ISSN 1880-8468
Technical Report ofInternational Development Engineering࿖㓙㐿⊒Ꮏቇႎ๔TRIDE-2009- 01

February 13, 2009

Abstracts of Master Theses
Presented in February 2009

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

Preface

Master theses of Department of International Development Engineering, Tokyo Institute ofTechnology were presented successfully on August 1, 2008 and February 13, 2009. This
technical report consists of the abstracts of those theses.

Technical Report of International Development Engineering
TRIDE-2009-01
Table of Contents

Practical detection issues of spectrum sensing for cognitive radio systems! Sabita Maharjan KHADKA

1

Semi machine translation system based on collective intelligence!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Takuya ISHIBASHI

5

Shigeo YAMADA

9Study of antenna radiation efficiency by computer simulation!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Determination of parameters for compacted soil and its application to stability analysis!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Shinichi WATANABE

13

The application of macro-element method to analysis for behavior of soft ground
improved by vertical drains!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Aki ARAI

17

Effect of initial water curing period on chloride permeability of hardened blast
furnace cement
Shohei KIMURA!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

21

Development of new approach to prepare CoMo/Al2O3 catalyst for deephydrodesulphurization!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Tatsuya KUSAMA

25

Modeling of sand transportation using long-term observed datasets in the semi-arid
shrub desert!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Yumi KONDO

29

Permeation of coal tar absorption oil through ionic liquid supported liquid membrane!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Yoshiyuki SHIMADA

33

PIV measurements of atmospheric turbulence within and above an outdoor urban
scale model!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Hiroshi TAKIMOTO

37

Mechanism of ammonia nitrogen uptake by sterile Ulva sp. and its application towater quality control for intensive shrimp culture pond in developing country!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

i

Shin TAJIRI

41

Method of probability density estimation for mahalanobis metric in vector space! Toshinori NAKAMOTO

45

Makoto NAKAYOSHI

49

Lagrangian human meteorology!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Influence of mixing -C2S on Cl- penetration in concrete cured using autoclave
Masayo HORIOKA!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

53

Liquid-liquid extraction rate of coal tar absorption oil in a continuous countercurrent
spray column
Toshiya MASUDA

57

Jo MATSUDA

61

Ayako MARUYAMA

65!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Extraction of text area using scale invariant feature transform!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Correlation analysis of coherent turbulence over reduced urban model!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

System to make teaching materials based on collective intelligence!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Mandana Amir KHOSRAVI

69

The property of dislocation motion tracks which formed in deformation of aluminumand influence on the dislocation
Chao HU!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

73

LES study on hierarchical turbulence organized structure above urban canopy!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Jin ZHANG

77

Impact of angular power spectrum (APS) on the achievable diversity gain and MIMO
capacity in a mobile terminal!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Elnaz Foroughi SHAFIEI81

The applicability of one-dimensional & two-dimensional soil/water coupled analysis insettlement prediction of embankment!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Longtao YOU

85

Experimental study on adhesion behavior between rough surfaces of solid bodies!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Lei LEI

89

He LI

93

Phenols-polluted water treatment using enzyme and recovery of free enzyme!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

ii

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Practical Detection Issues of Spectrum Sensing for Cognitive Radio
Systems
Student Number: 06M51349

1

Name: Sabita Maharjan Khadka Supervisor: Jun-ichi TAKADA

Introduction

performance has been investigated with and without
considering the effect of quantization in section 3.
The effect of noise uncertainty in the detector performance has been explored in section 4. Finally,
section 5 concludes the paper.

The radio frequency spectrum is a precious natural
resource. With the increasing bandwidth requirements of the current and emerging wireless services,
the effective and efficient management of spectrum
has been realized as a serious issue. However many
current systems do not seem to utilize the allocatedspectrum fully and efficiently. So, dynamic accessand utilization of spectrum is necessary. Cognitive
radio has been proposed as the means to promote
efficient use of spectrum by exploring the existenceof spectrum holes. The strategy is that the cognitive
radio system should opportunistically use a channel
which is allocated to a primary user only when thechannel is identified as vacant by spectrum sensing.
This approach has the advantage of minimal coordination with primary systems. The opportunistic
approach is also fair in the sense that the responsibility is on the secondary system to sense the signal
from the primary system if it wants to use the spectrum. The key challenge of spectrum sensing is thedetection of weak signals in presence of noise andinterference with a very small probability of misdetection.
The first application of spectrum sensing was studied by IEEE 802.22 Standard Working Group. The
IEEE 802.22 WG proposed to standardize a fixedwireless access system based on cognitive radio technology to enable spectrum access and sharing by
the secondary system. This standard is called IEEE
802.22 Wireless Regional Area Network (WRAN).
The IEEE 802.22 WRAN aims to provide the wireless broadband access to rural areas as well as to
sub-urban areas where the spectrum utilization rate
is quite low.
Energy detector is the simplest detector proposedfor cognitive radio so far. Even though the numberof literatures are increasing on the analysis of various detectors for cognitive radio, there has been relatively less work in the analysis of practical aspectsof the system. The effect of crucial signal processing blocks such as analog to digital converter andcrucial elements of system modeling such as noise
uncertainty etc. have not yet been explored much.
Therefore, there is a crucial need of detailed analysis
of signal processing for energy detector as a cognitive
radio receiver.
The rest of the paper is organized as following.
Firstly an economic energy detector prototype using off-the-shelf instruments has been proposed forcognitive radio system in section 2. The detection

2

Spectrum Sensing Technique

2.1

Neyman-Pearson Detection

Let us assume that a known deterministic signal s[n]is corrupted by additive white Gaussian noise (re2ceiver noise) w[n] with zero mean and variance σw[2].
Then, the received signal x[n] will have either of thefollowing two forms:
H0 : x[n] = w[n]signal is absent,

H1 : x[n] = h[n]s[n] + w[n](1)signal is present, (2)where n = 1, 2, ...., N is the discrete time index,
N is the number of samples considered and h[n] is
the linear time varying characteristic of the propagation channel. Assuming that the distribution of signal samples s[n] is a Gaussian random process withzero mean and variance σs2 , the decision statistic of
Neyman-Pearson (NP) approach is to determine between the hypotheses H0 and H1 based on the observations of X = [x[1]x[2]...x[N ]]T . The decision
statistic of NP detecctor is given by1
T = ℜ[

NX

x[n]s∗ [n]]

(3)

n=1

If the signal is absent, the decision statistic follows a central chi-square distribution with N degrees
of freedom. If the signal is present, it follows a noncentral chi-square distribution. Under either hypothesis, as long as N is large enough, since x[n] is Gaussian and since T is a linear combination of Gaussian
random variables, T is also Gaussian. So, based on
the central limit theorem, the distribution of T canbe approximated as Gaussian i.e.

H0 : T ∼ N (µ0 , σ02 )(4)
H1 : T ∼ N (µ1 , σ12 )where the received signal x[n] can be both real (passband) or complex valued (baseband) with the same
power.

1 in this case the considered detector is the matched filter
for which the incoming signal structure is known beforehand.

1Technical Report of International Development Engineering

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TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Energy Detector

signals. If the RF signal be directly fed to the ADC,
the sampling frequency is supposed to be very high.
So, the mixer in spectrum analyzer is used to downconvert the RF signal. The output of spectrum analyzer is the intermediate frequency (IF) signal. Once
the RF signal is converted to IF signal, all the signal processing can be done in IF range. The signal
is then fed to the analog to digital converter (ADC)
which performs sampling and quantization of the IF
signal in order to use the data for analysis in thedata acquisition system. In this prototype, PC isthe data acquisition system in which the energy ofthe quantized samples is computed, the threshold isdetermined and the hypotheses are compared to determine the presence/absence of the primary signal.

Energy detection is a signal detection mechanism
based on NP approach [2] [3]. The NP detector computes the energy of the received signal and comparesit to the threshold in order to determine whether or
not the signal from the primary system is present.
The decision value of the energy detector is given by,
T =

N
X

|x[n]|2 .

(5)

n=1

The probability of false alarm (PFA ) and the probability of detection (PD ) of energy detector are givenby2
γ − N σw),
PFA = Q( p
4
N σw

(6)

3

Effect of Quantization on Detection Performancefor complex valued signal. The energy detector
can meet any desired PD and PFA simultaneously if
the number of samples N is not limited provided thatw[n], s[n] as well as h[n] are modelled as stationary
and ergodic random processes. In reality however,these processes are neither stationary nor ergodic.
So, for a practical system, the robustness of the system towards various issues and errors should be carefully investigated in order to ensure that the detector
performance is acceptable.

3.1

Background2.3

Figure 2 shows the low pass model of cognitive radio
receiver. All blocks of the receiver except ADCs are
assumed to be linear [4] and the sampling time isassumed to have no jitter. So, the signal at the filter
output is given by2
γ − N (σw+ σs2 )).
PD = Q( p2 + σ 2 )2
N (σw
s

(7)

Most of the literatures about the analysis of detection performance of cognitive radio receiver consider
the detection performance based on actual samples.
In reality however, the performance depends on thequantized samples, not on the actual samples. So, it
is our motivation to explore the effect of quantizationon the performance of energy detector.

3.2

Energy Detector Prototype

Though the number of literatures regarding the performance evaluation of detectors for cognitive radio
system is increasing, the crucial need of the experimental study still persists to explore the feasibility
and the practical performance limits of the detectors
under real noise and interference conditions in wireless channels. So, it is our motivation to propose a
detector prototype for cognitive radio receiver feasible to work in practical environment. Our proposed
detector model is shown in Figure 1. It comprisesof off-the-shelf instruments which make it versatile,
economic as well as frequency agile.

System Modelx(t) = s(t) + n(t)(8)

where s(t) and n(t) are the signal and noise component respectively.

Figure 2: Model of the ReceiverThough the amplifier gain α can be automaticallycontrolled in practical systems, in this study, it isassumed to be fixed to analyze its effect [4]. Let us
assume that the input to the ADC is normalized andthat the full scale range (FSR) of the ADC is ±1. If
the amplitude of the input to the ADC is within the
FSR, the error is given by

Figure 1: Block diagram of the prototype to implement energy detector
The low noise amplifier is used to decrease theoverall noise figure of the system. The attenuator isused in order to prevent overloading in case of strong2

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

1

Table 1: Parameters of the ISDB-T signal used for
simulation

0.8

0.6

Values252 µsTu= 63 µs
4315 µs20
6.3 ms1405
5.575 MHz
16.254 MHz

Pd

Parameters
Effective symbol length (Tu )Guard interval (Tg )Symbol duration (Ts )Number of symbols
Total duration
Number of carriers
Total bandwidth
Sampling frequency

0.4

0.2

0
−40

∆q
,
(9)
2
where ∆q is the stepsize of quantization given by

0−10

PSD [dB]

−20
−30
−40
−50
−60
−70
−2

0

2

Frequency [MHz]

4

6

0

10

Noise Uncertainty

4.1

Background

Evaluation

Let s(t) denote a band-limited primary signal with a
total bandwidth of B. Let h be the fading process,and let w(t) be the additive noise process. Let us assume that the reeived signal (with additive noise) is
sampled ideally at Nyquist rate. A stationary white
Gaussian assumption for background noise is only anapproximation. So, Let us model the noise process
w[n] to have any distribution W from a set of possible distributions W. This set is called the noise
uncertainty set. Fading is modeled in similar manner. The fading process H ∈ Hf is considered apossibly random linear time-varying filter response.
Similarly, let us denote the set of distributions for S
as Sp . Although the actual noise variance might varyover distributions in the set W, let us assume that
there is a single nominal noise variance σn2 associatedwith the noise uncertainty set W. By convention, we
consider all the S ∈ Sp to share the same averagevariance σs2 .
Because the energy detector evaluates the detection performance based on energy of the incoming
signal, the distributional uncertainty of noise can be2summarized in a single interval σw∈ [(σn2 −ρ)dB, (σn2 +ρ)dB] where ρ > 0 dB is a parameter that quantifies
the size of the noise uncertainty.
Now including the effect of noise uncertainty as
described in [6], PFA and PD are given by

The ISDB-T signal was generated following the description given in [5] to analyze the effect of quantization assuming Mode 1. The spectrum of the generated ISDB-T signal is shown in Figure 3. The parameters of the generated signal are given in Table 1.

−4

−10

4

4.2
Simulation Results

−6

−20

Amplifier gain [dB]

Most of the literatures about cognitive radio detectors assume that the background noise is additive
white Gaussian and that the variance is exactly known,
which is most of the time not the case in real environment. So, it is our motivaion to explore the effectof noise uncertainty in the detection performance ofenergy detector.

2
,
(10)
∆q = M
2 −1
where M is the number of bits used for quantization. If the amplifier gain is too large such that the
input does no more fit within the FSR, clipping occurs hence increasing the error beyond what is givenby (9).

−80
−8

−30

Figure 4: Effect of Quantization and Clipping Errors(N = 1024, SN R = −9 dB, PFA = 1%)|eq [k]| <

3.3

M=4
M=8
M=12

8

Figure 3: Spectrum of the generated ISDB-T signal
Figure 4 shows the effect of quantization noiseand clipping. The performance is optimum withincertain range of α. For lower values of α, the probability of detection can be drastically improved by increasing the number of bits of ADC because in thiscase quantization error is dominant. On the other
hand, for higher values of α, increasing the numberof bits does not help because the clipping noise becomes dominant in this case. Therefore, the trade-off
should be made so that the detection performance isleast affected.

γ − N ρσn2
PF A = Q( p)N ρ2 σn43(11)Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

5γ − N ( ρ1 σn2 + σs2 ))PD = Q( qN ( ρ1 σn2 + σs2 )2(12)

In this paper, an energy detector prototype using
off-the-shelf instruments was proposed for cognitive
radio system. As ADC is one of the most importantsignal processing units in cognitive radio receiver, theperformance of energy detector was explored counsidering the effect of quantization and clipping. The
effect of quantization was clearly pronounced in thedetection performance of energy detector. Although
the effect of quantization is unavoidable in any practical detector, there are ways to tackle its effect byproper modelling and design of the instruments. For
example, if the dynamic range required for the detector is too high, using sufficient number of bits
for quantization will increase the resolution of thesystem and hence minimize the quantization error.
Though increasing the number of bits does not help
much in reducing the clipping error, it might not be
severe as long as the system can maintain fairly highdynamic range with sufficient number of bits. On
the other hand, if the expected signal level input tothe receiver has moderate dynamic range, using relatively less number of bits may be enough for fair
performance which is saving in terms of hardware
requirement.
As real noise is neither white nor its variance isexactly known in actual systems, the effect of noise
uncertainty was also investigated in the detection
performance of energy detector. The simulation results reflected that the detector becomes nonrobust
below certain values of SNR depending on the noise
uncertainty of the system.

for baseband signal where ρ is considered in linear
scale.

4.3

Simulation Results

For the simulation results that follow, the ISDB-T
signal as described in section 3 was used.
Figure 5 shows the performance of energy detector for different values of noise uncertainty ρ. As thevalue of ρ increases, the performance degrades. For
example, when the noise uncertainty is 1 dB, the detector does not work below an SNR of −8 dB. For
ρ = 5 dB, the detector does not work even for higher
values of SNR.
Figure 6 shows the variation of the probabilityof detection with sensing time for different valuesof the noise uncertainty ρ. From this figure, it canbe seen that the detection performance improves assensing time increases. However when the noise uncertainty is as big as 1 dB, the detector performanceis rendered by the uncertainty and hence it does notwork.
1ρ = 0 dB
ρ = 0.1 dB
ρ = 1 dB
ρ = 4 dB
ρ = 5 dB

0.8

Conclusion

Pd

0.6

0.4

0.2

References

0
−25

−20

−15

−10

−5

SNR [dB][1] C. Cordeiro, K. Birru and S. Shanker, “IEEE 802.22:
The first worldwide wireless standard based on cognitive radios ,” In proc. of DySPAN’05, November
2005.

0

Figure 5: Detection Performance for different valuesof ρ (N = 1024, PFA = 1%,)

[2] S. Kay, “Statistical decision theory I (Ch. 3)” and“Deterministic signals (Ch. 4),” in Fundamentalsof Statistical Signal Processing, Detection Theory,
pp.60-140, Prentice Hall, 1998.

1[3] H. Tang, “Some Physical Layer Issues of Wideband Cognitive Radio Systems,” 2005 First IEEE
International Sympo- sium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2005),
pp. 151-159, Nov. 2005.

0.8

P

d

0.6
0.4

ρ = 0dBρ = 0.1dB
ρ =1dB

0.2
0
0

500

N

1000

[4] M. Sawada, H. Okada, T. Yamazato and M.
Katayama “Influence of ADC nonlinearity on theperformance of an OFDM receiver,” IEICE Trans.
Commun., Vol.E89-B, No.12, Dec. 2006.

1500[5] “Transmission System for Digital Terrestrial Television Broadcasting,” ARIB Standard, ARIB STDB31 Version 1.5, Association of Radio Industries andBusinesses, 2003.

Figure 6: Detection Performance for different valuesof ρ (SN R = −9 dB, PFA = 1%)[6] R. Tandra and A. Sahai, “SNR Walls for Signal Detection,” IEEE Journal of Selected Topics in Signal
Processing, Vol. 2, No. 1, Feb. 2008.

4

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

SEMI MACHINE TRANSLATION SYSTEMBASED ON COLLECTIVE INTELLIGENCE
Student Number:06M18033

Name:Takuya Ishibashi

Supervisor: Yukihiko Yamasita

集合知に基づく 高精度半機械翻訳シ ス テ ム
石橋 卓也
イ ン タ ーネッ ト におけ る Wikipedia に 代表さ れる Wiki シ ス テ ム は， 世界中の数多く の人々
が 参加し ， 学術・ 生活など の広範囲で有益な 情報を 持続的に提供し て いる 。 し かし ， 現状のWiki シ ス テ ムには， 言語ご と に文書フ ァ イ ルを 用意する 必要があ る と いう 言語の壁が 存在す
る 。 こ の壁を 越え ， 一つの文書フ ァ イ ルから 世界中の人々が 情報を 取得でき る よ う にする ためには， 機械翻訳が 必要不可欠と な る が ， 既存の機械翻訳には， 構文解析や意味選択における 誤認識が 生じ る と いう 問題が 残さ れて いる 。
本研究では， 文法や意味など の情報を 付加し た XML 文書 (Adam, Auxiliary Description to Attach
Meaning) を 提案する 。 さ ら に ， 多数の人々が Adam 文書の記述を 可能にする 支援ツ ールを 開
発し ， 持続可能な 情報提供シ ス テ ム の構築を 目指す。

1

INTRODUCTION

and participate in that contents. Now Wiki system andBlog provide various and useful information using theCollective Intelligence.

A lot of people in the world participate in the Wikisystem project. Wiki system, such as Wikipedia, provides sustainedly useful information in various fields
such as study and life. However, the present Wikisystem has a problem that it is necessary to prepare
at least one document for each language. For solving this problem and getting information in many languages from one document, machine translation isnecessary. But, the present machine translation is notfree from errors in structural analysis and mean analysis. For the reason, even if it can be used as a support
tool, the system is not practiced.
In this research, I propose an XML document called
ADAM (Auxiliary Description to Attach Meaning)which has the information of grammar and meaning.
I developed a supporting tool to describe an ADAM
document aiming sustainable production of ADAM
document based on collective intelligence.

2

BACKGROUNDS

2.1

Collective Intelligence2.1.1 Wiki
Wiki [2] is a kind of system rewriting a hyper text
document on a web server by using web browser. The
software which is used by this system and all documents made by using this system are called Wiki. The
followings are the features of Wiki.
1. It is able to change and save documents for anyone
and at anytime and anywhere on Internet.
2. The tool needed to change a document is only a
web browser.
3. The rule to make-up a document at Wiki is easierthan HTML.
4. It is easy to link between documents in same Wikisystem. Therefore, we can make a complex set of
documents easily.
5. Various documents can be seen and changed without registering, user account or an advance permission if a person can access the Wiki server.
Wikipedia is the most famous Wiki system. Document in 229 languages exist in Wikipedia. English
project is the biggest project and has about 1.4 billion word. Japanese project has 260 thousand word.
But, it has problem that the substances of content andthe quantities of information are different among languages. One of solutions to overcome the problem ismachine translation. It may improve the quality andquantity of Wikipedia as Collective Intelligence.

Collective Intelligence is often used as the word
stands for sets of intelligence by many people. But, itmeans essentially the notion of the wisdom of crowds.
[1]
By the birth of Internet, it is easy for a lot of people
to deliver contents using the Collective Intelligence5

Technical Report of International Development Engineering

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TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Machine Translationand has additional information of grammar and meaning for machine translation. There are many mistakes
in machine translation. Then, it is very difficult thata person correct the translation. Therefore, it is efficient for a person to give the information of grammar
to translation machine.

Machine translation is to translate a text in a language into one in another language automatically. Asa practical service, there are the translation software
for computer and translation service on Internet. But
it is very difficult to translate a sentence precisely, because natural language is used by missing words andhas many synonym.
2.2.1

3.1 ADAM Document
Additional information of ADAM document consistsof a sentence, grammar and meaning. Error on machine translation is due to the analysis process of asentence and its meaning. For the reason, the ADAM
document provides the information in the part of analysis process. Detail of each information is mentioned
in followings.

Problem of Machine Translation

A computer is not able to understand the meaning ofwords different from a human. For this reason, a computer translates a sentence only by processing information of construction of a sentence. Then, following
problems occur in machine translation. Figure 1 is an
example of mistake in machine translation.

• Information of construction of a sentence
It describes the information in the analysis process of structure. This information is based on
English grammar. The construction of a sentence
is composed of clause and phrase. The information is composed of subjective phrase (clause),verb phrase, adjective phrase (clause) and adverb
phrase (clause). The construction of clause iscomposed of clause and phrase. The constructionof phrase is composed of phrase only.

• In the analysis process of construction of a sentence– Error in the analysis process of structure
Relationship between a subjective and a predicate is wrong.
– Error in the analysis process of meaning
Analysis of the meaning of each word is wrong.
– Error in the analysis process of context
Analysis of context is wrong or context is neglected.

• Information of grammar
It describe the grammar information of each word.
For example, a part of speech, tense, singular orplural and so on.

• In the transformation and generation process– Error in the generation process
The order of words in translation is wrong.
– Error in the transformation process
Expression of a word in translation is not appropriate.

• Information of meaning
It describes the meaning of each word.
ADAM document is a type of XML document. Figure 2 is an example of ADAM document. The example sentence is ’My name is Tom .’ The meaning ofa tag is shown in APPENDIX Table 1. The ADAM
Document starts from the <ADAM> tag. A sentence
is surrounded by the <sentence> tag. For information of tag, construction of a sentence, information ofgrammar, information of meaning are described in order. In the last section, the original form of the wordis written.

3.2 Editing Tool for ADAM Document
Figure 1: Example of mistake3

I develop a support tool for editing the ADAM document. I explain the functions of the tool. Figure
3 illustrates the picture of top window. Figure 4 illustrates the window to attach the information tag ofgrammar of words.

Semi Machine Translation Systemwith Adam Document

Function of File Menu

I propose the ADAM (Auxiliary Description to Attach Meaning) document that is an XML document

1. Input the original sentence

6Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

1: <?xml version="1.0"
encoding="UTF-8"?>
2: <!DOCTYPE ADAM SYSTEM "adam.dtd">word is selected, it is attached the informationof a part of speech by pushing the button.
Construction of Sentence Window

3: <ADAM>
4: <sentence>
<u>
5:
<snp>
6:
<det>
7:
<pos>
8:
<mean id="0">My</mean>
9:</pos>
10:</det>
11:
<n>
12:
<sg>
13:
<mean id="0">name</mean>
14:
</sg>
15:
</n>
16:
</snp>
17:
<vp>
18:
<v>
19:
<pres>
20:<be>21:<mean id="0">be</mean>
22:
</be>
23:
</pres>
24:
</v>
25:
</vp>
26:
<onp>
27:
<n>
28:
<sg>
29:
<prop>
30:<mean id="0">Tom</mean>
31:</prop>
32:
</sg>
33:
</n>
34:
</onp>
35:<sign>.</sign>
36:
</u>
37:
38: </sentence>
39: </ADAM>

1. Select a phrase or clause
It allocates the buttons of a subjective phrase(clause), a verb phrase, a adjective phrase(clause) and a adverb phrase (clause). If the
button of a phrase or a clause is pushed, it
switches to the state to select the word.
2. Select the word
If a button of a word is pushed, it is attached theinformation.
Amend the Word Window
1. Select the word
It allocates the buttons of words. If one of thesebuttons is pushed, the corresponding word is selected.
2. Amend
It amends the selected word to the original formby keyboard.
Information of Meaning Window
1. Select the word
It allocates the buttons of words. If one of thesebutton is pushed, the corresponding word is selected.
2. Select the meaning
It allocates the meaning from a multi-language
dictionary. If a button of meaning is pushed, theinformation is attached.
I pay the attention to the ability of speed and operation. For being more simple and fast, it can be used
only by a mouse.

Figure 2: Example of Adam Document• Input by keyboard• Read from text file
2. Read or save the ADAM document
3. Output the ADAM document

Figure 3: editing tool

Grammar of Word Window
1. Select the word
It allocates the buttons of words. If one of thesebutton is pushed, the corresponding word is selected.
2. Select the part of speech
It allocates the buttons of parts of speech. If a

Figure 4: Window of attaching grammar information

7

Technical Report of International Development Engineering

3.3

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Translation Machine System

Table 1: Tag list

index
A

The translation machine needs to analyze not natural language but an ADAM document. The following
functions are necessary.
• Read the ADAM document• Interpret the ADAM document
Since the ADAM document is the XML document, only the XML parser is necessary.
• Translate to another language
Translation rules to another language according to
information of an ADAM document is necessary.
It translates to another language by the rules.

B
C
D• Dictionary
One word has various meanings for many languages in this dictionary in order to translate tovarious languages.

4

F
G
I

CONCLUSIONSIn this paper, I proposed a semi machine translation
system based on collective intelligence in order toobtain more precise translation for the case such as
Wikipedia.
As a future work, I need to improve the method toattach tags for decreasing human error and add thefunction to check the ADAM document easily. Besides, I must develop a translation machine.

NOP

REFERENCES[1] Surowiecki, J.:THE WISDOM OF CROWDS, Anchor Books, England, 2005
[2] Eto, K.:Origin and Evolution of Wiki, IPSJ SIG
technical reports, vol.2007, No.41 pp.11-18. (inJapanese)R
S

APPENDIX

T
U
V

8

name
ac
adj
adv
advc
advp
ap
art
aux
be
comd
conj
dem
det
fut
futpt
ger
imp
inf
int
intr
ints
n
neg
onc
onp
p
per
pl
pos
posd
pp
ppt
prep
pres
presp
prespt
pro
pron
prop
rel
sg
sign
snc
snp
sub
supd
tran
u
v
vp

mean
adjective clause
adjective
adverbadverb clauseadverb phrase
adjective phrase
articleauxiliary
Be verb
comparative degree
conjunction
demonstrative
determiner
futurefuture perfect tense
gerundimperative
infinitive
interrogative
intransitive
interrogative sentence
noun
negative
objective noun clauseobjective noun phrase
past
personpluralpossessive
positive degree
past participle
past perfect tense
preposition
present
present participle
present perfect tense
proverb
pronounproperrelativesingularsign of end
subjective noun clausesubjective noun phrase
subjunctive
superlative degreetransitive
usual
verb
verb phrase

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Study of Antenna Radiation Efficiency by Computer Simulation
Student Number: 06M51326

Name: Shigeo YAMADA Supervisor: Jun-ichi TAKADA

計算機によ る ア ン テナ効率測定法の検討
山田 重雄
日本語要約 ア ン テナ放射効率を 簡易的に測定する Wheeler 法はよ く 使用さ れている も のの , 理論的な裏づけが十分でなく , 適用範囲が不明確であ る . 本論文では , 共振周波数付近の Wheeler 法によ る 放射効率の値が実際の放射効率
よ り も 小さ く なる 現象に関し て電磁界シミ ュ レ ータ を 使用し て検討を 行っ た .

1Introduction

Unfortunately, Wheeler method does not always provide the good estimate of the radiation efficiency. This
There are a lot of parameters to represent the charac- study investigate the mechanism of error in the Wheeler
teristics of the antenna. The radiation efficiency is one cap method to clarify the applicability.
of them. The radiation efficiency is the ratio of radiatedpower from the antenna to the input power to the anWheeler Cap Method and Probtenna. It is a most important parameter for the mobile 2
terminal antenna as the size of the antenna is limitedlem Statement
which leads the degradation of the efficiency. The radiation efficiency is defined asη=Pradiation
Paccepted(1)

However, it is known that the measurement of the radiation efficiency is rather difficult. The input power
Paccepted can be easily evaluated by measuring the reflection coefficient, but the radiated power Pradiated shouldbe evaluated by measuring the electromagnetic field radiated to all the directions. This straightforward approach is called the radiated power integration method.
Although the method is most popular, an anechoic chamber and a spherical antenna positioner are needed forthe measurement, and it is very time consuming in meaFigure 1: Equivalent circuit for Wheeler methodsuring the whole solid angles. Alternatively, a simpler
method known as the Wheeler method is often used.
In the Wheeler method, the radiation efficiency is esThe equivalent circuit proposed by Wheeler [1] is shown
timated by comparing the reflection coefficients of theinFig. 1. The power is represented as the resistance inantenna when it is set up in a free space and when it iscovered with a conductive cap. This method needs only the equivalent circuit. When the antenna is placed ina conductor cap and a network analyzer, but no ane- the free space, the loss and the radiation are represented
choic chamber nor spherical antenna positioner. There- as two series resistors Rloss and Rradiation .
On the other hand, only the radiation resistance isfore, this method is advantageous from the viewpoint ofcost and measurement time. However, Wheeler method short-circuited when the antenna is capped as the radiation power does not exist.
has the following limitations:
The radiation efficiency is calculated from these equiv• The antenna should be within the radian sphere, alent circuits as follows [2] [3]. Where Γcap and Γfree arei.e. the sphere of 1/2π wavelength in radius.
the reflection coefficients of the antenna with and without the cap. In this study ηw is called the Wheeler effi• The wall of the cap should be placed further than ciency, in comparison with thetrue radiation efficiency.
the radian length, i.e. 1/2π wavelength, from theantenna.
Rradiation
The mobile terminal antenna may be integrated into
(2)
ηw =
R
+ Rlossradiation
the handset. In the case, the measurement condition is
1 − |Γcap |2
relaxed as:= 1−(3)
1 − |Γfree |2• The measured antenna size is in the order of half
wavelength.

9Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

It is known that the Wheeler efficiency does not always
coincide with the radiation efficiency.
When the cap is resonant, strong electromagnetic fieldis generated inside the cap and the radiated power is
not reflected by the cap to the feed.
When the antenna is near resonant, the dip of the efficiency is often observed, although the reason is notclear. As the antenna is usually used around the resonant frequency, this is a serious problem.

3

Simulation

3.1

Simulation Condition

Figure 3: Reflection coefficient of the antenna

Figure 2: Patch antenna structure
A microstrip antenna is chosen for the study. The current distribution and the reflection coefficient are calculated by using the commercial electromagnetic simulator Ansoft HFSS [4], which utilizes the finite element
method as the solver of the Maxwell’s equation.
The structure of the microstrip antenna is shown in
Fig. 2. The antenna consists of two parallel conductor plates with different sizes. The top plate is sized
25 mm × 18 mm × 0.5 mm in (X,Y,Z) directions. The
bottom plate is sized 50 mm × 28 mm × 0.5 mm. The
plates are made of copper with the conductivity of 5.8×
107 S/m. The dielectric substrate of 1.6 mm thickness
in Z direction is placed between to conductors. The
substrate is made of Duroid, whose relative permittivity is 2.2 and the dielectric loss tangent is 0.0009. The
target system is IMT-Advanced． The antenna is fed by
the coaxial cable. The diameter of the inner conductor
is 1.78 mm, and the inner diameter of the outer conductor is 2.055 mm. The thickness of the outer conductor
is 1 mm. The characteristic impedance of the coaxial
cable is designed to be 50 Ω. The feed point of the top
conductor is offset at 8 mm along X direction from thecorner of the top conductor. The size of the analyticalspace truncated by the absorbing boundary condition issized 65 mm × 60 mm × 60 mm in (X,Y,Z) directions.
The cap is made of perfect conductor to distinguish theloss of the antenna from the loss of the cap. The cap issized 65 mm × 60 mm × 40 mm in (X,Y,Z) directions.

Figure 4: Radiation efficiency and Wheeler efficiency

efficiency and the Wheeler efficiency are in good agreement.
In the frequency range C, which is around the resonance frequency of the antenna, the Wheeler efficiency
does not represent the radiation efficiency.

3.3

Current Distribution

Fig. 5 - 8 show the surface current distribution of thebottom conductor of the patch antenna. The real partof the current distribution consists of the element that
contributes to the radiation. The imaginary part of thecurrent distribution contributes to storage of the reactive energy. The Conductor loss dissipated on the antenna is represented by the magnitude of current distribution.
3.2 Radiation Efficiency
Fig. 5 shows the current distribution in free space at
The simulation results are shown from Fig. 3 to Fig. 8. 3.60 GHz which is sampled within range B. The real part
The magnitude of the reflection coefficient calculation of the current has decreased more than the imaginaryis shown in Fig. 3. The antenna is resonance at 3.85 GHz. part because the radiation is suppressed. Fig. 6 shows
Fig. 4 compares the radiation efficiency and Wheeler the current distribution when covered with the cap. It
efficiency. The very deep dip A is due to the resonant is shown that the real part of the current has decreasedof the cap. In the frequency range B, the radiation obviously compared to the current distribution in free10

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Figure 5: Current distribution without cap @ 3.60GHz

Figure 7: Current distribution without cap @ 3.96GHz

Figure 6: Current distribution with cap @ 3.60GHz

Figure 8: Current distribution with cap @ 3.96GHz

Reflection coefficient Γfree without cap becomes,
space. It can be interpreted that the radiative component was suppressed by the cap according to Wheeler’s
Rloss Rrad
+Rrad − Rcir
expectation. On the other hand, imaginary part is not(5)Γfree = RRloss
loss Rradchanged. This shows that a reactive component is not
Rloss +Rrad + Rcir
seriously influenced.
Fig. 7 and 8 show the current distributions at 3.96 GHz, In a similar way, reflection coefficient Γcap with cap bewhich is sampled within the range C where the Wheeler comes,
efficiency exhibits large error due to the unkown reason.
Rloss − Rcir
(6)
Γcap =
Fig. 8 shows that the magnitude of the current has
Rloss + Rcir
decreased when the antenna is capped. However, The
similarity of the shape of current distribution is still pre- When these two expressions are transformed, the folserved. Therefor, the error is not due to the change of lowing relational expressions are obtained.
the current distribution, which violates the Wheeler’s¶µ1 − Γfree
1
1
assumption.
=
+
Rcir
(7)
Rloss
Rrad
1 + Γfree
1 − Γcap
Rcir
3.4 Impedance
=
(8)
Rloss
1 + Γcap
Equation 3 based on Wheeler’s assumption. It does notconsider the change in the current without adjustment Therefore, if this relational expression is substituted inof impedance. New equation that introduces this ele- equation 4, the radiation efficiency becomes,
ment is derived as follow.
Rloss + Rrad − Rloss
Rloss
It assume that equivalent circuit exist like Fig. 9
=
(9)
ηw =
Rloss + Rrad
Rloss + Rrad
In this case, E is an input voltage. A new equivalentRcir
circuit for computing the radiation efficiency mention
Rrad= 1 − RcirRloss Rcir (10)= 1−
below.
Rloss + Rrad
Rloss + Rrad
E
1
2
(
)
R
rad
R
loss
(1 − Γcap )(1 + Γfree )=(4)ηw = 1 E 22 Rrad 1 E 2
= 1−
(11)
R
+
R
(
(
)
R
+
)
R
rad
loss
loss
rad
(1
+ Γcap )(1 − Γfree )2 Rloss
2 Rrad=11

1−

1 − |Γcap |2 (1 + Γfree )2
1 − |Γfree |2 (1 + Γcap )2(12)

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Figure 9: New equivalent circuit

Figure 11: The model of problem of proposed expression

It is easy to compare the new formulation with the phase will flow in both losses and the radiation resistraditional wheeler efficiency using an existing reflection tance. The electric power charged in the reactance elcoefficient.
ement on the radiation loss side flows as shown in Fig.
Fig. 10 shows the comparison between proposed ex- 11 when the reactance element exists. This doesn’t bepression. ”Weff” shows traditional Wheeler efficiency as come a problem. However, if the anteenna is capped,
explained section 3.2. ”Weff2” shows traditional Wheeler the resonant circuit was composed on the reactance elefficiency with resized cap. The cap size is 60 mm × ement of the cap mutually and the reactance element
65 mm × 40 mm. Two result show that the radiation of the antenna. Then, even if a new expression is used,efficiency has depressed, the part where the error has a correct acoustic radiation efficiency can not be caloccurred. However, The other part is nearly correct. culated because the current flows by behavior different“New eff” and“New eff2” show the results of proposed from the expression thought above only due to the loss.
wheeler efficiency. “New eff” is better than “Weff” atthe part where the error has occurred. But in other part,
Conclusions“Weff” is better than “New eff”. “New eff2” shows con- 4
siderable result. This difference may be caused by the
influence of the reflection that due to the disagreement The Wheeler method was examined for the patch anof impedance. In other word, the change in the current tenna based on the simulation. The current distribution in the frequency, where the error of the radiation
is not considered in traditional expression.
efficiency has occurred without clear reason, was madevisible with the simulator. In addition, We proposed
the expression that was able to allow the change inimpedance. Moreover, it can be applied in a part of theband where the error has occurred in the calculation.

References[1] H. A. Wheeler, “The Radiansphere Around a Small
Antenna”, Proceedings of IRE, vol. 47, no 8,
pp.1325-1331, Aug. 1959.
[2] E. H. Newman, P. Bohley, and C. H. Walter,“Two Methods for the Measurement of Antenna
Efficiency”, IEEE Transactions on Antennas andPropagation, vol. 23, no. 4, pp.457-461, July. 1975.
Figure 10: Comparison of proposed expression and existing expression

3.5[3] K. Sakurai, K. Kikuchi, H. Arai, M. Ando and
N. Goto, “Measurements of Antenna Efficiency
Using Scaled Models by Wheeler Method,” 1987
Spring National Convention Record, IEICE, S8-3,
Mar. 1987.
[4] Ansoft HFSS,
http://www.ansoft.com/products/hf/hfss/

Problem of This Expression

The reactance element is not considered in this expression. Therefore, only a limited correction can be done.
The model is shown in Fig. 11.
When there is no reactance element, The current in

12

Technical Report of International Development Engineering  

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

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TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)'   !(/ 3D C1!

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31

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

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GJALm  -!8Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

THE APPLICATION OF MACRO-ELEMENT METHOD TO ANALYSIS FOR BEHAVIOR
OF SOFT GROUND IMPROVED BY VERTICAL DRAINS
Student Number: 07M18013 Name: Aki Arai Supervisor: Hideki OHTA and Thirapong PIPATPONGSA!"#$%&'()*+,-./0123456789:;<=$>&?@1AB
CD EF!"#$%&'()*+,GH6IJKLMNOPQRSTUV'WXYR9ZJ[JM\1]^RG
H_`OPabcdefgh45i9Hj6LkG'lJVZm\hM\1no_4pi9,qMrst(1986)L!"#$%&1uvwx_Xy$z{h|}6~h9:;<=$>&?@_J,Z
 hLM!"#$%&'()*+,GH_I6M:;<=$>&?@_ABJ,v
Xy45_VM@11_,Z,M}/012_]T6kGh91{_i9,qM ¡¢£6¤¥J,¦uvN§¨©ª«_VM¬­®$%¬¯&Y°±i9\Y6]T~²_,Zsamples of clay obtained from various sites in Japan. By
boring investigation, soil data were obtained for eachsample and shown in Table-1.
The test procedure is as follows: At first I saturate a
specimen and take back pressure (u=290kPa). Then, I
perform an isotropic consolidation and a constant volume
compression test. About 2 times pressure of the
pre-consolidated stress is applied during 24 hours. In theshearing process, the axis strain rate was set to be
0.05%/min and 0.005%/min. The details of the test
condition are shown in Table-2.

1. Introduction
Original Cam-Clay model1) and Modified Cam-Claymodel2) are widely used as a constitutive model of soils.
The undrained effective stress path obtained by a normal
shear tests are said to be good agreement with thesimulation by Modified Cam-Clay model rather than
Original Cam-Clay model. However, the shear raterequired by the normal test is about two orders than theshear rate measured at the real construction site. Therefore
I perform undrained triaxial compression tests at two
different constant shear axis strain rates are performed inorder to clarify which model is better used for analysis.
From the laboratory test results, the performance of eachconstitutive model represented the behavior of the true
ground will be able to be justified.
In addition, analysis is also extended to the ground
improvement by vertical drains (see Fig-1) under2-dimentional plain strain condition. Even thought thetreatment of 3 dimensions is needed, an application of themacro-element method suggested by Sekiguchi (1986) 3)
to overcome the problem is believed. And I thus
examined the validity of this method.

Table-1 Test samples
Sampling Position

Saitama

Urayasu

Urayasu

Urayasu

Depth (m)GL -11.50 ~ -12.33

GL -29.0 ~ -29.9

GL -22.0 ~ -22.7

GL -29.00 ~ -29.88
2.68

Specific gravity Gs

2.743

2.693

2.679

Natural water content wn (%)

43.8

61.9

64.3

80.4

Void ratio e

1.224

1.749

1.775

2.164

Liquid limit wL

45.4

74.2

92.3

112.4

Plastic limit wp

25.4

29.9

33.3

37.4

Plasticity index I p

20

44.3

59

75

Compression index Cc

0.45

0.68

0.93

1.14

Pre-consolidated stress Pc (kN/m2)

139

260

290

300

Table-2 Test cases

Vertical drain

No.

Sampling Position

Depth (m)Consolidation stress (kN/m2)

Axial strain rate (%/min)&

Saitama

GL -11.50 ~ -12.33

300

0.05

%

Urayasu

GL -29.0 ~ -29.9

550

0.05

$

Urayasu

GL -22.0 ~ -22.7

600

0.05

#

Urayasu

GL -29.00 ~ -29.88

600

0.05

"

Saitama

GL -11.50 ~ -12.33

300

0.005

!

Urayasu

GL -29.0 ~ -29.9

550

0.005

Urayasu

GL -22.0 ~ -22.7

600

0.005

3. The Results of Triaxial Tests
In the simulation, A specimen is modeled as one
element, and used the elasto-viscoplastic constitutive
model proposed by Sekiguchi and Ohta5).The input
parameters needed for the Sekiguchi and Ohta’s model
are summarized in Table.3. These are the parameters forthe elasto-plastic materials.

Fig-1 Ground improvement by vertical drains

2. The Outline of Triaxial Tests
The samples4) used in this study are the undisturbed

17

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Table-3 Material parametersvertical drain in a macro-element. The water discharge
from a macro-element is calculated as water discharge
from the perimeters of element and vertical drain. By
using this method, the effect of vertical drains can beconsidered appropriately even under 2-dimensional
condition.
In this study 2 construction sites are simulated by
employing this method.

Irreversibility ratio

M

Critical state parameter

D

Coefficient of dilatancy

!"
$
v0

Effective poisson ratio# v" 0Preconsolidation vertical pressure

K0

Coefficient of earth pressure at rest

# vi"

Effective overburden pressure

Ki

Coefficient of in-situ earth pressure at rest

Coefficient of secondary compression
Initial volumetric strain rate

Nomal element

First, plasticity index I , void ratio at preconsolidated
state e0 , compression index % and swelling index &that was already obtained by boring investigation are usedin the simulation. K and K assumed as 1.0, ! isalso assumed as 0.3. M is obtained from theexperimental result. The input parameters used for thesimulation are summarized in Table-4.

Macro-element
Vertical drain

p

'

i

z

0

z
y

z
y

x

y
x

V

x
V

Q

Q ! QVD

Fig-3 Basic concept of continuity condition equation
Table-4 Input parameters for simulation
Ip

e0

%

&

D

&

20

1.224

0.195

0.006380.0502

%

44.3

1.749

0.295

0.00885

0.0613

$

59

1.775

0.404

0.01645

#

75

2.164

0.495

"

20

1.224

0.195

!

44.3

1.749

59

1.775

No.

M

!'

$

v0

K0 # v' 0 K i # vi'
(kPa)
(kPa)

0.86171.508

0.3

0.0044

2E-05

1

300

1

300

0.89141.56

0.3

0.0054

2E-05

1

550

1

550

0.08310.85431.495

0.3

0.0073

2E-05

1

600

1

600

0.020830.08940.86571.515

0.3

0.0078

2E-05

1

600

1

600

0.006380.05020.89541.567

0.3

0.0044

2E-05

1

300

1

300

0.295

0.00885

0.06130.83311.458

0.3

0.0054

2E-05

1

550

1

550

0.404

0.016450.08310.85431.495

0.3

0.0073

2E-05

1

600

1

600

5. SiteThe first site of the analysis is the highway
embankment constructed on Ohsawago-site of Akita line
6)of Tohoku transversal highway. Fig-4 shows theanalyzed cross section of the embankment.
CL

Urayasu GL -29.0 ~ -29.9
600

500

fast

400
300
200
100

slow

MCC

CC

Deviatoric stress, q (kPa)

Saitama GL -11.50 ~ -12.33

500
400

Urayasu GL -22.0 ~ -22.7

Urayasu GL -29.00 ~ -29.88
600

300
200

CC

100
0
0 100 200 300 400 500 600
Effective mean stress, p' (kPa)Fig-4 Analyzed cross section

6. The Input Conditions in Analyses
From a consideration of the experimental results,
Sekiguchi and Ohta’s model was employed in the analysis.
Sekiguchi and Ohta’s model is expanded from theOriginal Cam-Clay model so that can express theaisotropic state.

6-1 The material parameters

600

400

area improved by sand drains

CC

Effective mean stress, p' (kPa)

fast
slow

organic clay
deposit100
00 100 200 300 400 500 600

MCC

surface crust

300
200

The list of the material parameters used for analysis ispresented in Table-5.
Table-5 Material parameters

500
400

MCC

fast

Depth

Type of soil[m]Thickness[m]

Embankment
Sand mat
Surface crust

300
200

berm

lime mixed soil
steel meshsand mat

MCC

fast

Effective mean stress, p' (kPa)500

main bodycompacted fill bodyslow

0
0 100 200 300 400 500 600

Deviatoric stress, q (kPa)

Deviatoric stress, q (kPa)

Deviatoric stress, q (kPa)

The results are shown in Fig-2. From Fig-2, the effective
stress path at fast strain rate adopted in normal laboratory
test becomes close to an undrained shear simulation of
Modified Cam-Clay model (MCC). And the effective
stress path of the shear rate that occurred in the real site isslow and closed to an undrained simulation of Original
Cam-Clay model (CC). From this results, when wechoose a constitutive model of FEM analysis, it is thoughtthat a choice may reproduce real ground behavior model
more precisely with Original Cam-Clay model (CC) thanwith Modified Cam-Clay (MCC).
600(Ohsawago, Akita)

CC

100

Peat

0
0 100 200 300 400 500 600
Clay

Fig-2 Comparison of effective stress path
Silty sand

4. Macro-Element Method
Sand

As shown in the Fig-3, it is supposed that there is one

18# v' 0
2

K0

M

Ki

'

0.70

1.850

1.00

0.330

!

!k

"

e0

D

k

0.210

0.210

0.900

1.36

0.04300

8.60E-03

2[kN/m ]
92.1

[m/day]2

11.5

E = 51.2E+03 [kN/m ]

0.0

0.7

0.7

2.0

0.330

1.0

0.3

4.1

E = 7.5E+03 [kN/m ]
21.0
0.34
1.693

1.00

0.7

0.12

0.254

2.127

2.127

0.854

9.22

0.10494

3.32E-04

1.0

2.0

1.0

4.6

10.4

0.34

1.693

0.19

0.254

2.127

2.127

0.867

9.52

0.10355

3.32E-04

2.0

3.0

1.0

5.4

5.4

0.34

1.693

0.34

0.254

2.127

2.127

0.890

9.79

0.10362

3.32E-04

3.0

4.0

1.0

6.2

6.2

0.34

1.693

0.34

0.254

2.127

2.127

0.941

9.80

0.10941

3.32E-04

4.0

5.0

1.0

7.8

7.8

0.40

1.501

0.40

0.286

1.116

1.116

0.918

5.14

0.11109

1.20E-04

5.0
6.0

6.0
7.0

1.0
1.0

10.4
12.9

10.4
12.9

0.42
0.42

1.429
1.448

0.42
0.42

0.297
0.294

0.743
0.841

0.743
0.841

0.914
0.948

3.55
4.29

0.10444
0.10401

1.20E-04
1.20E-04

7.0

Effective mean stress, p' (kPa)# vi'[kN/m ]
6.9

8.0

1.0

15.3

2

15.3

0.41

1.467

1.00

0.41

0.330

0.291

1.36

6.00E-01

8.70

0.939

0.939

0.969

5.11

3.32E-04

0.10149

1.20E-04

8.0

9.0

1.0

17.4

17.4

0.40

1.485

0.40

0.288

1.036

1.036

0.978

5.98

0.09772

1.20E-04

9.0

9.5

0.5

19.0

19.0

0.44

1.382

0.44

0.305

0.496

0.496

0.955

3.00

0.08582

1.20E-04

9.5

10.0

0.5

21.0

33.8

0.55

1.155

0.70

0.355

0.287

0.287

1.136

1.80

0.08507

8.00E-05

10.0

11.0

1.0

25.3

40.7

0.55

1.155

0.70

0.355

0.260

0.260

1.149

1.64

0.08156

8.00E-05

11.0

12.0

1.0

31.2

50.2

0.55

1.155

0.70

0.355

0.260

0.260

1.149

1.64

0.08156

8.00E-05

10.0

11.0

1.0

25.3

0.50

0.330

1.59

11.0

12.0

1.0

31.2

0.50

0.330

1.59

1.0E+00

0.50
0.50

0.330
0.330

1.59
1.59

1.0E+00
1.0E+00

12.0
13.0

13.0
14.0

1.0
1.0

E = 5.9E+04 [kN/m2]
E = 5.9E+04 [kN/m2]
2

37.1
43.0

E = 5.9E+04 [kN/m2]
E = 5.9E+04 [kN/m ]E = 5.9E+04 [kN/m ]
2

10.0

11.0

1.0

25.3

11.0

12.0

1.0

31.2

E = 5.9E+04 [kN/m ]

2

0.50

0.330

1.59

1.0E+00

12.0

13.0

1.0

37.1

E = 5.9E+04 [kN/m2]

0.50

0.330

1.59

1.0E+00

E = 5.9E+04 [kN/m ]2
E = 5.9E+04 [kN/m ]

13.0

14.0

1.0

43.0

14.0

15.0

1.0

48.8

2

0.50

0.330

1.59

1.0E+00

1.0E+00

0.50

0.330

1.59

1.0E+00

0.50

0.330

1.59

1.0E+00

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

occurred.
CL

cracksprobable slip line

The modeling of the sand drain can be performed by
two kinds of method. One is macro-element method andanother is a method to reproduce the clay ground byincreasing coefficient of permeability of the ground. In
the case of this method, Coefficient of permeability isconverted so that times for 50% consolidation ofhorizontal and vertical direction are the same. The factor
for permeability is obtained as 75.3.

(e)

(d)
(g)

(c)

Sand

Embankmen(b) (a)t
Crust
(f)
Peat
Clay Silty sand10
Area improved by sand drains
measuredcomputed (Macro-element method)computed (Mass permeability method)

1

!

2
3
0

!
"

" #

(e)

(d)

200 400
time (day)settlement (m)settlement (m)0

6-3 The mesh formation and the boundary
conditions
The mesh formation used in analysis is shown in Fig-5
and boundary condition is also shown in Fig-5.

(c)

600
1

3
0

0

(a)

(b)

200 400
time (day)600
0200 400
time (day)

"
#

2

5

"

#

settlement (m)6-2 Modeling of sand drains(f)
200 400
time (day)

600

600
1
2

(g)
3
0

200 400
time (day)600

Fig-7 Settlement

15.0m
150.0m

Fig-5 Mesh formation

7. The Results of Analyses
The locations obtained from the measurement
instrument and the locations indicated by the result of theanalysis are shown in Fig-6.
C
L
9.5m

14.0m

3.0m

9.0m

2.0m
4.0m

4.5m

nodal point at where outputed settlement
nodal point at where outputed pore water pressure

32.0m
33.5m

80

(d)

40
1 20
0
80

(e)

40
0

12 0
80

(b)

40
12 0
80

(c)

40

0

20 0
4 00
time (day )

0
0

6 00

2 00
4 00
t im e (d ay )60 0

The second site of analysis is the highway embankment8)
constructed on the site of the southern part of Sri Lanka.
Fig-9 shows the analyzed cross section.
CL

4.0m

piezometer

1 20
0

(a)

40

8 Site (Sri Lanka)

11.5m

4.0m

settlement gauge

804

Fig-8 Excess pore water pressure

53.0m

L-side8228.0m
Drainage boundary / X,Y-direction fixed

12

2

13.1m

x

me asu red
co mp ut ed (M acro-eleme nt m eth od )co mp ut ed (M ass p erm eab ility meth o d)
12 0

po re water pressu re (k N/m)yp ore wate r p res sure (kN/ m) fill h eig h t (m )53.0m

Drainage boundary/ X-direction fixed

Drainage boundary/ X-direction fixed

C
L

1.5m

main body

2.0m

platform

Fig-6 Setting positions of observation instrumentsarea improvedby vacuum consolidation

The results of the analysis are shown in Fig-7 and Fig-8.
A solid line is the result of macro-element method appliedand a dashed line is the result obtained by the method ofchanging a coefficient of permeability. It may be said thatthe analysis result used macro-element method canreproduce a behavior of the ground at the center ofembankment.
Although the measured values near the center ofembankment are smooth, there are the moments of whichsuddenly large settlement has occurred under the berm (isrepresented by the number at (c), (d), (e), (g) in Fig-7).
According to this sudden large settlement suddenly
occurred and the cracks observed at the slope of the main
body and the center of the berm, it is thought that the slip
was occurred as shown in Fig-7. The FEM program usedin this research is not able to represent a discontinuous
surface such as a slip surface.7) This caused the difference
between the computed settlement and the measured value
under the beam after the extrapolated time when the slip

organic clay depositsand

Fig-9 Analyzed cross section

9. The Input Conditions in Analysis
9-1 The material parameters
The material parameters used for analysis is listed inTable 6.
Table-6 Material parameters
Depth

Type of soil[m]Thickness[m]

Embankment
Platform

Peat

Peaty clay

Sand

19

# vi'

# v' 0
2

K0

M

Ki

'

!

!k

"

e0

D

k

0.700

1.850

1.00

0.330

0.210

0.210

0.900

1.360

0.043

8.60E-03

2[kN/m ] [kN/m ]
6.900
92.1

[m/day]

6.900

92.1

0.700

1.850

1.00

0.330

0.210

0.210

0.900

1.360

0.043

8.60E-03

0.0

0.5

0.5

0.549

14.0

0.595

1.619

4.88

0.373

1.736

1.736

0.803

4.018

0.172

4.00E-03

0.5

1.0

0.5

1.648

14.0

0.595

1.619

2.39

0.373

1.736

1.736

0.817

4.209

0.168

4.00E-03

1.0

1.5

0.5

2.757

14.0

0.595

1.619

1.72

0.373

1.736

1.736

0.824

4.297

0.167

4.00E-03

1.5

2.0

0.5

3.855

14.0

0.595

1.619

1.38

0.373

1.736

1.736

0.828

4.356

0.166

4.00E-03

2.0

2.5

0.5

5.082

14.0

0.595

1.412

1.01

0.373

0.651

0.651

0.853

2.514

0.112

4.00E-03

2.5

3.0

0.5

6.435

14.0

0.595

1.412

0.90

0.373

0.651

0.651

0.855

2.529

0.112

4.00E-03

3.0

3.5

0.5

7.779

14.0

0.595

1.412

0.81

0.373

0.651

0.651

0.856

2.542

0.111

4.00E-03

3.5

4.0

0.5

9.133

14.0

0.595

1.412

0.75

0.373

0.651

0.651

0.857

2.552

0.111

4.00E-03

4.0

4.5

0.5

11.18

E = 5.9E+04 [kN/m ]

2

0.50

0.330

1.00E-03

4.5

5.0

0.5

15.29

E = 5.9E+04 [kN/m ]

2

0.50

0.330

1.00E-03

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

pore water pressure (kPa) Applied pressure (kPa)

9-2 Modeling of vacuum consolidation
The modeling of vacuum consolidation is represented
by two kinds of method. One is macro-element method
and another is a method to reproduce the clay ground by
decreasing coefficient of permeability of the ground. ThenI alternate the mesh formation to perform negative
pressure at the element boundary. But it overestimates adrainage effect by applying negative pressure. Therefore itis necessary to decrease the coefficient of permeability9).
In this case method, coefficient of permeability isconverted so that times for 50% consolidation ofhorizontal and vertical direction are the same. The factor
for permeability is obtained as 0.175.

Drainage boundary/ X-direction fixed

Undrainage boundary/ X-direction fixed

13.1m

x

5.0m
150m
Drainage boundary / X,Y-direction fixedFig-10 Mesh formation

10 The Result of Analysis
The locations obtained from the measurement
instrument and the locations indicated by the result of theanalysis are shown in Fig-11.

nodal point at where outputed pore water pressure

2.5m

10.0m

Fig-11 Setting positions of observation instruments

settlement (m)0Applied pressure (kPa)

The results of the analysis are shown in Fig-12 andFig-13. A solid line is the result obtained by using
macro-element method and a dashed line is the result of
the method of changing a coefficient of permeability. It
may be said that the analysis result used macro-element
method can reproduce a behavior of the ground at thecenter of embankment.
200
platform (input)
vacuum pressure (measured)embankment pressure (measured)embankment pressure (input)
vacuum pressure (input)
vacuum and embankment (input)

100

0

1
2
3
4

(b) L-side

0

100

(a)
200
300
time (day)4000(b) R-side
100

200
300
time (day)

400
0

100

200
300
time (day)measuredcomputed (Macro-element method)computed (Less permeability method)

-30
0

100

200
time (day)

300

400

1) Schofield,A.N. and Wroth,C.P. : Critical state soil
mechanics, Chap.6, McGRAW-HILL, pp.135-166, 1968
2) Roscoe, K.H. and Burland, J.B. On the generalized
stress-strain behavior of ‘wet’ clay. Engineering Plasticity,ed. J. Heyman and F.A. Leckie, Cambridge University
Press: Cambridge, 1968; 535-609.
3) !"#$, %&', ()*, +",-./01234
56789:; <=8>?@ABCDEFG, H
31 IJKLMN>OPQRSTU, pp.111-116, 1986.
4) VWAKXY
5) Ohta,H. and Sekiguchi,H. : Constitutive equations
considering anisotropy and stress reorientation in clay,
Proc. 3rd. Int. Conf. on Numerical Methods inGeomechanics, Vol.1, pp.475-484, 1979
6) Z[\].^_`AaCABLMbc(d)ABLM
ecpp.252-258, 1997.
7) Ohta,H., Iizuka,A., Monda,S., Kuwahara,M. andMuta,T.
Progressive failure of soft clay underembankment, Proc. of 13th International Conference on
Soil Mechanics and Foundation Engineering (ICSMFE),
ISSMGE, Vol.2, pp.751-754, 1994.1
8) !"#$%
9) &'()*+,-.*/0123456789:;<=>?@AB, CDEFGHIJKLMG, 2008.

piezometer

nodal point at where outputed settlement

measuredcomputed(Macro-element method)computed(Mass permeability method)0

ReferencesCL
settlement gauge

30

The effective stress path by the triaxial compression tests
in which shear rate is relatively fast agreed well with thesimulation by employing the Modified Cam-Clay model.
But the effective stress path by the triaxial compression
tests with low shear rate derails from that of Modified
Cam-Clay model, and get closer to the simulation by
employing the Original Cam-Clay model. Therefore, weshould choose the Original Cam-Clay model whensimulating a real behavior of the ground with site artificial
construction and the change of the external force by thenatural phenomenon.
Simulation that reflected a process of the realconstruction could well reproduced settlement and porewater pressure observed on the site. So I was able toconfirm validity of the macro-element method.

CL

1.5m

0
60

11. Conclusions

The mesh formation used in analysis is shown in Fig-10
and boundary condition is also shown in Fig-10.

2.0m2.25m

100

platform (input)
vacuum pressure (measured)embankment pressure (measured)embankment pressure (input)
vacuum pressure (input)
vacuum and embankment (input)

Fig-13 Pore water pressure

9-3 The mesh formation and the boundary
conditions

y

200

400

Fig-12 Settlement

20Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Effect of Initial Water Curing Period on Chloride Permeability ofHardened Blast Furnace Cement
Student Number: 07M18020

Name: Shohei KIMURA

Supervisor: Nobuaki OTSUKI!"#$%&'()*+,-./012/345,6789:;<=>?

@ABC
DEFG,HIJ-1KL%&MNO"1PQRFG,HIJ-1STUV=WXYZ[\]^_`a[_b1cdefghib'FG,HIJ-13Tjk8UclmYZnop8Ydefgcqrstuv9t_Ywx`a[:yF%&"z'op89{<=>?c|}~wa[_t_9ibY_xbqF`o2/345,j8'(_Ya[_b()*+,-cF"1!"%&"z9;y18'
=bY'Wa[:yF9defg;yo2/345,6781'Z_Y_a[_b
hFhc!"%&"z'()*+,-./01op89{<=>?U#:;1/Uu ¡¢[£¤ZF`9()*+,-./01!"%&"z1e9¥_[£¤U¦§n
period remain coarse pore.
There are some reports that examined an initial
curing period and material permeability and a
relationship of the pore distribution including an
above-mentioned report. However it cannot be said
that it was still argued enough. The research thatconsiders even the continuousness of the pore in
the pore distribution is few. It aimed to understandthe effect that the initial curing period exerted on
the chloride diffusive quantitatively in thisresearch based on above, and to examine thechange in the pore distribution according to thehydration mechanism. Moreover, examined thepossibility of shorten the initial curing period of
the early strength slag cement

1 introduction
Blast furnace slag is a material that is expected to
be an action for environmental problems.
According to Kyoto Protocol Aim, there is a policythat says amount of CO2 emission in Japan must
decrease by to increase proportion of blended
cement to 24.8%. The percentage of blast furnace
slag cement in blended cement is over 90%.
Therefore it is a necessity to increase usage of blast
furnace slag cement. However, recently the usageof blast furnace slag cement does not increase
because blast furnace slag cement has several
problems that are include low early strength.
Meanwhile, initial curing period of concrete isdecided by JASS5J or Standard Specification forConcrete Structures and barometer of deciding
initial curing period is compressive strength.
However, Okazaki1) said that compressive strengthand durability such as permeability do not have aprincipal concern. Nakarai2) said that short initial
curing period occur the low compressive strengthand low resistance of permeability compared withenough curing was given the concrete. Hara3) focus
on relationship between initial curing period andpore distribution ,they said that short initial curing
period affects the pore distribution of the range
from 0.1µm to 1.0µm and concluded short curing

2 Experimental Procedure
2.1 Materials Used
The materials used in this study are ordinary
portland cement (OPC) and high early strength
portland cement(HPC) to remedy low earlystrength and blast furnace slag powder(BFS , slag
basicity:1.89 )Table.1 shows chemical composition of thesematerials. BFS was added the gypsum 2mass% as
SO3 concentration. Fine aggregate used in thisstudy is land sand from Chiba prefecture (Density
2.62 g/cm3 , water absorption 1.58%) .

Table.1 Chemical composition

OPC
HPC
BFS

ig.loss
1.05
1.12
0.49

Chemical composition (mass%)
SiO2 Al2O3 Fe2O3 CaO MgO SO3
20.38 5.18 3.37 63.96 1.88 2.24
20.59 4.88 2.42 65.03 1.35 3.25
33.58 14.26 0.41 43.13 6.05
-

21

Na2O
0.4
0.29
0.24

K2O
0.4
0.36
0.35

Blaine(cm2/g)
3420
4620
4550

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

!250

C-3
C-5
C-7
C-10
C-14
0

5

10

15

20

25

30

Time(day)
Mold

Water

Atmosphere!"#$%!&'(#$)*!%#$+,-(

.010

.10

1.0

10.0

!"#$%&'(#)#"$*+(,Fig.2
The example of mercury intrusion
porosimetry test result

Fig.1 Details of curing

+. 70
,
%
$+ 60
*
) 50
%)
(
' 340
&2
&1
%
$ 0
# /30
" 20
!
$ 10
#
" 0
!

!"#$%&!'(%)!$*+(

"
"
)-200
(
"
!
#150
+
'
)
,(
+100
)*
(
'
%&
#$ 50
!
"
!
0

C-1

0.5
!"

!#

!$

!%

!"&

!"#$%&'%$

0%

20%

50%

70%

t
n 0.4
e
i
c
if )c
f e0.3e s/oc2m
n6-c0.2
ios 0!1
uff (0.1
i
d
-l
C 0.0

!"'

!"#$%&'%$

0%

20%

50%

70%

C-1 C-7

C-14!"#$%&'%$!"#$%&'%$

0%0

20%
20

50%
50 70%
70

0%
0

20%
20

50%
50 70%70

Fig.2 Results of compressive strength test

Fig.3 Results of chloride diffusion test

2.5

2.5

!"#$%&'%$
2.0
h
t
g1.5
n
re
t
S

!"#$%&'%$!"#$%&'%$!"#$%&'%$

"!

2.0

!

#! $!

e
id
r1.5
lo
h
C

#! $!

!

K1.0

K1.0

0.5

0.5

0.0

0.0

"!

Fig.5
The sensitivity on chloride diffusion
coefficientFig.4 The sensitivity on compressive strength
2.2 Method of Manufacturing the Specimens
Water binder ratio was 0.5. Sand binder ratio was
3.0 of mortal for compressive strength test. The
specimens for X-ray diffraction, exposure test andmercury intrusion porosimetry test were made bypaste. Mixing of mortal for compressive strength
test was cast into 4×4×16cm mold based on JIS
R 5201. Mixing of paste which is for X-ray
diffraction test and mercury intrusion test was byhand for three minute and cast into mold of
2.5cm and hight1.5cm. The past for exposure test
was cast into 4×4×16cm mold.
2.3 Setting of Curing
In this study, curing method is water curing. The

detail of curing is presented in Fig.1. To put itbriefly, at 1st day, specimens cured in mold.
Afterward, specimens cured in water(20 ) while
predefined period. After water curing, specimens
cured in atmosphere(20 ! RH60%) until 28days.
After atmosphere curing, specimens for exposure
test were coated by epoxy except exposure surface.
Later, specimens for exposure test were into salt
water while 56days. Specimens for X-ray
diffraction and mercury intrusion porosimetry werestop hydration by using acetone and then vacuums
24hours to dry on age of 28day.

22

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

K Strength ! " C 14

2.4 Method of ExperimentCompressive strength were measured based on
JIS R 5201. Chloride diffusion coefficient were
measured based on JIS A 1154. Powder samples
for chloride analysis were ground off by sliced
specimens parallel to the exposed surface. Chloride
diffusion was calculated by fick’s second law.
The reaction ratio of chemical compound of
cement was measured by internal reference methodof X-ray diffraction test. X-ray source was used
Cu-K . Speed of X-ray analysis was 0.2°/min.
reference materials for internal reference method
was used -Al2O3 and add -Al2O3 as 10mass% tosamples.
Porosity was measured by mercury intrusion
porosimetry. Fig.2 is shows an example of result of
mercury intrusion porosimetry test. The amount of
total volume and pore volume above 50nm
diameter is shown at Fig.2.

"C 1

K strength: the sensitivity on compressive strength!C-1:Compressive strength on C-1!C-14 : Compressive strength on C-14
The sensitivity of compressive strength is increase
in increase with replacement levels at each cement
series. The sensitivity of chloride diffusion
coefficient is shown on Fig.6. The sensitivity on
chloride diffusion coefficient was calculated byfollowing formula.

K Chloride ! DC 1

DC 14

Kchloride : The sensitivity on chloride diffusion
coefficient
DC-1: The chloride diffusion coefficient on C-1
DC-14 : The chloride diffusion coefficient on C-14

3 Results and Discussion

The sensitivity of chloride diffusion coefficient isincrease in increase with replacement levels.
Moreover the sensitivity of chloride diffusion
coefficient is higher than compressive strength
cases especially on high replacement levels.
3.2 Pore Distribution
The total pore volume is shown in Fig7. The
influence at the replacement level and the initial
curing period was not able to be confirmed
according to the total pore volume. The porevolume above 50nm is shown in Fig8. The porevolume above 50nm assumed to exert the influenceon durability decreased with increasing at theinitial curing period, and was especiallyremarkable in high replacement level. It was able
to be confirmed to the blast furnace slag that there
was an action that changed the pore above 50nm
into a minuter pore.

3.1 Compressive Strength and Chloride
Permeability
Fig.3 shows the experiment result of compressive
strength test. The influence of initial curing period
was not confirmed in the replacement level 0%. On
the other hand, as for the blast furnace cement, thedecrease in strength was confirmed at C-1 and C-3.
However, the deterioration of strength was notconfirmed in each composition if the initial curing
period was five days or more.
All compositions is able to obtain the 40MPa.
Moreover, OPC-B20 and HPC-B00 can obtain
50MPa if initial water curing period above 5days.
The result of the chloride diffusion test is shownin Fig4. It was confirmed that the chloride
diffusion coefficient had decreased from C-1 to
C-7 in each composition. Moreover, the diffusion
coefficient had decreased from C-7 to C-14 was
confirmed on several composition. In addition, aremarkable decrease was seen by the chloride
diffusion coefficient as the high replacement levels.
Moreover, it was confirmed that the blast furnace
cement fell below the diffusion coefficient of thereplacement level 0% even if initial curingcondition was C-1.
That is, there is a possibility that initial curing
period in which 28days strength and the chloride
diffusion coefficient were considered can beshortened if it is a blast furnace cement of the HPC
series and the initial water curing period above
5days.
The sensitivity on compressive strength of initialwater curing period is shown on Fig.5. The
sensitivity on compressive strength was calculated
by following formula.

4
Relationshipbetween
Chloride
Permeability and Pore Distribution
The relation between a diffusion coefficient andan amount of pore above 50nm is shown in Fig9.
Both were able to confirm both correlations by
three layers "replacement level0%", "replacementlevel 20%", and "replacement level 50% and70%".
Namely, increase in initial water curing period
decrease amount of pore volume above 50nm
diameter. Then, chloride diffusion coefficient isdecreased.

5 Conclusions" At the initial water curing period above
5days, decrease of compressive strengthis not confirmed.
" Increase in initial water curing period
decreased the chloride diffusion

23

Technical Report of International Development Engineering

"250
!
+
200
+
,
150
(
+
$*
100
!
)%
(
'
!50
&
%$
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!"

!#

!"#$%&'%$

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

"
!
(
160
.(

!"#$%&'%$

0
0%

20
20%

50
50%

70
70%

0
0%

20
20%

50
50%

(
-120
,
$+100
#
%
!80
*
)
60
#
(40
&'
!
%$ 20
#
"
!0

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70%

Fig.7 The amount of total pore volume

t 0.4
n
ie
icf )cf e0.3e s/oc 2mn 6- c0.2
o
i 0
s !1
u
fif ( 0.1
d
-l
C 0.0

!#

!"$

'$%
($%

100

150

0
0%

20
20%

50
50%

70
70%

!"#$%&'%$

00%

20
20%

5050% 70 70%"References#
1) Shinichiro.O et.al: The Study of The
Influence of Curing Condition on
Strength and Permeability,cement
concrete, No.60, pp.227-234(2006)
2) Kenichiro.N et al : The analysis ofpermeability on several curingcondition based on change of pore
distribution of concrete, Concrete
engineering annual thesis collection
vol.29, No.1, pp.723-728(2007)
3) Kengo.H et.al : The effect ofde-mold period on physicality ofconcrete,
Concreteengineering
annual thesis collection, vol.30,
No.1, pp.681-686(2008)
4) Tsuyoshi.S et al: Evaluation of pore
distribution of mortal specimen based on
mercury intrusion porosimetry test,
inorganic material!" #!"$%&$%

50!"#$%&'%$

Fig.8
The amount of pore volume above 50nm
diameterC-7 C-1
C-14

0

!"

140

!"#

200

!"#$%!&'(#$$)*!%#$+,-($./)(#0#"$1(( !"#!

Fig.9
The relation between chloride diffusion
coefficient and pore volume above 50nm
diametercoefficient.
Howeverincreaseofreplacement level drastically decreased
thechloridediffusioncoefficientcompared to the initial water curing
period! Any initial water curing period, blended
cement is able to reach the lower
chloride diffusion coefficient thanordinary portland cement! The sensitivity of initial curing period
on chloride diffusion coefficient ishigher than that on compressive
strength, especially, in cases of highreplacement levels.
! Using HPC may shorten the initialwater curing period. If the demould
strength is enough.
! The effect of initial water curing periodcaused the decrease of pore volume
above 50nm, thus, the chloride diffusion
coefficient was decreased24Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Development of New Approach to Prepare CoMo/Al2O3 Catalyst for
Deep Hydrodesulphurization
Student Number: 07M18036 Name: Tatsuya KUSAMA Supervisor: Hirofumi HINODEᷓᐲ᳓⚛ൻ⣕⎫⸅ᇦ㐿⊒ࠍ⋡ᜰߒߚ CoMo/Al2O3 ⸅ᇦߩᣂⷙวᚑᴺ⎇ⓥ⨲㑆 ㆐਽
ᧄ⎇ⓥߢߪ‫ޔ‬ᓥ᧪ߩ೨㚟૕ߣߪ⇣ߥࠅ‫㉄ޔ‬ൻ‛ࠍᒻᚑߖߕߦ⋥ធ‫ޔ‬ᜂ૕਄ߦᵴᕈ☸ሶߢ޽ࠆ MoS2 ࠍᒻᚑߔࠆߎߣ߇಴᧪ࠆ Ammonium Tetrathiomolybdate (ATTM)ࠍ೨㚟૕ߣߒߡ↪޿‫ޔ‬ᜂ૕(Al2O3)ߩᲧ⴫㕙Ⓧ߿᳓⚛ൻ὾ᚑᤨ㑆߇ਈ߃ࠆ⸅ᇦᵴᕈ߳ߩᓇ㗀ߦߟ޿ߡ⎇ⓥࠍⴕߞߚ‫ޕ‬ᵴᕈ⹜㛎ߩ⚿ᨐࠃࠅ‫ޔ‬ᐢ޿Ყ⴫㕙Ⓧࠍ߽ߟᜂ૕߇ᦨ߽㜞޿ᵴᕈࠍ␜ߒߚ‫ޕ‬XRD࡮BET ߩ⚿ᨐ߆ࠄ‫ޔ‬ᜂ૕ߩᲧ⴫㕙Ⓧ߇ዊߐ޿ߚ߼ߦᵴᕈࠨࠗ࠻ߩᄙጀൻ߇⿠ߎࠆߩߢߪߥߊ‫ޔ‬὾ᚑ࡮੍஻⎫ൻߩᲑ㓏ߦ߅ߌࠆᲧ⴫㕙Ⓧߩᷫዋߦࠃߞߡ‫ޔ‬ᄙጀൻ߇⿠ߎࠆߣ⠨߃ࠄࠇࠆ‫ޔߚ߹ޕ‬᳓⚛ൻ὾ᚑᤨ㑆ߩ㆑޿ߢߪ‫ޔ‬᣿⏕ߥᵴᕈߩᏅ߇ᓧࠄࠇߥ߆ߞߚߎߣ߆ࠄ‫ޔ‬὾ᚑᤨ㑆ߦࠃࠆᓇ㗀ߦߟ޿ߡߪ⏕߆ߥ⚿⺰ߪᓧࠄࠇߥ߆ߞߚ

1.

II has weak interaction with support,
forming multi layer of MoS2 slabs andhas high activity. Therefore, productionof CoMoS phase Type II is moredesirable.
In the previous study [3], the following
three new preparation procedures using(NH4)2MoS4 (ATTM) as the precursor
were proposed:- Route-1 (R1) includes impregnation ofCo(NO3)2㨯6H2O, calcination under H2
atmosphere, impregnation of ATTM,
and vacuum calcination at 500ºC.
- Route-2 (R2) includes impregnation ofCo(NO3)2㨯6H2O, calcination under air
atmosphere, impregnation of ATTM,
and vacuum calcination at 500ºC.
- Route-3 (R3) includes impregnation of
ATTM, vacuum calcination at 500ºC,
impregnation of Co(NO3)2 㨯6H2O, andcalcination under H2 atmosphere.
It is reported that thiophene conversionof the catalyst prepared by Route-3 (R3)in the new procedure was higher than thatof the commercial catalyst [3].
The aims of this study are (1) theinvestigation of the effect of the specificIntroduction

The regulations on the sulfur content inliquid fuels have become stricter over theyears in order to protect the environment(e.g. Japan: less than 10 ppm)[1].
The possible methods to produce“sulfur-free (less than 10 ppm)” fuel are(1) building additional reactor, (2)improving reactor or equipment and (3)improving catalyst performance. Due torelatively high cost of bulding or
improving reactor, the studies of thehydrodesulphurization (HDS) catalyst are
performed more widely these days.
Among the HDS catalysts that are
widely studied, CoMo/Al2O3 attracts
much attention because of its highhydrodesulphurization ability. The known
active site for this catalyst is a kind of
CoMoS phase proposed by Topsøe et al[2].
This CoMoS phase was formed because
Co is located on the edge of MoS2 on the
supported material surface.
There are two types of CoMoS phase.
Type I has strong interaction with support,
forming single layer of MoS2 slab andhas low activity. On the other hand, Type25

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

surface area of Al2O3 supports and (2) theinvestigation of the effect of the H2
calcination period.

concetrationofthiophene
wasquantitatively analyzed by GC-MS(Shimadzu Co. QP5050A).

2. Experimental
2.1 Catalyst preparation
2.1.1 Materials used in preparation
catalyst
The catalyst supports were JRC-ALO2,
ALO5, ALO6 and ALO8 (Al2O3,
Reference Catalyst, The Catalyst Societyof Japan, BET specific surface area
148-285m2/g).
The
catalyst
precursors
wereammonium tetrathiomolybdate (ATTM),(NH4)2MoS4, as Mo precursor and cobalt(Τ) nitrate hexahydrate, Co(NO3)2.6H2O,
as Co precursor.

2.3 Catalyst characterizations
The samples were characterized bypowder X-ray diffraction (XRD, Rigaku
Co., MultiFlex). Specific surface areas ofthe samples were measured with
Brunauer-Emmett-Teller method (BET,
Quantachrome Co., AUTOSORB-1 MP).
3

Result and discussion
Figure 1 shows thiophene conversions at
300ºC using catalysts with supports ofdifferent specific surface areas and Table
1 shows the specific surface area of
support, before preparation and after
impregnation.

2.1.2 Catalyst preparation
A series of CoMo/Al2O3 catalyst was
prepared by double impregnation method.
The Mo loading was 17.5wt% and themolar ratio of Co/Mo was fixed at 0.27.
The catalyst was impregnated with
ATTM, and calcined at 500ºC for 2h in
vacuum. Then, the catalyst was
impregnated with Co(NO3)2.6H2O, andcalcined at 400ºC for 2, 6, 12 and 24h
under H2 atmosphere. Presulfidation was
carried out at 400ºC for 4h in 5%H2S/H2
gas stream.

㪫㪿㫀㫆㫇㪿㪼㫅㪼㩷㪚㫆㫅㫍㪼㫉㫊㫀㫆㫅㪲㩼㪴

㪈㪇㪇
㪐㪇
㪏㪇

㪐㪐㪅㪎

㪐㪏㪅㪊

㪐㪉㪅㪇

㪏㪏㪅㪏

㪎㪇
㪍㪇
㪌㪇
㪡㪩㪚㪄 㪡㪩㪚㪄 㪡㪩㪚㪄 㪡㪩㪚㪄㪘㪣㪦㪉 㪘㪣㪦㪌 㪘㪣㪦㪍 㪘㪣㪦㪏㫊㫌㫇㫇㫆㫉㫋㪲㪄㪴

Figure 1 Thiophene conversion at 300ºC using
catalysts with different supports

2.2 Activity test
The reaction was carried out in a
fixed-bed reactor under atmosphericpressure. The catalyst was pelletized,
crushed and sieved to 0.71~1.00 mm.
0.2 g of the sample was packed in thereactor and the total flow rate of the feed
mixture gas was fixed at 20 ml/min.
The concentration of thiophene in thefeed stream was maintained at 2.1mol%.
The reaction temperature was selected at
300ºC.
After the reaction had reachedsteady-state condition in two hours, theTable 1 Specific surface area of support before
preparation and after impregnation

26

SampleBeforepreparation[m2/g]

After
impregnation[m2/g]

JRC-ALO2285

206

JRC-ALO5233

181

JRC-ALO6

180137

JRC-ALO8

148

123

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

All catalysts showed almost the same
thiophene conversions regardless of thedecrease of specific surface area when theH2 calcination period was increased. With
this result, the influence of H2 calcination
period on the HDS activity could not be
observed. With lower Mo loading or
lower reaction temperature, a morecomparable result between different
calcination periods may be obtained.

The catalyst with JRC-ALO2 showed
the highest thiophene conversion of
99.7%. Thiophene conversion decreased
with the decrease of specific surface areaof support. At first, it was expected thatthe decrease of specific surface area of
support using the same Mo loading
would produce multi-layered MoS2 andform CoMoS phase TypeΤ. However,from this result it was concluded that
CoMoS phase Type II was not formed byonly decreasing the specific surface areaof support.

MoS 2
Al 2O3

㪐㪇

㪐㪐㪅㪎

㪐㪏㪅㪊

㪐㪏㪅㪍

ᒝᐲ

㪫㪿㫀㫆㫇㪿㪼㫅㪼㩷㪺㫆㫅㫍㪼㫉㫊㫀㫆㫅㩷㪲㩼㪴

㪈㪇㪇
㪐㪐㪅㪏

㪏㪇
㪎㪇

2ǰ

㪍㪇

Figure 3 XRD patterns of catalysts withsupports of different specificsurface areas

㪌㪇
㪉

㪍

㪈㪉

㪉㪋

㪟㪉㩷㪺㪸㫃㪺㫀㫅㪸㫋㫀㫆㫅㩷㫋㫀㫄㪼㩷㪲㪿㪴

Figure 2 Thiophene conversion at 300ºC
using catalysts with different H2
calcination periods

MoS 2
Al 2O32h

Before H2
calcination[m2/g]
206

After H2
calcination[m2/g]
202

6h

206

197

12h

206

183

24h

206

166

Sampleᒝᐲ

Table 2 Specific surface areas of catalysts
with different H2 calcination period(support: JRC-ALO2)

Fig ure 4 XRD patterns of2ǰ catalysts with

Figure 4 XRD patterns of catalysts withdifferent H2 calcination periods

Figure 3 shows the XRD patterns ofcatalysts prepared by different supports
and Figure 4 shows the XRD patterns ofcatalysts prepared at different H2
calcination periods. MoS2 peaks at 14.5,
34.2 and 58.3 were observed in all XRD
patterns in Figs.3 and 4. The relation

Figure 2 shows thiophene conversion
at 300ºC using catalysts with different H2
calcination periods and Table 2 shows
specific surface area of catalysts withdifferent H2 calcination periods.

27

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

between the amount of MoS2 and the
HDS activity could not be observed.
4 Conclusion
The catalyst with JRC-ALO2 showed
the highest conversion of 99.7%.
Thiophene conversion decreased with thedecrease of specific surface area of
support using the same Mo loading. So, it
was concluded that CoMoS phase Type II
was not formed by only the decreasing
the specific surface area of support.
The conclusion concerning theinfluence of H2 calcination period was
not obtained because almost the same
thiophene conversion. With lower Mo
loading or lower reaction temperature, aclearer result may be obtained.

References[1] Petroleum Association of Japan(http://www.paj.gr.jp/html/data/eco/lowsulphur.
html)[2] N. –Y., Topsøe, and H. Topsøe, J. Catal, 84,
386 (1983)[3] ZHANG, Haibo, A Master Thesis, Tokyo
Titech (2006)28

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Modeling of Sand Transportation
using Long-Term Observed Datasetsin the Semi-Arid Shrub Desert
Student Number: 07M18042

Name: Yumi KONDO

Supervisor: Manabu KANDA!"#$%& '()*+,-./0123
4567!"#$%&'()*+,-./01)2345# 67879:79:;<=>?>@A BCDEFGHIBJKL'M
NOP%BQRSTUVWX1YZ[K'VW\]^_`Zab%BcdefgEFhi'jklBmnfop])1Y#VWBqrFstZuFhievFw !"xkykTUz{i|L'}~>;B L
STUVWZ[|'VWZcdicdefgEFVWykTUwU'= J
lb#VWBEFst&kTjxUw<<transportation and parameters.
2) to determine the empirical constant C and frictional
threshold wind speed u*t for the equation of Owen
(1964).
3)
to investigate the effect of vegetation andprecipitation on C and u*t by using NDVI(Normalized Difference Vegetation Index) and
precipitation datasets respectively.
Two advantages of this study are given below;
1) Sand trap datasets used in this study have beencollected for more than 15 years since 1987.
Simultaneously primary climatological datasets suchas wind speed, precipitation and air temperature
have been measured at the weather station. These
datasets are the only datasets collected for such along term continuously all over the world.
2) In this study sand trap is measured by BSNE
sampler. The advantages of this instrument are low
cost, electric free and the necessity of lessmaintenance thus suitable for the measurement in
the desert. If we can establish the sand transportation
model by using BSNE datasets, sand transport
equations for various areas can be described.

1. Introduction
Desertification is one of the most serious
environmental problems in the world. Desertification iscaused by various factors, including climatic variations
and human activities. Sand transportation, the topic of
this study, is one of the main mechanisms to cause
desertification. In order to combat against desertification,
revealing the mechanism of sand transportation isimportant.
Sand transportation is mainly driven by surface wind.
Various slightly different equations for sandtransportation are proposed by several researchers. In
most sand-transport equations, total horizontal mass fluxof sand Q [kg m-1 s-1] is expressed as a function offriction velocity u* [m s-1] and threshold friction velocity
u*t [m s-1]. In this study, the simple equation proposed by
Owen (1964) is adopted;2ρ 3§ u ·(1)
Q = C u * ¨¨1 − *t 2 ¸¸gu* ¹©
where C is the dimensionless empirical constant value,ρ [kg m-3] is air density and g [m s-2] is gravitational
acceleration. Several researchers reported that Owen’s
equation best agrees with the acquired data (e.g.
McKenna Neuman et al., 1997; Iversen and Rasmussen,
1999)
Sand transportation is also affected by manyland-surface parameters, such as vegetation, roughness
elements, soil particle size distribution, soil moisture,surface crust, snow cover etc. However, studies of theinfluence of these parameters on sand transportation are
not fully developed yet.
The objective of this study is to describe sandtransportation as a function of surface wind and assess
the effect of land surface parameters on it. To achieve
this objective, three goals are set in this study;1) to check the bulk relation between sand

2. Study Site
The Jornada Experimental Range (JER) is located in
the northern Chihuahuan Desert, approximately 25km
northeast of Las Cruces, New Mexico, USA (+32.5N,-106.8W, elevation 1188m). The climate of JER is
characteristic of the northern region of the Chihuahuan
desert with abundant sunshine, low relative humidity,
wide ranges of daily temperature, and variable
precipitation both temporally and spatially (Havstad etal., 2000). The surface of this study area is dominated byshrubs such as honey mesquite (P. glandulosa) or
creosote (Larrea spp.).

29

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

4. Results
After the investigation of temporal changes ofseveral parameters, i.e. sand trap, NDVI, climatologicalparameters such as wind speed, precipitation, airtemperature and some climatological indexes, therelation between parameters were discussed. From thebulk point of view, sand transportation is provoked when
the wind speed is high. This can be strengthen by the factthat the season of high quantity of sand flux is incorrespondence to the season of high wind speed, i.e.
February to April. The correlation between sand flux andwind speed exceeds those between sand flux and otherparameters, which suggest that wind speed is the primaryparameter for sand transportation.

Fig. 1. Location of the Jornada Experimental Range(after McGlynn and Okin, 2006).

3. Materials and Methods
For the analysis in this study, the datasets of sandtrap, wind speed, precipitation, air temperature and
NDVI are used. The details of these datasets are
summarized in Table 1. Sand trap datasets were directly
passed from the research team who conducts themeasurement at JER. Climatological parameters were
provided by the Jornada Long-Term Ecological Research(LTER) project. NDVI was derived from MODIS(Moderate Resolution Imaging Spectroradiometer)
images, allowing a 250m maximum spatial resolution
with 16days temporal resolution.
Frictional wind velocity u* is calculated by using
log-profile law assuming neutral condition;

κ

ln

z
zo

(2)

where κ is the Karman constant (0.4), zo [m] is theroughness length, z [m] is the height of the anemometer(=2.5m) and u [m s-1] is the wind speed measured byanemometer. For this calculation the information of zo isnecessary, however the products of LTER project do notinclude zo. We assume zo =0.003m from the work of Kinget al. (2006) in which the measurements of roughness
length was conducted at JER.
Since the amount of transported sand flux hasvertical dependency due to gravity, the installation ofvertically integrated horizontal sand flux Q [kg m-1 s-1] isnecessary;∞

Q = ³ q( z )dz

wind speed (m/s)
#

%

'
(
)*+,-

"

3.5
3
2.5
2

"#

0.23
0.22
0.21
0.2
0.19
0.18
0.17
0.16
0.15
0.14

0

precipitation (mm)

u*

4

!"

NDVI

u=

!'
/
. !&
!
#
,
- !%
,
+*
$)( !$'%&$ !#
#
"
!

0

100

200
Julian Days

2

4

6

300

8

10

12

8

10

12

month

45
40
35
30
25
20
15
10
5
0
0

2

4

6
month

Fig. 2. Monthly change of sand flux, wind speed, NDVI and
precipitation (mm) averaged from 2000 to 2005.
/ !)
. !(
!
#
, !'
,
!&
+
)*
$ !%
(
!$
&'
$% !#
#
"
! !"

"*)'
#!"

"**

"**%

(3)

0

where q(z) [kg m-2 s-1] is the horizontal sand flux density.
From the sand flux density at three heights, 15cm, 50cm
and 100cm, horizontal sand flux density was calculatedusing the empirical formula used by Shao and Raupach(1992);

$%&'

$%%(

$%%)

#

#

#

'

$%%&

((

(('

!&&'

" "

" (

*+,-

%
,
+$
*+
)(
$'% #
&%
$"
$#
!" !

(4)
q( z ) = c exp[az + bz 2 ]where a, b and c are dimensional functions.

"**)
+,-.

%+*
)
$(# #
''
&%
$# !"
"!

!&'(

!&&

!&&$
)*+,

Fig. 3. Annual change of sand flux, wind speed and precipitation.
Table 1. Summary of datasets used in this study
data
sand trap data

instrument
BSNE sampler

height of instrument
15cm, 50cm, 100cm

wind speed
precipitation
air temperature
NDVI

Met One Wind Speed Sensor
WeatherMeasure 6011
Temperature Probe 107
earth observatory satellite Terra

2.5m
at the surface
1.6m

30

sampling interval
not constant
approximately one month
one hourone hourone hour16 daysstarting time
1987
1983
1983
1983
2000

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

5. Discussion

in this study, these results are unavoidable regardless its
unreality.

5.1. Analysis Procedure! $"Since the sampling interval of sand trap is roughly
one month whereas wind speed was recorded every one
hour, an unique procedure was adopted in this study.
Iterative calculation method was conducted for C from 0
to 1 with the resolution of 0.0001 and for u*t from 0 to
1.2 with the resolution of 0.01 to decide C and u*t
simultaneously. First, sand flux was calculated for eachu* above u*t;
ui*<u*t(5),
Qn ,i = 0
Q n ,i = C

2
u ·
3§
u i* ¨1 − *t2 ¸¨gu * ¸¹©

ρui*>u*t/ ! $.
,*$+ ! #")$(&'$% ! #
#
"
!

!

!"

#

#!"

%&'()*+,

Fig. 4. Scatter plot of deemed u* (u*) and observed sand flux Q(kg/m/s). Correlation coefficient ρ was 0.756.

(6).

! &$
! &#

/
- ! &"
.
,
! &
*+
$
!
%
$)
(
'
&% !
$
$
#
"
! !
#

After summing up all Qn,i for each sampling period of nset of data, we divided it by the number of u* in one
sampling period of sand trap (N);

!

N

∨

"

¦Q

i

(7).

Q = i =1
N

"
!'

!%

!(
)*+,-./0&&!&

Fig. 5. The ranges of both axes of Figure 5.3. were customized
into narrower region.

The best combination of C and u*t was chosen to make∨and observed Qn
the n set of residual error between Qnsmallest.

Comparing to the values of constant C for Owen’s
equation from various other studies, the acquired value
0.0187 from this study is considerably small (Table 2.).
Several possible reasons for this difference of C can beconsidered;(1)The land surface condition at JER is greatly different
from those of existing studies. While the land surfacesof other studies are covered with fine sediment
without vegetation, the land surface at JER is severely
vegetated.
(2)Since the deviations of datasets from regression line
are considerably large, there is an allowance for C.
(3)The difference of particle size distributions cangenerate a large difference of sand flux (Mikami et al.,
2005)(4)The procedures to derive C are different between thisstudy and other studies. As for other studies, since thesampling intervals of sand flux and wind speed
correspond each other and the intervals are enoughshort for the analysis, they can decide u*t from therelation between sand flux and wind speed. On theother hand, in this study C and u*t was decided
simultaneously by non-linear least-squared method
because the sampling periods of sand flux and windspeed are not in accordance. This technical difference
might cause some difference of C between this study
and other studies.

5.2. All-In-One Analysis
From the non-linear least-squared method using the68 datasets of sand flux and wind speed from 2000 to2005 adopting the equation for sand transportation
proposed by Owen (1964) and assuming roughness
length zo to be 0.03m, C was calculated as 0.0187 and u*t
was calculated as 0.78 (m/s);
ρ 3 § (0.78) 2 ·¸
Q = 0.0187 u* ¨¨1 −
2
g ©
u* ¸¹

(8).
^

Here we define deemed friction wind velocity u* torepresent u* through the sampling period. Since thesampling period of sand trap and wind speed do not^match, we need the representative value of u*. u * isderived by calculating back (5) substituting calculated
sand flux qc into Q.
^
Figure 4. shows the relationship between u* andobserved sand flux Q [kg m-1 s-1]. Solid line is the^theoretical curve of (5) which cross x-axis at u* =0.78(m/s) which is the threshold wind velocity for this case.
The open symbols on y-axis are the datasets in which allof the hourly u* were below u*t during the sampling
period of sand trap. According to the procedure adopted

Table 2. Empirical constant C and u*t from other studies. Most of C are on the order of 1.
SourceDetailthis study
field experiment
Gillette et al. (1996)
field experiment
Nickling and Neuman (1997) indoor wind tunnel
McKenna Neuman et al. (1997) field experiment

Surface ConditionC
vegetated (shrubs)
0.0187loose, sandy, flat
2.8
very well sorted 0.2mm sand
1.8
moderately sorted medium sands (0.3-0.5mm) 0.54 - 1.831

u*t (m/s)
0.78
0.18-0.35
0.24
0.21-0.28

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

5.3. Four-Matrix Analysis
In order to investigate into the effect of various
land-surface conditions on sand transportation, weclassified the land surface into four categories.
NDVI=0.18 and precipitation of 0.4 (mm/day) werechose to divide the numbers of datasets into four
categories, matrix a, b, c, and d, equally. C and u*t are
acquired for each category by the non-linear
least-squared analysis. The conclusion from four-matrix
analysis is that any effect of NDVI or precipitation on C
and u*t was not detected. Partial reason for this result isthe poor accuracy of the non-linear least-squared method
because of the shortage of datasets in each category.
Another technical reason for this result is that derived C
and u*t from this method are not independent each other;greater u*t leads C to larger value and smaller C follows
smaller u*t. Furthermore, the fact that the two landsurface parameters adopted in this study, NDVI and
precipitation, are not independent each other, makes theinterpretation of this result more difficult.

Fig. 7. Photograph near the sand trap station in JER taken in
December 2001(left) and May 2002 (right). Note that even without
leaves, shrubs can be enough obstacle for sand transportation.

As for the effect of precipitation, it was pointed
out that precipitation increases u*t and limits sand flux
via two effects; the growing of vegetation and increasingof soil moisture. The possible reason for the insensitivityof sand flux to precipitation in this study can beconsidered that precipitation is not a direct measure ofsoil moisture, which effect on sand transportation has
been studied by numerous researchers.

6. Conclusion
This study is challenging on the point that C and u*twere decided by non-linear least-squared method
simultaneously, which method is different from previous
studies, using the sand flux datasets acquired by BSNE
sampler. This study revealed that description of sandtransport equation is possible with the datasets from
BSNE sampler with approximately one month intervals,
though the efficiency of this description still leaves space
to be discussed.

Table 3. Summary of the result of four-matrix analysis
Category No.
a
b
c
d

NDVI
0.14-0.18
0.14-0.18
0.180.18-

precipitation (mm/day)
0.40-0.4
0.40-0.4

C
0.00060.02340.01930.0030u*t (m/s)
0.35
0.80
0.64
0.66

precipitationaq = 0.0006

ρ
g

(

2

u* u* − 0.352)

q = 0.0193

c

C = 0.0006
ut = 0.35(m / s )

g

(

)

'!$"% ('!$"% (/.
,
+ '! "% (
$*)
$(
'
&%
$ $! "% &#"!

References[1] Okin, G.S., Gillette, D.A., 2001; Distribution of vegetationin wind-dominated landscapes: Implications for wind erosion
modeling and landscape processes, J. Geophys. Res., 106, D9,9673-9683[2] McGlynn, I.O., Okin, G.S., 2006; Characterization of shrub
distribution using high spatial resolution remote sensing:
Ecosystem implications for a former Chihuahuan Desert
grassland, Remote Sens. Environ., 101, 554-566[3] Shao, Y., Raupach, M.R., 1992; The overshoot andequilibration of saltation, J. Geophys. Res., 97, D18,20559-20564[4] Owen, P.R., 1964; Saltation of uniform grains in air, J.
Fluid Mech. 20, 2, 225-242[5] MeKenna-Neuman, C., Lancaster, N., Nickling, W.G., 1997;
Relations between dune morphology, air flow, and sediment
flux on reversing dunes, Silver Peak, Nevada, Sedimentology,
44, 1103-1113[6] Iversen J.D., Rasmussen, K.R., 1999; The effect of windspeed and bed slope on sand transport, Sedimentology, 46,
723-731[7] Havstad, K.M., Kustas, W.P., Rango, A., Ritchie, J.C.,
Schumugge, T.J., 2000; Jornada Experimental Range: a uniquearid land location for experiments to validate satellite systems,
Remote Sens. of Environ., 74, 13-25[8] Mikami, M., Yamada, Y., Ishizuka, M., Ishimaru, T., Gao,
W., Zeng, F., 2005; Measurement of saltation process over gobi
and sand dunes in the Taklimakan desert, China, with newly
developed sand particle counter, J. Geophys. Res., 110, D18S02,
doi:10.1029/2004JD004688

! "#

! "#
!$

'

'!$

!$

)

*+,-./01b

2

u* u* − 0.64 2

C = 0.0193
ut = 0.64(m / s)/.
+, '! "% (
$*
$)
(
'
&%
$
#
" $! "% &
!

0.4

ρ

q = 0.0234

ρ
g

(

'

'!$

)*+,-./02

u* u* − 0.82

)

ρ

(

2

q = 0.003 u* u* − 0.662
gd)

C = 0.003
ut = 0.66(m / s)

C = 0.0234
ut = 0.8(m / s )'!$"% ('!$"% (/.
, '! "% (
*+
$)
$(
&'
$% $! "% &
#
"
!

/
.
, '! "% (
*+
$)
$(
&'
$%# $! "% &
"
!

! "#
!$

'

'!$

)*+,-./0

! "#
!$

'

'!$

)*+,-./0

0.18

NDVI

Fig. 6. Scatter plot of deemed u* (u*) and observed sand flux Q (kg/m/s)
for each category. The correlation coefficients in category a, b, c, d,were 0.529, 0.875, 0.703 and 0.798, respectively.

As for the effect of NDVI, in the previous studies it
was pointed out that in the presence of vegetation, u*t
severely increases and the amount of sand flux is limited.
The primary reason for the insensitivity of sand flux to
NDVI in this study can be considered that vegetation at
this study site is dominated by shrubs which can block
sand transportation even without leaves, which makes
sand transportation at this study site insensitive to NDVI.

32

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Permeation of coal tar absorption oil
through ionic liquid supported liquid membrane
Student Number: 07M18059

Name: Yoshiyuki SHIMADASupervisor: Ryuichi EGASHIRA

イ オ ン 液体支持液膜に お け る コ ール タ ール 吸収油の 透過
島田 義之
コ ール タ ール 吸収油− ヘ プ タ ン 系な ど の モ デ ル 混合物を 原料、 イ オ ン 液体（ 1‑ ブ チ ル ‑ 3‑ メ チ ル イ ミ ダ ゾ リ ウ
ム テ ト ラ フ ル オ ロ ほ う 酸塩） 水溶液を 膜液、 及び ト ル エ ン を 溶媒と し て 回分透過を 行っ た 。 い ず れ の 条件に
お い て も 、 吸収油中の 他の 成分に 比較し て 含窒素複素環式化合物が 選択的に 膜液を 透過し 、 こ れ ら の 成分間の 分離が 可能で あ る こ と を 確認し た 。 膜液に イ オ ン 液体を 添加す る こ と に よ り い ず れ の 成分の 透過速度も 劇的に 増加し た 。 さ ら に こ れ ら の 結果に 基づ い て 透過の 速度過程に つ い て 検討し た 。
1. Introduction
Coal tar absorption oil (AO) is one of distillation
fractions of a coal tar (b.p. = 470~550K) which is
obtained coal carbonization. There are many kinds ofchemical compounds contained in it, the nitrogen
heterocyclic compounds such as quinoline (Q),
isoquinoline (IQ), indole (I); the homocyclic compounds
suchas
1-methylnaphthalene(1MN),
2-methylnaphthalene (2MN), etc. The mass fraction ofsome main compounds in AO is shown in Table 1. These
compounds are useful as raw materials for agriculturalchemicals, medicines, perfumes, and many other usefulchemicals. Generally, the current method mainly used toseparate these compounds in AO is carried out in two
steps: first step is a rough separation of AO into several
fractions by acidic and basic extraction; and second step
are further separation and purification of these fractions
into respective products by other methods. The
separation for this first step in the industrial fields has
some drawbacks, e.g., corrosion of the equipments anddifficulties in solvent recovery. To solve these problems,
several alternative methods, such as liquid-liquid
extraction method and O/W/O supported liquid
membrane method (SLM) have been studied[1,2,3].
Ionic liquids (ILs) are emerging as alternative green
solvents to the volatile organic compounds typically usedin separation processes because they are air and water
stable, have a non-measurable vapor pressure. ILs areorganic salts that are liquid close to room temperature,
constituted by an organic cation and either an organic oran inorganic anion.
It has been already reported that the organic nitrogencompounds by supported liquid membranes based onionic liquids, etc. However there is no report of theseparation from an actual multi-component like AO.
In this work, the separation of AO by the ionic liquid
supported liquid membrane was conducted. The
permeation rate process through the ionic liquid
supported liquid membrane was investigated.

2. Experimental
2.1. Preparation of ionic liquid supported liquid
membrane
The structure of the ionic liquid used in this work is
described in Fig. 1 and the properties of it are shown
Table 2. 1-butyl-3-methylimidazolium tetrafluoroborate[bmim+][BF4-] was selected as the membrane liquid dueto the property of solubility[4]. This ionic liquid waspurchased from Wako Chemical Co., Ltd. 3 kinds of themembrane liquid were prepared (CIL=0,0.5,1).
The specifications of the hydrophilic filter paper(cellulose, advantec filter paper no.5B) used as asupporter in the previous work[2] are shown in Table 3.
The filter paper was purchased from Toyo Roshi Kaisha,Ltd.
The filter paper was impregnated with the ionic liquidby dropping carefully. Then, the excess of the ionicliquid from the membrane surface was removed and themass of the liquid membrane was adjusted.
2.2. Batch permeation
Figure 2 illustrates a permeator for the supported liquid
membrane (SLM). The liquid membrane was placed
between two Pyrex glass vessels. The operation
temperaturewas
kept
constantbytheconstant-temperature water passing through the tube
coiled around the permeator. The principal conditions of
permeation runs are shown in Table 4. The 12
permeation runs on 12 conditions were conducted byvarying the following factors; the mass fraction of the

Me

＋
○

N

N

−

BF4

Bt

Fig. 1 Structure of [bmim+][BF4-]
Table 2 Physicality and miscibility of [bmim+][BF4-]
m.p.

density

viscosity (298K)

Td

electrical conductivity[K][kg/m3]
1370

[cP]

[K]

[mS/m]

118.3

573

343

202

solubility with traditional solvents
H2O

MeOH

EtOH

Acetone

THF

HeptaneToluene

○

○

○

○

△

×

×

Table 1 Mass fractions of some main compounds in AO
x Q,0x IQ,0

x I,0

x N,0

x 1MN,0x 2MN,0x BP,0x DBF,0

0.077

0.019

0.036

0.012

0.107

0.263

0.064

0.098

Table 3 Specifications of the filter paper

33

materialmass

cellulose[kg/m2]
0.104

diameter[m]
0.07

thickness[m]
2.2×104

mean pore size[µm]
4real density[kg/m3]1550

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

3.0

6 flat blade paddle

key

yi ×103 [-]

0.04

0.03

0.01

0.08
[m]

supported liquid membrane

CIL = 0n=2

IQ

NSLM = 6000

I

2.0

１ MN
２MN

BP
DBF

1.0

Pyrex glass permeation vessel

i
Q

Hp

Fig. 2 Schematic diagram of experimental apparatus
0

Table 4 Material systems and experimental conditions
Feed

AO (V F =1.2×10-4 m3)
model solution ( x Q,0 =0.08, x 2MN,0 =0.25, x Hp,0 =0.67)

0

4

3.0

AO-heptane solution (v AO,0 =0.5, v Hp,0 =0.5) (V F =1.2×10-4 m3)

CIL = 0.5

toluene (V E =1.2×10-4 m3)

iSolventQ

n=2

Number of supporters

n = 1, 2, 3

IQ

NSLM = 6000

Membrane Liquidwater, ionic liquid([bmim ][BF4 ]) aqueous (C IL =0, 0.5, 1)
N SLM
T
t

key

-

[h-1]
[K]
[h]

yi ×103 [-]Stirring Velocity
Temperature
Time

+

12

6000 or 12000
298
12

8

12

8

12

8

12

8

12

I

2.0

N
１ MN
２MN

BP

1.0

DBF
Hp

membrane liquid (CIL=0, 0.5, 1), the stirring velocity inboth phases (NSLM=6000, 12000), the number of
supporters (n=2, 3). The feed and solvent were poured
into the respective vessels simultaneously and quickly,
and then the agitation of the feed and solvent phases
were started (t=0) to begin the batch permeation run. The
raffinate and extract phases were sampled at specified
operating times, for analysis by a gas chromatograph(GC-2010, Shimadzu Corp.).

0

0

4

t [h]

yi ×103 [-]3.0

3. Results and Discussion
3.1. Composition of extract phase
For all permeation runs, the membrane remained stable
during the operation run because of low solubility in theraffinate and extract phases and the affinity for the
supporter sheet[5]. Figure 3 shows examples of timecourses of mass fractions in the extract phases. The massfraction of each component increased linearly with time.
The permeation rates, especially for I, drasticallyincreased with the addition of the ionic liquid, because
the addition of the ionic liquid widely increased
solubilities of all components. The permeation rates of Q
were largest in the case without the ionic liquid and thoseof I were largest in the case with the ionic liquid. The
overall mass transfer from raffinate to extract phase wasgoverned by the permeation through the membrane,
because the permeation rate was not affected by thestirring velocity and was inversely proportional to thenumber of membrane supporter sheets.
3.2. Yield
The yield of component i, Yi, was defined as,

keyi

CIL = 1

Q

n=2

IQ

NSLM = 6000

I

2.0

N
１ MN
２MN

BP

1.0

DBF
Hp

0

0

4

t [h]

yi ×103 [-]

3.0

key

i

CIL = 1

Q

n=3

IQ

NSLM = 6000

I

2.0

N
１ MN
２MN

BP

1.0

DBF
Hp

0
0

3.0

yi ×103 [-]

E yi
Yi !
R0 x i , 0

8

t [h]

(1)

Figure 4 shows the examples of time courses of YQ.
Under all conditions, Yi of nitrogen heterocyclic
compounds were larger than those of other compounds,
namely, it was confirmed that these compounds wereseparated into each other by the ionic liquid membrane.
The yields of Q were the largest in the case without theionic liquid and those of I were the largest in the casewith the ionic liquid. The yields, especially for I,
drastically increased with the addition of the ionic liquid.

4

key

t [h]

i

CIL = 1

Q

n=2

IQ

NSLM = 12000

I

2.0

N
１ MN
２MN

BP

1.0

0

DBF

0

4

t [h]

Fig.3 Time courses of mass fraction in extract phase34

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

3.3. Overall permeation coefficient
Since the mass fraction of each component increased
linearly with time, namely, it could be assumed that thepermeation rates were proportional to the mass fractionof the feed and the overall permeation coefficients wereconstant in each component, the permeation rate wasexpressed by[2],E0dyi! Px ,i A xi ,0dt

Yi ×103 [-]

6.0

key

i

CIL = 0

Q

n=2

IQ

NSLM = 6000

I

4.0

１ MN
２MN

BP
DBF

2.0

Hp

(2)
0

Figure 5 shows the examples of the effects of CIL on Px,icalculated by Eq. (1). Regardless of the concentration of
the ionic liquid, Px of the nitrogen heterocyclic
compounds was higher than those of other compounds,
which means that the nitrogen heterocyclic compounds
were selectively permeated through the liquid membrane
to extract phase and could be separated from othercompounds. The overall permeation coefficient was
expressed by[2],#Di m i
Px ,i " ML
(3)

0

4

8

12

8

12

8

12

8

12

t [h]

Yi ×101 [-]

1.5

key

i

CIL = 0.5

Q

n=2

IQ

NSLM = 6000

I

1.0

N
１ MN
２MN

BP

0.5

DBF
Hp

n

where ρ ML, Di and mi denote the density of themembrane liquid, diffusivity of component i in the liquid
membrane and distribution coefficient, respectively. The
results that Px,i widely increased with the addition of theionic liquid and Px of I decreased with the increase of CIL
are most affected by mx.
3.4. Separation selectivity
The separation selectivity of the nitrogen heterocyclic
compounds relative to 2MN, i,2MN, was defined as,$ i , 2 MN !

Px , 2 MN

0

4

t [h]
1.5

Yi ×101 [-]

Px ,i

0

key

CIL = 1n=2

IQ

NSLM = 6000

I

1.0

N
１ MN
２MN

BP

0.5

(4)

i
Q

DBF
Hp

Figure 6 shows examples of the effects of CIL on i,2MN.
Whereas i,2MN of Q and IQ decreased with the additionof the ionic liquid into the membrane, I,2MN increased.
The effect of the addition of the ionic liquid on the othercomponents was not observed and i,2MNs of them areabout 1. The number of the supporter sheets had noeffect on i,2MN. The highest I,2MN was about 18 in thecase of CIL=0.5.

0

0

4

t [h]

Yi ×101 [-]1.5

4. Conclusions
The nitrogen heterocyclic compounds were separated
from AO by the ionic liquid supported liquid membrane.
The overall mass transfer from raffinate to extract phase
was governed by the permeation through the membrane.
The permeation rates and the yields of all components
dramatically increased with an addition of the ionicliquid. The yields of nitrogen heterocyclic compounds
were larger than those of other compounds. The
separation selectivities of each nitrogen heterocyclic
compound were affected by the mass fraction of the ionicliquid.

keyi

CIL = 1

Q

n=3

IQ

NSLM = 6000

I

1.0

N
１ MN
２MN

BP

0.5

DBF
Hp

0

0

4

t [h]

Yi ×101 [-]

1.5

key

CIL = 1n=2

IQ

NSLM = 12000

I

1.0

N
１ MN
２MN

BP

0.5

Acknowledgment
The author wish to thank JFE Chemical Co., Ltd. forproviding coal tar absorption oil.

i
Q

0

DBF

0

4

8

12

t [h]

NomenclaturesA= contact area[m2]
CIL = mass fraction of an ionic liquid in membraneliquid[-]Fig.4 Time courses of yields in extract phase35

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)= diffusivity of component i in the liquid
membrane[m2h-1]E= mass of extract phase[kg]= distribution coefficient of component i[-]mi
NSLM = stirring velocity in permeation vessel[h-1]n= number of supporters[-]= overall permeation coefficient based on massPxfraction in raffinate phase[kgh-1m-2]R= mass of raffinate phase[kg]
V= volume[m3]v= volume fraction in feed solution[-]x= mass fraction in raffinate phase[-]y= mass fraction in extract phase[-]<Greek>βi,2MN= separation selectivity of component i relative to
2-methylnaphthalene[-]ρML = density of the membrane liquid[kgm-3]<Subscript>
0= at initial state
1MN = 1-methylnaphthalene
2MN = 2-methylnaphthalene
AO = absorption oilBP= biphenyl
DBF = dibenzofuranE= extraction solventF= feed solutionHp= heptaneI= indole
IQ= isoquinolineN= naphthaleneQ= quinoline
Di

100
key

i

n=2

Q

NSLM = 6000

IQ

Px,i [kgh‑ 1m‑ 2]

I

10‑ 1

N
１ MN

BP
DBF
Hp

10‑ 2

10‑ 3

0

0.5

1

CIL [‑ ]
100

key

i

n=3

Q

NSLM = 6000

IQ

Px,i [kgh‑ 1m‑ 2]

I

10‑ 1

N
１ MN

BP
DBF
Hp

10‑ 2

10‑ 3

0

0.5

1

CIL [‑ ]Fig.5 Effects of IL concentration on the overall permeation
coefficient based upon raffinate concentration
102

key

i

n=2

Q

NSLM = 6000

IQ

βi,2MN [‑ ]I

Literature Cited[1] C. Salim; “Process to Separate Coal Tar Fraction
using Solvent Extraction,” Doctor Thesis, Tokyo
Tech (2005)[2] R. Egashira et al.; “Separation of coal tar fraction by
O/W/O liquid membrane,” 7th World Congress ofChemical Engineering, pp, C23-004, (2005)[3] H. Habaki, et al.; “Separation of Coal Tar Absorption
Oil by Emulsion Liquid Membrane -Effects ofAdditives in Membrane Phase on Permeation
Behavior-,” 8th International Conference on
Separation Science and Technology (ICSST08),
FP-07 (2008)[4] M. Matsumoto et al.; “Selective separation ofaromatic hydrocarbons through supported liquid
membranes based on ionic liquids,” Journal of
Membrane Science, vol.246, 77-81, (2005)[5] Raquel Fortunato et al.; “Supported liquid
membranes using ionic liquids: study of stability andtransport mechanisms,” Journal of Membrane
Science, vol.242, 197-209, (2004)

101

100

0

0.5

1

CIL [‑ ]
102

key

i

n=3

Q

NSLM = 6000

IQ

βi,2MN [‑ ]

I

101

100

0

0.5

1

CIL [‑ ]Fig.6 Effects of IL concentration on separation selectivity ofnitrogen heterocyclic compounds relative to 2MN

36

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

PIV MEASUREMENTS OF ATMOSPHERIC TURBULENCE WITHIN AND ABOVEAN OUTDOOR URBAN SCALE MODEL
Student Number: 07M18065 Name: Hiroshi TAKIMOTO Supervisor: Manabu KANDA!"#$%&'()!"#$%&'() PIV*+ ,$%./0123/45678&'9:;<=>?@A/$%BCDE FGHIJ?&'/
KLMNO/PQ6RSJTHU+VWJ6?LMX8YZ[\J'] ()^H_`/JaH
bcd[)ef(PIV) !"<?gh$%&'iJ/jk@A8=lH&'() m;#Un/
op?ghqr/stuv9wvxyz/$a{8|GH}~1?eXI'/9`;#U
outdoor case. By comparing these results, theinfluences of large scale disturbance and wind direction fluctuation are inspected, which are distinctions
between field and laboratory experiments.
Unfortunately, field PIV is possible only in night
time. Results from this study do not include the mostpart of the effects of solar radiation.

1 Introduction
Exchange processes of heat, pollutants, and water
between the earth's surface and the atmosphere aremainly induced by turbulent motions. Therefore,
understanding of temporal and spatial characteristics
of turbulent motion is a fundamental approach for the
improvements of atmospheric environment in cities.
However, measurements in urban cities are usually
tough. It is very difficult to take spatial measurements
in cities as compared to laboratory or numericalexperiments. Most of the measurements of urban
atmospheric turbulence were performed with single
point sensors such as ultrasonic anemometer [1], [2],[3]. For the measurements of spatial flow
characteristics, a large number of instruments are
required.
The main aim of this study is to investigate theflow inside street canyons in more detail, by applying
Particle Image Velocimetry (PIV) to an outdoor
urban canopy flow. PIV is one of thehighly-advanced measurement techniques that cancapture flow velocity vectors at high spatial
resolution
without
any
disturbancesfrommeasurement instruments. Velocities are obtained
from image analysis of visualized images of flow
fields. This technique has been utilized for turbulencemeasurements, mainly in laboratory experiments [4],[5]. Despite the high efficiency of PIV, applicationsof this method for atmospheric turbulence are stillrare [6]. Flow visualizations in outdoor environments
are difficult, due to highly-fluctuated wind direction
and intensive turbulent diffusivity. This is the first
application of PIV to the flow characteristics over an
outdoor urban-like roughness.
As a counterpart of field experiments, resultsfrom wind tunnel experiments are also presented. The
settings of the experiments were similar to that of the2

Experimental setup

2.1 Field experiment
A PIV measurement was carried out on September
4th, 2008, from 2100 JST to 2200 JST at an outdoor
urban scale model (COSMO, Figure 1). COSMO is a
simplified model city with no human activity and no

Figure 1. Comprehensive Outdoor Scale MOdel.

Figure 2. Setup of field PIV measurement.

37

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Institute of Electric Power Industry. The test section
was 10m-long with a cross-sectional area of 1m x 1m.
As building models, 75mm (=H) Styrofoam cubes
were used. Cubes are regularly aligned with a plan
area density of 0.25 in the same way as COSMO.
Buildings were set in 47 rows in streamwise direction
and 5 lines in spanwise direction. PIV measurement
section was a street canyon between 43rd and 44throws, located at 6.4m (85H) downstream of theentrance of the WT.
The WT PIV system contains a pulsed Nd:YAG
laser (120mJ/pulse), a fog generator, and a CCD
camera (1344 x 1024 pixel2). Double-pulsed images
were taken for 3minutes at a rate of 4Hz, and theinterval of each pair of particle images was set to
2.5msec. Oil-based tracer was released from theentrance of the WT through a perforated PVC pipe.
The size of the target area of PIV measurements was
288mm x 219mm. Roughness Reynolds number
Re * was 68 . This value is much larger than thecritical Reynolds number [7]. If roughness Reynolds
number is larger than a certain critical value( Re * ! 5.4 ), the flow would be independent ofReynolds number, except the vicinity of the wall.

heterogeneity of the surface geometry. It can provide
supplementary information to indoor and real-urban
experiments, under realistic synoptic conditions ofsunshine and wind fluctuations. This scale model
consists of 512 pieces of 1.5m (=H; average buildingheight) concrete cubes. That is a fifth of the scale ofthe typical residential building in Japan [2]. They arealigned in square array on a flat concrete plate with aplan area density of 0.25. The dimensions of theconcrete plate are 100m x 50m, and the longitudinal
axis corresponds with the dominant wind direction of
Asian monsoon. Hereinafter, longitudinal axis andvertical axis of the site are described as x-axis andz-axis. The velocity components of each axis are u
and w , respectively. The target area of the PIV
measurement was a vertical cross section 3m (H) x
2.25m (V) at the center of a street canyon (Figure 2).
The position of this street canyon was 60m (40H)
downstream from the edge of the COSMO.
For flow visualization, continuous-wave
Nd:YAG laser (1000mW) was mounted on a tower ata height of 5m. Tracer particles were oil-based fog
and they were supplied from multiple fog generators.
The tracer was released through perforated PVC
pipes ( 20mm) that were set at the upstream of themeasurement section and the inside of the street
canyon. To make sure that tracer was sufficiently
seeded in highly fluctuating wind direction, PVC
pipes were placed such that they can move
perpendicularly to the x-axis of the site. The outlet
velocity of the tracer was controlled so that it would
not disturb the flow field. For removing the fog heats,aluminum pipes wrapped in wet towels were joined
between PVC pipes and fog generators. As an
imaging device, a 30frame/sec CCD camera (1392 x
1040 pixel2) was used.
For complementary measurement of PIV, twosonic anemometer-thermometers, which can measure
three-dimensional wind velocity and temperaturefluctuation, were set at a height of 1.2H and 2H at thecenter of the street canyon. The sampling frequency
of sonic anemometer was 50Hz.
The measurement time was set to an hour, to ensure
the reliable turbulence statistics under theatmospheric environments. The mean wind speed
U 2 H during the experiment was 0.73m/s at 2H, andthe mean wind direction was inclined at 26.2° to thex-axis of the site. Atmospheric stability was slightly
unstable; the value of z ' / L was -0.15. Roughness
Reynolds
number Re * (! u* z 0 / ) of
thismeasurement was about 8.1"10 2 .

3Results and discussion

3.1 Accuracy of PIV
The accuracy of field PIV dataset was examined incomparison with sonic anemometer dataset. PIV data
was of a grid point nearby the sonic anemometer at
1.2H. The PIV data was not fully continuous but
temporarily lacking mainly due to the highlyfluctuated wind direction along the x-axis of the site.
Thus the comparison was done only for the period ofvalid PIV data. Table 1 shows turbulence statistics
obtained from PIV and sonic anemometermeasurements. Here # u , # w are standard
deviation of u , w , and u* is friction velocity
defined as u* ! ($u' w')1 / 2 . Every statistics wereclosely matching within the error of 10%. Not only
mean statistics, instantaneous values also agree well,indicating a good reliability of PIV measurement.
Table 1. Comparison of turbulence statistics.

2.2 Wind tunnel experiments
A series of wind tunnel experiments were conductedin a wind tunnel (WT) facility of Central Research

38

PIV (m/s)

SONIC (m/s)

PIV/SONIC

u

0.65

0.67

0.96

#u

0.37

0.38

0.97

#w

0.18

0.17

1.06

u*

0.12

0.11

1.03

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

agreements between two graphs suggest that
Reynolds stress is determined by inner-layer
variables and the effect of outer-layer disturbance issmall. However, it is found that oblique winddirection leads to larger Reynolds stress. This is dueto the transition of surface property with winddirection change. Square array becomes like astaggered array when wind direction is inclined.
Staggered array induces higher drag to the flow [8].

3.2 Mean flow characteristics
Mean velocity vector maps of COSMO and WT are
shown in Figure 3. The results are normalized with
U 2 H . Averaging time was 60 minutes for fieldmeasurement, and 3 minutes for WT measurement.
Both airflows have one big circulation in the street
canyons, but their characteristics are not the same.
They have distinct influx at the canopy top andstreamline near the floor.

1.4

(a)

1.2

1.4
1

(a)

z/H

z/H

1.2
0.8

1

0.6

0.8

0.4
Ref. Vector

0.2

0.6

1

0.2

0.4

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

1.2

1.4

1.6

1.8

x/H
Ref. Vector

0.2
1

0.2

1.4

0.4

0.6

0.8

1

1.2

1.4

1.6

(b)

1.8

1.2

x/H

(b)

z/H

1

2.5

0.8
0.6
0.4

2

Ref. Vector

0.2

z/H

1

1.5
0.2

0.4

0.6

0.8

1

x/H

Figure 4. Wind vector maps filtered by wind direction.
(a)" 5! , (b) 15! " " 45! .

1

0.5

Ref. Vector
1

1.4
0
0.5

1

1.5

2

2.5

(a)

3

x/H

Figure 3. Mean velocity vector maps.
(a) COSMO, (b) WT.

2.5
1.2

2
1.5

1

z/H

1
0.5

0.8

0
0.6

One good reason of these differences is theexistence of fluctuation in wind direction. Figure 4
are the conditionally averaged wind vector maps
when instantaneous wind direction
at 2H is (a)" 5! , (b) 15! " " 45! .
is the angle between
wind direction and x-axis of the site. Both data usedthreshold of u 2 H # 0.5m / s . When wind is flowing
perpendicularly to the street canyon, lower part of thecanyon flow became near-parallel to the floor. In
contrast, inclined wind direction makes stronger
circulation and stronger influx at the canopy top. That
is why mean flow is different between COSMO and
WT. Field measurement had inclination and larger
fluctuation in wind direction, compared to WT. For
further understanding of these differences,3-dimensionality is needed to be taken into account.
Figure 5 are the contours of Reynolds stressnormalized with inner-layer scale u*2 . Good

-0.5
-1

0.4

-1.5

Wind

0.2

-2
-2.5

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

x/H

(b)

2.5

2.5

2
1.5

2

1
0.5

z/H

1.5

0
-0.5

1

-1
0.5

-1.5

Wind

-2
-2.5

0
0.5

1

1.5

2

2.5

3

x/H

Figure 5. Contour maps of Reynolds stress u ' w' / u*2 .
(a) COSMO, (b) WT.

39

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

for the flow in field urban canopy was constructed.
Using this system, atmospheric turbulence flow overurban-like roughness was observed. We exhibited theflow structure minutely, and the results from field
experiment were compared with that of wind tunnel
experiments. The investigation revealed following
results.

3.3 Instantaneous flow structures
While one big circulation appeared in the mean flow,
snapshots of each moment exhibit various flow
structures. Especially, strong upward motions fromthe bottom of street canyon were most interesting
phenomena (Figure 6). Intensities of these events
varied widely, but visual inspection indicates thatgenerally they have duration time of 2 to 5 seconds,
and interval of 1 to 5 minutes. Similar flushing eventswere also observed in WT experiments. Although it isdifficult to identify the flushing events due to its
diversified intensity, one possible definition is "morethan 60 % of vectors satisfy the condition of
w | u | inside the street canyon". This condition
still contains arbitrariness, but it detected the flushing
events well from WT result. It revealed that the
duration time of upward motions in WT were lessthan quarter of a second, and the frequency was oncein 10 to 20 seconds. Considering the structures andthe normalized cycles of the phenomena in COSMO
and WT, these events seem to be generated by samemechanism.
Most likely cause of flushing events wasconsidered to be Turbulent Organized Structure(TOS) developed in urban boundary-layer [3]. TOS in
urban boundary-layer is characterized by its streaky
pattern of low-momentum region. Such coherent
structures account for most part of momentum
transport. From visual inspection of WT results, wefound strong correlation between flushing events andlarge scale low-momentum region. More than 80% offlushing events were occurred under the existence ofsuch large scale turbulent structures.

1) Flow structure inside the urban canopy was
successfully obtained with high spatial resolution.
The quality of PIV dataset was good in comparison
with the dataset from sonic anemometer.
2) Mean flow structures and Reynolds stresses were
found to be similar between field and wind tunnel,
although they have a little bit different characteristics.
Inclination and fluctuation of wind direction are
significant factors for these differences.
3) Strong intermittent upward motions from thebottom of street canyons were observed, which are
expected to make a contribution to the ventilation in
urban canopies. Our investigation suggested that the
turbulent organized structure developed in urban
boundary-layer is strongly related to the occurrenceof the upward motion.

References[1] Roth, M.: 2000, 'Review of atmospheric turbulence overcities', Quart. J. Roy. Meteorol. Soc., 126, 941-990.
[2] Moriwaki, R., Kanda, M.: 2006, 'Flux-gradient profiles
for momentum and heat over an urban surface', Theor.
Appl. Climatol., 84, 127-135.
[3] Inagaki, A.: 2008, 'Atmospheric turbulence over anarray of massive cubes', Ph.D. Dissertation, Tokyo
Institute of Technology.

1.4[4] Adrian, R.J., Meinhart, C.D., Tomkins, C.D.: 2000,'Vortex organization in the outer region of the turbulent
boundary layer', J. Fluid Mech., 422, 1-54.

1.2

z/H

1

[5] Liu, H., Liang, B., Zhu, F., Zhang, B., Sang, J.: 2003, 'A
laboratory model for the flow in urban street canyons
induced by bottom heating', Advances in Atmos. Sci.,
20, 554-564.

0.8
0.6
0.4

[6] Zhu, W., van Hout, R., Luznik, L., Kang, H.S.: 2006, 'A
comparison of PIV measurements of canopy
turbulence perfomed in the field and in a wind tunnel
model', Exp. in Fluids, 41, 309-318.

Ref. Vector

0.2
1

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

[7] Uehara, K., Wakamatsu, S., Ooka, R.: 2003, 'Studies on
critical Reynolds number indices for wind-tunnel
experiments on flow within urban areas',
Boundary-layer meteorol., 107, 353-370.

x/H

Figure 6. Instantaneous flow structure observed in
COSMO.

[8] Kanda, M.: 2006, 'Large-eddy simulations on the effectsof surface geometry of building arrays on turbulent
organized structures', Boundary-layer Meteorol., 118,
151-168.

4 Conclusions
In this study, a system of particle image velocimetry40Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Mechanism of ammonia nitrogen uptake by sterile Ulva sp. and its application towater quality control for intensive shrimp culture pond in developing country
Student Number: 07M18071

Name: Shin TAJIRI

Supervisor: Ryuichi EGASHIRA

不稔性ア オサによ る ア ン モニア 窒素摂取の機構と開発途上国型エビ 養殖池の水質制御に対する 適用
田尻

新

ま ず、 ア オサのキ ャ ラ ク タ リ ゼーシ ョ ン （ 炭素、 水素、 窒素、 ク ロ ロ フ ィ ル組成、 等の測定）、 様々な 条件における 培養液−藻体内部間のア ン モニ ア 窒素の分配平衡、 ア オサ表面の膜における ア ン モニ ア 窒素の透過速度、 およ びア オサ内部における ア ン モニ ア 窒素同化速度の実測、 等を 行っ た。 昼間を 想定し た 条件において透過速度は内部濃度基準の総括濃度差に比例し 、 昼間の条件の場合に比較し て 夜間の条件における 透過速度は著し く 低かっ た 。 ア ン モニ ア 窒素同化速度と 摂取速度はほぼ同等であ っ た。 こ れら の実験結果およ び既往のエビ 養殖池における 窒素循環モデルを 用いて ア オサによ る 水質制御計算を 行っ た 。 養殖水中のア ン モニ ア
窒素濃度を 低く 抑え る こ と ができ 、 本法を 簡便な 水質制御法と し て提案し た 。
Algae were cultivated for 2h in artificial seawatercontaining 1mM methionine sulfoximine, which inhibits
the assimilation of ammonia-N, before uptake runs.
Concentrated ammonia-N solution added to culture
medium at the beginning of uptake run and measured
ammonia-N concentration of culture medium.
Table 2.2.2-1 shows the principal conditions of uptake
runs. Some conditions were assumed daytime, others
were nighttime. In all runs, the algae without ammonia-N
assimilation ability were used to know the distribution
equilibrium of ammonia-N between the culture medium
and the ammonia-N pool in alga. After equilibration,ammonia-N excretions were also conducted byexchanging the medium with ammonia-N free seawater.
2.2.3 Assimilation of ammonia-nitrogen in alga
Concentrated ammonia-N solution added to culture
medium at the beginning of uptake run and measured
ammonia-N concentration of culture medium. The
ammonia-N concentration in alga was measured byadding carbonyl cyanide m-chlorophenilhydrazone into
the medium.
2.3 Results and discussion
2.3.1 Characterization of alga
Table 2.3.1-1 shows of mass of Carbon, Hydrogen, andNitrogen per unit dry biomass. Wt% of CHN decreased
with increase of stock cultivation time. This isconsidered those nutrients, which were pooled in the sea,
were exhausted for growth.
Table2.3.1-2 shows amount of chlorophyll-a,b,c per unit
dry biomass. There is not great differences of chlorophyll
concentrations in each sample of alga.

1 Introduction
Since the 1990s the shrimp industry, which has givenhigh profit and foreign exchange to developing countries,
has suffered many disease outbreaks[1]. Some shrimp
farmers introduced none or quite small water exchange
culture system to avoiding the infection of disease.
However, employing the system began to cause theserious water deterioration and the water quality control
becamemore
important.
Ammonia-nitrogen(ammonia-N,AN) excreted by shrimp respiration andfrom decomposition of bottom sediment is main cause ofwater deterioration. Ammonia-N is toxic to fishes andcrustaceans[2] and even if the concentration is low, thegrowth of shrimp is inhibited[3]. Most of nitrogencomponent in the shrimp feed supplied into pond is
finally discharged into the pond as the form ofammonia-N through excretion by shrimp anddecomposition of accumulated sediment.
In this study, we investigated mechanism of ammonia
nitrogen uptake by sterile Ulva sp. and simulated water
quality control in basis of nitrogen balance andammonia-N uptake mechanism of alga.
2 Mechanism of ammonia nitrogen uptake by sterile
Ulva sp.
2.1 Materials
Sterile Ulva sp. collected from April to November 2008
at Kanazawa Bay (Yokohama, Japan 35°20’32N,
139°38’32E). Commercial sea salt was used to prepare
artificial seawater (salinity: 30‰).
2.2 Experimental
2.2.1 Characterization of alga
A vessel made of glass of which capacity 5×10-2m3 and used
to store algae. Light source was 400W metal halide lamp.
Elemental analysis was carried out by CHN corder MT-6.
Chlorophyll concentration was determined by Scor/Unesco
method.
2.2.2 Distribution of ammonia-nitrogen between
culture medium and nitrogen pool in alga andpermeation through surface film of algae

Table 2.3 1-1 Results of elemental analysis
Stock
Biomass
cultivation
H
×103
time
[day]
[kgDM] [wt-%]
00.05815.30
00.02815.34
00.06465.25
50.05894.31
50.02064.78
50.0229
4.66
Sampling date 2008, Oct, 17th

41

C

N

[wt-%]
28.29
29.39
27.80
22.09
24.97
24.42

[wt-%]
3.26
3.50
3.13
2.35
2.55
2.39

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

relation between mean ammonia-N concentration in alga
and ammonia-N assimilation rate. Assimilation rateincreased with increase of ammonia-N concentration inalga at first 1 hour. However, assimilation rates rapidly
decreased with time. This decrease is provably due toexhaustion of other nutrients such as carbon.

C Chｌ-c× 103[kg-Chl kgDM-1] [kg-Chl kgDM-1] [kg-Chl kgDM-1]
1.5
0.6
0.6
2.1
1.0
1.0
2.7
1.2
1.1
2.2
0.9
0.7
2.3
1.0
0.8
2.0
0.9
0.8

2
-3
3

2.3.2 Distribution of ammonia-nitrogen between
culture medium and nitrogen pool in alga andpermeation through surface film of algae
Figure 2.3.2-1 shows the equilibrium relation between
ammonia-N concentrations in culture medium and in theammonia-N pool of alga. In condition assumed daytime,equilibrium ammonia-N concentrations in alga after
uptake were higher than those after excretion.
Equilibrium ammonia-N concentrations of internal algae
in condition assumed daytime were higher than thatconcentration in condition assumed nighttime. These
differences of equilibrium relation were considered to bechemical potential deference between external andinternal algae.
Figure 2.3.2-2 shows the relation between ammonia-N
uptake rate and concentration difference C´*N C´N. C´*N
was estimated by the equilibrium relationship after
uptake given in Fig.2.3.2-1. Mean gradient of collinear
approximations not through origin was 0.73 h-1-3-3

Culture density of alga ! U [kgDM m ]Cultivation time [h]-1Light intensity, PPF [µmol s m ]Temperature [K]103 [kg-N h-1 kgDM-1]
u,TAN ×C'TAN×103 [kg-N kgDM-1 ]6

4
2● After uptake,Daytime○ After excretion, Daytime◆ After uptake, Nightime

0
1

2

3 [kg-N h-1 kgDM -1]

10
a,TAN×
u,TAN,

6(C'*TAN -C'TAN)×103 [kg-N kgDM -1 ]Fig.2.3.2-1 Equilibrium between
AN concentrations in culture
medium and in alga

u,TAN

dt

dt

U

2

3

0.2

4

0

1

2

2

3

4

t [h]

2.5
u,TAN

a,TAN

●
●
○

▲
▲
△

Fig.2.3.3-2 Time courses of AN
concentration in alga

t 1~t 2
0~1
1~2
2~4

1.5

Table 2.3.3-1 Experimental conditio-3

1

C TAN,0 [kg-N m ]0.25~2.00

-3

0.5
0
0.5

! U [kgDM m ]0.41

PPF [µmol s-1 m-2]
Temperature [K]

1800
303

1

3 Water quality control for shrimp pond
3.1 Nitrogen balance in shrimp pond
Figure3.1-1 shows a concept of nitrogen dynamics
model.
Nitrogen as the form of the shrimp feed are supplied into
pond. Much of feed is eaten by shrimp(1), and a portionof feed is uneaten(2). Shrimp excretes ammonia-N
through
respiration
(4)
and
other
nitrogenmetabolite(feces, shed shell etc.)(3). Ammonia-N also
generate from sediment decomposition(7). Ammonia-Nin water column was removed by algal uptake(5), waterexchange(8), and other removal process(9). Algae areremoved from pond(6) as one of final form of nitrogen.

Fig.2.3.2-2 Relation between A
uptake rate and overall concentratio
difference, C´*TAN C´TAN

2.3.3 Assimilation of ammonia-nitrogen in alga
The material balance in a unit volume of the culture
medium is given by,
dC
dC #
(1,2)
!
$ % TAN $ ! TAN " !
U

0.4

Fig.2.3.3-3 Relation between mean
AN concentration in alga and AN
assimilation rate

2

4

0.6

C'TAN×103 [kg-N kgDM-1]

0.25~2.00

2

C TAN,0
2.00
1.00
0.50
0.25

0
1

0

4

0

CTAN×103 [kg-N m-3]

0.5

Fig.2.3.3-1 Time courses of AN
concentration in culture medium

0
0

0.8

t [h]

6

8

1

0

0.07~0.66
7~12
Daytime Nighttime
1800
5>
303
298

-2

1.5

○
◇
□
△

1

0

Table 2.2.2-1 Experimental condition
Initial concentration of culture medium C TAN,0 [kg-N m ]1.2

C TAN,0○ 2.00◇ 1.00□ 0.50△ 0.25! U= 0.41-1

C Chｌ-b× 103

C TAN ×10 [kg-N m ][kgDM]
0.064
0.053
0.044
0.048
0.033
0.043

C Chｌ-a× 103

3

Biomass×103

C' TAN ×10 [kg-N kgDM ]Table2.3.1-2 Chlorophyll concentration of alga

Feed

(6)

(2)

Ulva
(1)

a,TAN

Shrimpwhere u,TAN is ammonia-N uptake rate by alga, C´TAN is
the ammonia-N concentration in alga, and a,TAN is theassimilation rate. Integration of this equation from time t1
to t2 leads to,##
C TAN,1 " !CTAN,1$ CTAN,2 " !CTAN,2" ! a,TAN &t 2 % t1 ' (3)

(5)
(4)

(9)

Ammonia-N(3)(7)
Sediment

where a,TAN is mean assimilation rate between t1 and t2.
Figures 2.3.3-1 and 2.3.3-2 show the time courses ofammonia-N concentration in medium and those in algawith assimilation, respectively. Figure 2.3.3-3 shows

Fig.3.1-1 Concept of nitrogen dynamics model

42

(8)

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

k ! k U " kother

3.2 Basic equation and calculation
Material balance;
The material balance in a unit volume of pond water isgiven by,dCTAN
(4)
! rtotal,TAN rtotal,remove
dt
where rtotal,TAN is generation rate of ammonia-N,
rtotal,remove is removal rate of ammonia-N.
Ammonia-N generation
Generation rate of ammonia-N is given by,(5)
rtotal,TAN ! re,TAN " rsed,TAN

where kU and kother is light extinction coefficient of alga
and pond water, respectively. kU is determined bychlorophyll concentration in alga and $U and given by,(14)
k U ! kChl $ U CChl
where kChl is light extinction coefficient per unit mass ofchlorophyll-a, CChl is chlorophyll-a amount per unit dry
biomass of alga. "u,TAN is, from relation between "u,TAN
and overall concentration difference, given by
.*
.
(15)
CTAN
% u,TAN ! Pu CTAN

,

.
dCTAN
. % a,TAN RBiomass/N " % u,TAN % a,TAN (16)
! CTANdt,

where qTAN is ratio of ammonia-N from shrimp
respiration to total nitrogen metabolite. rmtb,N is excretion
rate of nitrogen metabolite from shrimp per unit volumeof pond water and given by,(7)
rmtb,N ! amtb,N $ s M s#-

where RBiomass/N is ratio of dry biomass to nitrogen in dry
biomass. As with "u,TAN, "a,TAN is given by% a,TANqlight% a,TAN(17)

From Fig. 4-3, assimilation rate is almost the same as
uptake rate and that can be written by,! a,TAN ! u,TAN (when ! a,TAN,MAX " ! u,TAN ) (18)where amtb,N is nitrogen metabolite from shrimp per unit
shrimp mass. s is culture density of shrimp. Ms isaverage shrimp mass and estimated from growth model.
! is allometric scaling of shrimp metabolism.
On the other hand, rsed,TAN is given by,(8)
rsed,TAN ! rr M sed,N! a,TAN! a,TAN,MAX (when ! a,TAN,MAX # ! u,TAN )(19)

where a,TAN,MAX is maximum assimilation rate ofammonia-N.
Calculation
Parameters of equations in chapter3.2 were estimatedfrom chapter2 and cited previous study[4][5].
Table3.2-1 shows the parameters of fixed value in all
calculation. Penaeus monodon was selected as culture
target. Cultivation time was 120days. It was assumed
nitrogen input was only feed and was assumed 20% of
total nitrogen input was assimilated by shrimp and 10%of that was uneaten by shrimp.
Table3.2-2 shows the parameters that were varied ineach calculation run. (1) was calculated as standard
condition, (2) as prediction of effect of culture density of
shrimp, (3) effect of saturation ratio of photosynthesis,(4) effect of water exchange and other removal process,(5) effect of ratio of nitrogen metabolite throughrespiration to total nitrogen metabolite, (6) effect ofwater turbidity, and (7)effect of algal harvest.

where rr is rate constant of decomposition. Msed,N isamount of nitrogen contained in sediment per unit
volume of pond water. Msed,N include the sediment
derived from uneaten feed and nitrogen metabolite fromshrimp.
Ammonia-N removal
Removal rate of ammonia-N is given by,(9)

Where "u,TAN is average uptake rate, f and o is rate
constants of water exchange and other removal process,respectively. In the case that saturation ratio ofphotosynthesis affect uptake performance, "u,TAN is givenby,% u,TAN ! qlight% u,TAN-

where Pu is overall mass transfer coefficient. Change rateof ammonia-N concentration in alga can be obtain frommaterial balance and given by below equation including
growth dilution of ammonia-N in alga pool,where re,TAN is rate of ammonia-N excreted by shrimp
respiration, rsed,TAN is rate of ammonia-N generated by
sediment decomposition.
re,TAN is given by,(6)
re,TAN ! qTAN rmtb,Nrtotal,remove ! $ U % u,TAN " fCTAN " oCTAN

(13)

(10)

where qlight is average saturation ratio of photosynthesis(qlight equaled 1 in case of not taking the effect ofsaturation ratio of photosynthesis on uptake into
account.) Relation between saturation ratio ofphotosynthesis qlight and light intensity is approximatedfollowing equation,

Table3.2-1 Parameters of fixed value
a mtb,N [kg-N h-1 kg-shrimp]

0.0000274

C Chl [kg-chl kgDM-1]

0.002131

P U [h-1]-1-1a,TAN,MAX [kg-N h kgDM ]

+
p (
I
(11)
&& !
qlight )) !
* pMAX ' I " K light
where I is light intensity at specific depth from pond
surface. Klight is constant depending on temperature. I canbe described by Beer-Lambert law as,(12)
I ! I 0 exp, kz where I0 is light intensity of pond surface, k is overall
light extinction coefficient, z is distance from pond
surface. k is given by,

43

0.73070.002042

R Biomass/N [kgDM kg-N-1]
ｈ [m]k Chl [kg-Chl-1 m-1]

30.40
1.0
11800

I 0,day [µmol s-1 m-2]

1800

I 0,night [µmol s-1 m-2]
T day [K]T night [K]! [-]0
303.15298.150.75

r r [h-1]

0.0025

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Table3.2-2 Calculatiuon conditions
u,0

q light

s,0
-3

f

o ×10

3

q TAN

[kgDM m-3] [m ][-] [h-1] [h-1]
0~2.0
40
1
0
0
0~2.0
40~120 10
00~2.0
40~120 ※10
00~2.0
40~120 1※2 8.330~2.0
40~120 1
0
0
0~2.0
40
0
0
※1
0~2.0
40
1
0
0

(1)
(2)
(3)
(4)
(5)
(6)
(7)

k otherrange of culture density may inhibit the shrimp culture
management.
4 Conclusion
We measured the ammonia-N distribution equilibrium
relation between culture medium and in alga,ammonia-N permeation rate, and assimilation rate.
Secondly, we carried out calculation of water quality
based on these data.
The water quality control method by using sterile ulva
can remove ammonia-N in shrimp pond more effectively
NomenclatureHu[-][m-1] [kgDM h-1m-3]
※3
1
2.5
1
2.5
※3
※3
1
2.5
1
2.5
※3
※3
0~1
2.5
1 1.0~4.0
※3
1
2.5
0

※1, qlight was calculated by equation(10)~(14)※2,Water exchange was carried out at night; Change rate is 0.8%, 8%,12%, and 16% day-1 in 0~30, 31~60, 61~90 and 91~120 day,respectively※3, Algae were harvested to keep culture density of algaamtb,N Nitrogen metabolite excretion rate [kg-N h-1 kg-shrimp-1]!
Allometric scaling of metabolism [-]CTAN
Ammonia-N concentration [kg-N·m-3]
CTAN,night,ave Average ammonia-N concentration in nighttime [kg-N·m-3]
CTAN,night,MAX Maximum value of average ammonia-N concentration innighttime [kg-N·m-3]
C´TAN Ammonia-N concentration in alga[kg-N·kgDM-1]
C´*TAN Equilibrium ammonia-N concentration in alga [kg-N·kgDM-1]
CChl-a Chlorophyll concentration in alga [kg-Chl-a kgDM-1]
d
Cultivation time[day]fwater exchange rate [h-1]
HU
Harvest rate of algae[kgDM h-1 m-3]hPond depth[m]I
Light intensity [µmol s-1 m-2]kOverall light extinction coefficient [m-1]kChl
Light extinction coefficient of chlorophyll [m2 kg-Chl-a]kotherLight extinction coefficient of pond water [m-1]kU
Light extinction coefficient of alga [m-1]
KlightConstant of apporoximation [µmol s-1 m-2]
Ms
Shrimp mass [kg-shrimp]
Msed,N Nitrogen in sediment per unit volume of pond water[kg-N m-3]oOverall Rate constant of other ammonia-N removal process [h-1]p
Photosynthesis rate [µl-O2 cm-2 h-1]
pMAX
Saturated photosynthesis rate [µl-O2 cm-2 h-1]
PUOverall mass transfer coefficient [h-1]qlightSaturation ratio of photosynthesis [-]qTAN
Ratio of nitrogen metabolite through respiration to total
nitrogen metabolite [-]RBiomass/N Ratio of dry biomass to nitrogen in algare,TAN Excretion rate of ammonia-N by shrimp respiration[kg-N h-1 m-3]
rmtb,N
Nitrogen metabolite excretion rate by shrimp [kg-N h-1 m-3]
rr
Rate constant of sediment decomposition [h-1]rsed,TAN Ammonia-N generation rate from sediment [kg-N h-1 m-3]
rtotal,TAN Total rate of ammonia-N generation [kg-N h-1 m-3]
r total,remove Removal rate of ammonia-N [kg-N h-1 m-3]t
Cultivation time [h]TdayTemperature at daytime [K]TnightTemperature at nighttime [K]Assimilation rate of ammonia-N [kg-N·kgDM-1·h-1]
a,TAN
Maximum assimilation rate of ammonia-N
a,TAN,MAX[kg-N·kgDM-1·h-1]
Uptake/permeation rate of ammonia-N [kg-N·kgDM-1·h-1]u,TAN!s
Culture density of shrimp [m-3]!U
Culture density of algae[kgDM·m-3]<Subscript>
a = assimilation ,Chl = chlorophyll, f = feed, mtb = metabolism,
N = nitrogen, s = shrimp, TAN = Total Ammonia-Nitrogen, u = uptake,U = Ulva, 0 = initial or pond surface, ¯ = average
Literature Cited[1]Primavera, J.H.; “Tropical Shrimp Farming and Its Sustainability,”
Tropical Mariculture, S. S. De Silva ed., pp. 257-289, Academic
Press, San Diego, U.S.A. (1998)[2]Haywood, G.P.; “Ammonia Toxicity in Teleost Fishes: A Review,”
Can. Tech. Rep. Fish Aquat. Sci., 1177, 1-35 (1983)[3]Chen, J. C. and C. C. Tu; “Influence of Ammonia on Growth of
Penaeus monodon Fabricius Post–Larvae,” Aquaculture andFisheries Management, 22, 457-462 (1991)[4]Burford, M. A., Lorenzen, K., “Modeling nitrogen dynamics inintensive shrimp ponds: the role of sediment remineralization,”Aquaculture, 229, 129-145(2004)[5]Lorenzen, K., Struve, J., Cowan, V.J., “Impact of farming intensity
and water management on nitrogen dynamics in intensive pond
culture; a math mathematical model applied to Thai commercial
shrimp farms,” Aquaculture Research, 28, 493-507(1997)

3.3 Results and Discussion
Figure3.3-1 shows effect of culture density of
shrimp(calculation run(1)(2)). Ammonia-N concentration
increase with time, also increase with increase of culture
density of shrimp.
Figure3.3-2 shows relation between initial culture
density of algae and limit culture density of shrimp(calculation run(2)(3)). Limit culture density of shrimp,
which was defined that maximum value of averageammonia-N concentration in nighttime does not exceed
0.001kg-N m-3, slightly decreased with degree of light
limitation qlight.
increased by water exchange and decreased by light
limitation.
Figure3.3-3 shows relation between ratio of nitrogenmetabolite through respiration to total nitrogenmetabolite qTAN and limit of culture density of shrimp.
Limit culture density of shrimp was increase withincrease of qTAN.
Figure3.3-4 shows relation between light extinction
coefficient of pond water and limit of culture density of
shrimp.
In the case that harvest of algae was not conducted, final
culture density of algae exceeded 2.0 kgDM m-3. This102

-3
U,0=1.0 kgDM m

1.2
1s,0=120 m

-3

0.8
0.6

-3
s,0=80 m

0.4
0.2

s,0=40 m

-3

0
0

30

60

90

Maximum limit of !ｓ ,0 [m-3]3-3

C TAN,night,ave×10 [kg-N m ]

1.4

101

Light limitation q ligh t━
Fixed(=1)━
Calculated

100

120

0

d [day]Fig.3.3-1 Time courses of
averageammonia-N
concentration at nighttime oneach day

0.1

0.15

0.2

Fig.3.3-2
Relation
betweeninitial culture density of alga andlimit of culture density of shrimp
0.15-3s,0=40 m-3U,0 [kgDM m ]-3U,0 [kgDM m ]

0.055

0.05

!U,0 [kg-DM m-3]

0.05

0.045

-3
s,0=40 m

0.1

0.05

0
0

0.5

1

q TAN [-]

Fig.3.3-3 Relation between ratioof nitrogen metabolite throughrespiration to total nitrogenmetabolite and minimum limit of

1

2

3

4

-1

k other [m ]Fig.3.3-4
Relationwater
turbidity and minimum limit ofculture density of alga

44Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

METHOD OF PROBABILITY DENSITY ESTIMATIONFOR MAHALANOBIS METRIC IN VECTOR SPACE
Student Number:07M18088 Name:Toshinori Nakamoto Supervisor:Yukihiko Yamashita
パタ ーン 認識や統計的解析において ， 扱う データ に相関が存在する こ と が多いが , 扱う データ の分布が非正規性を持つ場合， Mahalanobis 距離では正確な 評価は困難であ る 。 そのため， ベク ト ル空間上の Mahalanobis 計量の研究が行われて いる が ， 標本点から Mahalanobis 計量を 求める 手法は存在し て いな い。 本研究では， Mahalanobis 計量を 求
める ために適し た 確率密度関数を 与え る ， ノ ン パラ メ ト リ ッ ク な 密度関数推定法を 提案する 。 さ ら に ， 数値計算に
よ り ， 標本点から 密度関数を 推定し ， それを も と に Mahalanobis 計量方程式を 解く 実験を 行い， 提案手法の有効性を確認する 。

1

Introduction

space, the von Mises-Fisher distribution on a hyper-sphericalsurface, and an distribution proportional to e−κ cosh θ in the
Lobachevsky space. The Mahalanobis metric equation was
defined by extending the linear transformation to a diffeomorphism and using the equation of GLII [5]. It is remarkable that its differential equation does not depend on the coordinate system or the original metric. Furthermore, the diffeomorphism will disappear in it.
In this paper, a p.d.f. is estimated from sample points by
maximum likelihood approach, and we conduct an experiment to solve the mahalanobis metric equation.

The Mahalanobis distance [2], which is a distance normalized by a variance-covariance matrix of a distribution, is
widely used for pattern recognition and data analysis. It enables to improve the accuracy of recognition comparing to
the Euclidean distance.
For example, if two vectors differ in the direction in which
the variance is small, the difference is small in terms of Euclidean distance but may be large from the viewpoint of probability (Fig.1 (a))
When the distribution of patterns is normal, the normalization by the variance-covariance matrix is reasonable. However, suppose that the contour lines of a probability distribution function (p.d.f.), which is not normal, is given as in Fig.1(b). It is natural to evaluate the distance not along a straightline but along a curve. In order to realize such a distance, theMahalanobis metric was proposed.

2 Mahaklanobis metric equation
A normal distribution is characterized by the equality between the sample mean and the maximum likelihood estimator (C.F.Guass), by isotropic independence (Maxwell), by
the entropy, or by the central limit theorem [1], [3]. Let X1
and X2 be random variables and (Y1 , Y2 ) be the rotation of(X1 , X2 ) by an angle θ (, 0, ±π/2, ±2π/2, ±3π/2, · · · ). If X1
and X2 are independent and Y1 and Y2 are also, then the distribution of X1 and X2 should be normal and its variancecovariance matrix is aI (a > 0). By using this characterization, Maxwell provided the velocity distribution of the ideal
gas.
Here, we consider an n-dimensional Riemannian manifold[4]. We use the summation rule in the notation of equations.
For a small displacement dxµ in a coordinate system {xµ },its distance is given by (ds)2 = gµν dxµ dxν . gµν is called themetric tensor. Its inverse tensor is denoted by gµν . Let g be
the determinant of gµν .
The covariant differential for an antivariant vector field X µ
is given by ∇ν X µ = ∂ν X µ + Γµνβ X β , where ∂µ = ∂x∂µ and Γµνβ
is the connection [4]. The Levi-Chivita connection can bederived from gµν as

Figure 1: Mahalanobis metricIn the n-dimensional Euclidean space, the normal distribution with an average µ and a variance-covariance matrix Σ
is expressed by the p.d.f.:p(x) = √1
exp(−hΣ−1 (x − µ), (x − µ)i/2)(2π)n det(Σ)(1)

where h·, ·i denotes the inner product and Σ is assumed to be
regular. Let I be the identify matrix. When x is mapped toy by a linear transformation y = Σ(−1/2) x, p is transformed
to the p.d.f. of a normal distribution of which variancecovariance matrix is I. The inner product that expresses the
Mahalanobis distance is given as the pull back of the innerproduct as hy, y′ i = hΣ−1 x, x′ i.
The equation of geometrically local isotropic independence(GLII) was proposed to define a normal distribution ina manifold [5]. It provides an normal distribution of which
variance-covariance matrix is aI (a > 0) in the EuclideanΓαµν =1 αβg (∂µ gβν + ∂ν gµβ − ∂β gµν ).
2(2)In an Euclidean space, if a p.d.f. p(x1 , x2 ) satisfies∂1 ∂2 log p(x1 , x2 ) = 0(3)

it is clear that x1 and x2 are independent (p(x1 , x2 ) =p1 (x1 )p2 (x2 )). Based on the characterization by Maxwell
and eq(3), the equation of GLII for a normal distribution in a
manifold is defined.
1
45

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

For a p.d.f. p in a manifold M, suppose that a diffeomorphism from M to a manifold M ′ transforms p to a solutionof the equation of GLII in M ′ . Then, the Mahalanobis metricg̃µν in M is defined by the pull back of the metric in M ′ andis given by the Mahalanobis metric equation:!
˜∇µ ∇˜ ν log p − 1 log g̃ − f g̃µν = 0(4)2

respectively. We define the 4(N1 −2)(N2 −2)×3(N1 −4)(N2 −4)-matrix bywhere g̃ = det g̃µν and ∇˜ µ is the covariant differential derived
from g̃µν . A scalar f is determined according to the topologyof M. When M is an n-dimensional real space (but not an
Euclidean space), we can let f = −1. Furthermore, since weassume that M is a vector space, we add the condition R =gαβ Rγαγβ = 0, where Rκλµν = ∂µ Γκνλ − ∂ν Γκµλ + Γηνλ Γκµη + Γηµλ Γκνη .

and the 4(N1 − 2)(N2 − 2)-dimensional vector by3

 ∂F11 ∂g11
 ∂F12 ∂g11D =  ∂F
 ∂g 22 ∂R11
∂g11

F

=

∂F11
∂g12
∂F12
∂g12
∂F22
∂g12
∂R
∂g12

∂F11 
∂g22 

∂F12 
∂g22 
∂F22 
∂g22 

∂R 
∂g22

(9)

(F11 (r1 ), F11 (r2 ), · · · , F11 (r(N1 −2)(N2−2) ),F12 (r1 ), F12 (r2 ), · · · , F12 (r(N1 −2)(N2−2) ),F22 (r1 ), F22 (r2 ), · · · , F22 (r(N1 −2)(N2−2) ),R(r1 ), R(r2 ), · · · , R(r(N1 −2)(N2−2) ))T .

Furthermore, we define the 3(N1 − 4)(N2 − 4)-dimensional

Mahalanobis metric by Newton vector byRaphson method
G = (g11 (s1 ), g11 (s2 ), · · · , g11 (r(N −4)(N2−4) ),1

g12 (s1 ), g12 (s2 ), · · · , g12 (r(N1 −4)(N2−4) ),g22 (s1 ), g22 (s2 ), · · · , g22 (r(N1 −4)(N2−4) )).

We explain an algorithm to solve the Mahalanobis metricequation by the Newton-Raphson method. Here, we discuss
the case when the dimension of the space is two. For brief,
˜ etc. are denoted without ˜·. We expand the Mahag̃µν , ∇,lanobis metric equation (4) and let its left hand side be Fµν .
Then, we have
F11

F12

F22

=

=

=

Let D(l) , F (l) , and G(l) be the values of D, F and G after thel-th iteration, respectively. The algorithm with a relaxation
parameter ǫ is expressed as−1
G(l+1) = G(l) − ǫ (D(l) )T D(l) (D(l) )T F (l) .

∂1 ∂1 log p − Γ111 ∂1 log p − Γ211 ∂2 log p+Γ111 (Γ111 + Γ221 ) + Γ211 (Γ112 + Γ222 )∂− 1 (Γ111 + Γ221 ) + g11∂x∂1 ∂2 log p − Γ112 ∂1 log p − Γ212 ∂2 log p+Γ112 (Γ111 + Γ221 ) + Γ212 (Γ112 + Γ222 )∂− 2 (Γ111 + Γ222 ) + g12∂x∂2 ∂2 log p − Γ122 ∂1 log p − Γ222 ∂2 log p+Γ122 (Γ111 + Γ221 ) + Γ222 (Γ112 + Γ222 )∂− 2 (Γ112 + Γ222 ) + g22 .
∂x

(10)

4 Probability density estimation(5)

We propose an estimation method of p.d.f. for Mahalanobis
metric equation from sample points in 2-dimensional-latticeby maximum likelihood approach. pS and pG stand for valuesof p.d.f. on sample points and grid points, respectively. We
let lS = log pS , lG = log pG . Let n denote the number ofsample points, and a log likelihood L(lS ) is defined as(6)

L(lS ) = log(pS 1 pS 2 · · · pS n ) =

(7)

n
X

lS k .

(11)k=1

lG has to be calculated from lS because we maximize L(lS )under the condition ofΓµνβ and R can be calculated from gµν and its first and second
order derivatives.
For numerical analysis, gµν is defined on the N1 × N2 lattice. Since the differentials are approximated by differences, we cannot have Fµν and R on the boundaries. Then,
we have their values on (N1 − 2) × (N2 − 2) -lattice. When we
consider small changes of gµν , Fµν and R change at the point
and its neighbors. Then, we renew gµν on (N1 − 4) × (N2 − 4)lattice. The gµν not on the (N1 − 4) × (N2 − 4)-lattice is set tothe value at the nearest point in the lattice. We denote pointsin (N1 − 2) × (N2 − 2)-lattice by r1 , r2 , · · · , r(N1 −2)(N2 −2) andpoints in (N1 − 4) × (N2 − 4)-lattice by s1 , s2 , · · · , s(N1 −4)(N2 −4) .
∂Fµν∂Rand ∂gαβ
be the (N1 −2)(N2 −2)×(N1 −4)(N2 −4)Let ∂gαβmatrices of which (i, j) -elements are given by!
!
∂Fµν (ri ) ∂R
∂Fµν
∂R(ri )==,
(8)∂gαβ i, j ∂gαβ (s j ) ∂gαβ i, j ∂gαβ (s j )

N1 X
N2
X

pGµν = 1.

(12)µ=1 ν=1

Here, we provide a matrix to calculate lS from lG by theleast square approach and solve this inverse problem. Now,
we assume that lG is given in 2-dimensional lattice, and calculate the matrix A which expresses the interpolation from lG
into lS by least square approach with the nearest 3 × 3-gridpoints of the sample point as
lS = AlG .

(13)

Next, we let that lG is smooth, so assume that its third
derivatives are small. Matrices D x1 x1 x1 , D x1 x1 x2 , D x1 x2 x2 , andD x2 x2 x2 , which expresses the differentials of rank 3 as2
46

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

We calculate the Mahalanobis metric with the estimatedp.d.f. In this experiment, we set α = 27, β = 2.7, N1 = N2 =55, σ1 = 2.5, σ2 = 1, θ = π/6, γ = 3, λ = 0.1 and ǫ = 0.05.
The number of sample points generated in coordinate system{xµ } is 500. The 53 × 53-lattice is assumed to be the regionof [−26, 26] × [−26, 26] in the coordinate system {xµ }.
Figs.2 (a), (b), and(c) illustrate the results of estimatedp.d.f. with µ=200. Figs.2 (d) and (g) illustrate the calculatedgµν with µ=200. Figs.2 (e) and (g) illustrate the calculated
and the original gµν . Figs.2 (h) and (i) illustrate the squared
errors of gµν , and Fµν with the number of iterations.

∂3∂3
lG = D x1 x1 x1 lG ,lG = D x1 x1 x2 lG
1
3
1
∂(x )
∂(x )2 (x2 )∂3∂3
1 x2 x2 lG ,l=D
lG = D x2 x2 x2 lG .
Gx∂(x1 )(x2 )2∂(x2 )3
When we let Dall = D x1 x1 x1 ⊤ D x1 x1 x1 + D x1 x1 x2 ⊤ D x1 x1 x2 +D x1 x2 x2 ⊤ D x1 x2 x2 + D x2 x2 x2 ⊤ D x2 x2 x2 , we have
3
3
∂3 lG
lG + ∂3 lG+ ∂(x∂1 )l2G(x2 ) + ∂(x∂1 )(x
2 )2∂(x1 )3∂(x2 )3==2

hD x1 x1 x1 lg , D x1 x1 x1 lg i + hD x1 x1 x2 lg , D x1 x1 x2 lg i+h D x1 x2 x2 lg , D x1 x2 x2 lg i + h D x2 x2 x2 lg , D x2 x2 x2 lg ih Dall lg , lg i.
(14)

6 Conclusion
From those results, we can obtain the Mahalanobis metric by
estimating the p.d.f. from sample points and solving the Mahalanobis metric equation. However, the method does nothave enough accuracy. Then, it is necessary to survey parameter and to introduce the Newton method to maximum
likelihood approach.

Considering with eqs.(13) and (14), we obtain the minimization problem of JC
JC (lG ) = k AlG − lS k2 + µk Dall lG k2= h A⊤ AlG , lG i − 2hA⊤ lS , lG i+hlS , lS i + µhDall lG , lG i.

(15)

References

By the variation of J C , we have the matrix B for estimatinglG from lS as lG = BlS . µ stands for a smoothing parameter.
We define the n-dimensional vector by⊤lS ) · · · ∂L( lS ) .
J L = ∂L(
(16)
∂lS
∂lS

[1] W.Feller. An introduction to probability theory and its
application, third edition, vol.1, John Wiley & Sons,
New York, 1968.
[2] P.Mahalanobis. Normalization of statistical variates andthe use of rectangular co-ordinates in the theory of sampling distributions. Sankhay, 3:1-40, 1937.
[3] L.Maistrov. Probability theory, a historical sketch Academic Press, New York and London, 1974. (Translated
and Edited by Kotz, S.)[4] M.Spivak. A comprehensive introduction to differential
geometry, second edition, vol.1–5, Publish or Perish,
Inc., Houston, Texas, 1979.
[5] Y.Yamashita, M.Numakami, and N.Inoue. Maxwell normal distribution in a manifold and mahalanobis metric.
In D.-Y. Yeung, J. T.Kwok, A. Fred, F. Roli, and D. de
Ridder, editor, tructural, Syntactic and Statistical Pattern Recognition, pp.604-612. Springer Berlin Heidelberg, August 2006.

n

1

(κ)
(κ)
Let l(κ)
S , lG and J L be the values of lS , lG and J L after the κth iteration, respectively. After we adjust l(κ)
S in condition of
(κ)
(κ)
(κ+1)
normalizing lG (= BlS ), update lS by the steepest descentmethod with a parameter λ as(κ)
l(κ+1)= l(κ)S
S + λJ L .

5

(17)

Experimental results

In experiment, we generate sample points along a normal
isotropic distribution of which variance is 1 in the coordinate system {xµ }. Next, we let variances in the direction ofx1 and x2 be σ1 and σ2 . We define an coordinate system {yµ }with rotation of {xµ } by θ. In addition, {zµ } is given by a nonlinear transformation of {yµ }. We assume that sample points
in {zµ } are obtained. We define a coordinate transform from{yµ } into {zµ } as
z1
z2

=
=

y1
y2 + βh(y1 )h(y2 )with constants α, where

 
1


 e4 1− 1−(y/α)2h(y) = 0(−α < y < α) .
(else)

(18)
(19)

(20)

To estimate p.d.f. we consider the coordinate system {wµ }given by a liner whitening of sample points of which varianceis γ2 . And the proposed algorithm is applied to the sample
points.
347

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

0.0035
p

p
p

0.003

20

0.00250.003
0.0025

10

0.002

w2

p

0.002
0.001500.00150.001
0.0005

-10

0.001

-20

0.0005

0
20
10

20
0

w2

10
0

-10
-20

-10

-20

w1

-20

-10

0

10

0

20

-20

w1

(a) Estemated p(3D) with µ = 200(b) Estimated p(2D) with µ = 200

-10

0
w2

10

20

(c) Estimated p(w1 = 0) with µ = 200

0.04

g11
g11

0.035
0.03

0.04
0.035

0.025
g22

0.03
0.025
0.02

0.02
0.015

0.015

0.01
20
10

0
w2

0

-10
-20

-10

0

w1

-20

-20

g22
g22

0.045
0.04
0.035

g22

0.03
0.025
0.02
0.015

20
20

10
10

0

0

-10
-20

-10
-20

w1

0.1
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0

0
w1

10

20

calculated g22
ideal g22
-20

-10

0
w2

10

20

(g) g22 (w1 = 0) with µ = 200(f) g22 (3D) with µ = 200
0.12

19.9
Squared error of F

Squared error of g
19.8
Squared error

0.1
Squared error-10(e) g11 (w2 = 0) with µ = 200(d) g11 (3D) with µ = 200

w2

calculated g11
ideal g11

0.005

20

10

0.08
0.06
0.04
0.02

19.7
19.6
19.5
19.4
19.3

0

19.2
0

50
100
150
Number of iterations

2000(h) Mean square errors of Fµν vs. the num. of iterations

50
100
150
Number of iterations

200(i) Mean square errors of gµν vs. the num. of iterations

Figure 2: Experimental results

448

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

LAGRANGIAN HUMAN METEOROLOGY
Student Number: 07M18094

Name: Makoto Nakayoshi

Supervisor: Manabu Kanda

ラ グ ラ ン ジュ ア ン 人間気象学の試論
仲吉信人
本論文では ラ グ ラ ン ジュ ア ン 人間気象学（ LHM）
を 提案し その有用性を 議論する ． LHM
は， 個々人が計測器を 装着し ， 動線に沿っ て 変化する 熱環境， それに伴う 人体生理の変化を 監視評価する も のであ る ． 2008年夏季晴天日に行っ た 都心を 周回する 現地観測から 以下のこ と が示さ れた ． ①通勤ラ ッ シ ュ 時の混雑駅ホ ーム は熱中症の危険を 伴う 暑熱環境が形成さ れて いた ．
②満員電車内の環境は被験者の心拍・ 血圧値を 上昇さ せて いた ． ③都市街路空間は大手町ア メ
ダ ス 気温を 最高で3℃上回る 熱環境であ っ た．

1 Introduction

sensors. The sensors monitor ambient temperature (Ta),relative humidity (RH), wind velocity (U), mean radiative
temperature (MRT), body temperature (Tb), heart rate (HR),and blood pressure (BP). The perspective merits of LHM
include contributions to 1.) self-monitoring and precautionof health disorder such as heat stroke and 2.) evaluation of
actual micro-climate absent of eulerian fixed-observation
points.

Due to the global warming and the heat island phenomenon,
problems such as warmer environments and the increasing
incidence of heat stroke patients are usual in several Asianmega-cities. Monitoring the meteorological information incities is important for urban environmental amenity andhuman health. However, official meteorological information
can be largely different from actual micro-climate in urban
canyons where we are living, because the data are measured
over managed grasslands. In addition, our physiologicalresponse to micro-climate can be different by individuals
depending on their lagrangian movements and physical andmental conditions. Thus, lagrangian observational data
along human pathways are better suitable for urban
meteorological information on health rather than that fromfixed-point observations in Euler sense. Here I propose a
new lagrangian concept for urban bio-meteorology named"Lagrangian Human Meteorology (LHM)".

3 Lagrangian observation
To confirm the effectiveness of LHM, The author
conducted a lagrangian observation in central Tokyo on a
typical fair day in summer, 20th August in 2008. Measuring
items are represented in Table 1. All of the meteorologicalsensors were packed in a carry bag (Figure 1). The summaryof the event records and the observational route map areshown in Table 2 and Figure 2, respectively.

3.1 Results and Discussion
2 Concept of LHM
Standard effective temperature (SET*) and Ta are focusedhere for micro-climate variables (Figure 3 (a) and 4). SET*The concept of LHM is to investigate continuous changes of
micro-climate and the dynamical physiological response
along human pathways carrying small bio-meteorologicalU
風速セン サTable 1 Measurement items
Item

SensorManufacturer

Ta
MRT
RH

Thermocouple (0.2 mm)
Globe temperature sensor (40 mm)
Humidity transmitter

NEWC*2
Self-produce
VaisalaSampling
frequency
1 Hz
1 Hz
1 Hz

U
Hot-wire anemometerHR
Sphygmomanometer (wrist type)BP
Tb*1
Thermocouple (0.2 mm)*1: Axillary body temperature*2: Ninomiya Electrical Wire CO., Ltd.

Kanomax
Omron

1 Hz
−

NEWC*2

1 Hz

Ta & MRTRH

HR & BP

Figure 1 Measurement system
49Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Table 2 Summary of event records of the lagrangian observation. Alphabet in ID column corresponds to that in Figure 2
and Figure 4.
Time
6:55
7:06
7:08
7:21
7:22
7:41
7:50
8:31
8:39
12:08
14:40
14:16
15:05
15:41
15:48
15:50

ID
a
a’
b’
b
c’
c
d
e
f

Event

Time

Leaving home (by foot)Arriving at Okayama station
Boarding Oimachi line
Arriving at Futakutamagawa station
Boarding Denentoshi line
Arriving at Nagatuda station
Boarding Denentoshi line
Arriving at Shibuya station
On the street at Shibuya area
Taking in the sun at Miyashita park
Shopping around Shibuya and Harajuku area
Lunch
Shopping at Tokyu hands
Arriving at Shibuya station
Boarding Hanzomon line
Arriving at Aoyama-itchome station

16:01
16:03
16:20
16:30
18:32
18:39
21:51
23:01
23:11
23:19
23:31
23:34
23:54
0:08
0:28
0:41

(a) Rail road map

Event
Boarding Toei-Oedo line
Arriving Roppongi station
On the street at Roppongi area
Walking around at Roppongi hills
Arriving at Mid town
Moviegoing at garden theater of Mid town
Chatting with a friend (open-air cafe)
Leaving Mid town
Arriving at Roppongi-itchome station
Boarding Toei-Oedo line
Arriving at Shibuya station
On the street at Shibuya area
Boarding Denentoshi line
Arriving at Futakotamagawa station
Arriving at Okayama station
Going home

g
h
i
j
k

m

Tokyu Denen Toshi line

Tokyo Metro Hanzomon line

RoppongiTokyo subway Oedo line

ShibuyaIkejiri-Hhachi

Aoyama-itchome

Tokyo Tech.

(c) Harajuku
Continue (a)Sangenjaya

OkayamaKomazawa-daigaku

Tokyu Oimachi line

Jiyugaoka

Sakurasinmachi

Yoga

Mizonokuchi

Nagatsuda

Futakotamagawa(b) Shibuya(d) Roppongi
Garden theater

Harajuku
StationkdjTokyo Midtown

Miyashita
park

f
Tokyu
Hands

ID

e

Roppongi-itchome
Station 3rd EXITi
Roppongi Hills(a) continue

start

m

ShibuyaStationFigure 2 Lagrangian observational route map
is also plotted in Figure 3 (a) for comparison of thelagrangian data and the eulerian data. Time series of thephysiological responses are plotted in Figure 3 (b).
(1) Micro-climate in train and station platform in rushhour
The data on 7:06-8:31 include trains and station platforms in

is a physical index for thermal sensitivity based onmathematical models of both human thermoregulatory
mechanism and energy budget on human body1. SET* is
computed from Ta, RH, U, and MRT. Figure 3 (a) shows
the time series of SET* and Ta from the lagrangian
observation. Ta at Tokyo meteorological observational site

50

Technical Report of International Development Engineering

140
130
120
110
100
90
80
70
60

37
35

24

23

22

21

20

19

18

17

16

15

14

13

9

8

7

31

12

Axillary T emp.
Blood Pressure
Heart Rate

33

B.P. [mm Hg] or H.R.[bpm]SET *T a_lagrang.
T a_Otemachi

11[Degree Celsius]

(b)

39
36
33
30
27
24
21
18
39

10

[Degree Celsius](a)

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Japan standard time [hour]

Figure 3 Time series of the lagrangian observation.

[Degree Celsius]

39
36
33
30
27
24
21
18
39
36
33
30
27
24
21
18

[Degree Celsius][Degree Celsius]

(a)

39
36
33
30
27
24
21
18

(b)

a’
a

b’
b

c

7

8

9

Shadow

10

Sunny

d
11

(c)

SET*
Ta_lagrang.
Ta_Otemachi

c’

e

12

f

13

g

15

14

j

i

h

16

17

18

Japan standard time [hour]

Figure 4 Time series of the lagrangian observation. Time axis of Figure 3 is enlarged. (a):7-11, (b):11-15, (c):15-19
85
80
75
70
65
60

23

24

25 26 27 28 29
SET* [Degree Celsius]

3031(c)110100

HR [bpm]

120
115
110
105
100
95

Diastolic BP [mmHg](b) 90

Systolic BP [mmHg](a) 125

90
80
70

23

24

25 26 27 28 29
SET* [Degree Celsius]

30

31

23

24

25 26 27 28 29
SET* [Degree Celsius]

30

31

Figure 5 Relation between (a) systolic BP and SET*, (b) diastolic BP and SET*, and (c) HR and SET*.
of Tokyu Denentoshi line (STD) was 27.8 C (Figure 4 (a),c’) and higher than the preset temperature of the air
conditioner (25~26 C, Tokyu railway company HP).
Meanwhile, average Ta in trains for Futakotamagawa of
Tokyu Oimachi line (FTO) and for Nagatsuda of Tokyu
Denentoshi line (NTD) was 25.2 C (Figure 4 (a), a’) and26.4 C (Figure 4 (a), b’), respectively, and ranged in thepreset temperature. The congestion degree in the train may

rush hour. 3-times leap of SET* and Ta occurred in theplatform of Ookayama station (32.0 C, Figure 4 (a), a),Nagatsuda station (31.8 C, Figure 4 (a), b), and Shibuya
station (34.4 C, Figure 4 (a), c), respectively. Even in theearly morning, Ta in Shibuya-station platform was higher
than the daily maximal temperature in Otemachimeteorological site by 2 C, and SET* was over 37 C. It
involved heat stroke risk. Average Ta in a train for Shibuya

51

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

HR

affect the thermal environment in the trains, which means
that, the anthropogenic heat emission from passengers may
be a non-negligible factor for the micro-climate in trains.
(2) HR and BP in train and station platform
The values of HR and BP in STD were high compared tothose in NTD and FTD (Figure 3 (b), region enclosed bybroken line); average HR in STD is 97 bpm and 88 bpm in
NTD and FTO; average systolic BP in STD is 111 mmHg
and 104 mmHg in NTD and FTO. Figure 5 shows therelation between HR and SET* and between BP and SET*.
HR and systolic/diastolic BP appeared to be correlated with
SET*. Some studies reported that the enhancement of heatstress resulted in an increase of HR but a small decrease ofBP2, 3. However, our findings are not consistent with them.
These previous surveys also assessed the relation between
physical-mental stresses and HR/BP, and inferred thatexercises increase both HR and BP4 and acute mental
stresses increase BP5. Therefore, the current results may
suggest that the influence of physical/mental stress in thepacked train might lead to the increase of both HR and BP
rather than influences of micro-climate in the trains; SET*in the train and the station platform air-conditioned is likely
to be influenced by the congestion degree, namely
anthropogenic heat emission from passengers. Human
physiology is affected by micro-climate, physical/mental
conditions, and activities of subjects. Further studies onhuman physiology in commute trains are required.
(3) Micro-climate in street canyons
The data on 11:50~15:50 include the street canyons in
Shibuya and Harajuku (Figure 4 (b) and (c)). Except for theindoor environment, Ta from the lagrangian observation
was higher than Ta at Otemachi by 3 C at a maximum.
Figure 4 (b) and (c) indicate the subject underwent theabrupt changes of thermal environment (over 10 C for Ta
and SET*). Unfortunately, this measurement system could
not detect the exact response of BP and HR accompanied byabrupt transition of heat environment. Sudden heat exposure
enhances the heat stoke risk (guideline for heat stroke
prevention by Japanese Society of Biometeorology), andvital signs may be affected by abrupt shift of micro-climate.
Continuous measuring system of vital signs is necessary forlagrangian observations. Possibilities of developing suchmeasuring system are discussed in Chapter 4.

Ta & RH

MRT

Figure 6 Photo of bio-meter prototype.
Left half: CPU and logger. Right half: sensors.
continuous change of BP and HR accompanied by abrupt
shift of micro-climate. In order to solve such problems, aprototype of the bio-meter was developed. Figure 6 shows
the appearance of the instrument. Specific features of the
prototype are as follows; (1) it can measure Ta, RH, MRT,and HR, (2) the data are stored up to 2 GB, (3) it is muchsmaller and lighter than the current measurement system (72x 75 x 25 mm, 110 g). A wind velocity and BP sensors areto be mounted on the compact measurement system.

5 Conclusions
I proposed the new lagrangian concept for urban biometeorology. The concept is to investigate continuouschanges of micro-climate and the physiological response
along human pathways carrying a compact measurement
system. The first results of the observation suggested that
LHM has a potential to evaluate the micro-climate andphysiological response along human pathways andcontribute to urban biometeorology.

References[1] Gagge, A.P., Stolwijk, J.A.J., Nishi, Y.: An effective temperaturescale based on a simple model of human physiological regulatory
response, ASHRAE, pp. 247-262, 1971.
[2] Niimi, Y., Matsukawa, T., Sugiyama, Y., Shamsuzzaman, A.S.M.,
Ito, H., Sobue, G., Mano, T.: Effect of heat stress on muscle
sympathetic nerve activity in humans, Journal of the Autonomic
Nervous System, pp. 61-67, 1997.
[3] Gaebelein C.J., Senay L.C. Jr., Ladd C.M.: Changes in bloodpressure, heart rate and blood constituents during heat exposure inmen with elevated blood pressure, Eur J Appl Physiol, 54, pp.506510, 1985
[4] Matsuda M., Haga S., Kitao H., Nosaka T., Iida K., Sugishita Y., Ito
I.: Influence of arterial blood pressure level during strength exercise on

4 Re-development of the measurement system

left ventricular hypertrophy, Adv. Exerc. Sports Physiol., 2, pp. 13-18,
1996

The sensors used in the observation were not specialized forlargangian measurements and the observational system washeavy and bulky. In addition, the current BP and HR sensor
operates intermittently and it is difficult to detect the[5] Douglas C., George D.S., Martin J.S., Andrew S., Eric J.B.,
Michael G.M.: Blood pressure reactions to acute phychological stressand future blood pressure status: A 10-year follow-up of men in the
Whitehall II study, Psychosomatic Medicine, 63, pp.737–743, 2001.

52

Technical Report of International Development Engineering

Influence of mixing
Student Number: 07M18102

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)-C2S on Cl- penetration in concrete cured
using autoclave
Name: Masayo Horioka

Supervisor: Nobuaki OTSUKI-C2S !"#$%&%'()*+,-./01234! Cl56789:;<=>?@AB
C./01DEFGHIJ9 5C2S *"#KLMN1OPNQ()DRST()*UK-VWL 5
C2S XY3!TZ[\]8D^Y_`!FM0679a<bcd8!ef!gh9ij<bklmnoXL(1) 5C2S *"#KLMN1OPNQ()pqrRST()*s+K-./01tuv*+,wLxy)z{D|}9~!Tpqr T{FM0*W[9KL(2)!0
ON1F9y+KwL0ON1F9pb T{FM0!D*-k

1. Introduction

replacement ratio of -C2S. Specific objectives are:(1)To design a paste specimen with a surface densified withvaterite and with core structure made of tobermorite using
180oC autoclave curing and CO2 acceleration.
(2) To investigate the relationship between pore distribution andthe permeability of chloride ion of paste specimen with !
-C2S.
(3) To compare the chloride ion permeability between-C2S containing paste specimen and RC piles, and using thisconclusion, design a high-durability RC pile

Generally, in order to improve the durability of concrete
structures, it is important to consider the resistivity against
external degrading materials. In has been shown in previous
research, that the use of the material called -C2S ( -2CaO
SiO2) as admixture for concrete, improves the durability of themember because of the 2 abilities of -C2S for durability : (1) itreacts with CO2 and become CaCO3 (vaterite); (2) -C2S assist
in making tobermorite under autoclave curing. Crystalline
tobermorite has a stable structure so it can affect thedimensional stability and chemical stability of the specimen,
The group of Morioka, Yokozeki and Watanabe1) 2) made anattempt at improving the strength and permeability of theconcrete by exposure of specimen to carbonation with -C2S.
Further research was done on the utilization of -C2S inconcrete by adding the utilization of autoclave curing. In the
study by Saito et. al. 3) 4), it was shown that -C2S can possibly
make a more durable member. But the possibility only
considered the neutralization test in durability. So far,consideration to relation of production, pore distribution, andpermeability of Cl-, as important deterioration factors in
reinforced concrete are not yet done. Moreover, theexamination of the use of -C2S for concrete is not yet
performed.
Therefore in this study, the technique of using -C2S wasapplied for concrete pile. The concrete pile was also cured by
autoclave. The main objective of this study is to design ahigh-durability concrete pile by investigating the optimum

2.The change of product in carbonated cement
paste with!-C2S
2.1 Methods of manufacturing the test specimen
2.1.1 XRD
Paste test specimens containing OPC and ! -C2S atsubstitution levels of 0, 20, 40, 60 and 80% were prepared as
the source of lime. The lime source (OPC+!-C2S) and "-quartz were mixed in a ratio of 5:5 and deionized water wasadded to the powder at water-to powder ratio of (w/p)of 0.3(mass ratio). The prepared paste was cast in a mould withdimensions of 1 x 1 x 8 cm and allowed to harden at 100%RH
for 4 hours at 65#. The hardened paste specimen was removed
from the mould and autoclaved for 8 hours at 180 #.
Accelerated carbonation of the samples was carried out in a
carbonation chamber with settings of 5% CO2 by volume, 20#
temperature and 60%RH for 28days. After carbonation, eachsample was completely submerged in acetone at 20#for 1
hour inside a vacuum containment, in order to terminate
hydration .Afterwards, reduced pressure drying was carried out
for 24 hours.

53Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)(') peak of CaCO3

The test sample was cut in layers as follows: 0-2 mm as
Surface layer; 4-6 mm as Middle layer and 8-10mm as Core
layer. The mix proportions for the paste are shown in Table.2.1.
Table.2.1 Mix proportions for the paste specimens

C (g)
10$0

-C2S !g"AD (g)0$10
10IntensityW(g)# 5.555

80% Surface

CA (g)
0.045

W…water
C…cement
AD…ground silica sandCA…water-reducing admixture

0% Surface

0% Core2.1.2 Compression test
The specimen for compression test was made using the samemix proportion as shown in Table. 2.1. The mixed paste wascast in cylindrical moulds, 5cm×10cm, autoclave cured andexposed to carbonation using the same settings explained in
2.1.1. Autoclaved compression tests specimens withoutcarbonation were also prepared.

24

80% Core

25

2

26

Fig.2.4 vaterite peak of 0% & 80%
In the case of 0% and 20% -C2S substitution, the XRD
peaks of crystalline tobermorite have completely disappeared at
all layers from the exposed surface. This result may have been
due to the complete carbonation of the specimen that lead to thedestruction of the structure of the crystalline tobermorite thatwere formed during autoclave curing. On the other hand, In thecase of 40% and 60%-C2S substitution, the peak of
crystalline Tobermorite remained in all layers. This means thatthe voids were filled up thus retarding the progress ofcarbonation. These voids were actually filled with Vaterite as
evidenced by Figs.2.3 which shows high Vaterite peaks after
carbonation. This was seen especially in the case of 80%-C2S substitution where the crystalline tobermorite peak foundin the core layer has the same intensity as that found in the noncarbonated case. Also, there are no carbonation products foundin the core layer. From both these results, it is deduced thatcarbonation only reached the middle layer.

2.1.3 Dimensional stability test
Paste test specimens were prepared as explained in section
2.1.1. Gauge plugs were bonded on the samples using quick
curing adhesive. An initial value of dimension was measured
immediately after autoclave curing. The specimens were thenstored in moist chamber for 22 hours at 20% and were later
tested of its dimension using a strain gauge at 70%RH for 24
hour at 20% following the measuring standard set by JIS
A1129-1.
2.2 Results & Discussions
2.2.1 Result of x-ray diffraction
Fig.2.2 shows the XRD peak intensity of crystalline
tobermorite while Fig.2.3 shows the CaCO3 peaks made from
CO2 acceleration. of the 0% and 80% substituted specimens.
(&) peak of tobermorite

2.2.2 Result of compression test
In the non-carbonated case, the compression strength of thecylinder specimen decreased as the -C2S replacement ratio
was increased. When carbonation was induced for 28days,
improvement was observed as the compressive strength
increased in all levels of replacement ratios.
The 60% substitution turned out to have the highest
improvement rate of compressive strength (45%) after
carbonation. This was followed by 80%, then 40%
substitution ratios. This maybe due to the of -C2S generated
vaterite3) from carbonation.

80% Surface

Intensity

80% Core

0% Surface
0% Core2.2.3 Result of dimension stability test
In all replacement ratios, the rate of length change for
specimens that underwent autoclave curing was smaller by atleast 50% than those specimens that underwent moist curing. It
turns out that using autoclave curing can lead to the formationof tobermorite crystals that helped improved shrinkage
deformation.

6

8
10
2
Fig.2.2 XRD peak intensity of crystalline tobermorite

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Technical Report of International Development Engineering

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from reaching the core layer.
According to Dr .Saito3), there is a report that replacement of
80% ratio or more of -C2S in 150" cured specimens lead tolower deterioration factor. In this study, it was shown that using
40% or more replacement ratio of -C2S in 180" autoclaved
cured and carbonated specimens can lead to the possibility oflowering the factor of deterioration.

3.The change of pore distribution incarbonated cement paste with!-C2S
60.0

Pore Volume (mm3/g)

Surface
12"!"Core !"

40.0'()*+,-.(),/0()#$%&

4. The influence the changeof poredistribution on Cl- diffusivity
Diffusion Coefficient (cm2/sec)

20.0

.0
.010

.10

1.0

10.0

100.0

Pore diameter (µm)

Fig.3.1

0% Pore Volume

Pore Volume (mm3/g)

60.0

Surface
12"Core !"

40.0'()*+,-.(),/0()
#$%&

.10

1.0

10.0

6.0E-10
4.0E-102.0E-100.0E+00
0%

40%

80%

Fig.4.1 Cl- diffusion Coefficient
In the case of 0% substitution, the Cl-diffusivity is decreased inorder of Surface, Middle, and Core layer. In contrast, the Cldiffusivity on 40% and 80% substitution ratios is increased inorder of Surface, Middle, and Core layer. Looking at the results
for the surface layer the specimen, the value with the smallest
Cl-diffusivity is 80% replacement ratio. Thus 80% replacement
ratio has the lowest permeability to Cl- . Moreover, this result
agrees to the result of the product change before and after
undergoing carbonation, and also with the results of the voids
structure.
In the surface layer of the specimen with replacement ratio of
0%, because of carbonation deterioration, the pore diameter
becomes higher thus increasing the Cl- diffusivity. On the other
hand, in the case of 40% and 80% replacement ratio, thethreshold pore diameter of the Surface layer becomes small dueto the filling of voids thus the Cl- diffusivity becomes lower.
In the Core layer of the specimens with replacement ratio of
80%, it is deduced that the Cl- diffusion coefficient is increasing
due to the presence of Tobermorite crystals, the formation ofwhich is card shaped thus containing larger voids.

20.0

.0
.010

8.0E-10100.0

Pore diameter (µm)

Fig.3.2 80% Pore Volume
In the case of 0% and 20% substitution ratio, carbonation
deterioration occurred in all layers. After carbonation, thebehavior of the threshold pore diameters shifted to the larger
diameter. This result is in agreement with the results of the
XRD test. On the other hand, in the case of 40% and 60%
substitution, the behavior of the threshold pore diameters
shifted to the small values of diameter. After autoclave curing,
the remaining unreacted -C2S was exposed to carbonation thus
forming Vaterite that eventually filled the voids and prevented
further penetration of CO2. This was seen especially in the caseof 80% substitution where there was no significant change inthe threshold pore diameter behavior in the surface and middle
layers although the amount of voids with size 0.03!m or lessdecreased. In the core layer, the voids and pore size distribution
did not change at all before and after the exposure tocarbonation. Thus, it can be deduced that the surface layer was
extremely densified, leaving carbonation to reach only the
middle layer, and preventing further progress of carbonation

5. Comparing Cl- diffusion coefficient of
RC Pile and paste
5.1 Method of manufacturing the test specimen
Concrete piles embedded with steel bars were preparedfollowing the mix proportions shown in Table.5.1.

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Technical Report of International Development Engineering

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of the specimens with replacement of 80% is about half thatfound for the specimens with 0% replacement.

Table.5.1 mix proportion of concrete pileCA/
S/a AD/Air
W/(%)(C+AD) (%) (C+AD) (C+AD)
(%)
(%)
(%)
12 3 2.0
32.9
50
14.4
1.25
Amount of Unit (kg/m3)
!
"
#
$ %&
"%
148
385
905
905 65
5.63
Centrifugal conditions were used in the casting of thespecimens. The specimens were then pre-cured in hot water(65oC). After pre-curing, the specimens were autoclaved
followed by exposure to accelerated carbonation as that
explained for cement paste. The specimens were then soaked inwater bath for four months.
slump
(cm)

Surface(0~8mm)
Densification from CO2 acceleration

InsideDimension stability
Chemical stability
Crystalline tobermorite

Fig.5.4 High durability concrete pile
In this study, the replacement of 80% -C2S showed thelowest permeability of Cl-. The surface zone of the member has
high densification and the inner portions contain crystalline
tobermorite which has good dimensional and chemical stability.

Non
NonCarbonation
Carbonation
After
AfterCarbonation
Carbonation

10-8cm2/sec

Cl- Diffusion Coefficient

5.2 Results of test of chloride content in RC pile
10
9
8
7
6
5
4
3
2
1
0

6. Conclusions

0%

40%

(1)In cement paste with 0 to 20% -C2S substitution,
carbonation proceeded throughout all layers and thetobermorite structure was destroyed. In cement paste with 40 to
60% -C2S substitution, the tobermorite structure was kept
intact and the pore distribution was improved due to filling with
Vaterite. In cement paste with 80% -C2S substitution, thesurface layer was highly densified keeping the tobermorite andpore distributions of the core layer intact.
(2)Substitution of 0 to 20% -C2S to cement paste lead to thedecrease in resistance against penetration of of Cl- ion.
Substitution of 40 to 60% -C2S dramatically increased thedensity of the outer layers of the cement paste and improved its
resistance against penetration of Cl-. In the case of 80%
substitution with -C2S, the penetrations of both CO2 and Clwere prevented by the formation of very dense surface layer.
(3)Tests on the amount of chloride ions concentration in RC
piles -C2S after 4 months exposure show the same trend ofchloride penetration resistance as in cement pastes with -C2S

80%

Fig.5.2 Diffusion coefficient of RC pile
The amount of Cl- g/cm3

Prevent fromdegradation ion

0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0

Non
NonCarbonation
Carbonation

After
AfterCarbonation
Carbonation

0%

40%

80%

Fig.5.3 Cl- around of steel bar

References

Fig.5.2 shows the diffusion coefficient of Cl-. In any
replacement ratio, the Cl- content in the pile exposed tocarbonation has decreased. Moreover, the results show thatafter carbonation, the specimen with 40% or more -C2S show
lower Cl- diffusion. It was thought that the material -C2S had
demonstrated the effects of reducing the permeability to Cl- at
the replacement ratio 40% with carbonation and corresponds to
the results observed previously for cement paste.
Fig.5.3 shows the total amount of Cl- around the steel bar.
After carbonation, as replacement ratio of -C2S was increased,
the amount of Cl- content decreased. The amount of Cl- content[1] Minoru Morioka, Takayuki Higuchi, Cement Science andConcrete Technology!No.57!2003[2] Minoru Morioka, Kouji Okuyama, Kenzou Watanabe,
Yasuhiro Yokozeki, Cement Science and Concrete
Technology!No.58!2004[3] Tsuyoshi Saito, Thesis of Doctoral Degree, Tokyo Tech, 2006
[4] Tsuyoshi Saito, Etsuo Sakai, Nobuaki Otsuki , kenzou
Watanabe, Minoru Morioka, Meeting & Research in Cement
Concrete ,P1-6,2008

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Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

LIQUID-LIQUID EXTRACTION RATE OF COAL TAR ABSORPTION OIL
IN A CONTINUOUS COUNTERCURRENT SPRAY COLUMN
Student Number: 07M18119

Name: Toshiya MASUDA

Supervisor: Ryuichi EGASHIRA

連続式向流接触ス プレ ー塔における コ ールタ ール吸収油の液液抽出速度
増田敏也

含窒素複素環式化合物、 同素環式化合物、 など の有用成分を 含むコ ールタ ール吸収油を 原料分散相、 メ タ ノール水溶液を 溶媒連続相と し て、 こ れら を 向流接触さ せた。 他の成分に比較し て含窒素成分は選択的に溶媒相に抽出さ れ、 こ れら の成分間の分離が可能であ る こ と を 確認し た。 含窒素複素環式化合物の収率、 その他の成分に対する 分離の選択度は、 それぞれ最大で 0.5、 20 程度であっ た。 総括物質移動容量係数を 求め、 物
質移動係数の相関関係を 導き 既往の研究と 比較し 抽出速度過程を 検討し た。
the details of the distributors. The distributor of thedispersed phase has 8 needle nozzles of which the innerdiameter is 6×10-4m. The distributor of the continuous
phase has outlets on side of the cylinder to prevent fromfalling drops entering in it.
2.2. Procedure
AO and MeOH aq. were stocked in the tanks. AO,
dispersed phase, was fed to the top of the column, MeOH
aq., continuous phase, to the bottom and these twophases contacted countercurrently. The inlet flow rates
were kept constant by controlling the flow valves and thelevel of the interface between the continuous phase andaccumulated raffinate phase at the bottom wasmaintained by adjusting the drain valve of raffinate phase.
The inlet and outlet flow rates were determined byweighing the mass collected in 10 minutes. The holdupof the dispersed phase in the column was determined bymeasuring the rise of the interface after about 1hour

1. Introduction
Coal tar, one of the byproducts from coal carbonization,
contains many useful compounds to chemical industry.
Absorption oil (AO) which is one of the fractions of coaltar (b.p.=470~550K) contains nitrogen heterocyclic
compounds (nitrogen compounds) such as quinoline (Q),
isoquinoline (IQ), indole (IL), etc., homocyclic compounds
such as naphthalene (N), 1-methylnaphthalene (1MN),
2-methylnaphthalene (2MN), biphenyl (BP), etc., andoxygen heterocyclic compounds such as dibenzofuran(DBF), etc. Generally, the separation and purification ofthese compounds in AO are carried out in two steps; 1:
AO is separated into several fractions by reactive
extraction with acid and/or base, 2: these fractions are
separated and purified into respective products bydistillation, crystallization, adsorption, etc. However, thisprocess is relatively costly because the acid and baseused as solvent are very difficult to be recovered andcause corrosion of the equipments. For this problem, theordinary solvent extraction method with aqueous
methanolic solution (MeOH aq.) and the liquid
membrane method have been studied1-6). In thecontinuous countercurrent liquid-liquid extraction6), a
spray column was chosen for the equipment, because it
was the simplest differential-contact device in laboratory
studies, and mass transfer rate was measured andexamined.
Mass transfer occurs in three steps which are drop
formation, drop coalescence and drop falling. The masstransfer from the single drop during its falling to thecontinuous phase has been studied 7,8). Some researchers
7,8)
correlated the continuous mass transfer coefficient byusing NRe, NSc and NSh.
In this study, a countercurrent spray column wasapplied to the extraction of AO and the separation
performance was examined. The mass transfer
coefficients were experimentally measured andcompared with the previous correlations7,8).

⑥

Et
④

Z

④
④

⑨

Rt

⑤

⑨
⑧

Rb

④

⑤

④

⑤
①

②

⑦

⑨

Eb

③

①
②
③
④
⑤
⑥
⑦
⑧

AO tank
Solvent tank
Pump
Valve
Flow indicator
AO distributor
Solvent distributor
Pyrex glass column
D=0.037 m
Z=0.495 m
Level controller③

Fig.1 Schematic diagram of the experimental apparatus-2

2.7×10 m

1.9×10-2m

2.0×10-2m-2

3.3×10 m

6×10-4m

2. Experimental
2.1. Apparatus
The schematic diagram of the apparatus is shown in
Fig.1. Iwaki Magnet Gear Pumps are equipped with eachtank to supply the column with each phase. The column
is made of pyrex glass of which the inner diameter is0.0037m and effective height is 0.495m. Figure 2 shows-2

1.4×10 m-2

2.8×10 m

Fig. 2 Details of distributors;

57

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

from closing AO inlet and drain at the same time. Each
operation was carried out in 3 hours to reach steady state.
Each phase was analyzed by GC-2010 (Shimadzu Corp.)
The dispersed drop diameters were determined by taking
photos of column and measuring the sizes of the drops.
Table 1 shows the principle experimental conditions.
The density and viscosity of each phase were measured
with pycnometers and Ostwald viscometers.
Table 1 Experimental condition
No.

0.03

EC1
EC2

H [-]

0.02

0.01

solvent: MeOH aq.

feed: AO

0

R t [kg・m ・h ]y MeOH,b [-]E b [kg・m ・h ]500〜2500
500〜2500

0.73±0.03
0.73±0.03

1600±1003200±100

-2

EC1
EC2

-1

-2

-1

Absorption oil
Aqueous methanolic solution
Raffinate phase
Extract phase-31040~1100
870
1100
885~890104

dp [m]

0.002

0.001
Key Run No.
EC1
EC2

0
102

103

104

Rt [kg・m-2・ h-1]

Fig.4 Drop diameter of dispersed phasemass fraction, x i ,t [-]0.025~0.071
0.007~0.020
0.017~0.036
0.025~0.030
0.093~0.103
0.230~0.254
0.064~0.072
0.105~0.125
0~0.012density [kg・m ]103
Rt [kg・m-2・h-1]

Fig.3 Holdup of dispersed phase

103
Key Run No.

a [m2・m-3]

EC1
EC2

3.2. Operability
3.2.1. Density and viscosity
Table 3 shows the densities and viscosities of thematerials. The density of the dispersed phase was larger
than that of the continuous phase. The viscosities of
MeOH aq. and the extract phase were same.
Table 3 Densities and viscosities of materials
materials

102

0.003

3. Result and discussion
3.1. Composition of absorption oil
Table 2 shows the compositions of feed AO. The
compositions of the feed AO changed every runs,
because the raffinate phase in the previous run wasrecovered and used as feed in the next run. If necessary,
fresh AO was added to the recovered raffinate phase. The
ranges of compositions of nitrogen compounds werelarge, because the transferred amounts to continuous
phase were high.
Table 2 Compositions of feed AO
component i
Quinoline, Q
Isoquinoline, IQ
Indole, IL
Naphthalene, N
1-Methylnaphthalene, 1MN
2-Methylnaphthalene, 2MN
Biphenyl, BP
Dibenzofran, DBF
Methanol, MeOH

Key Run No.

102

101

100
102

103
104
Rt [kg・m-2・h-1]

Fig.5 Specific interfacial area
calculated by,(3.1)
a=6H/dp
Figure 5 shows the results of a. a increased with Rt anddecreased slightly with an increase Eb.
3.3. Separability
3.3.1. Composition of extract phase
Figure 6 shows the result of compositions in the extract
phase, yi,t. yi,t of nitrogen compounds were higher thanthose of other compounds. In the range of Rt<1500, yi,t ofnitrogen compounds increased with Rt, and in the rangeof Rt>1500, the changes of yi,t were small. This was
because yi,t of nitrogen compounds reached equilibriumcompositions in the range of Rt>1500. yi,ts of othercompounds were almost constant against Rt because
those reached equilibrium compositions.
3.3.2. Yield
Yield of component i, Yi, was defined as(3.2)
Yi =Et･yi,t/(Rt･xi,t)Figure 7 shows the results of Yi . Yi decreased with anincrease in Rt. yi,t increased with Rt and yi,t almost
approached yi,t*. However, Rt became bigger than theviscosity [cP]at 290K
1.533
1.533

3.2.2. Behavior in the column
In all runs, entrainment of the dispersed phase drops
into the continuous phase and flooding were notobserved. The substantial mass transfers of thesecompounds could be detected with this bench scalecolumn of which effective contact height was 0.495m. In
the range of higher Rt, the drops were falling down with
zig-zag movement and the coalescence of the dispersed
phase and axial mixing were observed.
Figure 3 shows the results of the holdup of dispersed
phase in the column, H. H increased with Rt. Figure 4
shows the results of the drop diameter, dp. dp decreased
with an increase in Rt. Specific interfacial area, a, was58Technical Report of International Development Engineering

IQ

i

10 2

Key Run No. i
Key Run No. i
EC1
EC1
1MN
BP
EC2
EC2
EC1
EC1
2MN
DBF
EC2
EC2

IL
N

10 -1

10 -1

(a)

10 1
(a)

(b)

i/2MN [-]Q

Key Run No.
EC1
EC2
EC1
EC2

i/2MN [-]i

Key Run No.
EC1
EC2
EC1
EC2

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

10 1

10 0

(b)

10 -2

10 0
10 2

yi,t [-]

yi,t [-]

10 -2

10 -3

103

10 4

10-1
10 2

104

104
(b)

104

Rt [kg・ m-2 ・ h-1 ]

10 3

104

R t [kg・ m-2・ h-1 ]Fig.6 Composition of extract phase(a) in EC1, (b) in EC2
0.6

0.1

(a)

(b)

Kc,i [kg・m-2・h-1]

10 -4 210

Kc,i [kg・m-2・h-1]

(a)
10 3

104

R t [kg・m-2 ・h-1 ]Fig.8 Separation selectivity relative to 2MN(a) nitrogen compounds, (b) other compounds(keys are the same as Fig.6)

10 -3

10 -4 2
10

103

R t [kg・m-2 ・h-1 ]

103

102

103

102

0.5
0.075

101
102

Yi [− ]

Yi [− ]

0.4
0.3

0.05

0.025

0.1
0

102

103

101 2
10

103
104
-2
-1
Rt [kg・m ・h ]Fig.9 Overall mass transfer coefficient based oncontinuous phase concentration(a) nitrogen compounds, (b) other compounds(keys are the same as Fig.6)

0.2

0

103
104
-2
-1
Rt [kg・m ・h ]

102

103

104

Fig.7 Yield(a) nitrogen compounds, (b) other compounds(keys are the same as Fig.6)

did not change so much, and in the range of Rt>1500, Kc,idecreased with an increase Rt. This was because the axial
mixing of the dispersed phase in the column was
occurred. Kc,i also increased with Eb. Kc,i of nitrogencompounds was smaller than that of other compounds.

increase of the transferred amount of these components.
Yi slightly increased with Eb. The maximum Yi values ofnitrogen compounds and other compounds were 0.5 and
0.1.
3.3.3. Separation selectivity
The separation selectivity of component i relative to
2MN, i/2MN, was defined as(3.3)
i/2MN=(yi,t/y2MN,t)/(xi,b/x2MN,b)Figure 8 shows the results of i/2MN. i/2MN did notchange so much as Rt changed. i/2MN of nitrogencompounds and other compounds were around 15 and 1.
This was because the difference between the distribution
coefficients of nitrogen compounds and othercompounds was about 10 times. Therefore, thedistribution coefficients affected i/2MN.
3.4. Mass transfer rate
3.4.1. Overall mass transfer coefficient
The overall mass transfer coefficient based on thecontinuous phase concentration, Kc,i, was calculated by,(3.4)
d(E･yi)/dz=−Kc,i･a･(yi *−yi )The equilibrium composition, yi *, was calculated by,(3.5)
yi *=mi･xi
where mi (=yi,1/xi,1) was distribution coefficient and thevalue estimated in previous6) study was used. Figure 9shows the results of Kc,i . In the range of Rt<1500, Kc,i

3.4.2. Correlation of mass transfer coefficient
In previous work6), the mass transfer within continuous
phase was more dominant than within the dispersed
phase in the overall mass transfer. The mass transfer
coefficient in the continuous phase, kc,i, was, thus,
assumed to be equal to Kc,i and compared with theprevious correlations7,8). Thorsen and Terjesen havecorrelated the continuous phase mass transfer
coefficients from the single drop to the continuous phaseby using NRe, NSc and NSh as:
NSh = 178 + 3.62!NRe1/2!NSc1/3
This equation was applied to the mass transfer by theinternal circulation of the drop. They confirmed the rigid
drop by the addition of surfactants. Garner andSuckling8) used solid spheres as dispersed phase drops
and obtained the correlation below:
NSh = 2 + 0.95!NRe1/2!NSc1/3
This was applied to the mass transfer of rigid sphere
drop.
Here, NRe, NSc and NSh are expressed as follows;(3.6)
NRe= cudp/ ! c(3.7)
NSc= ! c/ cDi(3.8)
NSh=kc,idp/Di
u is slip velocity in the column and obtained from below
equations.

Rt [kg・ m-2 ・h-1]

104

Rt [kg・ m-2・ h-1]59Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

ud=Rt/( dH)(3.9)(3.10)
uc=Eb/{ c(1-H)}(3.11)
u=ud+uc
The diffusivities of component i were determined byusing Wilke-Chang equation.
Di =7.4×10-8(BMc)1/2T/( ! cvi0.6)(3.12)
NSh is plotted versus NRe1/2×NSc1/3 in Fig.10. In this study,
NSh increased with increasing NRe1/2×NSc1/3. The results inthis study were closer to the correlation by Thorsen andTerjesen than to that by Garner and Suckling. So, it was
confirmed that in this separation system of AO the masstransfer occurred by the internal circulation of thedispersed drops. NShs of nitrogen compounds were below
the two lines. Meanwhile, NShs of other compounds wereabove the line of Thorsen and Terjesen. In this work, thissystem was of multi-components and this should makethe mass transfer process more complicated. In this case,it was assumed for the mass transfer to be controlled by
the continuous phase and this assumption might not beable to fully explain this situation, causing the NSh trend.

Nomenclaturesa: specific interfacial area
[m2･m-3]
B : associated factor of solvent[-]
D : diffusivity[m2･h-1]
E: superficial mass flow rate of continuous phase[kg･m-2･h-1]
H : holdup of dispersed phase[-]
Kc : overall mass transfer coefficient based ofcontinuous phase concentration[kg･m-2･h-1]
mi : distribution coefficient of component i[-]
M : molecular weight[kg･mol-1][-]
NRe : Reynolds number[-]
NSc : Schmidt number[-]
NSh : Sherwood numberR: superficial mass flow rate of dispersed phase[kg･m-2･h-1]
T: temperature[K]u: velocity of fluids[m･h-1]v: molecular volume at standard boiling point[m3･mol-1]
x: mass fraction in oil phase[-]y: mass fraction in aqueous phase[-]y* : equilibrium mass fraction in aqueous phase[-]Y: yield[-]z: distance from top of the column[m]"i/2MN: separation selectivity of component i relative to
2MN[-]: density[kg･m-3][cP]! : viscosity<Subscripts>
1: at equilibrium
1MN : 1-methylnaphthalene
2MN : 2-methylnaphthaleneb: at bottom of the columnBP: biphenyl
DBF: dibenzofuranIL: indole
IQ: isoquinolinei: component i
MeOH : methanolN: naphthaleneQ: quinolinet: at top of the column

5. Conclusion
The separation of AO with continuous countercurrent
spray column was favorably carried out. The yields, Yi,
and selectivity, i/2MN, were about 0.5 and 20 at
maximum, respectively. It was confirmed that nitrogencompounds could be selectively separated.
The overall volumetric mass transfer coefficient basedon the continuous phase concentration, Kc,i ･a increased
with Rt. The correlation of the continuous phase masstransfer coefficients approximately corresponded to theequation obtained by Thorsen and Terjesen. The
disagreement of the mass transfer coefficient correlationof nitrogen compounds was due to the difference of therange of NSc.
Acknowledgment
AO was provided by JFE Chemical Corporation.

7)

Thorsen and Terjesen
8)
Garner and Suckling

300

200
N Sh [-]

Reference

1) Egashira, R., Nagai, M., Sekiyu Gakkaishi (J. Jpn.
Petrol. Inst.), 43, (5), 339 (2000)
2) Egashira, R., Salim, C., Sekiyu Gakkaishi (J. Jpn.
Petrol. Inst.), 44, (3), 178 (2001)
3) Salim, C., Saito, J., Egashira, R., Journal of the Japan
Petroleum Insititute, 48, (1), 60 (2005)
4) Salim, C., Journal of the Japan Petroleum Insititute,49, (6), 326 (2006)
5) Egashira, R., Solv. Ext. Res. Dev. Jpn., 14, 63 (2007)
6) Egashira, R., Journal of the Japan Petroleum Insititute,50, (4), 218 (2007)
7) Thorsen and Terjesen, Chem. Eng. Sci., 17, 137 (1962)8) Garner and Suckling, Aemr. Inst. Chem. Eng. J. 4, 114(1958)

100

0
0

50

100

150

NRe1/2 ×NSc1/3 [-]Fig.10 Correlation of continuous phase masstransfer coefficients(keys are the same as Fig.6)

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TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

EXTRACTION OF TEXT AREA USINGSCALE INVARIANT FEATURE TRANSFORM
Student Number:07M18125

Name:Jo Matsuda

Supervisor: Yukihiko Yamasita

SIFT アルゴ リ ズ ム を 用いた 文字領域特定松田 穣
携帯電話のカ メ ラ やデジ タ ルカ メ ラ の普及， その高解像度化に 伴い， それら を 入力手段と する 文書画像解析， 文字認識への期待が 高ま り つつあ る 。 そこ で本研究では Scale-Invariant
Feature Transform(SIFT) を 利用し た 文字領域抽出・ 認識法を 提案する 。
SIFT は， 特徴点の検出と その点の特徴量を 抽出する 手法であ る 。 SIFT によ り 検出さ れる 特徴点やその特徴量は， 画像の回転・ ス ケ ール変化・ 照明変化等に頑健であ る ため， 環境の変化に対し て 頑健性を 持つ文字領域抽出・ 認識の実現が 期待でき る 。 本研究では， SIFT を 利用
し た 文字領域抽出プ ロ グ ラ ム を 作成し ， その性能確認実験を 行っ た 。

1

3 OVERVIEW OF SIFT

INTRODUCTION

Scale-Invariant Feature Transform (SIFT) is amethod for detecting and extracting local feature descriptors that are reasonably invariant to changes inillumination, image noise, rotation, scaling, and smallchanges in viewpoint. We will explain the algorithmof SIFT.

Recently, the digital camera and the digital video
recorder are miniaturized and have very high resolution. Such features are progressing rapidly and many
functions are added to them. The digital camera canbe used to acquire character information from the environment.
The digital camera and the cellular phone are very
attractive as instruments for the character recognition and the document analysis. Different from thetwo-dimensional environment for a scanner, the threedimensional environment for such instruments has
many difficulties such as background, deformation,lighting and so forth.
To solve such problems, we propose a new character area extraction method using Scale-Invariant Feature Transform algorithm[1] [2]in this research.

2

3.1 Algorithm of SIFT
The processing of SIFT consists of two stages. Thatis, the detection of the key point and the descriptionof the feature. SIFT is done by the following flows.
1) Detection of scale and key point.
2) Localization of key point.
3) Calculation of orientation.
4) Description of features.
In 1), the scale and the key point candidates are detected by the DoG (Different of Gaussian) processing.
In 2), from the candidates, the key point are chosen
by it’s main curvature. Next, the sub-pixel-position is
specified. In 3), for the calculation of the orientation,
the histogram is generated from gradient informationon the key point. The orientation is calculated fromthe histogram. The invariance of rotation is obtainedby this operation. In 4), the area for describing features is rotated in the direction of the orientation previously determined. Afterwards, the the features arecalculated by using gradients within the rotated area.
The feature vector is normalized at the end. Becauseof normalization, the influence of light and shade are
eliminated.

OVERVIEW OF TEXTANALYSIS

Recently, the accuracy of optical character recognition has reached to high level. Usually in opticalcharacter recognition, the image of document is takenby the scanner, and it is converted into the form that
we can edit in the computer. The recognition of theLatin typed document is practical. However, the technology that extracts the character from the scene image with a digital camera and a portable camera is still
incomplete.

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d1 < wd2(2)

d1 : T he distance o f the nearest pointd2 : T he distance o f the second nearest pointw : threshold

4.4 Selection match point
Figure 1: orientation

According to the difference of fonts, the matching condition is loosely set. Therefore, the matchedpoints exist except in the text area. Then, we selectmatched points by the parallel relation and their density. In order reduce the number of matched points,
we select a matched point that has other matchedpoints in its neighbor such that the segment between
the two key points of the matched point is parallelto those of matched points. Then, isolated matchedpoints are discarded. By using Gaussian filter a highdensity region of matching points are extracted.

4.5 Binarzation

Figure 2: feature vector

4

Proposed technique

4.1

Over view

The area is separated by overlapping blocks. The
blocks in which the integral of the filtered density ofmatching points calculated on section 4.4 excess thethreshold is labeled as a character region.

5 Experimental Results

The proposed technique aims at the text extractionthat is robust to rotation, scale, and lighting changes.
A flow of the process is described as follows.
1) the feature vector is described with the detection of the key point by SIFT. 2) The key points
in the learning data and input data are matched. 3)
Matched point is selected from them by using the eachother position. 4) the area where the density of match
points is thigh is extracted. 5) The extracted area is
Binarized. Afterwards, a final text area is extracted.

4.2

5.1 Experiment using various type ofimage
The experiment is conducted by using the various
images. The types of images used in this experiments
are scene images, web image and poster image. We
used five images for each experiments. And the representative results are shown as following figures.

Feature vector

The feature vector for input and learning images are
extracted by SIFT.

4.3

Matching

The matching is done by comparing the feature
vectors. The pair of feature vectors of which distanceis the smallest is extracted as matched points. The
distance is evaluated by the following expressions.
kI1

kI2

d(v , v ) =

s

128

∑

kI
kI
(vi 1 − vi 2 )2*The area around red line is extracted area
Figure 3: scene image

In Figure 3, it includes natural background information. In Figure 4, it includes the informationof web object. In Figure 5, it is conducted to check

(1)

i=1

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Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)*The area around red line is extracted area
Figure 4: web image*The area around red line is extracted area.
Figure 6: symmetric 1*The area around red line is extracted area.
Figure 5: poster image*The area around red line is extracted area.

the resistance for the poster image. From the experiments result, we can say the proposed system extracts
target text area in many case(scene image=4/5 web
image=3/5 poster image=4/5). And, the proposedsystem extract target area completely in their experiments.
However, the proposed system was not able to defect precisely when the font size is too small, proximity background is complex, the target image has lots,
and the target text uses special font. For example, thefont size is too small in the Figure 4. Then, the nontarget text area is included.

5.2

Figure 7: symmetric 2

Experiment using added change
image

In the following experiment, changes are added tothe original images. The changes used in this experiment are symmetric transformation, rotation, reduction and expansion, lighting, and projective transformation.
In Figure 6 and 7, the robustness for symmetrictransformation is examined. In Figure 8, the robustness for rotation is examined. In Figure 9, the robustness for projective transformation is examined. In
Figures 10 and 11,the robustness for scaling is examined. In Figures 12 and 13, the robustness for lightingchange is checked.

*The area around red line is extracted area.
Figure 8: rotation=90degree

From the results, the proposed system shows robustness in many case (Figure 6, Figure 7, Figure 8,
Figure 10, Figure 12, Figure 13). For the reduction

63Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)*The area around red line is extracted area.

*The area around red line is extracted area.

Figure 9: Projective transformation=20degree

Figure 12: Lighting change1(Figure 11), it does not extract completely. Because
the target font size in reduced image is too small. But
target areas are extracted more than 70 percent.
However, for the projective transform(Figure 9),
it does not extract precisely, when the text includes
characters that are symmetric to each other.

*The area around red line is extracted area.
Figure 13: Lighting change2

6 Conclusions
We proposed a new character area extraction
method that uses SIFT. We show its robustness forimage transformation, and lighting change.
For future tasks, we have to develop a method thathas a robustness against projective transformation.
*The area around red line is extracted area.

REFERENCES

Figure 10: expansion[1] D. G. Lowe:Object recognition from local scaleinvariant features, IEEE International Conference on Computer Vision (ICCV), pp.11501157(1999)[2] Hironibu Fujiyoshi: Extract feature vector by
gradient base -SIFT and HOG- , PRMU, pp.511517(2007)*The area around red line is extracted area.
Figure 11: Reduction

64Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

CORRELATION ANALYSIS OF COHERENT TURBULENCE OVER REDUCEDURBAN MODEL
Student Number:07M18131

Name: Ayako MARUYAMA Supervisor:Manabu KANDA

屋外模型都市に お け る 乱流構造の 時空間解析
丸山綾子

本論文では，屋外模型都市において発達する 乱流構造の時空間解析を 行う こ と によ っ て，渦の移流速度を 算出し ，乱流構造の時間と 空間の対応関係を 明ら かにし た．さ ら に相関係数の水平形状から 乱流構造の定量化を 試み, 地表面形状と の比較を 行う こ と で地表面形状によら ない乱流構造の相似性が明ら かと なっ た．

1 Introduction

C2

C1

Recently, various environmental problems in urban
cities, such as heat island and concentrated heavy rain,
were observed. Urbanization significantly impact thetransport processes of momentum, water vapor and heat.
Various studies reveal that these processes are dominatedby turbulent coherent structures (Inagaki and Kanda [1]).
For a flat surface, Adrian et al. [2] indicated theschematic diagram of the coherent strucures using PIV(particle image velocimetry） measurements. In addition,these structures were also observed over vegetation
canopies (Finngan [3]). Nevertheless, there is a dearth ofresearch quantifying coherent structures due to thedifficulty of establishing relationships between spatial
and temporal aspects of such structures. In the present
study, I investigated these relationships by evaluating the
spatial and temporal scales of these structures, andcomparing with other studies. Furthermore, we evaluatedthe convective velocity over the reduced urban model.
The convection velocity Uc is instrumental in Taylor’s
hypothesis, which converts temporal data to spatial data.
This hypothesis is the time-history of the flow signal
measured from a stationary probe, and regards theconvection flow as a ‘frozen’ spatial pattern of
turbulence past the probe. The mean wind velocity U
is approximated by the value of Uc in Taylor’s
hypothesis. Yet, various studies suggested the Taylor’s
hypothesis does not work on various surface conditions.
Shaw et al. [4] found that Uc / U =1.2 at a height of 2
times the vegetation canopy by using correlation

S1

S2

S3

S4

S5

S6
Flow

Figure 1 COSMO

analysis, while Castro et al. [5] yielded Uc / U =1.3 atthe canopy height using wind tunnel experiment with astaggered pattern of cubes.

2 Experimental methods
2.1 COSMO
The experiments were conducted at the COSMO(Comprehensive Outdoor Scale Model), Nippon Instituteof Technology, which was constructed for urban climate
studies. The floor area is 50m by 100m, covered withconcrete cubes of 1.5-m dimension (H) to represent
urban type roughness, arranged in a symmetrical andaligned pattern with an area coverage density of 25%(Fig.1).
2.2 Installation of the instruments
Figure 1 shows the installation positions of instruments
for the 3 cases. For case 1, 15 anemometers were locatedat each spanwise-line through C1 and C2. For case 2, 4
sonic anemometers were located at S3, S4, S5, and S6,along with 7 other probes arranged in a spanwise-line

65Technical Report of International Development Engineering

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That is to say, the outer-scale motion is evaluated from[u ] , and the inner-scale motion is evaluated from u "s" .
3.3 Filtering condition
I set thresholds for turbulent intensity (<0.5), winddirection ( ± 10 degree) and stability (neutral)
exclusively for the S6 probe. Furthermore, mean velocity
increment of 0.5 (m % s $1 ) from 0.5 (m % s $1 ) was selected.
Additional threshold values for all probes were set as
follows: mean temperature (0< T <50), momentum( u "w" <0), and angle of elevation (±15 degree). Numberof samples per threshold velocity range are shown in
Table 2.

aligned to S6. Case 3 is similar to case 2, except thatprobes at S1 and S2 replace those at S4 and S5,
respectively. The spatial intervals of each probe dx are
shown in Table 1. For simplification, I substituted
symbols for each dx . All anemometers were located at
2H (H: canopy height). Sampling frequency is 10Hz forcase 1, and 50Hz for cases 2 and 3.
Table 1 Spatial intervals of each probe
symbol
D6
D9
D14
D22
D27
D36
D50
D66
D84

dx
(m)
5.6
8.85
14.45
21.55
27.15
36
50.35
65.85
84

instrument number
leewardwindward
S5
S4
S6
S5
S6
S4
S4
S3
S5
S3
S6
S3
S6
S2
S6
S1
C1
C2

Table 2 Number of samples per threshold velocity range

threshold velocity (m /s )0.5〜1.0
1.0〜1.5
1.5〜2.0
2.0〜2.5
2.5〜3.0
3.0〜3.5
3.5〜4.0
4.0〜4.5
4.5〜5.0
5.0〜5.5
5.5〜6.0
6.0〜6.5

3 Analytical Procedures
3.1 Definition of space-time correlations
Two-point correlation coefficients were calculated asfollows,Ruu !

u (r , t )u (r dr , t dt )(1)

Number of sample
case1
case2
case3
neutralneutralneutral
3
5
4
14
23
9
12
37
3
7
43
3
6
45
4
9
9
7
7
5
2
2
-

u 2 (r , t ) u 2 (r dr , t dt )4 Results

where r represents the position with spatial coordinates( x, y, z ) , t is time, dr is the distance between 2
points, dt is the time lag. Ruu , Rvv , and Rww arecalculated from velocity fluctuation components for the
streamwise, spanwise and vertical directions ( u " , v" , w" ).
3.2 Computation approach
The convection velocity is calculated using theequation:
Uc ! dx / #(2)
where # is the time delay required to maximize thespace-time correlation. Specifically for D84 (case 1),
decomposition of inner- and outer-scales described by
Inagaki and Kanda [1] was used, with the following
equation:u ! [u ] u "s u "s"(3)
where the square brackets represent spatial averaging,the over-bar symbolizes temporal averaging, the prime
represents spatial fluctuation, and the double prime
indicates the temporal and spatial fluctuation component.

4.1 Convection velocity for 30-min averaging time
Figure 2 shows a comparison of Uc computed fromtwo-point correlations (Equation (2)) and the local mean
streamwise wind velocity calculated from u " .
The scattered plots indicate that the Uc exceed themean wind velocity. When the distances between
instruments are relatively close (D6 to D14), thecorresponding plots are closer to the 1:1 gradient-linewith respect to the other plots. The plots for D84 arelinear and exceed the 1:1 gradient-line, indicating thatthe outer-scale eddies significantly exceed the mean
wind speed. Furthermore, the plots corresponding tolarge dx (>22 m) gather near the 1:1.6 approximation
line. This suggests that the Uc of inner- and outer-scaleeddies can be distinguished by the spatial interval size. It
can be deduced that small interval-sized plots (D6 toD14) represent inner-scale Uc because it seems that the66

Technical Report of International Development Engineering

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12

12

10

1:1.6

10

dx / " ( m ! s 1 )dx / " ( m ! s 1 )

(a')

1:1.6

(a)

8
1:1
6
4

D6
D14
D27
D50
D84

2

8
1:1
6
4

D9
D22
D36
D66

D6
D14
D27

2

0

D9
D22
D36

0
0

2

4

U (m ! s 1 )

6

8

0

2

4

U (m ! s 1 )6

8

Figure 2 Convection velocities computed from time lag

Figure 3 Convection velocities computed from time lag

Each scattered plots for the distance between probes; solid line

Each scattered plots for the distance between probes; solid line

is 1:1 line; dashed line is the approximation line of D84

is 1:1 line; dashed line is the same line of Fig.2

eddies involved retain their shape in the streamwise
direction. On the other hand, larger interval-sized plots(D27 to D84) appear to capture outer-scale Uc , wherein
the corresponding inner-scale eddies do not retain theirshape due to their shorter life-time. Therefore, thecorrelation of outer-scale motion becomes stronger thanof inner-scale motion.
4.2 Convection velocity for 3-min averaging time
To clearly distinguish the inner- and outer-scale eddies
associated with Uc , I reduced the averaging time from30 minutes to 3 minutes. The reduced averaging timeallows us to focus on the inner-scale motion, which has
smaller time scale than the outer scale motion, by
eliminating large-scale motions which are included in themean component of this shorter time average.
Figure 3 shows the result of this 3-minute averaging
calculated from u # . The difference in Uc previously
observed in Figure 2 is more obvious since there is now
less scatter around the corresponding approximationlines. The 3-minute plots of D6 to D14 are closer to 1:1
line, while the 3-minute plots of D27 and D36 vary lessthan the 30-minute plots. This verifies that the smaller
averaging time eliminates the influence of eddies withfrequencies greater than 3 minutes. Nevertheless, theinfluence of outer-scale motion is still apparent for large
interval plots.
4.3 Comparison with other studies
The Uc from the previous plots are shown in Table 3.
These are approximated from the gradient ofTable 3 Convection velocity

Uc / U
u#

〜D14
1.3

D84
1.6

approximation lines using the 3-minute plots of D6 to
D14 for the inner-scale, and the 30-minute plot of D84
for the outer-scale, respectively. These Uc ’s are fasterthan the mean wind velocity, especially for theouter-scale motion. Considering inner-scale fluctuationand outer-scale fluctuation are independent and have nointeraction with each other [6], and the structure
attributed to the inner-scale eddies [7], it was considered
the structure above COSMO is transported by the
inner-scale convection velocity.
This inner-scale Uc agrees with other studies, such thatover vegetation ( Uc / U =1.2: Shaw et al. [4],Uc / U =1.3: Su et al. [8])) and rough surfaces( Uc / U =1.3, Castro et al. [5]). These indicate that theconvective velocities of the inner-scale motions are
similar over vegetation and COSMO.
4.2 Horizontal distribution of correlations at 2H
Figure 4 shows a comparison of horizontal distribution
computed from two-point correlations of ( u # , v# ). The
horizontal axis is the converted time scale to length scaleusing mean wind velocity and normalized by H. ‘TD’
represents the outer-scale motion, and ‘SD’ represents
the temporal and spatial fluctuation in Equation (3). It
can be observed from Fig.4(a)-(b) that the influence of67

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-0.5
5

y/H

-2
5

1
5

（a）TD _ Ruu-25（b）TD _ Rvv

-2
-12

-6

0
x/ H

6

12

（c）SD _ Ruu（d）SD _ Rvv

-2
-12

-6

0
x/ H

6

12

Figure 4 Correlations in the horizontal plane
TD: including outer-scale fluctuation SD: remove outer-scale fluctuation

the outer-scale motion is elongated in the streamwise
direction. The shape of Rvv distribution is more roundedsince the coherent structure is meandering. Outer-scale
motion does not affect w fluctuation (not shown).
4.3 Quantification and Comparison
From Fig.4(c), the length in streamwise direction is
11.0H using Uc / U =1.3. Calculating the spatial andtemporal scales of the coherent turbulence from SD, thehorizontal to vertical ratio is 9:2. Using Uc / U =1.3, theratio becomes 11:2. This is shown that the conveciton
velocity is important parameter for quantification.
Furthermore, this result is in agreement with the findingsof LES over rough surface of Zhang [9] (2H), windtunnel over vegetation of Shaw et al. [4] (H) and windtunnel over flat surface of Ganapathisubramani et al.
[10].These results suggest that the structure of
inner-scale motion is geometrically similar regardless of
surface condition.

References[1] Inagaki, A. and Kanda, M.: 2008, ‘Turbulent flow similarity
over an array of cubes in near-neutrally stratified atmospheric
flow’, J. Fluid Mech., 615, 101-120.
[2] Adrian, R. J., Meinhart, C. D. and Tomkins, C. D.: 2000,‘Vortex organization in the outer region of the turbulent
boundary layer’, J. Fluid Mech., 422, 1-54.
[3] Finnigan, J. J.: 2000, ‘Turbulence in Plant Canopy’, Annu.
Rev. Fluid Mech., 32, 819-571.
[4] Shaw, R.H., Brunt, Y. and Finnigan, J.J and Raupach, M.R.:
1995, ‘A wind tunnel of flow in waving wheat: two-point
velocity statistics’, Boundary layer meteorology, 76, 349-376.
[5] Castro, I. P., Cheng, H. and Reynolds, R.: 2006,‘Turbulence Over Urban-Type Roughness: Deductions From
Wind-Tunnel Measurement’, Boundary layer meteorology,
118, 109-131.
[6] McNaughton, K. G. and Raubach, J.: 1998, ‘Unsteadiness asa cause of non-equality of eddy diffusivities for heat andvapour at the base of an advective inversion’, Boundary-Layer
Meteorol., 88, 479-504.
[7] Inagaki, A.: 2008, ‘Atmospheric turbulence over an array ofmassive cubes’, Phd thesis, Tokyo Institute of Technology.
[8] Su, H. B., Shaw, R.H. and Kyaw tha paw u: 2000,‘Two-point correlation analysis of neutrally stratified flow
within and above a forest from large-eddy simulation’,Boundary layer meteorology, 49,423-460.
[9] Zhang, J.: 2009, ‘LES study on hierarchical turbulence
organized structure above urban canopy’, Master thesis, Tokyo
Institute of Technology.
[10] Ganapathisubramani, B. et al.: 2005, ‘Investigation oflarge-scale coherence in a turbulent boundary layer using
two-point correlations’, J. Fluid Mech., 524, 57-80.

5 Conclusions
The conclusions of this study were summarized asfollows:
1. The inner-scale convection velocity is 1.3 times fasterthan the mean wind velocity at 2H, and that ofouter-scale is 1.6 times faster at COSMO.
2. At COSMO, the horizontal to vertical ratio of thestreamwise structure is 11:2. The ratio is in good
agreement with studies for vegetation canopy and LES ofrough and flat surface.
These results indicate the coherent structures of
inner-scale motions are similarity irrespective of thesurface conditions.

68Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

System to Make Teaching Materials
Based on Collective Intelligence
Student Number: 07M18148

Name: Mandana AMIR KHOSRAVI Supervisor: Yukihiko YAMASHITA

集合知に基づく 教材作成シ ス テ ム
ア ミ ル ホ ス ラ ビ マン ダ ナ
テキ スト ベース の e-Learning を 実現する tobe シ ス テ ムと ， Wiki の概念を 取り 入れた ， 集合知に基づく 教材作成シ ス テ ム を 構築する 。 Wiki を 使う こ と によ っ て e-Learning の教材の作成を 行い，維持管理問題を 解決し て いる 。 Wiki シ ス テ ム は， 世界中の多数の人々が 参加する こ と によ っ て ，
広範囲で詳し い情報を 持続的に提供する 。 本研究では， Wiki の考え 方に基づき ， 特別な IT ス キル
を 必要せず， ネッ ト ワ ーク 上で多数の人々が 容易に 1 つの教材の作成に参加する こ と ， 及び， 利
用する こ と を 可能にする シ ス テ ム を 構築する 。

2 e-Learning

1 Introduction

Electronic Learning (or e-Learning)[1] is a typeof technology supported education/learning, where
the medium of instruction is computer technology, particularly involving digital technologies. eLearning has been defined as "pedagogy empowered by digital technology". e-Learning is usedinterchangeably in a wide variety of contexts. In
companies, it refers to the strategies that use thecompany network to deliver training courses to employees. Lately in some universities, e-Learning isused to define a specific mode to attend a course orprograms of study where the students rarely attend
face-to-face for on-campus access to educational
facilities. Table 1 shows the e-Learning history.

After 1990, due to the innovations of Information
Technology, utilization of equipments like PC has
become widespread among general households.
Then nowadays, according to development of theInternet and WWW, we can exchange information
regardless of time and place. And utilization of
e-Learning system gives a chance to learners to
use PC for learning anytime and anywhere. But
the problem is that to make teaching materials for
e-Learning, not only teaching methodology skill
but also IT skill are necessary, and correction andchanging of materials are difficult. Therefor making materials costs much. Furthermore, using Wikisystems gives an opportunity to people around theworld to exchange their information. And according to Wiki philosophy, applying Wiki does notneed any especial skill, and making materials in agroup is possible. However, Wikis are static pages,
thus Wikis cannot be an effictive learning/studing
system.

3 tobe system
The tobe system[2] is a system to change the textbase data to animation. In the tobe system, theplayer that does this conversion is called Expositor . In this system all the data are written in textbase, therefor the correction and changing data areeasy. And Expositor makes a situation similar toreal classroom on the PC screen. Expositor just canread the text which is written in the tobeML language. The tobeML is a markup language basedon XML which is defined originally for this system.
When a learner plays the Expositor, Fig.1 ap-

Then in this research, we proposed a new system, combined the tobe (Text Oriented Bi-Stream
Explanation) system and Wiki system. The tobesystem is an text-base learning system that makes
animation from tobe text. The tobe text has to be
written in tobeML (XML based markup language).
Then, its combination with Wiki enables to createa tobe text easily in a group via a network.
1
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and competition of many individuals. CI can also
be defined as a form of networking enabled by therise of communications technology, namely the Internet. Web 2.0 has enabled interactivity and thus,
users are able to generate their own content. Collective Intelligence draws on this to enhance thesocial pool of existing knowledge. Communications tools enable humans to interact and to shareand collaborate with both ease and speed. With thedevelopment of the Internet and its widespread use,the opportunity to contribute to community-basedknowledge forums, such as Wiki systems become
possible.

Table 1: e-Learning history
first
generation

secondgeneration

third
generation

CBT(Computer Based Training):
Have to install materials
directly to the PC or use
CDs, learners can study in any
where and at any time, but the
problem is information exchanging is just one-way.
WBT(Web Based Training):
Using web browser, and using
network makes a possibility
to have two-way learning.
LMS(Learning Management System):
In addition to WBT functions,
we can manage the records andand check the learners’ progress.

4.1 Wiki

Wiki[4] is a Hawaiian word for "fast". "Wiki Wiki"is a reduplication. A wiki is a page or collection of Web pages designed to enable anyone who
accesses it to contribute or modify content, using
a simplified markup language. Wikis are often
pears on the screen. As you can see in Fig.1 the used to create collaborative websites and to power
tobe system includes three main parts, board, pro- community websites. The collaborative encyclofessor with pointer and talk part (the part that pro- pedia Wikipedia is one of the best-known wikis.
fessor explains by voice).
Wikis are used in business to provide networks andknowledge management systems. Ward Cunningham, the developer of the first wiki software, WikiWikiWeb, originally described it as "the simplest
online database that could possibly work".
Wiki is a piece of server software that allows
users to freely create and edit Web page content
using any Web browser. And Wikis have a simple
text syntax for creating new pages.

Fig. 1: tobe system
However making materials in tobeML language
is not easy and the data creator has to memorize
tobeML tags. To solve this problem, in this research we proposed the tobeWiki system.
Fig. 2: Wiki and general web page

4

Collective Intelligence

And the main characteristics of Wiki are:Collective intelligence (CI)[3] is a shared or groupintelligence that emerges from the collaboration• Wiki invites all users to edit any page or tocreate new pages within the wiki Web site.
270Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)• Wiki promotes meaningful topic associations
between different pages by making page linkcreation almost intuitively easy and showing
whether an intended target page exists or not.
• Ordinarily, the structure and formatting ofwiki pages are specified with a simplified
markup language, sometimes known as "wikitext". For example, starting a line of text withan asterisk ("*") is often used to enter it in abulleted list.

5

Proposed system

The proposed system, the tobeWiki system, is the
combination of the tobe system and the Wiki system. In this system we define the formatting rules
for tobeWiki to make teaching materials easily ina group. And after making materials as a text on
Wiki, the text-base data will be changed to the tobe
text and tobeML tags will be added to the Wiki text
automatically to be readable in Expositor. Fig.3 illustrates the tobeWiki system. To define wiki formatting rules, we used simple symbols. The defined formatting rules on tobeWiki are as below.
• To make the header part: we put the title, author, panel size and professor character information in the bracket and divide up them by“/”.
[title/author name/panel size/professor character]• To make the board part (the part which is going to appear on the board): in this part, on the
Wiki pages we use simple symbols to maketext-base data which are going to appear on
the board. The symbols are listed in Table 2.
• To make the talk part (the part that professor isgoing to explain by voice): in this part, on the
Wiki pages we use simple symbols to maketext-base data which are going to change toaudio. The symbols are listed in Table 3.
Fig. 3: tobeWiki system

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The advantages of this system for a creator are:
• Creator does not need to use videos for making materials, just have to download Wiki on
the PC.
Table 2: Board symbols
symbol
=}
*
**
***
#
｜
Q( )
A( )
Ex( )
P( )
D( )
centerrightleft= （ more than 4 ）• Creator does not need to memorize tobeMLtags, just have to memorize Wiki symbols.

meaning
pointer target
sectionsubsection
subsubsection
itemizefiguretable
questionanswerexampleproof
definition
centerrightleft
new panel• Creator does not need to have any special IT
skills.
• Because the created data are text-base, correction and changing are easy.
• Makng Materials in a group is possible.
The advantages of this system for a learner are:• Because of the created data are text-base,learner does not need to care about amount ofdata and environment.
• Learner can choose the necessary data bychecking tobeML tags. tags.
And finally, (header)+(boerd part)+(talk part) forma tobe text, and Expositor converts the tobe text toanimation.

6 Conclusion
In this research we developed a system to improve
the learning through the Internet and making teaching material easier in a group. According to thissystem, first we make data on Wiki pages, and as anext step these data will be changed to tobe texts.
And finally convert these data to animation.
However, still the system need to be improved,
and as a future work we have to improve it graphically. And now the tobeWiki system works onlyin English, but it should correspond to other languages, too. And we also need to define more formatting rules for Wiki to have easier way for making tobe texts.

Table 3: Talk symbols
symbol
T====
T=}
{{
}}
^^
:]..
..
;;
:)..

meaning
new panelpointer target
back
next
jump
nod
pause
walk
smile

References[1] SATT: e ラ ーニン グ と は , http://satt.jp/tech/e-learning.htm.
[2] 戸部章子: XML ベース の説明記述言語およ びその講義形式
プレ イ ヤに関する 研究 (2005).
[3] Wikipeida:
intelligence/.

CI,

http://en.wikipedia.org/wiki/Collective-[4] Wikipedia: ウ ィ キ , http://ja.wikipedia.org/wiki/.

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The property of dislocation motion tracks which formed in
deformation of aluminum and influence on the dislocation
Student Number: 07M18154

Name: Chao Hu

Supervisor:Kunio Takahashi

変形する Al 内部に形成さ れる 転移移動痕の性質と それが転移におよ ぼす影響
胡

超透過型電子顕微鏡の中でア ルミ ニウ ム を 引張り 破断し 、 その場観察実験を 行っ た。 常温と ５ ０ ℃における 結果を 比較し た。 いずれの場合も 材料内部に転位のすべり 痕が形成さ れた。 そのすべり 痕は面欠陥であ り ， 時間が経てばやがて消失する が、 ５ ０ ℃における 消失速度は常温のそれよ り も 小さ い。 ま た， す
べり 痕は後続の転位の移動の障害と なる こ と が観察さ れた。 し たがっ てすべり 痕はア ルミ ニウ ム の力学的性質に多大な影響を 及ぼし ている と 推察さ れた。

1 Introduction
In the recent studies by Kiritani et al1–6), many experimental

the stress is unloaded.

results which imply the existence of deformation mechanism

2 Experimental Method

without dislocation were reported. In this deformation, theyobserved few dislocations at the fractured tip of thin

2-1 Specimen

metal foil at which heavy deformation occurred.
Instead, they observed an anomalous number of point
defect clusters. They proposed the existence of aplastic deformation mechanism that proceeds without
dislocation. Kiritani et al1,7,8) proposed the new deformation
mechanism but the detail of the deformation is still unknown.
To interpret the phenomenon discovered by Kiritani et al,

Fig. 1 Specimen in tensile specimen holder

motion of the dislocations has been observed byelectron microscopy.

The tensile deformation process of pure aluminum
was observed by an electron microscope. The

Plastic deformation in metals occurs by the gliding

specimen used waspure aluminum with 99.999%

of line-type crystal lattice defects called dislocations.

purity. It is considered that few impurities in

The theory of the strength of metals is based onaluminum influence on the experiment, but theinteractions between these dislocations and various

influence is still unknown. Specimen was cold rolledkinds of crystal lattice defects, including theto a thickness of 50µm, annealed at 873 K, and thendislocations themselves, all of which act as barriers to

cut into pieces of size 2mm×10mm in order tothe gliding motion of the dislocations. In this study,

accommodate it in a tensile specimen holder(Fig. 1).

we show the slip traces of

dislocations formed

A notch cut where is the arrow was introduced in theinside of the aluminum foil which has been discovered

center of the piece in order to render the rupture of thein aluminum by electron microscopy.

It exists only

specimen to begin at the center. In order to remove theunder elastic strain and disappears completely when

dislocations, we annealed the specimen at 773 K an

73

Technical Report of International Development Engineering

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hour.
Table. 1 Number of samples for the experiment andtheir experimental conditions
Temperature

298K

323K

Number of Samples

8

11

2-2 In-situ tensile experiment
The in situ observation of tensile fractures

wasperformed using a JEOL 2010 electron microscope,Fig. 2 Appearance of dislocations motion tracks in

specimen observed with electron microscope at thealuminum

acceleration voltage of 120keV.Crosshead speed of thestraining holder was controlled to 0.1 µm/s. Specimen
temperature was 298K and 323K. The direction of theobservation is from <100> direction, and g=200
reflection beam was selected. Dark field observation
for TEM image was recorded by a video recorder.

By pulling the specimen, cleavage proceeds from thenotch cut.

Dislocation motion tracks in aluminumhas been observed by stop pulling the specimen justbefore the foil ruptures.

And the tracks disappear
Fig. 3 Dislocation motion tracks in a difference

when the tensile stress is unloaded.

direction observation

3 Experimental Results
3-1 Appearance of dislocations and theirmotion tracks in aluminum
Figure 2 shows dislocation motion tracks images
observed by transmission electron microscope (TEM)in aluminum foil. (a) Initial state before theappearance of new
have

dislocations.(b)Dislocations

appeared from the directions of the arrows andstopped. The contrasts of the tracks are yet very faint at
this stage. (c) The contrasts of the tracks have gradually

Fig. 4 Schematic description of dislocation motion

become stronger. (d) The contrasts of the tracks havetrack

become clear. These dislocation motion tracks Fig. 3

3-2 Disappearance of dislocation motion
trackswere known type of planar defects (stacking fault) in adifference direction observation. Fig. 4 shows aschematic description of the dislocation motion track,
the track consists of

Figure 5 shows variation of the image contrasts of the“surface track” and “internal

dislocation motion tracks with time at room

track”.

temperature when the stress is unloaded. The images
have gradually become faint after 12 seconds, they74

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

have almost disappeared. Fig. 6 shows A,B and C fieldbrightness change with time is dislocation motion
track field,

A is no specimen field and B is no

dislocation motion track field in specimen. It isconsidered the dislocation motion tracks is not steady,they disappears completely when the stress isunloaded.

Fig. 7 Contrasts of the dislocation motion tracks
with time at 323K

3-4 Interaction between dislocation andmotion track

Fig. 5 Contrasts of the dislocation motion tracks
with time at room temperature

Fig. 8 Interaction between dislocation and motion
track

Figure8 shows a very interesting sequence of theinteraction between dislocations and dislocation
motion tracks. Fig. 8(a) is the initial state. Then in
Fig. 6 Brightness variation of dislocation motion

Fig. 8(b), a dislocation appeared and stopped at P.

tracksSimultaneously, Q became bright. The bright part isconsidered to be an intersection line between two

3-3 Difference of dislocation motion tracks
disappears between room temperature and323 K

different dislocation motion tracks. In Fig8(c),Padvanced again and stopped at barrier Q.

In Fig.

8(d),P advanced upward and disappeared. When P
broke through the barrier Q, the bright line image at Q

Figure 7 shows variation of the image contrasts of therotated clockwise. It is obvious that the remotedislocation motion tracks with time at 323K when theinteraction between P and Q in Fig. 8(b), at Q, pushstress is unloaded., In Fig. 5 after 12 seconds, theout of atomic arrays toward the direction of the arrow

dislocation motion tracks images have gradually

is observed.

become faint, dislocation motion tracks variation oftaking place by the touch of far dislocations that exists

323K is much slower than the variation at roomat the distance of several hundreds nm.

temperature.

dislocation motion tracks as a conductor of the stress75

It is surprising that the shift of atoms is

This role ofTechnical Report of International Development Engineeringisextremely

important

when

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

considering

2,3)

the

of the thin foil is the same for all

mechanical properties of polycrystalline metals.

, it would be

expected that the elastic strain necessary to form an
dislocation motion tracks in these FCC metals would
be higher, considering their higher elastic strain

4 Discussions

observed. Aluminum has a rather large lattice constantof 0.405 nm for its low atomic number of 13. It is

4-1 Causation of dislocation motion tracks
formed in aluminum

thought that this coarse structure enables the atoms toshift to the position with a low elastic strain comparedto other FCC metals.

From the observed results of dislocation motion
tracks images,

Conclusion

The contrasts of the tracks wasformed by motion dislocation, these dislocation

Formation of dislocation motion tracks in aluminum

motion tracks Fig.4 were known type of planarhas been discovered by the in-situ tensile experiment

defects(stacking fault). Amplification of the amplitudeof transmission electron microscopy. The tracks areof the horizontal wave of the lattice vibration isformed just behind the dislocations motion at the room

thought when the stress was loaded.

temperature and 323K. These dislocation motion
tracks were known type of planar defects (stacking

4-2 Influence to the mechanical properties

fault) in a difference direction observation. The tracks
disappear when the tensile stress is unloaded. In 323K

The interaction between dislocations and the tracks

the speed of the disappearance is slower than that of thehas been observed (Fig. 8). Since the tracks work as

room

the barrier for dislocation motion, it is considered that

dislocations and the tracks has been also observed.

they give a large influence to the mechanical properties

Since the tracks work as the barrier for dislocationof the aluminum including process hardening andmotion, it is considered that they give a large influence

serration,on the mechanical properties of the aluminum.

especially in the case of high strain rate. It

is necessary to revise the theory of the strength ofmetals at least in the case of aluminum.

temperature.

The

interaction

between

References

And this

discovers has possibility that elucidate the mechanism of1) M. Kiritani, K. Yasunaga, Y. Matsukawa and M.

anomalous vacancy cluster formation in tensile

Komatsu: Radiat. Eff. Def. Solids 157 (2002) 3-24.

ruptured metal foils which was detected by Kiritani et2) Y. Matsukawa, K. Yasunaga, M. Komatsu and M.

al.

Kiritani: Mater. Sci. Eng. A350 (2003) 8-16.
3) Y. Matsukawa, K. Yasunaga, M. Komatsu and M.

4-3 Possibility of dislocation motion tracks
formed in other face-centred cubic (FCC)
metals

Kiritani:Mater. Sci. Eng. A350 (2003) 17-24.
4) S. Kojima and C. Hu: Mater. Sci. Eng. A489 (2008)
150-157.
5) Y. Satoh, T. Yoshiie, H. Mori and M. Kiritani: Mater.

The accumulated dislocation motion tracks serve as

Sci. Eng. A350 (2003) 44-52.9

planes of slip for the synchronized rotation of6) K. Arakawa, K. Ono, M. Iseki and M. Kiritani:

4)nanolayers , and the anomalous formation of point

Radiat. Eff. Def. Solids 157 (2002) 25-30.

defect clusters occurs at the intersection of dislocation

7) M. Kiritani, Y. Satoh, Y. Kizuka, K. Arakawa, Y.

motion tracks formed in different orientations. It

Ogasawara, S. Arai and Y. Shimomura: Philos.

might seem logical that dislocation motion tracks

Mag.Lett. 79 (1999) 797-804.

would also be formed in other face-centred cubic8) M. Kiritani: Radiat. Eff. Def. Solids 148 (1999)(FCC) metals since the morphology of the ruptured tip

233-267.

76

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

LES Study on Hierarchical
Turbulence Organized Structure Above Urban Canopy
Student Number: 07M18160 Name: Jin ZHANG

Supervisor: Manabu KANDA!"#$%&'(")*+,-./0'1&23456789:;<=(
(
>( ?(
(


!"#$%&'$()*"#$+,-./012/.3$+405678%9:+;<='>?:0+@AAB.CDEF3GHI%J/.3$K,-?GH=?LM1NGHI%DOPQRSTU(PALM)(VW

3XYZ[\]^_`abTc(TSUBAME)Kd:?DJ/.3$KefghIijk02(lmn(=

M1J2A.o./M3pqrTcK@(+DstTU,u(vwxy3z{Kd:?J3|}~ȃ$
K.A+=M1

45$6

2
computational domain, which has a size of !"#$ %1 Introduction!"#$ % "##$&along x, y, z directions respectively,
with 5m grid length. To close approximate the real
atmospheric boundary, the initial temperature profile is
The atmospheric boundary can be divided into two
set as showed in Figure 2. The geostrophic wind velocity
parts, mixed layer and surface layer. It is known thatand the ground heat flux are set to be 20m/s andboth of these layers influence the other to a certain#'#() * $+,, respectively.
degree. Most of the studies related to those layers,
however, only focused on one of them. This is caused by
the restriction of resources. In this study, a LES (Large% #$Eddy Simulation) model PALM (PArallelized% #$ %&#$ %&#$
%&#$
!"#$
Large-Eddy Simulation Model) which is capable of%&#$calculation for large domain size was employed.Byusing this modelwith TSUBAME grid cluster system in!"#$
TITech, this numerical study managed to simulate bothlayers together which made the investigation of thecoherent organized structure of turbulence within alogarithmic region of urban boundary layer possible.
The coherent structure of turbulence plays an important%%'()*+,%&#$%-.%/%+01*
role in the exchange process of momentum and scalars in
the near-surface region, so the study of the coherent
structure would be useful in understanding the physicalbackground of the statistical structure of wall turbulence,modeling and controlling turbulence for industrial andgeophysical applications.
To investigate coherent structures of turbulence in3
urban boundary layer, the results are analyzed by
Figure 1: Plan view of computational domain
visualization of instantaneous flow fields and byconditional averaging. A filtering technique is also
employed to exclude the large scale influence from the
9/3:*0;<=1/$>0.;
mixed layer and to educe small scale turbulence
structures. In addition, quadrant analysis and two-point
C.D*E+0-.%F/3*E
correlations are performed to determine the statistical?@&8AB$characteristics of coherent structures.

2 Overview of the numerical setting
GH$-+><*E0I%J-(.1/E3%F/3*E

In this study we perform LES to elucidate thephenomenology of coherent structures in the log layer
above three-dimensional roughness comprised of aregular array of cubes. Figure 1 shows a plan view of the7586

Figure 2: Initial temperature profile

77

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

3 Flow statistics

3.2 Spectra and Cospectra

3.1 Performance evaluation

In the study of coherent structures in COSMO, Inagaki& Kanda(2008) observed that the low frequency part ofthe streamwise velocity spectra was larger than the fieldobservation results in the Kansas experiments (Kaimal etal, 1972). In contrast, the counterpart of vertical velocity
spectra and Reynolds stress cospectra had good
agreements with Kaimal’s results. By removing the
instantaneous spatial mean component, the low
frequency part of the streamwise velocity spectra
decreased significantly. This means the low-frequency
fluctuations of streamwise velocity didn’t follow the
inner-layer scaling similarity due to the outer-layer
disturbance.
Figure 4 shows the spectral densities and wavenumbers
which were normalized by the surface layer variables u*
and . / , respectively. The reference curves are from theKansas experiments and COSMO observations.
Two curves from this simulation are plotted in thisfigure. PALM_TS was derived from time series data at 8
points along the y direction at 2h. PALM_SP wasderived from the averaging of the spatial data along the x
direction. The results of PALM_SP were the largest.
This reflects the energy imbalance problem in a point
observation. It is known that the flux obtained by using
time series data from point observations tends to beunderestimated. Since PALM_SP evaluated all thevelocity information at xy cross section, the spectral
densities turn out to be larger.
The spectra and cospectra in the high frequency regionof PALM_TS exhibit good agreement with otherexperiments results, but the low frequency spectra forthis study was not produced. This could be caused by
two possibilities: the small domain size along x direction,or the larger damping for outer layer vortices due to thelarge building size.

In this section, turbulence statistics from the simulation
are presented, and detailed comparisons are made withmeasurements performed in outdoor scale modelexperiments for urban climate (COSMO).
Figure 3 shows the vertical profiles of potential
temperature, sensible heat flux, variance of verticalvelocity up to 40h (h:building height 40m) and mean
streamwise velocity up to 10h. From Figure 3(a), Figure3(b), the boundary layer height is determined as about
1200m and the influence of heat flux from entrainment
layer is limited to 800m. It is critical that the boundary
height is high enough so that surface layer and mixed
layer are separable. From Figure 3 (c), two maximum
values for ! exist. The upper one is at about 10h andthe lower one is at about 2h. This phenomenon isconsidered to be caused by the convection in mixed layer
and the turbulence produced by the shear in surface
layer.
Figure 3 (d) shows that a surface layer could be defined
up to 5h approximately where the mean velocity profile
is logarithmic. We follow the meteorological convention
and write the log law over rough surface as (Raupach etal. 1991)"#$%($,' *+
(3.1)
"&

)

$.

Where is von Kármán’s constant, and the parametersz0 and d are the roughness length and zero-plane
displacement, respectively. In this study, z0 and d are
1.4m and 33m respectively. Almost identical results for
d/h were obtained by Cheng & Castro (2002), where its
value is 0.825.
A stability parameter showed in equation (3.2) is also
derived.
$!"#$%&'#( & '

(3.2)

)+
* %,-



Here, z ! z " d. At 2h, . /L is -0.038, which can beconsidered to be neutral, consistent with the results
referred by Inagaki & Kanda (2008) in COSMO.

a)

f Su



1GOSGR
)5935



6'23E:9(a)6'23E96



(b)





f'



!"

!"



b)
1GOSGR



f Sw

)5935
6'23E:9



6'23E96



#$%&



(c)




f'

(d)



c)
1GOSGR)5935

f Couw!"



6'23E:9



6'23E96234(5673/8
-"./01
,
*+




f'

'!( )

Figure 4: Comparison of spectra and cospectra

Figure 3: Vertical profiles of various flow statistics

78

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

more sweeps, but the ejections are more significant basedon their contribution to the Reynolds stress. The results
are different to what is observed in COSMO, where theS4 are dominant in surface layer due to large influence
from the mixed layer. Since there is large correlation
between ejection (S2) and coherent structures, bycomparing with Figure 5, it seems that the larger
coherent structures at higher level in the surface layer
relatively contribute more ejections to the Reynolds
stress.

4 Coherent structures
In this section the coherent structures in the surface
layer will be investigated through the methods of
two-point correlations, quadrant analysis, spatial
averaging and conditional averaging.

4.1 Two-point correlations
Two-point velocity correlation defined by!! "#$ %#& '!( ")&!( ")*+)&

4.3 Spatial averaging(4.1),!(- ")&,!(- ")*+)&In COSMO’s study, an instantaneous spatial average ina horizontal small section to separate the inactive
turbulence(4.3)=" ' >="? @ =""where the square brackets and the double prime indicate
the mean and fluctuation of the spatial average in a finite
area, respectively. In this study, two different averaging
areas are used: a square area with 8h, and another with
2h on a side. The 8h averaging area is used to remove theinactive influence from the mixed layer, since this scale
is in the middle of large scale turbulence in mixed layer,and small scale turbulence induced from the surface.
Figure 7 shows a contour plot of fluctuating streamwise
velocity 4"" at 2h. The low speed regions (black) areelongated in the streamwise, which corresponds to theresults in section 4.1.

are computed for separation ! in the spanwise andstreamwise directions at 2h, 3h, 4h heights, respectively.
Figure 5 shows that the spanwise width and streamwise
length increase with height. By comparing Figure 5 (a)and (b), it is obvious that the streamwise length is larger
than spanwise width, but the aspect ratio of length towidth of the !! ' ./0 is approximately constant as 2.4
with increasing height. This means that the streamwise
and spanwise length scales increase roughly in the same
proportion with distance from the wall. So the overall
shape of the structures is preserved on average.
1.0

1.0
(a)

(b)

0.6

0.6
Ruu

0.8

Ruu

0.8

0.4

0.4

0.2

0.2

64

0
-3.75 -2.5 -1.25

0 1.25
r/h

2.5

!
#!
"!

0
-3.75 -2.5 -1.25

3.75

0 1.25
$r/h

2.5

56

3.75
48

Figure 5: Two-point correlations !!
(a): spanwise, (b): streamwisey/h40

4.2 Quadrant analysis

32

24

In the quadrant analysis technique, one considers thefrequency of occurrence and contribution to Reynolds
stress of velocity fluctuations lying in the four quadrants
defined by
123 45 6 .$ 7 5 6 .
 8193 45 : .$ 7 5 6 .
(4.2)
1;3 45 : .$ 7 5 : .
5
5
1<3 4 6 .$ 7 : .
Figure 6 shows the relative number of ejections (S2),sweeps (S4), and their relative contribution to the
Reynolds stress. Away from the roughness, there are

16

8

0
0

8

16

24

32

40

48

56

64

x/h

Figure 7: Instantaneous snapshot of streamwise velocity
4"". Black regions: u<0.8um. White regions: u>1.2um.
40

39

(a)

(b)

y/h

38

z/h

z/h

37

36
S2
S4
S1,S3

35
32

34

36

38

40

42

x/h
Contribution of each quadrant

Number in each quadrant

Figure 8: vector distribution in a part of the xy crosssecion at 2h. Grey regions: strong ejections

Figure 6: Quadrant analysis within surface layer

79Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

In Figure 8, the area enclosed by the white box in Figure
7 is enlarged. The grey regions represent strong ejections
that were two times larger in magnitude than thetemporal mean of ! . It is observed that there arestrong vortices on both sides of the ejection areas. To
clarify the relationship between the ejections and theirsurrounding vector fields, a conditional averaging
method is used.
Figure 10: The domain size of conditional averaging forthe data derived from large spatial averaging (8h). A, B,
C correspond to the xycross sections in Figure 9.

4.3 Conditional averaging
To educe the dominant structures, a local minimun
velocity below a threshold was set at 75% of the spatial
mean velocity. Flow information around these thresholdpoints were averaged three-dimensionally.
Figure 9 shows fluctuating velocity vector fields andcontours of fluctuating streamwise velocity
fromspatial averaging (8h) at " # $%&'(, 0, and 0.5h, where" # % is the reference height at 2h (Figure 10). At eachheight, there is a pair of counter-rotating vortices with anelongated low-speed region between. As height increases,
the center of the vortices shifts from upwind to
downwind. The counter-rotating vortices are considered
to be the legs of the hairpin vortices and the shift of thevortex center means the legs of hairpin vortices have an
inclination angle with respect to the ground.
Two-point correlations based on the spatial averaging
results are also computed in the horizontal and verticalplanes through conditional averaging. Figure 11 (A), (B)are the contours of Ruu in xy cross section through z=0
and Rvv in zx cross section through y=0, respectively.
Figure 11 (a), (b) are the counterparts derived with small
spatial averaging length 2h. Both of u and v show good
similarity in structure with different spatial averaging
lengths. The aspect ratio of spanwise width tostreamwise length, as defined by the Ruu=0.4 contours, isapproximately equal to 2 in both cases. The contours of
Rvv in Figure 11 (B), (b), show that both of the structures
have an inclination angle with respect to the surface,which could be inferred as the vortex leg observed in
Figure 9.

y/h

2.5h

5h

0

z/h

z/h

-1.25h
-2.5h

0
x/h

2.5h

0.5h

(B)

0
-5h

-2.5h

0
x/h

2.5h

5h

0.2

(b)

0

-0.5h
-2.5h

0.6

0
x/h

2.5h

1

Figure 11: Contours of two-point correlations
(A), (B):Ruu and Rvv at xy cross section and zy crosssection respectively.(a), (b): the counterparts of (A), (B)with small spatial averaging data (2h).

5 Conclusions
In this study, LES has been conducted to investigate thecoherent structures of turbulence within the surface layer
in urban atmospheric boundary layer. Following results
have been obtained.
1.
2.
3.

5.
7.5h

2.5h

The similarity of the inner-layer statistics isapplicable for urban boundary layer.
The averaged aspect ratios of the coherent structures
are preserved in the surface layer.
The number of coherent structures decreases withheight, but the contribution of ejections fromcoherent structures increase in the surface layer.
Counter-rotating vortices that are considered to bevortex legs of the hairpin vortices are observed
along the sides of the low speed regions.
Large scale turbulence and small scale turbulence
derived with different spatial averaging length
exhibit good similarity in their structures.

B

1.25h
y/h

0
x/h

-h

0

3.75h

-2.5h

h

4.

0
x/h

y/h

y/h

-5h

A

-3.75h

(a)

0

-2.5h

-1.25h
-2.5h
-7.5h

(A)

-1.25h

2.5h
1.25h

1.25h

2.5h
1.25h

References0-1.25h
-2.5h
-7.5h

[1]
-3.75h

0
x/h

3.75h

7.5h

2.5h
C

[2]

1.25h
y/h

0

-1.25h
-2.5h
-7.5h

[3]
-3.75h

0
x/h

-0.8

-0.4

3.75h

7.5h

0 (m/s)[4]

Figure 9: Fluctuating velocity vector fields and contoursof fluctuating streamwise velocity . A, B, C are thecross sections showed in Figure 10.

80

Raupach, M.R., Antonia, R.A. and Rajagopalan, S.:
Rough-wall turbulent boundary layer, Appl. Mech. Rev.
44, 1-25 1991.
Cheng, H. and Castro, I.P.: Near wall flow overurban-like roughness, Boundary-Layer Met, 104, 229-259,
2002.
Inagaki, A. and Kanda, M.: Structure of active turbulenceover an array of cubes within the logarithmic layer ofatmospheric flow, J. Fluid Mech, (submitted).
Kaimal, J. C., Wyngaard, J. C., Izumi, Y. & Cote, O. R.
1972 Spectral characteristics of surface layer turbulence.
Q. J. R. Met. Soc. 98, 563–589.

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Impact of Angular Power Spectrum (APS) on the Achievable
Diversity Gain and MIMO Capacity in a Mobile Terminal
Student Number: 07M18177

Name: Elnaz FOROUGHI SHAFIEI Supervisor: Jun-ichi TAKADA

Abstract
The array antenna systems in the mobile terminals, such as antenna diversity has been evaluated under theuniform (omnidirectional) angular power spectrum. The influence of angular power spectrum (APS) together
with the user rotation on the performance of antennas are examined. Omnidirectional and unidirectional angularpower spectrum models are investigated for direction diversity and space diversity in a multipath environment.
The goal of this research is to provide a guideline for how much in detail APS should be modeled for theevaluation of an array antenna system in a mobile terminal.

1

Introduction

rated in distance. This type of diversity is referred toas space diversity [4]. In this case, independent paths
are realized without an increase in transmit signal
power. In direction diversity, angle is provided by
restricting the receive antenna beamwidth to a given
angle [4]. The use of narrow beamwidth provides
angle discrimination that can reduce interference.
In order to concentrate on only the impact of
APS, very simple modeling and evaluation scheme
are deployed. i.e. the APS and the directivity of theantenna are simplified and the diversity performanceis evaluated.

An antenna in a wireless communication system isthe device through which, in the transmission mode,
radio frequency energy is coupled from the transmitter to the free space, and from free space to the receiver in the receiving mode. In many applications,
it is necessary to design antenna with very directive characteristics (very high gain) or very high efficiency, to meet demands for different types of communication scenarios.
There are many classical parameters to evaluate
antenna systems, of which directivity and efficiency
are the most common. However, for the array antennas in the multipath environment, classical parameters of the antenna such as directivity and efficiency
are not sufficient for the evaluation of the performance of the antenna system as a whole [2]. Propagation channel should be taken into account for theappropriate evaluation [1]. There exists some channel models proposed for antenna evaluation. However, they are too complicated for the comparativeevaluation of the array antennas of the user terminal as those models are originally developed for the
purpose of the system level performance evaluation[1]. Development of channel model for antenna evaluation is still a major issue.
In order to examine the performance of antennas
in various environments, this research examines theinfluence of concentrated angular power spectrum(APS) on the performance of user terminal array antennas, using diversity technique. Diversity scheme
refers to a method for improving the reliability of amessage signal by utilizing two or more communication channels with different characteristics. The
main purpose is to coherently combine the independent paths so that the effects of the multipath ismitigated. There are many diversity techniques, ofwhich we focus on space diversity and direction diversity in this research.
One method is to use multiple transmit or receive
antennas, where the elements of the array are sepa-

2

Antenna Evaluation Approach

In this section the approach of the antenna evaluation is presented. To simplify the formulation, APS
is concentrated into horizontal plane and only theazimuth APS is considered. In order to focus on theinfluence of concentrated APS together with the user
rotation to the performance of the array antennas, a2-Dimensional analysis is done for simple analyticaltreatment [2].
The correlation matrix of UT array can be derived in the same manner as the correlation matrixof the diversity antenna. APS for vertical polarizations are defined as pUT (ϕ) to satisfy the following
normalization condition.
2

Z 2π
0

{pUTi (ϕ)} dϕ = 1(1)

To represent the UT antenna characteristics, polarimetric complex directivity of i-th user terminal
antenna is defined as eUTi (ϕ) for ϕ also to satisfy
the normalized condition in the same manner as theantenna gain as12π

Z 2π n0|eUTi (ϕ)|

2odϕ = ηi(2)

where ηi ≤ 1 is the efficiency of the i-th UT antenna considering the loss and mismatch.

811Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

The matrix elements of [RU T ]ij can be obtained bysubstituting pG , eS1 and eS2 in Eq.(3), and pG , eG1and eG2 in Eq.(3) for space diversity and direction
diversity respectively.
The eigenvalues are calculated by general Eigenvalue decomposition (EVG) as,

The complex correlation matrix of i-th and j-thbranches of UT array is then calculated by using APS
and the complex antenna directivity of UT antenna
array as[RUT ]ij = 2

Z 2π n03oeUTi (ϕ) e∗UTj (ϕ) pUT (ϕ) dϕ

RUT = EΛEH

(3)Impact of Angular Power Spectrum

In order to examine different environmental characteristics, two APS models are considered, omnidirectional APS pO (ϕ) and Gaussian unidirectional APS
pG (ϕ). They are defined aspO (ϕ) =1
2π(ϕ ϕ0 )2∆ϕ2p

pG (ϕ, ϕ0 , ∆ϕp ) = A∆ϕp exp
( π<ϕ

!

(5)

ϕ0 ≤ π)A∆ϕp√= 2 2∆ϕp

Z π

exp

−π



ϕ2
2∆ϕ2p



dϕ

(6)

(7)
(8)



ϕ2
, π < ϕ < π (9)eG1 (ϕ) = B∆ϕe exp
2∆ϕ2e


(ϕ + π)2eG2 (ϕ) = B∆ϕe exp, 2π < ϕ < 0 (10)2∆ϕ2ewhere satisfying Eq. (2),
∆ϕe
=
2
B∆ϕ
π
e

Z π

−π

exp



ϕ2
∆ϕ2e



dϕ

(13)

R12 R21 )



(14)


λ2 1

x
exp(
)
λ2



λ1 6= λ2 (15)

Various parameters are used to represent the characteristics of the antenna and the environment.
Beamwidth is defined as the range of angle where
the antenna power gain is within the half of the peak.
Also, Angular Spread is the standard deviation of theangular power spectrum.
The Reference Antenna used in the study is a single omnidirectional antenna [5], under the same APS.
The reference measurement is taken in the same setup
as for the real measurement and then compared.
Diversity antenna gain-outage probability (DAGOP), is the improvement of SNR from the reference
antenna as the CDF of a certain probability, which
is set to 1[%] in this study. The CDF graph for thereference antenna (FREF (γ < x)) and the measurement antenna (FMES (γ < x)),is obtained as shownin Fig.1, where γ is the SNR at the reciever. Thenthe difference of respective SNRs when FREF (γRES <x) = 0.01 and FMES (γMES < x) = 0.01 is calculatedas(16)
DAG OP = γMES γREF

The two-element complex directivities of direction diversity array π separated Gaussian unidirectional elements are defined as follows:1

Where E is unitary and Λ is diagonal matrix of
Eigenvalues λ1 and λ2 .
In this research, the two-branch diversity is considered. The characteristic equation can be analytically solved and the eigenvalues are given as,

1
F (γ ≤ x) =
λ1 λ2

 
x
)
λ1 1 exp(
λ1

where ϕ0 is the angle of arrival (AoA) varying
within [0, 2π) according to the rotation of the user
terminal, and ∆ϕP is the standard deviation of theGaussian functions for angular power spectrum (APS).
The two-element complex directivities of spacediversity array with half-wavelength separated omnidirectional elements are defined as, π1
j cos ϕ , π < ϕ < πeS1 (ϕ) = √ exp
2
2
 π

1
eS2 (ϕ) = √ exp +j cos ϕ , π < ϕ < π
2
2

0
λ2

Once the eigenvalues of the correlation matrix
is known, cumulative distribution function (CDF)
F (γ ≤ x) of output SNR γof the maximum ratio
combining (MRC) is can be presented by the following equation [1],It should be noted that pG (ϕ) is a symmetrically truncated Gaussian function, and A∆ϕp is aconstant, satisfying Eq. (1) as,
1

λ1
0


1
λ=
(R11 + R22 )2
q2
4 (R11 R22± (R11 + R22 )

(4)
2

Λ=



(12)

(11)

where, γRES is defined so that F (x ≤ γRES ) = 0.01 .
82

2

Technical Report of International Development Engineering'

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)



'





'
&#)12=F$?

%&(

'



'
4GHGTGPEG
5RCEGFKXGTUKV[&KTGEVKQPFKXGTUKV['
' 





504YKVJTGURGEVVQ4GHGTGPEG=F$?




φ 





φ  πFigure 1: CDF of relative SNR for reference antenna,
space diversity and direction diversity
#5=FGI?



Figure 3: DAG-OP Characteristics of Space Diversity Antenna



λ))


'KIGPXCNWG

λ))

λ)5

λ)5







&#)12=F$?










φ =FGI?






Figure 2: Angle of Arrival (AoA) dependence of theeigenvalues of correlation matrices

4









Numerical Results#5=FGI?

&#)12=F$?

Figure 4: DAG-OP Characteristics of Space DiverThe variation of eigenvalues for the four scenarios
sity Antenna where AoA is averaged over ϕ0 = 0 to
explained in section 3 is shown in Fig.2. The eigenϕ0 = 2πvalues represent the equivalent uncorrelated branch
powers. The eigenvalues are fluctuating along ϕ0 (AoA)for
Gaussian unidirectional APS. The gap of the eigenvalues is the biggest when ϕ0 is 0 and π. The fluctuation of the graph is to a great extent reduced for
the Gaussian omnidirectional APS.
To analyze the impact of APS on array antennas,
simulations were conducted for space diversity anddirection diversity antenna arrays under different angular spreads (AS), and the impact of beamwidth
was also analyzed.
The simulation condition is presented in Table.1.




Table 1: Parameters Used in Simulation
Parameters
AoA
AS
BW
Values0[deg] 0 360[deg] 0 360[deg]Values90[deg] 0 360[deg] 0 360[deg]




$9=FGI?

The DAG-OP characteristics of space diversity
antenna for the two extreme cases of AoA=0[deg]and AoA=90[deg] is shown in Fig.3. As shown in
the figure, when AoA=0[deg], when AS is very small,













#5=FGI?

Figure 5: DAG-OP Characteristics where AoA ϕ0 =0 -3D Plot83

3

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)









&#)12=F$?

&#)12=F$?

Technical Report of International Development Engineering













$9=FGI?

















$9=FGI?

#5=FGI?













#5=FGI?

Figure 6: DAG-OP Characteristics where AoA ϕ0 =π
2 -3D Plot

Figure 7: DAG-OP Characteristics where AoA is averaged over ϕ0 = 0 to ϕ0 = 2π -3D Plotthe gain is low. The reason is, only one antenna hasrecognition in this case. When AS is small, for the
AoA of 0[deg] and 90[deg], the DAG-OP starts fromdifferent values. However, after the AS increases
more than 90[deg], the DAG-OP of both angle ofarrivals of 0[deg] and 90[deg] reach the same value.
This means when the AS is big, both cases they showomnidirectional behavior. Fig.4 shows the DAG-OP
characteristics of space diversity antenna when the
AoA is averaged over 0[deg] to 360[deg]. As shownin the figure, this case also shows a similar behavior
to the previous ones.
The DAG-OP characteristics of direction diversity (Gaussian) antenna for angle of arrival of 0[deg]and 90[deg] the 3-D graphs are shown in Fig.5 andFig.6 respectively.
For the case of A0A=0[deg], when the AS and
BW are small, the gain is very high, and it reduces
when the they increase. Also it could be observedthat when BW increases, the antenna shows omnidirectional behavior. Meanwhile, as the AS increases,
the gain also increases.
In contrast, for the case of angle of arrival of
90[deg], when the AS and BW are small, the DAGOP starts from a very small value. This is because forthis case, the unidirectional antenna almost can notrecognize the APS. The gain then increases when the
AS and BW increase. This also proves that similar
to A0A=0[deg], for the A0A=90[deg], when the BW
and AS are big, they show omnidirectional behavior.
Fig.7 shows the DAG-OP characteristics of direction diversity antenna when the AoA is averaged over0[deg] to 360[deg]. As shown in the figure, this casealso shows a similar behavior to the previous ones.

diversity performance was evaluated. It can be observed that for both cases space and direction diversity, when the angular spread is very high, the gain
is independent of beamwidth and angle of arrival.
Also in the direction diversity case, for very highbeamwidth, the gain becomes independent of angleof arrival and angular spread. This study shows thatthe justification of use of omnidirectional APS instead of unidirectional APS is rejected. As shownin this research, in reality, when the angular spread
is very small, the diversity antenna gain is also verysmall and so they show different behaviors.

5

References[1] J.Takada, ”Impact of Concentrated Azimuth
Power Spectrum for Performance Evaluation ofUser Terminal Array Antenna (invited),” International Union of Radio Science XXIX General
Assembly (URSI-GA 08), Aug. 2008 (Chicago,
IL, USA).
[2] J.Takada, ”Propagation Modeling for Performance Evaluation of MIMO Antennas,” 2007
Microwave Workshop and Exhibitions (MWE2007), WS8-1, Nov. 2007.
[3] J.Takada and K.Ogawa, ”Concept of Diversity
Antenna Gain,” COST273 7th Meeting of theManagement Committee, TD(03)142, May 2003
(Paris, France).
[4] Andrea Goldsmith, Wireless Communications,Cambridge University Press, 2005
[5] A. Balanis, Panayiotis I. Ioannides, Introduction
to Smart Antennas, Morgan and Clayborne 2007

Conclusion

This research examined the influence of concentrated
angular power spectrum (APS) on the performanceof user terminal array antennas, for the cases of spacediversity and direction diversity. In order to concentrate on only the impact of APS, very simple modeling and evaluation scheme was proposed, and the84

4Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

The applicability of one-dimensional & two-dimensionalsoil/water coupled analysis in settlement prediction of embankment
Student Number: 07M18183 Name: Longtao YOU Supervisor: Hideki OHTA & Thirapong PIPATPONGSA!"#$%&'()* 1 +,-2 +,!/./012"345!"#$%&'()*+$%,-./012+345+6789:;<=/>?@ABCDEF
GH[1]I4.(JK,LMN;<O=I0P,Q(1 RST 2 RS+EFI9UVWX,(1 RS
EFT 2 RSEF,YZ[\]+^.I_`Z<a,(B/D (O=b B Tcdefgh D +i)-Yjklm(1 RSn2 RSEF,YZ[\]+oT 2 RSEF,YZ[\]T+i)T.VpqI
rsQ(O=+[\tu,-vZ 1 RSEF+345,w./67xZW
and Ohta (1987) [1] and revised by Takeyama(2007) [3], and the practicability was confirmed inpast researches. The analysis technique employs anelasto-viscoplastic constitutive model proposed by
Sekiguchi and Ohta (1977) [4]. In addition the applicability of one-dimensional and two-dimensional soil/water coupled analysis in settlement
prediction of embankment will be discussed.

1. Introduction
Constructing geotechnical structures such as anembankment on soft ground cause often more orless settlement deformation. Prediction of the settlement of the embankment is useful for taking
appropriate measure in the planning/construction
stage, and taking countermeasure such as rational
reparation in the maintenance/management stage.

2. Difference between one-dimensional
and two-dimensional settlement

Recently, because of the technological advanceof the computer and FEM (finite element method)technique, the case prediction of the settlement by
two-dimensional analysis is gradually increasing.
Although it is simple to understand the deformation of a geometric by two-dimensional analysis,
there is the same time much disadvantage sincehigh cost (demanded for time and talented people)
and special technique such as some obvious analyzed conditions (boundary condition, geometricalcondition) are required. And it is difficult to avoid
completelytheerror.
However,the
one-dimensional consolidation analysis based on
Terzaghi’s[2] consolidation theory is still used up
to now in engineering practice because of its low
cost and simple technique.

Figure 1 shows the difference between one-dimensional and two-dimensional settlement.

(a) narrow fill (P3)(b) wide fill (P1)(c) one-dimensional settlement
The modification of circle by the maximum andminimum principal strain (2.5 times of strain)

In certain different geometrical condition of theembankment, analysis result showed that the settlement computed by two-dimensional analysis is
close to the one computed by one-dimensional
consolidation analysis.

Figure 1: Difference between one-dimensional andtwo-dimensional settlement.

In this study, some constructed embankments
will be computed in one-dimensional andtwo-dimensional analysis by soil/water coupledanalysis technique which was developed by Iizuka

These two analysis results Figure 1(a) and Figure 1(b) are drawn based on the two-dimensional
analysis results of Nagasaki Highway site which
will be introduced in Chapter 4. Figure 1(c) shows

The vectors of displacement (2.0 times of displacement)

185Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

the deformation of the subsoil layers when thewidth of the embankment is infinite. The circles
and the ellipses show the maximum and minimum
principal strain on the left of the figure, and thearrows show the displacement of clay layer on theright of the figure.

Soto-asahikawa in the part of Akita Highway project which was constructed on an overlain by very
soft organic clay which deposited on sloping base.
The three embankment cross-sections analyzed inthis paper are also shown in Figure 2 as their nameBC11, BC21, and BC31. The geologic figures ofthese sections are illustrated in Figure 3.

When fill materials are laid on soft ground, thecentre of an embankment settles right under, andthe top of slope and the toe of the embankment
settle and displace to the outside. In some cases,
the toe of the embankment swells from the surfaceof the ground contrarily. Paying attention to the
behavior of the subsoil elements beneath the embankment, we can find that the two-dimensional
deformation strongly appear so as to leave the centre of the embankment. Overall, the settlement by
two-dimensional analysis at the centre of the embankments is close to the one-dimensional analysis, but it does not mean that there is a
one-dimensional consolidation.

84.0

BC11
0.5
4.0
10.0
19.5

Sand drain area
85.0

BC21
0.5
4.1
12.1

For this reason, investigation on the difference
between one-dimensional and two-dimensional
analysis by referring to two evaluation indicators
are proposed. First indicator is B/D which is theratio of the filling width (B) to thickness (D) of
soft ground, and second is A (approximation)
which is the ratio of the difference between settlements computed by one-dimensional analysis andtwo-dimensional analysis to the settlement computed by two-dimensional analysis. It is consideredthat A will approximate to 0 when B/D is infinite,whereas this value reduced below unity when B/D
is small.

20.5
Sand drain area
99.5

BC31
0.5
5.9
7.7
14.1

Sand drain area

Unit: mFill

Sand mat

Crust

Peat

Clay 1Clay 2

Figure 3: Shape of embankment, bedrock and subsoil layers

3. Analysis Site (Akita Highway)
These three cross-sections are covered by apeat layer of about 5m thickness which has very
high water content and plasticity index. Underneath the peat layer lays a soft clay layer (Clay 1)
and a stiff clay layer (Clay 2). The bedrock is not
symmetric, therefore analysis area should be considered to appropriate wide range.

Akita Highway was constructed in 1993, and opened for traffic from 1997. This analysis site is called

The Seaof Japan

BC11
SITE

1D

1m

2D

CL

BC21
AKITA CityNAKITA Hightway

drainage
undrainage
load

BC31

Figure 4: Boundary condition of one-dimensional
and two-dimensional analysis
Figure 2: Location of Akita Highway site

In one-dimensional analysis, just the boundary286

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

drainage condition of upper surface of which thehydraulic head is set with 0 for modeling as drainage boundary shown in Figure 4. In two-dimensional analysis, the surface of the ground and embankment is set as drainage boundary. And input
parameters used in one-dimensional analysis arecompletely the same as two-dimensional analysis.

gravel bed containing silt and sand. The soft clay isuniform and highly sensitive. The shape of eachembankment and subsoil layers are summarized in
Figure 7.
56.3

(a)

(b)

excess porewater pressure (kPa)fill thickness (m)settlement (m)

15
10
5
0
1
2
3 CL
4
100 G.L.-2.5m
50
0100 G.L.-9.0m
50
0100 G.L.-15.8m
50
0 0
10
101

15
10
5
0
1
2
3

8.5
3.0

Ac
Ag
29.65

9.0
4.0

Ac
Ag
69.7

P3

8.5
8.5
3.5

P4 (asymmetric)

7.0
7.0
3.0

Ac
Ag
45.5

Ac
Ag

P6

Fill
Clay

7.7
5.0
2.0

Ac
Ag

UnitymGravel with silt and sandSandstone

Figure 7: Shapes of embankments andsubsoil layers
(e)

0

100

200

300

400

1m

1D

500

time (day)monitored
computed(2D,gradually increasing load)
computed(1D,gradually increasing load)

(c)
(d)
102

P2

8.5

8.5

Analysis of BC21 could not finish until completion of construction because critical failure occurred under the fill. The settlements at the centreof BC11 and BC31 of embankments computed in
two-dimensional analysis agree well with themonitored settlement. But the one-dimensional
analysis predicts settlement smaller than two-dimensional analysis. The simulation results are
BC11 cross-section shown in Figure 5.

45.4

P1

drainage

2D

undrainage

CL

load

103

time (day)CL

Figure 5: Simulation results (BC11)
Figure 8: Boundary condition of one-dimensional
and two-dimensional analysis

4. Analysis Site (Nagasaki Highway)

In one-dimensional analysis, the boundary
drainage conditions of upper and lower surface ofintermediate sand layer are set with the hydraulichead is 0 for modeling as drainage layer. And input
parameters used in one-dimensional analysis arecompletely the same as in two-dimensional analysis.

This is another analysis site, Nagasaki Highway
site. Six embankments were constructed as thepreload at Nagasaki Highway in the
Takeo-Kitakata Interchange project in Kyushu.
SITE

Preloadembankment

P3
P1

Oita

P6

C
L

P2
High way
Sections analyzed
T.P. (m)P2
Ariake clay +10

Gravel withsilt and sand
Sand stone

P4 0
P5

scale

P1

100(m)
P6

0
-10
-20

excess porewater pressure (kPa)

Figure 6: Location of Nagasaki Highway site
Site plan and soil profile are shown in Figure 6.
Five case studies are carried out for embankments
for P1 through P4 and P6. Embankment P5 is excluded from the analysis because of special improved with lime-treated columns. The subsoil
foundation consists of an alluvial clay layer and1284

monitored
computed(2D,gradually increasing load)
computed(1D,gradually increasing load)
computed(1D, instantaneously loaded)

0
1.0
2.0
0

3.0
150
100
50
0
150
100
50
0
0

G.L. -2.45m

G.L. -4.85m

2depth (m)Nsettlement (m)fill thickness (m)Nagasaki

4
6
8

370th day10
100 200 300 400 500 600 700

time (day)0

0.2 0.4 0.6

lateral displacement (m)Figure 9: Simulation results (P1)387Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

The correlation between B/D and Approximationis shown in Figure 11.
Overall, if the maximum error about 20% (thegray area in the Figure 11) is admissible for theconstruction sites, the prediction computed by
two-dimensional analysis in any shape of embankment and bedrock can be replaced by the prediction computed by one-dimensional analysis.

84monitored
computed(2D,gradually increasing load)
computed(1D,gradually increasing load)
computed(1D, instantaneously loaded)

0
1.0
2.0
3.0
150
100
50
0
150
100
50
0
0

0

G.L. -3.48m

2depth (m)excess porewater pressure (kPa)settlement (m)fill thickness (m)C
L
12

G.L. -6.78m

4
6

6. Conclusion

8

480th day10
100 200 300 400 500 600 700

time (day)0

The conclusions acquired in this paper are summarized as follows:

0.2 0.4 0.6

lateral displacement (m)Figure 10: Simulation results (P3)1) The applicability of one-dimensional soil/
water coupled analysis in consolidation settlement prediction of embankment is presented.

The simulation results of section P1 and P3 areshown in Figure 9 and Figure 10. Both the
one-dimensional and two-dimensional analysis cansimulate the settlement behavior well.

2) According to the comparisons between thesettlements, in the case of Akita highway ofwhich B/D is low, two-dimensional analysis
can simulate the settlement behavior well, but
one-dimensional analysis cannot, and in thecase of Nagasaki Highway of which B/D ishigh, both the one-dimensional andtwo-dimensional analysis can simulate thesettlement behavior well.

5. B/D and Approximation
Two indicators were proposed in Chapter 2. B/Dsof all analyzed sections are summarized in Table 1
except BC21 of Akita Highway site of which theanalysis actually stopped at about 370day becauseof critical failure of many elements. In Table 1, S1D
is the settlement computed by one-dimensional
analysis, and S2D is the settlement computed bytwo- dimensional analysis.

3) In this study, when the maximum error about
20% is admissible for the construction sites,
the prediction computed by two-dimensional
analysis in any shape of embankment andbedrock can be replaced by the prediction
computed by one-dimensional analysis.

Table 1: B/Ds and settlements in analysis sites

H (m)
B (m)
D (m)
B/D

Akita Highway
BC11 BC31
P1
11.7 13.7
8.5
84.0 99.5
112.6
17.5 26.0
8.5
4.7
3.7
13.2

Nagasaki Highway
P2
P3
P4
8.5
8.5
7.0
90.8 59.0 69.7
9.0
8.5
7.0
10.1 6.9 10.0

P6
7.7
91.0
5.0
18.2

S 2D (m)

3.38

4.70

2.22

2.62

1.95

1.72

1.41

S 1D (m)

3.02

3.82

2.21

2.42

2.28

1.71

1.18

Approximation

section

1.0
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1.0
0

References[1] Iizuka, A. and Ohta, H. : A determination
procedure of input parameters inelasto-viscoplastic finite element analysis,
Soil and Foundations, Vol.27, No.3,
pp.71-87, 1987
[2] Terzaghi, K. and Peck, R. : Soil Mechanics in Engineering Practice, 2nd Ed., John
Wiley & Sons, 1967
[3] Takeyama, T.: Some problem affected on reliability of solution in soil/water coupled finite element method and its theoreticalresolution methods, 2007zin Japanese{[4] Sekiguchi, H. and Ohta, H. : Induced anisotropy and time dependency of clay,
Proc.Specialty Session 9th ICSMFE,
pp.229-239, 1977

Akita Highway
Nagasaki Highway
5

10
B/D

15

20

Figure 11: B/D and Approximation

4
88

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Experimental study on adhesion behavior between
rough surfaces of solid bodies
Student Number: 07M18190

Name: LEI Lei

Supervisor: TAKAHASHI Kunio

表面粗さ を 持つ固体間における 凝着現象の実験的検討
雷磊
正弦波状表面粗さ を 持つアルミ ニム ブロ ッ ク と 平面シリ コ ン ゴ ム を 用いて , 実験的に外圧と 凝着幅と の関係を 調べた . 外圧と 凝着幅のヒ ス テリ シス 関係が観察さ れた . それは試験サン プル表面の sub-roughnessの影響だと 考えら れる . エネルギー損失率 α と いう 概念を 面凝着理論に導入する こ と で , ヒ ス テリ シス を予測する こ と ができ た． ま た , 面凝着理論に基づき , 部分接触凝着を 表面粗さ , 凝着仕事, 及び弾性率で表
すこ と ができ , 理論と 検証実験を 通し て , 弾性率可変材料の使用によ り ， 把持及び離脱の可能性を 示唆した.

1 Introduction

Figure 1 shows the schematic illustration of the adhesion between a semi-infinite elastic body with flat surface
and a rigid body with sinusoidal surface roughness under
external pressure. The relation between the external pressure p̄ and the contact width 2a can be expressed by Eq.
(1).
p̄∗ = sin2 (πa/λ)!1/2q− ∆γ̄ 1 + (2πh0 /λ)2 sin2 (2πa/λ) tan(πa/λ)

The effect of adhesion on elastic contact is significant
in joining technology as well as micro- and nano-scale
applications (e.g. micro-/nano-electromechanical systems (MEMS/NEMS) components). The adhesion contact between an infinite elastic body and a rigid body withsingle-sinusoidal surface roughness has been solved theoretically by Rachmat[1]. The hysteresis of the contact
is assumed as an energy dissipation and a simple treatment for the dissipation is proposed by Johnson[2]. The
mechanism of the dissipation energy by the surface subroughness was theoretically and experimentally investigated by Guduru[3][4], although the investigation is only
for the point contact. In case of point contact, the adhesion force is only dependent on the surface shape (curvature) and the work of adhesion. However, in case of area
contact, the adhesion force not only depends on the workof adhesion and surface shape, but also depends on theelastic constant. Using the elastic constant dependency
property, it is possible to design a mechanism to control
grip and release.
The present study is based on Rachmat’s theory[1].
The mechanism of hysteresis and the possibility of grip
and release by varying elastic constant are investigatedexperimentally.

E ∗ = E/(1 − ν2 )

(1)

g
loa
din

C

α=0.5
0

-0.2

Semi-infinite
elastic body

α=0.0

0.2

A

B
D Sep.
0

0.2

lo
ad
in
g

p

Snap to perfect contact

h0 /λ=0.1∆γ =0.1

0.4

unNormalized external pressure, p*

The solid line in Fig.2 shows the plot of Eq.(1). As
shown in Fig.2, at the initial contact of the two bodies without external pressure, the contact width increases
from A to B where the energy is at its local minimum.
After that, if we give a pressure between D and C, thecontact width changes along the solid line. If we give apressure larger than C, the contact will snap to the perfect contact. If we give a pressure less than D, the contact
will be separated.

2 Theory

0.4

0.6

0.8

1

Normalized contact width, 2a/λFig. 2 The relation between the normalized externalpressure and the normalized contact width for h0 /λ=0.1,∆γ̄ = 0.1

y
x


"
∆γ̄ = ∆γ E ∗ h20 π2 /(2λ) ,p̄∗ = p̄ (E ∗ πh0 /λ),

2a 2h
0

0

2.1 Sub-roughness model
Rigid body

In Rachmat’s theory[1], the roughness is assumed tobe single-sinusoidal. However, the actual surfaces haveanother sub-roughness on the sinusoidal roughness. The
effect of the sub-roughness on the adhesion could be
explained in the same manner as the work done by

Fig. 1 Model of adhesional contact between a semiinfinite elastic body and a rigid body having sinusoidal
surface roughness.

89Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Total energy

loading

Normalized work of adhesion, ∆γcrit

Guduru(2007)[3], which shows the effect of the subroughness on point contacts. But the contact in thepresent study is area contact.

h0/λ =0.100

0.6unloading

Da

Q3

0.8

Snap to perfect contact(C)

Separation
(D)

0.4

0.2

B

D

DE

DE
A

C

O

0
-0.8 -0.6 -0.4 -0.20Q1

0.2 0.4 0.6 0.8

1

Normalized external pressure, p*

EFig. 4 The relations between the work of adhesion andthe external pressure for h0 /λ = 0.1.

Emin

Contact width

Separation stress σsep./(∆γ / λ)Fig. 3 schematic illustration of the relation between the
total energy and the contact width.

104
103

Figure 3 shows a schematic illustration of the relation
between the total energy and the contact width. The existence of the sub-roughness is supposed to change theenergy curve from the solid line to the broken line. The
most stable state is point C. However it might stop at a
locally stable point A, due to the existence of the subroughness. In the same manner, in case of unloading, thecontact width might stop at E. Therefore we can observe
the hysteresis loop between the loading and unloading
process. Since Guduru’theory[3] is for point contact, it
can not be applied to the present case. However, the effect of the sub-roughness can be quantitatively discussed
using the concept of this theory[3]. Furthermore, the effect can be approximately explained using the theory ofJohnson[2]. In the same manner as the theory[2], we canassume that excess energy is required both in loading andunloading processes, to overcome the energy gap ∆E in
Fig3, respectively. Since the energy release rate G is expressed by
G = ∆γ
(2)

102
101

h0/λ =0.010
h0/λ =0.100

102

104

106

108

Elastic constant E* /(∆γ / λ)1010

Fig. 5 The relation between the elastic constant and theexternal pressure required to separate the interface, partially contacted.
(5)(6)

σ̆sep. = σsep. /(∆γ/λ)Ĕ = E ∗ /(∆γ/λ)Figure 5 suggests that three-figure of change in elastic
constant is required to make one-figure of change in adhesional force.

3 Experiment system and proceduresin case of no sub-roughness, we have to add some excess energy corresponding to the energy gaps. So, during loading, the energy release rate must be changed to−G = −∆γ + αG, and during unloading, G = ∆γ + αG.
Therefore, the hysteresis can be expressed by replacing
the ∆γ in Rachmat’s theory[1] by

12Stress σ (kPa)G = ∆γ (1 + α)G = ∆γ (1 − α)100h0/λ =0.001

(3)
(4)

E*=60kPa

1086loading
unloading

42

An example of the loading and unloading processes isplotted in Fig.2 with dashed lines, using α = 0.5.

0

0.05

0.1

0.15

0.2

0.25

0.3

Strain ε

2.2 Grip and release by varying elastic constantFig. 6 The stress-strain curve for silicon rubber.

The pressure at point (D) and point (C) in Fig.2 aredependent on ∆γ̄. Their relations are shown in the plot
in Fig.4. In this figure, curve OQ3 shows the separation point (D). Curve Q1 Q3 shows point (C) approaches astate of perfect contact. After normalizing the curve OQ3
in Fig.4 by the following methods (Eq.5〜6), the relation
between the pressure required to separate the partiallycontacted interface and the elastic constant can be obtained, as shown in Fig.5.

A transparent silicon rubber (FUSOUGOMU) of 15mm (z) × 38 mm (x) × 10 mm (y) is used as the elastic
body. The elastic constant is measured as shown in Fig.6,
and E ∗ = 60 is obtained. Aluminum alloy blocks (purity
99.95%, 30 mm (z) × 37.5 mm (x) × 3 mm (y) are usedas the rigid body. Their surface are processed to have sinusoidal roughness of two different amplitudes, such as,
h0 /λ=0.04,h0 /λ=0.02,λ=5 mm, by using a wire-cutting
90

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

machine. The surfaces are then polished carefully usingalumina particles (Baikalox, 0.1CR).

1.5

External pressure p (kPa)

Technical Report of International Development Engineering

to Controller

( D)
z

25 50

y

75

150

( C)

175

x
120

Aluminumalloy block

Low stress region
High stress region

1.0

0.5

loading-0.50

y0 . 000g( A)z

unloading

0

140

130

130

120

( B)

140

Silicon rubber

h0/λ =0.02
λ =0.005m

0.001

0.002

0.003

0.004

Contact width 2a (m)0.005

Fig. 9 The hysteresis measured in a lower stress region
and a higher stress for h0 /λ=0.02.

x

Fig. 7 Illustration of the experiment system used.
2.0

External pressure p (kPa)

Figure 7 shows the experimental system, which consists of (A) an electronic balance (Sartorius, TE153S) tomeasure the external pressure, (B), (C) automated precise
stages, crossed roller stage and goniometer Stage (Suruga Seiki, K701-20LMS, B43-38N, B54-60UNR) to adjust the vertical position and the angle of the elastic body,and (D) an optical microscope (KEYENCE, VH-7000)
to observe the contact width through the transparent rubbers. The experiment is done in an acrylic box to avoid
the effect of dusts and moisture. The samples are cleaned
in an ultrasonic bath with alcohol and set on the system
as shown in Fig.7. The horizontal angles of the elastic
body are adjusted by the stages (C) and the samples are
driven by automated stage (B). The contact width at thecenter of the sample is observed.In each measurement of
the force, it takes 3 to 10 (min) to obtain stable width.

loading
0.5

0unloading

0

0.001

0.002

0.003

0.004

Contact width 2a (m)0.005

Fig. 10 Comparison between theoretical and experimental result for h0 /λ=0.02.
6.0

External pressure p (kPa)

External pressure p (kPa)

1.0

Theoreticalh0/λ =0.02
λ =0.005m∆γ=0.063J/m2
E*=60kPa
α=0.578-0.5

4 Results and discussion
h0/λ =0.02
λ =0.005m
Dry contact
Oil contact

1.5

1.5

5.0
4.0

Theroreticalh0/λ =0.04
λ =0.005m∆γ=0.027J/m2
E*=60kPa
α=0.793

3.0
loading
2.0
unloading
1.0
0

1.0

-1.0
0
loading

0.001

0.002

0.003

0.004

Contact width 2a (m)

0.005

0.5

Fig. 11 Comparison between theoretical and experimental result for h0 /λ=0.04.

unloading
0

-0.5
0

0.001

0.002

0.003

0.004

Contact width 2a (m)mechanism of the hysteresis is considered to be due tothe energy gaps caused by the surface sub-roughness.
The Eq.(1) is fitted to the experimental results asshown in Fig.10 and 11. As the results, ∆γ = 0.063J/m2
and α = 0.578 are obtained for the sample shown in
Fig.10), and ∆γ = 0.027J/m2 , α = 0.793 are obtained
for the sample shown in Fig.11. Consequently, adhesionis very sensitive to the surface condition. So, the fitting resulte of the work of adhesion is different between
Fig.10 and Fig.11. The experimental results show a good
agreement with the theory in the loading processes. On
the other hand, in the unloading process, the measurement results does not agree well with the in loading process. Furthermore, the unloading process of Fig.10 and
11 shows the same tendency. The mechanism of the ten-

0.005

Fig. 8 The hysteresis measured under a dry condition
and an oily condition for h0 /λ=0.02.
Figure 8 shows the hysteresis measured under dry
condition and oily condition using a fatty alcohol (Linear AlkylbenzeneSulfonate). Fig.9 shows the hysteresis
loops both in lower stress region and higher stress region.
As shown in these figures, the comparable hysteresis isobserved even in the oily condition as well as in dry condition and the hysteresis seems independent of the stress.
These results suggest that the hysteresis is not mainly due
to the surface friction. Since no hysteresis is observed in
the measurement of elastic body as shown in Fig.6, the91Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

due to the edge effect, the difference would decrease forlarger samples or larger applictions.

7.0
Theoretical

5.0

Snap to perfect contacth0/λ =0.02
h0/λ =0.04
λ =0.005m

105

Separation stress σsep.(Pa)

External pressure p (kPa)

6.0

E*=60kPa

4.0
3.0

loading104∆γ (1+ α)=0.022J/m2

2.0

10

1.0
∆γ (1+ α)=0.05J/m2

0
0

0.001

0.002

0.003

0.004

Contact width 2a (m)External pressure p (kPa)theoretical datap1p2

∆γ (1-α)=0.15J/m2

unloading

0

-1.0
0

Sep.
0.001

∆γ (1-α)=0.16J/m2

0.002

0.003

0.004

2

3

.1
∆γ =0

6J/m

105

106

107

Elastic constant E* (Pa)108

Figure 14 shows experimental results of the separation stress as an function of the elastic constant. A shapememory gel prepared by professor Gong is used. The
elastic constant of the shape memory gel is 2 × 105 〜
5 × 105 Pa above 50 ℃, and 107 〜3 × 107 Pa below 30℃. The theory suggests the work of adhesion ∆γ to be
0.16 〜 0.72 J/m2 , which is well acceptable from the view
point of material science. The dispersion of the measurements seems larger than that at the lower temperature. It
could be due to the stability of temperature and the alignment process, which is easier at the lower temperaturethan that at higer temperature. Since the elasticity dependence of the separation stress is well expressed by thetheory, it can be used for the design of grip-and-releasedevices.

2.0

1.0

2J/m

Fig. 14 Comparison between theoretical and experimental result for h0 /λ=0.04.

4.0
h0/λ =0.02
h0/λ =0.04
λ =0.005m
E*=60kPa

2

.7
∆γ =0

102

0.005

Fig. 12 Comparison between theoretical and experimental result for h0 /λ=0.02, h0 /λ=0.04. (loading process)3.0

h0/λ =0.04
λ =5mm0.005

Contact width 2a (m)Fig. 13 Comparison between theoretical and experimental result for h0 /λ=0.02, h0 /λ=0.04. (unloading process)5 Conclusion
The adhesion contact between the silicon rubber andthe Aluminum alloy block having sinusoidal roughness
is investigated using Rachmat’s theory [1] considering
the surface sub-roughness. Based on the sub-roughness
model, the work of adhesion and the parameter α can beobtained from the measurements. The pressure required
to snap to perfect contact and to separate the contact canbe well predicted using the work of adhesion and the parameter α.
Based on Rachmat’s theroy[1], the possibility of grip
and release by varying elastic constant is considered. The
experimental results, by using shape memory gel, was ingood agreement with the theoretical prediction.

dency is still unclear. However the sub-roughness assumption used in the present study can be treated as agood approximation for the hysteresis loop.
Figure 12 shows the pressure which lead to snap to theperfect contact. In case of h0 /λ = 0.02, the expeimental
result shows good agreement with theoretical one. But
in case of h0 /λ = 0.04 the measurement slightly differsfrom the theory at the region of p̄ > 2.0 kPa. The external pressure p̄ of this region, by considering the stress at
the contact region, corresponds to the stress σ > 4 kPa
in Fig.6. As show in Fig.6 at this stress the elastic constant slightly decreases. This explains the reason why thepressure required to snap to perfect contact decreases, as
shown in Fig.12.
Figure 13 shows the experimental results for separation process. The pressure is decreased from the contact
width 2a ≈ 3.10 mm. As for the sample h0 /λ = 0.02,
during the pressure decreases from p̄1 ≈ 3.4 kPa top̄2 ≈ 2.8 kPa, the change of the contact width is verysmall and different from the theoretical prediction. On
the other hand, at the region p̄2 < 2.8 kPa, the mesurement results are in good argreement with the theory with∆γ/(1 − α) = 0.15 J/m2 . Similar tendency is also observed for the sample of h0 /λ=0.02. However, the separation stresses for both samples seem to be smaller than
the theoretical prediction. Just before the separation, separated area expands from the sample edge of z-direction
and the separation occurs, meanwhile the theory assumes
the infinite width of the sample. Since the difference isReferences[1] R. Rachmat A. Sriwijaya: Adhesion of a semiinfinite elastic body in contact with a sinusoidal rigid
surface, Doctoral thesis (Tokyo Institute of Technology , 2007)[2] K. L. Johnson: Mechanics of adhesion, Tribology
Int. 31 413[3] P. R Guduru, C. Bull: Detachment of a rigid solidfrom an elastic wavy surface: Theory, Journal of the
Mechanics and Physics of Solids 55 (2007) 445-472[4] P. R Guduru, C. Bull: Detachment of a rigid solidfrom an elastic wavy surface: Experiments, Journalof the Mechanics and Physics of Solids 55 (2007)
473-48892

Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

Phenols-polluted Water Treatment Using Enzyme and Recovery of Free Enzyme
Student ID: 07M18208

Name: He LI

Supervisor: Prof. Sachio HIROSE,
Associate Prof. Naoya ABE

フ ェ ノ ール系排水の酵素的処理と その遊離酵素の回収に関する 研究李賀

Abst r act
本研究では、 高価な 酵素を 有効利用する た め、 添加剤によ り 酵素反応を 促進さ せ、 かつ、 遊離酵素
を 回収・ 再利用する フ ェ ノ ール系排水の酵素的処理法を 検討する 。 添加剤と し て 温度応答性を 有する
キ ト サン 誘導体を 利用し 、 酵素反応プロ セス における 酵素再利用条件を 明ら かにする 。 併せて、 フ ェ
ノ ール系排水と し て 、 カ テコ ール、 ク レ ゾ ール、 塩素系フ ェ ノ ールな ど を 含む混合系排水について酵
素的処理の可能性を 検討する 。

Key words: Phenolic compounds, wastewater, Enzyme treatment, Temperature-responsive
polymer, enzyme recycle
Biological technologies dealing with the use ofoxidoreductive enzymes, for instance, laccases,
peroxidases and tyrosinases, may represent anefficient, alternative way to address the clean
up of phenol-polluted wastewater. And theyshow many attractive properties for biotransformation, such as wide specificity, highstability in solution, and easy availability fromplant materials.
In enzyme-based treatment method, various
enzymes such as Horseradish peroxidase(HRP), Coprinus macrorhizus peroxidase(CMP), Arthromyces ramosus peroxidase(ARP), and Soybean peroxdase (SBP) have
proven to be effective in removing phenolic
compounds from water (Al-Kassim et al., 1993,
Mceldoon et al., 1995)[3-4]. Among these
enzymes, HRP is the most widely used due tothe stability and its advantage in production.
However, there were only few studies that
focused on the mixture wastewater and highcost of enzyme still remains as a challenging inenzyme treatment. Thus, the recycle of enzyme
could be a way for practical application.
In this study, the type of enzyme wasselected at the first. Catalytic activity,
economic and quantity of production of enzyme
were appraised. HRP was selected finally. And
tyrosinase was also used to contrast.
Therefore, the objectives of this study are to:(1) investigate removal rate of phenolic
compounds using HRP and tyrosinase; (2)investigate the effect of the chemical additives

1. Introduction
Phenolic compounds are discharged in thewastewater streams of various industries suchas coal conversion, wood preservation, olive oil
factory,metal
casting,
pulp,
paper
manufacturing and so on. Most of thesecompounds are toxic and have been classified
as hazardous pollutants. Phenols in water havespecial adverse effects since as little as0.005mg/L of phenol will cause objectionabletastes and odors when it combines withchlorine to form chlorophenols.
There are many advantages of an
enzyme-based treatment over conventional
biological and chemical/physical treatment
which have been discussed by Nicell et al.
(1993) [1]. In most instances, physicochemicaltreatment processes are not very selective in
condition that the number of pollutants
removed during treatment; therefore, suchprocesses are more economically feasible forthe treatment for dilute wastewater. Chemical
oxidation, for example, can become very
expensive for high strength wastes, although
the targeted pollutants might have a low
concentration. Activated sludge is commonlyused to reduce organic compound in municipal
and industrial wastewater; however it has
difficulty in removing toxic pollutants to lowlevels (Aitken, 1993) [2].
Enzymes have a major appeal in chemical
processes as ‘green chemistry’ reagents, which
will allow future sustainable development.
193Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

2.5 3D-HPLC analysis

includinghydroxybutyl
chitosan(HBC),
carboxymethylcellulose(CMC) and chiosan on
the efficiency of the catalytic transformation ofphenols; and (3) investigate the recovery rate offree enzyme after treatment using HBC or κ
-Carrageenan.

The 3D-HPLC analysis was performed with a
Hitachi instrument equipment (LaChrom Elite
L-2455). A wakoshi ¢ (4.6mm×10mm column)
was used. Isocratic solution was performed at aflow rate 1ml/min mobile phase composed ofwater, and acetnitorile (60:40%; v/v),T=30℃,
Pmax=20MPa.

2. Materials and Methods
2.1 Materials

2.6 HRP activity assay

HRP was purchased from Biozyme Laborates(South Wales, UK). Tyrosinase (5370Units/mg,
solid) was purchased from Sigma Chemical
Company. And all other chemicals were thehighest purity available and purchased from
Wako Pure Chemicals Co., Japan.

A modified assay was employed to measure
the HRP enzyme activity using phenol,
4-amonoantipyrine (4-AAP) and hydrogen
peroxide as substrates. The approach provided
all components except enzyme near saturation
concentration so that the initial rate of reaction
became directly proportional to the amount of
enzyme present. The assay mixture contained
250 μ l of 48mM 4-AAP, 2500 μ l of 20mM
phenol, 1250μl of 0.1M phosphate buffer (pH6.5) and 1000μl of enzyme solution. The rateof reaction was measured by monitoring therate of formation of a non-precipitated productwhich absorbed light at a peak wavelength of
450nm (UV-1800, Simadzu).

2.2 Phenolic compounds polymerizing reaction
Each of the phenolic compounds polymerizing
reaction was carried out at 37 ℃ using
phosphate buffer (pH 6.5). The initialconcentration of phenol was 500mg/l. After
treatment, the supernatants were filteredthrough 0.45 μ m filters and analyzed forphenols concentration by 3-dimensional
high-performanceliquidchromatography(3D-HPLC). The concentration of phenolic
compounds in mixture wastewater (phenol;
catechol and substituted phenols) were also
analyzed as same procedure.

3. Results and Discussion
3.1 Phenolic compounds polymerizing reaction
without additives
The enzymatic activity of HRP andtyrosinase is dependent on pH with a broad
optimum over the pH range of 6 to 9. In
previous paper[5-6], the optimum conditions of
the activity of HRP is 37℃ and pH6.5. Table 1
shows that phenolic compounds removal
efficiency when each enzyme 4U/ml was added.
It can be seen that enzymatic activity of HRP is
greater than tyrosinase. And the reaction rateof HRP is also higher than that of tyrosinase.
In actuality, there are some different
phenolic compounds in a wastewater. Twomodels wastewater of phenolic compound
mixtures were investigated in this study. For
instances group (Ⅰ) includes phenol, catechol,and chloro-derivatives. Group ( Ⅱ ) includes
phenol, catechol, and p-substituted phenols.
Table 2 shows removal efficiency of phenolic
compounds in two groups. Although eachpolymerizing reaction reacts at the same time,thetransformationisdifferent.
The
exceptional behaviour of p-nitrophenol ingroup (Ⅱ) shows that no enzymatic reaction
occurred completely. Because the reaction
ability of each phenolic compounds is different.

2.3 Effect of the additives
Each additive (0.5g/l) was added into thetreatment. After the treatment, phenol
concentration of the samples were analyzed by
HPLC. And phenol concentration wereanalyzed when HBC(0.5〜20g/l) or CMC(0.96〜2.02wt%) was added.

2.4 Recovery rate of the free enzyme
After the phenols polymerizing reaction,
HBC(20〜30g/l) or κ-Carrageenan(10g/l) wasused to recover the free enzyme. The treatment
system using HBC was shown in Fig. 1. The
recovered enzyme activity was analyzed by
UV-1800.

Figure 1. Treatment System

294Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

It can be seen that the total quantity oftransformation is similar between two groups,
because catalytic ability of HRP was notchanged.
TABLE 1Treatment of Phenols by Enzyme in a Batch
ReactorEnzymeHRP

Tyrosinase

Compounds

Removal(%)

PhenolCatecholp-chlorophenol
2,4-dichlorophenol
2,4,6-trichlorophenol
p-nitrophenolp-cresol

29
65
49
88
100
23
64

PhenolCatecholp-chlorophenol
2,4-dichlorophenol
2,4,6-trichlorophenol
p-nitrophenolp-cresol

7
43
54
13
31
0
25

polymer did not precipitate very well, whenκCarrageenan was added(Fig. 3).
none

29

Glycine31

Chitosan

35

HBC

85

HPC

98

PEG

99

Gelatin

79

? -C

44

Arg

27

Glu

31

0

20
40
60
80
Phenols Transformed (%)

100

Figure 2. Phenol Removal Efficiency
Using Additives

TABLE 2
Transformation of Phenols in Mixture Model
Wastewater

Compounds
Ⅰ.

PhenolCatecholp-chlorophenol
2,4-dichlorophenol
2,4,6-trichlorophenol
Total

16.0
43.7
8.0
18.5
71.0

3.4
11.90
1.24
2.27
7.19
26.00

PhenolCatecholp-chlorophenol
p-nitrophenolp-cresol
Total

9.0
47.0
9.5
0
58.0

1.91
12.81
1.48
0
10.73
26.93

Figure 3. Insoluble Precipitates in
Polymerizing Reaction
Fig. 4 shows the effect of additives on otherphenols removal at 500mg/l initial phenol
concentration. The highest removal efficiency
is observed when using HBC. When HBC or
CMC is added, the viscosity of solution
increased. Fig. 5 indicates that thepolymerizing reaction would be disrupted if theviscosity of CMC is too high.
100

Tr a ns f or med

( %)

Ⅱ.

Removal Quantity(%)(mmol)

3.2 Phenolic compounds polymerizing reaction
using additives
Fig. 2 shows transformation of phenols inpolymerizing reaction using additives. It
observed that, the removal efficiency isimproved definitively than before, when HBC,
HPC, PEG, or gelatin was added. Addition of
chitosan or κ - Carrageenan remarkably
improved the removal efficiency. But, insoluble

None
Chit osan
Gelat in
HBC

75
50
25
0
P henolCat echolp‑chl or ophenolp‑ cr es ol

p‑ ni t r ohpenol

Figure 4. Effect of Additives on Treatment
395Technical Report of International Development Engineering

TRIDE-2009-01, Februay 13, 2009 (ISSN 1880-8468)

180

Viscosity (mPa・s)

Phenol Transformed (%)

Enzyme Act ivit y （U)1000 2000 4000 6000 8000 10000
100

T=25℃

80
60
40

140
120
100
80
60
40
20
0

20

0

0
0.69 0.96 1.24 1.39

1.5

Temperature-responsive of polymer, HBC orκ- Carrageenan was used to recover the free
enzyme(Fig. 1). About 38% HRP can berecovered by HBC; and 23% byκ- Carrageenan(Fig. 6). The recovery rate is lower than that be
expected, because HRP is inactivated by H2O2
(Fig. 7). Use of HBC can recover 79% activated
HRP at 40min after the beginning of thetreatment.

30
20
10
0
2

100

[1] J.A.Nicell, et al., Bioceterioration Abstracts,
Vol 7, pp1-8 (1993)[2] Aitken M.D: Waste treatment applicationsof enzyme: opportunities and obstacle.
Chem.Eng.J, Vol 52, B49-B58 (1993)[3] Al-Kassim L, et al., Evaluation of theremoval of aromatic and halogenatedunsaturated hydrocarbons from synthetic
wastewaterbyenzymecatalyzed
polymerization. In 48th Purdue Industrial
Waste Conference Proceedings, pp413-420(1993)[4] McEldoon J. P, et al., Enzyme Microb.
Technol. Vol 17, pp359-365 (1995)[5] Shuichi KAWATOKO, Enzymatic treatmentof phenol wastewater with thermo-responsive chitosan, Master thesis of Tokyo
Tech (2006)[6] LI He: Removal of Phenol in highconcentration condition using Chitosan
derivative and Enzyme, Bachelor thesis inTokyo Tech, (2007)

HBC 20g/L
HBC 25g/L
HBC 30g/L
κ‐ 10g/L

180

Reference50

Re c ov e r Ti me s ( ‑)60

The enzymatic method successfully removed
phenolic compounds from model wastewater.
Using additives such as HBC is an option to
improve the enzymatic method in economic
perspective. Further improvement of the
enzymatic method may be achieved byretaining HRP in additives polymer if the
enzyme inactivation is sufficiently suppressed.
The recover enzyme system using HBC seems
to be more economic and potential for practicaluse.

3.3 Recovery rate of the free enzyme

040Time (min)4. Conclusion

Figure 5. Effect of Viscosity on Treatment

40

20

Figure 7. Enzyme Activity in Treatment

1.59

CMC Concentration(wt%)

Recover y Ra t e ( ％)H2O2
HBC 20g/L
HBC 25g/l
HBC 30g/l

160

3Figure 6. Recovery Rate of the Free Enzyme

496