の認識率

CLAFIC 法

相対 KL 変換法

No.1

100%

100%

No.2
No.3
No.4

100%
73.3%
50%

100%
53.3%
33.3%

No.5

50%

20%

pp.25-32, Feb. 1973.
[2] 池野靖行，山下幸彦，小川英光， 相対 KL 変換によるパターン認識

電子情報通信論文誌， vol.
2, pp.1031-1033, Aug. 1998.

[3] Y.Yamasita and H. Ogawa, Relative Karhunen-LoéveTransform,. IEEE Trans.on Signl Processing. vol.44,
no.2, pp.371-378, Feb.1996.

パラメータ α と認識率の関係を調べるために，様々な

250Influence of water cement ratio, initial chloride content and chloride fixing admixture on corrosionof steel bar in mortar exposed to marine environment
Student number: 11_19571
name: Koki HASHIZUME
Supervisor: Prof. Nobuaki OTSUKI
1. Introduction
For the use of RC structure in marine environment chloride
attack is serious for its deterioration due to corrosion of steel
bar. To reduce this risk, low initial chloride content andproper water cement ratio (W/C) are recommended
According to previous research of Mizuma¹⁾, after
32 years exposure to marine environment, external
chloride ion is much than initial chloride ion. As theresult, influence of initial chloride content on
corrosion is smaller than that of W/C.
It is considered that chloride ion accelerates
corrosion in incubation period. Therefore influenceof initial chloride content on corrosion in incubation
period cannot be ignored. However influence of W/C
and initial chloride content on corrosion in
incubation period is not clear.
To reduce influence of initial chloride content on
corrosion, the use of Chloride fixing admixture (CF)is considered to be an effective mean. CF has highchloride fixing ability because the main componentof CF is calcium aluminate(CaO・2Al₂O₃). Howeverin case of using seawater as mixing water, influenceof using CF as admixture on material property andcorrosion is not clear.
Considering the background, three objectives are set inthis study.
1) To clarify influence of W/C and initial chloride content
on corrosion of steel bar in mortar exposed to marine
environment for 91 days.
2) To clarify the factor that influences on corrosion of steel
bar in mortar exposed to marine environment for 91 daysand 32 years.
3) To clarify the effect of reducing influence of initialchloride content on corrosion of steel bar exposed tomarine environment with using CF as admixture.
2. Materials and specimens
2.1 Materials
Freshwater and seawater(ASTMD1141-98(2003), Cl ⁻2%) are used as mixing water. Land sand are used as
aggregate. SR235 (Φ: 9mm, length: 100mm) are used forreinforcement. Cement type is OPC (density: 3.17g/cm3,
specific surface area: 3180cm2/g). CF (DENKA) is used as
admixture.
2.2 Specimens
Specimens are prism mortar (40x40x160mm). In mortar,
there is steel bar (the cover is 15mm) to clarify oxygen
permeability and corrosion behavior. Table 1 shows mix
proportion of mortar used in this study. W/C has 3levels(45, 55, 65%). Mixing water has 6types (W: tap water, S:
seawater, 0.25S and 0.5S: diluted seawater to two and fourtimes, 2S and 4S: concentrated chloride ion in seawater
two and four times). The replacement ratio of CF is 10%.

2.3 Exposure environment
These specimens are exposed to artificial tidal environment.
Tidal cycle is 12 hours. This is because to reproduce sameenvironment of specimens exposed to marine environmentfor 32 years.
3. corrosion after 91 days’ exposure
Figure1 shows influence of W/C and initialchloride content on corrosion current density (icorr)
after 91 days exposure. Besides 0.2µA/cm²
proposed by FIB is used to judge corrosion of steel
bar. According to Figure1, influence of W/C is notconfirmed. On the other hand, it is confirmed thatas initial chloride content increases, icorr increases.
Figure2 shows influence of oxygen permeability
and chloride content on steel bar on icorr after 91
days exposure. According to Figure2, influence ofoxygen permeability on icorr is not confirmed. On
the other hand, it is confirmed that as chloride
content on steel bar increases, icorr increases.
Table 1 mix proportion of mortar specimens
W/C
(%)

45-W
45-0.25S
45-S
45-2S
45-CF
55-W
55-0.25S
55-0.5S
55-S
55-2S
55-4S
55-CF
65-W
65-0.5S
65-S
65-4S
65-CF

45
45
45
45
45
55
55
55
55
55
55
55
65
65
65
65
65

Corrosion current density（µA/cm²）

Specimens
Mark

Initialchloride
content(kg/m³)
0
1.45
5.82
11.6
5.82
0
1.67
3.34
6.67
13.35
26.7
6.67
0
3.72
7.43
29.72
7.43

C
(kg/m³)

CF(kg/m³)

W(kg/m³)

S(kg/m³)

652
652
652
652
587
613
613
613
613
613
613
551
577
577
577
577
519

0
0
0
0
65.2
0
0
0
0
0
0
61.3
0
0
0
0
57.7

297
297
297
297
297
337
337
337
337
337
337
337
375
375
375
375
375

1304
1304
1304
1304
1304
1225
1225
1225
1225
1225
1225
1225
1154
1154
1154
1154
1154

1.0E+02
1.0E+01
1.0E+00
1.0E‐01FIB
0.2 µA/cm²

1.0E‐02
1.0E‐03
40

50

60

70

0

W/C（％）

5 10 15 20 25 30 35
Initial chloride content（kg/m³）

Corrosion current density（µA/cm²)

Figure 1 influence of materials on icorr
1.0E+02
1.0E+01
1.0E+00
1.0E‐01FIB
0.2 µA/cm²

1.0E‐02
1.0E‐03
0.0
2.0
4.0
6.0
8.0 0
Oxygen permeability（10⁻¹¹・ｍｏｌ・cm2/sec）

20
40
60
Chloride content on
steel bar（µg/cm²）

Figure2 influence of material properties on icorr

51

1.54

Table3 T value of property to corrosion
Objective Corrosion current density
After 91 days exposure
Explanatory

15
10
5
0

Corrosion current density
After 32 years exposure¹⁾

Oxygen permeability

0.94

3.71

Chloride content on steel bar

4.41

0.28

6.0
5.0
4.0
3.0
2.0
1.0
0.0
45‐W
45‐S
45‐CF
55‐W
55‐S
55‐CF
65‐W
65‐S
65‐CF

1.33

5.12

70
60
50
40
30
20
10
0

Oxygen permeability(10⁻¹¹・㏖・cm2/sec)

0.62

20

45‐W
45‐S
45‐CF
55‐W
55‐S
55‐CF
65‐W
65‐S
65‐CF

W/C
Initial chloride content

25

Chloride fixing ability（％）

Corrosion current density
After 32 years exposure¹⁾

45‐W
45‐S
45‐CF
55‐W
55‐S
55‐CF
65‐W
65‐S
65‐CF

Objective Corrosion current density
After 91 days exposure
Explanatory

Chloride content on steelbar(µg/cm²)

Table2 T value of material to corrosion

Figure3 influence of CF on material properties
1.00.E+01

Corrosion current
density(µA/cm²)

4. Multiple regression analysis on the factor that
influence on corrosion
Multiple regression analysis is used to evaluate
influence on corrosion. Values in Table3 and Table4
show “T value”. Generally, absolute value of “T vale”
exceeding 2.0 shows major influence.
According to Table3, after 32 years exposure,influence of W/C and initial chloride content on icorr
is not confirmed. On the other hand, after 91 days
exposure, correlation between initial chloride
content and icorr is confirmed.
According to Table4, after 32 years exposure,correlation between oxygen permeability and icorr isconfirmed. And after 91 days exposure, correlation
between chloride content on steel bar and icorr isconfirmed.
Comparing the result of 91 days exposure withthat of 32 years exposure, it is confirmed thatchloride ion on steel bar has large influence on
corrosion in incubation period and oxygen
permeability has large influence on corrosion after
propagation.
5. Influence of CF on corrosion
5.1 Influence of CF on material property
Figure3 shows influence of CF on material
properties (chloride content on steel bar, chloride
fixing ability and oxygen permeability) aremeasured after 91 days exposure. According to
Figure3, Chloride content on steel bar in mortar
mixed with CF is reduced to almost the sameamount of that mixed with freshwater. Chloride
fixing ability in mortar mixed with CF is higher
than that mixed with freshwater. Oxygen
permeability in mortar mixed with CF is almost
the same amount of that mixed with freshwater.
5.2 Influence of CF on corrosion behavior
Figure4 shows influence of CF on corrosion
behavior of steel bar. According to Figure4, corrosion
behavior of steel bar in mortar mixed with CF is not
so different from that mixed with freshwater.

FIB
0.2 µA/cm²

1.00.E+00

1.00.E‐01

1.00.E‐02
0
45‐W

55‐W

50
65‐W

45‐S

100
150
Time(day)55‐S 65‐S 45‐CF 55‐CF

200
65‐CF

Figure4 influence of CF on icorr
From above results, CF can reduce influence ofinitial chloride content on corrosion in incubation
period.
Because corrosion behavior move to propagation
period and corrosion rate is controlled by oxygen
permeability. It can be considered that CF doesn’t
influence on corrosion behavior after propagation.
6. Conclusion
1) Initial chloride content has a large influence on
icorr of steel bar in mortar exposed to marine
environment for 91 days. On the other hand,
influence of W/C on icorr is not confirmed.
2) Chloride content on steel bar has a large
influence on icorr of steel bar in mortar exposed
to marine environment for 91 days. On the other
hand, oxygen permeability has a large influence
on icorr of steel bar in mortar exposed to marine
environment for 32 years.
3) CF can reduce influence of initial chloride
content on corrosion of steel bar in mortar
exposed to marine environment.
It is clarified that chloride ion in mortar has large
influence on corrosion in incubation period.
However in case of using CF as admixture, CF can
reduce influence of corrosion behavior of steel bar inmortar mixed with seawater.
7. Reference
1) Ayako Mizuma (2014) Influence of initialchloride content and water cement ratio on
corrosion of steel bar in mortar exposed tomarine environment for 32 years, bachelor
thesis in Tokyo institute technology

52

Environmental Strategies observed in Enterprise Cooperationin Japanese Automotive Industry
Student ID : 12_09239, Name: Kyosuke TANAKA, Supervisor : Naoya ABE

1. Introduction

In order to compete in the globally competitive market,
automotive enterprises seek to take various measures andone of them is “cooperation” with other enterprises.
From the view of enterprise management, enterprise cooperation aims to realize mutually larger profits among
parties and possibly increasing their own market share.
[1] Remarkable point is that some of them cause byadopting renewal regulations, though the relationshipbetween regulation and effect is not clear.
Thus the objective of this study is to investigate
whether or how environmental regulations haveinfluenced on enterprise cooperation.

PM regulation levels(g/kWh)

In Japan, automotive industry is considered one of the
major industries which support the national economy.
The industry has many related industries and thecompetition among the automotive companies at global
scale has been more and more getting. Automotive
industry has been also one of the major targets ofenvironmental regulations by governments because theproduction of this industry requires quite large amount of
resource inputs and also emit various type of solid andambient pollutants, if there is no treatment.
An environmental regulation in Japan started in 1973,
which set limits to the amount of specified gas emissions,
namely CO (carbon monoxide), HC (hydrocarbon), andNOx (nitrogen oxides). In addition to these emission
controls, fuel efficiency and noise reduction regulation
were adapted one after another.
From a global environmental regulatory point of view,
as shown in figure 1, the historical trends of NOx & PM
(particulate matter) regulation levels in Japan, EU(European Union) and the U.S. are not necessarily thesame but continuously getting more stringent, implyingthat the compliance with various regional environmental
regulations are also challenges for globally operating
automotive firms. Automotive companies thus could
have stronger incentives to figure out how they could
maintain their competitiveness in the global market due
to more stringent environmental regulations.
Increasing public interest in environmental problems
and the attitudes by corporates could be found in realizedsocial responsibility of eco-friendly products, researchand development. To be executed it, there are different
possible approaches which include both consideration forenvironment and growth of its enterprise, that is,“environmental strategies.” In order to compete in the
globally competitive market, automotive enterprises seek
to take various measures and one of them is “cooperation”
with other enterprises.

2. Literature Review
There are some of literatures evaluating whether
environmental regulations let companies to be moreinnovative, even if those are supposed to be the threat.
Porter(1991) built the following hypothesis; “Strict
environmental regulations do not inevitably hinder
competitive advantage against foreign rivals; indeed,
they often enhance it.”(Porter, 1991) Some of economists
insisted stronger regulations may become repellents togrow market competitiveness, but others argue it can bevitalizing external factors to research and development.

Figure 2 SWOT Evolution between Regulations
and Innovation(Source: Debnath (2015))

0.8
0.7

Japan(1994)

Debnath (2015) applied SWOT analysis to evaluate theroles of external regulations. Figure 2 shows regulations
can create innovations to help to develop a new productand gain profits; moreover they lead to increase
investment for corporates. These efforts helped
companies to improve their technological capabilities,
and these flows can help companies to create further
innovations. This spiral is basically synonymous with“innovation offset”, which means regulations work
efficiently to improve technologies.
Like this, there are some of theoretical researches ofregulation efficiency, but few empirical researches areorganized based on actual data. The significance of thisstudy is worth of an example of empirical analyses ofJapan’s enterprise decision-making through some of
regulations.

Japan

0.6

EU

0.5

the U.S.

0.4

Tier0(1994)
Japan(2000)
EURO1(1991)
0.3
Japan(1998)
Japan(2005)
0.2
Japan(2003)
EURO2(1996)
0.1 EURO5(2009)
Tier1(1996)
Japan(2009)
EURO4(2005)
EURO3(2000)
0
0
0.1
0.2
0.3
0.4
0.5
Tier2(2007) EURO6(2014)
NOx regulation levels (g/km)

Figure 1 The trends of NOx and PM regulation levels(Source: Compiled by the author based on Japan’s
governmental data)53

3. Data Collection and Methodology

16

For the objective above, the data and information about
the historical evolution as well as the forms ofautomotive enterprise cooperation were collected. The
main source of the information includes empirical data
recorded in each firms and article reporting news. The
analysis covers from 1978 to 2014 for those automotive
enterprises which are members of JAMA (the Japan
Automobile Manufacturers Association, Inc.) Someforeign companies were also considered when they werepartners of a Japanese automotive enterprise.
Table 1 shows the list of the car firms, which wereconsidered in this study and Table 2 shows the types ofcooperation among the firms. As Table 2 indicates, six
different forms of enterprise cooperation were identified
based on details in enterprise cooperation recorded inempirical data.
Analysis method we conduct is categorizing empirical
data into 6 forms and observing the changes of eachcooperation forms. And compering the changes andenvironmental regulations, we evaluate how regulations
effect on cooperation.

14

Table 1Enterprise Cooperation (pairs)

1) Capital Cooperation

Foreign
Firms

NissanSuzuki
Mitsubishi
Fuso

Mazda
SubaruIsuzu
UD Trucks

Renault

Daimler

General Motors

PSA

BMW

Ford

Fiat

Sollers

Tesla Motors

6

Cooperation forms
Capital Cooperation
Production Commitment
Completed Vehicle OEM
Equipment OEM
Joint Development (to cope withenvironmental regulation)
Joint Development (towards others)

4) Equipment OEM
5) Joint Development (Env.)

86) Joint Development (Others)

6
4

1967

1972

1977

1982

1987 1992 1997
Time (year)

2002

2007

2012

Figure 3 The changes of Japanese
automotive enterprise cooperation trend(Source: Compiled by the author based on empirical data)

tal problems had been heightened because of Kyoto
Protocol held in 1997. In these situation, diesel engine(esp. made by Mitsubishi and Isuzu) gained attention as
eco-friendly engine, because of high fuel economy andefficient output. From the view of cost reduction,equipment OEM has been more popular. These are main
reasons of 4)’s rapid spike. On the other hand, since 1998,
5) has progressive changes because Japanese enterprises
have cooperated with foreign ones in technologicaldevelopment caused by sharing mutual interests. Both 4)
and 5) are extremely influenced by strengthened
regulations from 1997 to 2005, which reveal regulations
at those times had great impacts on the automotive
industry.
Nowadays, among 12 Japanese firms, 2 enterprises
have adopted 4) and 5) extremely actively: Toyota andNissan. These two firms expand their business indifferent background; Toyota has mainly regard capitalcooperation as core management, while Nissan has done
OEM relationship. However, in the aspect of resent
environmental technological development, the two firms
have similar enterprise cooperation trends.

Table 2 Categorized forms of cooperation
No. ofCategory
1
2
3
4
5

10

0

Target firms
Japanese
Firms3) Completed Vehicle OEM

2

The list of analysis target firms

ToyotaHonda
Daihatsu
Hino2) Production Commitment

12

No. of
Pairs
17
8
27
17

5. Conclusion

11

This study reveals that environmental regulations
deeply linked to equipment OEMs and environmental
technological developments based on the empirical data,
which was compiled by the author. This study found that
Toyota and Nissan, which are the leading company in theJapanese automotive market, tend to have moreconnections with other automotive enterprises, andconfirmed that they play significant role to develop
environmental technologies.

9

4. Analysis and Results
Fig. 3 shows the changes of Japanese automotive
enterprises cooperation divided into above 6 forms.
There are following remarkable 3 points. First, since
1990s, 4) equipment OEMs are rapidly increasing,second, 5) environmental technological development canbe also flourish from the later 1990s. Last, many of 1)
capital cooperation have been adopted since 1970s,
however, this aspect may be easy to reflect from national
economy situation.
Considering increasingly tighten environmental regulations since 1990s, a hypothesis can be designed; 4) and5) are deeply related to the trend of regulations. This
period of Japanese history was in the collapse of the
bubble economy; in addition, our interest in environmen-

REFERENCES[1] Angel Martínez Sánchez et al. (2003), “Cooperation and the Ability to
Minimize the Time and Cost of New Product Development within the Spanish
Automotive Supplier Industry”, Journal of Product Innovation Management
Vol.20(1), pp.57–69[2] Porter, Michael E. (1991), “America’s Green Strategy,” Scientific American,
264, 16[3] S.C. Debnath(2015), “Environmental Regulations Become Restriction or a
Cause for Innovation – A Case Study of Toyota Prius and Nissan Leaf”, Social
and Behavioral Sciences 195, 2015, pp.324-333

54

The prototype of side-contact type elastic multi-beam using PDMS
Student Number: 12_13212, Name: Mai Ngoc Trung, Supervisor: Kunio Takahashi

1. Introduction
Gecko can move quickly on walls and ceilings [1].
They have a lot of fine hairs on their fingers
surface, which are called setae and spatula. The
hairs work like springs which can absorb surface
roughness and generate enough adhesion force [2].
Adhesion devices which mimic a fine hairstructure gecko were prototyped [3-5]. However,compliance with rough surface and easy
detachment of the existing devices are stillinsufficient.
A theory of adhesion between an elastic beam anda rigid body is proposed using linear beam theory[6]. In this study, based on this model, theadhesion device of multi-beam was prototyped andevaluated the performance.

Multi-beam

One beam

Fig.2 Dimensions of multi-beam

3. Fabrication procedure
In this study, fabrication method of the multibeam is pouring the PDMS mixture into the mold.
The multi-beam was produced as below (3 steps).
3.1 Making mold (Step1)

2. Theoretical study and design

The mold used in this study was designed asassembly-type mold. From unit molds, arrange ina row (Fig.4b), fix with pins and screws (Fig.4c).
The material of the mold is stainless (SUS304).

The relation between normalized force andnormalized displacement with different value ofparameter  is shown in Fig.1.

(a)Unit molds(b)

Fig.1 The relation between force and displacement

Fig.3 Assembly-type mold

The parameter , related to dimensions (L, H),
mounting angle ( in Fig2) of the beam and workof adhesion , is defined as
6∆𝛾𝐿2 1𝜏=√
𝐸𝐻3 tan 𝜃(c)

3.2 Making multi-beam (Step2)
Process of pouring PDMS into the mold is shownin Fig.4.

(1), where E, H, L is Young's modulus, thickness,length of the beam.is mounting angle.
In order to the gripping force can be generated,the value of  must satisfy(2)
𝜏 > 0.5 [7].
Based on this condition, the dimensions, materialof the beam were determined. The dimensions of
the multi-beam are shown in Fig.2. The materialof the multi-beam is PDMS (Polydimethylsiloxane). The number of beams is 24 (4 rows with
6 beams in one row) and distance between rows
and beams is respectively 9mm, 2mm.

(1) Measure(2)Mix main(3) Agitate PDMS

(4) Flow PDMS
into the mold(5) Draw
vacuum(6)Cure PDMS
(12h,60℃)

Fig.4 Process of pouring PDMS into the mold1

55

be better.
Effect2: Because of increase of thickness of thebeams and accumulation PDMS at the base of thebeam, the stiffness of the beam is larger.
The maximum gripping force of multi-beam isshown in Fig.9. As shown in Fig.9a, the adhension
force of multi-beam coated by diluted is steadyincrease when the number of coating is from012 times. The reasion of this result is
considered that because of improvement of thebeam surface (effect1).
However, the adhension force decreases from 2 to
4 times of coating. It is considered that because of
the increase of the stiffness of the beam, as shownin Fig.10 (effect 2). The highest adhension force iswhen the number of coating is 2 times (34mN).
As shown in Fig.9b, the adhension force of multibeam coated by PDMS are almost same, about
80mN. The adhension force was larger than when
coating by diluted PDMS.

3.3 Surface coating (Step3)
In order to absorb the roughness of the beam
surface, the multi-beam is coated with differentways.

(1) Put into
coating agent(2)Rotate inspin coat(3)Cure PDMS
(1h,45℃)

Fig.5 Process of coating

Fig6. The different ways of coating

4. Experiment and discussion
4.1 Experiment
The schematic illustration of experimental
apparatus is shown in Fig.7.
a)Coating by diluted
PDMSb)Coating by PDMS

Fig.9 Adhesion force with different ways of coating

Fig.7 The experimental system.

For performance evaluation of the multi-beam,
force against the displacement when the beam isin contact with the rigid body was measured. The
result of the experiment is shown in Fig.8.

Fig.10 Stiffness of multi-beams coating by diluted
PDMS(n is number of coating time )5. Conclusionsa)Coating by diluted PDMS
by toluene with different
number of coating time(n=04)

By using the method of flowing the resin into theassembly-type mold, multi-beam was prototyped.
Different ways of coating surface beam wasconsidered. The adhesion force was compared andthe result shows that coating by PDMS is more
effective than diluted PDMS by toluene.

b)Coating by PDMS one timewith different rotation time
(t=20,300sec)

References[1] Autumn K, et al, Nature 405, 681-685, 2000.
[2]Takahashi K, et al, J. Adhesion& Adhesive 26, 639-643, 2006
[3] Giem A., et al, Nature Materials, 2, 461 – 463, 2003
[4] Sangbae Kim, et al, IEEE Transactions on Robotics, Vol 24
no1, 65-74, 2008.
[5] Hoon Eui Jeonga, et al, PNAS vol.106 no.14, 5639-5644, 2009[6] Sekiguchi Y, et al, J Adhesion Science and Technology, Vol
26, 2615-2626, 2012.

Fig.8 Experimental result of the measured force

4.2 Discussion
By the coating, there are 2 effects.
Effect1: Roughness of the surface beam can beabsorbed effectively, this makes contact condition

56