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

TRIDE-2014-04

June 5, 2014

Abstracts of Master Theses
Presented in February 2014

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 5, 2013 and February 13, 2014,
respectively. This technical report consists of the abstracts of those theses.

Technical Report of International Development Engineering
TRIDE-2014-03m
Table of Contents(Completing in September 2013)
Stakeholders’ Perspectives on Adoption and Diffusion of CASBEE in theJapanese Building Market.................................................................................................. Sheau-Chyng WONG

1

Lifetime Cost Reduction Study of a Ground Source Heat Pump System in
Mongolia.................................................................................................. ByambatuyaDAGVA

5

Eco-efficient Modal Split of Interregional Freight Transport in GMS........................................................................................................ Tomoaki KATO

9Empirical Research on Effectiveness of Improved Packaging Technologies forTransport Damage on Agricultural Products in Vietnam........................................................................................................ Yuki TAKEHISA

13

Airport Design Guideline as a Humanitarian Logistics Base.......................................................................................................... Sunkyung CHOI

17

Study of the Effect of ICT on Antenatal Care in Remote Mountainous
Region of Nepal.............................................................................................. Kazuhiro KAMIYAMA

21

Contribute of ICT Use to Promote Student-Centered Approach in Primary
Schools in Mongolia............................................................................................................ Shotaro YANO

25

(Completing in March 2014)
Database of Meteorological Urban Geometric Parameters of Japan and its Expansion
to Global Scale............................................................................................................ Takuya MAKABE

29

Les Analysis of the Effect of Vegetation on Flow Field in Urban Area................................................................................................................Hiroyuki KATO

33

Research on Stochastic Typhoon Model in Low Latitudes of Northwest Pacific Ocean......................................................................................................... Sarii KAWAI

37

Composting by Inoculation of Fungus that Degrades Antimicrobial Compounds
Present in the Compost Raw Material Pretreated Using Sub-Critical Water................................................................................................................. Akiko OINUMA 41
The Isolation and Utilization of Thermopilic Lactic Bacterium Strain TP1 in the
Biorefinery................................................................................................................. Yimeng XU

45Multiple Perspectives of the One Laptop per Child Initiative: the Case ofMongolia........................................................................................................ John AUXILLOS49

DEA Evaluation of Agriculture and Industry Water Use Efficiencies in China.......................................................................................................................Ru GAO

53

Estimating Direct and Imdirect CO2 Emissions of Automotive Manufacturing Supply
Chain in China....................................................................................................................... Yun GU

Clarification
Transportationof

Agricultural

Products

SupplyChain

Structure,

57

IncludingMode Choice in Vietnam........................................................................................................... Van Hung CHU

61

Visual Object Categorization by Background Removal with Depth Image................................................................................................................. Joowon KIM

65

Control Method of Boost Switching Regulator for Generators with Voltage Variation......................................................................................................... Yoshito HONDA

69

Temperature Distribution Change by Point Contact Current.......................................................................................... Kazuki WAKABAYASHI

73

Effect of Curing Conditions and Reinforcing Bars Arrangement on the
Corrosion of Steel in Concrete mixed with Seawater............................................................................ Zoulkane MOUSSA GARBA-SAY

77

A Study about Influential Factors on Corrosion Behavior of Paint-coated Steelin Submerged Zone............................................................................................................... Kenji WADA

81

Effect of Shear Pin Arrangement to a Critical Width of Undercut Slope
Aligned with a Bedding Plane.................................................................................................... Shuhei KITAKATA

85

Active Arch Action due to Interface Friction in a Rigid Retaining Wall................................................................................................................... Lin TANG

89

Fe-TiO2-MWCNT Composite Photocatalyst for Degradation of Methylene
Blue..................................................................................................................... Hao ZUO

93

Selective Catalytic Reduction of Nitrogen Oxides with Propene over Metal Oxides
mixed with (Ti,Zr)2O4Catalyst..................................................................................................................... Dongil KIM

97

Wastewater Treatment by Adsorption with Activated Carbon from Wood Residues in
Rubberwood Sawmilling Process...................................................................................................................

Xiao HAN

101

Recycling of Valuable Metals by Solvent Extraction using Carboxylic Acid as
Extractant .............................................................................................................
................................................................................................... Kazuma NAKAMURA

105

Evaluation of UWB-BAN Coordinator with Multiple Antennas............................................................................................................ Sho KOBAYASHI

109

Visualization of the Propagation Channels and Interpretation of the Mechanisms in
Macro Cellular Environments at 11 GHz.............................................................................................................. Rieko TSUJI

113

Fracture Criterion between a Multi-beam Structure and Rough Adhesive
Surface....................................................................................................... Kazuhito EMURA

117

Mechanism of Adhesion Hysteresis in the Elastic Contact between a
Silicone Rubber and a Silica Glass Lens........................................................................................................ Dooyoung BAEK

121

Radio Channel Parameter Estimation Using SAGE Algorithm.......................................................................................................... Van Hue PHAM

125

Study about Antenna De-Embedding from 2-Dimensional Propagation Channel around
Scattering Object................................................................................................... Osamu WATANABE

129

Development of MIMO Antenna Evaluation Method using Channel Capacity and
LTE throughput utilizing Extended Kronecker Model........................................................................................................ Yuta MARUICHI

133

Cooperative Communication in Narrowband Wireless Body Area Network................................................................................................. Karma WANGCHUK137

STAKEHOLDERS’ PERSPECTIVES ON ADOPTION AND DIFFUSION OF CASBEE IN
THE JAPANESE BUILDING MARKET
Student Number: 11M51525

Name: Sheau-Chyng WONGSupervisor: Naoya ABE

CASBEE was developed in 2001 for the promotion of sustainable building practices in Japan. Since then, only limited studies
have been conducted to understand the perspectives of CASBEE’s stakeholders. In a building market where numerous sustainablebuilding policies and schemes coexist, CASBEE’s status and practicality has yet to be validated. This study examined four main
aspects – perceptions, motivations, incentives and barriers – towards the adoption and promotion of CASBEE from the projectstakeholders’ perspectives. Data were collected through surveys administered to CASBEE Accredited Professionals and local
governments. The findings show that CASBEE’s adoption is limited in the building market and that substantial gaps exist between
the perspectives of stakeholders. This study contributes to the policymaking for the Japanese sustainable building market byproviding recommendations for the development and implementation of CASBEE.
and an environmental labeling tool could vary significantly(Figure 1). This study recognizes that the interests of all
stakeholder groups must be addressed and aligned before the
CASBEE system can be effectively utilized for the promotionof sustainable building practices in Japan.

1 Introduction
Comprehensive Assessment System for Built Environment
Efficiency (CASBEE) is a building performance assessment
method (green building rating system) originally developed as
an architectural design tool in Japan. Since its introduction in
2001, CASBEE’s role has expanded into various areas.
CASBEE’s current key applications in Japan include use by:1) architects and engineers as a building design tool; 2) local
governments for their ‘Sustainable Building Reporting System’(SBRS) policy; and 3) building owners or developers as anenvironmental labeling tool for asset assessment. [3]Nonetheless, no official studies have previously been
conducted to fully understand the perceptions, barriers or
motivations towards the adoption and promotion of CASBEE
from the perspectives of its direct users i.e., stakeholders. The
number of CASBEE-certified buildings has remained small
relative to the volume of construction in Japan. Thisphenomenon could be attributed to the social and psychologicalbarriers within the building industry, which must be overcome
in order to bring structural changes throughout the industry [2].
Since 2007, the Japanese central government has
introduced a series of green incentive programs to promote‘sustainable buildings’, ‘energy-efficient buildings’, ‘lowcarbon buildings’ and ‘long-life quality housing’ [1]. The
simultaneous operation of these programs, sometimes withoverlapping agenda, would conceivably cause confusion in thebuilding market.

2 Objectives
The purpose of this study is to examine the direct projectstakeholders’ perspectives towards the adoption and diffusionof the CASBEE system in the Japanese building market. The
following research objectives have therefore been established:
1. To uncover the direct project stakeholders’ perceptions of
CASBEE.
2. To identify the favorable factors (motivations, incentives)and unfavorable factors (barriers) for the adoption anddiffusion of CASBEE in the Japanese market from theperspectives of different direct project stakeholders; and tofind the gap between the perspectives of these stakeholders
and identify the opportunities to bridge the gap.
3. To provide recommendations regarding the development
and implementation of CASBEE.

3 Research Design
This study employed a quantitative data collection method to
examine the stakeholder’s perspectives. First, questionnaire
surveys were conducted among the direct project stakeholdersof CASBEE. The survey data were then interpreted using astraightforward descriptive analysis based on the frequency
results. Finally, Multiple Correspondence Analysis was utilized
to further analyze the data and summarize the main
characteristics of the data set.
3.1 Questionnaire Surveys
Two separate surveys were conducted in early 2013 to collectfeedback from the following groups: 1) local governments
currently adopting CASBEE for SBRS purpose; and 2)
CASBEE Accredited Professionals (CASBEE-AP) representing
the building community. The two main classifications of
CASBEE-AP, CASBEE-AP for Building and CASBEE-AP for
Detached House, are typically acquired by building
professionals from the nonresidential sector and residential
sector respectively, and therefore they could be considered
representations of the two building sectors. The key survey
topics and questions are summarized in Table 1.

Figure 1 CASBEE’s Direct Project Stakeholders
Source: by author.

This study has identified the following groups as the direct
project stakeholders of CASBEE: project owners (building
owners/developers), building designers (architects/engineers),building contractors and local governments. The core interestsof these stakeholders are highly diverse, oftentimes conflicting,and therefore their motives towards sustainable construction1

as ‘central government guidance’ and ‘comprehensive
promotion of sustainable building… and other environmental
issues’. They are also guided by the interests of ‘thedepartment-in-charge’ and ‘elected officials’, rather than the‘local business leaders’ or ‘developers/ industry’, which may
infer a lack of communication between the local governments
and their building community.

Table 1 Key Survey Topics/Items(individuals)(governments)
Sustainablebuilding
policies
Perceptions

Barriers

Motivations
Incentives

Survey Topics/Items
 Region of company or government Job title, professional certification, years of work
experience, size of company
 Number of support staff in charge of SBRS, andaccredited as CASBEE-AP respectively
 Tools to promote sustainable building

Frequency of Use

 Influential factors in sustainable building policy ‘Impression of CASBEE’ with respect to its benefits
for society and business.
 ‘Level of engagement’ with CASBEE measured by
its regular use and recommendation of CASBEE inprojects
 Most important barriers to the application of
CASBEE standards
 Additional time or cost on the design or constructionof a CASBEE building Design experience with CASBEE project in terms oflevel of difficulty and effort
 Most important motivations for the application of
CASBEE standards
 Incentives that are most attractive for applying
CASBEE standards
 Incentives currently offered by local governments

Tool to Promote Sustainable Building

Topic
General

a

10

b

5

8

c

2

6
5

d

1

1 1

f

1 1

4

1

5

2

11

6
3

1

2

3

6

e

2

1

3

1
9

1

14

2

1

18

1

Total respondents = 23
Note: Numbers shown inside bar represent the number of response
Very Frequently
RarelyQuite often
Never

Sometimes
No answer"Tool" indicator:

3.2 Exploratory Data Analysis

a. Provide publicity for green buildings (e.g., City’s homepage)b. Develop green building policies or regulations
c. Provide recognition for green buildings (e.g. architectural award)d. Provide educational activities on green buildingse. Offer seminars in green building technology
f. Conduct study trips on green buildings

3.2.1Test of Independence
The Pearson's chi-squared (χ2) test was used to determine
whether significant dependency exists between two variables,e.g., motivation and size of firm. This study considers twovariables to be ‘significantly dependent’ when the p-value fromthe chi-squared test was found to be below 5%.

Figure 2 Results on “Tool to Promote Sustainable Building” (Survey 1)
Level of Influence

3.2.2Multiple Correspondence Analysis (MCA)
Multiple Correspondence Analysis is a multivariate analyticalmethod commonly applied to contingency tables to uncoverassociations between categorical variables. In this study, MCA
was applied to the survey data to characterize stakeholder
groups with CASBEE’s factors (barrier, motivation, incentive
and perception); and, to associate this characterization with thedescriptive variables (CASBEE accreditation, location, etc.).

Influential Factors in
Sustainable Building Policya4 Results and Discussion

5

b

8

4

c

9

3

d

2

e

2

f

1

g

1

h

1

4

1
5

10

2

3

2

3

6

7

6

1

2

3

3

3

3

12

3

3

5

11

3

3

3

11
12

3
3

2
4

3
3

Total respondents = 23
Note: Numbers shown inside bar represent the number of response

4.1 Survey 1
Questionnaires were mailed to all 24 (sample size) Japanese
prefectural or city municipalities that are implementing a
CASBEE-based SBRS policy. In total, 23 questionnaires werereturned but only 15 of them contain complete, effective
answers, yielding an effective survey response rate of 62.5%.

Very Strong Influence
Little Influence

Strong Influence
No Influence

Some Influence
Do not know

"Influential Factor" indicator:

a. Central government guidance on sustainable buildingb. Interest in sustainable building generated from within thedepartment-in-chargec. Comprehensive promotion of sustainable building, global

4.2 Findings
The highest numbers of respondents (local governments) arelocated within the Kansai region (7), Kanto (6) and Chubu (4).
Less than half of these governments have one or more
CASBEE-AP’s, which imply that the CASBEE-based SBRS
policy in some jurisdictions may be purely administrative.
As illustrated by Figure 2, to promote sustainable building,
local governments most frequently ‘provide publicity for green
buildings’ and ‘develop green building policies or regulations’;
educational type activities such as ‘seminars in green building
technology’ are much less frequently used. It would later beshown in Survey 2 that the publicity efforts are insufficient toraise awareness of CASBEE among the general public.
As evident in Figure 2, the sustainable building policy of
local governments is highly influenced by political factors suchwarming and other environmental issues
d. Interest and/or appeal of sustainable building by elected officials
e. Global movement in sustainable building
f. Interest and/or appeal of developers/industry etc.
g. Interest and/or appeal of sustainable building by local businessleadersh. Networking among local governments

Figure 3 Results on “Influential Factors in Sustainable Building Policy”(Survey 1)

The incentive most frequently offered by the local
governments in conjunction with the SBRS program is‘preferential interest rates’ (mostly limited to residentialbuildings), followed by ‘recognition for building owners anddevelopers’. Unfortunately, no government is offering ‘priority
reviews’, an incentive most desired by the building community
according to survey 2 (Table 3).

2

or tangible incentives that substantially benefit the project
owners rather than the design or construction team. The
implicit suggestion is that the adoption of CASBEE, or any‘unconventional innovation’ that complicates the building
process, must be first and foremost be endorsed by the owners;
the right market incentives are needed to motivate the owners
to adopt CASBEE in their projects.

4.3 Survey 2
The request to participate in the survey was successfully
delivered to 3,921 (sample size) out of the 4,408 email
addresses of CASBEE-AP’s published on the CASBEE’s
homepage (as of March 2013). In this email, a link to an online
survey site was provided. A total of 440 respondents completed
the web questionnaire forms, but only 436 were consideredeffective, yielding an effective survey response rate of 11%.
The respondents comprised 320 (73%) architects/engineers,80 (18%) contractors, 12 (3%) building owners and 24 (6%)
other professionals. Among all, 243 (56%) are accredited as
CASBEE-AP for Building and 267 (61%) as CASBEE-AP for
Detached House (dual certification is possible). The highest
proportions of respondents work in Kanto (38%), Chubu (22%)
and Kansai (14%). The respondents are relatively evenly
distributed across firm size, and the majority (54%) has over 20
years of work experience.

Table 2 Ranking Result on “Most Important Motivation”
Motivation% Respondents
1 Promotion of environmental initiatives
2 Lower building life-cycle or energy costs
3 Compliance with local governments’ SBRS policy
4 Client demand
5 Preferential interest rates offered by banks
6 Corporate social responsibility (CSR)
7 Higher value of green/CASBEE buildings
8 Increased longevity of buildings
9 Other
10 Recognition for buildings
11 Financial payback / higher return on investment
12 Competitive advantage of CASBEE buildings
Reduced liability and risk of green/CASBEE
13
buildings
13 Help to promote sustainable building market

4.4 Findings
The results have confirmed that the practical application of
CASBEE has been extremely limited in the building market in
Japan. About 50% of the respondents indicated that they haveno practical experience in using CASBEE. The response
patterns on “perceptions” (Figure 4) suggest that although most
respondents are motivated to utilize CASBEE in practiceconceivable because they believe CASBEE is beneficial for thesociety, they are not given the opportunities or the rightbusiness environment to use CASBEE in practice.

"Perceptions" indicator0%aLevel of Agreement

20%
13%

b

40%

60%

33%

33%

24%

80%

57%

0
0

Table 3 Ranking Result on “Most Attractive Incentive”
Incentive% Respondents
1 Priority reviews of CASBEE projects
2 Preferential interest rates offered by banks
Financial incentives for building owners, e.g.,3
property tax reduction, subsidy
4 Promotion and advertising of CASBEE buildings
Density bonus for CASBEE building as allowed by
5
local government
6 Recognition for building owners and developers
7 Financial incentives / rewards for building designers
8 Reduction of building permit fees
9 Recognition for building designers
10 Recognition for builders / contractors
11 Other

100%
18%

48
12
10
8
6
5
4
3
2
1
1
0

3%

12% 6% 1%

22
21
16
10
9
5
5
5
4
2
1

Table 4 Ranking Result on “Most Important Barrier”
c

6%

d

12%

15%

24%

49%

42%

28%

Barrier
1 Lack of public outreach / education / training
2 Complexity of certification process
3 Complexity of CASBEE certification standards
4 Higher upfront construction costs
5 Amount of time required for certification
Lack of certified materials or resources meeting
6
CASBEE standards
Confusion among different programs/versions of
7
CASBEE
8 Learning curve of CASBEE system
9 Certification fees
9 Lack of demand for green/CASBEE buildings
9 Other
12 Insufficient incentive for using CASBEE
Increased liability and risk of green/CASBEE
13
buildings

6%
14%

4%

Total respondents = 436
Note: Numbers shown inside bar represent % of response
I strongly agree
I somewhat agree
I somewhat disagree
I strongly disagree

Do not know

“Perceptions” indicator:

a. The application of CASBEE enhances the competitiveness of

my company.
b. CASBEE has significant financial and environmental benefits
for our current society and future generations.
c. My company is currently using CASBEE standards on aregular basis.
d. I actively recommend the adoption of CASBEE standards inbuilding/ construction projects.

Figure 4 Survey Results on “Perceptions” (Survey 2)% Respondents
24
15
11
11
10
7
5
5
3
3
3
2
0

As evident from Table 4, the main challenges of utilizing
CASBEE from the building community’s perspectives are
two-fold. First, insufficient publicity has contributed to lack ofawareness of CASBEE among the general public, which
explains the low demands for CASBEE projects. Second, thecomplex nature of the CASBEE system (standards, certification
process etc.) inevitably imposes additional time and cost on
building owners, designers and contractors. The latter point was
further confirmed by a sub-set of survey questions concerning
the time and cost burden associated with CASBEE application.

Table 2 shows the ranking results on the top motivations
for the CASBEE-AP’s to apply CASBEE in their work. It canbe observed that the motivations lean towards ‘intangible
motivations’ (promotion of environmental initiatives), rather
than tangible rewards or monetary incentives (preferential
interest rates etc.). This could be further evidence that thepractical application of CASBEE in projects is not supportedby the current business environment; it also leads to the
speculation that real tangible or monetary benefits of CASBEE
buildings have remained absent from the market.
The incentives most desired by the respondents are listed inTable 3. The top three types of incentives (‘priority review of
CASBEE projects’, ‘preferential interest rates’ and ‘financial
incentives for building owners’) could be regarded as financial

4.5 Discussion
Comparing the two survey results shows that substantial gaps
exist between the perspectives of the local governments andthose of the building community. In particular, the incentives to3

outreach/education/training’ compared with other barriers. In
contrast, CASBEE-AP’s for Building consider ‘complexity’issues such as ‘complexity of certification process’ and‘complexity of CASBEE standards’ as the bigger obstacles.

promote CASBEE seem to be misplaced; certain incentives
most desired by the building community are not available.
Furthermore, the publicity efforts of CASBEE by the local
governments appear to be insufficient or be misdirected, andtherefore fell short of raising the awareness among the generalpublic, who constitute the majority of project owners. The
aggregate findings may infer a general lack of communication
between the local governments and their building community.

5 Exploratory Data Analysis and Interpretations
The χ2-tests have revealed that significant dependency exists
between most aspects and CASBEE-AP type and/or region(Table 5). The test results of other descriptive variables, e.g.,
profession, company size, years of work experience, are notshown but these variables will be included in the discussions if
significant associations with any of the factors were found.

ICT_1: Priority reviews
ICT_2: Reduction of building permit fees
ICT_3: Preferential interest rates
ICT_4: Recognition for owners
ICT_5: Recognition for contractors
ICT_6: Recognition for building designers
ICT_7: Density bonus
ICT_8: Advertising of CASBEE buildings
ICT_9: Financial incentives - owners
ICT_10: Financial rewards- designers
ICT 11: Other

Table 5 P-values for χ2-tests between Variables (Survey 2)

Perception (a)Perception (b)Perception (c)Perception (d)Barrier
Motivation
Incentive

samplesize

CASBEE-AP
Building

CASBEE-AP
Detached House

Region

436
436
436
436
241
434
435

0.164
0.230
0.004***
0.078
0.079
0.000***
0.000***

0.041**
0.122
0.000***
0.030**
0.001***
0.000***
0.000***

0.433
0.119
0.296
0.561
0.739
0.009***
0.001***

Figure 6 MCA Plot of “Most Attractive Incentive” and “Region”

6 Conclusions and Recommendations
Overall, this study has revealed significant differences inperspectives between building sectors and between regions
within the building community. The residential sector holds
more negative views of CASBEE and has fewer opportunities
to use CASBEE conceivably due to the lack of CASBEE
knowledge amongst their clients and the time and cost burden.
The regional differences might stem from the varying social,economic and political conditions of regions. The gaps between
the perspectives of the local governments and their building
community are most evident from the aspects of misplaced
incentives and insufficient publicity efforts.
In conclusion, the research points toward theunderdevelopment of a favorable business environment for
CASBEE’s dissemination. It is recommended that promotional
efforts to raise public awareness of CASBEE be made priority.
The central and local governments should create a mix ofincentives that meet regional and sectoral needs, in conjunction
with the consolidation and streamlining of the variety of
incentive programs that coexist in the building market today to
improve the effectiveness of their sustainable building policies.

Note: ∗∗∗ indicates p-value <1% significance level; ∗∗ indicates p-value <5% significance level.

5.1 Perceptions
The MCA analysis revealed that CASBEE is more positively
perceived by CASBEE-AP’s for Building (nonresidential
sector). Furthermore, the nonresidential sector has higher levelof engagement with CASBEE as illustrated in Figure 5.
AGREE:
strongly agree
agree:
somewhat agree
disagree: somewhat disagree
DISAGREE: strongly disagree

Figure 5 MCA Plot of “Perceptions: Level of Engagement” and“CASBEE-AP Type”

5.2 Motivations
According to the MCA analysis, the top-ranked motivations‘promotion of environmental initiatives’ and ‘lower building
life-cycle or energy costs’ tend to be associated with the
respondents from relatively small companies in the Chubu andKanto areas; ‘compliance with local government’s SBRS’ tends
to motivate CASBEE-AP’s for Building who work forrelatively large companies located in Kansai, which have thehighest number of local government implementing SBRS.

7 Limitations and Future Research
By studying CASBEE’s adoption and diffusion from theperspectives of its direct project stakeholders, this study has
gained valuable yet partial insights into sustainable building
market in Japan. In particular, the perspectives of the project
owners’ group could not be adequately clarified due to its small
sample size. Future studies should extend the present findings
by exploring the project owners’ perspectives or the regionaland sectoral differences in sustainable building practice.
Examinations of aspects such as level of public interest in
green building and levels of bureaucracy in the development ofgreen building policy may also provide comprehensive
evaluation of sustainable building schemes in Japan from both
regulatory and voluntary aspects.

5.3 Incentives
The MCA results showed that ‘preferential interest rates’ and‘financial incentives for building owners’ tend to be favored by
CASBEE-AP’s for Detached House. By contrast, ‘promotion…
of CASBEE buildings’ and ‘density bonus’ are more appealing
to CASBEE-AP’s for Building. Furthermore, the respondents
from different regions have vastly different preferences on
incentives (Figure 6).

References[1][2]

5.4 Barriers
The MCA results demonstrated that the CASBEE-AP’s for
Detached House are more strongly affected by ‘lack of public[3]

4

Hashimoto, K. (2013). Status and Prospect of the Policy on Housing andBuilding toward Low-carbon Society. Keynote session of 3rd Eco House &Eco Building Expo. Tokyo, Japan.
Hoffman, A. J., & Henn, R. (2008, December). Overcoming the Social
Barriers and Psychological Barriers to Green Building. Organization &Environment, 21(4), 390-419.
Japan GreenBuild Council / Japan Sustainable Building Consortium.
http://www.ibec.or.jp/CASBEE/index.htm.

Lifetime Cost Reduction Study of
A Ground Source Heat Pump System in Mongolia
Student Number: 11M51258

Name: Dagva Byambatuya

Supervisor: Abe Naoya

This study aimed at quantifying the lifetime cost reduction of Ground Source Heat Pump
(GSHP) system by focusing on an actual installed system in Mongolia. The comparison between a
recently built GSHP system and a typical traditional heat generating system, which utilizes coal, a main
source of air pollutants extensively, is thoroughly conducted to identify the critical risk factor in terms ofthe change of the total present value of the lifetime cost reduction. The study is supposed to be areference case for further investors and policy makers of the technology application in the country.
GSHPs are now the fastest growing
application of direct geothermal energy use, with
about 3 million GSHP installed units globally at
the start of 2010 (IEA 2010). GSHPs have faced
an enormous market development in some
European countries during the last years asshown in Figure 2.

1. Introduction
Ulaanbaatar (UB) is the coldest capital cityin the world. In Mongolian harsh winter, the air
pollution in UB gets distinctly worse mainly
because of fossil fueled space heat production bysuch as simple household ger1 stoves, heat only
boilers (HOB), and thermal power plant etc.
Because of the air pollution in UB, 1600 people
die every year and the levels of premature death,chronic bronchitis, and cardiovascular diseases
are increasing rapidly as World HealthOrganization identified. Therefore, Mongolia
needs to promote more efficient and greener
technologies to produce heat for reducing the air
pollution. One of the best solutions can be using
Ground Source Heat Pump (GSHP) technology forspace heating to overcome extremely harsh
winter in UB.
GSHP uses the earth as a heat source forheating or as a heat sink for cooling, depending on
the season (Figure1). This characteristic has
made it possible for all countries to use the heat of
the earth for heating and/or cooling, as proper.
The required energy amount to run a GSHP
system, which is mainly certain amount ofelectricity to run a pump for fluid circulation, isfrom one-third to one-fifth the required energy
amount transported from a lower temperaturelevel to a higher one (John, 2011). Thus thetechnology allows us to reduce consumption offossil fuels (coal), protect valuable natural
resources, lower emissions and get economic
efficiency.

584,649
372,317396,550

2006

2007

526,263

490,962

2009

2010

250,144

2005

2008

Figure2. Development of GSHP sales numbers in
Europe (Austria, Finland, Denmark, Italy, Norway,
Sweden, Czech, and United Kingdom)
Source: (Dumas, 2011)

The number of installed GSHP in Japan has
started to increase about a decade ago (Figure3).
The total number of GSHP has reached 990 for
the heating and cooling system and for the snow
melting system by the beginning of the year 2013
(Ministry of Environment of Japan, 2013).
600
500
400
300
200
100
09

07

05

03

01

99

97

95

93

91

89

87

85

83

81

0

Figure3. GSHP cumulative increases, Japan(Source: Geo Heat Promotion Association of Japan,
2013)

The National Renewable Energy Centre(NREC) of Mongolia, a state owned enterprise,
has already initiated in implementing a pilot
project on GSHPs using government funding.
This study is focusing on a kindergarten GSHP
system implemented as the pilot project.

Figure1. GSHP system operations(Source: IGSHPA, 2013)1

Ger is a circular domed Mongolian tradition dwelling that is
portable and self-supporting.
52. Objectives of the study

The main goal of this study is to quantify the
lifetime cost reduction of GSHP system in
Mongolia and provide a reference case for further
investors and policy makers of the technology
application in the country. The GSHP system atthe “Ireedui” Kindergarten of “Tuv” province near
UB is analyzed as a case study in comparison
with the previous heating solution, heat only
boiler (HOB), in this study.
Having reviewed the current state of GSHP
in various countries, including in Mongolia, theobjectives of the study are set as:1) To estimate present values of lifetime cost
reduction (PV-LCR) by the adoption of GSHP for
12-year, 13-year, 14-year, 15-year, 20-year,
25-year and 30-year lifetime respectively bycomparing present values of lifetime costs(PV-LC) of HOB and GSHP system for therespective lifetimes.
2) To determine the payback period2 of the GSHP
system done by its operational cost saving.
3) To identify the most sensitive cost variables on
PV-LCR of the GSHP system through sensitivity
analysis and to determine the riskiest variable
causing uncertainty on PV-LCR of the GSHP
system.
4) To identify perspective of the users of the
GSHP system.

Salary0%2%Materials

7% 5%Transportation

8%

Rental equipment
Engineering

39%

Drilling
Commisioning

36%

Contingency
Tax

1%
1%

Other cost

1%

Figure4. Share of percentage of each cost of initialinvestment. Note: Raw data provided by NREC

4. Data analysis
The financial analysis was implemented bydeveloping discounted cash flow (DCF) model at
the MS-Excel software. A typical DCF model for apotential investment makes forecasts of costs andrevenues over the life of the project and discounts
those back to present values.

1- Expected values of net cash flows in eachperiod; - Discount rate
In this study, only lifetime costs both for
before (HOB) and after (GSHP) case were
forecasted and the values were discounted topresent values because there is no substantial
revenue for the owner. Lifetime cost of HOB
includes only heating service charge paid by thekindergarten. Lifetime cost of GSHP includes its
initial investment, operation and maintenancecosts. Present value of life time cost of HOB isdenoted as PV-LC-Before and present value of
lifetime cost of GSHP is denoted as PV-LC-After
respectively. Afterwards by comparing the
PV-LC-Before and PV-LC-After, estimatedpresent value life time cost reduction (PV-LCR)
becomes the main focus in this study.
After the financial analysis, sensitivity
analysis was carried out, which is the first step to
conduct risk analysis. In order to conduct thesensitivity analysis all the cost variables that are
significant to the outcome of the project, PV-LCR,
were tested. The variables that have great
impacts on the PV-LCR were identified asmaterials and drilling cost (Figure5). Appropriate
probability distribution and likely range of values
were assigned to the two variables based oneither past data or experts’ opinions (Table2.) todetermine the most crucial variables on PV-LCR.
Monte Carlo simulation was used to generate aprobability distribution of the outcome, PV-LCR,
through the help of Crystal Ball™ with 1,000
trials.

3. Data collection

A site survey was conducted in April, 2013 in
UB and Tuv Province, Mongolia aiming to get all
the qualitative and quantitative information used
for the study. The main approach of the survey
was interviewing with professionals and officials
at various organizations and site visit.
The main data of initial investment,
electricity usage (for operation cost estimation),and maintenance of the GSHP system were
provided by NREC. The data in regards of theprevious heating solution, HOB, cost wasprovided by the “Ireedui” kindergarten.
Assumption input for conducting risk analysis(explained in Data analysis) ideas of the GSHP
adoption were obtained through the survey.
Major cost of initial investment of the GSHP
system was spent for drilling (36%) and materials
purchase (39%) (Figure4).
Perception of the GSHP system by the users
was identified by individual interviews at thekindergarten. The satisfaction level of the users
was high (with mean score 4.8 out of 5) and theirattitude toward the existing system was positive
mainly because of its reliable operation, lowoperation cost, and convenient (constant) indoor
temperature.
2

Payback period refers to the year when initial investment costof GSHP recovered by PV-LCR at this study.
6

12-year, 13-year, 14-year, 15-year, 20-year,
25-year, and 30-year lifetime by Monte Carlosimulation @Crystal ball software. Forecasted
PV-LCR distributions for 12-year and 30-year
lifetime are illustrated in Figures8 and 9 as
examples. All the result of the simulation issummarized in Table5 and its values areillustrated in Figure6.

Table2. Probability distribution (triangular)
assumption made for material and drilling costMaterial
cost
Drilling
costMin$105,411

Likeliest$147,575

Max$189,739

Min$67,463

Likeliest$134,926

Max$269,852

Table5. PV-LCR for the seven different lifetimes

5. Results
Financial analysis: Present values of lifetime cost

PV-LCR

were calculated for 12-year, 13-year, 14-year,
15-year, 20-year, 25-year and 30-year separately
both for GSHP (PV-LC-Before) and HOB(PV-LC-After) to make comparison of them. GSHP
system is expensive to install but it has
considerably lower operating and maintenancecosts than that of conventional HOB system. For
this reason it can do saving (PV-LCR) by its
extremely low operation cost (Table3.).

Lifetime

Table3. PV-LC-before and after; PV-LCR
PV-LC-After

PV-LCR(A)(B)(C)=(B)-(A)12-year$ -435,241$ -429,807$5,43413-year$ -491,482$ -436,073$55,409

14-year$ -551,935$ -442,604$109,331

15-year$ -616,918$ -449,415$167,503

20-year$ -1,022,564$ -488,068$534,49525-year$ -1,604,679$ -535,680$1,068,999

30-year$ -2,440,034$ -594,326$1,845,708

Elasticity

1$ -152,010$109,056

13-year$55,409$28,922$ -102,034$159,031

14-year$109,331$82,844$ -48,112$212,953

15-year$167,503$141,016$10,060$271,12520-year$534,495$508,008$377,052$638,117

25-year$1,068,999$1,042,511$911,555$1,172,621

30-year$1,845,708$1,819,221$1,688,265$1,949,330

Base Case

Mean

Minimum

Maximum

1,500
1,000
500
0
12-year 13-year 14-year 15-year 20-year 25-year 30-year
Lifetime of GSHP

Figure6. PV-LCR for the seven different lifetimes

The probabilities that PV-LCR will be more than“Zero” for 12-year, 13-year, 14-year, 15-year,
20-year, 25-year and 30-year lifetimes are shownin Table4.
Table4. Probability of PV-LCR to be more than “Zero”

1.2
25-year(after Monte Carlo simulation)$ -21,054(500)

cost for salary of construction workers, material,
rental equipment utilization (Rental), drilling,
electricity usage, and maintenance (Maint) were
tested. To compare the all six different costs,
elasticity of them are calculated and presented in
Figure5. The most sensitive variables arematerial and drilling cost.
20-yearMaximum$5,4342,000

Sensitivity analysis: Six cost parameters such as

15-year

Minimum

12-year

PV-LCR ( Thousands$)

PV-LC-Before

Mean

At thebase DCF
model

30-year

0.8
0.6

Lifetime(year)

12

13

14

15

20

25

30

Probability
(%)

37

72

94

100

100

100

100

After the simulation, material and drilling cost
contribution shares on PV-LCR variance were
found 86.7% for drilling cost and 13.3% formaterial cost (Figure7).

0.4
0.2
0
Material

Drilling Electricity

SalaryMaint

RentalMaterial

Figure5. Elasticity of costs on PV-LCR

Drilling

13.30%
86.70%

Monte Carlo Simulation: After identifying themost sensitive variables, the probability
distributions (Table2) were assigned. Then
PV-LCR forecast distributions were generated for

Figure7. Material and drilling cost contributions for thevariance on PV-LCR

7

Figure 8. PV-LCR distribution for
12-year of lifetime

6.

Figure 9. PV-LCR distribution for
30-year of lifetime

If lifetime of the GSHP increases, elasticity ofeach cost on PV-LCR reduces (Figure5) and
PV-LCR
increases
distinctively(Figure6).
Considering lifetime and performance of a GSHP
depends greatly on designing and installation(early stage works), they have to be done at highquality. The cost of a GSHP installation is very
important; however, the more important concern
relates to the quality of the design andinstallation. A low-cost designing and installation
might not be a better choice except it can perform
well over a long time. Drilling cost highly depends
on soil physical properties (texture, density,
porosity etc.) and weather (season).
Thusphysical properties of soil need to be investigatedin advance and drilling work should be planned
appropriately in a proper period of time (season)of a year.
Areas for further study: More improved input
assumptions for more variables for the MonteCarlosimulation
shouldbedeveloped.
Assessments concerning various aspects such as
health and environmental impact of GSHP
adoptions were not performed in this study. It ishighly recommended to perform an economic
analysis covering various aspects as above todetermine the impacts of GSHP technology if
widely adopted since the technology has otherimpacts besides operational cost savings. It will
require comprehensive and systematic approach.
An extensive study titled “Air Quality Analysis of
Ulaanbaatar”, which can be one of the usefulreferences for the further recommended analysis,
was conducted by The World Bank in 2011.

Conclusions

1) PV-LCR values are quantified for lifetimes of
12-year, 13-year, 14-year, 15-year, 20-year,
25-year and 30-year of the GSHP system; include
base DCF model results and its mean, minimum,and maximum values after Monte Carlosimulation as presented in Table5. The generaltrend is PV-LCR increases distinctively if life timeof the GSHP increases (Figure6). At the base DCF
model, PV-LCR becomes positive at the 12th-yearof operation as $5,434. After conducting theMonte Carlo simulation, the mean value of
PV-LCR becomes positive starting from 13th-year
as $28,922 and the minimum value of PV-LCR
becomes positive from 15th-year of operation as$10,060.
2) The certainty of PV-LCR can be more that “zero”
is 37% at the 12th-year, 72% at the 13th-year, 94%
at the 14th-year and more than 100% from the
15th-year of the operation (Table4). The minimum
value of PV-LCR is $ -48,112 at the 14th year and$10,060 at the 15th year becoming positive value(Table5). Thus the payback period done by its
operational cost saving is 15 years. To make sureto have positive PV-LCR, the system needs to lastmore than 15 years.
3) According to the sensitivity analysis, the mostsensitive variables are material and drilling cost.
As a result of conducting risk analysis (afterMonte Carlo simulation), drilling cost is theriskiest variable sharing 86.7% of sensitivity(Figure7); thus it is capable of causing highuncertainty on PV-LCR.
4) It is assumed that GSHP is suitable for
Mongolia technologically because the pilot projecthas
been
working
properlysince
itscommissioning in 2010 as identified by the site
survey. The regular user’s attitude at thekindergarten building toward the existing GSHP
system was quite positive mainly because of its
reliable operation, low operation cost, andconvenient (constant) indoor temperature.
Recommendations: Lifetime of a GSHP system
is extremely important and should be maximized.

References

John, S., 2011. Residential Geothermal Systems, Heating And
Cooling Using The Ground Below. 2nd ed. New York.
IEA, 2010. Renewable Energy Essentials: Geothermal.

International Energy Agency.
Dumas, P., 2011. Increasing deployment of GSHP in Europe market, incentives, regulations - and savings. Presentation
Material. Brussels, Belguim: European Geothermal Energy
Council.
IGSHPA,
2013.
[Online]Availableat:
http://www.igshpa.okstate.edu/geothermal/ [January 2013].

8

ECO-EFFICIENT MODAL SPLIT OF INTERREGIONAL FREIGHT TRANSPORT IN GMS
Student Number: 11M18060

Name: Tomoaki Kato

Supervisor: Shinya Hanaoka

大メコン圏の地域間貨物輸送における環境を考慮した機関分担率の算出加藤智明

本研究では、大メコン圏の地域間貨物輸送を対象に、輸送費用、輸送時間、二酸化炭素排出量を目的関数とし、機関分担率を決定変数とする目標計画問題を定式化した。バンコク－ハノイとバンコク－ヤンゴンの 2 つの路線をケーススタディとして、既存輸送機関の改善と貨物鉄道新規建設の 2 つの開発シナリオと、目的関数の削減目標値を設定し、目標に対する最適な機関分担率の算出を行った。
その結果、路線や削減項目、削減目標ごとの最適機関分担率の傾向や差異が定量的に明らかになった。具体的には、バンコク－ヤンゴ
ン路線では、輸送距離が著しく長いために海上輸送距離の優位性が低く、トラック輸送や鉄道輸送の分担率が相対的に高いこと、また、
両路線共、時間と排出量の同時削減を目指す場合には鉄道輸送が高い分担率を担うことが望ましいことなどが示された。

2)

1. Introduction
Nearly 40% of greenhouse gas emissions, which areperceived as the causes of the climate change,
originated from Asian region. Transport sector occupied
over 20% of the world total CO2 emissions and was thesecond most emitting sector following electricity andheat. Therefore it is our great challenge to establish
low-carbon transport system which is one of main
components of Low carbon Asia [1].
For interregional transport, strategies to realize
low-carbon transport system are classified into three:
AVOID, SHIFT and IMPROVE [1]. The present study
is focused on SHIFT, which is the shift to lower
emission transport modes such as water or railway
transport. Modal split expresses the share taken byeach transport mode and is an important indicator of
SHIFT. But few studies have attempted a quantitative
discussion of optimal modal split despite the fact thatmany previous studies pointed out the significance ofwater or railway intermodal transport. Therefore it isrequired to set modal split targets as one of indicatorsof modal shift.
The study area, Greater Mekong Subregion (GMS),is currently at a crucial stage of the modal shift of its
interregional freight transport. The first reason is adramatic growth of regional freight demands driven by
the economic growth in this region. Secondary thisregion has been putting considerable resources into thedevelopment of the major economic corridors such as
East-West Corridor, North-South Corridor, andSouthernCorridor.
Consequently
thehardinfrastructure for truck transport in this region has
been substantially improved compared to before.
Thirdly not only the hard infrastructure but also soft
infrastructure has been being developed. All GMS
countries signed Cross Border Trade Agreement with
the intension to promote smoother movement of people
and goods crossing the borders. Mainly these threeimportant changes of situation are expected to cause
freight modal shift from maritime transport, which has
been dominating interregional freight transport in
GMS, to truck transport. Truck transport has
substantial advantages over other transport modes interms of logistics performance such as lead time,
flexibility and frequency. From the viewpoint ofenvironmental impact, however, its emission factor is
far larger than those of other modes. Therefore it isimportant to present the vision of eco-efficient modal
split based on backcasting approach, which stands fordrawing a pathway from a desirable future to present,
not like forecasting.
Against this background, the objectives of this study
are set as follows.
1) To formulate the model of interregional freightmodal split to reflect logistics performances andenvironmental impacts.

To calculate optimal modal splits in GMS based on
several scenarios regarding transport modes andreduction targets of cost, time and emissions byusing goal programming.

2. Methodology
2.1 Freight demand and mode of focus

This study examines three transport modes:
maritime-truckintermodal,
truck
only
and
railway-truck intermodal. Intermodal transports are
the combination of main transport (line-haul transport)such as vessels or railways and truck transport
connecting between origins/destinations and terminals(pre/post-haulage transport) In GMS, railway
intermodal transport is hardly used for interregional
freight transport at the moment. But in long term,
there is a possibility of new railway construction.
Therefore it is worthwhile to take into accounthypothetical railways.
Regarding freight demand of focus, cargoes which istransported in standardized containers for distance ofover 500km is of interest because some previous
studies have revealed that such freight demand is
adaptable to modal shift [2].

2.2 Case study routes(1) Bangkok – Hanoi route

With the opening of the Second Thai – LaoFriendship Bridge in 2006, truck transport from
Bangkok to Hanoi via East-west corridor is available.
Maritime-truck intermodal transport, however, ispredominant on this route. It ships from Bangkok city
to Laem Chabang Port by truck. The cargo will reachHai Phong Port, which is approximately 100km awayfrom Hanoi after transshipment at Ho Chi Minh Port.
Railway transport route is a hypothetical route and it’s
not fully connected at the moment.

(2) Bangkok – Yangon route

Trucks go north up to Tak and reach Yangon via
western section of East-west corridor. Even though theland transport route is much shorter in distance thanmaritime transport, some sections in Myanmar still
have very poor road condition. Therefore maritime
route, which is a roundabout by Strait of Malacca, deals
with almost all of freight demands. The railway route isalso a hypothetical route.

2.3 Modal split calculation

Calculation of modal split is shown in figure 1 in thenext page. The procedure is divided into two stages:
baseline analysis and estimation of optimal modal split
using goal programming approach.

9(b) Transport time
 dmi
daei
1
1 

f 2   si  tt i  pti 

vm
cm
vae
cae
i
i
i
i
i 


(4)

s 1
i

(5)

si  0(6)iFigure 1 Flow of modal split calculation

This study estimates several different optimalmodal splits depending on scenarios and targets. Twotypes of scenarios regarding transport modes are built
to determine the model inputs. Those are(i) improvement of existing modes, and (ii) new
construction of freight railway in addition to theimprovement of existing modes.
Improvement of existing modes specifically assumes
following situations:1.
Improvement of road conditions such as improved
pavement and multiple lanes
2.
Facilitations for night driving
3.
Free entrance of foreign-registered vehicles
4.
Single window/stop
5.
Improvement of terminal operation efficiency
6.
Rerouting of maritime transport
Since railway transport routes are hypothetical,
some of inputs are based on similar examples in othercountries.

(1)

s 1
i

(2)

si  0(3)ii: transport mode (1:maritime-truck intermodal, 2:
truck only, and 3: railway-truck intermodal)si: modal split of mode i
cost

of

mode

dmi

: line-haul transport distance of mode i (km)tci

: terminal operation cost of mode i (USD/ton-cargo)pci: custom processing cost of mode i (USD/ton-cargo)

daei

:

vmi

: line-haul transport velocity of mode i (km/hr)

dmi: line-haul transport distance of mode i (km)cmi

: line-haul transport capacity of mode i (ton-cargo)tti: terminal operation time of mode i (hrs/ton-cargo)pti: custom processing time of mode i (hrs/ton-cargo): pre/post-haulage transport velocity of mode i(km/hr): pre/post-haulage transport distance of mode I(km): pre/post-haulage transport capacity of mode i(ton-cargo)

pre/post-haulage transport(USD/ton-cargo*km)

cost

of

(c) CO2 emission
f 3   si mi  dmi  t i  aei  daei i(7) si  1(8)isi  0(9)i: transport mode (1:maritime-truck intermodal, 2:
truck only, and 3: railway-truck intermodal)si: modal split of mode i

μmi: emission factor of line-haul transport of mode i(kg-CO2/ton-cargo*km)dmi: line-haul transport distance of mode i (km)μti

: emission factor of terminal operation of mode i(kg-CO2/ton-cargo): emission factor of pre/post-haulage transport ofmode i (kg-CO2/ton-cargo*km)

μaei
daei

: pre/post-haulage transport distance of mode i (km)2.6 Goal programming(a) Transport costf 1   si Cmi  dmi  tci  pci  Caei  daei iCaei: modal split of mode i

caei

Following three objective functions are taken into
account as indicators of logistics performance andenvironmental efficiency. Formulations were done byreference to Hanaoka et al (2011) [3].

line-haultransport(USD/ton-cargo*km)

si

daei

2.5 Formulation of objective functions:: transport mode (1:maritime-truck intermodal, 2:
truck only, and 3: railway-truck intermodal)

vaei

2.4 Scenario building

Cmi

i

mode

Goal programming is a special form of linear
programming in which multiple and conflicting
objectives are expressed as constraints. As each ofthese objectives has a goal or target value to beachieved, unwanted deviations from this set of target
values are then minimized in a regret function [4]. Goal
programming problems of this study is formulated as
below. Three objective functions presented above areconverted into constraints. Modal split si and all thedeviations are decision variables. The regret function to
be minimized in this problem is expressed as the sum ofsquared “degree of unsatisfaction” (defined asover-attainments divided by target values) of eachindicator. LINGO 14.0, a comprehensive mathematical
calculation tool, is used for solving the goal
programming problem.

iimin R  (: pre/post-haulage transport distance of mode i (km)

10

dc 2
d
d
)  ( t )2  ( e )2
Tc
Tt
Te

(10)

baseline scenario is determined as 67.3% for maritime
transport and 32.7% for truck transport by reference tothe example of Japan.
It is assumed as the current modal split on Bangkok– Yangon route is fully occupied by maritime transport.
Similarly to Hanoi route, predicted modal split isdetermined as 53.4% for maritime transport and 46.6%
for truck transport by reference to the example ofJapan.
The table 3 and 4 compare values of the objectivefunctions in current status and baseline scenario.

s.t.

 s Cm  dm  tc  pc  Cae  dae   d  d  T
i

i

i

 dmi

1

i

i

i


c

i


c

(11)

c

i

daei

1 

 s  vm  cm  tt  pt  vae  cae   d  d  T(12) s m  dm  t  ae  dae   d  d  T

(13)

i

i

i



i

i

i

i

i

i

i

i

i

i

i


t




e


t


e

t

e

i


c


c

d d  0(14)

dt  dt  0

(15)


e


e

d d  0(16)

s  1

(17)

i

i


c


c


t


t


e


e

d , d , d , d , d , d , si  0

Current status

(18)

Tc

: target value of transport cost (USD/ton-cargo)

Tt: target value of transport time (hrs/ton-cargo)Te: target value of CO2 emission (kg-CO2/ton-cargo)dc-

Table 3 Current and baseline scenario (Hanoi route)

Baseline scenario
Rate of change: over-attainment of transport cost (USD/ton-cargo)

Current status: under-attainment of transport cost (USD/ton-cargo)dt-: over-attainment of transport time (hrs/ton-cargo)dt+: under-attainment of transport time (hrs/ton-cargo)de-: over-attainment of CO2 emission (kg-CO2/ton-cargo)de+: under-attainment of CO2 emission (kg-CO2/ton-cargo)

Rate of change

Since target values of the goal programming
problem are given values, target setting done based on
the baseline. Two ways of target setting are attempted,
which are (a) reduction of cost and emission, and(b) reduction of time and emission. In order to observe
the difference by reduction levels, three levels of
reduction are set respectively. The details of the
reduction levels are shown below.

Time
Baseline
10% up
20% upCost
Baseline
10% up
20% upTime
10% down
20% down
35% down

52.99
82.3
+55.3%

Transport cost

Transport time

CO2 emissions(USD/ton-cargo)(hrs/ton-cargo)(kg-CO2/ton-cargo)

7.46
4.34
-41.77%

53.75
71.11
+32.29%137.77157.37+14.23%The optimal modal splits are calculated by the
scenarios, targets and routes. The results are shown in
the figure 2 in the next page. Since not all targets areachieved, the degrees of unsatisfaction are also shownin figure 3 in the next page. 50% of unsatisaction, forexample, means that the actual value is 1.5 times
greater than the target value. The degree of
unsatisfaction is shown as 0 if the target is achieved or
lower than the target.
When the reduction of cost and CO2 emission is
aimed, the results of optimal modal splits in (i)improvement of existing modes scenarios are consistent
with the expectation. That is, the higher the reductionlevel the larger share of maritime transport. On theother hand, the shares of truck transport remain
relatively high for time and emission reduction targets,
but the targets are not well achieved. In (ii) new rail
construction scenario, the share of truck transport issubstituted by railway transport and the achievements
are improved. A remarkable difference can be observedin the trends of railway share between reductions
targets. The railway share increases as the reductionlevel goes higher in time and emission reduction.
The share of truck transport is fairly high in case oftime and emission reduction, while the trend is similar
to that of Bangkok – Hanoi route when the reduction of
cost and CO2 emission is aimed. The change in share isvery small even if the reduction targets go higher. In

Emission
10% down
20% down
40% down

Table 2 Level of time and CO2 emission reduction

Level 1
Level 2
Level 3(kg-CO2/ton-cargo)

11.32
4.94
-56.35%116.06113.44-2.26%

3.3 Optimal modal splits

Table 1 Level of cost and CO2 emission reduction

Cost
10% down
20% down
25% down

CO2 emissions(hrs/ton-cargo)

For Bangkok – Hanoi route, the baseline is slightly
lower in cost, considerably lower in time andconsiderably higher in emission compared to thecurrent status. Despite the increase of share of truck
transport, which is more expensive mode, cost slightly
decreases probably because cost of both transportmodes are substantially reduced by the infrastructure
improvement. Particularly the effect of maritime
rerouting is influential. For Bangkok – Yangon route,comparison between the current status and thebaseline shows different trend in cost from Bangkok –Hanoi route mainly because of remarkable increase oftruck transport share.

2.7 Target setting

Level 1
Level 2
Level 3

Transport time

(USD/ton-cargo)

Table 4 Current and baseline scenario (Yangon route)

Baseline scenariodc+Transport cost

Emission
10% down
20% down
40% down

3. Results and discussion
3.1 Inputs

Three input sets according to the built scenarios areprepared for each case study. The values are
determined based on the surveys of JETRO and someother literature reviews. Presentation of specific valuesof inputs is omitted here due to the limitation of space.

3.2 Baseline analysis

As for Bangkok – Hanoi route, current modal split
are assumed as 95% for maritime transport and 5% fortruck transport. Predicted modal split used in the11

(ii) new rail construction scenario, and the highest
reduction levels, the modal share was occupied by twomodes, those are truck and railway in time andemission reduction case, and maritime and railway incost and emission reduction case. In lower targets, on
the other hand, no mode has little shares. Comparing
to Bangkok – Hanoi route, the maritime transport
generally occupies smaller shares. This implies that themaritime transport holds relatively weak advantage
over the land transport modes due to its much longer
transport distance.
As an overall trend, achievements of time andemission reduction targets are worse than those of costand emission reduction targets. That is because timeand emission are often in the relationship of trade-off.
This study quantitatively reveals the efficiency of the
new railway construction.

optimal modal splits for respective scenarios, targets
and routes were calculated and the trends anddifferences between them were also revealed. Morespecifically, on Bangkok – Yangon route, maritime
transport holds relatively weak advantage over theland transport modes due to its much longer transportdistance. The results also implied the efficiency of the
new railway construction on the both case study routes
particularly when .the reduction of time and CO2
emission is aimed.
References[1]Hayashi, Y. and Nakamura, K.: Climate change,
mobility and cost of transport, Transport Policy, 2013.
[2] 高橋宏直：モーダルシフト化率の推計方法と動向分析、
国土技術総合研究所資料、No. 407、2007.
[3] Hanaoka, S. et al.: Measurement of energy-saving
effect by intermodal freight transport in Thailand,World Review of Intermodal Transportation Research,
Vol.3, No.4, pp.320-337, 2011.
[4] Yang, X. et al: Analysis of intermodal freight from
China to Indian Ocean: A goal programming approach,
Journal of Transport Geography, Vol.19, pp.515-527,
2011.

4. Conclusion

Modal split (%)

In this study, interregional freight modal split in
GMS was formulated as a goal programming problem
which aimed to achieve the targets of transport cost,transport time and CO2 emission in order to calculate
eco-efficient modal split. Two case study routes,
Bangkok – Hanoi and Bangkok – Yangon, were
examined by the scenarios and targets. As a result, the

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3
Reduction of
Cost andEmission

Reduction ofTime andEmission

Reduction of
Cost andEmission(i) Improvement of existingmodes

Reduction ofTime andEmission

Reduction of
Cost andEmission

Reduction ofTime andEmission(i) Improvement of existingmodes(ii) New rail construction

Hanoi route
Railway

－
23.3

Truck

－
8.4

Reduction of
Cost andEmission

Reduction ofTime andEmission(ii) New rail construction

Yangon route－－－－－ 31.71 12.08 0.39 49.64 66.92 91.69 －0.77 28.74 24.84 14.2
000.52 1.14 2.93
0 35.69 13.93－

048.5 51.12 46.25 25.11

Maritime 76.7 91.6 99.23 71.26 75.16 85.8 68.29 87.92 99.09 49.22 30.16 8.31 64.31 86.07 100－－ 23.93 41.17 70.74 26.97 44.73 80.62

－

0

0

43.77 35.38 19.38

51.5 48.88 53.75 50.96 58.83 29.26 29.26 19.89

0Figure 2 Results of optimal modal split calculations

Degree of unsatisfaction (%)

65
50
55
40
30

≈

20
10
0

Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3 Lv 1 Lv 2 Lv 3
Reduction of
Cost andEmission

Reduction ofTime andEmission

Reduction of
Cost andEmission(i) Improvement of existing modes

Reduction ofTime andEmission(ii) New rail construction

Reduction of
Cost andEmission

Reduction ofTime andEmission

Reduction of
Cost andEmission(i) Improvement of existing modes

Hanoi route

Reduction ofTime andEmission(ii) New rail construction

Yangon routeCost

2.94 1.22

000.21 0.52

0000.77 7.81 13.61 15.95 0.64

0

0

0

0

0

0

Time

4.9

2.52

0

13.3 30.2 68.8
53.8 1.07 0.67

0

0

0

5.12 7.51 11.34 10.21 9.46 21.07 39.17
54.2

0

0

0

0

0

5.85

Emission

0

0

0

5

0

0

0

14.93 4.76

0

0

0

0

0

0.47

0

0

11.4 23.9
55

0

0

3.6

26

0

0

12.22 27.95 51.34
66.3
55
55

Figure 3 Results of degree of unsatisfaction

12

Empirical Research on Effectiveness of Improved Packaging Technologies forTransport Damage on Agricultural Products in Vietnam
Student Number: 11M18108 Name: Yuki TAKEHISA Supervisor: Shinya HANAOKA

ベトナムにおける農産物輸送時損傷に対する梱包技術改善の有効性の実証
竹久 祐貴
本研究では、輸送段階で生じる農産物損傷に対する梱包技術改善の有効性を明らかにすることを目的に、ベトナム現地の農家、輸送業者、小売業者の協力を得てトマトを対象に梱包実験を行い、改善梱包の採算性に関する分析を行った。
その結果、MA 梱包とメッシュバッグを導入することで、損傷の割合が低下することが分かった。また、内装に新聞紙、個装にメッシュバッグを使用した改善梱包の場合に得られる利益が最も高いことが分かった。

1. Introduction

profitability of improved packaging.

Roughly one third of food produced for humanconsumption is estimated to lose or waste
globally, which amount to about 1.3 billion ton
on 20111). Those losses are called food losses
that defined as the decrease in edible food mass
throughout the part of the supply chain thatspecifically leads to edible food for humanconsumption2). Food losses are divided into two
categories. First one is postharvest losses that
occurred on transport, storage, processing andso on. Second one is food waste that occurred onretail and household.
Unlike developed countries, postharvest
losses are serious problem rather than foodwaste. Main causes for food losses in developing
countries
arebasically
attributed
totechnologicallimitations
such
as
poor
harvesting techniques, poor storage and coolingfacilities, poor transport systems and so on1). In
additiontotechnologicallimitations,socioeconomic factors such as inadequate
marketing systems, inadequate transportation
modes, unavailability of needed materials andtools, lack of information, governmental
regulations and legislations are also related3).
In order to reduce the postharvest losses indeveloping countries, this research focuses on
improved packaging. Some field tests ofimproved packaging show that it generates
increased incomes more than 30% to introduce
plastic box instead of sack and add carton as
cushion3). In previous research, they achieved
to identify some effective improved packaging.
However, there are few researches refer to costs
and financial benefits of improved packaging.
Furthermore, the combination of individual
packaging, inner packaging and outer
packaging has not been well researched yet.
Therefore, the research objectives are first tomeasure the performance of improved
packaging with consideration of packaging
combination during transport in developing
countries and second to calculate the2. Evaluation for improved packaging(1) Calculation for the ratio of damage
The ratio of damaged is calculated byfollowing equation.
(1)is the ratio of damage in
Suppose thatis the quantity
improving packaging i (%),
isof damage in improved packaging i (kg),the total quantity in improved packaging i (kg).
Current packaging is also calculated by same
equation.
(2) Calculation for the profitability of improved
packaging
Profitability of improved packaging is
calculated by following equations.
(2)

＝

(3)

is benefit when
Suppose that
introducing the improved packaging i comparedis the profit
to current packaging (VND),
is thein improved packaging i (VND),
profit in current packaging (VND).
Revenue and cost are calculated by following
equation
＝

1

(4)
(5)

13

(6)
is the packaging material
Suppose thatis the labor cost for packaging
cost (VND),
i (VND), ALC is the average labor cost
(VND/sec). Current packaging is also calculated
by same equation.
Fig.2 Hanoi and Da Lat in Vietnam

3. Research target(1) Country and productVietnam, Tomato are selected since Vietnam
is severely constrained by tomato losses whichamount to 14.6 million dollars in 20044).
Tomato is selected because amount of
production is high in Vietnam and also highperishability.

From Da Lat to Hanoi, there are many
stakeholders involved to transport. This
research focuses on supply chain with blue line
shown in Figure.3.

(2) Definition of damaged tomato
For this research, damaged tomato is definedas dent, peeling and crack on the tomato’s
surface (Fig.1).

Fig.3 Tomato supply chain
As for their role, big farmer produce tomato
and package tomato to transport from farm topackaging house in Da Lat. In the packaging
house, they remove damaged tomato andrepack tomato to transport to Hanoi. Trader isonly in charge of transporting from packaging
house to transfer point in Hanoi. Big wholesaler
receives tomato from trader, they sell it tomarket retailer in transfer point. Market
retailer transports to retail market to sell to
consumer.
The supply chains are divided into 3 stages.
Each stage has different road condition,transport mode, transport time (Table.1).

Fig.1 Damaged tomato (Dent, Peeling, Crack)
The causes of damaged tomato are divided
into 2 categories.
a) Weakening of the tomato’s surface
The quality of tomato decreases after
harvesting due to water loss, respiration. That
results in making tomato’s surface easier to bedamaged.
b) Extraneous impact
Extraneous impact is caused by 3 factors
such as pressure from tomato weight, friction
with other tomatoes and outer packaging,strong impact from the unpaved road.

Table.1 Condition in each stage
Stage 1
Stage 2
Stage 3

4. Tomato supply chain

For consumer in Hanoi, they are basicallysupplied by neighborhood production area.
However, Da Lat in southern part becomesmain supply chain on July, August due toseasonality. Supply chain from Da Lat to Hanoi
is selected since field survey was conducted onthat period. The distance between them isabout 1600 km (Fig.2).

Road condition

Unpaved

Paved

Paved

Transport mode

Small truck

large truck

MotorbikeTransport time

1 hour50 hours

1 hour

5. Experiment of improved packaging(1) Types of packaging
Packaging is divided into 3 categories. There
are outer packaging, inner packaging andindividual packaging.

14

(2) Current packaging
For current packaging, plastic crate is usedas outer packaging and newspaper is used as
inner packaging. Capacity of plastic box is 25kg.

(4) Procedure of packaging experiment
The procedure of packaging experiment isfollowing steps.
a) Making improved packaging
2 plastic crates are used for packaging
experiment. Specifically, Current, Improved1,
Improved2 are put together in one plastic crate
and Improved3, Improved4, Improved5 are put
together in other one plastic crate (Fig.5).

(3) Improved packaging
Improved packaging is proposed based on
current packaging, effectiveness for reducing
the damage, packaging availability in Vietnam.
The number of combination of improved
packaging is 5 in total (Table.2).
a) Carton
Carton could be used as inner packaging thatput inside of plastic craters. It has cushion to
reduce extraneous impact.

Fig.5 Packaging for experimentb) Transport
After sorting tomato into plastic crates,
packaging is loaded on truck or motorbike.
Then packaging is transported.

b) Mesh bag
Mesh bag is used as individual packaging
that reduce extraneous impact (Fig.5). The
capacity is about 1.3kg. It is currently using in
supply chain for supermarket.

c) Measurement for damaged tomato
After transport, damaged tomato is checkedby visual contact. After sorting, weight ofdamaged tomato is measured.

c) MAP (Modified Atmosphere Packing)
MAP is used as individual packaging that
automatically modifies the composition ofinternal atmosphere of a package in order toreduce the speed of weakening of the surface(Fig.4). It also reduces the extraneous impact
since it’s made by thick plastic bag. The
capacity is about 1.0 kg.

6. Results(1) The performance of improved packaging
From Table 4, we could see the performanceof improved packaging. As for inner packaging,carton doesn’t reduce the damage compared tonewspaper. It means that newspaper is enoughto reduce the damage or inner packaging
doesn’t have important role to reduce.
As for individual packaging, MAP, Mesh bag
reduce the damage compared to without
individual packaging. Both packaging seems tohave same effect on the damage.
(2) Goodness of fit test
Goodness of fit test was conducted to test the
hypothesis that carton has same effect withnewspaper and also Mesh bag has same effectwith MAP. As for comparison between
newspaper and Mesh bag, we assume that theeffect of newspaper is correct. The calculation isshown in Table 4. As for individual packaging,same calculation was conducted in both stage 1
and stage by assuming that the effect of Meshbag is correct (Table.5). From the results, we
could see that no significant difference between
newspaper and carton, and between Mesh bag

Fig.4 Mesh bag (left) and MAP (right)
Table.2 Combination of improved packaging
Outer
Inner
Individual
Plastic
Newspaper
Current
Plastic
Newspaper
MAP
Improved1
Plastic
Newspaper Mesh bag
Improved2
Plastic
CartonImproved3
Plastic
CartonMAP
Improved4
Plastic
CartonMesh bag
Improved515

and MAP.
1,000,000
500,000
0‐500,000‐1,000,000‐1,500,000‐2,000,000‐2,500,000

Benefit (VND)(3) The effect of road condition on damage
From Table 4, we could see that the ratio of
damage in stage 1 is highest since the roadcondition in stage 1 is not paved (Fig.6)

Stage 1
Stage 2
Stage 3

0.332
0.075
0.3
0.042

0.4
0.1
0.4
0

Costs (VND)

Improved5

Expected frequency

0.3
0.075
0.3
0

Mesh bag

Improved 5

Ratio of damage

MAP

Improved4

13.2%
1.3%
NA
NA
NA
NA

In this paper, the packaging experiment was
conducted to measure the performance ofimproved packaging and calculate theprofitability. We conclude that postharvest
losses could be reduced and made benefit byintroducing the improved packaging that use
newspaper as inner packaging and Mesh bag as
individual packaging.

Reference
1) FAO. (2008), GLOBAL FOOD LOSSES AND
2)Table.5 Comparison between Mesh bag and
MAP in goodness of fit test
Stage 1
Stage 2Mesh bag

Improved3

7. Conclusions

Table.4 Comparison between newspaper andcarton in goodness of fit test
Newspaper
CartonObserved frequency
4
6.72
Ratio of damage
0.25
0.25
Expected frequency
4
4
0
1.84

Observed frequency

Packaginglabor cost
PMC(Meshbag)
PMC(MAP)
PMC(Carton)
PMC(New
spaper)
PMC(Plastic crates)

Fig.8 Cost of packaging for 1000kg of tomato

Stage3

5.0%
0%
0%
8.6%
0%
0%

Improved2

25.0%
7.5%
8.3%
27.3%
10.0%
6.7%

Improved1

Current

Current
Improved1
Improved2
Improved3
Improved4
Improved5

Improved 43,500,000
3,000,000
2,500,000
2,000,000
1,500,000
1,000,000
500,000
0

Table.3 The ratio of damage
Stage2

Improved 3(4) Profitability of improved packaging
From Figure 7,8 we could understand thatmost profitable packaging is improved 2 thatuse newspaper as inner packaging and Meshbag as individual packaging since it uses
individual packaging and costs is cheapest. It’s
profitable in both stage 1 and stage 2.
On the other hand, other packaging is all
unprofitable since cost is higher than benefit of
improved packaging (Fig.7). In particular, Costof MAP and Carton account for big proportionof cost (Fig.8).

Stage1

Improved 2

Improved 1

Fig.7 Benefit of improved packaging for 1000kgof tomatoFig.6 Paved road (left) and Unpaved road(right)

3)

MAP

0.268
0.1
0.4
0.001

4)

16

FOOD WASTE
Parfitt, J., Barthel, M. and Macnaughton, S. (2010),
Food
waste
withinfood
supplychains:quantification and potential for change to 2050,
Phil. Trans. R. Soc., vol. 365, pp. 3065-3081
Saran, S. and Roy, S.K. (2012), Appropriate
postharvest
technologies
for
small
scale
horticultural farmers and marketers om SibSaharan Africa and South Asia – Part 2. Field trial
results and identification of research needs forselected crops, Proc. XXVIIIth IHC
Weinberger, K.C., Genova, I.I. and Acedo, A. (2008),
Quantifying postharvest loss in vegetables along
the supply chain in Vietnam, Cambodia and Laos,Int. Postharv. Technol. Innov. 1:288-297

AIRPORT DESIGN GUIDELINE AS A HUMANITARIAN LOGISITCS BASE
Student Number: 11M51241 Name: Sunkyung CHOI Supervisor: Shinya HANAOKA
Airports play a critical role as a node for humanitarian logistics when natural disaster hits a region. However, there are no guidelines governing space allocation of an airport. This paper proposes a design guideline
for an airport as a humanitarian logistics base concerning two components mainly: 1) base camp (space for
emergency workers), 2) staging area (area to deal with sorting, storing, loading and unloading relief goods).
We develop a methodology to estimate total area of the base and visualize layout by space planning. The
result suggests approximate size and layout of a base camp and a staging area to be included as a humanitarian logistics base. The space planning methodology is further applied to Shizuoka airport as a case study.

1. Introduction

Current practices of humanitarian logistics are mostly led
by government operation. Kapucu et al. (2007)[2] mentions
that there are no officially-documented guidelines regarding staging area selection as emergency management
planning. Therefore, This research follows a methodology
framework as in Figure1 in order to assist design guideline
for space allocation of an airport as a humanitarian logistics
base.

Following the March 2011 earthquake and tsunami,
there was a certain need to revisit disaster management
planning of infrastructures regarding natural disaster. Since
disasters come in all different sizes and impacts, it is difficult to predict and response well in some situations.Therefore, it is important to build a sound disaster
preparedness plans in many disaster prone cities andcountries, this research would lead academics and practitioners to attain attention for disaster management planning.
In emergency logistics or humanitarian logistics, it is
known that air transport is more used than normal cases
since destructive damage in land transportation modes andthe other transportation modes. As a node for enabling
immediate disaster response, some argues that it is preferable if staging area can be set up within an airport sincemost regional airports have vacant space which enables
various activities, accessibility, hard stand area for loading/unloading goods, and helipads.
Despite critical role of airports in humanitarian logistics,
some limitations still lie in airports space usage inpost-disaster. Such space constraints are mentioned in
Hanaoka et al. (2013)[1]. The author argues that airports
need to deal with the space constraints in order to be prepared well enough to deal with humanitarian logistics operation in airports. In this study, two space constraint issues
are to be answered by research question. Two issues arespace for emergency workers and place for relief goods.
The fundamental question that the author intended toaddress is how to plan space allocation of a humanitarian
logistics base in an airport. By answering this question, thisresearch aims to propose a design guideline for an airport asa humanitarian logistics base. There are three objectives
that derived from the research goal.
1) Estimate area of required facilities in a humanitarian
logistics base2) Make a bubble diagram for each facility3) Draw a schematic plan for Shizuoka airport based on
scenario analysis
By achieving objectives, this research would make an
attempt to deal with space limitation issues in an airport inpost-disaster and assist effective decision making in planning a humanitarian logistics base in an airport with regard
to space planning.

Humanitarian logistics base in an airport

Base camp

Staging area

Define functional areas in each facility
Area estimation method
Area calculation of each facility
Space planning
Make an adjacency matrix andadjacency requirement

Create a bubble diagram
Draw a schematic plan

Design guideline for a humanitarian logistics base in an airport
Figure1: Framework for a humanitarian logistics base

2.2 Area estimation method
2.2.1 Calculation method for a base camp
Data was collected through government’s project papers
and practical emergency planning in Florida, U.S.A. [3]Figure 2 explains flow for a base camp estimation. In thispaper, required number of emergency workers (m) is defined as 100, 250, 500, 750 and 1000 in this study in orderto support standardized guideline for base design. The
following equation (1) and (2) is for calculating eachfunctional area to be included in a base camp.
Unit area u is defined as 30m2 for minimum estimation and
50m2 for maximum unit area (MLIT, 2003)[4].
is estimated based on current practices of base camp design inFlorida State Emergency Planning of United States. Total
area of base camp is a sum of all functional areas within thearea. Functional areas are noted as, when considering m
number of emergency workers.

2. Methodology
2.1 Methodology framework
A proposed methodology would be formulated by unfying ideas of practical projects and acadmic researches.

17

Input70000. Total area of a staging area consists of three parts
which are warehouse, support area for workers, and open
area for loading and unloading goods. Equation (4) explains required space for warehouse in order to store humanitarian aid goods Equation (5) is for support area withunit area of 30m2 equation (6) explains open area for staging area.

OutputTotal number ofdestroyed houses

× 0.4

× u × 𝑅𝑘

Required number of
emergency workers(m)Required number of emergency workers (m)Space for accommodation
(𝐴1𝑚)

× 𝑅𝑘
Space foraccommodation (𝐴1𝑚)

1Space for clinic (𝐴𝑚2)Space for administration (𝐴𝑚3)∑Space for toilet (𝐴𝑚
5)
2

k

m
u

(

)

3

(1)

Each amount of aid
goods (j=1 to 5)

Each amount of aid
goods (j=1 to 5)
Total number of aid
goods

× 𝑟𝑗 × 𝑠𝑗
× unit area*

(

× )×

(∑

)

(∑

× )×

(

)

(6)

1

space for warehouse when total number of affected population are p2

space for support area when affected population are p3

space for open area when number of affected population are pp

total number of affected population

jidentification for items needed for affected population
j = 2: foodj = 3: blanket
j = 4: mandatory kit
j = 5: temporary toilet
required amount for item j per one person
scale factor of item j from converting weight to area

2.3 Space planning
2.3.1 Adjacency matrix
Adjacency matrix is used in architectural planning inorder to see relationship between each functional area in abuilding.[5] The adjacency diagram would let designers to
identify the proximity requirements. This does not havedefinite answer for concluding the best answer and there
may lay various approaches.
2.3.2 Bubble diagram and schematic plan
Architectural bubble diagrams are used to consider
layout of functional areas in a floor plan. Bubble diagrams
are to explore relationships among the sizes, adjacencies,
and approximate shape of the spaces needed for various
activities. A schematic plan is a revised version of bubble
diagram before planning actual floor plans as in Figure 4.

𝑝

Space for warehouse (𝐴1 )𝑝Space for support area (𝐴2 )Space for open area𝑝
(𝐴3 )Total Area of
Staging Area(𝑇𝑠 )2(5)

j = 1: water

2.2.2 Calculation method for a staging area
Total number ofaffected population (p))

total area of staging area

total area of base camparea for functional space k when total m number of emergency
workers
identification of each functional space in base camp
k = 1: space for accommodationk = 2: space for clinic
k = 3: space for administrationk = 4: space for shower roomk = 5: space for toilet
k = 6: space for recreation centerk = 7: space for laundry roomk = 8: space for dining and kitchen
k = 9: space for staff
k = 10: space for management
ratio of functional space
to 1 ,
when k = 1
number of required emergency workers
unit area for base camp per one emergency worker
Output

(

1

(2)

Input

(4)
×

1

Total Area ofBase Camp (𝑇𝐵 )

×

×

1

⋮

×

)

1

Space for shower (𝐴𝑚4)

Figure 2: Calculation flow for a base camp
∑ 1
(
)

(3)

3

(

∑

1

2

Figure 4: Graph representation in bubble diagram
Source: Adapted from Ruch (1978)[6]2Unit area* for support area is 30m and for open area is 50m

3. Result

Figure 3: Calculation flow for a staging area

3.1 Base campCalculation flow for size of staging area is calculated
dbased on Figure3. In this study, the number of affected
population is assumed defined as 10000, 30000, 50000, and3.1.1 Functional area estimation in a base camp

18

Approximate size of base camp area is calculated inTable 2. If 1000 workers would support humanitarian logistics in an airport in a base camp adapting a minimum
unit area, accommodation area is approximately 9009.00m2
and total area for base camp is assumed as 3ha.

9009.0 6756.7 4504.5 2252.2 1351.3

900.9

Clinic1126.1

844.5

563.0

281.5

168.9

112.6

Admin

1126.1

844.5

563.0

281.5

168.9

112.6

to secure enough space, 120% of total sum of each area isregarded as 1288.98 m2. Table 3 shows estimation forsupport area for workers in staging area. Total support area
when assisting 10000 people is 4042.5 m2. Table 4 shows
estimation for open space in staging area. When supporting
10000 people, outdoor handling and staging is required as
4812.5m2 and flexible use is as 4812.5 m2 and parking
space would be as 9625 m2. Table 5 shows open area estimation. Total open space would be approximately 1.9ha
when supporting 10000 people. Outdoor handling andstaging area and flexible use are assumed to be the samesize.

2252.2 1689.1 1126.1

563.0

337.8

225.2

Table 2: Storage area estimation in a staging area (Unit:m2)

Toilet1407.6 1055.7

703.8

351.9

211.1

140.7

Affected population

Shower1407.6 1055.7

703.8

351.9

211.1

140.7

Water

342.3

Laundry

563.0

281.5

140.7

84.4

56.3

Food

396.9

Table 1: Base camp area estimation (Unit:m2)
Emergency

1000

workers
Accommodation

Recreation center

Dining/Kitchen

750

422.2

500

250

150

100

12263.5 9197.6 6131.7 3065.8 1839.5 1226.3

Staff

563.0

422.2

281.5

140.7

84.4

56.3

Management

281.5

211.1

140.7

70.3

42.2

28.1

Total

30000

22500

15000

7500

4500

3000

3

2.25

1.5

0.75

0.45

0.3

Total(ha)

10000

30000

50000

70000

1026.91711.52396.11190.7

1984.52778.3

Blanket

133.2

399.6

666.0

932.4

Mandatory kit

111.0

333.0

555.0

777.0

Toilet

90.7

272.2

453.7

635.2

1288.93866.96444.99022.8Storage area

Table 3: Support area estimation in a staging area (Unit:m2)

3.1.2 Space planning
Figure 5 shows immediate proximity and convenientproximity are assumed on base camp design from practicaldesigns of State of Florida (2009). Immediate proximity
means strongly recommended being located near eachother, and convenient proximity means better to be locatednear each other.

Affected population

10000

Workers
Accommodation
OfficeToilet/shower
Catering area
Common area

135
3234
202.1
202.1
202.1
202.1

30000
404
9702
606.3
606.3
606.3
606.3

50000

70000

674
16170
1010.61010.61010.61010.6943
22638
1414.81414.81414.81414.8Support area
4042.512127.520212.5
28297.5
Table 4: Open area estimation in a staging area (Unit:m2)
Affected population

10000

30000

50000

70000

4812

14437

24062

33687

4812

14437

24062

33687

Parking space

9625

28875

48125

67375

Open area

19250

57750

96250

134750Outdoor handling/staging
Flexible use
Figure 5: Adjacency matrix in a base camp

An initial bubble diagram and its adjusted figure withconsidered each functional area’s relative size is in Fig.6.
Staff area and management area are combined for simplicity in a diagram. It can be easily seen that 1 and 8 which areaccommodation area and dining/kitchen area consist mostof base camp gross area. The largest part within base camp
is dining/kitchen area and accommodation area. (1: Accommodation, 2: Clinic, 3: Administration area, 4: Recreation center, 5: Toilet, 6: Shower, 7: Laundry, 8: Dining/Kitchen, 9: Staff/Management)

The result from Table 7 suggests an approximate size of
total staging area estimation combining Table 4, Table 5,
and Table 6. In order to assist 10000 affected population,
staging area is required as 2.45 ha within a humanitarian
logistics base.
Table 5: Total area estimation of a staging area (Unit:m2)
Affected population

10000

30000

50000

70000

Staging Area
Staging Area(ha)

24581
2.45

73744
7.37

12290712.29

17207017.2

3.2.2 Space planning

Figure 6: Bubble diagram for a base camp

3.2 Staging area
3.2.1 Staging area functional area estimation
Estimation for storage in staging area is indicated inTable 2. In order to support 10000 people, total sum of eacharea for goods required is assumed as 1074.15 m2. In orderFigure 7: Adjacency matrix in staging area

The result of space planning are adjacency matrix andbubble diagram. Adjacency matrix is drawn in order tounderstand space relationships within a facitliy as in Figure

197. All functional areas in a staging area are located close toeach other concerning proximity. Basic architectural planning concept is utilized in building adjacency matrix.
Figure 8 shows relative size of staging area and howeach functional area is related to each other. Open area arecorrelated each other in order to assist smooth flow of aid
goods. Parking space would take the position as the biggest
part for staging area due to unexpected amount of vehicles
and aid goods may clog in the area. (1: Storage, 2: Accommodation area, 3: Office, 4: Toilet/shower, 5: Cateringarea, 6: Common area, 7: Outdoor handling and staging, 8:
Flexible use space, 9: Parking space)
Figure 11: Layout plan for Shizuoka airport

4.3 Discussions
The result suggests an approximate size of a base campand staging area. It also visualizes by following spaceplanning as an output of a bubble diagram and a schematicplan. The case study of Shizuoka airport suggested that
schematic plan may be larger than current size of eachfacility in Shizuoka airport since this study didn’t consider
space for aisles between goods in warehouses. The otherreason is that hardware of architctural planning such as
thickness of walls or other infrastructures allocations are
not included. Following methodology of the study, staging
area is comparatively smaller than the current plan. Moreconsideration in revising relationship of the facilities insideof a humanitarian logistics base is recommended. The otherconsiderations would be needed in determining how thesize of a base can be determined.

Figure 8: Bubble diagram for a staging area

4. Case Study
4.1 Scenario building
According to Tonankai disaster scenario by Cabinet office of Japan (2007), affected population and needed
emergency workers in Shizuoka prefecture are 43,000
people and 17,000 people respectively. Shizuoka airport isassumed to cover between 25% and 30% of total required
emergency workers and number of affected population.
Current space constraint of a land area is assumed approximately as 16ha.

5. Conclusions

4.2 Space planning for Shizuoka airport

This study proposed a design guideline for a humanitarian logistics base in an airport, and has presented its
conclusion by integrating calculation model and architectural planning methodologies. This study is unique in asense that it tackled an issue in border with architecturalplanning, humanitarian logistics and air transport studies.
This research is an initiative research in airport as a humanitarian logistics base with various disciplines. This
thesis investigated each facility space allocation and its
inner space planning issues. Several future studies might
focus on the following remaining issues such as mathematical model development concerning airport constraints
and its coverage in region. Also, integration with urban
planning perspective can be later developed in understanding relationship between the base and surrounded environment.

Fig.9 and Fig.10 shows space planning of a base camp
and a staging area by the proposed methodology. Initial
bubble diagrams are developed into a schematic plan. This
process is iterative in a sense that it aims to locate ascompact ac possible.

Bubble diagram
Rectangular formation
Schematic plan
Fiure.9: Base camp planning process

References[1] Hanaoka, S., Indo, Y., Hirata, T., Todoroki, T., Aratani, T., and Osada, T. ,“Lessons and Challenges of Airport Operation during a Disaster: Case
Studies of Iwate Hanamaki Airport, Yamagata Airport, and Fukushima
Airport during the Great East Japan Earthquake”, Journal of JSCE, Division
F: Construction Engineering and Management, In Press. 2013.
[2] Kapucu, N., Lawther, W., Pattison, S., “Logistics and staging areas inmanaging disasters and emergencies”, Journal of Homeland Security andEmergency Management, Vol. 4, No. 2, pp.1-17, 2007.
[3] State of Florida, Division of Emergency Management Logistics Section,“State of Florida: State Unified Logistics Plan”, 2009.
[4] MLIT, Nagoya Regional Disaster Prevention Network Working Group.,“Simulation on Estimation Ideas of Case Studies”, 2003.
[5] Demkin, J. The American Institute of Architects., “The Architect’s Handbook of Professional Practice”, 13th edition, 2001.
[6] Ruch, J., “Interactive Space Layout: A Graph Theoretical Approach”,
Proceedings of the 15th conference on Design automation, pp.152-157,
1978.

Bubble diagram
Rectangular formation
Schematic plan
Figure 10: Staging area planning process

Fig. 11 is a combined schematic plan as a humanitarian
logistics base. This shows a layout for a humanitarian logistics base within current Shizuoka airport layout plan. It
is estimated that gross land area of a base may be estimatedaround 16ha.

20

Study of the Effect of ICT on Antenatal Carein Remote Mountainous Region of Nepal
Student Number: 11M18083 Name: Kazuhiro KAMIYAMA Supervisor: Jun-ichi TAKADA
ネパール山岳地域での情報通信技術を用いた妊産婦の保健管理の効果に関する研究

神山 和大
本研究では, ネパールの山岳地域に住む妊産婦を対象に, ICT を活用することによって, 母子医療保健知識を提供するプロジェクトを通して現地の村でアンケート・インタビュー調査を実施した. 調査結果から, 妊産婦がプロジェクトや Web アプリケーションに対して高い満足度を示していることがわかった. また,Web アプリケーションによって,5 つの指標(食事・娯楽・家族との関係性・家事・休暇)のうち娯楽以外の 4 つの指標に対して妊婦の行動や彼女たちの家族の意識を改善することができたことが確認された.

1. INTRODUCTION
The reduction of maternal mortality has now become oneof the leading global health agendas as emphasized inMillennium
Development
Goals(MDGs)
5.
Approximately, 300000 women died worldwide due tocomplications related to pregnancy or childbirth in2008[1]. The maternal mortality rate is particularly high inpoor developing countries such as Nepal. In Nepal,
maternal mortality rate is 170 per 100,000 whereas in the
average of world maternal mortality rate is 66 per 100,000.
Since this is the average rate of whole nation, the situation
is more serious in the marginalized and poor community
living in high altitude and remote rural areas of Nepal [2].
There are various reasons such as traditional customs,
cultural barriers, lower literacy rates, as well as lack ofinfrastructure and qualified doctors [2]. It is known that
antenatal care (ANC) is an important factor in reducing
the maternal mortality. And information andcommunication technology (ICT) can be an effective tool
to connect pregnant women to health services in remoteareas.

Figure1. Schematic view of project
The city doctors develop the education contents ofantenatal care for pregnant women and make it available
on the Internet by uploading them to the ENRD servers.
Due to the Internet bandwidth constraints at the remotevillages the contents are mainly texts and audio recordings,
although few videos are also available.
The FCHV, nominated by individual villages, aretrained by the project to handle laptop or tablet PC. They
download the information onto a laptop or tablet and takeit to the pregnant women's home. Moreover, pregnant
women can register on the Web site of the project, which
provides them with antenatal care information. As theylogin with her username and password they will start toget antenatal care related audio, video and text contents
according to the stage of her pregnancy. Doctor and
Health worker can also login to track and support pregnant
women under their supervision. The main objective of thisweb application is to establish network among pregnant
women, FCHV, health Post, and city hospital, and tomonitor the situation of pregnant women.
In Nepal the internet penetration rate is just over 20.9%
with majority of them using mobile internet and mainly,
located in urban and city area [3]. However, Nepal
Wireless Networking Project (NWP) led by ENRD has
already networked health posts in more than 200 villages.
All of the health posts have PC [4].
This project developed a Web application to provide
pregnant women with antenatal care information. This
project also enables the health posts in each village, local
pregnant women, and the hospital in Kathmandu toconstantly contact each other through the ENRD server.

2.RESEARCH BACKGROUNG
2.1 Mother and Child Protection Program
implemented by E-Network Research andDevelopment
The author is involved in Mother and Child Protection
Program (MnCP) in Nepal. This study focuses onantenatal health care element of the Child Protection
Program being implemented by E-Network Research andDevelopment (ENRD) from 2011 December in 15 villages.
ENRD is a non-profit and non-governmental organizationin Nepal. Its goal is to empower and support ruralcommunity through the use of ICT. Figure 1 shows theschematic view of project. In this project, there are four
primary stake holders; 1) the city hospital doctors in
Kathmandu, 2) Female Community Health Volunteers(FCHV), 3) community health worker and 4) pregnant
women in the villages. The secondary stake holders are
Ministry of Health/Local government, Internet Society(ISOC) as the funding organization, ENRD as a project
organization, and the families of pregnant women.

21to TV or FM Radio. Furthermore, by using this Web
application pregnant women were able to better
understand FCHV’s advice. However, question 2, 3 shows
relatively low score. It indicates this project cannot be analternative to medical services.

2.2 Research Objectives
In this study, we focused to see how satisfied thepregnant women were after receiving the antenatal careinformation through the project. We used questionnaireand focus group methodology for data collection purpose.
The objective of research is as follows;
1) To investigate the attitude and behavior of pregnant
women with regard to the maternal health in the
project site2) To study how the project (Child Protection Program)is important towards maternal health care in
mountainous regions of Nepal
3) To present possible issues and the future direction of
the project through the above discussion

Table

1.

5-scale evaluation
application(N=60)

Questions

of

the

Web

ResultMean value

1.
2.
3.

2.3 Methodology
To know the effect of the project/Web application andthe attitude and behavior of pregnant women in the remotevillages after they received antenatal health careinformation through the use of Web application, this study
conduct the questionnaire survey and interview survey in
6 villages (Tolka, Histan, Shikha, Keshabter, Nangi,
Dadagau ) .
The details of the questionnaire and interview survey
are as follows;
1) Questionnaire survey
 5-scale evaluation of Web application
 5-scale evaluation of the project Basic information of pregnant women2) Interview survey (Individual, Focus group discussion) The current situation of the project site (e.g.,superstition in the villages)
 Pregnant women’s prior knowledge about
antenatal health care before participating in the
project
In this study, the research procedure is as follows;
1) Making the questionnaire which will enable us toevaluate the effect of the project.
2) Conducting a field survey in remote 6 villages of
Nepal to solicit answers to these questionnaires frompregnant women.

4.
5.

6.

7.
8.

This web application is better
than FM radio and TV programs.
This web application can replace
hospital service.

4.85
2.67

This web application can reduce
the number of visit to doctor.
I trust this application.
I am confidence with my skill ofhandling computer and mobile touse this application.
This web application improves
relation between me and healthworkers and/or doctors.
FCVH's advices are easy tounderstand.
Web contents are easy tounderstand.

2.75
4.70
4.45

4.73
4.82
4.69

3.2 Result of the questionnaire (2)Table 2. shows the 5-scale evaluation of the project. In
this table, we evaluated the 5 indicators (food, relation
among family, household work, rest, entertainment),
which was selected from the baseline survey. The baseline
survey was conducted by project members from October05- 25, 2011 in Nangi, Tolka, and Dadagau villages.
According to this table, all indicators, except for“entertainment”, got high scores. Particularly, it show thatfamily members became more supportive and paid
attention to pregnant women during pregnancy period and,helped with household work after participating the project.
Moreover, table 2. also indicates that pregnant women got
sufficient rest and improved their eating habit.
Table 2. 5-scale evaluation of the project (N=59)

2.4 Field survey
The field survey was carried out from 21st November
2012 to 1st December 2012, and from 22nd to 25th
December 2012 in Nepal. The author participated in the
project and observed the pregnant women in the remoteTolka, Nangi, Histan, Khibang, Dadagau and Shikha
villages. In these villages the project is already being
implemented and Internet connection is available. This
study obtained information by means of questionnaire
survey of all the 62 pregnant women who had participatedin this project and received antenatal care information.

Questions

Result
Mean

1.
2.
3.
4.

5.

3.RESULT OF THE SURVEY
3.1 Result of the questionnaire (1)6.

Table 1. shows the 5-scale evaluation of the Web
application. According to this table, Web application ishighly regarded, especially, Web application improved therelation between pregnant women and doctor/TBA, andpregnant women preferred the Web application, compared7.

22

Have you established better
relationship with your family?
Have you improved eating habit
during pregnancy?
Have you shared the houseworkload with other family members?
Have you been respected yourbehavior and feelings from yourfamily?
Have your family members
become serious about pregnancy
related issues?
Have you enjoyed entertainment,such as sightseeing, group
dancing, picnic?
Have you taken rest sufficiently?

value

4.77
4.17
4.48
4.58

4.52

3.38
4.45

In this study, the author tried to evaluate the impact ofusing ICT to provide antenatal care information topregnant women through this project. However, it isdifficult to clarify the impact of the project due to the factthat there are various restrictions such as, in themountainous region of Nepal pregnant women cannot
walk to the health post by themselves. This limits thenumber of times survey can be carried out and therefore
data set. However, in this study we present possible
issues and the future direction of the project through theabove discussion by using socio-technical approach and
Design Reality- Gap.

3.3 Qualitative analysis between baseline
survey and questionnaire survey
Table 3. shows the qualitative analysis between
baseline survey and questionnaire survey. Baseline survey
has been already conducted by ENRD before the author
participated in this project. According to this table, Food
habit, household work, and amount of rest have changed
after pregnant women received the knowledge of antenatal
care through the project by using the Web application.
This is evident from the high score of the Web applicationfrom Table 1.
Table3. Qualitative analysis of this study(N=62)
Baseline survey

Result of this study

Indicators(Food,
Rest,
Entertainm
ent,
Relation,
Household
work)





Web
application

After pregnancy,
they didn’t change
their food habit
andhouseholdwork
Pregnant women
didn’ttakesufficient rest due
to the householdwork
TV and FM Radio
primarily are used
for entertainment
and they gave
lower priority toantenatalcare
broadcast

4.2 Socio-technical perspective
Many researchers (e.g. Checkland and Scholes 1990;
Mumford 1995) support the socio-technical approach for
information system projects. The socio-technicalapproach is theoretically based on the socio-technicaltheory (Emery and Trist 1960) which claims that “atechnological system cannot be separated from the social
system of those involved with it’ (Emery and Trist 1960
cited in Checkland and Holwell 1998: 226). The
suitability of the socio-technical approach for informationand communication technology for development (ICT4D)
projects can be justified (Heeks, 2008). In this project, theWeb application aiming to lessen the gap between
mountainous region and urban areas by providing
pregnant women with the antenatal care information.
Although, in this study, questionnaire survey shows that
Web application is highly regarded among pregnant
women, as many researchers (Madon 1994; Castells
2001; Heeks 2002b) mentioned, the social, economic andcultural environments determine the extent to whichpeople can benefit from ICT. (Sein and Harindranath2004). In this study, pregnant women were socially andgeographically in a difficult position to get the benefit of
ICT. Therefore, FCHV might have a vital role to play as
an interface between the pregnant women and technology.

Changed their food
habit and decreased
the household work
after pregnant women
received information
through the project
Took sufficient rest
during pregnancy

Acquired antenatal
care
information
through the use of
Web application
They believe the
Web application isreliable, and they aresatisfied with it

3.4 Result of interview survey
In parallel with conducting questionnaire survey, theauthor conducted the interview survey of pregnant womenin the remote villages of Nepal. From the interview survey,
there are two findings.
Firstly, superstition still exists in the remote villages. For
example, few pregnant women believe that it is good to
eat lots of food during pregnancy and that if they work
hard during pregnancy it becomes easier to give birth to ababy. Few pregnant women believe that babies should
sleep only as long as adults.
Secondly, pregnant women could have used the media asa means to get antenatal care information even before
participating in the project, however they did not use themedia such as TV and FM Radio to obtain the antenatal
care information. Instead if the pregnant women had time
to watch TV or listen to FM Radio, they spent their time
only entertainment program. Therefore, most pregnant
women have on snippets of knowledge about antenatal
care because they did not watch TV and listen to FM
Radio for related broadcasts.
Therefore, expected effects of the project are as follows:
1) improve the 5 indicators (food, relation among family,
household work, rest, entertainment) by providing theantenatal care information; 2) weaken the influence ofsuperstitious and wrong traditional beliefs regarding
antenatal care.

4.3 User participation
On the other hand, many researchers pointed out thatuser participation is important factor in order to make the
ICT4D projects a success ( Hickey and Mohan, 2004 ).
Heeks (2008) state that one of the paradigm shifts fromold ICT4D projects to the latest ICT4D projects is to treat
local users as producers, not consumers. Therefore, in thisproject, pregnant women are required to participate
actively to lighten the FCHV’s work load. To providing
opportunities to use Web application and to participate inthis project can contribute not only to motivating them
but also to making them confident. In other words, it is anempowerment of local users (i.e. pregnant women).

4.4 Design-Reality Gap
The importance of the socio-technical approach withuser participation is clarified. However, one more problem
is the gap between project design and reality. Unless the
gap is minimized, it is quite difficult to realize projectsuccess. The ITPOSMO checklist (Heeks 1999a; 2006) isa useful tool to evaluate and measure the gaps from thepoint of the socio-technical perspective since it covers
both technical and the other dimensions such as
Information, Technology, Process, Objectives/Value,

4. DISCUSSION
4.1 Limitation of this study

23

Skills/Staffs, Management/Structure, Other resources(Time/money). Table 4. shows the Design-Reality Gap of
this study. According to the table, under the factors of
information, process and skill, FCHV were burdened withmany tasks such as, they explain the Web application bybringing laptop/tablet to pregnant women’s home.
Furthermore, under the factors of technology andobjective/value, the villages currently have serious
problems such as, poor electric infrastructure and theInternet connection. These problems were not consideredduring project design.
Table4. Design-Reality Gap of this study
DesignFactorInformation

The project develops the
Web application, which ismade with the advice ofdoctors in Kathmandu, andthen FCHV explain thisapplication by visiting
pregnant women’s home.

Technology

Web application provides
pregnant women withadequate antenatal careinformation anytime.

Process

As they login with herusername and password
pregnant women start toget antenatal care related
audio, video and text
contents according to stageof their pregnancy.
To introduce localized ICT
tools to the rural women,
which will directly
enhance the digital literacy
and improve their behavior
relating antenatal careinformation
FCHV were trained by the
project on how to use the
Web application and theyin turn explain it to thepregnant women

Objective/Va
lue

Skill /Stuff

Management/
Structure

The project recommend
pregnant women to go to
the health post in thevillage in order tocommunicate with the
medical doctor via
Internet.

women through more active participation in the project.
Actually, in this study, questionnaire survey shows that
Web application is highly regarded among pregnant
women. However, this means that pregnant women
depends on FCHV for using the Web application and alsocome to bring it to their home. However, in terms of
success of ICT4D project, users (pregnant women)
participation can be one of the possible solutions to lessen
the design-reality gaps.

5.CONCLUSION
In this study, antenatal care information provided
through the Web application improved the attitude andbehavior of pregnant women in the 4 indicators (food,
relation among family, household work, rest) except for“entertainment” after they participated in the project.
Moreover, this study found that FCHV plays vital role
to take ICT to pregnant women. Also through the analysisof the socio-technical approach and Design-reality Gap,
FCHV, who introduced and explained how to use the web
application, is found to be integral.
Therefore, to make the ICT4D project successful in thelong term, user participation (pregnant women) might bevery important.

RealityIn the survey, Web
application had highscore However, sincemost of pregnant women
don’t have laptop ortablet PC, FCHV have to
explain the application tothem.
It is necessary to
download the Webcontents for offline use
due to the poor electricalinfrastructure andinternet connection.
Even if FCHV explain
the Web application to
every pregnant womenthe same way, eachpregnant women’s
understanding isdifferent.
Each village has
different to theconnectivity of theInternet and also eachpregnant women’s home
has different theconnectivity.
The frequency of visiting
pregnant women’s home
is different among each
FCHV due to thegeographical conditionin the mountainous area.
Pregnant women cannot
often go to the healthpost, because they havehousehold work and it isdifficult for them to walkin mountainous region

REFERENCES[1] World Health Organization,2012, ”World Health Statistics 2012”,
http://www.who.int/gho/publications/world_health_statistics/2012/en/,(Accessed on March 3, 2013).
[2]Padam Raj Bhatta, 2011, “Nepal Demographic and Healthy Survey
2011”, Ministry of Health and Population [Nepal], United States
Agency for International Development (USAID), New ERA, and Macro
International Inc.
[3]Nepal Telecommunication Authority, 2012, “Management
Information System (MIS) report”, Nepal Telecommunication Authority,
Kathmandu, Nepal.
[4]E-Network Research and Development (ENRD), 2012, “Child
Protection Application”, unpublished report, Kathmandu, Nepal[5]Checkland, P. and Scholes, J., 1990,” Soft Systems Methodology in
Action”, John Wiley & Sons, Chichester.
[6]Mumford, E., 1995, “Effective Systems Design and Requirements
Analysis: the ethics approach”, MacMillan, New York.
[7]Emery, F.E. and Trist, E. L., 1960, “Socio-technical system, inManagement Science Models and Technique”s”, Vol. 2, Churchman, C.
W. and Verhulst, M. (eds), Pergamon, Oxford.
[8]Checkland, P. and Holwell, S., 1998, “Information, Systems andInformation Systems: making sense of the field”, John Wiley & Sons,
Chichester.
[9]Heeks, R. B.,2008a, “The ICT4D 2.0 Manifest”o, Development
InformaticsWorking, Paper Series, Paper No. 30, IDPM, University ofManchester.
[10]Madon, S.,1994, “Designing information systems for development
planning” , Henley, Alfred Waller.
[11]Heeks, R. B. , 2002b, “i-Development Not e-Development: Special
Issue on ICTs and Development” , Journal of International
Development, vol.14, no.1, pp. 1-11.
[12]Sein, M. K. and Harindranath, G., 2004, “Conceptualizing the ICT
Artifact: Toward Understanding the Role of ICT in National
Development”, The Information Society, vol. 20, no. 1, pp. 15 – 24.
[13]Hickey, S. and Mohan, G., 2004, “Participation: From Tyranny toTransformation?”, Zed Books, London.
[14]Heeks, R. B., 1999a, “Reinventing Government in the Information
Age”, Routledge, London.
[15]Heeks, R. B. ,2006, “Implementing and Managing eGovernment:
An International Text”, Sage, London.

4.5 Problem identification
It should be noted that the Web application is used by
FCHV, and not the pregnant women. Considering thisfact, to fill these gaps, this study suggests two points.
First, at the beginning of the project, the project paid
attention to the quality of Web application and how to
distribute the contents to each village. However, thisanalysis suggests the most important thing is how often
FCHV can visit the pregnant women’s home which isdifficult in the mountainous region, and explain thisapplication.
Second, as social-technical approach discussed, FCHV's
burden have to be reduced and shared by the pregnant

24

Contribute of ICT Use to Promote Student-Centered approachin Primary Schools in Mongolia
Student Number: 11M18172 Name: Shotaro Yano Supervisor: Shinobu YAMAGUCHI, Jun-ichi TAKADA

モンゴルの小学校での「子ども中心の指導法」における ICT ツールの活用に関する分析
矢野	
  晶太郎
近年、モンゴルにおいて、教育の質の向上のために情報通信技術(ICT)の導入と従来の指導法から「子ども中心の指導法」への転換が促進されている。本研究においては、小学校で実際に利用されている各種 ICT ツールが「子ども中心の指導法」に有用であるか分析を行う。その結果、教員は ICT を授業で活用することに積極的であり、ICT ツールは「子ども中心の指導法」を促進させる上で有効なツールということが判明した。反面、機材の不足、ICT を使用して効果的な教材を作成するための知識や技術が課題となっていることが明らかとなった。

1.

Background Information
In the early 1990s, Mongolia experienced
decentralization and democratization of its
government, along with a transition to a freemarket economy. The education sector also
encountered problems such as a fall in the
education budget, decreasing literacy rate, urban
migration of rural teachers, and also inadequate
infrastructure. As a result, the Mongolian
government enacted several policies to addressthese issues described in Table.1.

depending on what adults want; in this way claiming thatchild will be more creative and freer [2]. The several
institutes such as UNICEF, UNESCO and JICA pointed
out the important factors of student-centered approach.
lskills acquisition; it is also about constructing
knowledge with others (UNICEF)l

and leaner-centered teaching and leaning strategies
and citizenship objectives implicit in reorienting
education towards sustainable development (UNESCO)l

Mongolian
GovernmentPlan(2008-2012)

ActionEducation
MasterPlan (2006-2015)
Information andCommunication
Technology in
Education Policy(2012-2016)

Students take lesson themes as their own and findsolutions on their own by using their mind and body,and through interacting with others (JICA)

In Mongolia, student-centered approach has
been introduced MES since 1990s. However theclear definitions of student-centered approach has
not been shared in Mongolian context [3].
1.2 Scratch as a tool to creating teaching materials
Scratch is the programming learning
software for children was developed by MIT
media lab [4]. And in Mongolia, Scratch wasintroduced for creating teaching materials
through educational project since 2011 [5] for thefollowing features: 1) it is free and open source
software, 2) Mongolian language can be used, 3) it
includes many ready-made materials suchillustration, pictures and sound, 4) original
materials can be used and 5) it is easy to use.
The feasibility analysis was conducted in2011 [6]. Teachers indicated that 1) scratch can
attract students using animation, 2) scratch canenhance the students’ group work and discussion.
The result showed that Scratch has potential tosupport student-centered approach.

Table 1 Policies related to education

New
Educational
Standard (2005)

To enhance skills for using a wide range of interactivethat underpin the knowledge, critical thinking, values

In 2005 the New Education Standard wasintroduced to promote student-centered approach,a methodology to make students engaged more in
their learning as opposed to a teacher-centeredapproach. By 2012, the Mongolian government
amended the Education Law to encourage thesector to use ICT for further improvement ofeducation quality. Furthermore in 2012, theMinistry of Education and Science (MES)
developed “ICT in education policy”.
New Education Law(1993, 2003)

Leaning is not just about individual comprehension and

Decentralized school management,
more flexibility to manage theschool curriculum.
Increase the schooling year from
10 years to 12 years, promote theuse of student-Centered Approach
Improve the training system forteacher with the use of ICT anddistance learning, increase thenumber of PCs in each school,
Supply every teacher with alaptop, Connect the schools to theinternet
To integrate ICT in teaching andlearning
To increase the use of e-teaching,e-learning content in Mongolian
languageinprimary
andsecondaryeducation
classrooms/teaching

2.

Objectives of Research
In the current Mongolian education sector,
there are two approaches are considered
important to improve quality of education. First,
introducing ICT tools for managing theinformation and developing the teaching material
can enhance school management and teaching.
Second,introducing
thestudent-centeredapproach to deliver effective lessons to 29 pupils
in the classroom teaching [7].

(Source: created by author, 2012)

1.1 Student-centered approach
Kawaguchi indicated that student-centeredapproach was derived from Socratic method thatteachers try to draw out the answers from learner[1]. Yucel defined that student-centered approachaims at training child according to its own nature, not25

reviews in 4 different primary schools on different
regions. This study utilized the classroom
observation to know how teacher implement
student-centered teaching and the use of Scratchteaching materials through lesson assessment
sheet. In total 29 teachers in Bayankhongor and
20 teachers in Ulaanbaatar observed lesson using
Scratch.

However, definition of student-centeredapproach is not clearly shared among teachers.
Also effectiveness of ICT tools on thestudent-centered approach has not been assessed.
On this point of view, this research focus on two
objectives as follow, 1) to identify the key-factorsof student-centered approach on Mongolian
context and 2) to illustrate how lessons using ICT
tools contribute to promoting a student-centeredapproach in primary schools in Mongolia. The
research was mainly conducted in Bayankhongor
aimag, with additional information from andSongino Khair Khan district of Ulaanbaatar.
3.

Research Methodology
The research consists of three components.
First is clarification of the definition of
student-centered approach in Mongolian context.
The study was conducted to identify theimportant factors of student-centered approach
using both questionnaire and interview analysis.
The professional staff of JICA identified historicalinformation on history and definition of“student-centeredapproach”.
Then
four
professors of Mongolian State University of
Education confirmed definition, practices anddifficulties of student-centered approach. Further,potential
key-factorsofstudent-centeredapproach were extracted based on the results ofthese interviews and survey results. In addition,questionnaire was conducted to clarify thedefinition of student-centered approach among
schools. In total 145 out of 204 questionnaire wereretuned, yielding 71% response rate.
Second, in the analysis on the current state of useof ICT tools during the implementation of
student-centered teaching. Various ICT tools(Computer, LCD Projector, Digital Camera, Video
Player, Audio Player, TV, Radio, Power Point,
Word, Excel, Scratch and Movie Maker) were
evaluated for their usage, effectiveness, andissues through the questionnaire and focus group
discussion. A total of 145 questionnaires warecollected (69 from Bayankhongor, 76 fromScongino Khairkhan district), yielding 81%
response rate. Furthermore, the responses of
Bayankhongor came from 25 out of 27 schools.
Therefore
resultsofquestionnairein
Bayankhongor could represent of trend of
Bayankhongor aimag.
In addition, 28 people in Bayankhongor and29 people in Songino Khairkhan district
participated to focus group discussion to observe
the effectiveness of ICT tools, and discussed
impression
andissuesineducational
environment.
Third, in the analysis of the effectivenessof Scratch teaching materials through lesson

Fig. 1 Overview of research(Source: created by author, 2013)

4.
Findings
4.1 Student-centered approach in Mongolian
primary education
Surveyandinterview
resultswithMongolian teachers corresponded to theprevailingdefinitionof
student-centeredapproach. It emphasized the importance of
placing students as a core part of classroom
teaching, through developing curriculum andactivities suited for the group of students.
1)

Student-centered approach in Mongoliaemphasizesonstudents’creativity,
self-learning abilities, problem-solving skills
through interesting and innovative classroom
activities
Teachers recognize the following three
aspects the most important: 1) developing
students’ potential abilities; 2) activities
centering students in classrooms; and 3) creating
supportive
environment
to
implement

26

equipped with enough skills to use variety of
programs. Further, teachers use computers for
self-learning at schools and willing to learn newtechnology.

student-centered learning. Among 12 factors topromote student-centered approach identified by
Mongolian teachers, the top three factors are“developing students creativity”, “developing
self-learning’,and“developing
students’problem-solving skills”. While these top there
factors are ranking the highest, it does not meanthese or any of the other factors are all required
to implement the student-centered approach.
Definition of Student-centered approach in
Mongolia is in line with definition identified by
the existing literatures, but it particularly focus
on abilities of the students.

2)

Teachers consider that use of ICT tools
support student-centered approach
Survey result indicated that multiple
equipment and software are considered effective
and applicable supporting tools to conduct
student-centered approach.
Concrete reasons
include: 1) to attract students interest; 2) topromote students self-learning; 3) to save time (byavoiding writing information on blackboard); 4)
to promote new way of information gathering; and5)
to explain difficult concept easy tounderstand (by using visual materials).

2)

Teachers are expected to understand theneeds for students by carefully reflecting, age,learning progress as well as level ofunderstanding
According to survey result, to promotestudent-centered teaching, it is vital thatteachers analyze the interest, problem-solving
skills of the students, together with learning
progress. Building onto the accumulated
knowledge and understanding of the students isbasis of effective student-centered approach.

3)

Teaching materials produced with software ofvisual effect was found particularly effective
among teachers
Particularly, Power Point, Movie Maker,
and Scratch, which enable to create visualmaterials were found effective to attract students
interest, and thus, improved concentration duringclassroom teaching.
According to interviews
with teachers, photos, illustration and sounds
make students to motivate to learn andparticipate in classroom activities. Scratch was agood example to keep students’ concentration,and thus, was used for “motivating students tolearn new subject”, and “getting attention among
students
when
importantconcept
wereintroduced.”3)

By introducing student-centered approach,teachers are expected to be equipped withmore knowledge and skills
To promote students’ participation inclassroom activities, as well as to increase
motivation of the students, teachers need to learn
various teaching methods and teaching skills.
Teachers found the difficulty to shift fromteacher-centered teaching to student-centeredapproach. Further, introducing more discussion,group activities, and students’ presentation istime consuming and it is difficult to integratethese initiatives within the limited teaching
hours. Lack of equipment and facilities also
limit participatory activities using ICT tools.

4)

School leaders and community members
expect teachers to use ICT tools into teaching
Reflecting high motivation of teachers to use
ICT into teaching, schools provide technicalsupport and ICT training for teachers. Survey
result indicates that parents and othercommunity members expect teachers to use
computers and other ICT tools at schools.

4.2 Use of ICT tools and its effectiveness to promotestudent-centered approach
Teachers perceive the effectiveness ofusing ICT tools to promote student-centeredapproach. Multiple equipment and software arefound effective and applicable in primary schools
in Mongolia.

5)Teachers believe that use of ICT tools todevelop teaching materials improve teachers’
creativity
The definition of student-centered approach
generally focuses on students. However, thesurvey result illustrated that teachers feel that
their skills and creativity have improved throughexperiences of using different ICT tools anddeveloping various teaching materials. As New
Education Standards require local governmentand schools to integrate local information andavailable materials, teachers try to be creative indeveloping own materials. This condition, alongwith introduction of new tools promoted teachers

1)

Teachers are motivated to use ICT tools andfrequently use different tools to produce
teaching materials
Survey result indicated that 84% of the
respondents use computers more than once per
week to produce teaching materials. Teachers
use Power Point, Words, Excel and Scratch
programs for material production, and they are27

to be "creative".

3)

Further teacher training is necessary for theteachers to effectively utilize Scratch forteaching materials
Quality use of teaching materials with
Scratch promotes students to be engaged into
participatory activities, and thus promotestudent-centered learning. For many teachers,
producing teaching materials with Scratch was
new experiences, and thus, a series of training
were found necessary, not only to improve skills
to operate Scratch but also to incorporate it into
curriculum.

6)

Lack of equipment is still an issue to further
promote use of ICT
Lack of equipment and facilities also limit
participatory
activities
using
ICT
tools.
Currently, each school is equipped with at least
two printers and one LCD projector [9], but this isconsidered not sufficient for the teachers to
conduct classroom teaching using ICT.
The
condition is even worse where classes are
conducted with 2 or 3 shift per day. Addition, atthe one of the visited school, teacher couldn’t use
Scratch effectively due to the LCD projector’smechanical problem. The maintenance of the ICT
equipment is also expected to fully utilize the ICT
tools in education environment.

5.

Concluding remarks
This study identified specific definition of"students-centered teaching" in Mongolian
context. Using such definition, the survey wasdeveloped and data was collected to illustrate howteachers utilize ICT tools effectively and in
applicable manner in classroom teaching.
The study found, teachers have positive
perception on the use of ICT tools into teaching
and various ICT tools are effective to enhance
student-centered approach. ICT use in teachingin current Mongolian primary schools has
potential for further development.
This study illustrated the current conditionof Bayankhongor case in Mongolia. Thesefindings cannot explain the educational
environment in entire Mongolia, but can beshared as useful information for educational
sector for further development.

4.3 Effective use of Scratch to promotestudent-centered approach and issues
According to the results of questionnaire,
focus group discussion and lesson review, Scratch
is useful tool to enhance student-centeredapproach.
1)

Scratch is useful for its visual effect and can beparticularly used for introduction/motivation ofclass lessons
Lesson reviews in Bayankhongor revealed
that teachers were creating teaching materials
using Scratch with visual aids. Particularly,
teachers used animation combining photos,
illustrations and sounds, and such teachingmaterials was useful to get students’ interest andto concentration. Teachers also found it useful topromote students’’ understanding of topics withvisual effects.
In lesson reviews, it wasnoticeable that teachers used Scratch for
introduction ( for attention getter) and identifying
the problems.

References
[1]
[2]

[3]
[4]

2)

Teaching materials produced by teachers
using local materials would further interest
students
Students enjoy teaching materials locallyavailable. An advantage of Scratch is thatteachers can incorporate own photos, illustrations
and sounds to create unique teaching materials.
During the lesson reviews, it was observed thatstudents showed strong interest when teachers
use familiar photos and information that students
find close to, and thus, was promoting
student-centered learning.

[5]

[6]

[7]

[8]

28

Kawaguchi., (2012): Overview of Introducing “Student
Centered Approach” – A case study of MalawiYucel, G.,(2009), The effect of Student Centeredinstructional
approaches
onstudent
success,
Department of Educational Sciences, Gazi University
JICA.,(2005): モンゴル国子どもの発達を支援する指導法
改善プロジェクト	
  実施協議報告書”, 平成 18 年 10 月
Scratch.,(2013): For Educators (about Scratch) ,[online],(available) http://scratch.mit.edu/educators/ , (accessedon July, 13 .2013)
Yamguchi Laboratory, (2012): モンゴルにおける持続可
能 な 教 員 研 修 の た め の ICT 教 材 開 発 ,[online]
http://www.yamaguchi.gsic.titech.ac.jp/research/monpri
introduce/ (Accessed on July 10th)
Shotaro, YANO, Seregelen Sukhbaatar, Shinobu,
YAMAGUCHI.,(2012), Development of Teaching
Material for Primary Schools in Mongolia : Lessons
from Teachers’ Feedback, 56th Annual Conference,
Comparative and International Education Society
Puerto Rico, April, 2012
Ministry of Education Culture and Science, (2011):
Statistical Abstract Education, Culture, Science andTechnology, p.16
ADB,(2012): 教育セクターにおける ICT 現状評価広告書,
2012

DATABASE OF METEOROLOGICAL URBAN GEOMETRIC PARAMETERS OF JAPANAND ITS EXPANSION TO GLOBAL SCALE
Student Number: 11M18143

Name: Takuya MAKABE

Supervisor: Manabu KANDA

気象解析のための全日本都市幾何データベースの構築と世界への拡張可能性
真壁 拓也
本論文では，日本全国の建物データを用いた気象シミュレーションのための都市幾何パラメータのデータベースを構築し，詳細な 3 次元都市幾何データベースを用いてその精度を検証した．また，詳細な建物データが未整備である都市へ同種のデータベースを拡張するための手法として，ほぼ全球的に整備され，無償で公開される衛星観測データのみを用いた都市幾何パラメータを推定する手法を提案
し，その精度検証を行った．

1

geometric parameters, including average buildingheight 𝐻𝑎𝑣𝑒 , maximum building height 𝐻𝑚𝑎𝑥 ,standard deviation of building height 𝜎𝐻 , plane areaindex 𝜆𝑝 (ratio of area occupied by buildings to thetotal area), frontal area index 𝜆𝑓 (ratio of area ofbuilding walls that face a specific direction to the total
area. In this paper, average value of 𝜆𝑓 for 8 different
direction is used.), roughness length for momentum 𝑧0,
displacement height 𝑑, and sky-view factor 𝑆𝑉𝐹 , arecalculated for each 1 km2 mesh in Japan.
Displacement height 𝑑 and roughness length formomentum z0 were calculated based on equations
proposed by Kanda et al. [4] And sky-view factor is
calculated based on equations proposed by Kanda et al.
[5]. The distribution of displacement height 𝑑 is show
in Figure 1. Higher values can be observed aroundmajor cities such as Tokyo, Osaka, and Nagoya.

Introduction

Numerous numerical simulations on urban
meteorology have been conducted, and the land surface
models employed have shown a great progress [1].
Thus, it is of importance that creating detailed
geometry database of cities to conduct accurate
numerical weather predictions. For example, Chen et al.
[2] reports that incorporation of UCM (Urban Canopy
Model) [3] to a meso-scale meteorological model WRF
can improve reproducibility of the simulation.
However, preparation of such database requires a great
deal of effort. With a very small number of exceptions,detailed urban geometric database is not available inmost of the cities in the world. In this study, we propose
a method to estimate urban topography using satellite
observational data, which is now open to public
inspection. Along with that, database of urban
geometric parameters in Japan are created using adetailed building data.

2

Database of Urban GeometricParameters in Japan

2.1. Data used
The dataset of building heights is taken from ageographic information system (GIS), which isdeveloped and distributed by ESRI Japan, Inc. The
dataset contains the category, shape, location, andnumber of floors of buildings in Japan. Note that onestory buildings are not included in the dataset. On thebasis of an assumption that height per floor is 3m,building heights are estimated by multiplying numberof floors by 3m. To validate the accuracy of theseparameters, a detailed building database, MAPCUBE,
was employed. These data contain building height datawith spatial resolution of 1 m. In this paper, the data inTokyo Metropolis are used for the validation of theparameters calculated.

Fig. 1: Distribution of displacement height 𝑑 acrossJapan (the color range is not consistent with the actual
range)

2.3. Comparison to detailed building data

2.2. Calculation of Geometric Parameters
Using datasets mentioned in previous section, urban

29

[6]. The horizontal resolution of this DEM is 1 arcsecond (approximately 30m), and its root-mean-squareerror (RMSE) in elevation is between ±7 m in US and± 15 m in other regions. [7] The other is called
GMTED2010 (Global Multi-scale Terrain Elevation
Data 2010), which is developed and distributed by the
U.S. Geological Survey (USGS) and National
Geospatial-Intelligence Agency (NGA). This DEM
contains 3 different horizontal resolutions: 7.5 arcseconds, 15 arc-seconds, and 30 arc-seconds [8]. In thispaper, DEM with the resolution of 7.5 seconds is
employed. At 7.5 arc-seconds, the RMSE range inelevation is between 26 and 30 m. In addition to terrain
elevation, this DEM also has statistical based products,
such as average elevation, maximum elevation,
minimum elevation, and standard deviation ofelevation calculated based on values of 3x3 pixels.
Before analysis, horizontal resolutions of 2 DEMs areadjusted to 1 arc-second by bilinear interpolation.

The calculated geometric parameters are validated bycomparing to that based on detailed building heightdatabase MAPCUBE. For any parameters, the values
from 2 different data sources show very highcorrelation. However, it is revealed that parameters
calculated, except plane area index, tend to be smaller
than that based on MAPCUBE (not shown). This might
be due to the assumption that height for one floor isfixed to 3m for all kinds of buildings. For theconsistency between parameters based on the 2different data sources, height for one floor is changed
according to building categories: 3m for low-risedwelling houses, and 4m for the other buildings. The
modified parameter, 𝐻𝑎𝑣𝑒 , and that from MAPCUBE
is shown in Figure 2.

3.1.2. Methodology
To estimate urban geometry, 3 different methods are
examined. Procedures of each method are explained
below.
a) CIM method:First, divide the target DEM, ASTER GDEM2 into
small areas. The shape of the small area is square, and3 different sizes are examined: 3x3, 7x7, 11x11 pixels.
Then, check if the value of the central pixel is theminimum in the area. If the value is the minimum, keep
the value as the representative value of the area.
Otherwise, retain null value as the representative valueof the area. After this manipulation, pixels with values
are concatenated by linear interpolation, and theoutcome is regarded as terrain elevation without theinfection of artificial objects. Finally, distribution ofbuilding height is estimated by subtracting the outcome
from the target DEM before manipulation.
b) JM method:
Almost the same as the CIM method, but the central
pixel of a small area is replaced by the minimum valueof the area.
c) AmG method:
This method exploits one of the statistical based
products of GMTED2010, that is, minimum value ofeach 3 x 3 pixels (GMTEDmin). Building height
distribution is estimated by subtracting GMTEDminfrom ASTER GDEM2. In this procedure, only the areasthat are occupied by buildings are considered according
to MAPCUBE.

Fig. 2: Relation between average building height 𝐻𝑎𝑣𝑒based on ESRI and MAPCUBE (for Tokyo Metropolis)

3

Estimation of Urban GeometricParameters using Satellite Data

Constructing databases of urban geometric parameters
requires accurate data of building shapes, which is very
costly and are not available in most cities. Therefore,
alternative method to substitute these data is ofparticular importance. In this chapter, urban geometryis estimated based on satellite digital elevation models(DEM), which are available almost anywhere on earth
and open to public. Besides, building footprints are
estimated by analyzing satellite visible imagery.

3.1. Estimation of Urban GeometricParameters using Satellite DEM
3.1.1. Data Source
Two DEMs are used to estimate building height
distribution. One is called ASTER GDEM2, which is
generated from satellite imagery captured by The
Advanced Spaceborne Thermal Emission and
Reflection Radiometer (ASTER) instrument on-board
the National Aeronautics and Space Administration(NASA)’s Terra spacecraft is employed. This DEM is
prepared and distributed in cooperation with NASA andthe Ministry of Economy, Trade and Industry of Japan

3.1.3. Result
Figure 3 shows building height distribution estimatedby AmG method. It is noteworthy that the higher
buildings in the congested areas are captured. Figure 4
shows relation between estimated average building30

heights based on the 3 different methods and that basedon MAPCUBE. For the CIM and JM methods,
regression line is proposed using estimated values
larger than 5m. For the AmG method, the estimatedvalues are seemed to be distributed on an exponential
curve, so the regression curve is given in the
exponential form. Among all the methods proposed, theAmG method shows the highest correlation between
the values based on MAPCUBE.

vegetation, and bare soil are extracted manually fromimages, and create training datasets with them. Then,
multi-class supervised classification is conducted using
the training datasets. Features in an image are classified
to 3 different classes. Figure 6 shows one of the results.
Here, 4 different training datasets are examined. Afterclassification, road faces are excluded from the result
using road face data contained in the ESRI data. The
area of each class is calculated and plane area index isestimated.

Fig. 5: High-resolution satellite image used. Features
for training are colored. (Retrieved from Google Maps)

Fig. 3: Distribution of estimated building heights inTokyo Metropolis. (AmG method)

3.2. Estimation of Building Footprints using
Satellite Visible Imagery
3.2.1. Data Source
Satellite visible imagery is retrieved from Google Maps
(https://maps.google.com). One image covers an area
whose width is 45 arc-seconds in longitude and is 30
arc-seconds in latitude. This area corresponds
approximately to 1km2 in Japan. An image consists of
2340x1940 pixels with
0.5m/pixel in spatial
resolution. Each pixel contains 3 bands: Red, Green,and Blue. (see Figure 5.)

Fig. 6: Result of supervised classification. (Purple:
building rooftops, Green: vegetation, Orange: barelands. Road faces are whitened using ESRI data)

3.2.3. Result

3.2.2. Methodology

From the results of supervised classification, plane areaindex is estimated by the equation 6.
𝜆𝑏𝑙𝑑𝑔 = 𝐴𝑏𝑙𝑑𝑔 /𝐴(6)

Supervised classification is conducted using a GIS
software ArcGIS. The procedure conducted is
described as follows: First, building rooftops,(a)Where 𝐴𝑏𝑙𝑑𝑔 is the area classified as building rooftops,
while A is the total area that an image covers.
Additionally, area of vegetation and bare land is(b)(c)

Fig. 4: Relationship between estimated average building heights and that based on MAPCUBE: (a) CIM method, (b)JM method, (c) AmG method.
31

estimated by the equation 7.
𝜆𝑉+𝐵 = (𝐴𝑣𝑒𝑔 + 𝐴𝑏𝑎𝑟𝑒 )/𝐴

constructed using a GIS with building data. Also, themethods for expanding the database to cities where
detailed building dataset is not available are proposed.
The results are summarized as follows:(a) A database of urban geometric parameters isconstructed using a detailed building data. The
parameters are compared to that calculated basedon a detailed 3D building data, and showed highcorrelation.
(b) UsingDEMs
generatedfromsatellite
observational data, methods to estimate urban
geometry are proposed. And regression curves areproposed as well.
(c) By analyzing satellite visible imagery, building
footprints in urban area is estimated.

(7)

Where 𝐴𝑣𝑒𝑔 is the area classified as vegetation,
whereas 𝐴𝑏𝑎𝑟𝑒 is that for bare lands. Since
appearances of vegetation and bare land are expected
to have more homogeneous colors and textures thanbuilding rooftops, considering 𝜆𝑉+𝐵 has a potential toestimate the real plane area index more accurately than
𝜆𝑏𝑙𝑑𝑔 . 1 − 𝜆𝑉+𝐵 is compared to plane area index
based on MAPCUBE, because it can be regarded as theupper limit of the real plane area index 𝜆𝑝 of the area.
Besides, it is observed that the classification results arevery sensitive to the training datasets and differ
depending on the training dataset given. Therefore, theaverage of results from 4 different training datasets is
considered. As expected, estimation using λ𝑉+𝐵
showed higher correlation than that using λbldg .
Results for λ𝑏𝑙𝑑𝑔 and 1 − 𝜆𝑉+𝐵 are shown in Figure
7 and 8, respectively.

Reference[1] Kanda, M.: Progress in Urban Meteorology: A
Review, J. the Meteor. Soc. Of Japan, 85B, pp.363383, 2007.
[2] Chen, F., Kusaka, H. et al.: The Integrated
WRF/Urban Modeling System: Development,
Evaluation,andApplications
to
Urban
Environmental Problems, Int. J. Climatol., Vol. 31,
pp.273-288, 2011.
[3] Kusaka, H., and Kimura, F.: Coupling a Single-layer
Urban Canopy Model with a Simple Atmospheric
Model: Impact on Urban Heat Islands Simulation for
an Idealized case, J. Meteor. Soc. Japan, Vol. 82,
pp.67-80, 2004.
[4] Kanda, M. et al.: A New Aerodynamic
Parameterization for Real Urban Surfaces, Bound.
Layer Meteor., Vol. 148, pp.357-377, 2013.
[5] Kanda, M., Kawai, T. and Nakagawa, K.: A Simple
Theoretical Radiation Scheme for Regular Building
Arrays, Bound. Layer Meteor., Vol. 114, pp.71-90,
2005.
[6] Abrams, M., “The Advanced Spaceborne Thermal
Emission and Reflection Radiometer (ASTER): data
products for the high spatial resolution imager on
NASA’s Terra platform”, International Journal of
Remote Sensing, Vol. 21, Issue 5, pp. 847-859, 2000.
[7] Hirano, A., Welch, R. Lang, H., “Mapping from
ASTER stereo image data: DEM validation andaccuracy assessment”, ISPRS Journal of
Photogrammetry and Remote Sensing, Vol. 57, Issue
5-6, pp. 356-370, 2003.
[8] U.S. Department of the Interior and U.S. Geological
Survey: Global Multi-resolution Terrain Elevation
Data 2010 Open-file report 2011-1073, 2011

Fig. 7: Relationship between estimated plane areaindex 𝜆𝑏𝑙𝑑𝑔 and plane area index λp based on
MAPCUBE.

Fig. 8: Relationship between 1 − 𝜆𝑉+𝐵 and plane areaindex λp based on MAPCUBE.

4Conclusion

A database of urban geometric parameters in Japan is32

LES ANALYSIS OF THE EFFECT OF VEGETATION ON FLOW FIELD IN
URBAN AREA
Student Number: 12M18057 Name: Hiroyuki KATO

Supervisor: Manabu KANDA

街区風に及ぼす植生の影響に関する LES 解析
加藤寛之
本論文では，実都市の建物形状及び，植生配置を考慮した数値計算を行い，植生が都市の流れ場及び大気環境に与える影響について検討した．また，都市環境に効果的な植生配置条件の提案も行った．植生を考慮した場合，植生領域において突風率が減少することが定量的に示された．運動量輸送は建物の影響を受けやすく単純に植生割合に依存しないのに対し，スカラー輸送は空間に占める植生割合が直接的に影響することが明らかになった．

surface geometry and vegetation distribution were

1. Introduction

hardly done.

Vegetation in urban area affect wind field,

In this research, in order to clarify the effect oftemperature, and scalar concentration field which arevegetation on flow-field in real urban areas, buildings

generated by complex arrayed buildings. Theseand vegetation were incorporated as fluid resistanceschanges lead to various type of environmental

into large-eddy simulation model. In the consideration

problems like heat island phenomena, air pollution inpart, gust is estimated in terms of the practicalurban area. Therefore, for urban planning in terms ofperspective, and concentration field analysis was done

the practical perspective such as disaster prevention

by using passive scalar. To discuss the impact ofand environmental improvement, it is important tovegetation quantitatively, bulk transfer coefficients forinvestigate the impact of buildings and vegetation on

momentum and scalar were estimated, which relate tourban atmospheric environment quantitatively and set

the process of turbulence transfer. Finally, thean appropriate standard for vegetation arrangement.

appropriate vegetation array were proposed.

2. Method

Recently, real surface geometry data wasdeveloped and used as bottom boundary condition for
numerical

experiments

insteadof

2.1 Basic equationsahorizontally-homogeneous building array. As a result,
Parallelized

the flow-field was reproduced with a high degree oflarge-eddy

simulation

model

accuracy [1]. Also, the modeling of vegetation effect(PALM) was used. The equations used in this model

are studied so far to consider its effect into calculation

are Navier-Stokes equations (eq.1), the continuity

model

equation (eq.2), and the conservation equation for a[2].

However,

in

these

researches,

passive scalar (eq.3).

horizontally-homogeneous plant canopy like forests
was assumed, and there are few cases which focusedon trees on streets and around buildings. Furthermore,large-eddy simulations which consider both real33

3. Simulation settings

̅̅̅
𝜕𝑢̅𝑗
𝜕𝑢̅𝑖
1 𝜕𝑝̅
𝜃∗
+ 𝑢̅𝑗
=−
+ 𝜀𝑖𝑗3 𝑓𝑢̅𝑗 + 𝑔𝛿𝑖3
𝜕𝑡𝜕𝑥𝑗
𝜌0 𝜕𝑥𝑖
𝜃
−

𝜕
(𝑢
̅̅̅̅̅
𝑢 − 𝑢̅𝑖 𝑢̅𝑗 ) − 𝑐𝑑 𝑎𝑈𝑢̅𝑖
𝜕𝑥𝑗 𝑖 𝑗

3.1 Calculation conditions(1)

Numerical settings of the simulations are shownin Table1. Since the simulations assume thermallyneutral stratification, heat flux from the ground and

𝜕𝑢̅𝑖
=0
𝜕𝑥𝑖

(2)

building surfaces are zero. Cyclic boundary conditions
were used for both horizontal boundaries, and volume

𝜕𝜒̅
𝜕𝜒̅
𝜕
+ 𝑢̅𝑗
=−
(𝜒𝑢
̅̅̅̅̅𝑗 − 𝜒̅ 𝑢̅𝑗 )
𝜕𝑡
𝜕𝑥𝑗
𝜕𝑥𝑗
− 𝑐𝜒 𝑎𝑈(𝜒̅ − 𝜒𝑐 )flow was conserved at each time step. 3-dimensional
urban surface geometry is reproduced by using(3)

MAPCUBE which includes two-dimensional buildingheight information obtained from aerial survey.

Each variable represents as follows; 𝑢𝑖 is the velocity

Passive scalar were supplied from the ground surface

in the 𝑥𝑖 -direction, 𝑝 is pressure, 𝜌0 is density, 𝜒constantly.

is scalar concentration, the upper bars denote filteredvariables. The vegetation effect is introduced toTable1 Calculation conditions

momentum equations in the final term as external

Domain size

1000m×1000m×600m

Grid size

2m×2m×2m

Initial wind velocity

6.0 m s-1

Boundary condition (x,y)

Cyclicscalar exchange between leaves and atmosphere are

Boundary condition (Top)Slipneglected.

Boundary condition (Bottom)

No-slip

Calculation time

18000 sec

force, where 𝑐𝑑 is the leaf drag coefficient, 𝑎 is theleaf area density, 𝑈 is the instantaneous local wind1̅ 2 )2. In
speed which is defined as 𝑈 = (𝑢̅2 + 𝑣̅ 2 + 𝑤
this research, Coriolis force, Buoyancy force, and

2.2 SGS model

3.2 Vegetation data
SGS flux of momentum and scalar are presented
as follows,

Spatial distribution of vegetated area was

(𝑢
̅̅̅̅̅
̅𝑖 𝑢̅𝑗 ) = −𝐾𝑚 (𝑖 𝑢𝑗 − 𝑢(𝜒𝑢̅̅̅̅̅𝑗 − 𝜒̅ 𝑢̅𝑗 ) = −𝐾𝜒𝜕𝑢̅𝑖 𝜕𝑢̅𝑗2+) + 𝛿𝑖𝑗 𝑒̅𝜕𝑥𝑗 𝜕𝑥𝑖
3

𝜕𝜒̅
,
𝜕𝑥𝑗

obtained from the satellite image of Google by using(4)

Feature Analyst for Arc GIS which can derive
vegetation area precisely. It is assumed that the height(5)of tree is set a constant value of 15 m, and leaves exist
above 3m where fluid feels a resistance. Drag

where 𝑒̅ is the SGS kinetic energy. 𝐾𝑚 and 𝐾𝜒 arecoefficient and leaf area index are 0.2, 0.3 m2m-3

the SGS eddy diffusivities for momentum and scalar

respectively.

respectively, and modeled by using Deardorff’s SGS

3.3 Calculation areamodel as follows,
𝐾𝑚 = 𝐶𝑀 Λ√𝑒̅Λ 𝜕𝜒̅𝐾𝜒 = − (1 + 2 )
,
∆ 𝜕𝑥𝑗

(6)

Four different areas were chosen in Tokyo.
Shinjuku is a skyscraper, Shibuya is a commercial(7)area, Denenchofu is a residential area, and RoppongiΛ is the SGS length scale and given by :is also a commercial area and has a high-rise building.
The example of distribution of vegetation and buildingΛ = min(0.7 ∙ z, ∆) ,(8)height are shown in Fig1, and geometric parameters ofeach areas are shown in Table2. Three different

where ∆ is the grid scale, ∆= (∆𝑥∆𝑦∆𝑧)1⁄3.
34

simulations were conducted for each area by changing

the last 30 minutes of calculation, and 𝑢∗ is thethe amount of vegetation as follow; (a) no vegetation

friction velocity. Left of Fig2 is the Probability density

exist (Noveg), (b) real vegetation distribution werefunction of each vegetation case in Shinjuku. Withconsidered (Real), (c) all ground is covered byintroduction of vegetation, occurrence of strong gustvegetation (Fill).

decreases and the gust factor becomes less than 4 in
all areas of case ‘Fill’. Right of Fig2 is the contour
map near surface, which shows the difference between
the gust factor of ‘Real’ and that of ‘Noveg’. An
introduction of vegetation decreased gust factor inmost area at close to the ground, however, thoseincreased in some areas; such as main street with notrees and open area behind buildings.

Fig1 Left: vegetation distribution
Right: building height map
Table2 Surface geometric parameters
Shinjuku

ShibuyaDenenchofu

Roppongi

𝜆𝑝

0.30

0.38

0.34

0.34

𝜆𝑓

0.59

0.62

0.25

0.43

𝐻𝑎𝑣𝑒

52.64

28.31

7.72

23.53

𝐻𝑚𝑎𝑥

244

188

42

256

Fig2

𝜎𝐻

60.28

21.10

4.03

34.47

Right: Gust factor difference between ‘Real’ - ‘Noveg’

Left: Probability density function of gust factor

4.3 Scalar concentration field

4. Result & Discussion

Fig3 shows the scalar concentration map in

4.1 Turbulent statistics

Shinjuku. Scalar concentration increased at the area
The effect of vegetation on the streamwise

where the vegetation covered. This is because

velocity and Reynolds stress were examined. It isvegetation suppressed the turbulent mixing between in

found that horizontally-averaged streamwise velocity

and above the vegetation canopy and scalar, which isdecreases near the ground due to vegetation for all

released from the ground, is kept near the ground.

areas. In Denenchofu, mean streamwise velocity

Therefore, horizontally-averaged scalar concentration

becomes lower at entire level of the numerical domain.

is correlated to vegetation ratio (Fig4).

However, the decline of mean streamwise velocity inthe other areas is enclosed at close to the ground. The
magnitude of peak Reynolds stress increases with an
introduction of vegetation in most cases sincevegetation acts as larger aerodynamic drag on fluid.
4.2 Gust analysis
Gust is the strong wind which blows locally andinstantaneously. It is quantified as 𝑈𝑚𝑎𝑥 ⁄𝑢∗ in thisresearch, where 𝑈𝑚𝑎𝑥 is the maximum wind speed of35

4.4 Bulk transfer coefficientFig6 Bulk transfer coefficients for scalar versus
Fig5 shows the effect of vegetation on the bulk

vegetation ratio

transfer coefficients for momentum. Vertical axis is
the

value

derivedby

predicted(○:Shinjuku □:Roppongi △:Shibuya ◇:Denen)

aerodynamic

parameters, and Horizontal axis is that derived by

5. Conclusion

results of LES. There are some biases, however, it canbe said that the prediction equation is sufficient to

The effect of vegetation on flow-field in realestimate the urban aerodynamic parameters. Generally,urban areas is examined in terms of gust, scalar

vegetation has small impact on these coefficients forconcentration, and momentum and scalar transports.

momentum. In Shibuya and Shinjuku, the coefficientsare smallest in ‘Real’. It means that transportation of

The occurrence of gust and the magnitude of gustmomentum doesn’t depend on vegetation ratio directly.

factor can be reduced and scalar concentration

Fig6 shows the relation between the bulk transfer

increased with the introduction of vegetation. Scalarcoefficients for scalar and vegetation ratio. Withtransport depends on the vegetation ratio, while

increasing in vegetation ratio, coefficients for scalar

momentum transport depends on the surface geometry

decrease and the variation become smaller. Therefore,

predominantly.

transportation of scalar depends on the vegetation

References

ratio directly.

[1]

Kanda, M., Inagaki, A., Miyamoto, T, Gryschka, M,
Raasch, S. (2013) : A New Aerodynamic Parametrization
for Real Urban Surfaces,

Boundary-Layer Meteorology,

Vol48，pp. 357-377.

[2] Watanabe, T. (2004) : Large-eddy simulation of coherent
turbulence structures associated with scalar ramps overplant canopies, Boundary-Layer Meteorology,

Vol112,

pp.307-341.
[3]

Kanda, M., Moriizumi, T. (2009) : Momentum and heattransfer over urban-likes surfaces ,Meteorology,[4]

Vol131,

Boundary-Layer

pp385-401.

Letzel, MO., Krane, M., Raasch, S. (2008) : High
resolution urban large-eddy simulation studies from street

Fig5 Prediction versus LES resultscanyon to neighborhood scale, Atmospheric
Environment,

36

Vol42, pp.8770-8784.

Research on Stochastic Typhoon Model in Low Latitudes of Northwest Pacific Ocean
Student Number: 12M18063

Name: Sarii KAWAI

Supervisor: Hiroshi TAKAGI

北西太平洋低緯度海域を対象とした確率的台風モデルに関する基礎的研究
河合 彩里伊将来的な台風発生の予期・予防は防災上重要な課題である．日本を含む北西太平洋中緯度海域に着目した確率的台
風モデルはこれまでにも幾つか提案されているが，フィリピンやベトナムなど低緯度海域に焦点を当てたモデルは提案されていない．本研究では 1951 年から 2012 年の台風経路データに基づき，北西太平洋における台風の発生特性や強度特性を分析し，低緯度海域における台風発生位置を確率的に予測するモンテカルロ法に基づく確率的台風発生モデルを作成した．過去の発生頻度および空間的な広がりと比較した結果，概ね妥当な結果を与えることが分かった．

1. Introduction

2.1

In the last few years, strong tropical cyclones have
unexpectedly occurred in lower-latitudes where used to
be almost free from tropical cyclones, such as Typhoon
Haiyan in 2013, Typhoon Bopha in 2012 and Severe
Tropical Storm Washi in 2011. These tropical storms
have caused a lot of casualties and damaged properties
due to land slide, flooding and storm surge. The damage
due to tropical cyclones can be exacerbated particularly
in lower-latitudes due to lack of people’s awareness fortropical cyclones. Thus, assessing occurrence of theselower-latitude tropical cyclones is essentially important
for achieving disaster risk reduction.
Many studies on the development of stochastic
typhoon model for the mid-latitude areas of northwest
Pacific Ocean have been carried out to date, particularly
focusing on the typhoons making landfall in Japan.
However the studies focusing on lower-latitudes ofnorthwest Pacific Ocean encompassing such as thePhilippines and Vietnam have not been established so far
yet. Thus, a stochastic typhoon model focusing onlower-latitudes needs to be developed to predict the
future possibilities of lower-latitude tropical cyclones.
Typhoon track data (called Best Track Data) between
1951 and 2012 provided by JMA is used in the present
research, and the total number of tropical cyclones in thebest track data is 1,619. Though it covers more than60years, it may be insufficient to predict the future
occurrence of unexpected severe tropical cyclones inlower-latitudes as the data does not necessarily containhistorical large typhoons which may only occur once
every 100 years or further smaller chances. In case thedata available is limited, a stochastic model is often
utilized in predicting future possibility of severe disasters.
Thus the authors try to develop the stochastic model
which is able to generate future possible devastating
tropical cyclones.

The Best Track Data between 1951 and 2012 innorthwest Pacific Ocean were examined to understandgeneral trends of tropical cyclones in terms of tropical
cyclone genesis, annual frequency and travel direction.

Analysis of tropical cyclone data(i) Tropical cyclone genesis
The map showing the locations of tropical cyclone
genesis of a total of 1,619 tropical cyclones between
1951 and 2012 is shown in Fig.1. The point of tropical
cyclone genesis indicates the location at which tropicaldepression became a tropical storm of which windspeeds exceed 17 m/s.
As Fig.1 shows, some of tropical cyclones passed
through the lower-latitudes, contrary to the fact that the
Coriolis force can be too small to generate the whirlpoolof the tropical cyclone. This kind of unexpected tropical
cyclone path can occur partly because 1) a tropicaldepression which is generated at middle latitude goessouthward and developed into tropical storm at lower
latitude or 2) sea surface temperature has been rising by
the global warming. However, the behavior of tropical
cyclone is essentially complex phenomenon with many
uncertainties which are predominated by stochastic
natures. Regarding climate change effects, it isconfirmed that sea surface temperature rose by 0.45℃
for this 100 years. However the relationship between the
global warming and the annual number of tropical
cyclones is not clear scientifically.
(ii) Tropical cyclone path
The traveling paths of the total of 1,619 tropical
cyclones are shown in Fig.1.
According to the Fig.1, there appear to be two
distinctive patterns, namely (1) tropical cyclones
traveling westward nearly in parallel to the equator, and(2) tropical cyclones traveling westward and turn theircourses to northeastward with the influence of westerlies
blowing around N30°. To develop a stochastic typhoon
model for predicting the future occurrence oflower-latitude tropical cyclone, cyclones which primarily
travel westward and affect damage to lower latitudes
need to be distinguished from others.

2. Analysis and extraction of tropical
cyclone data
To establish the stochastic typhoon model which is able
to deal with typhoons traveling in lower latitudes,
historical tropical cyclones occurred in such areas firstneeds to be separated from the entire paths in Northwest
Pacific Ocean.

(iii) Traveling angle
Distribution of angles between the locations where
tropical cyclones are generated and disappeared is shownin Fig.2. Angle 0°shows tropical cyclones traveling inan eastward direction, 90°in a northward, and 180°in
a westward respectively.
37

2.2 Extraction of tropical cyclone data

According to the Fig.2, there exist two types of
distributions, (a) angle from 0 to around 125 and (b)angle from around 125 to 360. Tropical cyclones
traveling to northeast are considered to be included in (a)and tropical cyclones traveling to west from east areconsidered to be included in (b). Thus (b) needs to be
extracted from others to develop stochastic typhoon
model focusing on lower-latitudes.

Historical tropical cyclone data mainly influencing onlower-latitudes are extracted in reference to two
separation methods mentioned in the previous section,
namely (iii) traveling angle and (iv) latitude where
tropical cyclones disappeared.

2.2.1 Extraction with angle(iv) Latitude where tropical cyclones disappeared
Distribution of latitudes where tropical cyclones
disappeared is shown in Fig.3.
According to the Fig.3, there exist two distinctive
patterns of distributions, (c) latitude from N 0 ° toaround N 28° and (d) latitude from around N 28°to N
50°. Tropical cyclones traveling westward from east areconsidered to be included in the group of (c). Tropical
cyclones traveling northeastward are considered to beclassified in (d). Thus (c) needs to be extracted fromothers to develop stochastic typhoon model focusing onlower-latitudes.

Tropical cyclones traveling northeastward can beeliminated with the angle between the locations where
tropical cyclones occurred and disappeared as mentioned
in chapter 2.1 (iii). To extract tropical cyclones whichwere classified as (b); angle from around 125 to 360,
composition of two gauss functions is applied torepresent the distribution of traveling angles. The
coefficients of the gauss function were decided as shownin Eq.1 and 2, adjusting the correlation between the
proposed function and actual angles to be a maximum
value. Fig.4 shows two gauss functions and composedvalue.

◆ Actual location where tropical cyclones are generated― Path𝑔(𝑥) = 0.07 ∙ 𝑒𝑥𝑝 (−(𝑥 − 82)2)
2 ∙ 322⋯ ⋯ ⋯ ⋯ (Eq. 1)−(𝑥 − 155)2)
2 ∙ 162⋯ ⋯ ⋯ ⋯ (Eq. 2)

𝑔(𝑥) = 0.091 ∙ 𝑒𝑥𝑝 (A total number of 654 tropical cyclones are classified as(b) and applied with Eq.2 to be eliminated from theoriginal set of tropical cyclones which includes the totalof 1,619 tropical cyclones observed between 1951 and2012.
However, the extraction with angle seems not to beenough to thoroughly separate tropical cyclone data inlower latitudes because some tropical cyclones still
appear in middle latitudes.

Fig.1 Locations of genesis shown in dots and travelingpaths of tropical cyclones between 1951 and 2012.

Fig.2 Azimuth from original locations to locations
disappeared

Fig.4 Gauss functions of angles

2.2.2 Extraction with latitude
With still unwilling tropical cyclone paths as described in
the previous section, the revision of the extraction
method is further required to improve the accuracy ofstochastic typhoon model.
To extract tropical cyclones which were classified as(c), tropical cyclone data whose latitude where they
finally disappeared in the middle latitudes (higher than N30°) was also eliminated.
A total number of 607 tropical cyclones classified as(b) and (c) were finally extracted from the original data,
and they are shown in Fig.5. It can be confirmed thatFig.3 Latitudes where tropical cyclones disappeared38extracted 607 tropical cyclones mostly move within thelower-latitude band.

3.2 Calculation process
The flow of the proposed stochastic typhoon model isshown in Fig.6. The number of repetition number N was
decided as 1000 in this study, after examining stability of
the calculation results for many settings with different N
values.

3. Development of stochastic typhoon
model

Input probability
distribution of latitude

Set latitude

Input the ratio ofwest : east

To the East of thePhilippines

To the West of thePhilippines

Input probability
distribution of longitude

Set longitude

Set longitude

3.3 Proposed model
3.3.1 Probability distribution function ofeach parameter
To develop a stochastic typhoon model, probability
distribution which can reasonably represent the extracted
607 tropical cyclone data is needed to be assumed.
Normal distribution or lognormal distribution wasapplied for probability distributions for this purpose.
However, it was found that two associated parameters ofmean and standard deviation without adjustments many
produce inconsistent results at a specific part of the areas(e.g. unrealistic tropical cyclone generation in EurasianContinent). Thus, the authors introduce adjustment
coefficients for modifying the mean and standard
deviation to fit the probability distribution with the actual
distribution.

3.1 Monte Carlo method(I) Annual number of the tropical cyclones
Lognormal distribution is applied to represent annual
number of tropical cyclones with increasing the mean
vale by 4.8 % and decreasing the standard deviation by
20.8 % from these unadjusted values.
It should be noticed that in Fig.7 a peak of the annual
frequency of tropical cyclones appears at the number of 5which is the smallest number among all the numbers of
frequency in the range between 5and 21. However, itappears that the curve would be unexpectedly biased
towards smaller side if such small number is included indetermining the distribution. Though it may not correctscientifically, the frequency of 5 in Fig.7 wasintentionally eliminated as the frequency of tropical
cyclones genesis should not be underestimated from aviewpoint of the disaster prevention.

(𝑛 = 1,2, ⋯ ) ⋯ ⋯ ⋯ (Eq. 3)

𝑥0 = 𝑏 ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ (Eq. 4)
𝑢𝑖 = 𝑥𝑖 ⁄𝑚 (𝑖 = 0,1,2, ⋯ ) ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ (Eq. 5)

Using 𝑢𝑗 calculated above, Box-Muller method is adopted
to generate random numbers; Y which reflect normal or
log-normal distributions as Eq.6 and 7. M is mean value
and SD is standard deviation.

𝑌 = 𝑆𝐷 ∗ 𝑋 + 𝑀

Set the annual number oftropical storms

Fig.6 Flowchart of proposed stochastic typhoon model

Numerical simulation by the Monte Carlo method uses
random numbers which have been produced many times
according to a given probability distribution function.
Therefore, the probability distribution has to express
actual phenomenon precisely and random numbers has tobe produced so that probability distribution is reflected
correctly.
Multiplication and division method is adopted togenerate uniform random number 𝑢𝑖 , as Eq.3, 4 and 5. In
Eq.3, mod(𝑎𝑥𝑛 , m) is the surplus that m divides 𝑎𝑥𝑛.

𝑋 = √−2𝑙𝑜𝑔𝑈 𝑐𝑜𝑠(2𝜋𝑉)

Input annual number oftropical storms

Generated location isdecidedTo predict the future occurrence of lower-latitude
tropical cyclones, a stochastic typhoon model especially
focusing on lower-latitudes needs to be developed on thebasis of a long-term historical typhoon records.
Parameters on tropical cyclones derived in chapter 2
are used to develop the stochastic typhoon model inchapter 3. The calculation performs the iterative
calculation based on a Monte-Carlo method that changes
a random number and estimates a probability of typhoon
occurrence at given location. Stochastic typhoon model
which estimates the location where tropical cyclones will
be generated has been developed in this study, so
programing a model about tropical cyclones’ path andstrength makes this model upgraded.

𝑥𝑛+1 = 𝑚𝑜𝑑(𝑎𝑥𝑛 , 𝑚)

Set the repetition number: N

Repeat ( 62years×N times )Fig.5 Extraction of tropical cyclone data

Examination of therepetition number⋯ ⋯ ⋯ ⋯ ⋯ (Eq. 6)(II) Latitude where tropical cyclones are generated
Normal distribution is simply applied to represent
latitudes where tropical cyclones are generated without
any modifications for parameters.

⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ (Eq. 7)

39

(III) Longitude where tropical cyclones are generated
Tropical cyclone cannot be generated on thePhilippines’ land. Therefore, the tropical cyclones
generated around E 120 °need to be removed, andconsequently the distributions in terms of longitude
would be prepared for both in the east side and west side.
When a distribution is applied without considering thePhilippines’ land, tropical cyclones are generated on thePhilippines’ land unrealistically. Tropical cyclone dataneeds to be divided into the east side and west side of thePhilippines and applied to probability distribution for
each. West side is to the west of E 122°, and east side isto the east of E 122°. According to the tropical
cyclone data for these 62 years, the ratio of the tropical
cyclone generation between west side and east sides is0.277: 0.723. Thus when the calculated random numbers(which would be within the range between 0 and 1)
indicate less than 0.277, the distribution of west side isapplied to calculate the longitude at which tropical
cyclone occurs.
Normal distribution is applied to the calculation of
the west side’s longitude, with increasing the mean by
0.16 % and decreasing the standard deviation by 8.01 %than the actual data to modify the width narrower. On theother hand, lognormal distribution is applied to thecalculation of the west side’s longitude, with decreasing
the mean by 1.2 % to slightly shift the distribution
towards west and decreasing the standard deviation by
3.13 % than the actual data.
To decrease the expected number of tropical cyclones’
generation around E 120°, tropical cyclone data to thewest of E 124 ° is used to examine probability
distribution of longitude about the west side and tropical
cyclone data to the east of E 124°is used to examine
probability distribution of longitude about the east side.
As the result of composing these two distributions, theexpected number of tropical cyclones which weregenerated on the Philippines’ land could be decreased.
Actual data of longitude and two types of distributions
are shown in Fig.8.

3.3.2 Results of simulation
As the result of stochastic typhoon model, expected
number of tropical cyclones in every 2°×2°grid andactual location where tropical cyclones are generated areshown in Fig.9.
Correlation of calculation results and actual data on
annual numbers of tropical cyclones and location where
they are generated is higher than 0.87. And the results ofthe generation frequency and the spatial distribution
show a proper result with the model.
Annual expected number of tropical cyclones■ 0.08 ~ 0.14
■ 0.04 ~ 0.08
■ 0.011 ~ 0.04
■ 0.001 ~ 0.011■~ 0.001◆ Actual location

Fig.9 result of stochastic typhoon model

4. Conclusion
In this research, 1) tropical cyclones in Northwest Pacific
Ocean between 1951 and 2012 were examined to
identify characteristics of tropical cyclone genesis
location and frequency using the Best Track Data of
JMA. 2) Tropical cyclones which move westward wereextracted in reference to both the traveling angles fromthe origin and the latitudes where they disappeared. 3)
Stochastic typhoon model which is able to predict theoccurrence of future possible significant tropical
cyclones was developed based on Monte Carlo method.

5. References[1] Jonas Rumpf, Helga Weindl, Peter Hoppe, Ernst
Rauch, Vilker Schmidt, “Stochastic modeling of
tropical cyclone tracks”, 2007
[2] Hiroyasu KAWAI and Noriaki HASHIMOTO,“Evaluation of Occurrence Probability Distribution ofExtreme Storm Surges Using Stochastic Typhoon
Model”, technical note of the port and airport
research institute No.1122, 2006
[3] Tomohiro YASUDA, Kei ANDO, Nobuhito MORI
and Hajime MASE, “Prediction and Stochastic
Modeling of Future Typhoon Characteristics based on
AGCM Projections under Global Warming Scenario”,
2010[4] 國富將嗣, “高潮と高波の同時生起確率特性に関する研究”, pp.43-80, 2005

Fig.7 Annual number of the tropical cyclones

Fig.8 Distribution of longitude where tropical cyclones
are generated
40

COMPOSTING BY INOCULATION OF FUNGUS THAT DEGRADES ANTIMICROBIALCOMPOUNDS PRESENT IN THE COMPOST RAW MATERIAL PRETREATED USINGSUB-CRITICAL WATER
Student Number: 12M18034 Name: Akiko OINUMA Supervisor: Kiyohiko NAKASAKI

亜臨界水処理した生ごみ中に含まれる阻害物質の分解菌の単離および単離菌の接種によるコンポスト化
生沼 晶子
近年、有機性廃棄物を資源化する前処理として亜臨界水が注目されており、コンポスト化の前処理としても期待された。本研究では、食品残渣の亜臨界水処理により微生物活性を阻害するフルフラール類が生成されるのでそのままではコンポスト化できないが、新たに発見したフルフラール類を分解する糸状菌を接種することにより可能になること、また食品残渣を 160℃の亜臨界水で前処理するとコンポスト化 10 日間で 186%以上の GI を達成し、高速コンポスト化が可能であることを確かめた。

1 Introduction

and 12.45 g/kg-ds for acetic acid, propionic acid,butyric acid, and lactic acid, respectively. The foodwaste and sawdust were mixed at a ratio of 10:9 andthen, the total 20g-ws of the reaction mixture wastreated by sub-critical water for 30 min at 160, 180,
200, 220, and 240ºC. After the treatment, the organic
matter decomposition rate was calculated from ash
contents of the reaction mixture before and after
treatment (1). The concentrations of 5-HMF and
furfural in the samples were determined by highperformance liquid chromatography (HPLC).

Composting is one of the methods for treatingorganic waste. Among waste materials, organic
fractions such as food waste originating fromhouseholds, restaurants, and food processing factories
can be reclaimed as compost for agricultural use [1].
Development of an accelerated composting method
has been expected to treat a large amount of foodwastes rapidly. In recent years, food wastes has beentreated by sub-critical water based on an assumptionthat the breaking up of the food waste by the
pretreatment using sub-critical water would make thefood wastes more easy to be degraded by the
microorganisms. However, the generation of
5-hydroxy methyl furfural (5-HMF) and 2-furfural(Furfural) during the sub-critical water pretreatment
has been pointed out. Both the 5-HMF and furfural are
known to have the inhibitory effect on the microbialactivity and the efficacy of the sub-critical water
pretreatment came to be doubted. In this study, weinvestigated the effect of the sub-critical water
pretreatment of the food waste on the performance ofthe composting using the treated food waste as raw
material.

2(1)

2.2 Composting of food waste after
sub-critical water pretreatment andisolation of fungus decomposing the
5-HMF and furfural
Food wastes and sawdust were mixed at a ratio of
2:1 on wet weight basis and the mixture was treatedby sub-critical water at 180°C for 30 min to prepare
the treated raw material. The treated raw material was
mixed with a commercial seeding material at a ratio of
19:1 on dry weight basis and then, the moisture
content and the pH were adjusted to 50% and 5.0. At
the start of composting, approximately 3000 g of theraw compost mixture was put into the reactor,
diameter: 300 mm and depth: 400 mm (Fig. 1). Twotypes of seeding materials, Compost product A and B
were used for the Run A1 and B1, respectively.
Temperature was controlled at 30°C until the third day

Material & Methods

2.1 Organic matter decomposition
rate and the generation of 5-HMF and
furfural
The rabbit food and rice were mixed at a ratio of 4:1
to prepare the representative model of food waste. 4
kinds of organic acids are characteristic of food waste:acetic acid, propionic acid, butyric acid, and lactic
acid [2]. These were all added to the reaction mixture
to achieve adjusted concentrations of 2.90, 3.02, 2.43,
41

and then, raised to 60°C at a constant rate of 2.5 °C h-1,
and the 60°C was maintained until the tenth day. The
composting runs were carried out for 10 days. At thetime of turning, approximately15 g of compost waswithdrawn from the reactor at every day. The
degradation of organic matter was monitored bymeasuring CO2 evolution rate, expressed in moles of
CO2 evolved per unit of dry solid compost material
weight per day. In addition, a fungus was isolated
from third day sample in Run A1 and identified bydetermining the base sequence of the ITS1, 5.8S, ITS2
gene in the genome of isolated fungi.

B3. At the start of composting, approximately 12 g of
the raw compost mixture was put into the reactor (Fig.
2). The temperature was controlled similarly as
described at 2.1. Two composting runs, i. e., Run A3and B3 were carried out for 10 days. Changes in theconcentration of the 5-HMF and furfural in thecomposting runs were determined by HPLC.

Fig. 2 Schematic diagram of the composting system.

2.5 Composting of food wastes treatedby sub-critical water with different
heating conditions
The same mixture same as 2.1 was prepared andthen, treated by sub-critical water for 30 min at 160°C(Run B4), 200°C (Run C4), 240°C (Run D4). In
addition, Run A4 was carried out with the row
mixture. The mixtures prepared were mixed withseeding material of compost products at a ratio of 19:1
to prepare the compost raw materials. The moisture
content and pH of the compost raw materials were
adjusted to 50% and 5.0, respectively. At the start ofcomposting, approximately 10 g of each compost raw
material was put into the mini reactor. The
temperature was controlled at 30°C until the fifth day
and then, raised to 60°C at a constant rate of 2.5 °C h-1,
and the 60°C was maintained until the tenth day. On
the fifth day of composting, The moisture content andpH was adjusted to 50% and 8.0. The composting runs
were carried out for 10 days. The conversion ofcarbon at a given compost time was defined as amolar ratio of carbon loss (as CO2) to the total carbon
present in the rabbit food and rice of raw compost
material. Germination index (2) were calculated forzero and tenth day compost sample of A4, B4, C4, andD4 to evaluate the matulity [3].

Fig. 1 Schematic diagram of the composting system.

2.3 Decomposition of 5-HMF, furfuralby the isolated fungus in the liquid
culturePD liquid medium was added with 5-HMF and
furfural to the final concentrations of 7g/L and 0.4g/L,
respectively. The prepared medium with and without
isolated fungus was Run A2 and B2. The FA13 wasstored in a -80°C freezer and precultured twice inpotato dextrose liquid medium at 30°C while shaking
to prepare the inoculum. Upon inoculation, theconcentration of FA13 was adjusted to 105 CFU/ml of
the raw compost mixture. Run B2 was the control
without inoculation of FA13.

2.4 Degradation of 5-HMF and
furfural in the after sub-criticalwater-pretreated food waste using theisolated fungus
The compost raw material (same as 2.2) was mixed
with a commercial seeding material of compost
product B in a ratio of 19:1 on dry weight basis andthen, the moisture content and the pH were adjusted to
50% and 5.0, respectively. The compost row material
with and without the isolated fungus was Run A3 and42

CO2 evolution rate ×105 (mol/h/g-ds)

3

Results & Discussion

3.1 Degree of organic matterdecomposition and the generation of
5-HMF and furfural
Percentage of organic matter decomposition was 6.3,
16.1, 26.1, 37.6, and 56.1% in 160, 180, 200, 220, and
240 ºC, respectively. The case of 240 ºC was thehighest organic decomposition rate in 160-240 ºC. In
addition, the concentration of 5-HMF was 1.32, 5.30,
3.05, 0.50, and 1.10 and furfural was 1.15, 4.67, 3.21,
1.14, and 0.06 in 160, 180, 200, 220, and 240 ºC,
respectively. Concentration of 5-HMF and furfural in
180 ºC were the highest in 160-240 ºC.

Conc. of 5-HMF and furfural (mg/g-ds)

0
2

4
6
Time (d)810The concentration of inhibitors was measured underboth conditions (Fig. 6). The concentration of 5-HMF
decreased 85% after 72 hours and the concentration of
furfural decreased to below the detection limit after 48
hours in Run A2. On the other hand, the concentrationof both inhibitor didn’t decrease in Run B2. Therefore,
decomposition efficiency of 5-HMF, furfural by FA13
became clear.

642

3.4 Composting of food waste by
sub-critical water pretreatment with
FA13

0
8

2

3.3Decomposition efficiency of 5-HMF,
furfural by FA13

5-HMF (Run A1)
Furfural (Run A1)
5-HMF (Run B1)
Furfural (Run B1)

4
6Time (d)4Fig. 5 Phylogenetic tree for the strain FA13

10

2

6

Fig. 4 The courses of CO2 evolution rate during thecomposting for Run A1 and B1.

The courses of the concentrations of 5-HMF and
furfural during the composting were shown in Fig. 3.
The concentration of 5-HMF was decreased from
8mg/g-ds to 3mg/g-ds and the concentration of
furfural was decreased to below the detection limit
until third day in Run A1. On the other hand, theconcentration 5-HMF was remained 3.1mg/g-ds ontenth day and furfural was decreased to below thedetection limit until eighth day in Run B1. Fungi
increased to 105.6 CFU/g-ds on third day in Run
A1, and, any microorganisms didn’t increase on third
day in Run B1 (data not shown). CO2 evolution rateincreased on third day in Run A1 (Fig. 4). On theother hand, CO2 evolution rate was low until ninth day
in Run B1. It was suggested that the fungi
decomposed the organic materials include inhibitor
and the CO2 evolution rate increased on third day. The
fungus was isolated and identified as Paecilomyces sp.
(Fig. 5). The fungus was named strain FA13.

0

Run A1Run B18

0

3.2 Composting of food waste after
sub-critical water pretreatment andisolation of fungus decomposing the
5-HMF and furfural

8

10

10

The marked production of CO2 was observed in Run
A3 in contrast to the case of Run B3 though both runs
were conducted under the same experimental
conditions and it was confirmed that the organic
matter was degraded vigorously in Run A3 (Fig. 7).

Fig. 3 The courses of concentration of 5-HMF and
furfural during the composting for Run A1 and B1.

43

A4 was the highest value among 4 experimental runs.
It suggest that a parts of organic matter was changed
intodecomposing
persistentmatterfor
microorganisms by sub-critical pretreatment. It wasreported that the GI for very mature, mature andimmature sample were >90, 80-90% and <80%,
respectively. The GI was 0% in Run B4, C4 and D4
on day 0. On the other hand, GI was 25.2% in Run A4,
194% in Run B4, 319% in Run C4 and 186% in Run
D4 on day 10. It suggested that the food waste with
sub-critical water pretreatment became maturecompost without containing the germination andgrowth inhibitor.

(n=3)

8000
7000
6000
5000

(n=3)

4000

60

Run A2 (5-HMF)
Run B2 (5-HMF)
Run A2 (Furfural)
Run B2 (Furfural)

3000
2000

Conversion of C (%)

Concentration of 5-HMF and furfural (mg/L)

Fig. 7 compares the concentration of 5-HMF and
furfural in Run A3 and B3. The concentration of
5-HMF on day 0 was 8.0mg/g-ds and it decreased to
below the detection limit on third day in Run A3,
which demonstrated that the strain FA13 had the
5-HMF degradation ability.

1000
0
0

24

48

72

Time (h)3Conc. of 5-HMF and CO2 evolution rate × 10
furfural (mg/g-ds)(mol/d/batch)

Fig. 6 The courses of concentration of 5-HMF and
furfural for Run A2 and B2.

Run A4 (Control)
Run B4 (160℃)
Run C4 (200℃)
Run D4 (240℃)

50
40
30
20
10

(n=3)

8

0

Run A3
Run B3

6
4

0

2

4
6
Time (d)810Fig. 8 The courses of conversion of C during thecomposting for Run A4, B4, C4 and D4.

20

4 Conclusions

10

5-HMF (Run B3)
5-HMF (Run A3)
Furfural (Run B3)
Furfural (Run A3)

8
6

In this study, it can be achieved the composting offood waste with sub-critical water pretreatment by
inoculation of FA13. Food waste with sub-criticalwater pretreatment became mature compost without
containing the germination and growth inhibitor for
shorter periods of composting than food waste without
sub-critical water pretreatment.

4
2
0
0

2

4
6
Time (d)810Fig. 7 The courses of CO2 evolution rate andconcentration of 5-HMF and furfural during thecomposting for Run A3, B3.

References[1] Nakasaki, K., Araya, S., Mimoto, H., Inoculationof Pichia kudriavzevii RB1 degrades the organic acids
present in raw compost material and accelerates
composting. Bioresour. Technol. (2013)[2] Sundberg, C., Franke-Whittle, I., Kauppi, S., Yu,
D., Romantschuk, M., Insam, H., Jönsson, H.
Characterisation of source-separated household waste
intended for composting. Bioresour. Technol. 102,2859-2867. (2011)[3] Kanazawa, S., 肥効の高い堆厩肥の製造と新し
い腐熟度検定法. Soil and Microorganism. 56, 1,
45-54. (2002)

3.5
Composting of representativemodel of model food waste by
sub-critical water pretreatment ofdifferent heating condition with FA13
Conversion of carbon during composting wasmeasured as depicted in Fig. 8. The higher the heat
pretreatment, higher the conversion of C became on
day 0. On the other hand, Run A4 was 50%, B4 was
37%, C4 was 32%, D4 was 38% on day 10 and Run

44

The isolation and utilization of thermopilic lactic bacterium strain TP1 in thebiorefinery
Student Number: 12M18212 Name: Yimeng Xu

Supervisor: Kiyohiko Nakasaki

バイオリファナリーにおける好熱性乳酸菌 TP1 株の単離および利用
徐芸萌本研究では、耐熱性乳酸菌の単離と､単離した好熱性乳酸菌を用いたバイオマスからの乳酸生産を試みた。耐熱性乳酸菌として TP1 株を単離することができ、同定の結果 Bacillus smithii strain NRS-173と 99％の相同性を有することがわかった。TP1 株によるグルコースからの乳酸生成速度を常温乳酸菌
LA1 株と比較したところ、TP1 株の方が大きい生成速度を示した。また､バイオマスとしてマイクロウ
ェーブ処理したタケ、未処理のアナアオサとチガイソを使用し、TP1 株を用いて乳酸生成について検討したところ、チガイソが最も乳酸生成に適することが確かめられた。

1of these biomass to enhance the efficiency ofenzymatic hydrolysis of glucans which arepolysaccharides composed of glucose.
Generally, chemical reaction proceeds more
rapidly under higher temperature condition.
Therefore, it is considered that lactic acid can beproduced more rapidly at high temperature
condition. In this study, it was aimed to isolate athermophilic lactic acid bacterium and to produce
lactic acid from biomass under high temperature
condition using newly isolated microorganism.

Introduction

Biorefinery, production of bulk chemicals andfuels from biomass, has attracted attention in recent
years. Lactic acid is used as raw material of
biodegradable plastic, and the development of theprocess for an efficient lactic acid production frominedible biomass has long been required. Thus,
many studies have been performed on the
production of lactic acid from inedible biomass,
such as lignocellulosic biomass [1], paper sludge [2],and other wastes [3-4].
In order to produce lactic acid from biomass, theenzymatic hydrolysis of polysaccharide in biomass
to produce fermentable sugar and fermentation of
the sugar by lactic acid bacterium to produce lactic
acid are combined. In addition, the efficient
enzymatic hydrolysis of polysaccharide in biomass
requires a pretreatment to make enzyme moreaccessible to polysaccharide. The pretreatment ofbiomass using acid, alkali, or organic solvent[5]enhances the efficiency of the enzymatichydrolysis of polysaccharide, but chemical reagent
such as acid, alkali, and organic solvent has anegative effect on the environment. Therefore,hydrothermal treatment is recognized as apromising pretreatment method.
Microwave treatment is a hydrothermal treatment,
and microwave irradiation heats water in thistreatment. In this study, bamboo, one of thelignocellulosic biomass, sea lettuce, one of thegreen seaweed, and chigaiso, one of the brownseaweeds, were used as inedible biomass, andmicrowave treatment was used as the pretreatment

2

Materials & Methods

2.1 Biomass, enzyme, and lactic acidbacterium
Bamboo, sea lettuce (Ulva pertusa Kjellman),and chigaiso (Alaria crassifolia Kjellman) (Fig.1)
were used as biomass for lactic acid production.
Moso bamboo obtained in Shizuoka prefecture
was used as bamboo, and pulverized into fine
powder that has an approximately 50 μm of
average particle size by using a grinder (PA-C,
Marudai Co.). Sea lettuce and Chigaiso were
harvested in Hokkaido prefecture. These seaweeds
were washed using tap water, and dried in the sunfor 5 h. Dried seaweeds were powdered using a mill
(ZM-100, Retsch GmbH) to less than 0.5mm indiameter before use. The glucans contents ofbamboo, sea lettuce and chigaiso wereapproximately 45.0%, 22.0%, and 24.5%,
respectively, on a dry weight basis. In addition,
mannnitol was also contained as a fermentablesugar in chigaiso with the content of 7%.

45

Meicerase (CEPB-5394, Meiji Seika Kaisya Ltd.),derived from Trichoderma viride was used as
enzyme for the hydrolysis of glucans in biomass.
Lactobacillus paracasei LA1 (strain LA1),
isolated from a wastewater sludge, was used as
lactic acid bacterium.

Bamboo(Fine powder)

Sea Lettuce

conditions were 180, 190, and 200ºC. The
enzymatic hydrolysis of biomass with and without
microwave treatment was carried out to investigate
the effect of microwave treatment for enzymatichydrolysis. Each biomass was added to 0.1 M citricacid buffer solution (pH 5.5). The mixture wassterilized by autoclaving at 121ºC for 20 min. Filter
sterilized Meicelase solution was then added to the
mixture. The concentrations of biomass andMeicelase were adjusted to 20 and 1 g/L,
respectively. Enzymatic hydrolysis was conducted
at 35ºC for 96 h. The concentration of glucose afterhydrolysis was determined using HPLC.

Chigaiso

2.5 Lactic acid production frombiomass using isolated bacteriumFig.1 The pictures of the biomass used in this study.

In order to produce lactic acid from biomass,lactic acid fermentation was carried. Bamboo
treated by microwave at 190ºC for 30 min waswashed using distilled water and then used for lactic
acid production. Sea lettuce and chigaiso without
microwave treatment were used for lactic acidproduction.
Enzymatic hydrolysis of biomass was conducted
as described in 2.4 except that hydrolysis
temperature and the concentration of biomass werechanged to 50ºC and 60 g/L, respectively. Afterhydrolysis, Bacto peptone and yeast extract wereadded to the hydrolysate so that the concentrationsof Bacto peptone and yeast extract attained 5 and 10
g/L, respectively. The precultured isolated lactic
acid bacterium was then inoculated, andfermentation was conducted at 60ºC for 36 h.
The concentrations of fermentable sugars andlactic acid, acetic acid were determined using HPLC,
and the cell density of isolated bacterium was also
determined using the dilution plating method.

2.2 Isolation and identification of athemophilic lactic acid bacterium
Seaweed compost of 1g in 9 mL of sterilized
water was homogenized and the suspension wasserially diluted with sterilized water. The diluted
suspension was spread onto GC agar medium andthe agar plate was incubated at 60ºC. GC agar
medium contained insolubile CaCO3 andgeneration of lactic acid bacteria will dissolve
CaCO3. Therefore the formation of a clear zone
around the colony of lactic acid bacteria was
expected. For the identification of the isolated
bacteria, DNA extraction, PCR amplification andDNA sequencing of 16s rRNA gene fragment werecarried out.

2.3 Lactic acid production fromglucose
Production of lactic acid from glucose using theisolated thermophilic lactic acid bacterium andstrain LA1 were carried out. The thermophilic lactic
acid bacterium was inoculated to GC liquid medium
and cultivated at 60ºC 150rpm for 48h. The
cultivation of the strain LA1 was the same with thatof isolated bacterium except that the temperature
was 30ºC instead of 60ºC. During the cultivation,
samples were taken and concentrations of glucose,
lactic acid, acetic acid were measured by HPLC.

Bacillus methanolicus strain
Saccharococcus thermophilus strain 657
Bacillus aeolius strain 4-1
Bacillus ginsengihumi strain Gsoil 114
Bacillus isabeliae strain : CVS-8
Bacillus seohaeanensis strain BH724
Bacillus sporothermodurans strain M215
Bacillus firmus strain KSC SF8b
Bacillus kribbensis strain BT080

2.4 Enzymatic hydrolysis of biomass
with and without microwave
treatment

Bacillus smithii strain NRS-173
TP1
0.005

One gram of biomass was put into a microwave
reactor with 10 mL of distilled water. The reactor
was irradiated by microwave (Wave magic,
EYELA), and heated. The heating temperature

Fig. 2 The phylogenetic tree of strain TP1 base on
gene sequences.
46

3

Results & Discussion

were 1.5, 2.6, 4.7, and 4.8 g/L, respectively, andmicrowave treatment enhanced the efficiency ofenzymatic hydrolysis of bamboo. Since theconcentrations of glucose produced from bamboo
treated at 190 and 200ºC were similar, we usedbamboo treated at 190ºC as substrate for the
production of lactic acid. The conversion of glucans
and oligosaccharides was calculated as 52.2% in thecase of bamboo treated at 190ºC.
The concentrations of glucose produced fromseaweeds treated by microwave at all temperature
were lower than those from untreated seaweed. In
addition, glucans and oligosaccharides contained
in seaweeds were considerably hydrolysed without
pretreatments, such as microwave treatment, and58.0% and 94.2% of glucans and oligosaccharides
conversions were achieved in the cases of sea
lettuce and chigaiso, respectively.

3.1
Identificationofisolatedthermophilic lactic acid bacterium
The thermophilic lactic acid bacterium, strain
TP1, was successful isolated from seaweed compost.
Fig. 2 shows the phylogenetic tree of strain TP1
constructed based on the 16s rRNA gene sequence.
Strain TP1 showed 99% of similarity with the genesequences of Bacillus smithii strain NRS-173.

3.2 The productivity comparison
between isolated bacterium andstrain LA1
Fig. 3 and Fig. 4 show the courses ofconcentration of glucose, lactic acid and acetic acidduring the cultivation of the strain TP1 and strain
LA1 respectively. It was ascertained that the lactic
acid was produced by strain TP1. Most of the
glucose was consumed by strain TP1 in 6h and 8.07
g/L of lactic acid was produced. On the other hand,
there remain some glucose in the culture of strain
LA1 after 6h and 6.77g/L of lactic acid was
produced. The productivity of lactic acid by strain
TP1 and LA1 in 6h were 1.34g/L/h and 1.13g/L/h,respectively. The productivity of strain TP1 washigher than strain LA1 though the difference was
not much significant as we expected.
After 6h of cultivation, the increase in the acetic
acid concentration was observed with the decreaseof the lactic acid concentration. Therefore, it wasalso revealed that the longer cultivation time than
6h reduced the productivity of lactic acid because of
the conversion of lactic acid to the acetic acid by
TP1. On the other hand, acetic acid producing
ability of TP1 was indicated. Therefore, by
shortening the fermentation time, lactic acid can beproduced and by extending the fermentation time,
acetic acid can be produced. Since acetic acid isalso produced in the biorefinery production ofacetic acid in addition to the lactic acid using thestrain TP1 was expected.

Concs. of glucose, lactic acidand acetic acid(g/L)

12
Glucose
Lactic acidAcetic acid

10
8
6
4
2
0

0

6

12
Time (h)1824Fig. 3 The courses of concentrations of glucose,
lactic acid and acetic acid by strain TP1 cultivation(n=3).

Concs. of glucose, lactic acidand acetic acid(g/L)

12

3.3 Effect of microwave treatment
on the enzymatic hydrolysis ofbiomass864
20The concentration of glucose produced byenzymatic hydrolysis of biomass treated by
microwave at different temperatures for 30 min iscompared to that of untreated biomass in Fig. 5. The
concentrations of glucose produced from untreatedbamboo, bamboo treated at 180, 190, and 200ºC

Glucose
Lactic acidAcetic acid

10

0

6

12
Time (h)1824Fig. 4 The courses of concentrations of glucose,
lactic acid and acetic acid by strain LA1 cultivation(n=3).
47

Therefore, untreated sea lettuce and chigaiso wereused as substrates for the production of lactic acid.

produce in the fermentation of chigaiso. Higher
concentration of lactic acid and acetic acid could be
produced from chigaiso compared to those from sea
lettuce and treated bamboo, and it was consideredthat chigaiso was more suitable for the fermentation
using strain TP1.

Concentration of glucose (g/L)

7
BambooSea Lettuce
Chigaiso

6
5

4

4
3
2
1
0
No

180℃

190℃

200℃

Fig. 5 Comparison of the concentration of glucose
produced by enzymatic hydrolysis of biomass
treated by microwave at different temperatures for
30 min and that of untreated biomass (n=3).

3.4 Lactic acid production frombiomass
The concentrations of lactic acid and acetic acidproduced from biomass using strain TP1 are shownin Fig. 6. After 6 hours cultivation, glucose wasalmost consumed and the lactic acid concentration
attained 6.8g/L in the fermentation of microwave
treated bamboo. The productivity of lactic acid fromtreated bamboo after 6h cultivation was 1.13g/L/h.
In addition, it was confirmed that 4.1 g/L of acetic
acid could be produced after 24h cultivation.
In the fermentation of sealettuce、 5.4g/L of Lactic
acid after 6h and 4.1 g/L of acetic acid after 24h
cultivation were attained while 9.0 g/L of lactic acidafter 12h and 8.0g/L of acetic acid after 48h was

References[1] Garde A, Jonsson G, Schmidt AS, Ahring BK.
Lactic acid production from wheat straw
hemicellulose hydrolysate by Lactobacillus
pentosus and Lactobacillus brevis.Bioresour
Technol 2002;81:217–223.
[2] Nakasaki K., Adachi T. Effects of Intermittent
Addition of Cellulase for Production of L-lactic
acid from Wastewater sludge by Simultaneous
Saccharification and Fermentation. Biotechnol
bioengineering 2003; 82:263-270.

Concentration of lactic acidand acetic acid (g/L)

12
10Conclusions

In this study, thermophilic lactic acid bacterium
Bacillus smithii, strain TP1 was successfully isolated.
It was demonstrated that the productivity of lactic acidfrom glucose by strain TP1 was higher than that by thestrain LA1. In addition to the lactic acid, the acetic
acid also can be produced using strain TP1 bycontrolling the fermentation time. Microwave
treatment facilitated the enzymatic hydrolysis ofbamboo and high lactic acid productivity by strain
TP1 from treated bamboo could be demonstrated.
Both the lactic acid and acetic acid could be produced
form the sea lettuce and chigaiso, and fermentation ofchigaiso showed more efficient productivity than thatof sealettuce.

Lactic acidAcetic acid

[3] Ohkouchi Y, Inoue Y. Direct production of
L-(+)-lactic acid from starch and food wastes using
Lactobacillus
manihotivorans
LMG18011.
Bioresour Technol 2006; 97:1554-1562.

864[4] Chan-Blanco Y, Bonilla-Leiva AR, Velazquez
AC. Using banana to generate lactic acid throughbatch process fermentation.Appl Microbiol
Biotechnol 2003;63:1

2
0Microwave
Sea Lettuce
treated bamboo

ChigaisoFig. 6 The concentration of lactic acid andacetic acid produced from biomass using
strain TP1(n=3).

[5] Sun Y, Cheng J. Hydrolysis of lignocellulosic
materials for ethanol production: a review.
Bioresource Technol. 2002;83:1-11
48

MULTIPLE PERSPECTIVES OF THE ONE LAPTOP PER CHILD INITIATIVE: THE CASE OF MONGOLIA
Student Number: 11M51175 Name: John AUXILLOS Supervisors: Shinobu YAMAGUCHI & Jun-ichi TAKADAThis study employs a multi-phased pragmatic mixed-methods research that investigates the impact of the One
Laptop Per Child (OLPC) initiative introduced in Mongolian in 2008. The OLPC is a non-profit organization foundedby Nicholas Negroponte in 2005 to empower the world’s underserved children, following the constructivist learningtheory, through purposely built low-cost and rugged laptops filled with educational software. In Mongolia, 46 schools
were given a total of 12,100 OLPC XO1 laptops and this research analyzes both quantitative and qualitative datacollected between December 2011 and May 2013 from the stakeholders. The findings indicate that children develop
differently and the impact also proliferated to the community. While these findings are not generalizable, it builds acase for further research.

1. Introduction

2. Literature Review

Over three decades ago, Seymor Papert, a protégée of a
Swiss development psychologist named Jean Piaget,suggested that “it is possible to design computers sothat learning to communicate with them can be anatural process” and when computers are designed
suitably, it was envisioned that learning tocommunicate with it, as suggested by theconstructionist learning theory, will change howlearning takes place. (Papert, 1980, p. 6). In 1980,
Papert and Nicholas Negroponte conducted anexperiment in Dakar, Senegal and found that children
they encountered would learn how to use the computer
similar to middle-class Americans (Negroponte, 1996).
These ideas and experiments lead to the launch of the
One Laptop Per Child (OLPC) initiative in 2005 with agoal of designing, manufacturing, and distributing
laptops with a target price of 100 USD for children
between the ages of 6 to 12 in underserved areas in theworld.
The OLPC is a non-profit organization and its
vision is also embodied in its name. Thoughtful designof laptops is believed to create learning opportunities
for children. What they envisioned is not that of ateacher in a classroom teaching, but rather children
exploring and building a mental model of ideas andknowledge using a laptop. Around the world, there are
54 countries with OLPC deployments to date (One
Laptop Per Child, 2011)
In Mongolia, the OLPC initiative was introducedby two MIT students, Enkhmunkh Zurgaanjin and Jan
Jungclaus. By late 2007, a Memorandum ofUnderstanding was made between OLPC and theMongolian government to introduce the laptop tochildren in the rural area and in Ulaanbaatar City
(Embassy of Mongolia, 2007). A total of 12,100 OLPCXO1 laptops were distributed throughout the country to
46 schools.
The objective of this research is twofold. The firstis to document and understand the impact of the OLPCXO1 laptops distributed in Mongolia since 2008 on thechildren and other stakeholders. The second is toconduct this research using a pragmatic mixed methods
approach, a methodological exercise, to be able toillicit breadth and depth in understanding the context ofthe stakeholders of the project.

There is widespread belief that there is a need to doresearch on ICT in education as “it is generally
believed that ICTs can empower teachers and learners,
promote change and foster the development of 21st
century skills, but data to support these beliefs are still
limited.” (Trucano, 2005, p. 5)
In the studies conducted over the past decade,
impact of the use of computers and its software on
student learning achievement scores has not beenfound (Angrist, 2002; Institute of Education Sciences,
2007). Specifically, in a two-year randomized
evaluation of the Computer for Education project inColumbia published in 2009, there was little impact onmath and Spanish test scores (Barrera-Osorio &Linden). In a large-scale randomized evaluation of the
OLPC program in Peru after 15 months of
implementation in 319 primary schools found noevidence of effect on test scores in Math and Language(Cristia, Ibarrarán, Cueto, & Santiago, 2012).
There are various opinions about the OLPC
project in current literature. James (2010) questions theneed for the one laptop per child ratio that the OLPC
adopted, especially in the context of improving
education in developing countries. Mitra’s project inIndia (2006) found evidence that groups of children
using a computer can have positive results. In Uruguay,
Hourcade (2008) found that in spite of problems with
infrastructure, hardware, and software problems, there
was a positive impact on children, the school, and thetown, with children specifically increasing theirinterest in reading and writing. In Peru, researchers
found that cognitive abilities may increase throughusing the programs on the laptop and it was reflected inslight increases measured by Raven’s Matrices (Cristia,
Ibarrarán, Cueto, & Santiago, 2012). In Nepal,
researchers claim that OLPC allowed teachers to fully
integrate ICT-based instruction since students cancontinue learning outside the classroom (Bhatta, 2008).
Literature about the OLPC in Mongolia is limited.
No journal articles have been published thus far on thiscountry deployment. Therefore this study serves tocontribute towards understanding the OLPC
deployment in the Mongolian context. It furthers thecurrent literature by conducting a study with the use ofmultiple perspectives.

49

3. Methodology

included questions relating to numeracy, algebra,
geometry, and probability while the reading test
covered topics on language use, meaning, grammar,
and an essay section. To analyze the data, thefollowing OLS (ordinary least squares) model wasused to estimate the effect of the OLPC XO1 laptops
on math score (1) and reading score (2), controlling forrelevant factors:

3.1. Mixed-Methods
Mixed-methods was chosen because of three reasons:First, the research problem of this study is a complex
one that seeks to understand the relationship of a pieceof technology, the people who use it, and also in thecontext of the community they are in. The second
reason is the limited information available for the
study, which is a reality in developing countries. The
third is the lack of a standard methodology for fully
assessing the impact of computers on children(Trucano, 2005).
This study was conducted between December
2011 and May 2013 including six field visits to
Mongolia. Both quantitative and qualitative datacollection techniques were used to gather different
perspectives. It involved three phases.

𝑚𝑎𝑡ℎ. 𝑠𝑐𝑜𝑟𝑒 = 𝛽! + 𝛽! 𝑐𝑎𝑠𝑒. 𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦+ 𝛽! 𝑠𝑜𝑐𝑖𝑜𝑒𝑐𝑜𝑛𝑜𝑚𝑖𝑐. 𝑖𝑛𝑑𝑒𝑥+ 𝛽! 𝑠𝑡𝑢𝑑𝑒𝑛𝑡. 𝑠𝑒𝑥 + 𝛽! 𝑠𝑡𝑞02.0+ 𝛽! 𝑠𝑡𝑞14.0 + 𝛽! 𝑠𝑡𝑞16.0+ 𝛽! 𝑠𝑡𝑞20.0+ 𝛽! 𝑠𝑡𝑢𝑑𝑒𝑛𝑡. 𝑐𝑙𝑎𝑠𝑠. 𝑟𝑎𝑡𝑖𝑜+ 𝑒𝑟𝑟𝑜𝑟𝑟𝑒𝑎𝑑𝑖𝑛𝑔. 𝑠𝑐𝑜𝑟𝑒 = 𝛽! + 𝛽! 𝑐𝑎𝑠𝑒. 𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦+ 𝛽! 𝑠𝑜𝑐𝑖𝑜𝑒𝑐𝑜𝑛𝑜𝑚𝑖𝑐. 𝑖𝑛𝑑𝑒𝑥+ 𝛽! 𝑠𝑡𝑢𝑑𝑒𝑛𝑡. 𝑠𝑒𝑥 + 𝛽! 𝑠𝑡𝑞02.0+ 𝛽! 𝑠𝑡𝑞14.0 + 𝛽! 𝑠𝑡𝑞16.0+ 𝛽! 𝑠𝑡𝑞20.0+ 𝛽! 𝑠𝑡𝑢𝑑𝑒𝑛𝑡. 𝑐𝑙𝑎𝑠𝑠. 𝑟𝑎𝑡𝑖𝑜+ 𝑒𝑟𝑟𝑜𝑟

3.1.1. Phase 1
The first phase focused on establishing a base ofknowledge in the case of Mongolia and seeks toanswer: 1. What is the context the OLPC wasintroduced in Mongolia? 2. What is the extent of the
project implementation? 3. What are the available
information about the OLPC initiative in Mongolia? 4.
What are the opportunities and challenges the OLPC
initiative are facing in Mongolia?
Interviews and focus group discussions wereconducted with two members of the OLPC ProjectManagement Unit in Mongolia, 10 teachers, 4 training
managers, and 7 methodologists. A questionnaire wasalso distributed to all 46 OLPC schools where 34
schools responded. This covered the following fiveaspects: 1) the background of the school, 2)
infrastructure available at the school, 3) OLPC
distribution information, 4) status of the hardware, and5) the views of the initiative.

(1)

(2)

where math.score and reading.score represents theoutcome variable, and case.category is a dummy
variable for treatment assignment status. Control
variables include socioeconomic.index an 18-point
scale measuring available materials at home and school.
Other variables included are, student.sex (a dummy
variable), the number of family members (stq02.0), thedaily hours a student spends on homework (stq14.0),
the daily hours a student spends on house chores(stq16.0), the daily hours a student spends watching
TV (stq20.0), and the total number of Grade 5 students
divided by the number of Grade 5 classes in a school(student.class.ratio). Finally, error is the error term.
The coefficient 𝛽! is the parameter of interest andcorresponds to an estimate of the average treatment
effect. 𝛽! to 𝛽! are the coefficients of the control
variables.
The second instrument was the Computer
Attitude Measure for Young Students (CAMYS), a tool
to measure children’s’ disposition towards computers.
The CAMYS scale is presented as a 5-point Likert
scale (5 - strongly agree to 1 - strongly disagree) thatconsists of twelve questions divided into three groups:
1) perceived ease of use; 2) affect towards computer;and 3) perceived usefulness. Independent samples t-test
was used to compare the average CAMYS scores of 7
paired schools with a total of 1596 valid samples.

3.1.2. Phase 2
The second phase was a quasi-experimental study
conducted with the use of two instruments. It intends tounderstand the impact of the OLPC measured by
student learning achievement scores and a computer
attitude measure. Data was collected from 2000
students in November 2012 from 14 schools, where
half were control schools. Of the 7 pairs of schools, 3pairs were from the capital city, and one pair of schools
was then selected from the northern, southern, eastern,
and western regions. Schools were paired on the basisof location and advise from the local education
specialists.
The first instrument was the Mongolian National
Assessment of Primary Education Mathematics andReading for 5th graders, a student learning achievement
instrument developed, piloted, and administered in2008 under the World Bank Rural Education andDevelopment project. Among 7 paired schools, 3 pairs,
one pair from Khovd province and two pairs from
Ulaanbaatar City, were selected for the analysis with a
total of 489 valid samples. The mathematics test

3.1.3. Phase 3
The third phase is a confirmation of the data collectedin the first two phases with the use of case studies. The
research questions of this phase are as follows:
1) What are the similar experiences of using the
OLPC in the different schools?
2) What are the similar issues of concern of thedifferent OLPC schools?
3) What are the similar observed impacts of the
OLPC across schools and different stakeholders of
the project?
504) What are the unique practices of specific OLPC
schools that can lead to better implementation of theinitiative?
Interviews and focus group discussions wereconducted with a total of 15 children, 22 teachers, 2parents, 5 school administrators, and 2 methodologists
from Tsast-Altai, a school in Khovd province, School#52 in the center of Ulaanbaatar city, and School #12
in the periphery of Ulaanbaatar city.

student sex and the daily hours a student watches TV,
suggest the followings: 1) female students would score1.46 points higher on average; and 2) students who
spend longer hours watching TV would score 0.95
points higher.
𝑟𝑒𝑎𝑑𝑖𝑛𝑔. 𝑠𝑐𝑜𝑟𝑒 = 24.76 + 3.42𝑐𝑎𝑠𝑒. 𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦− 0.01𝑠𝑜𝑐𝑖𝑜𝑒𝑐𝑜𝑛𝑜𝑚𝑖𝑐. 𝑖𝑛𝑑𝑒𝑥− 2.16𝑠𝑡𝑢𝑑𝑒𝑛𝑡. 𝑠𝑒𝑥− 0.24𝑠𝑡𝑞02.0 + 0.12𝑠𝑡𝑞14.0+ 0.30𝑠𝑡𝑞16.0 + 1.29𝑠𝑡𝑞20.0+ 0.04𝑠𝑡𝑢𝑑𝑒𝑛𝑡. 𝑐𝑙𝑎𝑠𝑠. 𝑟𝑎𝑡𝑖𝑜+ 𝑒𝑟𝑟𝑜𝑟4. Findings
4.1.

Findings from Phase 1

The reading results is 𝑅 ! = 0.065, 𝐹 8,480 =
4.187, 𝑝 < 0.001 .
Variableofinterest
is𝑐𝑎𝑠𝑒. 𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦 = 3.42 and is statistically significant
at the 99% level, indicating that a student with an
OLPC computer can score an average of 3.42 points
higher for a 52-point reading learning achievement test.
Similar to the math results, two significant control
variables, student sex and the daily hours a student
watches TV, suggest the following analysis: 1) female
students would score 2.16 points higher on average;
and 2) students who spend longer hours watching TV
would score 1.29 points higher.
Independent-samples t-tests were conducted tocompare mean computer disposition as measured by
the CAMYS instrument in OLPC and non-OLPC
schools. It was found that rural schools (Darkhan-Uul,
Dornogobi, Khovd, and Sukhbaatar) all exhibited
statistical differences in the average computer
disposition of 5th grade students, whereas urban
schools (UB Bayangol and UB Khaanuul) exhibited
similaraveragecomputerdisposition.
UBSongingnokhairhain is the exception to the urban
schools group since and is likely because of its location
at the periphery of the capital city.

The OLPC initiative introduced in 2008 is the largest
ICT in Education project for Mongolia. With 12,100
laptops distributed to 46 schools, this was primarily arural project as 57% (26) schools that participated wererural schools and 61% (7494) of laptops were
distributed to rural schools. Electricity was available
for 89% (41) of the participating schools. Internet wasavailable for 59% (27) schools but this does notindicate whether students themselves can access theinternet on their laptops. As a matter of national policy,
the OLPC XO1 laptops distributed are the property ofthe state and parents must sign a tripartite contract with
their child’s teacher and the school that binds parents
to any costs incurred when the laptop needs to be
repaired due to damages arising from their child’s
usage or loss. The OLPC initiative and responsibility
was handed to the Ministry of Education and Science,
who formed a Project Management Unit (PMU) to
oversee the program. Gaps were found on theunderstanding of the project objectives from thedifferent levels of the stakeholders. The OLPC vision
was to empower children by providing them withlearning opportunities through the XO1 laptop. The
state understood the project as enabling access to
education. Teachers understood project as giving
children the opportunity to be exposed to ICT. At thismoment, the future of the OLPC initiative in Mongolia
is uncertain as indicated by the PMU.

4.2.

4.3.

Findings from Phase 3

Schools that were visited indicated that children areable to develop a variety of skills as a result of the
OLPC program. Stakeholders have also indicated that
the OLPC has a positive benefit to teachers, parents,
and the community such as increasing teachers andparents’ ICT skills. In one school a parent indicatedthat because of the program, they are now willing andable to invest in buying their own computer and also
support repair costs of broken laptops.

Findings from Phase 2

The result of the OLS Regression on the Mongolian
National
AssessmentofPrimary
Education
Mathematics and Reading is as follows:
𝑚𝑎𝑡ℎ. 𝑠𝑐𝑜𝑟𝑒 = 23.03 + 2.37𝑐𝑎𝑠𝑒. 𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦− 0.02𝑠𝑜𝑐𝑖𝑜𝑒𝑐𝑜𝑛𝑜𝑚𝑖𝑐. 𝑖𝑛𝑑𝑒𝑥− 1.46𝑠𝑡𝑢𝑑𝑒𝑛𝑡. 𝑠𝑒𝑥− 0.19𝑠𝑡𝑞02.0 − 0.27𝑠𝑡𝑞14.0− 0.04𝑠𝑡𝑞16.0 + 0.95𝑠𝑡𝑞20.0+ 0.02𝑠𝑡𝑢𝑑𝑒𝑛𝑡. 𝑐𝑙𝑎𝑠𝑠. 𝑟𝑎𝑡𝑖𝑜+ 𝑒𝑟𝑟𝑜𝑟(4)

5. Discussion
As a result of the interviews and focus group
discussions with the different stakeholders, several
trends have emerged that can solicit further
investigation. 1) The OLPC lead a bottom-up adoptionof ICT. 2) Teachers worked together to teachthemselves ICT. 3) Teachers believe there is a positive
impact on children’s’ development. 4) Teachers wereable to find a means of maximizing the utility of the
XO1 laptops. 5) The design of the XO1 laptop is adeterrent to theft. 6) There was a positive acceptance of(3)

The math results is 𝑅 ! = 0.050, 𝐹 8,480 =
3.17, 𝑝 < 0.01 . The variable of interest was𝑐𝑎𝑠𝑒. 𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦 = 2.37 and is statistically significant
at the 99% level. This indicates that a student with an
OLPC computer can score an average of 2.37 points
higher for a 44-point math learning achievement test.
In addition, two significant control variables, namely,51

the OLPC initiative. 7) There are possible negative
repercussions.
As there is also no coherent national policy on
how the XO should be integrated into the curriculum,
every school had its own policy and a variation of its
implementation. It was observed that the integration of
the OLPC XO1 into the school curriculum was
influencedbyTeacher’s
motivation,schooladministrator leadership, and methodologist leadership.
In terms of the impact of the OLPC initiative inMongolia, student learning achievement scores indicate
positive results. However, the low 𝑅 ! indicates otherfactors to predict test scores are not present in themodel, and thus further investigation is required. On
the qualitative side, there are many interesting findings
from the teachers that should be used as areas to further
validate in future studies. The stakeholders who took
part in this study strongly believe in the positive effectof the OLPC program. The positive effects, which
include communication skills and creativity, are notmeasurable by student learning achievement tests.

On the other hand, the study also found there are
multiple challenges that teachers, parents, and school
administrators face, in planning and implementing
OLPC initiatives at school level, including financial
implications for the parents.
This research concludes that there is an impact inseveral areas but it is not generalizable in entire
Mongolia, and thus, needs to be further studied.

References[1] Angrist, J., & Lavy, V. (2002). New Evidence onClassroom Computers and Pupil Learning. The
Economic Journal, 1–32.
[2] Barrera-Osorio, F., & Linden, L. L. (2009). The
Use and Misuse of Computers in Education.
Policy Research Working Paper, 1–43.
[3] Bhatta, S. D. (2008). Tackling the problems of
quality and disparity in Nepal’s school education:
The OLPC model. Studies in Nepali History andSociety, 11(1), 00–00.
[4] Cristia, J., Ibarrarán, P., Cueto, S., & Santiago, A.
(2012). Technology and Child Development:
Evidence from the One Laptop Per Child
Program. IZA Discussion Paper Series, (No.
6401), 1–43.
[5] Hourcade, J. P., Beitler, D., Cormenzana, F., &Flores, P. (2008). Early OLPC Experiences in a
Rural Uruguayan School. CHI Proceedings, 2503–
2512.
[6] Institute of Education Sciences, Dynarski, M.,
Agodini, R., Heaviside, S., Novak, T.,
Campuzano, L., et al. (2007). Effectiveness of
Reading and Mathematics Software Products (No.
2007-4005). U.S. Department of Education.
[7] James, J. (2010). New Technology in Developing
Countries: A Critique of the One-Laptop-PerChild Program. Social Science Computer Review,
28(3), 381–390. doi:10.1177/0894439309346398[8] Mitra, S. (2006). The Hole in the Wall. New York.
[9] Negroponte, N. (1996). Being Digital. Vintage
Books.
[10] One Laptop Per Child. (2011, October). One
Laptop Per Child Deployments. Retrieved January
22, 2014, fromhttp://www.laptop.org/en/children/countries/[11] Papert, S. (1980). Mindstorms: Children,
computers, and powerful ideas. Basic Books, Inc.
[12] Embassy of Mongolia, Washington, D.C.. (2007)
President N. Enkhbayar's Official Visit to theUnited States. Retrieved July 17, 2013, fromhttp://www.mongolianembassy.us/mongolia_and_usa/mongolian_presidents_visit_to_us.php[13] Trucano, M. (2005). Knowledge Maps: ICT in
Education. Washington, DC: infoDev / The WorldBank.
[14] Trucano, M. (2013). Mobile learning andtextbooks of the future, e-reading and edtech
policies: Trends in Technology Use in Educationin Developing Countries. The World Bank.

6. Conclusion
Seymour Papert’s idea of designing computers so thatlearning to communicate with it as a natural processthat facilitated learning drove the creation of One
Laptop Per Child initiative. Mongolia is one of 54
countries around the world with OLPC XO1 laptops
deployed with the hopes to improve education.
This research studied the impact of the OLPC
initiative in Mongolia from multiple perspectives,
looking at learning achievement scores, computer
attitude measures, perspectives of children and thedifferent stakeholders.
The implementation of the OLPC initiative inMongolia started with a PMU overseeing the entire
deployment but later moved towards a model where theschool would be the center with its own policies andsources of support for the program. Each school had adifferent implementation because of a variety of factors
such as school’s leadership, access to resources,
proximity to UB, support of the community, andteacher’s ability to implement.
Student learning achievement scores indicate thatstudents with an OLPC computer can score higher forboth math and reading. While it is indicated that there
are some gains, these cannot be generalized for theentire case of Mongolia as it did not pass some of therigors of randomized control tests. Computer attitude
measure on paired schools found rural schools all
exhibited statistical differences in the averagecomputer disposition of 5th grade students, whereas
urban schools, with the exception of the one located at
the periphery, exhibited similar average computer
disposition.
Interviews and focus group discussions with 68
stakeholders found that the OLPC was a positive
experience for children, teachers, parents, and thecommunity. The different stakeholders believe thatchildren have learned computer literacy and typing
skills, and it is also able to foster creativity,communication, and independence.

52

DEA Evaluation of Agriculture and Industry Water Use Efficiencies in China
Student Number: 12M18198 Name: Lu Gao Supervisor: Naoya Abe
包絡分析法を用いた中国における農業用水と工業用水の利用効率性評価
Water shortage is becoming one of the most crucial issues in China because of the rapid increasing water demand for
economic development. In order to propose an appropriate policy, we mainly need to work on the two problems: firstfinding in the evident how much the value of agricultural and industrial water use efficiencies are in each target regionand second identifying the factors affecting agricultural and industrial water use efficiencies. The data envelopment
analysis (DEA) is adopted to measure the agriculture and industry water use efficiencies. We also identify the dominantfactors affecting water use efficiencies by the Tobit model.

1. Introduction
Water shortage has become a crucial issue in China
because of the rapidly growing population. At present,
61.3% of water is used for agriculture, which accounts
for only 8.9% of GDP, and China’s water use efficiency
is lower than that of developed countries(3). Because
industrial output has increasingly become much more
profitable than agricultural output, water resources arebeing transferred to industry, which affects agricultural
production. For this reason, increasing water use
efficiency is an important issue for China.
In order to solve this problem, the Chinese
government has initiated a number of projects, such astransferring water from agriculture to industry in watersaving irrigation in Ningxia and Inner Mongolia since2003. In this study, Ningxia, Inner Mongolia, andGansu provinces are selected to evaluate whether watertransfer projects affect water use efficiency in eachregion. Data envelopment analysis (DEA) is adopted tomeasure the agriculture and industry water use
efficiencies. We also identify the dominant factors
affecting water use efficiencies by the Tobit model.
2. Methodology

Max  k ( ,  )1 y1k   2 y 2 k     s y sk
 1 x1k  2 x 2k    m x mk(1)

1 y1 j  2 y2 j    s ysj
 1 j  1,2,n 1x1 j   2 x2 j     m xmj(2)

Subject to1, 2 ,, m  0(3)

1, 2 ,, s  0(4)

The ( * ,  * ) obtained as an optimal solution for FP
results in a set of optimal weights for DMUk .  i* is
the optimal weight of the input item i and  r* is the
optimal weight of the output item j . The ratio scale isevaluated bys k* 

 r* yrk

r 1

(5)

m



i 1

*
i xik

The DEA defines three different forms of efficiency:
technical efficiency (TE), pure technical efficiency(PTE), and scale efficiency (SE). Table 1 explains thethree efficiencies.

2.1. Data Envelopment Analysis

Table 1. DEA efficiencies and their explanations

2.1.1. Conventional DEA Model
We adopt DEA to analyze water use efficiency. Thisapproach is used to measure the relative efficiency ofhomogenous units called decision making unit (DMU).
The efficiency of each DMU is the ratio of the sum of
weighted outputs to the sum of weighted inputs; thisvalue is never greater than 1. If the efficiency is 1, itmeans that the DMU is efficient; otherwise, it isinefficient.
The input-oriented model of the Charnes, Cooper, andRhodes (CCR) model was chosen in this study. We use
fractional programming (FP), as shown in equations 1–
4, to obtain values for the input weights (  i ,
i=1,2,…,m) and output weights (  r , j=1,2,…,m) of
DMUk to obtain the maximum efficiency of DMUk
( max  k )(9).

Concept

Explanation

DetailPTE

The conversion of physical For the current technical level,
inputs into outputs relative to the inputs are completely
the best practiceutilized.

SE

For a given level of output,
Indicats whether the scale of
inputs are chosen to minimize
production is overlarge or small
the cost of productionTE

Is technically efficient if it is
The conbination of pureboth technically pure and scaletechnical and scale efficiency.
efficient.

2.1.2 SE–DEA
The conventional DEA model leaves all efficient units
with a unity score and thus does not allow the rankingof the efficient units themselves. An extended DEA
model provides a procedure for ranking them bycomparing the units under evaluation with a linear
combination of other units in the sample. The unit
obtained in this case an efficiency score above 1. The
score reflects the radial distance from the DMU under153

evaluation to the production frontier estimated with the
DMU excluded from the sample.
The model is identical to the conventional BBC model
except that the unit evaluation is not included in thereference set. (5) The programming problem equation is
given byprovinces have more people work in agriculture than in
any other industry. In each of these three provinces,more than 74% of water is used for agriculture; inNingxia, over 90% of water is used for agriculture,
which comprises only 11% of the GDP(2).

min 𝐸𝑗 − 𝛿𝑒 ′ 𝑠 − − 𝛿𝑒 ′ 𝑠 ++s. t. 𝐸𝑗 𝑋𝑗 = ∑𝑚
𝑘=1 𝑧𝑘 𝑋𝑘 + 𝑠 ,𝑘≠𝑗

𝑌𝑗 = ∑𝑠𝑘=1 𝑧𝑘 𝑌𝑘 − 𝑠 − ,

(6)

𝑘≠𝑗

𝑧, 𝑠 + , 𝑠 − ≥ 0{

where 𝑋𝑗 is an m-dimensional input vector, 𝑌𝑗 is an sdimensional output vector for the jth unit, 𝐸𝑗 is ascalar defining the share of the jth DMU input vector
within the reference technology, Z is an intensity vector
in which 𝑧𝑘 denotes the intensity of the kth unit, 𝛿 isa non-Archimedian infinitesimal, and 𝑒 ′ is the row
vector (1,…,1) of the appropriate dimension.
Once the efficient frontier is determined, inefficient
DMUs can improve their performance to reach theefficient frontier by either increasing their current
output levels or decreasing their current input levels.
However, both desirable (good) and undesirable (bad)factors may be present. For example, if inefficiency
exists in production processes where final products are
manufactured with a production of wastes andpollutants, the outputs of waste and pollutants are
undesirable and should be reduced to improve
performance. This paper will use the data translation
invariance property of the DEA to improve
performance. (1)(2)(6)2.2. Tobit Model
After the evaluation of water use efficiency, the next
step is to determine the influence factors. Some similar
studies(4) use a Tobit model to estimate a second-stage
relation between the efficiency related influential
factors, which is expressed by equations 7 and 8.
(7)
 k*  Z   k* if 0   k*  1 k  0 if  k*  0
1 if  *  1kFigure 1. Map of China

3.2. Input and Output for the DEA Model
For the purpose of agricultural water use efficiency
analysis, the input is the volume of agricultural watertaken from water resources, and the output includes thegross output value of agriculture, forestry, animalhusbandry, fishery, and the net income of rural
households. For industry water use efficiency analysis,
the input is the volume of industrial water taken fromwater resources, and the output is aggregated into two
categories: industry value-added and wastewater
discharged by industry.
3.3. Determinant Factors for the Tobit Model
The Tobit model is adopted to identify the determinantfactors. Following the previous literature and theories
associated with water use efficiency, the main elementsthat affect water use efficiency are given in Tables 2
and 3.
Table 2. Explanation of the involved variables(Agricultural water use efficiency)

(8)

 k*

where
is the DEA efficiency score of DMUk forwater use as a dependent variable and Z is a vector of
the independent variable.  is the vector and  isthe error term vector.(10)3. Data Collection
3.1. Scope of StudyIn this study, 31 areas in Ningxia (5 areas), Inner
Mongolia (12 areas), and Gansu (14 areas) were used
to calculate the DMU for each area (Figure 1).
In China, Ningxia and Gansu have the third- and fifthsmallest GDP by province, respectively, and Inner
Mongolia has the fifteenth-largest GDP. These three

NaturalSystemSocialSystem2
54

Variablename
Water
Endowment
NaturalConditions
EconomyLevel
Industrial
Structure
PolicyMarketOpenness

Variable definition

Unit

Water resource
capacity per capita

m3 /person

Precipitation
Ln (GDP per capita)

100 million
c.m.
Yuan/
PersonPrimary Industry/GDP%

Water right trade

0 or 1
100 million
dollars

Foreign tradeTable 3. Explanation of the involved variables(Industry water use efficiency)

NaturalSystemSocialSystemvalues for 2008–2011 are 0.298, 0.479, 0.453, and0.259 respectively. The results show that industry water
use TE values in the target areas during the research
period are relatively low on the whole. Gannan is at a
DEA-efficient level for most years. Guyuan, Baotuou,
Erdos, and Qingyang reached the DEA efficiency levelfor one year during the research period. However, mostareas were DEA-inefficient during the research period.
The average annual TE, PTE, and SE values of industry
water use for each province are summarized in Figure
3. As the results show, PTE has more influence than SE
on TE in Ningxia, Inner Mongolia, and Gansu. Thismeans that water resources were used extravagantly inall provinces.

Variable
Variable definition
Unit
name
Water
Water resource
m3 /person
Endowment
capacity per capita
EconomyYuan/
Ln (GDP per capita)
Level
PersonIndustrial
Secondary%
Structure
Industry/GDP
Water Price Industrial use water fee Yuan/c.m.
Fixed Asset
Urban faxed asset
100 million
Investment
investment
yuan
PolicyWater right trade
0 or 1Market
100 million
Foreign trade
Opennessdollars

4. Results
4.1 Water Use Efficiency
The DEA model is estimated using the model program
Deap 2.1 under the assumption of variable returns toscale (VRS). The agricultural water use technicalefficiency (TE) values in the target areas during 2008–2011 are relatively low as a whole, with average annual
values of 0.284, 0.342, 0.353, and 0.272, respectively.
In all of the target area, Jiayuguan and Gannan were at
DEA-efficient levels for most years. However, mostareas were DEA-inefficient during the research period.
The average annual TE, PTE, and SE values ofagricultural water use for each province aresummarized in Figure 2. The results show that PTE has
more influence on TE in Ningxia and Gansu, whereas
SE has more influence on TE in Inner Mongolia. Basedon the input-orientated DEA, the results show that there
is water overabundance in the agricultural productionof Ningxia and Gansu. In contrast, the agricultural
production scale is overlarge in Inner Mongolia.

Figure 3. Industry water use efficiency in eachprovince (TE, PTE, and SE).

4.2 Determinant Factor Results
The Tobit model is estimated using the model program
Stata 12 for 31 areas. The estimated results for the six
models showed incomplete consistency (Table 4).
Table 4. Agricultural Tobit model results
Independent
variable

Model 1

EconomyLevel*-0.0765

Industrial
Structure

Model 2Model 3Model 40.0024MarketOpenness**-0.0600

Model 5Model 6-0.0966-0.0687*-0.0127-0.0118****-0.1021-0.0976***-0.2715

Policy*-0.1251

Water
Endowment-0.0684-0.0594*-0.0909

NaturalConditions**
0.0007**0.0006*****0.00090.0006******0.00110.0011

Constant**
1.4458*0.5613*****1.30470.6480****2.96632.6255-0.0578*-0.0939-0.0911*

Note: (1)Robust estimates are used to eliminate data
heteroscedasticity.
(2)***indicates a 99% significance level, ** a 95% significance level,* a 90% significance level.

Figure 2. Agricultural water use efficiency in eachprovince (TE, PTE, and SE)

The results show that the natural conditions

The average annual industry water use efficiency
355

variable—that is, rainfall—was significant andpositively influenced agricultural water use efficiency
in the six models. Generally, natural conditions greatly
affected agricultural production. The market openness
variable showed a significantly negative influence on
agricultural water use efficiency in models 3, 5, and 6.
The negative coefficients imply that the export benefits
exceed the production cost, which motivates people touse more water. According to conventional views,
economic development level significantly influences
water use efficiency. In this paper, this conclusion iscalled into question by the estimated results for models
5 and 6. In these models, the EL was not significant.
Perhaps the better economy did not bring advanced
technology of agriculture production. The test
significance of the variable policy also was inconsistent
between models 4 and 6. For the society–economy
system, the regression result of policy was significant(model 4). Because water right transfers may make itpossible for farmers to compensate for their losses,
farmers may lose the motivation to improve water use
efficiency.
As shown in Table 5, the estimated coefficients of the
11 models showed inconsistency.

models 7–9. The increase of investment in fixed assets
indicates that advanced equipment and facilities are
employed to utilize water for production.
5. Conclusions and Suggestions
This study showed that agricultural and industrial water
use in the study area fail to reach overall technicalefficiency levels, as both agricultural and industrial
water use efficiency were at relatively low levels. PTE
has a more significant impact on TE than SE does. For
the determinants of agricultural water use efficiency,
economic development level, agricultural industry
structure, policy, and water endowment significantly
influenced agricultural water use efficiency in somemodels. In addition, market openness and natural
conditions were consistently significant. For thedeterminants of industrial water use efficiency, urban
fixed asset investment, market openness and water
price significantly influenced industrial water use
efficiency. In order to improve water use efficiency, thisstudy proposes the following policy recommendations.
1. Develop modern agriculture: utilize advanced
agricultural technology, adopt drop irrigation, anddevelop agri-corporations. 2. Use advanced watersaving equipment and facilities and improve water use
technology. 3. Improve the water price mechanism.

Table 5. Industry Tobit model results
Independent
M1
variable
Economy
Level

M2

M3

M4

M6

M7

M8

*

0.07

Industrial
Structure

0.122 0.13

M10

M11

References1.

Agha IQBAL ALI, Lawrence M.SEIFORD, 1990,
Translation Invariance in Data Envelopment Analysis,
Operations Research Letters, 11, pp. 403–405.
2. Lawrence M. Seiford, Joe Zhu, 2002, Modelingundesirable factors in efficiency evaluation, European
Journal of Operational Research, 142, pp. 16–20.
3. National Bureau of Statistics of China. (2011). CHINASTATISTICAL YEARBOOK. 12(17), Beijing INFO
Press.
4. Onishi A, Sato Y, Shi F, Han J, Morisugi M, Watanabe
T, Fukushima, Y. 2009. Evaluation of Regional
Difference of Agricultural Water Use Efficiency inChina. J. Japan Soc. Hydrol. and Water Resour., 22(5),356–371.
5. Per Andersen , Niels Christian Petersen,1993, A
Procedure for Ranking Efficient Units in Data
Envelopment
Analysis,
Management
Science,39(10),pp:1261-1264.
6. Rolf Fare, Shawna Grosskopf, 2004, Modelingundesirable factors in efficiency evaluation: Comment,
157, pp. 242–245
7. Stihn Speelman, Marijke D’Haese, Jeroen Buysse, Luc
D’Haese. A measure for the efficiency of water use andits determinants, a case study of small-scale irrigation
schemes in North-West Province, South Africa.
Agricultural Systems, 2008, 98:31–39.
8. T. Yaghi, A. Arslan, F. Naoum, 2013, Cucumber(Cucumis sativus, L.) water use efficiency (WUE) underplastic mulch and drip irrigation [J], Agricultural Water
Management, 128, pp. 149–157.
9. William W. Cooper, Lawrence M. Seiford, Kaoru Tone,
2007, Data Envelopment Analysis, Springer, NY, p. xix.
10. Wooldridge, Jeffrey. 2002. Econometric Analysis of
Cross Section and Panel Data. Cambridge: MIT Press.

MarketOpenness*
0.003 0.049 0.051-0.04* -0.05 0.128 -0.04 -0.04

-0.01

Price
Policy0.123*

0.109 0.109
0.068

0

**

0.003 -0.05 6E-04 6E-04

6E-04

Water
0.01
Endowment

M90.012 0.012 0.017

0.04

Fixed Asset
Investment

Constant

M50.009 0.006

-0

-0.03

0.012 -0.01 0.005 0.006 -0.01 -0.01

0.02 0.07 0.401 0.499 0.41** 0.402 0.206 0.102 0.009 0.385 0.345

Note: (1)Robust estimates are used to eliminate data heteroscedasticity.
(2)***indicates a 99% significance level, ** a 95% significance level, * a 90%
significance level.

The estimated coefficients of the economic
development level, fixed asset investment, and water
price were positive. The estimated coefficient ofindustry structure was positive except for model 9. The
variable market openness was the opposite. The
estimated policy coefficient did not show identity
between models 6 and 11. The estimated coefficients ofwater endowment were inconsistent in all the models.
Among the variables, the estimated coefficients ofwater price and market openness were significant at the
10% significance level in model 5 and model 7,
respectively. The water price mechanism definitely
affected water use efficiency. In addition, a moremarket openness will lead to stronger competition
production. Furthermore, urban fixed asset investment
significantly influenced industry water use efficiency in
456

ESTIMATING DIRECT AND INDIRECT CO2 EMISSIONSOF AUTOMOTIVE MANUFACTURING SUPPLY CHAIN
IN CHINA
Student Number: 12M18229

Name: Yun GU

Supervisor: Shinya HANAOKA

中国における自動車産業サプライチェーンの直接・間接CO2排出量の将来推定
谷蘊

本研究では、中国の自動車メーカーの生産・輸送・使用段階における乗用車一台当たりの直接・間接CO2
排出量を、サプライチェーン全体を考慮して算出した。サプライヤーへのインタビュー調査により輸送機
関や調達情報を確認し、現状の排出量を推計した。次に排出量削減シナリオを設定して推計したところ、使用段階の排出量が最も大きく、低公害車の普及や燃費改良が有効なことを明らかにした。また、石炭発電量の削減や鉄道輸送普及により、生産と輸送段階の排出量が同時に削減できることを示した。

calculate related data on GHG emissions. In addition,
Chinese companies have been asked to share their GHG
emissions information by foreign companies.
Looking at automotive manufacturing in China, morethan 120 automobile companies and 2000 automobile partfactories have been established in recent years. However,
the merging and acquisitions of manufacturers with eachother or with foreign manufacturers brings difficulty ingetting the accurate data. Along with the problems ofimitation of foreign car design and securities, several
manufacturers shut down or transfer their website andeven have their name changed. Many researches on estimation of CO2 emissions in supply chain were conducted by using input-output table which can only makean average estimation, for example, an average estimationof all parts production in production phase. With the urgency of knowing the emissions of automotive manufacturing in China, and making a more accurate result, theresearch objectives are set as the followings:
1) To calculate the CO2 emissions from automotive
manufacturing in China based on the supply chain of both
direct and indirect emissions.
2) To make CO2 emissions reduction scenarios based on
the present situation in China, and clarify the most efficiency way of reducing CO2 emissions by comparing
scenarios and current results.

1. Introduction
CO2 emission reduction is one of the biggest issues in
the world. Eighty percent of world’s CO2 emission comesfrom energy and heat, transportation and industry sector.
Fossil fuel combustion generates a high emission in theworld. China has been the largest CO2 emission country
since 2010. The role of CO2 reduction in China, which
relies on thermal power generation, has become more
important. An automotive manufacturing, in particular,emits a large amount of CO2 on its supply chain, as shownin Table 1.
Table1. Automotive manufacturing and CO2 emissions
Step
Content
Emission sector
Production ofEnergy andparts andFossil fuelcompletecombustion
electricity
vehiclesTransportation Delivery from supof parts andplier to manufacture Gasoline orcompleteand from manufac- other fuelsvehiclesture to dealer
Use of vehiGasoline orRun a carclesother fuelEnd-of-life
Recycle and disFossil fuelvehiclespose
combustion
Automotive manufacturing occupies an important position in China manufacturing industry. The production andsales of automobile became number one in the world in2009. However, the retain volume per thousand people in
China is still 71, about half of the average retain volume
per thousand people compared with developed countries.
Purchasing power as well as demand for vehicles will
increase along with an increase in economic growth andpopulation number. Automobile sales will therefore increase significantly in China. It is certain that this would
negatively affect the environment due to more CO2
emissions from the manufacturing process.
According to Greenhouse Gas (GHG) protocol many
companies and organizations have taken action in calculating and reporting GHG emissions while there are few
Chinese companies that do so. Chinese companies are
reluctant to announce their information to the public,
which makes it difficult for third party to collect and2. Estimation Method
2-1. Study Boundary
According to GHG protocol, scopes of emission are
defined into three categories. Combine the situation of
automotive manufacturing, the boundary of this researchis:1) Direct CO2 emissions – Direct emissions are generated
from electricity, steam or heat in equipment that is owned
by assembly plant when producing complete vehicles.
2) Indirect CO2 emissions – Indirect emissions are generated from consumption of purchased electricity, naturalgas, steam or heat that is not owned by assembly plant.
For example, emissions from suppliers by producing parts.
Relevant emissions from delivery of parts and complete
vehicles, the use of vehicles and dispose stage are also
considered as indirect emissions.

57

By considering locations and transportation modes ofsuppliers, the emission estimation might be more accurate.

Where: Ep and Ea is CO2 emissions from suppliers andassembly plant on production process, respectively, gn andg are electricity use ratio in China. f is emission factor. n is
the number of supplier.

2-2. Data
2-3-2. Transportation Phase

To estimate the direct CO2 emissions, we need input
energy data of complete vehicles production phase.
To estimate indirect CO2 emissions, we need the data ofelectricity used in assembly plants, and energy used insuppliers during making parts in production phase. Dataon total travelling distance and mode of transport (road,rail, maritime etc.) should be collected in transportation
phase. In addition, data of total distance traveled by avehicle also need to be considered in indirect emissions.
By comparing all automobile companies in China,
Shanghai Automotive Industry Corporation (SAIC) has
the largest share of production and sales, especially its
branch company, Shanghai Volkswagen Automotive Co.
(SVW). Considering the complex environment of automobile companies in China, one vehicle model (Lavida) is
chosen as a representative in the research target considering data availability. Further, due to data unavailability,
Life Cycle Assessment Society of Japan (JLCA) database(Japanese vehicle data) was used instead of Chinese database in production phase and transportation phase.

Calculation of this part is divided into road transportation and railway/maritime transportation. Road transportation is calculated by improved tonnage method while
railway and maritime transportation are calculated bytonnage method. These calculations are made by estimation tool of the Policy Research Institute for Land, Infrastructure, Transport and Tourism (PRILIT). This tool wasestablished under Ministry of Land, Infrastructure,
Transport and Tourism (MLIT) of Japan. Equations arefollowings.
Road transportation for parts:⁄(3)

Land transportation for complete vehicles:⁄(4)

Railway and maritime transportation for complete vehicles:(5)

Table2. Comparison of Lavida and JLCA database modelType
4 door sedan
4 door sedan
Weight[kg]
1265
1037
Displacement[cc]
1598
1500

(6)
Where: Ei and Ec are CO2 emissions from truck by suppliers and assembly plant. ER and EM are CO2 emissions
from railway and maritime by assembly plant deliver todealers. d is distance. Wi and W are the weight of parts andone complete vehicle. C is fuel use ratio basic unit. H isheat generation per unit. F is emission coefficient. FR and
FM are emission factors. u and q are number of unit andnumber of complete vehicles.
Since there are all 876 dealers considered in this research, emissions of complete vehicles transportation
phase from assembly plant to dealers can be calculated asfollows:∑∑oror

There is no supplier list of SVW in manufacturing
Lavida. By collecting supplier from reference materials,
checking each part of suppliers producing and considering
the distance of suppliers to assembly plant, a brief supplier list has been made. To ensure the accuracy of list,
telephone interviews were directly done by asking suppliers’ provider and method of delivery. After ensuringlocation of suppliers, distances between suppliers andassembly plant were measured by considering road traffic
situation.
Dealers are found in the website of SVW. It shows
number of dealers in each province in China. However, it
was not clear whether the dealers deliver directly fromassembly plant or not. By interviewing dealers directly,
the method they use in transportation was then identified.
For land transportation, Google map was used in distancemeasurement, while in railway and maritime part, distance information between each station was found in theirofficial websites.
In use phase, the official fuel consumption is muchsmaller than the actual voting in the website. When considering reality, the bigger value is chosen for the research.

∑(7)
Where: ED is CO2 emissions from assembly plant todealers on transportation process. S is number of dealers
in each province.

2-3-3. Use Phase
Equation in use phase is as follow.
(8)
Where: Eu is CO2 emissions in use phase. d is average
distance of one vehicle until life end. e is fuel consumption. f’ is emission factor by gasoline.

3. Results
3-1. Present Emissions

2-3. Methodology
2-3-1. Production Phase

From the interviews of suppliers and dealers, it is foundout that road transportation is the most fundamental anddominating transportation mode. This is because of its
low cost and availability of door to door service. Even
though distance is more than 500km from assembly plant,

Emissions from suppliers and emissions from assemblyplant can be calculated based on Equation (1) and (2).
∑
(1)
(2)

58

they prefer to use trailers than railway or shipping. Resultsof CO2 emissions on supply chain of one vehicle in thisresearch are shown in Table3. Use phase has the highest
emissions among all stages. It shows urgency in reducing
emissions on use phase.
Table 3 Current CO2 emissions (t- CO2/vehicle)
Production
Transportation
Parts
ComParts
Completeplete
vehiclevehicleUse
Total
0.2788 0.6361
0.00760.88070.92
0.89 49.92 51.73

railway infrastructure development is expected to increasein the future, the use ratio of railway is expected to increase too. This refers to d) Railway transportation in
Figure1. Because of the emission factor of railway ismuch lower than truck and trailer, the reduction of CO 2
emissions could be forecasted. In this scenario, we set
transportation mode as railway in the case when transportation distance is larger than 300km.
a) Energy composition×d) Railway transportation
Furthermore, a combination of energy composition andrailway transportation can be considered as one of the
scenarios (point a)×d) in Figure 1). This can not only
effect transportation phase, but also production phase of
CO2 emissions.

3-2. Scenario Building
From the results above and the equations in calculation,
there are some factors that might affect CO2 emissions.
Besides fixed factors like distance and weight, other factors such as emission factors of electricity and fuel consumption might change results of emissions. In addition,
results also rely on transportation modes because theemission factors are different. Therefore, several scenarios are considered, as shown in Figure 1.

a) Energy
composition

Production phaseb) CleanvehiclesTransportation
phasec) Fuel consumption

Use phased) Railway transportation

End of lifee) Location ofassembly plantii. Technical Improvement Scenarioc) Fuel consumption
SVW aims to reduce their fuel consumption on vehicles
to 0.049L/km, while the current fuel consumption ofLavida is 0.09L/km. Infrastructures and traffic situations
affect fuel consumption in reality. In this scenario, we use
official fuel consumption in calculation without thinkingof real traffic situations. This refers to c) Fuel consumption in Figure1.

energyiii. West Development Scenarioe) Location of assembly plant×d) Railway transportation
Due to high cost of labor, market saturation and environmental degradation, more companies move to the
mid-west China for development. Chinese government
provides preferential policies in taxation to attract morecompanies to develop west side of China. In fact, SVW
has made a new assembly plant in Xinjiang located inwest of China to expand production.
Based on the consideration of the local resources,
market share, as well as cost of labor, Yunnan province ischosen in this scenario as a new assembly plant. In addition, the railway connect Yunnan to Singapore is expected
to be built in 2030; it will be more convenient for complete vehicles export through Yunnan. By considering thecurrent location and situation of dealers, we can supposethat the new assembly plant will be built in Yunnan in
2020. Under the high use ratio of railway on transportation, CO2 emissions might change in this case, whichshows in Figure1 e)×d).

Figure1. Scenarios consideredi. Environmental Protection Scenarioa) Energy composition
This scenario is based on changes in emission factor ofelectricity generation. Emission factor of electricity generation in China plays an important role in production,transportation and use phase. For example, reduction ofcoal in energy consumption can make emission factor ofelectricity become much lower. Under the policy on expanding the use of natural gas, this scenario is considered
as a) in Figure 1. In order to make comparison, electricity
generation scenarios made by Low Carbon Asia research
project are used in this research to estimate emissions in
2050 of both business as usual and mitigation results.
b) Clean energy vehicles
Another way of protecting environment is the popularization of a new energy car. This shows b) Clean energy
vehicles in Figure 1. By 2020 mild hybrid & full hybridcars are estimated to have more than 50% share of total
sales of passenger vehicles in China.
d) Railway transportation
In transportation phase, the use ratio of trailers is currently high in complete vehicle transportation according
to interviews. Currently there are no relevant laws andregulations to guide utilization of trailers. Dealers areused to overload the trailers. However, since freight3-3. Results of Scenario Analysis
The results of scenarios are shown in Figure 2.

i-a) In this scenario, by changing the a) Energy composition, all stages of supply chain will be affected.
From the results, we can find that by changing the electricity generation, emission from the use phase is reduced
significantly. Natural gas fuel emits fewer emissions thangasoline. Emission reduction on production phase ishigher than on transportation phase, which shows energy
composition plays significant role in production phase.
i-b) In this scenario, fuel consumption in use phase ischanged from gasoline to fuel used by hybrid car.

59

More than half of the emissions will be reduced by using
hybrid car instead of current passenger vehicle. Although
the result only changed in use phase, it shows that it isimportant to generalize clean energy vehicles in China inorder to reduce CO2 emissions in automotive manufacturing.

if all suppliers are identified and utilized in calculation,
the emissions from production and transportation phases
still cannot reach the emissions as high as in use phase.
Furthermore, by comparing with Japanese vehicles, theemission in use phase in Chinese case is more than 7 times
larger of Japanese case. There are two reasons considered:(1) the vehicle total travel distance is 2.5 times more thanJapanese one, and (2) the fuel consumption of Chinese
vehicle is 3.2 times more than Japanese one. However, of
all life cycle, use phase has the greatest emission share ofboth countries’ automotive manufacturing.
From both the current results and scenario analysis, we
can identify that the more efficient way to reduce CO2
emissions is by reducing the use phase emissions. Bychanging the mode in transportation phase can also lead toan emission reduction, even though the reduction is relatively small. Compared to changing energy composition,
popularization of clean energy car is considered more
effective in reducing CO2 emission. However, the emissions will not be much reduced in case that the energy
composition is not changed because clean energy cars use
electricity as fuel.
Moreover, the traffic congestion situation should also be
considered in this issue, since the CO2 emissions are verymuch dependent on the fuel consumption of vehicle speed
in the use phase. Without reasonable urban planning andvehicle purchase policy, the CO2 emission reduction will
not be completely effective.

i-d) By using railway on complete vehicles delivery, theCO2 emission on transportation phase can be reduced
significantly. Although the total emission is still high, theexpansion railway transportation can still be consideredmeaningful.
i-a)×d) Combine changes on energy composition, andtransportation mode to railway.
Reductions of emission on transportation phase are
now higher than on production phase. This means thatusing railway on transportation is more significant compared to only changing the energy composition on transportation stage. In general, emission reduction of a) islarger than d), because use phase still has a biggest emissions on whole supply chain.

ii-c) The aim of this scenario is to reduce CO2 emissionsin use phase by reducing the fuel consumption. We assume that there is no change in production and transportation phase.
In use phase, the reduction is almost half of current
emissions. The scenario shows changes in use phase hasvery effective result in CO2 emissions reduction.

8

t-CO2/vehicletransportation
total reduction

67%

7iii-e)×d) In this scenario, we consider that the locationof the assembly plant is moved to Yunnan. Therefore, thetransportation distance will also be changed. To makesome assumptions on this scenario: firstly, the distance ofdealers to assembly plant is between each railway stationof provinces city; secondly, the method of transportation
is by railway only; finally, the scenario only on transportation stage.
From this result, it is clear that by transferring the assembly plant to West China and by using railway astransportation, CO2 emissions will be reduced.
Because of lack of data, on this scenario there are a lotof assumptions. In order to get more accurate result, thedata need be reconsidered.

productionuse(t/10)

80%
70%

6

60%
46%

5

50%

4

40%

3

22%

30%

23%

2
1

20%

3%

3%

0

10%
0%

current
resulta)i. Environmental
Protection Scenario

b)

d)

a)×d)

c)

e)×d)

iii. West Develop
ii. Technical
Improvement Scenario ment Scenario

Figure2. Results of comparisons of scenarios(For ease of comparison among the stages, to set unit ofuse as t/10)

4. Conclusions and Discussions
This research calculated CO2 emissions on automotive
supply chain of one vehicle by considering locations ofeach supplier. This method may estimate more accurate
results than input-output table. By identifying the suppliers, companies can get accurate emission data, and also
can quickly take actions when problems happened withthe suppliers.
By calculating the direct and indirect CO2 emissions on
supply chain of automotive manufacturing in China, wefound out that the emission in use phase is much larger
than any other two phases, takes about 96% share of CO2
emissions in all phases. About 80% of real suppliers areused in this research due to data limitation. However, even

References[1] 国土交通政策研究所：物流から生じる CO2 排出量に関する手引き，国土交通政策研究第 105 号，2012．
[2] Wang Shoubing el al.: Life cycle inventory of a China Car, Journal of
Fudan University (Natural Science), 45(3), 2006.(in Chinese)[3] 林寧他：産業連関表を用いた中国における経済発展と二酸化炭素排出に関する研究，Journal of Life Cycle Assessment, Japan,
6(4), 2010．
[4] 湯進：中国自動車産業のキャッチアップ工業化，専修大学社
会科学年報第 45 号，pp.109-127, 2011．
[5] 李景明他：中国新能源資源潜力及前景展望，天然气工业，28(1),pp.149-153, 2008．
[6] 丹治和男：中国におけるアフターマーケットの動向，Roland
Berger Strategy Consultants, Vol.10, 2003.

60

CLARIFICATION OF AGRICULTURAL PRODUCTS SUPPLY CHAIN STRUCTURE, INCLUDING
TRASPORTATION MODE CHOICE IN VIETNAM
Student Number: 12M18235

Name: Van Hung CHU

Supervisor: Shinya HANAOKA

ベトナムにおける輸送機関選択を含めた農産物サプライチェーン構造の実態解明
チューバンフン
本研究は、ベトナムの主要農作物である米とそれを用いた加工食品を対象に、輸送機関選択を含めたサプライチェーン構造の実態を現地調査により解明することを目的とする。農家、集荷業者、代理店等の各アクター間の輸送量シェア、輸送機関分担率を算出し、距離別輸送機関分担率の違い、生産地と消費地で利用する輸送機関の違いを明らかにした。また、現状のサプライチェーンには多くのアクターが存在するという問題点とその原因を指摘した。
the supply chain. Vo, et al.[4] drew up the rice supply
chain in the Mekong River Delta. This research only
showed transportation volume share between eachactor, but there was no information about modal sharebetween each pair of actors in supply chain. This
research also did not consider processed food asimportant actor.
The objective of this study is to clarify the realsituation of supply chain structure, including themodal share of agricultural products and processed
foods in Vietnam. In specific, 1) Clarify actual
situation of supply chain, especially focus on rice andconsider processed food as important actor. 2)
Estimate transportation share and modal sharebetween each actor in supply chain. 3) Identify
problems of supply chain structure.

1 Introduction
Vietnam is a developing country and its economy ishighly dependent on agriculture. 48.4% of total
employees are engaged in agriculture, forestry andfishery in 2011[1]. Rice plays an important role in theeconomy of Vietnam because of the production
volume (i.e. the largest among agricultural products)
and workers (i.e. production, transportation, sales andthe other sectors of rice).
Market size of processed food has been expandingat 17% annual rate in recent years [2]. In Vietnam, bothtraditional retail stores and modern retail stores (i.e.
convenience stores, supermarkets, and hypermarkets)
do exist. A number of modern retail stores are growing
23.7% annually while traditional retail stores increase
slowly at rate 1.9%.
The processed food market has been growing
because of change of economic development andlifestyle (i.e. working women, awareness of health andsafety). The level of expectation of consumer becomes
higher, so sales method should be changed. To meetthe high requirements of consumers, large retailers
demand high quality of products from suppliers. As aresult, it requires a comprehensive innovation in the
supply chain to meet these high requirements ofconsumers. Supply chain of agricultural products are
said to be underdeveloped and need strategies toimprove the supply chain. Many motorcycles thathave low carrying capacity are used for transportationof agricultural products. It is also necessary to clarify
which mode of transportation should be used fortransportation between actors. Besides, processed foodneeds to be considered as important actors in the
supply chain of agricultural products because it
creates high value-added even higher than agricultural
products produced.
So far, there are many research related toagricultural products of Vietnam, but the researches
which clarify the structure of supply chain are still
very few. Phan, et al.[3] came up with a solution to
replace co-operatives in the supply chain by acompany to complete supply chain for a safe
vegetables area at Tuy Loan- Da Nang, but thisresearch did only at the introduction to what kind ofactors should exist in the supply chain. Quantitative
analysis did not show transportation volume share in

2 Formulations
To clarify the supply chain of agriculture products,
this study uses two formulations below.
2-1 Calculation of transportation volume sharebetween each actor

k

i

j

Figure1: Description of origin and destination
Assumed thatis origin actor,
is destination
actor, andis origin actor of actor ,is numberof actors existing in the supply chain, therefore＝. Products transported insupply chain, in this case, are rice and processed foodfrom rice such as liquor or dried noodle.
is the transportation volume share of products
transported from origin actor to destination actor
in total weight of products transported in supply chain.
is calculated by equation (1) below.
(1)
Here,
is the weight (unit: kg) of
products transported from origin actor to destination
actor
is total of transportation volume share of products
transported from another actors
to actorbe calculated as:(2)
61

The constraint condition here will be:

was volume of product transported to another actor?
And 3) how far of distance of products transported in
one shipment?
The total number of respondent is 470 and total ofsample size obtained in survey is 1056. Actually, one
respondent in interview can give one or more sample.

(3)
and,
(4)
Equation (3) means that in supply chain, theproducts will be transported from an origin actor to a
destination actor and not be able to converselytransport from destination actor to origin actor.
In supply chain, total of transportation volume
share of products transported from another actor
to actor
will be equal to total oftransportation volume share of products transported
from actor to another actor. Therefore,
equation (4) means that total of transportation volume
share of products transported from actor
to anotheractor will be equal 100%.
is the sample size obtained from survey in thecase of products transported from origin
todestination actor ,is one of samples,
.
Then,
(5)
Therefore:

4 Results
4-1 Structure of supply chain
After conducted field surveys, we divided thenumber of actors existing in the supply chain and thenumber of transport modes used to be 16 and 24
respectively.
Names of the actors are summarized in the Table 1.
Actors i), ii), iii), iv), v) located in producing area
while actors vi), viii), ix), xii) located in consuming
area. Actors vii), x), xi), xiii), xiv) located in bothproducing area and consuming area.
Table1: The name of the actors
Name of actors, (number of respondents), (sample size)i) Farmix) Regional agency,(6)(12), (33)

2-2 Calculation of modal share between each actor
is modal share of transportation mode
used to transport products from origin actor
todestination actor ,will be calculated as theequation (7) below:(7)ii) House of farmer,

is the weight (unit: kg) of products
transported from origin actor to destination actor
by mode ,(8)
Therefore:(101)x) Bottling plants, (0), (0)(213), (489)iii) Collector, (22), (39)iv) Agency, (66), (136)v) General agency, (35),vi) Wholesaler,
Polishing factory (3), (13)xi) Distributor ofprocessed food, (1), (2)xii) Super market, (3), (6)xiii) Traditional store,
grocery store, (23), (39)xiv) Consumer in Red
River Delta (individual
consumer, hotel, restaurant,
karaoke, army, school)vii) Processed foodhousehold (liquor, dried(9)xv) Whole Vietnam
except Red River Delta

noodle), (85), (171)3 Field survey
Red River Delta including rice-producing area
(Kim Son district of Ninh Binh Province and 3
District of Nam Dinh Province) and rice consuming
region (Capital Hanoi, Nam Dinh City, Ninh Binh
City) were chosen to be the places for field survey.

viii) Distributor of rice,

Names of transportation modes are summarized in
the Table 2. The transportation distance of motorcycle
and three wheels motorcycle is longer than the othershort trip modes (i. e. (b), (d), (k), (p), (q), (r), (s), (t),(u), (x)). The volume transported by three wheel
motorcycle in one shipment is larger than thattransported by the motorcycle in Figure 3. All trucks
are overloaded (i.e. (e), (f), (g), (h), (i)). For example,(e) 0.5 ton truck is designed to transport 500 kg ofgoods, but in fact it is used to transport nearly 2,000
kg of rice. Bus is used to transport rice and processedfood in the distance from 20km to 1700km in Figure3.
By using data obtained from the field survey, thisstudy can clarify the supply chain structure of rice andprocessed food (liquors, dry noodles) made from ricein the Red River Delta, and is able to calculate amountof transportation share between each actors.
The transportation volume share and structure of
supply chain are drawn as the Figure 7. The result is

HaNoi
Nam Dinh City

Red River Delta

Ninh Binh City
Kim Sonxvi) Export(7), (27)Xuan Truong
Hai Hau
8
Nghia Hung

Figure 2: Location of field survey
All actors are required to answer the questions
asked in the questionnaire. Important questions are 1)
what kind of vehicle have you used? 2) How much62

(a)Motorcycle
kg
N=164
300
150
0
0
25
50 km
(e) 0.5 ton truck
kg
N=39
2000

(c) Three wheel motorcycle
kg
N=173
2000
1000
0
0
25
50 km
(m) Bus
kg
N=91
3000

1000

1500

0

0
0

150 300 km

25%

50%

75% 100%vii)→xiii)in shortdistance(under 20km)vii)→xiii)in long
distance(over 20km)(a)Motorcycle(e)0.5 ton ruck(h)3.5 ton truck(p)Bicycle(c)Three wheel motorcycle(g)1.25 ton truck(m)Bus(u)Human rickshaw

Figure 4: Different of modal share between shortand long transport distance of vii)→xiii)
N=81 0%

25%

50%

75%

100%

ii)→iii)
ii)→iv)(a)Motorcycle(b)Mode of combining box and two wheel motorcycle(c)Three wheel motorcycle(d)Cong nong(e)0.5 ton truck(h)3.5 ton truck(p)Bicycle(q)Mode of combining shelf and bicycle(u)Human rickshaw

Figure 5: Modal share in producing area
N=38

0

0%

N=89

Table 2: The name of transportation modes(a) Motorcycle(m) Bus(b) Mode of combining(n) Railway
box and two wheel
motorcycle(c) Three wheel(o) Coastal shipping
motorcycle(vessels)(d) Cong nong(p) Bicycle(e) 0.5 ton truck(q) Mode of combining
shelf and bicycle(f) 1 ton truck(r) Cyclo, trishaw(g) 1.25 ton truck(s) Put on head(h) 3.5 ton truck(t) Put on shoulder(i) 8 ton truck(u) Human rickshaw(j) Trailer(v) Taxi(k) River shipping(w) Animals (horse,(boats)buffalo)

900 1800 km

0%

25%

50%

75%

100%

viii)→ix)

Figure 3: Dispersion diagram of transportation distanceand transportation volume of (a), (c), (e) (m) in one
shipmentix)→xiii)
ix)→xiv)

that 100% of total volume of rice products aretransported
actor i) to (x)actorii) after harvesting,(l) Electric frommotorcycle
Wheelbarrows
15.62% of total volume of rice products are used tomake processed food such as liquor, dried noodle,
only 2.23% of volume of rice are sold throughsupermarket. While 50.93% of total of rice andprocessed food such as liquor and dried noodle is soldthrough actor xiii). 62.96 % of total volume of riceand processed food are consuming by actor xiv),
32.04 % of total volume of rice and processed foodare sold to actor xv), only 5% of total volume of rice
are exported directly from actor v) and vi).

(a)Motorcycle(b)Mode of combining box and two wheel motorcycle(c)Three wheel motorcycle(e)0.5 ton truck(f) 1 ton truck(g)1.25 ton truck(h)3.5 ton truck(r)Cyclo, trishaw

Figure 6: Modal share in consuming area
the footrests of passenger seat, space in the bus, orunder the bus where using to put luggage.
In producing area, main transport mode is not truck.
The main transport modes are motorcycle and threewheel motorcycle because of some reasons (i.e. a lotof motorcycles are available; farmers do not sell muchin one time; roads from the house to farmer are
narrow; the using of homemade transportation modes,
such as mode (b), are not prohibited etc.) in Figure 5.
In consuming areas, 0.5 ton truck and motorcycle
are mainly used as shown in Figure 6. The reason is
because roads in the capital Hanoi or other cities are
narrow, and drivers want to avoid traffic congestion.

4-2 Modal share between each actor
This study calculates modal share between eachactor in the supply chain, also shows the difference ofmodal share between short and long transport distancein the supply chain as shown in Figure 4. In shortdistance transport, motorcycle is mainly used. In long
distance transport, uses of motorcycle are also found.
Transportation by bus also exists for long distancetransport because it is more convenient and cheaper
than truck or train when transporting in small volume
only as shown in Figure 4. Owner of bus put bags ofdry rice or bags of dried noodles, cans of liquor under63xvi) Export
(5%)

1.43%
6.22%

3.57%

66.97%

2.14%

14.31%

0.17%

7.83%

0.05％
3.49％
6.57％

5.52％

5.1%
34.25%
1.25%

2.24%

2.23%

50.93%xv)Whole Vietnam except Red River Delta (32.04%)

4.2%

Number shows volume share

2.47%

1.57%

1.22%

2.65%

0.36%

vii) Processed food

6.16%

0.82%

0.57%

4.06%

2.09%

xiv) Consumer in Red River Delta (62.96%)

4.13%

6.29%

34.32%

xiii)Traditional store, grocery store

0.89%iv) Agency

22.61%

5.4%

13.93%

0.36%xii)Super market

26.54%
14.64%

1.36%

0.14%

x)Bottling plantsix) Regional agency xi)Distributor of processed food28.53%

iii) Collectorii) House of farmeri) Farm

100%v) General agency

4.61%

0.43%

viii) Distributor of ricevi) Whole saler , Polishing factory

2.84%

Figure 7: Structure of supply chain of rice, processed food from rice (liquor, dried noodle) in Red River Delta
4-3 Identify problems
There are three reasons why many actors exist in
supply chain. First, it is easy to participate in the
supply chain (i.e. Free market, rice is producing inwhole Vietnam). Second, consumer mainly buy ricefrom traditional stores (sold by traditional stores is50.93% and supermarket is 2.23%), most consumers
do not consider value-added of rice, so actor iii)
Collector who cannot make value-added still exsits.
Third, it is difficult for an actor to make his own
distribution and marketing network; and lack of
distribution network (ex. Yamato or Sagawa in Japan)
because, except for actor vi) and actor xii), all actors
can be managed with only few employees from 1 to 5
persons, so many actors need to play as a distributor in
supply chain now.
Both iv) Agency and v) General agency existing in
supply chain are one of special characteristics ofVietnam because of first reason and third reason
written above.

through modern retail store (i.e. supermarket)
collectors do not need to exist in supply chain. In thiscase, collectors mean iii) and other actors such as iv),v), viii), ix) shown in Figure 7.
Until now, there are a lot of cooperatives existing in
Vietnam, but most of them only cooperates in
upstream of supply chain, only have relationship with
farmer as supplier of irrigation services, plant
protection and agricultural materials such as fertilizers,
pesticides (Pham Vinh Dien[5]). Therefore, we propose
to re-eatablish cooperative to replace the role ofintermediary actor such as actor iv), v), and vi) locatedin producing area. This cooperative can play the roleas actor wholesaler, polishing factory and haveenough ability to make high quality of rice to solddirectly for supermaket or retailer (such as actor xii),xiii) at consuming area.
References[1] General Statistics Office of Vietnam:
http://www.gso.gov.vn/default_en.aspx?tabid=466&idmid=3.
[2] The food market environment research in Thailand,
Vietnam, Myanmar, Daiwa Institute of Research
report, 2012 (in Japanese).
[3] Phan Thi Nhu Hoa, et all.: Completing supply
chain for a main safe vegetables area at Tuy
Loan- Da Nang, Collections of Report of student
scientific research Conference 8th at Danang
University, 2012 (in Vietnamese).
[4] Vo Thi Thanh Loc, et all,: Part1: Value chain
analysis of rice product in the Mekong Delta,
Science journal, 19a, 96-108, 2011 (inVietnamese).
[5] Phan Vinh Dien: The current situation anddevelopment solution of agriculture cooperative of
our country today, Southern Center for Supportand Development of Cooperative, Small andMedium Enterprise, (in Vietnamese).

5 Conclusions
After clarification of the rice supply chain in the
Red River Delta area, it is found out that there are a
lot of transportation modes used between each actor.
Actors mainly use motorcycle, three wheel motorcycle
and homemade mode in producing area, while actors
mainly use motorcycle and 0.5 ton truck in consuming
area. In long distance, actors still use motorcycle andbus for transportation.
At present, existing problem in supply chain is that
there are too many actors. This problem leads to dropin quality and loss in quantity of rice because
repackaging at each actor, which make supply chain
become inefficient. Moreover, profits of famer
become very few because after agricultural products
were produced by farmer, they have to go throughmany intermediaries before reaching consumer.
In future, when consumers mainly buy products
64Visual Object Categorization by Background Removalwith Depth Image
Students Number: 12M18175 Name: Joowon KIM Supervisor: Yukihiko YAMASHITA

深度画像によって背景情報を除去する画像分類
金

柱源

近年，スマートフォンの普及により爆発的に増加したデジタル画像は，日付や場所などの情報を含んでおり，その情報によって自動的に整理されている。しかし，その画像内の物体やシーンの情報に基づく現在の自動的な整理手法にはまだ性能が低いという問題がある。そのため，自動的に画像内の物体を認識して分類する手法の高性能化が要求されている。画像分類では，
画像を局所特徴量を用いて分類する Bag-of-Keypoints 法が提案され，広く利用されている。しかしながら，この手法は画像全体から特徴を抽出するため，背景情報の影響を受けやすいという問題がある。そこで，本研究では深度画像により背景を除去する手法，そして階層型データベースの構築手法を提案し，計算機実験によって提案手法の有効性を検討する。

1

Introduction

In recent years, the digital image revolution in theWorld Wide Web facilitates the storage of large collections of digital images. Especially, the proliferationof digital imaging sensors in smartphones has increased
the number of images exponentially. These images ofvarious scenes include an important information suchas datetime, place and the type of camera. However,this information is not enough to manage a huge number of images. Thus, this exponential growth of thedigital images has generated a compelling need for innovative techniques to retrieve and categorize images
from large data to use education, the artificial intelligence and the medical field.
For visual object categorization, many kinds of methods were proposed from 1960. Among many methods,
Bag-of-Keypoints (BoK) [1] that expresses an image
by a histogram has been applied widely because of
the computation eﬃciency and time. However, thismethod has limitations that image lost its size and thehistogram can be influenced by the background information. Thus, I focus the research on the backgroundremoval and the construction of hierarchical database
based on the size and the shape to improve the categorization time and precision.
The rest of this paper is organized as follows. Section
2 presents the Bag-of-Keypoints method and its disadvantages. Section 3 presents the proposed method andSection 4 presents experimental results and discussions.
Finally, I conclude this paper in Section 5.

2

Bag-of-Keypoints

Recent advances in image processing techniques havegiven rise to extract such robust and invariant featuresfrom images. Among many techniques, Scale Invariant
Feature Transform (SIFT) [2] has been applied to thevisual object categorization because of the robustness

to changes in scale, rotation, and illumination. Usually, a large number, hundreds or thousands, of features are extracted from each image by computing theintensity pattern using SIFT. However, the visual object categorization method with all SIFT features has
a disadvantage on computational complexity and time.
The Bag-of-Keypoints method is similar to Bag ofWords (BoW) in the text retrieval. First, each keypoint is extracted by a vector descriptor such as SIFT
and described as a high dimensional vector. The calculated descriptors are vector-quantized by the k-meansclustering. Then, all of the descriptors are assigned to
the nearest cluster. Finally, an image is represented bya bag of these keypoints expressed by a histogram sothat images are categorized by a classifier.
However, this method has two disadvantages. In the
Bag-of-Keypoints model, an image is considered as aset of keypoints besides loss of size and shape. However, the characteristics such as size and shape are very
important informations of the object. Therefore, it isnecessary to use not only keypoint descriptors but also
other characteristics to improve the precision of categorization. Also, in this method, the keypoints are
extracted in a whole image so that the backgroundinformation is contained in the histogram. The information of background decreases the precision. In
recent years, the RGB-D camera such as Kinect thatcan get not only 2D location but also depth has been
started to use in our daily life so that it will propagate rapidly in the future. The background can beremoved easily if the depth between the object and thecamera is known. Therefore, to overcome the limitation, I propose a background removal method by using
depth images and a construction method of a hierarchical database. In background removal stage, the histogram of depth values is used for background removal
and the RANSAC method is used for ground removal.
Also, in the database construction stage, the size andthe number of keypoints are used.
65

3

Overview of Proposed Method the plane is estimated by these three points. To findIn general, for background removal, color-based image
segmentation techniques are often used. However, it isvery diﬃcult to extract the exact region of an object.
Therefore, I propose to use a depth image for background removal. A depth image has an image channel
that contains information about the distance between
the object and the viewpoint. It is obtained by infrared
sensors of a RGB-D camera. Usually, an image consists of background, object, and ground. Each region
has diﬀerent characteristics. In the background region,
the depth values are larger than those of the object or
the ground and the most of depth values have similarvalues. Besides, in the ground region, the ground is aplane and the depth values are increased continuously
from bottom to up in an image. Thus, I extract the object region by 2 steps: background removal and groundremoval. First, the histogram of depth values is used
for background removal. The depth value is increased
sharply on the boundary between an object and an
background in a depth image. It means that the depth
values between the object and the background do notexist. Thus, the histogram is divided into two regions
so that the background can be removed by removing
the region of high depth values in the histogram. Also,
the region of 0 depth values is removed.

the best plane, the same process is repeated. By thismethod, the object region is extracted.

Figure 2: Ground removal
For the construction of a hierarchical database, I use
the size of an object and the number of keypoints. The
size is an important characteristic to categorize the images based on objects. The size of an object is computed by counting pixels in the object region. However,the size depends on the distance between the object
and the camera. Thus, some objects are downsized if
the object is closed to the camera and some are upsized
if the object is far from the camera. Also, the numberof keypoints can be used as a characteristic for categorization. We can expect that the object which has
a large number of keypoints is a complex object andthe object which has a small number of keypoints is a
simple object. Therefore, I build a three layer hierarchical database of the training images by using the size
and the number of keypoints. The third layer consistsof the original data. The second layer consists of thethree clustered image groups based on the size of an
object. The first layer consists of the nine clusteredimage groups based on the number of keypoints.

Figure 1: Background removal
Second, I propose to use the constrained RANdom
SAmple Consensus (RANSAC) [3] method for groundremoval. RANSAC that was proposed by Fischer is an
iterative method to estimate a statistical model from a
set of data which include outliers. In general, groundis a plane and an object is on the ground in many
images so that the ground is considered as an inlier
for plane fitting in an depth image. However, objects
have many shapes so that an object is considered as an
outlier. The process of ground removal is as follows.
First, three columns are selected randomly from thedepth image. Second, the depth values are analyzed
by bottom up approach in the selected three columns.
The two points are selected when the depth value ofthe below pixel is smaller than that of the upper pixel
and one point is selected when the depth value of the
below pixel is larger than that of the upper pixel. Then,

Figure 3: Hierarchical database
The precess of the proposed method is as follows:
1. Remove the background of each training image
based on its depth image.
2. Detect and make descriptors of keypoints in theobject region.
3. Generate visual vocabularies by applying the vector quantization.
66

4. Assign all descriptors to a set of visual vocabularies which is called as codebook.
5. Construct a resulting histogram on an individual
training image, which counts the number of descriptors assigned to each vocabulary and treat thehistogram as a feature vector.
6. Build hierarchical database by the size and thenumber of keypoints.
7. Construct a resulting histogram of an unknown
image based on the same codebook.
8. Evaluate the similarities between the query andtraining images.

4

Experimental Result

To evaluate the proposed method, a large image collection for the visual object categorization task by depth
images is used [4]. The experimental data set consists of 20 kinds of objects, the total number of images are 18,511. Before the learning process, 9,904 images are selected as a training set. To compare thecategorization time and precision, I set the seven different numbers of visual vocabularies as 10, 30, 50,
100, 200, 300, and 500. After the construction of visual vocabularies, all images in the training set are
represented by histograms. For a quantitative evaluation of the categorization results, another 8,607 images are selected as a test set and the nearest neighbor method is used for categorization. The distancesthat are used for the nearest neighbor are euclidean
distance, manhattan distance, correlation, chi-square,intersection, and Bhattacharyya distance. The categorization time is used to evaluate the construction ofhierarchical database.
Figure 4 shows the results of the background removal
by using a depth image. It is observed from Figure
4 that for the image that consists of a background,an object, and a ground, its object region can be extracted clearly. However, for the image that consists ofa turntable and an object, its object region cannot be
extracted. Also, for the images such as a soda can anda water bottle which have reflective surfaces, the exact
region of an object cannot be extracted because of the
0 depth value.
Figure 5 shows the categorization time by performing the proposed method and the original method toshow the actual improvement on seven diﬀerent numbers of visual vocabularies. The categorization timeis the average of six trials. It is clear from Figure 4that the categorization time of the proposed method isabout 5 times faster comparing to that of the original
method. This result shows that constructing a hierarchical database is an eﬀective method to speed up the
categorization.

Figure 4: Examples of background removal

Figure 5: Categorization time
Figure 6 shows the precision of categorization onseven diﬀerent numbers of visual vocabularies by using six kinds of distances. It is observed that the precision of the proposed method is increased comparing
to that of the original method. This result shows thatthe background removal method and the hierarchicaldatabase based on the size and the number of keypoints
improve the precision. Also, it is clear from Figure 6
that the precision of categorization by using manhattan distance and intersection is better comparing tothat by using other distances. It is the reason that the
influence of outliers in the histogram becomes larger
when the distance is raised to the second power.
Table 1 shows the precision of categorization in eachobject when the number of visual vocabularies is 300
and the distance for the nearest neighbor is intersection. It is clear from Table 1 that the objects such as
67

Table 1: Categorization rate on each object
Original Proposed
methodmethodObjectPrecision Precision
apple
79.13%
77.56%
ball
4.23%
6.55%
banana41.22%
31.08%
bowl
16.01%
25.29%
calculator
26.99%
0.00%
cap
62.70%
89.29%
cereal box
55.46%
78.18%
coﬀee mug
23.09%
40.97%
flashlight
0.00%
0.00%
food bag
58.00%
0.8%
food box
9.88%
20.50%
food can
38.70%
67.87%
greens41.22 %
30.07%
instant noodles
28.12%
72.98%
keyboard
92.13%
71.76%
kleenex80.88%
43.34%
notebook
42.37%
30.84%
soda can
20.67%
31.01%
toothpaste
25.46%
56.52%
water bottle
13.16%
80.78%

Figure 6: Precision of categorization

cap and cereal box have good precisions in the proposed method. By analyzing the sizes of objects, it isobserved that the two kinds of objects have distinctive
characteristics. They are larger than other kinds ofobjects. Thus they are clustered into the same groupby constructing the hierarchical database based on thesize so that the precisions are increased sharply. Also,
it is observed that the precisions of objects of whichbackground regions are removed clearly are increased
but the precisions of balls and calculators are still low.
It is the reason that those objects are too small andhave various shapes.
From those results, it is not necessary to evaluate
all training images. We can speed up and improve
the precision by evaluating between a query image andselected images.

5

apply to a practical use. It would be necessary to improve the precision in more than 50% for a practicaluse.
For future works, I plan to research on a better Hierarchical database for training data to speed up the
categorization time and improve the precision. Also, I
plan to study on a better visual object categorization
method by using many kinds of characteristics.

References[1] G.Csurka, C. Bray, C. Dance, and L. Fan.: Visual categorization with bags of keypoints, ECCV Workshop
on Statistical Learning in Computer Vision, pp.1-22(2004).

Conclusions[2] Lowe, D. G.: Object recognition from local scale- invariant features, IEEE International Journal of Computer Vision, 60, 2, pp. 91-110 (2004).

I have investigated the visual object categorization bybackground removal and a hierarchical database. In
this approach, the background and the ground region
are removed at the preprocessing stage. An keypoint is
detected and described by the SIFT descriptor. Basedon the construction of visual vocabularies, an image
is represented by a histogram. The proposed method
evaluates the similarities/correlations between hierarchical training data and a query image. The query
image is categorized by the nearest neighbor method.
Experimental results showed that the proposed method
improved the categorization time and the precision of
categorization. However, the results are not enough to[3] Martin A. Fischler and Robert C. Bolles.: Random
Sample Consensus: A Paradigm for Model Fittingwith Applications to Image Analysis and AutomatedCartography. Comm. of the ACM, pp.381-395 (1981).
[4] RGB-D Object Dataset:
http://www.cs.washington.edu/rgbddataset/dataset/rgbd-dataset/

68

Control Method of Boost Switching Regulator for Generators with Voltage Variation
Student Number:12M18117

Name: Yoshito HONDA

Supervisor: Kunio TAKAHASHI

周期的に電圧が変動する電源を入力とした昇圧スイッチングレギュレータの制御手法
本多 慶人
変動のある電源を入力とし昇圧スイッチングレギュレータを用いてエネルギーを蓄積する際に、最大出力点追従を用いない制御手法を検討している。電源を直流電源と変動と見立てた交流電源に置き換え、等価回路モデルを用いてエネルギー蓄積効率を解析的に導出した。等価回路モデルの限界により解析解を用いることのできない範囲では数値的にエネルギー効率と各パラメータの関係を明らかにした。導出したエネルギー効率をもとに昇圧スイッチングレギュレータの制御手法を提案した。

1. Introduction

2. Theoretical approach

Energy harvesting has become a popularresearch topic as a technology of scavenging
energy. The energy sources are vibration, sunlight,
wind, water flow, and so on. The characteristics ofharvested energy from these energy sources are
small or unstable to use directly. In order to use
the energy sources as a power sources, Maximum
Power Point Tracking (MPPT) methods using a
convertor is researched [1][2][3]. Maximum Power
Point (MPP) is a point on i-v characteristics atwhich the harvested energy is maximized. MPPTis the technique for searching and tracking thevariation of MPP by the power source’s voltage
variation. Tanaka optimized a boost switchingregulator for energy harvesting analyticallyconsidering MPPT [4]. Fig.1 is a schematic
illustration of the relation of the sampling periodof MPPT TMPPT , the switching period of theregulator TS and the period of power source’s
voltage variation TP . Considering the applicabilityof MPPT, when TP is enough longer than TMPPT ,MPPT is effective. However, when TP iscomparable or shorter than TMPPT , MPPT is not
adoptable. In this study, for suggesting a control
method of the boost switching regulator for the
power source with the voltage variation without
MPPT, the energy efficiency of the boost switchingregulator is obtained by analytically and bynumerically. When TP is comparable or shorter
than TS , the switching regulator cannot be used.
So, in this study, TP is assumed enough longer
than TS .

2.1 Equivalent circuit of switching regulator
circuitFig.2 shows a switching regulator circuit. To
make an equivalent circuit of the switchingregulator, some assumptions are introduced. A
power source which has voltage variation isassumed as a DC voltage source and an AC voltage
source which have a constant internal resistanceand linear I-V characteristics like fig.3. The
waveform of output voltage of power source isshown in fig.3 (b). It is assumed that the period of
AC voltage source is enough longer than theswitching period of the regulator. A capacitor isused as the storage device. The capacitor has large
capacitance so that the capacitor’s voltage can beassumed to constant voltage in several switching.
In other part of the switching regulator, the circuit
which is used in [4] is used. Then the equivalentcircuit is shown in fig.4. Followings are parametersin the equivalent circuit and the model of powersource.

Fig.2 The switching regulator circuit

Fig.3 The model of the power source

Fig.1 The relation of periods

Fig.4 The equivalent circuit

69

dio n t , n (1), Ro nio n t , n   VP_ D  VP_ A sint dt
di t , n 
L o ff
 Ro ff io ff t , n   VP_ D  VP_ A sint   VCD (2).
dt

VP_D : Average voltage of power source

L

VP_A : Amplitude of power source’s variation

RP : Internal resistance of power source
TP : Period of power source’s variation
L ：Inductance
RL : Internal resistance of inductor
Vd ：Forward voltage of diodewhere Ron  RP  RL  RS , Roff  RP  RL  Rd .Fromeq.(1) and eq.(2), the current of the regulator
ion t , n , ioff t , n is derived as

Rd : Internal resistance of diodeRS : Internal resistance of FET
VC : Voltage of capacitor
VCD : VC  Vd
ion t , n : Current when switch is on
ioff t , n : Current when switch is off
Ton : Time span when switch is on
Toff : Time span when switch is off
The open circuit voltage of power source is definedas Vin  VP_D  VP_A sin t where  is the angularB  A1  e1 d T  e RL t nTS   A  C sint   (3),ioff t , n   A  B 1  edT  e RL t nTS dTS   B  C sint   

(4),

~

~

1  eT~~1  eT~
where T  RTS L , A  VP_D R , B  VP_D  VCD R ,C  VP_A

R 2  L 2 . The internal resistance of thepower source is assumed enough large to be assumed thatRon  Roff  R . The energy which stored in the capacitor
during one cycle of the power source’s variation is derived
from eq. (4). The energy efficiency of one cycle is definedas the stored energy during one cycle per the ideal energy
which is harvested at the maximum power point during
one cycle. The energy efficiency is derived asrate of the voltage variation and is defined as  2 TP . n is the number of switching times. In
order to get an effect of voltage variation, the~voltage variation ratio is defined as V  VP_A VP_D .







 g~ 2 1  e dT 1  e 1d TRPVS ~1~T cycle T 1 e1 ~ RVCD 

1 V
~
~
 1  d g 2  g 2

The switching period of the regulator is defined asTS  Ton  Toff . The duty ratio of the regulator isdefined as d  Ton TS . The gain of the regulator isdefined as g~  V V. The equivalent circuitCDion t , n  P_D

has a low pass filter consisted of the inductor andthe resistance. In this study, the cutoff frequency isenough longer than the switching frequency andthe frequency of the power source’s variation.
In order to use the equivalent circuit, to know theapplicable condition of the equivalent circuit isneeded. In the equivalent circuit, the diode in theregulator is replaced with the forward voltage andthe resistance. In the regulator, the reverse current
from the storage device cannot exist by therectifying effect of the diode. However, the reverse
current can exist in the analytical solution of thecurrent of the equivalent circuit. When the reverse
current exists, the equivalent circuit does not fit
the real phenomenon of the regulator. In this study,
the condition in which the reverse current does notexist is named the applicable condition of theequivalent circuit. In the applicable condition of
the equivalent circuit, the energy efficiency ismaximized by analytically. Out of the applicablecondition of the equivalent circuit, the energy
efficiency is maximized by numerically.

~



~



(5).

Considering the parameters in eq. (5), it is clearthat the period of the power source’s variation has
no effect for the energy efficiency when the periodof voltage variation is enough longer than theswitching period. In eq. (5), only the duty ratio isthe controllable parameter. The optimum duty
ratio is defined as a duty ratio which maximizes
the energy efficiency. The optimum duty ratio
which is analytically approximated is obtained as
~
1  1 1 
d opt  1  ~ ln   ~  1  e T 
T  2 g   12  g1~  1  e   e  (6).
2





~ 2
T

~
T



2.3 Applicable condition of the equivalent circuit
Before deriving the energy efficiency numerically,it should be clear the relation of the applicablecondition of the equivalent circuit and the voltage
variation ratio. In the applicable condition of theequivalent circuit, the analytical solution of thecurrent should be positive. From a condition inwhich eq.(4) is positive, the relation of theapplicable condition of the equivalent circuit andthe voltage variation ratio is obtained as~g~1  e 1d T  
R 2  L 2    V~
1  
~T  
R
21  e  

 


(7).

Considering that the analytically approximatedIn order to obtain the energy efficiency duty ratio is used, eq.(7) can be described as a~analytically, the analytical solution of current is function of g~ and T because the optimum duty
obtained. Considering each current of the regulator, ratio is a function of g~ and T~ . Then, eq.(7) is
the Kirchhoff ’s voltage laws are written as
plotted in fig.5. The area under each line is the

2.2 Obtain the energy efficiency analytically70

applicable condition of the equivalent circuit. In
the applicable condition of the equivalent circuit,the analytical approximated optimum duty ratio is
the same as the optimum duty ratio. The range ofvoltage variation has a convergence value and theconvergence value is less than 0.5 in each case.

In order to visualize the relation of the voltage
variation ratio and the energy efficiency using the
optimum duty ratio, fig.7 is plotted. The energy
efficiency used the optimum duty ratio and theenergy efficiency used the optimum duty ratio canbe compared in fig.7. The energy efficiency using
the optimum duty ratio is larger than the energy
efficiency using the analytical approximated duty
ratio. However, it needs more complex calculation
to obtain the optimum duty ratio than to obtain theanalytical approximated duty ratio. From Fig.7,
the difference of the energy is about 10%. So, bothusing the optimum duty ratio and using theanalytical approximated duty ratio should beconsidered as the control method.
1

Energy efficiency cycle

The optimum duty ratio
Analytically aproximated duty ratio

Fig.5 The relation of the voltage variation ratio and thegain which meets the limitation of equivalentcircuit

2.4 Obtain the energy efficiency analyticallyOut of the applicable condition of the equivalentcircuit, the energy efficiency is obtained bynumerical integration. In the calculation, theanalytical solution of ioff t , n is used as the valueof current when ioff t , n is positive. The value ofcurrent is assumed 0 when ioff t , n is negative.

g~~ = 4.88

T = 1.04

0.9

0.8

0.7

0.6

0

0.2

0.4

0.6

0.8

~

1

Voltage variation ratio V
Fig.7 The relation of the energy efficiency and thevoltage variation ratio when the optimum duty
ratio is used

Fig.6 shows, the relation of the energy efficiency~
and the duty ratio when V  1. In fig.6, the solidline is the energy efficiency obtained numericallyand the dash line is the energy efficiency obtained
analytically. From fig.6, it is clear that thenumerical energy efficiency is larger than theanalytical energy efficiency and that the numericalenergy efficiency is maximized by a duty ratio
which is different from the analyticallyapproximated optimum duty ratio out of theapplicable condition of the equivalent circuit.
When the voltage variation ratio is 1, themaximum energy efficiency is 20% larger than theenergyefficiency
using
the
analytical
approximated duty ratio.

3. Experimental setup and result
In order to validate the energy efficiency whichobtained by the theoretical approach, the energy
efficiency is obtained by measuring the capacitor’s
voltage. In the experimental setup, a DC voltage
source of MATSUSADA PL-36-2.2 and an AC
voltage source of KENWOOD FG-273A which has
an internal resistance RP  48[] are used as thepower source with linear I-V characteristics.
Panasonic
L  470[μH] and RL  0.21[] of
ELC18B471L is used as the inductor. RS  78[mΩ]of TISHIBA TPC6006-H is used as the FET.
Vd  0.32[V] and Rd  0.20[] at 100[mA] of forward
current flow of TOSHIBA CMS16 is used as thediode. C  219[mF] of BHC ALS3-224NP040 isused as the storage device. The capacitor’s voltage
is measured 6.95[V] to 7.05[V] . In this range, therelation of the energy efficiency and the duty ratio
does not change in the theoretical approach. The
experimental setup is shown in fig.8.
In the first experiment, the relation of the energy
efficiency and the duty ratio with respect to thevoltage variation ratio which obtained numericallyis validated. The result is shown in fig.9. In fig.9,
the experimental points fitted the relation
obtained numerically well. However, the difference

Fig.6 The relation of duty ratio and the energy efficiency

71

between the theoretical energy efficiency and theexperimental result increases with decreasing theduty ratio. The causes of the difference aresupposed that the numerical error from theassumption occurred or that the effect of theinductor of the regulator is not estimated well in
the numerical calculation.

Energy efficiency cycle

1
The optimum duty ratio
Analytically approximated duty ratio
g~~ = 4.88
T = 1.04

0.9

0.8

0.7

0.6

0

0.2

0.4

0.6

0.8

~

1

Voltage variation ratio V
Fig.10 The experimental result about the voltage
variation ratio and the energy efficiency withrespect to the optimum duty ratio

Fig.8 The experimental setup
1

Energy Efficiency cycle

NumricalAnalyticalg~ = 4.88~
T = 1.04
~
V= 1

0.8

0.6

efficiency is needed, the optimum duty ratio should
be chosen and calculated according to the gain.
When the simple control is needed, the analytical
approximated duty ratio should be chosen.

5. Conclusions
In this paper, the control method of the boost
switching regulator without MPPT is suggested bydiscussing the effect of voltage variation of powersource for the energy efficiency. In the theoretical
approach, the energy efficiency and the analytical
approximated duty ratio are obtained by using theanalytical solution of equivalent circuit’s current.
In the condition in which the analytical solution
cannot be used, the energy efficiency and the
optimum duty ratio are obtained by the numericalintegration. In the experiment, the relation of theenergy efficiency and each parameter are validated.
In the result, the control method of the duty ratioof the boost switching regulator is suggested byconsidering the energy efficiency obtained by the
analytical approximated duty ratio and the energy
efficiency obtained by the optimum duty ratio.

0.4

0.2

0
0.6

0.7

0.8

0.9

1

Duty ratio d
Fig.9 The Experimental result about the relation
between the duty ratio and the energy efficiency

In the second experiment, the relation of theenergy efficiency and the voltage variation ratiowith respect to the optimum duty ratio and the
maximized duty ratio is validated. From fig.10, theexperimental points fitted the modified curve well.
From experimental results, it is considered thatthe relation obtained in the theoretical approach
have applicability.

References[1] R. Dayal, K. Modepalli and L. Parsa, ”A New Optimum
Power Control Scheme for Low-Power Energy Harvesting
Systems,” IEEE Trans. Ind. Applications, vol. 49, no. 6,
Nov.-Dec. 2013[2] G. Joseph, C. Foreman and M. L. Mclntyre, “A Variable Duty
Cycle Maximum Power Pint Tracking Algorithm for Wind
Energy Conversion System,” IEEE Power Electronica andMachines in Wind Applications, 2012
[3] R. Asami, “Prototype of boost converter for energy
harvesting with automatic Maximum power Point
searching,” Bachelor’s thesis of Tokyo Institute oftechnology, 2013[4] M. Tanaka, P. Hemthavy and K. Takahashi, “Optimizationof control parameters of a boost converter for energy
harvesting”, Journal of Physics: Conference Series, vol. 379,
no. 1, 2012

4. Discussion
From the theoretical approach and experiment,
the obtained energy efficiency is validated. Thenthe control method of the duty ratio of the boost
switching regulator is discussed. When the voltage
variation ration is in the applicable condition of theequivalent circuit, the duty ratio should becontrolled by using eq.(6) because the optimum
duty ratio is the same as the analytical
approximated duty ratio. When the voltage
variation ratio is out of the applicable condition of
the equivalent circuit, the optimum duty ratio or
the analytical approximated duty ratio should bechosen depend on the needs. When the high energy
72Temperature Distribution Change by Point Contact Current
Student Number: 12M18130

Name: Kazuki WAKABAYASHI

Supervisor: Kunio TAKAHASHI

点接触部における通電による温度分布変化
若林一貴
本論文では、点接触部における通電による温度分布変化を理論的に検討している。点接触とは二物体間の微小領域における平面接触を指す。温度分布が定常である系の固体内部の電流密度分布が過渡状態場合にも適用可能であることを示し、電流密度分布が接触部端部に持つ特異点の扱いに注意をしながら、
温度分布変化を求めている。その結果、温度は接触部中央付近で最も高くなる。また温度と温度変化率
を接触面電位と接触径を変えることで制御可能であることが示唆されている。

1. Introduction
Temperature distribution change by point contact
point is significant for the design of processes anddevices, for example, the resistance welding, themechanical relay, etc.
Kohlrausch[1] obtained relationship between
temperature and voltage inside the body under thesteady condition in which temperature distribution
does not change. Greenwood[2] obtained current
density distribution under the same condition as
Kohlrausch used. Both researches did not discusstemperature distribution for non-steady condition.
Kubono[3] did FEM thermal analysis for non-steadycondition by using current density distribution
obtained by Greenwood with the assumption that thecurrent density distribution is available for the
non-steady condition. The result of the thermal
analysis could differ according to the way to deal
with the singular point, however the way to deal withthe singular point has not clearly discussed.
In this study, current density distribution obtained by
Greenwood is proved to be available for non-steadycondition and temperature distribution change by
point contact current is theoretically investigated.

2. Derivation of
distribution
2.1

current

Fig. 1 Schematic illustration of the model

radius; 𝐼[A] is the total current introduced to the body.
The boundary condition at the contact area is muchreasonable if the difference of resistivity of twomaterials is larger and if the geometrical symmetricproperty of the two materials is higher. The
followings are assumed to prove current density
distribution obtained by Greenwood is available forthe model; the contact area is circle, magnetic effects
are ignored, the potential equals zero at infinity far
from the contact area, and the electric
resistivity 𝜌 [ Ω m ] is constant. Even though theresistivity changes with temperature, the order of theresult doesn’t change. Note there is no assumption ofsteady state.

density

2.2

Model and assumptions

Derivation of
distribution

the current

density

Basic equation which current density distribution
Semi-infinite asymmetry body with point contact ismust satisfy is Gauss’ law without charge div 𝑬 = 0
introduced as shown Fig.1. The finite current isand Ohm’s law 𝑬 = 𝜌𝒊. By combining them, Eq. 1 ispassed from the outside to a semi-infinite body. The
obtained.
dark part represents the contact area. 𝑉𝑐 [V] is thepotential at the contact area; 𝑎[m] is the contact73

conductivity 𝜅[W/m K] and density 𝜌𝑑 [kg/ m3] areconstant, the loss of heat from the surface is ignored,
and the latent heat and phase transition are ignored.
3.2 Derivation of the temperature distributionchangeThe heat conduction equation is shown as Eq. 5.
𝜕𝑇(𝒓, 𝑡)= 𝐷∆𝑇(𝒓. 𝑡)𝜕𝑡where 𝐷(= 𝜅/𝐶𝜌𝑑 ) is thermal diffusivity and ∆ is
Laplace operator. The solution of Eq. 5 for theimpulse heat input 𝑑𝛿𝑄 [J] (𝑡 = 𝑡 ′ ) at 𝒓 = 𝒓′ isobtained as Eq.6.

Fig. 2 Normalized current density

div 𝒊 = 0

(5)

(1)

𝑑𝛿𝑇(𝒓, 𝒓′ , 𝑡, 𝑡 ′ )𝑑𝛿𝑄1|𝒓 − 𝒓′|2=exp (−)
3/2
𝐶𝜌𝑑 (4𝜋𝐷(𝑡 − 𝑡′))
4𝐷(𝑡 − 𝑡′)(6)

Current density distribution must satisfy Eq.1 andboundary condition described in the model andassumptions. Greenwood showed current density
distribution as shown Eq. 2 in the ellipsoidal where 𝑑 represents variation of space and 𝛿
coordinate system.
represents variation of time. Temperature distributionchange 𝑇(𝒓, 𝑡) when there is heat distribution is
2𝑉𝑐
1
obtained as Eq. 7 by integrating Eq. 6 over the space𝒊=(, 0,0)(2)𝜋𝑎𝜌 √(1 + 𝜉 2 )(𝜉 2 + 𝜂 2 )𝑣′ and heat input period 0 ≤ 𝑡 ≤ 𝑡in .
𝑑𝛿𝑇(𝒓, 𝑡, 𝑡in ) = 𝑇0 +where 𝑟 = 𝑎√(1 + 𝜉 2 )(1 − 𝜂 2 ) , 𝑧 = 𝑎𝜉𝜂 , 𝜉 ∈[0, ∞), 𝜂 ∈ [−1,1] . Since the component 𝜉 of thedivergence in the ellipsoidal coordinate system isshown as Eq.3, Eq. 2 satisfies Eq.1.
1

𝜕

𝑎(𝜉 2 + 𝜂 2 ) 𝜕𝜉

𝑡in

′

∫ ∭
0

𝑣′

𝑑𝛿𝑄(𝑟 , 𝑡 )
𝐶𝜌𝑑

(7)

′

−3/2

(4𝜋𝐷(𝑡 − 𝑡′ ))exp (−(√(1 + 𝜉 2 )(𝜉 2 + 𝜂 2 ))(3)|𝒓 − 𝒓′|2)4𝐷(𝑡 − 𝑡′)where 𝑇0 [K] is the initial temperature. Heat is
generated by current inside the body in this case. The
Potential distribution derived from Eq.2 based on heat distribution is obtained as Eq. 8 by the Ohm’s
𝑬 = −grad𝑉 is shown as Eq.4.
law.
𝑑𝛿𝑄(𝒓) = 𝜌|𝒊(𝒓)|2 𝑑𝑣𝛿𝑡
(8)
2𝑉𝑐
1
𝑉(𝜉) =
tan−1 ( )(4)
Since d𝑣 = 𝑎3 (𝜉 2 + 𝜂 2 )𝑑𝜉𝑑𝜂𝑑𝜃 in the ellipsoidal𝜋𝜉
coordinate system, 𝑑𝛿𝑄(𝒓) is obtained as Eq. 9 by
Eq.4 satisfies the boundary conditions. Therefore, Eq. 2, 8.
Eq.2 is the analytic solution of the current density
4𝑉𝑐 2 𝑎 1
distribution in this model. Fig.2 shows the result of𝑑𝛿𝑄(𝒓) = 2𝑑𝜉𝑑𝜂𝑑𝜃𝛿𝑡(9)𝜋 𝜌 1 + 𝜉2
Eq.2. Note the current density distribution has the
singular point at the edge of the contact area.
Note that the heat distribution has finite value
everywhere in the body while the current density
3. Derivation of temperature
distribution has the singular point. Temperature
distribution change
distribution change by point contact current is
3.1 Model and assumptions
obtained in an integration form as Eq.10 bysubstituting Eq. 9 for Eq. 7.
Additional assumptions are introduced for thermal
analysis: specific heat 𝐶 [J/K kg], thermal
74

shows that the heating rate is higher around origin(10) than far parts. The heating rate only at the origin has
non-zero value 𝛼̃ℎ = 1 and at other parts equal zero.
𝑡̃in
1
1
∫ ∭
Fig.6 shows that the cooling rate at the origin is3
2
0𝑣 ′ 1 + 𝜉 (𝑡̃ − 𝑡̃ ′)2
always positive. It means the temperature at theorigin immediately decreases after current passage|𝒓̃ − 𝒓̃′|2exp (−) 𝑑𝜉𝑑𝜂𝑑𝜃𝛿𝑡̃stops. Some parts have negative value of the cooling4(𝑡̃ − 𝑡̃′)rate in certain period after current passage stops. It
where parameters whose have dimension of length means temperature increases for the period there
and time are normalized as 𝒓̃ = 𝒓/𝑎 and 𝑡̃ = even though current passage stops.
𝑡/(𝑎2 /𝐷), and temperature is normalized as Eq. 11.
4.2 Possibility of the control of the temperature2
and temperature change rate with respect to time
4𝑉𝑐
𝑇̃ = (𝑇 − 𝑇0 )/
(11)
𝜅𝜌𝜋 2
Temperature is normalized as Eq.11 and temperaturechange rate with respect to time is normalized as Eq.
The form of Eq. 10 suggests that FEM thermal 14. Temperature depends on potential at the contact
analysis can be done appropriately by modifying the area but not on contact radius while temperature
coordinate system of the simulation to the ellipsoidal change rate depends on contact radius. The
dependencies suggest controllability of the maximum
coordinate system.
temperature and temperature change rate by varying
4. Results and discussion
potential at the contact area and contact radius.
3𝑇̃(𝒓̃, 𝑡̃, 𝑡̃in ) = (4𝜋)−2

4.1 Temperature distribution change and the 5.
temperature change rates

Conclusion

Temperature distribution change by point contact
current is theoretically investigated. The current
density distribution obtained by Greenwood isproved that it is the analytic solution of the current
density distribution for this non-steady state model
under the assumptions: magnetic effects are ignored
and the electric resistivity 𝜌[Ω m] is constant. The
current density has a singular point at the peripheral
parts of the contact area and the singular point isclearly treated by introducing the ellipsoidal
coordinate system. The temperature distributionchange is obtained under the assumptions: specificheat 𝐶[J/K kg], thermal conductivity 𝜅[W/m K] anddensity 𝜌𝑑 [kg/ m3] are constant, the loss of heat fromthe surface is ignored, and the latent heat and phasetransition are ignored.
𝑑𝑇
Temperature distributes higher around the origin and
𝛼ℎ =
(1)
𝑑𝑡
gradually decreases with the distance from the origin
𝑑𝑇
while
temperature distribution, conventionally, has
𝛼𝑐 = −(2)𝑑𝑡
an edge at the peripheral of the contact area. The
difference is due to the treatment of the singular
Both temperature change rates are with respect topoint. This result suggests that when the melting
time normalized as Eq. 14.
happens by passing current at the point contact,materials around the origin melts and spreads to the4𝑉𝑐 2
periphery
part. Temperature change rate with respect(3)𝛼̃ = 𝛼/𝐶𝜌𝑑 𝜌𝑎2 𝜋 2
to time is obtained which would be useful forquenching.
Fig.5,6 shows Eq. 12,13 normalized as Eq. 14. Fig. 5 Temperature depends on potential at the contact area

Fig. 3, 4 shows the temperature distribution change
at the surface. Fig. 3 takes normalized time as thehorizontal axis and Fig. 4 takes normalized radius.
As shown in Fig.3,4, The result shows the vicinity ofthe origin has the highest temperature andtemperature gradually decreases with the distancefrom the origin while temperature distribution,
conventionally , has an edge at the peripheral of thecontact area. The difference is due to the treatment of
the singular point. This result suggests that when themelting happens by passing current at the point
contact, materials around the origin melts andspreads to the periphery part.Temperature heating
rate and cooling rate are introduced as Eq. 12,13.

75

Fig. 5 Normalized heating rate at the surface

Fig. 3 Normalized temperature change at the surface.

Fig. 4 Normalized temperature distribution change at Fig. 6 Normalized cooling rate at the surface. The
the surface ( 𝑡in = 0.5 ). Solid lines represent the horizontal axis is the normalized elapsed time
temperature distribution while current is passed and 𝑡𝑒 = 𝑡 − 𝑡in .
dotted lines represent the temperature distribution after
current passage ends.
alen der Physik, pp132-158, Issue.1, Vol.306(1900).
[2] J. A. Greenwood and J. B. P. Williamson, Electricalconduction in solids II. Theory of temperature-dependent
conductors, Proceedings of the Royal Society of London.
Series A, Mathematical and Physical, pp13-31,no.1244,
Vol.246(1958).
[3] Takayoshi KUBONO, Temperature Distribution in theConstriction Region of Electrical Contacts Carrying theDC-current, The transactions of the Institute of ElectricalEngineers of Japan.A, pp47-53, no.6, Vol.104(1985)

but not on contact radius while temperature change
rate with respect to time depends on contact radius.
The dependencies suggest controllability of the
maximum temperature and temperature change rateby varying potential at the contact area and contact
radius.

Reference[1]
F.
Kohlraush,
Ueber
den
stationaren
Temperaturzustand eines elektrisch geheizten Leiters, Ann76

Effect of Curing Conditions and Reinforcing Bars Arrangement on the Corrosion of
Steel in Concrete Mixed with SeawaterStudent ID: 12M18270

Name: Zoulkanel MOUSSA GARBA-SAY

Supervisor: Nobuaki OTSUKI

海水練りコンクリート中鉄筋の腐食における養生方法および鉄筋配置の影響に関する研究
ムッサ ガルバ サーイ，ズルカネル
本研究では海水練り鉄筋コンクリートにおいて養生方法と部材高さが物質透過性に及ぼす影響と、鉄筋配置が腐食挙動に及ぼす影響を検討し、構造物の寿命を定量的に評価した。その結果、海水で養生を行った場合塩化物拡散と中性化速度が小さくなる。また、大きな供試体においても上部より下部のほうが塩化物拡散と酸素透過性が小さいことがわかった。一方、海水の場合は腐食開始が早いので伏期間が短くなるが、腐食速度あまり大きな差が認められなかった。結論としては海水中に養生すると潜伏期が長くなった。高さの影響に関しては上部より下部の方が 1.5～3 倍寿命が長く、小さい供試体に比べても上部の方が短い寿命だった。

mixed

1. Introduction
Fresh water scarcity represents one of the major
crisesonst21

century.

According

to

with

seawaterundermarineandcarbonation environment.

World

2. Experimental procedure

Meteorological Organization, by 2025 about 2/3 of the

Two types of specimens mixed and cured with tap

world will not have access to enough fresh water. So it

water and seawater, OPC (Ordinary Portland Cement)

seems important to save fresh water, by promoting

and BFS (Blast Furnace Slag cement: 0, 40 and 70%)

seawater usage. On the other hand, in the concreteas binder were fabricated; water/binder ratio was 0.5

industry some studies on seawater usage in concrete

The first type is plain concrete specimen for analyzing

demonstrated that it could be possible to use seawater

the effects of curing on Cl diffusivity and carbonation

for RC material, if appropriate material is used [1]. But

rate. The second type is reinforced concrete used for

those studies did not consider real construction factors

investigating height effects on Cl diffusivity andsuch as curing and rebars arrangement.

oxygen diffusivity, and effects of rebars direction on

Therefore the objective of this study is tosteel

corrosionunder

accelerated

marineandinvestigate the effects of curing condition, size ofcarbonation environment (Fig 1). The concrete covermembers and rebars disposition on corrosion behavior

was 4cm for all rebars. Curing patterns are summarizedof steel in concrete mixed with seawater. To attain thisin table 1; for the second type, only burlap curing was

objective, sub-objectives have been set as follows.

conducted.

-

To Determine the effects of curing and height ofspecimen on material properties such as chloride
diffusivity,

carbonation

rate

and

oxygenpermeability.
-

To elucidate the effects of height and direction ofrebars on corrosion behavior.

-

To quantitatively estimate the lifetime of concrete
1772.1. Chloride diffusivity test
After curing the specimens were submerged into salt
water (3% NaCl) for 9months, or Alternate Dry andWet (ADW) test (3%NaCl, 50℃) for 6 months. After
testing, chloride content was analyzed by method
conforming to JSCE-G 573-2003 standard. From theconcentration in carbonation chamber, 0.07= indoor

value of total chloride by depth, chloride diffusivity

CO2 concentration.

coefficient (Dap) was determined by using Fick’s law

As result, BFS concrete showed higher rate ofof diffusion (Eq.1).

carbonation than OPC; because of lower pH value in
BFS. However, for concrete mixed or cured withC(x, t) = C0 (1 − erf (

x/2

))

2

seawater the carbonation rate was lower or almost(1)√(Dap ×t)same as normal concrete (Fig. 3). From these results, it
3

In which: Dap(cm /year), Co(=13kg/m ): Surface

can also be confirmed that the rate of carbonation

Chloride content, C(x,t): Chloride concentration atdecreases with moisture supply. Thus 12days seawater

position (x) and time (t), erf: Error function

curing had the lowest value; 1.0 for OPC and 2.3

As shown in figure 4, for same curing method,mm/√(year) in case of BFS.

seawater mix cases had lower chloride diffusivity
coefficient; this could be due to lower gradient ofconcentration. Also due to the fineness of particle andchloride binding ability, BFS cases had lower
diffusivity. On the other hand, Dap increased withheight; and this is principally because of density
Fig. 3 Effect of curing on carbonation ratevariation along the height (Fig. 2.1 and 2.2).
2.2. Carbonation test

2.3. Oxygen permeability

The specimens were exposed into carbonation chamber

Oxygen permeability (JO) was estimated from cathodic(10% CO2, 20 ℃ ), and carbonation depth waspolarization curve measured on RC specimens

measured after 1, 4 and 12 months by Phenolphthalein

subjected to ADW test.

method. The carbonation rate was calculated by √(t)dQ

method (Eq. 2).
X = (0.742 − 0.224logC)A√C⁄0.07 ∙ tilim
JO = dt = − nF

(3)

Where, Ilim(A/cm2): Limit current density, n(=4):(2)

Where: A(mm/√t): carbonation rate coefficient X(mm):numbers

carbonation depth, t: exposure time, C: CO2

F(96500C/mol): coulomb number.
2

78

of

electronsincathodic

reaction,

O2 permeability was higher at upper layers, but there

period was estimated by determining the critical

was no significant difference between mixing wateramount of rust to induce cracks by an approximation(fig. 4). However, when mixed with BFS JO became far

method proposed by Yokozeki et al.

lower than concrete mixed with OPC; because of
reduction ability of oxygen by BFS

Fig. 5.1 time dependent change of icorr
Fig. 4 Effect of height on oxygen permeability
2.4. Corrosion phenomena in marine condition
Corrosion of steel was investigated by conducting
Alternate Dry and Wet (ADW) test into 4%NaCl water.
Polarization resistance 𝑅𝑐𝑡 (𝛺) was measured by AC
Fig. 5.2 Macrocell corrosion behavior

impedance method, and the microcell corrosion current
density𝐼𝑐𝑜𝑟𝑟 (μA/𝑐𝑚2) was estimated (Eq. 4).
K

Icorr = R ×S
ct

(4)

Where: S (cm2): steel surface area, K(=0.0209 V):
Stern-Geary constant.
Fig. 5.3 Total corrosion rate with Height

Also macrocell current was estimated analytically, andthen total corrosion rate was calculated from microcell
and macrocell current.
As results, the corrosion rate of horizontal rebars wasalmost same as horizontal ones. And because of small
bleeding rate, there was no significant difference
between upper and bottom layer. On the other handupper layers were anodic and bottom were cathodic(Fig 5.1~5.3)

2.5.1.

2.5. Estimation of Lifetime

In marine condition, mixed and cured with seawater

The lifetime of concrete was estimated on the basis of

had shorter initiation period, due to initial Cl content

material properties defined. It is divided into initiation(fig.7). But this can be elongated by conducting longer

and propagation period, as shown in the conceptual

curing into seawater. On the other hand, initiation andgraph (fig. 6). Investigations were done under few

propagation periods were both longer at bottom

assumptions: corrosion threshold Cl content= 5.5 forcompared to upper layers. And for propagation, BFS

3

Initiation and propagation period

OPC and 3.5kg/m for BFS; concrete cover=7cm forcase showed longer duration than OPC.

marine and 5cm for carbonation condition. Propagation

Under carbonation, the initiation period was inversely
379

proportional to carbonation rate (Fig. 3). As result, 12(Fig. 9). It could also be confirmed that BFS mixed

days seawater curing had longest initiation periodwith seawater may have longer or almost same lifetime

equals to 2500 years (Fig. 7.2). Almost all specimens

as normal OPC concrete mixed with tap water.

had more than 75 years which was long enough; thus
under carbonation the propagation period was not3.

estimated.

Effects of curing, height and rebars direction on

Conclusions

corrosion of steel in seawater mixed concrete havebeen investigated, and the conclusions are as
following.
1. Cl diffusivity and carbonation rate became lower
when concrete was cured with seawater; and so
12days seawater curing was more effective.

Fig. 7.1 Initiation period under marine conditions

In large specimens bottom layers had lower Cl andO2 diffusivity, because of higher density thanupper layer.
2. Corrosion of steel in concrete mixed with seawater
begins faster than tap water case, because of initialchloride. However rebars arrangement did not

Fig. 7.2 Initiation period under carbonation conditions

affect much the corrosion rate.

Fig. 7 Effect of curing on initiation period

3. Initiation period of seawater mixed concrete wasshorter than tap water case. But when cured into
seawater, longer initiation period can be obtained;
so in marine conditions, initiation period of BFS
40% mixed with seawater and cured for 12days inseawater was about 40years.
Fig. 8 Effect of height on initiation and4. Total lifetime at bottom layer was 1.5~3 times

propagation period (marine conditions)longer than upper layer which was almost same as
specimen case.
References[1] N. Otsuki et al., “Possibility of Seawater as Mixing
Water in Concrete”, Journal of Civil Engineering andArchitecture, V6, No.10 serial 59, 2012.
[2] H. Ohara, “Lifetime Estimation of Seawater mixed

Fig. 9 Total lifetime of concrete
2.5.2.

Concrete in Marine and Carbonation Environment”,

Total lifetime

In marine conditions, the total lifetime was 1.5~3 times

Feb. 2013.

longer at bottom layers compared to upper layer,[3] M.A. Baccay et al., “Influence of Bleeding on

because of higher density. In addition, the upper layers

Minute Properties and Steel Corrosion in Concrete”,

had shorter lifetime than small size concrete specimen

JACT, Vol.2, No.2, 2004.
480

A Study about Influential Factors on Corrosion Behavior of Paint-coated Steel in Submerged Zone
Student Number: 12M18152 Name: Kenji WADA Supervisor: Nobuaki OTSUKI

干満帯直下における塗装鋼板腐食への影響因子の検討
和田賢治
海洋環境下に存在する塗装された鋼構造物においては、干満帯直下部（干潮位のすぐ下）における塗膜の欠陥を起点とした腐食が問題となっている。本研究では干満帯直下における欠陥を有する塗装鋼材の腐食劣化機構解明に取り組み，
とくに塗料種類と塗料膜厚、複合環境による影響が腐食挙動に与える影響について明らかにした。

1. Introduction

Submerged Zone in Actual Environment

At offshore steel structure in marine environment,
paint coating is often appllied to protect structurefrom corrosion. However, in submerged zone
sometimes severe corrosion occurs due to paintdefect by impact of floating object.
In exisiting structure, various kind of paint coating isused. However, ability of paint coating as corrosion
inhibitor is not clear. Also environment seems tohave influence and another important issue.
From the above background, objective of my study
is “To investigate influential factors on corrosion
behavior of Paint-coated Steel in Submerged Zone”.
The objectives are divided into three followings
objectives:
Purpose 1: Investigate influence of paint type on
corrosion behavior of paint coated steel insubmerged zone quantitatively in actual
environment.

(1) Outline of exposure test
 Specimens: Steel pipe with various paints (Fig. 1).
Paints are divided into four groups as shown in
Table 1: (a) Polyethylene paint, (b) Epoxy paint,(c) Glass flaked paint and (d) Vinyl paint.
 Exposure Site: Taira Bay in Miyako’s island for
20 years.
 Measuring Method: Following items were measured.
(ⅰ)Appearance was observed
Table 1: List of paint coating

Purpose 2: Investigate deterioration process
and influence of paint thickness on corrosion
behavior of paint coated steel with defect insubmerged zone using accelerated test.
Purpose 3: Investigate influence of multiple
environments on corrosion mechanism ofpaint coated steel with defect in submergedzone with exposure test.
2. Investigation of Influence of Paint Type on
Corrosion Behavior of Paint Coated Steel inTable 2: Comparison of Paint Ability as Corrosion Inhibitor(a)Splash Zone(b)Tidal Zone(c)Submerged
Zone
Fig. 1: Paint Coated Steel Pipe

181

Fig. 2: Corrosion Depth at Each Environment and Skematic Model of Macrocell Corrosoin (Tar + Zinc)

Fig. 4: Acceleration Test
Fig. 3: Paint Coated Divided Steel with Defectmicrocell corrosion in submerged zone obtained(ⅱ)Drop-weight impact test reveals resistance for
impact by checking how much area is peeled byfrom AC impedance method is much smaller. This
impact.
graph suggests macrocell corrosion had
contribution of penetration of steel pipe.
(ⅲ) Adhesion test reveals how much power isneeded to peel paint coating off from steel pipe.
(ⅳ) AC impedance method can get paint resistance and 3. Investigation of Deterioration Process ofpolarization resistance with bode plot. With Tar Epoxy and Influence of Paint Thickness
polarization resistance, microcell current density was on Corrosion Behavior of Paint Coated Steelcalculated as Stern-Geary constant (In this study,
with Defect in Submerged Zone Using
0.0209V) divided by Polarization resistance.
Acceleration Test
(1) Outline of acceleration test(2) Result of exposure test
 Specimens: Divided steel plate which consists of 6
divided parts as shown in Fig. 3 (a) is prepared.
 Paint type: As Table 2 shows, polyethylene paintkeeps sounds. On the other hand, specimens with
Lead wire is attached by soldering on the backside
vinyl or glass flaked paint are heavily corroded. Inof each part as shown in Fig.3 (b). Location of eachcase of tar epoxy, more research is necessary as
part is fixed by gray epoxy coating as shown in Fig.
well as the influence of paint thickness. ( discuss
3 (c). Then, tar epoxy is spraied on the top side within next chapter)
80, 100, 150, 300μm thickness and defect (φ10mm)
is installed at the center as shown in Fig. 3(d).
 Corrosion in Submerged Zone: Fig. 2 shows
close outlook of deteriorated part of specimen withCenter circulated steel was called “R-0”. Other
tar epoxy with zinc paint at each environment.
steel plates were called “R-1” to “R-5” from inside.
In submerged zone, severe corrosion was
The area of each steel plate is as shown in Fig. 3(e).
observed and corrosion made penetration.
By connecting lead wire, the divided steel platesCompared with the value of total corrosion depth
were considered as one circulated plate.
in submerged zone, value of corrosion depth by  Accelerated test: Accelerated corrosion test was
282

Blister

1day

16days(a)Outlook

Ripping

Measuring method:(ⅰ)Appearance(ⅱ)AC impedance method( ⅲ )Ammeter is used to measure macrocell
current by connecting between each ring.

(2) Result of acceleration test
Deterioration Process: Fig. 5 shows change inappearance of a specimen with tar epoxy. Blisteroccurs at 16 days and ripping occurs at 343 days.
Comparing appearance with change in paintresistivity shown in Fig. 6 it can be said that paintresistivity dropped especially when blister andripping occurs.
Macrocell corrosion along with deterioration isshown in Fig. 7. From this result, it can be said thatwhen blister occurred at paint coated part, cathodic
reaction got larger and anodic reaction (corrosionrate) at defect also got larger. Then when ripping
occurred at paint coated part, cathodic area got
anode and anodic reaction (corrosion rate) at defectgot smaller.
 Influence of Paint Thickness: Days until blisteroccurs seems in proportion to the paint thickness incase of more than specific paint thickness (Fig. 8),
considering diffusion of oxygen.

343days(b)Close Outlook
Fig. 5: Outlook (Tar Epoxy)

4. Investigation of Influence of Multiple
Environment on Corrosion Behavior of
Paint Coated Steel with Defect inSubmerged Zone with Exposure Test

Fig. 6: Change in Paint Resistivity (Tar Epoxy/ R2)(1) Outline of Exposure Test
・ Specimens: Fig. 9 shows specimens. At the backof the steel, lead wire is soldered and wascovered with epoxy resin. At the surface, phthalicresin with a thickness of 150μm was sprayed. At
element in submerged zone, defect is installed. In
addition, ends of the steel were coated with clear
epoxy. When specimens immersed, lead wire
between steel elements connected.
・ Exposure environment: Artificial sea watertank in Port and Airport Research Institute,
located in the Yokosuka, Kanagawa Prefecture isused for exposure site.
(2) Result of Exposure Test
Fig. 10 shows change in appearance atsubmerged zone. From these results, corroded area
in case of multiple environments is wider than area
in case of single environment. Fig. 11 shows
macrocell corrosion rate at each area. At first, large
macrocell corrosion occurs at submerged zone at
defect point with large cathodic area at paintcoated part. Then blister occurs at tidal zone andcathodic reaction get larger and anodic reaction at
defect in submerged zone also become larger. Finallyblister in tidal zone are ripped and then macrocell
corrosion within tidal zone where newly ripped
area as anode and other blistered or sound area ascathode occurs.

Fig. 7: Change in Macrocell Corrosion Rate
at Each Part (Tar Epoxy)conducted. This test was proposed by JSCE
simulating under low water level (Fig. 4). Test
specimens were submerged to NaCl solution(3.0w.t. %, 50˚C). 2 l/min air was pumped.
3
83

Considering above all, wider corroded area insubmerged zone in case of multiple environment
seems due to the macrocell corrosion between
submerged zone with anode and tidal zone withcathode.

5. Conclusions
Purpose 1: (1)Severe macrocell corrosion occurs insubmerged zone.
・It is proved what kind of paint can keep steel soundin long term.
Purpose 2: (1)As for corrosion of paint coated steel
with defect,(1)-1 when paint blistered, macrocell corrosion at
defect get larger.
(2)-2 when paint ripped, macrocell corrosion at
defect get smaller.
(3) Term of incubation stage seems in proportion to
the paint thickness in case of more than specificpaint thickness.
Purpose 3: As for multiple environments, insubmerged zone, heavy macrocell corrosion occurs
with tidal zone as cathode.

Fig. 9: Specimens for Single and Multiple
Environments (Phthalic Resin 150µm)

Day until Blister
Occurs (day)Reference 1) PWRI, Joint research report about durability of marine
steel structures – Research result until exposing 20years(a) Single Environment (b) Multiple Environment
Fig. 10: Change in Appearance (Phthalic Resin 150µm)

Paint Thickness (µm)
Fig. 8: Days until Blister Occurs in Each Paint
Thickness (Tar Epoxy)

Fig. 11: Change in Macrocell Corrosion Rate in Each Area (Phthalic Resin 150µm)
484Effect of shear pin arrangement to a critical width of undercut slopealigned with a bedding plane
Student Number: 12M18070 Name: Shuhei KITAKATA Supervisor: Thirapong Pipatpongsa

層理面に沿う斜面法尻での限界掘削幅に及ぼす抑止杭の配置の影響
北方 秀平
In the previous research, the undercut method developed from physical and theoretical models has been successfully
applied to the Mae Moh open-pit lignite mine of Thailand. Due to the weakening basal support after backfilling process,shear pin reinforcement is required in the subsequent excavation. In this study, the effect of shear pin arrangement andits failure mechanism was studied using a series of physical model of moist silica sand No.6. A bedding plane wasmodeled by Teflon sheet and shear pins were modeled by bolts and wires. Particle image velocimetry and high-speed
video camera were used to capture slope movement and triggering mechanisms of instability. The study reveals that the
number and stiffness of shear pin, location of installment, interval span and size of shear pin have effects on a critical
width of undercut slope.

1 Introduction

3 Experiments

Prediction of the maximum stable undercut width
under which the slope does not collapse for mining
purpose was developed in the past research (Khosravi,
2012; Pipatpongsa et al., 2012&2013, Leelasukseree
et al., 2012). The actual engineering application of thedeveloped theory was immediately tested byElectricity Generating Authority of Thailand (EGAT)at Area 4.1 of the Mae Moh open-pit mine in the northof Thailand. The current undercut slope was foundstable after mining the lignite; however, it is necessary
to fill the current pit and cut the neighboring slope inthe subsequent procedure. This subsequent mining
will cause the factor of safety less than one; therefore,
EGAT has installed an array of shear pins to reinforce
the slope. In order to evaluate the reliable factor ofsafety for undercut slope reinforced by shear pins,
failure mechanisms studied by physical models are
required to before starting the actual excavation. In
this study, we aim to investigate the effect of shear pin
arrangement, location and number of pins on a critical
width of undercut slope, failure modes as well as
failure speed in order to apply to the site.

Physical model was made of moist silica sand No.6
with bulk density of 1,395 kg/m3 and water content of
10%. This model was composed of two parts, the baseparts and the slope parts. The base part was 1.3×0.4
m2 and the slope part was 1.3×0.8 m2 with thickness
0.06m. The slope angle was 40°. Both were placed on
10 mm-thick acrylic plates. The acrylic plate of theslope part was covered with a 2 mm thick Teflon sheet
in order to provide a low friction interface. Typical 1G
model of slope is shown in Fig 1.
The list of material parameters is shown at Table 1
following Khosravi et al 2012. According to Khosravi
et al 2012, water content 10% and bulk unit weight
13.68 kN/m3 is suitable to achieve slope failure results
within a width of the model. Unconfined compressive
strength σc of moist silica sand no.6, interface
adhesion ci between Teflon plate and moist silica sandno.6, interface friction angle ϕi between Teflon plateand moist silica sand no.6 was obtained from the pastlaboratory tests (Khosravi, 2012).
In the present study, shear pins were additionallyinstalled using either the screw bolts (∅ = 4 mm) or
steel wires (∅ = 0.28 mm). The arrangement of shear
pins is shown in Table 2 where the span of shear pins
means the interval between shear pin and shear pin
and the position of shear pins means the location
measured from the toe of slope along the bedding
plane where shear pins are fixed. A digital camera was
set to monitor movement every 5 seconds for PIV
analysis and a high speed camera was set at 2000
frame per second to capture triggering mechanisms.
The method of undercut followed Khosravi (2012).
The base part of the model was cut with a 0.05 m slice
until the failure of slope. Subsequent excavations were
continued up to a total failure. The undercut widths of
the first failure, second failure or more aresummarized in Table 2. For example, Fig. 2 shows thefirst failure of undercut slope with 3 screw bolts.

2 Theoretical review
We employ the theory of arching effect to estimate
the stable width of excavation (Khosravi, 2012).
1𝜎𝑐(1)
𝐵𝑓 = 𝑘𝑐𝑖 𝛾(𝑠𝑖𝑛𝛼 − 𝑡𝑎𝑛𝜙𝑖 𝑐𝑜𝑠𝛼 − 𝛾𝑇)
In this equation, T is a thickness of slope, 𝛼 is anangle of slope, 𝜙𝑖 is an interface friction angle, 𝑐𝑖 isan interface adhesion, 𝛾 is a bulk unit weight, 𝜎𝑐 isan unconfined compressive strength, 𝐵𝑓 is a failure
width and k is defined as an arching coefficient (k0 =0: no arching, k1 = cosϕ: strip arch with soil slip, k2 =1: segmented arch with stable scarp, k3 = 4/π: circulararch with slope buckling).

85

Table 1 Material parameters
Water content of moist silica sand no.6

w

10%

Bulk unit weight of moist silica sand no.6 (ρ = 1395 kg/m3)

γ13.68 kN/m3

Unconfined compressive strength of moist silica sand no.6

σc1.59 kPa

Interface adhesion between Teflon plate and moist silica sand no.6

ci

0.1 kPaInterface friction angle between Teflon plate and moist silica sand no.6

ϕi

18.5°

Thickness of slope made of moist silica sand no.6

T

0.06 mTable 2 Arrangement of shear pins and failure width
Test number

1

Model of shear pins

2

3

4

5

No

Number of shear pins

0

6

7

Bolts (∅=4mm)

0

0

1

3

Span of shear pins (m)

1

0.12

Failure undercut width 1(m) 0.45 0.45 0.525 0.60

9Wires (∅=0.28mm)

0.1

Position of shear pins (m)

8

3

22

12

0.1

0.01

0.02

0.12

0.12

0.24

0.65

0.52

0.40

0.40

0.425

Failure undercut width 2(m) 0.525 0.525 0.55 0.625 0.78

0.57

0.52

0.45

0.575

Failure undercut width 3(m)

0.70

0.70

0.60

indicating the effect of shear pins installed at theposition 0.12 m on the failure width in relationshipwith a number of pins. Though the subsequent failure
widths were higher, the first failure width for Test 6
and Test 7 where bolts were installed at the position
0.24 m were not significantly greater than those of no
reinforcement (Test 1‒3), indicating that the locationof shear pins has an effect on the failure width. The
closer the location of shear pins to the toe of slope, thehigher the reinforcement takes effective. However, if
the shear pins are installed excessively close to the
excavated pit, local failure along the interval of shear
pins could occur.
(2)
sin(𝛼 − 𝜙𝑖 ) 𝑐𝑖
𝜎𝑐
−
=𝑘
𝑐𝑜𝑠𝜙𝑖
𝛾𝑇
𝛾𝐵𝑓

40°
12cm

0.05m
0.8m
0.2m

0.4m

1.3m

0.05m
0.06m

Fig.1 Model of slope with 3 screw bolts

0.6

The Bolts
Y= sin(α-ϕi)/cosϕi-ci/γT

0.5

0.65m

Fig.2 Failure of undercut slope with 3 screw bolts

0.4
0.3
0.2
0.1

0

4 Results and discussion
4.1 Critical excavation width
In Table 2, the first and total failure widths of Test
4 and Test 5 (with bolts) were significantly greaterthan those with no reinforcement tests (Test 1‒3),

0

0.1

0.2

0.3
X=σc/γB

0.4

0.5

0.6

k1
k2
k3
Test 1
Test 2
Test 3
Test4
Test5
Test 6
Test 7
Test 8
Test 9Fig. 3 Relationship between experimental results andtheoretical predicitons86

(1) Test 1 (Bf =0.40 m)(2) Test 2 (Bf =0.40 m)(3) Test 3 (Bf =0.50 m)(4) Test 4 (Bf =0.55 m)(5) Test 5 (Bf =0.60 m)(6) Test 6 (Bf =0.50 m)(7) Test 7 (Bf =0.35 m)(8) Test 8 (Bf =0.35 m)(9) Test 9 (Bf =0.40 m)

Fig. 4 Contours of deviatoric strain observed in Test 1‒9
The test using wires (Test 8 and Test 9) revealed
that the first and second failure width were not higher
than those of no reinforcement (Test 1‒3). Therefore,
flexible type of pin might not be sufficiently effective
in reinforcement than rigid type. In other words,
stiffness of shear pins has an effect on the failure
width. However, discontinuous plane developed alongwires during compaction process would weaken thestability of slope instead of low stiffness of shear pins.
The presentation of Eq.1 can be alternatively
expressed in Eq.2 and exhibited in Fig.3 by referring
the right-hand side and the left-hand side of Eq.2 tothe X-axis and the Y-axis, respectively. Most
experimental data are appeared between boundary ofk2 (arch) and k3 (buckling) except those of Test 4 andTest 5; thus, reinforcement by shear pins at suitablelocation takes effect with a wider critical widthobserved at the first failure than the limit predicted by
the theory for slopes without reinforcement.

Arching involves in an ability of lateral loadtransmission due to relative displacement where
yielding part transfers load to unyielding part. Partial
movements due to sliding along the bedding planecaused by gravitational loading cause an intense
deviatoric strain. According to Fig.4, arch action canbe observed in all tests because yielding andunyielding parts are clearly appeared. The lower
intensity of deviatoric strain above the bolts installedat the position 0.12 m measured from the toe of slope
as shown in Fig. 4(4)‒(5) can be interpreted as effects
of reinforcement when compares to those of no
reinforcement (Test 1‒3). Once the position of bolts
were shifted higher to 0.24 m measured from the toe(Test 6‒7), the lower intensity of deviatoric strain isalso observed as shown in Fig. 4(6)‒(7); however, theintensity of deviatoric strain under the bolts was ashigh as those of no reinforcement with susceptible
forming of arch failure. Therefore, the bolts cansignificantly decrease the movement above them, butcannot sustain movements under them. This fact
implies that the bolts should be installed within theheight of the crown of arch failure as observed inthose with no reinforcement. Flexible type (wires)showed no effect of reinforcement. For each test, thecenter line of the captured area was chosen to obtain
the incremental displacement with respect to width of
excavation as shown in Fig.5. It was observed that
incremental displacement at the central line of all tests
except Test 7 considerably increased before failure.

4.2 PIV analysis
To analyze the surface movement when the slope
was excavated, the photos taken from digital camera
were analyzed using PIV techniques (White & Take,
2002). Displacement vectors and contours ofdeviatoric strain of slope part were analyzed withcareful consideration of physical coordinates. The
contours of deviatoric strain at a stage just before
failure (first failure) for Test 1‒9 are summarized in
Fig.4 where Bf means the undercut width of each test.

87

Table 3 Failure mode of total collapse and time interval
Test No.

1

2

3

4

5

6

7

8

9

Buckling

○





○





○

○

○

Time interval

3.3 s

-

5.9 s

1.5 s

3.2 s

4.9 s

1.9 s

2.1 s

-

Note: “-” indicates observation by high-speed camera was not successful
4.3 Failure mechanisms
Progressive failures every 0.1 second time interval
exhibited in Fig. 6 were selected from VDO stream ofhigh-speed camera set at speed 2000 frame/second.
Table 2 summarizes results observed by high-speed
camera. Failure modes of total collapse were notobviously different between slopes with and without
reinforcement. Hence, shear pins might not be able tochange the final mode of failure, but could take effectonly on the initial stage. Generally, time interval ofcollapse under buckling mode was shorter. Upheaval
buckling occurs at the abutments of slope; thus,
reinforcement at the central portion of slope would be
an ineffective measure against buckling while
counter-weight backfill would be an effective measure.
Buckling failure happened in subsequent failure;
therefore, it is depended on the geometry of scrap left
after the previous failure, not shear pins.

5 Conclusions
Based on a series of 1G physical model conductedin this study, main conclusions are summarized below.
5.1 Despite local failure due to detachment along
the interval of shear pins was observed, experimental
results confirmed that movements of slope above
shear pins for rigid type (bolts) were decreased.
5.2 Rigid-type shear pins located near the scrap
gave a better performance in reinforcement; therefore,
reinforcement by shear pins installed within aboundary of arch failure is effective. Still, total failure
observed in slope with/without shear pins did notchange significantly; thus, shear pins could be
effective only in the initial stage because shear pins
could not change a final model of failure.
5.3 Interpretation of movements of slope withrespect to undercut width observed in physical models
might be useful to monitoring scheme of actual sites.
Incremental movements behave in both increment anddecrement during excavation due to readjustment
process of load transmission, but will dramaticallyincrease when approaching to the failure.

700
600

Y (mm)

500

B=0.1m
B=0.15m
B=0.2m
B=0.25m
B=0.3m
B=0.35m
B=0.4m

400

300
200
100

Reference[1] M.H Khosravi (2012), Arching effect ingeomaterials with applications to retaining walls andundercut slopes, Department of International
Development Engineering, Graduate School of
Science and Engineering, Tokyo Institute ofTechnology, PhD Dissertation.
[2] T. Pipatpongsa, M.H. Khosravi, D. Stathas, C.
Leelasukseree and J. Takemura (2012), Cohesive arch
action in laterally confined block of moist sandplacing on an inclined Bedding plane, 7th Asian RockMechanics Symposium, pp.1378-1387.
[3] C. Leelasukseree, T. Pipatpongsa, M.H. Khosravi
and N. Mavong (2012), Stresses and a failure mode
from physical and numerical models of undercut slope
lying on inclined bedding plane, 7th Asian RockMechanics Symposium, pp.1295-1304.
[4] T. Pipatpongsa, M.H. Khosravi and J. Takemura(2013), Physical modeling of arch action in undercut
slopes with actual engineering practice to Mae Moh
open-pit mine of Thailand, 18th International
Conference on Soil Mechanics and GeotechnicalEngineering, Vol.1, pp.943-946[5] White, D. J. & Take, W. A. (2002) GeoPIV:
Particle image velocity (PIV) software for use ingeotechnicaltesting.
Cambridge
University
Engineering Department.

0
0

0.5
1
Incremental Displacement

1.5

Fig. 5 Changes between incremental displacements vswidth of excavation B along the center line of Test 1① time = t0+1.1s② time = t0+1.2s③ time = t0+1.4s④ time = t0+1.5s⑤ time = t0+1.5s⑥ time = t0+1.7s⑦ time = t0+1.8s⑧ time = t0+1.8s⑨ time = t0+1.9s⑩ time = t0+2.0s

⑩

⑤
③

⑧ ⑨ ⑥
⑦

①

②

④

time to collapse= t0+3.3s

Fig. 6 Progressive failure occurred before a totalcollapse in the second failure of Test 1
88

ACTIVE ARCH ACTION DUE TO INTERFACE FRICTION IN A RIGIDRETAINING WALL
Student Number: 12M18241

Name: Lin TANG Supervisor: Thirapong PIPATPONGSA

剛体壁の界面摩擦による主働的アーチ効果の観察
唐 麟

Abstract: In the previous study, lateral pressure distribution on the rigid retaining wall under translation mode has been
derived using the arch action theory and validated by a 1g physical model. This study extends the previous work inorder to validate the theory using different interface friction of the retaining wall with/without a surcharge load appliedon the surface of backfill. Pressure distribution along a retaining wall was measured by a set of precise miniaturepressure cells and backfill movement was observed by particle image velocimetry. Sandpaper used in the previous study
was replaced by Teflon sheet. Surcharge using bearing balls was additionally considered. Reliability of pressure gauges
under both loading and unloading processes was discussed. Despite difficulties in controlling a uniform density of Silica
sand No.8, the experimental results sufficiently confirm the developed arch action theory.

1.

Introduction

active earth pressure theory which considers the arching

Retaining walls have the function to prevent soil or slope

effect. In addition, the measured earth pressures werefalling, meanwhile sustain lateral earth pressure fromcompared with the previous testing results which wereretained materials or backfilled soils. The estimation of

conducted in fully rough condition of retaining wall in

active earth pressures acting on retaining walls isorder to understand the influence of interface friction on

important in geotechnical design. Normally, civil

the profile of earth pressure distribution.

engineers have calculated the active earth pressure against
rigid walls using either Coulomb (1776)’s or Rankine

2.

Theoretical Background(1857)’s classical theory. Both theories assume that the

2.1 Lateral earth pressure at-rest

distribution of active earth pressure exerted against the

In soil mechanics, lateral earth pressure at-rest for thewall is triangular. However, many experiment results

horizontally inclined subsoil is generally calculated byshow that the distribution of active earth pressure on a

Jaky (1948)’s theory as follows.

wall is non-linear and depends on the mode of wall

σ h = K 0 γH , K 0 = 1 − sin φmovement, which is different from the assumption madeWhere K0 is a coefficient of lateral earth pressure at-rest,by Coulomb and Rankine. The non-linearity of the active

ϕ is an internal friction angle of subsoil, γ is unit weight,

earth pressure distribution results from arching effects inand H is a depth of subsoil.

(1), (2)backfill due to roughness of the retaining wall.
Arching, as the word suggests, is a stress redistribution

2.2 Active arch action in retaining wallby which stress is transferred laterally around a region ofArching effect has been considered in the analysis of

the soil mass, which then becomes to lower stress. This

active earth pressure exerting on a retaining wall byresearch focuses on earth pressure acting on rigid

various studies. Khosravi et al. (2013) proposed aretaining wall under active translation mode. A series offormulation to describe the active earth pressure behind aretaining wall experiments with/without a uniform

retaining wall under active translation mode bysurcharge were conducted to validate the developed

integrating the two-dimensional equilibrium conditions

1
89

with an assumption on a uniform distribution of verticalsample preparing. In loading process, the sample waspressure in a planar active wedge. The interface friction

prepared 50 mm step by step, while in unloading process,between the wall and the backfill is mobilized while thethe sand was removed 25 mm step by step. The average

active wedge is separated from the stagnant backfill

valuesalong the slip line with a critical angle determined fromhydrostatic pressures were plotted in Fig. 2.

ofmeasuredpressures

againstcalculated

Coulomb or Rankine’s theory.
According to Khosravi et al. (2013), the magnitude ofactive lateral earth pressure σh at a depth h of a retaining
wall with backfill height H and a uniform surcharge Q isexpressed by Eq.(3).
n γ H 
h 
h 

−
1
 
 −  1 −   
1− n  H   H 
σ h ( h) = Kw 

n
h



 +Q  1 − H 






Kw =

(3)
Fig. 1 Sample preparation by air pluviation method poured at

1 − cos(ω − φw )sin φ sin φw , ω = sin −1 
1 + cos(ω − φw )sin φ sin φ constant height 100 mm in an acrylic container(4), (5)4(6), (7), (8)Measured vertical earthpressure,σσv: kPaπ φn = µ w K w cot α , µ w = tan φw , α = −4 2

3where Kw is a ratio of horizontal to vertical soil stress at
the wall, µw is the wall friction, γ is the bulk unit weight ofHydrostatic
H=10_Loading
H=10_Unloading
H=15_Loading
H=15_Unloading
H=20_Loading
H=20_Unloading
H=25_Loading
H=25_Unloading
H=30_Loading
H=30_Unloading2

backfill, α is a critical angle of active wedge, ϕ is an1angle of shearing resistance of backfill, ϕw is an interface
friction angle between the backfill and the wall.

0
0

1

2

3

4

Calculated vertical earth pressure,γh: kPa

3.

Fig. 2 Validation of pressure cells using Silica sand No.8
in unloading process

Preliminary Laboratory Element Tests

3.1 Validation of pressure cells in Silica sandIn retaining wall experiment, “bin effect” and “cellTable 1 Basic properties of dry Silica sand No.8
Specific gravity
2.637
Maximum grain size
0.250 mm
Medium grain size (D50)
0.090 mm
Uniformity coefficient (Uc)
3.05
Minimum density
1.153 g/cm3
Maximum density
1.554 g/cm3

action” must be taken into account when conducting asmall-scale 1G model. Bin effect or silo effect is causedby arch action in the soil mass stored in the bin. If thedimension of the bin is too narrow, pressure distribution
will not be linear along the depth direction. In contrast,

80

local arching in the surrounding soil next to the pressure

70

Shear stress (kPa)cell face may cause cell action which leads to over/underregistration of the cell.
Validations of the pressure cells in dry Silica sand No.8
and No.6 in a chamber were conducted in order to60
50

ϕ = 24.1º

40
30
20
10

evaluate the silo effect and unloading responses which

0
0

50

100

150

200

Normal stress (kPa)will have significant influence on the interpretation ofFig. 3 Direct shear test on dry Silica sand No.8 withinterface friction between Teflon sheet

experiments. Air pluviation method (Fig. 1) was used in
2
90

cm
35

opposite wall covered by Teflon sheet. Pressure cell in

35

30

ch1

big size was placed on the bottom of acrylic container to

25

ch2

measure vertical stress. A retaining wall retained the

20

ch3

backfill soil inside an acrylic container as shown in Fig. 5.

15

ch4

10
7.5

ch5
ch6
ch7
ch8

5
2.5
0

10

15

5
0

ch9

A strong screw passed through a fixed rigid frame andch10

connected the wall to a pulley. Rotation of the pulley andch11

screw made the wall able to slide horizontally. The speedof wall movement was controlled by an electric motor.

10

Fig. 4 Configuration of pressure cells (left is retaining
wall side, right is the opposite side)

During experiment, digital camera in front of thetransparent side of acrylic container will take photos for
PIV analysis. A lamp was used to provide light source
when digital camera working. A darkroom was in the
middle of PIV camera and acrylic container to minimize
the unwanted reflections on the screen.
4.2 Retaining wall experiments without surcharge
Backfilled soil was produced by filling sand to thecontainer using air pluviation method pouring from a

Fig. 5 A general view of the experimental setup

funnel. By keeping the pouring height constant at 100 mm
above the sand level during the process of preparation, a

The hysteretic nature of the calibration curve was drawn

uniform density of sand in the container was reached.

to compare the variation of coefficient of calibration

Data logger recorded earth pressures every second fromunder both loading and unloading processes. In general,

the initial condition in which sand was deposited inpressure cells show linear behavior in loading process,acrylic container, to the active condition when the wall isbut show non-linear behavior in unloading process. For

gently moved outward. The electric motor rotated andphysical model of retaining wall, using Silica sand No.8

pulled the wall to move horizontally at a constant speed

would better reduce “bin effect” and “cell action” thanof 0.005 mm/sec. Digital camera was set in time intervalsilica sand No.6 even at the almost same density.

about 20 seconds to take images for every 0.1 mm of wall
movement. Conditions of 4 actual retaining wall

3.2 Physical profile of Silica sand No.8

experiments without surcharge were listed in Table 2.

The basic physical properties of Silica sand No.8 is listed
in Table 1. Direct shear test was conducted with a shear
rate of 0.22 mm/min to obtain the interface friction angle

Non-dimensional depth h/H

between Silica sand No.8 and Teflon sheet, which isArch-action-based earth pressure

0.1∆x= 0 mm0.2

∆x=1.5 mm，0.3

shown in Fig. 3.

4.

0.0

Retaining wall experiments with/withoutsurcharge

線形 (at-rest earth pressure)
線形 (active earth pressure)

0.4
0.5
0.6
0.7
0.8
0.9

4.1 Instruments and experimental setup

1.0
0.0

0.1

0.2

0.3

0.4

0.5

Non-dimensional lateral active earth pressure,σ/γH

Totally 11 miniature pressure cells (Fig. 4) were

Fig. 6 Changes of lateral earth pressure from at-rest to
active conditions along the depth in normalized scale

embedded flush to the surface of retaining wall and the391Table 2 Retaining wall experiments without surcharge
Test

9
10
11
15

Height ofwall
H (mm)
300
350
200
250

Amount ofpressure
cell
7
8
6
5

Bulk
densityρ (kg/m3)
1242
1224
1206
1219

4.3 Retaining wall experiments with surcharge

Relative
densityDr (%)
28
22
17
21

Experiments were conducted by following the sameprocedure of retaining wall experiment without surcharge.
What the difference is surcharge was loaded after
finishing sand ground preparation. Bearing ball with adiameter of 12.68 mm was used as surcharge and loadedon the surface of sand ground in 3 times with a total
weight 6 kg. Another 4 tests with height of backfill 350,
300, 250 and 200 mm were conducted. In the initial state,
at-rest earth pressure shifts from Jaky’s theoreticalpressure due to surcharge. When retaining wall moved 2∆x=0.1mm∆x=1.5mmmm outward, active earth pressure decreased but with no∆x=2.0mm

agreement with the distribution of arch-action based
earth pressure, which means there was low influence
from arching between Teflon sheet and retaining wall.

5.
∆x=0.1mm∆x=1.5mm

Conclusions

The observed lateral pressure acting on Teflon sheet did∆x=2.0mm

not indicate a strong arch action like what achieved inFig. 7 Vector displacement and contours of shear strain
analyzed in Test 9, 10, 11 and 15

the previous study using sandpaper; therefore, theexperimental results satisfied with arch-action based
theory indicating that the smoother the surface, the closer

When retaining wall started to move, the magnitudes ofthe profile of lateral active earth pressure approaches toearth pressure decreases gradually. This decrement

Rankine’scontinues until “active wall movement” (∆xa), referring

activeearth

pressure.

Bothvectordisplacement and shear strain contour obtained from PIV

to the state when the measurements on every pressure

analysis showed a clear distinction between stationary

cells reach nearly constant values and do not change

and failure zones. Active wall movement observed bymuch despite further wall movement. Average of ∆xa inpressure cells agreed with that observed by PIV with theevery test is around 1.75 mm. Changes of lateral earthsame value independent of depth of backfilled sand andpressure is plotted in Fig. 6, where at-rest pressure shows

surcharge. Therefore, the same pattern of pressure change

a good agreement with Jaky’s semi-empirical equation.

can be confirmed by both lateral earth pressure analysis

At the active wall movement of 1.5 mm, pressure of theand PIV analysis.

upper portions of the wall is slightly less than thetheoretical prediction by Eq.(3).

References

Vector displacement and contours of shear strain were

1) M.H. Khosravi, T. Pipatpongsa and J. Takemura

plotted in a range of panel 200 mm × 300 mm as shown in(2013), Experimental analysis of earth pressure against

Figs. 7, each of which showed vector displacement andrigid

shear strain contour for ∆x = 0.1, 1.5 and 2.0 mm using a

retaining

walls

under

translation

mode,

Géotechnique, Vol. 63(2), pp.1020-1028.

common scales. There are no significant change once ∆x2) J. Jaky, (1948), Earth pressure in silos, 2nd ICSMFE,

reaches to ∆xa=1.5 mm which is a value of active wall

pp. 103-107.

movement determined from pressure cells.
492

Fe-TiO2-MWCNT Composite Photocatalyst for Degradation of Methylene Blue
Student Number: 12M18206 Name: Hao ZUO Supervisor: Hirofumi HINODE

Fe-TiO2-MWCNT 複合触媒によるメチレンブルーの分解
左 皓
本研究の対象中国では、重化学工業を中心とした高度経済成長期に入ってからの大量生産、大量消費、
大量廃棄という自然の浄化力を上回る社会活動の流れの中で、種々の環境汚染問題が発生してきた。特に、繊維生産による染料の廃水は毒性が高く、生物による分解の可能性も比較的低いため、すでに生態系に深刻な環境被害をもたらしている。この現状を踏まえて、本研究では、鉄ドープ酸化チタンと多層
カーボンナノチューブ(MWCNT)を複合した新しい複合触媒 Fe-TiO2-MWCNT を開発することを目的としている。

1. Introduction

textile wastewater treatment is an applicationof photocatalyst through advanced oxidation
process (AOPs). Titanium dioxide (TiO2) is oneof the most efficient photocatalyst due to its
high stability, chemical inertness, non-toxicity,and low cost. Yet, efficient application of solar
irradiation for the photocatalysis is restricted
due to the limitation of TiO2 than can only be
activated under UV light due to its wide band
gap of 3.2 eV [3]. To increase the efficiency ofTiO2 by extending the activity into the visible
light range, TiO2 can be modified by dopingwith transition metal and modified by CNT.
In this research, the photodegradation of
methylene blue (MB), as a representative oforganic dye compounds due to its ubiquitouspresence in factory wastewater, under visible
light irradiation using the composite of Fe-TiO2
and multi-walled carbon nanotube (MWCNT)
photocatalyst will be investigated.

Recently, the rapid growth of industries
leads to the expansion of environmental
problems in China. One of the main
environmental problems is water pollution
from sources such as industries, agricultures,and households, which contain contaminants
such as organic and inorganic compounds [1].
In particular, textile wastewater is well-known
for its high variability of composition withintense colors, fluctuating pH values, highchemical oxygen demand (COD) and relatively
low biodegradability with large amount ofsuspended solids and dissolved salts. These
effluents deteriorate the aesthetics of receiving
water body and pose significant threat to thesurrounding ecosystem and human health.
Textile industry wastewater is usually treatedusing conventional physical methods such as
adsorption or biological technologies. Sludge
formation and large number of aromatic rings
present in organic dye compounds may cause
conventional biological treatment methods to
be ineffective for their mineralization.
Moreover, adsorption may be effective fordecolorization but the process only involves aphasetransferofpollutants
which
subsequently requires additional treatment or
disposal [2].
Recently, the new approach proposed for

2. Experimental
2.1. Cutting of MWCNT
As used MWCNT synthesized by chemical
vapor deposition (CVD) method contains manycatalysts [4], the raw MWCNT was put into 300
ml of concentrated HCl under magnetic
agitation for 5 h followed by filtration toeliminate these catalysts. The cutting
experiments were carried out as follows: 250
193mg of pretreated MWCNT was suspended in
300 ml of concentrated H2SO4 under magnetic
agitation for 30 min at room temperature thenadded by 180 ml of concentrated HNO3. Thenthe mixture was heated at 60℃ for 6 h. The cut

Elemental composition of the catalysts wasanalyzedbyenergydispersive
X-ray
spectroscopy (EDS). The Brunauer Emmett
and Teller (BET) adsorption-desorption of
nitrogen gas at the temperature of liquid
nitrogen to measure specific surface area was
performed on autosorb-1MP-Quantachrome.
Quantitative analysis of photocatalysts wasdone using Inductively Coupled Plasma-Atomic
Emission Spectrometry (ICP-AES).

MWCNT was collected using glass fiber filter
paper and washed with deionized water until
the pH value reach neutral.
2.2. Preparation of Fe-TiO2-MWCNT
Fe-TiO2-MWCNT was prepared by amodified sol-gel method using titanium
tetraisopropoxide (TTIP) as the Ti-precursor.
Iron nitrate (Fe(NO3)3・9H2O) was used as the

2.4. Photodegradation Experiments
The photocatalytic set-up is showed in Fig.
1. The experiments were carried out in a glass
photochemical reactor. The reactor was
equipped with a UV and visible light lamp (100W, 312-577 nm) located axially and held in aquartz immersion, equipped with a UV-cut film
which allows only visible light (400-577 nm) to
pass. The UV photodegradation experiments
were carried out without the UV-cut film andthe visible light photodegradation experiments
were carried out by applying the UV-cut film on
the lamp. For each run, 0.35 g of photocatalyst
was dispersed in 700 mL of methylene blue
solution with an initial concentration of 20
mg/L. Before irradiation, the MB solution withphotocatalyst was stirred in a dark condition
for 1 h to establish an adsorption-desorption
equilibrium.

metal precursor. 18.6 mL of TTIP washydrolyzed using 35.8 mL of glacial acetic acidat around 0℃. To this solution, Iron nitratesolutions (395 mL) with appropriate amount of
Fe of 0.25 mol%, 0.5 mol% and 1.0 mol% wereadded drop wise under vigorous stirring for 1 h,
subsequently the solution was ultrasonicatedfor 30 min and continued the stirring foranother 5 h until a clear pale yellow solution
was formed. Simultaneously, amount of cut
MWCNT of 10wt. %, 20wt. % and 30wt. % weremixed with 20 ml ethanol and ultrasonicatedfor 30 min. Subsequently, these parts were put
into the previous pale yellow solution andultrasonicated for another 30 min. After thisperiod, the solutions were placed in an ovenmaintained at a temperature of 70℃ for 12 h
for aging process. The gels were then dried at
100 ℃ and subsequently the catalysts werecrushed into fine powder and calcined at 500℃.
For comparison, undoped TiO2, Fe-TiO2 andTiO2-MWCNT
composites
were
also
synthesized using the same route.
2.3. Characterization of photocatalysts
Crystal structure and crystallite size of thephotocatalysts were determined by X-ray
diffraction spectroscopy (XRD). Morphology
and particle size were investigated bytransmission electron microscopy (TEM) andscanning
electronmicroscopy(SEM).

Fig. 1 Photocatalytic set-up
294

3. Results and discussion

parameters, it indicates re-arrangement of
atoms in the crystal of anatase structure by
substitution of metal dopants, most probably
because Fe being an element with smaller
atomic radius, in the TiO2 structure. The lattice
parameters
decreased
andeventuallystabilized in the event that maximum dopantloading is reached as shown in Figure 4 and 5.
The maximum dopant loadings to affect thelattice parameters were 0.5% and 0.5% for aand c, respectively.

3.1. BET and XRD Characterization
Table 1 shows the results of BET and XRD
of each Fe doped TiO2. It indicated that there
were some positive effects of Fe doped TiO2. Fe
doped TiO2 had higher specific surface area andsmaller crystal size. And Fe3+ also acted aselectron traps to decrease in electron-hole
recombination.
Table. 1 BET and XRD results

Fig. 3 Left: Plot of effect of Fe-doping onunit cell parameter a of anatase TiO2.
Right: Structure of anatase TiO2 crystal.

The XRD patterns showed that TiO2
present in the photocatalysts were anatase andno characteristic peaks indicating Fe phases or
its oxides were observed in the patterns.

Fig. 4 Left: Plot of effect of Fe-doping onunit cell parameter c of anatase TiO2.
Right: Structure of anatase TiO2 crystal.
3.2. Photodegradation of MB
Figure5showstheresultsofphotodegradation of MB using Fe doped TiO2
under UV-visible light irradiation. Commercial
TiO2 degussa P25 showed better photoactivity,
which can degrade 20 ppm of MB completely
within 120 min. Undoped TiO2 degraded 20
ppm of MB completely within 300 min. 0.5mol%
Fe- TiO2 degraded 71.7% of MB within 300 min
under UV-visible light irradiation.

Fig. 2 XRD patterns of Fe-TiO2
The effect of doping on the crystallinity ofanatase TiO2 was confirmed after further
analyzing the XRD data for the lattice
parameters a and c of anatase (a tetragonal
crystal) using the h, k, l and d values. Plotting
the % Fe doping against the unit cell
395

Fig. 7 MB degradation under UV-visible lightirradiation using Fe-TiO2-MWCNT

Fig. 5 MB degradation under UV-visible lightirradiation using Fe-TiO2

The results indicate that the presence of
MWCNT slightly enhances the photocatalytic
activity.

Figure6showstheresultsofphotodegradation of MB using Fe doped TiO2
under visible light irradiation. 0.5 mol%
Fe-TiO2 degraded 38.6% of 20 ppm of MB
within 300 min, which showed a better
photoactivity than undoped TiO2 under visible
light irradiation.

Fig. 8 MB degradation under visible lightirradiation using Fe-TiO2-MWCNT

4. Conclusion
Fe-TiO2-MWCNT composite photocatalyst
was synthesized by a modified sol-gel method.
The new catalyst was more effective than
Fe-TiO2 under visible light irradiation formethylene blue treatment by the synergetic
effect between Fe-TiO2 and MWCNT.

Fig. 6 MB degradation under visible lightirradiation using Fe-TiO2
Figure7showstheresultsofphotodegradation of MB using composite
photocatalyst under UV-visible light irradiation.
0.5mol% Fe-TiO2-20 wt.% MWCNT degraded
74.7% of 20 ppm of MB within 300 min underUV-visible light irradiation.
Figure8shows
theresultsofphotodegradation of MB using composite
photocatalyst under visible light irradiation.
0.5mol% Fe-TiO2-20 wt.% MWCNT degraded
42.6% of 20 ppm of MB within 300 min undervisible light irradiation.

Reference[1] Paruchai Pongwan et al. / ENGENEERINGJOURNAL, Volume 16 Issue 3[2] Yean Ling Pang et al. / Applied Catalysis B:
Environmental 129 (2013) 473-481[3] Shaari N et al. / JOURNAL OF RARE
EARTH, Vol. 30, No. 7, July 2012, P. 651[4] P.X. Hou et al. / Carbon 40 (2002) 81

496

Selective Catalytic Reduction of Nitrogen Oxides with Propene
over Metal Oxides mixed with (Ti,Zr)2O4 Catalyst
Student Number: 12M18181 Name: Dongil KIM Supervisor: Hirofumi HINODE

C3H6 を還元剤とした機械的混合法による(Mo,W)-(Ti,Zr)2O4 複合触媒の NO の選択還元
金

東一（キム

ドンイル）

本研究では、排ガス内に混在する炭化水素のプロペンを還元剤とした NO の選択還元 (HC-SCR) を目的とした触媒の開発を行った。担体として(Ti,Zr)2O4 を用い、Mo と W を用いて含侵法と機械的混合法によって調製した複合触媒の活性及び特性の変化について検討した。これらの複合触媒の中で機械的混合法によって調製された 30%MoO3+(Ti,Zr)2O4 触媒が 450℃で最大活性を示し、約 78%の NO 分解が達成できた。また、最大活性を示した触媒の実用面を考慮した水の影響や再利用性について述べる。

1

Introduction

2NO+O2 → 2NO2
3NO+3NO2+C3H6 → 3N2+3CO2+3H2O

Nitrogen oxides (NO, NO 2 and N2O) are major
sources of atmospheric environmental problems
such as photochemical smog, acid rain, ozone
depletion and greenhouse effects. Furthermore,presence of nitrogen oxides in the atmosphere cancause problems to human health. Most of the NOx
comes from automobiles (48.5%) and power plants(46.2%) using fossil fuels [1].
Nowadays, three-way catalysts (TWC) are
generally used to reduce NOx in automobiles. Thismethod can reduce NOx with high efficiency atspecific air to fuel (A/F) ratio. However, thedevelopment of lean-burn engines that havehigher fuel economy and cleaner emissions
requires catalyst for NOx reduction that canfunction also at higher A/F ratio which cannot be
achieved using TWC only. One potential method
to reduce NOx in exhaust gas is by selective
catalytic reduction of NO using hydrocarbon as
reducing agent (HC-SCR of NO) [2]. Among
several applicable methods, HC-SCR contained in
the exhaust is currently the most studied
technology for NOx reduction.
Previous study showed that TiO2 supported Mo
catalyst was effective in NH3-SCR of NO [3].
Compared with impregnated catalyst, manually
mixed MoO3+TiO2 catalyst showed more activity
for the selective catalytic reduction of NO by
NH3[4]. Similar with MoO3, WO3 can improvemechanical strength of the catalyst by acting as
chemical and structural promoters thus enlarging
the temperature window of the SCR reaction.
The main reactions taking place during SCR
process are the following:

(1)
(2)

Another study reported that (Ti,Zr)2O4
composite used as support material exhibited
higher catalytic activity towards HC-SCR of NO
when compared to bare TiO2 [5]. Also (Ti,Zr)2O4 isknown of its high BET surface area and highmechanical strength, and is widely used in many
reactions as catalyst[6].
Therefore, in this study, the catalytic activities
of (Ti,Zr)2O4 supported Mo and W catalysts wasstudied. Mo supported catalyst was prepared by
two different methods, impregnation (IM) andmanual mixing (MM). W supported catalysts wereprepared by MM method. (Mo-W)xOy+(Ti,Zr)2O4
metal combined catalysts were also investigatedfor comparison of the catalytic activity. They were
investigated for HC-SCR of NOx using propene as
reducing agent[7-9].

2 Experimental

2.1 Materials(Ti,Zr)2O4 catalyst was prepared by co-precipitation
methodusing
Zr(NO3)2.2H2O(Wako)
and[(CH3)2CHO]4Ti (Wako) as precursors with the same
molar ratio for Ti and Zr [4]. First, Zr(NO 3)2.2H2O was
dissolved in 35 ml of deionized water with continuous
stirring and the pH was controlled by addition of HNO3
(pH=0.5-1.0). Then [(CH3)2CHO]4Ti was added to thesolution and the pH was changed by addition of NH3
solution (pH=9-11). The resulting mixture was filtered,dried at 100℃ for 8 h and calcined at 550℃ in air for
4 h.

1

97

Fig.1 shows the conversion of NO to N2 over TiO2, ZrO2,
MoO3, (Ti,Zr)2O4 catalysts. (Ti,Zr)2O4 catalyst shows thehighest activity at 450 ℃ among all the catalysts
followed by ZrO2 and TiO2 while MoO3 and WO3
showed the lowest conversion to N2.

NOx conversion to N2[%]

In the case of IM method, (NH4)6Mo7O24.4H2O(Wako) was dissolved in 50 ml of deionized water andmixed with (Ti,Zr)2O4. Then the mixture was stirred atroom temperature for 12 h and dried at 80℃ for 12 h.
The catalyst prepared by IM method was designated as
Mo/(Ti,Zr)2O4.
In the MM method, Mo precursor used in IM method
was calcined first at 400 ℃ prior to mixing with
(Ti,Zr)2O4 prepared earlier. The mixing was carried out
by hand using mortar and pestle with a little amount of
ethanol. WO3 was used for preparing MM W supported
catalysts.
(NH4)6H2W12O40.xH2O was used as W precursor for
preparing metal combined catalyst. Both W and Mo
precursor dissolved in deionized water at the same time,and catalyst were prepared by sol-gel method.
All prepared catalysts were calcined at 550℃ in air
for 4 h. Finally, the catalysts were crushed and sieved to
0.71-1.00 mm [4]. The catalyst prepared by MM method
was designated MoO3+(Ti,Zr)2O4, WO3+(Ti,Zr)2O4,(W,Mo)xOy+(Ti,Zr)2O4.

10%
Mo/(Ti,Zr)2O4
20%
Mo/(Ti,Zr)2O4
200

300

400

500

600

NOx conversion to N2[%]

MoO3
WO3
600

Fig.1 Catalytic activity of bare catalysts for the reduction ofNOx conversion to N2 using C3H6 as a reductant

40
30
20
10
200

300

400

500

600

40%
MoO3+(Ti,Zr)2
O4
50%
MoO3+(Ti,Zr)2
O4

Fig.2 shows the conversion of NO to N2 overMo/(Ti,Zr)2O4 catalyst by IM method with Mo loadinglevels from 0-30 wt.%. Metal loaded catalyst showed
lower catalytic activity than unloaded (Ti,Zr)2O4 catalyst.
It is possible that the addition of Mo metal on the(Ti,Zr)2O4 support by IM method reduced the exposed
surface of (Ti,Zr)2O4 available for reaction thus reducing
its catalytic activity [3].
Fig.3 shows the conversion of NO to N2 over
MoO3+(Ti,Zr)2O4 catalysts by MM method with Mo
loading levels from 0-50 wt.%. Catalyst with 30% MoO3
showed the highest catalytic conversion at 450 ℃
followed by 10% and 20%. However, further increase of
Mo loading to 50% showed a decrease in activity ascompared to the bare (Ti,Zr)2O4 catalyst.
Fig.4 shows the conversion of NO to NO2 and theconversion of C3H6 to CO2 using the (Ti,Zr)2O4 and 30%

TiO2

0

50

Fig.3 Catalytic activity of MoO3+(Ti,Zr)2O4 IM method
catalyst for the reaction of NOx to N2 using C3H6 as a reductant

20
10

60

Temperature[℃]

ZrO2

30

70

100

(Ti,Zr)2O
4

40

80

0

Results and Discussion

50

30%
Mo/(Ti,Zr)2O4

30%
MoO3+(Ti,Zr)2
O4
10%
MoO3+(Ti,Zr)2
O4
20%
MoO3+(Ti,Zr)2O4(Ti,Zr)2O490

3.1 Catalytic Activity
NOx conversion to N2[%]

5%
Mo/(Ti,Zr)2O4

Fig.2 Catalytic activity of Mo/(Ti,Zr)2O4 IM method catalyst
for the reaction of NOx to N2 using C3H6 as a reductant

fixed-bed flow reactor. The reactant gas was composedof 1500 ppm NO, 10% O2, 1500 ppm C3H6 and He as abalance gas. 0.8~1.4 g catalyst was used with acorresponding space velocity of 13000 h-1 and a total gas
flow rate of about 4 mL/s. The temperature was changed
stepwise from 150℃ to 550℃.
NO and NO2 concentration were analyzed by NOx
analyzer (Shimadzu, NOA-7000). N2O, CO2 and CO
were analyzed by gas chromatograph (GL Science,
GC-323w for N2O; GL Science, GC-390 for CO2 andCO). The catalysts were characterized by TG-DTA, XRD,
N2 adsorption (Autosorb 1MP/TSU, BET analysis) andSEM-EDS.

200 300 400 500
Temperature[℃]1%
Mo/(Ti,Zr)2O4

Temperature[℃]

The SCR activity experiments were carried out in a

100

(Ti,Zr)2O4100

2.2 Catalytic Activity Test

3

50
45
40
35
30
25
20
15
10
5
0

2

98

50.00
45.00
40.00
35.00
30.00
25.00
20.00
15.00
10.00
5.00
0.00

NO conversion to NO2 [%]

6.00
5.00
4.00
3.00
2.00
1.00
0.00
100

200

300

400

500

value. There was no synergetic effect from Mo with W in
which the result of (Mo,W)xOy+(Ti,Zr)2O4 catalyst
showedlower
NOx
reducing
abilitythan
MoO3+(Ti,Zr)2O4 and WO3+(Ti,Zr)2O4.
It was reported by Ch. Fountzoula et al.[3] that
addition of MoO3 to bare catalysts improves its
mechanical strength through chemical and structural
promotion which enlarges the temperature window of the
SCR reaction. The synergistic effects could also be
observed in the result of this study by comparing MoO3and (Ti,Zr)2O4.

C3H6 conversion to CO2 [%]MM method MoO3+(Ti,Zr)2O4 catalysts. Addition of
30%Mo by MM method increased the conversion of
C3H6 to CO2 while decreasing the conversion of NO to
NO2. This suggested that addition of Mo improved theselectivity of NO reduction to N2 as shown in Fig.3.

3.2 Catalyst Characterization

600

temperature [℃](Ti,Zr)2O4 NO→NO2
30% MoO3+(Ti,Zr)2O4 NO→NO2(Ti,Zr)2O4 C3H6→CO2
30% MoO3+(Ti,Zr)2O4 C3H6→CO2

Fig.4
Catalytic
activity
of(Ti,Zr)2O4,
30%MoO3+(Ti,Zr)2O4 catalyst for the conversion of NO to
NO2 and C3H6 to CO2 using C3H6 as a reductant
30%MoO3

90+(Ti,Zr)2O4

70(Ti,Zr)2O4

60

Fig.6 XRD patterns of Mo supported (Ti,Zr)2O4 catalyst
prepared by IM method.

50

30%WO3+40

Fig.6 showed that formation of binary-type oxides
such as Zr5Ti7O24 and Zr(MoO4)2 on the surface
deactivated the NOx reduction performance.

(Ti,Zr)2O4

30
30% Mo9-

20

W1 +

10
0
100

200

300

400

Temperature[℃]

500

600

250

(Ti,Zr)2O4
1%Mo /

Specific surface area [m2/g]

NOx conversion to N2[%]

80(Ti,Zr)O4

Fig.5 Catalytic activity of various kind of Mo, W MM
(Ti,Zr)2O4 catalyst for the conversion of NOx to NO2 and C3H6
to CO2 using C3H6 as a reductant

This time, 30%MoO3+(Ti,Zr)2O4 catalyst showed
highest catalytic activity than other metal supported(Ti,Zr)2O4 combined catalyst. Fig.5 gives us an overview
of catalytic activity changes and comparison of eachcatalysts conversion property. WO3 shifted bare
(Ti,Zr)2O4 catalysts’ optimal temperature to a higher

200
Ideal

150

real

100
0

10

20

30

40

50

60

Molybdenum oxides ratio [%]Fig.7 BET results of MoO3+(Ti,Zr)2O4 catalyst prepared by
MM method.

3

99

time, second time and third time usage is shown in Fig.9.
The NO reduction performance decreased with thenumber of use, and C3H6 oxidation also shown the same
pattern. However, at 500℃, despite the decrease in NO
reduction performance, C3H6 oxidation performance notchanged. It was thought that for repetitive usage, the NO
reduction mechanism via NO2 become weaker, thus, thedecrease in NO conversion did not followed by decreasein C3H6 conversion.

From the specific surface area (SSA) of bare MoO3and (Ti,Zr)2O4, the SSA of catalysts prepared by MM
method can be calculated. It was based on the ratio of
each constituents (Ideal value). But as shown in Fig.7,
the real value of SSA showed lower value compared to
calculated value of SSA. It was thought that MoO3
particles enter the pores of (Ti,Zr)2O4, thus the actual
SSA value was lower than the calculated one.

3.3 The Effect of Water Vapor
90

Conversion Ratio[%]

4 Conclusions

0%H2O NO → N280

The catalyst prepared MM method MoO3+(Ti,Zr)2O4
catalyst showed catalytic activity towards selective
catalytic reduction of NO to N2 with C3H6 as reducing
agent. Compared to the IM method, catalyst prepared by
MM method exhibited higher catalytic activity. The
catalysts prepared by MM method showed optimum ratioof Mo addition at 30%. It is possible that MoO3 highoxidation ability improved the catalytic activity of
MoO3+(Ti,Zr)2O4 as suggested by previous study.
Manually mixed WO3 or (Mo,W)xOy with (Ti,Zr)2O4
catalyst showed catalytic activity loss compared to thebare (Ti,Zr)2O4 because of its formation of binary-typeoxides on the catalyst surface.

70
60

10%H2O NO → N2

50
40

0%H2O C3H6 →
CO2

30
20
10
0
100

200

300

400

500

600

10%H2O C3H6 →CO2Temperature[℃]

Fig.8 The effect of Water vapor to the NOx reduction andC3H6 oxidation performance of 30%MoO3+(Ti,Zr)2O4 catalyst

References

Fig.8 showed the influence of water vapor to theperformance of the catalyst. The presence of water vapor
makes not only lower the reduction of NO to N2, but also
lower the oxidation of C3H6 to CO2.

[1] Norio Arai Techno-System Corp (1997)[2] R.Burch et al, Appl.Catal.B, 11, (1997) 207[3] Ch.Fountzoula et al, Appl, Catal. B, 35, 295(2002)[4] P.Forzati et al, Catal. Today, 62 (2000) 51[5] M.Haneda et al, Catal. Today, 42, 127-135(1998)[6] B.M.Reddy et al, Appl. Catal. A, 228 (2002)
269-278[7] J.Mitadera, Master Thesis, Tokyo Institute ofTechnology (2003)[8] H.Kawai, Master Thesis, Tokyo Institute ofTechnology (2004)[9] M.Makii, Master Thesis, Tokyo Institute ofTechnology (2008)

3.4 The Reusability of the Catalyst

Fig.9 Comparison of NO reduction and C3H6 oxidation
activity of catalyst at first, second, third time usage

The comparison of activity of catalyst during the first

4100

Wastewater Treatment by Adsorption with Activated Carbon
from Wood Residues in Rubberwood Sawmilling Process
Student Number: 12M18169 Name: Xiao HAN Supervisor: Ryuichi EGASHIRA

ゴム木材製材プロセスにおける残材由来活性炭を用いた吸着による排水処理
韓笑東南アジアのゴム木材製材プロセスの改善ために、残材の熱処理生成物である木酢液を木材の防腐剤，活性炭を防腐剤の排水を処理するための吸着剤として利用する新たなプロセスに対し、使用済み活性炭の処理について検討した。ゴム木材おが屑を熱処理して得られた活性炭及び使用済み活性炭を熱再生して得られた再生活性炭のキャラクタリゼーション及びフェノールとクレゾールを含むモデル排水に対する回分式吸着実験を行った。再生活性炭の吸着性能は未使用活性炭よりも低い吸着性能であった。使用済み活性炭の処理を考慮した製材プロセスのシミュレーション計算を行い，必要なおが屑の量が実現可能な範囲内にあることを示した。

Exit
(PA)
Tar

Heat
generation 1

Wood
residues

Steam: Material flow
: Energy flow
: Current process: Proposed process
Exit(wood residues)

Thermaltreatment

CPA

Products

AC

Wastewater
treatment

Waste water

Molding

Preservation &DryingRubberwood

Cutting /Band sawing

PA

Off-gasTreated
water
Spent
AC

Heat
generation 2

In Southeast Asian countries, rubberwood
furniture manufacturing is an important industry. The
current sawmilling process includes the process
shown by black boxes in Fig.1. Rubberwood logs are
cut, preserved and dried, then molded into products.
Two major problems were reported in the existingprocess; the utilization of toxic preservatives, andlarge amount of wood residues [2]. The preservatives
contain the harmful compounds such as boric acidand mixture of borax pentahydrate and the workers
are exposed to these harmful compounds. In addition,
the waste water, containing the preservatives, isdischarged without any treatment, which causes soil
and water pollutions.
To solve these problems, the utilization of the
products from thermal treatment of wood residues(WR) was proposed. The proposed process is shownin Fig.1. It was suggested that the wood residues
were thermally treated to produce pyroligneous acid(PA), activated carbon (AC), and off-gas, and theseproducts were effectively utilized in the process[1][2]. Pyroligneous acid was characterized tocontain the components effective for preservations,and it can be used as preservative agent instead of thecurrent purchased preservative agent. However someof the chemical components in pyroligneous acid arenecessary to be removed from the wastewater of thepreservation. So, the wastewater is treated by the
prepared activated carbon to meet the regulation of
the wastewater. After treatment of the wastewater,
the spent activated carbon (SAC) should be obtained
and the treatment of it has not been discussed inprevious studies.
In this work, the waste water treatment using
activated carbon was studied, in which the treatmentof the spent activated carbon was incorporated in the

distillation

process. The virgin activated carbon (VAC) was
obtained by thermal treatment of WR sawdust, andspent activated carbon was prepared by adsorption ofphenol with virgin activated carbon. Thermal
regeneration of spent activated carbon was carriedout to obtain the regenerated activated carbon (RAC).
The adsorption of phenol and p-cresol in the aqueous
solution by virgin activated carbon and regenerated
activated carbon were conducted to measure thechange in the adsorption capability. Then the processincorporating the treatment of spent activated carbon
was evaluated based on the material and heatbalances.

1. Introduction

Exit
(AC)

Fig. 1 Current and proposed process of sawmilling:material and heat flows

2. Activated Carbon from Wood Residues
2.1 Experimental
Wood residue, obtained from Malaysia, wasthermally treated under steam atmosphere by thethermal treatment equipment, as shown in Fig. 2 [3],to obtain the virgin activated carbon. Virgin activatedcarbon was treated by adsorption with phenol
101aqueous solution to obtain spent activated carbon.
Next, thermal regeneration of spent activated carbon
was carried out using the same equipment shown in
Fig. 2 to prepare regenerated activated carbon underN 2 atmosphere. Thermal regeneration was chosen inthis study because it was a commonly used
regeneration method. Table 1 and 2 show the
principal conditions of thermal treatment andregeneration.
Experiments were also conducted to examine thecharacterization of the activated carbons. Scanningelectron microscope (SEM) was used to observe theappearance of the activated carbon surface. The
elemental analysis was conducted to measure thecomposition of the activated carbons. The specificsurface area was measured by a surface area
measuring instrument.

H2O

(7)

(5)

(3)

Non-condensable
gas

(6)
(7)

Thermal treatment of wood residues produced
crude pyroligneous acid, virgin activated carbon andoff-gas. The colour of crude pyroligneous acid wasdark brown and water content was about 80%. It was
because it contained a lot of tar components. All
wood residues were evenly treated to virgin activatedcarbon. Virgin activated carbon was black in colorand lighter in mass if compared with feed wood
residues. Off-gas was non-coloured gas with a badsmell. Mass of obtained virgin activated carbon,
crude pyroligneous acid, and off-gas were about 21%,35% and 44% of the feed sawdust, respectively. Massof off-gas was derived based on material balance.
From the SEM pictures of virgin activated carbon
and regenerated activated carbon, it was found thatparticle size of the regenerated activated carbon was
smaller than that of the virgin activated carbon. The
results of elemental analysis were showed in Table 3.
The content of oxygen could not be measured thistime because too much ash content in them. In thecase of activated carbon made from plants, it usually
had a low content in sulphur and nitrogen [4]. The
results of this experiment agreed with this trend.
Specific surface area of virgin activated carbon,
spent activated carbon and regenerated activatedcarbon were 582.54, 42.91, 271.19 m2/g,
respectively. After adsorption of phenol, the surface
area of virgin activated carbon was obviously
reduced. The possible reason was that phenol might
occupy the pores of the activated carbon.

T.I.

(1)
(4)

2.2 Results and Discussion

(2)

(8)

F.I.
(9)
N2

(10)

Fig. 2 Schematic diagram of thermal treatment apparatus:(1) tubular reactor; (2) electric tubular furnace; (3) sample
holder; (4) feed/solid product; (5) NiCr-Constantan
thermocouple; (6) micro-plunger pump; (7) valves; (8)condensers; (9) liquid product trap; (10) iced bath(275~277 K); F.I. flow indicator; T.I. temperature
indicator

Table 3 Element analysis of RW, AC and RAC
Element
[wt%]
RW
AC
RAC
C
45.8
87.27
92.5
O
44.77
H
5.61
1.72
0.39
N
0.19
0.4
0.47
Ash
0.7
3.9
2.7

Table 1 Principal conditions for thermal treatment ofwood residues
FeedWR
Mass of feed [g]30.0 ± 1.0
Atmosphere
N2, H2O
Flow rate of atmospheric <473 K 0.003 (N2)>473K0.0012(N2), .003(H2O)
gas [m3∙h−1]
Temperature [K]873
Holding time [h]13. Batch adsorption of Model Wastewater by
Activated carbon from Wood Residues
3.1 Experimental
In this study, in order to compare the adsorption
performance of virgin activated carbon andregenerated activated carbon, phenol or p-cresol
solution was chosen as the model wastewater,
because they were typical harmful substances of thepyroligneous acid. Activated carbon was washed,dried, ground and sieved before adsorption
experiments to equalize the properties of it. The
batch adsorption experiment was conducted using a
vessel with magnetic stirrer. Contacting time was
decided as 120 hours according to pervious study [3].

Table 2 Principal conditions for thermal treatment of
SAC
Feed
SAC
Mass of feed [g]12.0 ± 1.0
Atmosphere
N2
Flow rate of atmospheric<473 K 0.003 (N2)gas [m3∙h−1]
Temperature [K]1223
Holding time [h]0102After reaching adsorption equilibrium, the sample
solutions were analyzed by gas chromatograph(GC-2010 with FID, Shimadzu Co., Ltd.) todetermine the concentration of the solution. The
experimental conditions are shown in Table 4.

activated carbon, and adsorption isotherm could be
described by Langmuir equation.
The saturated amount of adsorption is shown in
Table 5. Adsorption amount of phenol and p-cresol
were almost the same. The adsorption amount ofregenerated activated carbon was about 10% of
virgin activated carbon.
From the results mentioned above, we propose totreat spent activated carbon as energy source,
because the efficiency of regenerating it is not very
good.

Table 4 Principal conditions for adsorption with stirring
vesselAqueous solutionof phenol
Aqueous solutionof p-cresol

Volume of feed solution [m3]Concentration of phenol in feedsolution,, C0 [g∙m−3]
Adsorbent
Particle radius AC, dp [µm]Concentration of adsorbent,
CAC [g∙m−3]
Stirring speed [rpm]Contacting time [h]Contacting temperature [K]250 × 10-6
540
AC
0.15-0.35

0.14

30000

0.12

500
120
303

0.1

q[g/g-VAC]

Feed solution

3.2 Results and Discussion

VAC_phenol

0.06

RAC_phenol

0.04
0.02
0

The mass balance relation in the adsorption
experiments can be expressed as,

0

500

1000

Ce [g/m-3]

L0C0  L0C1  S 0 q1

Fig.3 Adsorption isotherm for phenol by VAC and RAC

Ce q  K L
1  Ce K L

0.14
0.12
0.1

q[g/g-VAC]

L0, C0 , C1 , S0 , and q1 are the volume of feedsolution[m3],
feed
concentration[g/m3],
concentration of the solution after equilibrium [g/m3],
mass of the activated carbon [g], and amount ofadsorbate on activated carbon [g/g-activated carbon],respectively. The adsorption amount of each sample
was calculated by this equation.
Langmuir equation expressed blow was used tofind saturated amount of adsorption:

q 

0.08

0.08

VAC_cresol

0.06

RAC_cresol

0.04
0.02
0
0

500

Ce
Ce, q,q∗ ,KL are concentration of the solution after
equilibrium [g/m3], adsorption amount for 1g
adsorbent [g/g-activated carbon], the saturated
amount of adsorption for 1g adsorbent, and Langmuir
equilibria constant, respectively.
Based on the adsorption results, adsorption
isotherms of phenol with virgin activated carbon andregenerated activated carbon are shown in Fig. 3, andthose of p-cresol are shown in Fig. 4. The lines show
adsorption isotherm calculated, and the plots show
the experimental data. In this study, more than 80%
of model harmful substance was adsorbed by virgin

1000[g/m-3]Fig. 4 Adsorption isotherm for p-cresol by VAC and
RAC

Table 5 Saturated amount of adsorption
VAC
0.10838q∗phe[g/g-AC]
0.12423q∗cre[g/g-AC]

103

RAC
0.01147-

amount of activated carbon required. In this case, 32
ton/year excess pyroligneous acid could be obtained,
and 772 ton/year wood residues will be left.
Minimum residue ratio could be calculated as 0.044
in this case.

4. Improvement of Rubberwood Sawmilling
Process
4.1 Overview of the process
In this study, the simulation calculation was basedon the assumption that all the spent activated carbon
is used as energy source in heat generation2 process.
In heat generation2, off-gas and spent activatedcarbon will be used preferentially, then wood
residues will be used. The rest of wood residues will
get out of the system. Residue ratio αwr,Th means theratio of wood residues using for thermal treatment tototal wood residues. Possible range of αwr,Th was
calculated from material balance and heat balance ofthe proposed process.

:FWr,Exit

4.2 Calculation
In this study, toxic component in wastewater was
assumed to be only phenolic components. The
concentration of phenolic components in waste water
was considered, because adsorption of unfavorable
substance in wastewater was affected by not only
activated carbon adsorption performance, but also
the concentration of the substance. Since previous
study reported that there were 2.7% of phenolic
components existed in pyroligneous acid [1]. The
concentration of that in wastewater could be
calculated as 499ppm. The standard concentration ofwastewater in Malaysia is 1ppm [1]. By using thedata mentioned above, activated carbon amount in
wastewater treatment process could be calculated.
Flow rate of feed rubberwood was supposed to be1000 ton of a year.
The yield and other characteristics of products
were based on experimental results of this study andprevious study [3].

Fig. 6 Flow rate change of exited wood residues

5. Conclusion

4.3 Results and Discussion
FWr,Exit means the flow rate of wood residues which
get out of the system, and the change of it is shown in
Fig.6. In this figure, if FWr,Exit become minus, itmeans the necessary heat for the whole process can’t
be covered by using the products from thermal
treatment of wood residues. Maximum residue ratio
could be calculated from this figure as 0.53. In thiscase, no wood residue is left, 749 ton/year excess
amount of pyroligneous acid and 102 ton/year excess
amount of activated carbon could be obtained.
If excess amount of pyroligneous acid is 0, namely,
the amount of pyroligneous acid produced equal tothe amount of pyroligneous acid required. In this case,activated carbon produced couldn’t cover therequirement.
If excess amount of activated carbon is 0, namely,
the amount of activated carbon produced equal to the104

Model harmful substance could be removed by
activated carbon made from wood residues.
The adsorption isotherm results showed that theadsorption amount of regenerated activated carbon
was about 1/10 of that of virgin activated carbon.
Therefore, it is concluded that regenerated activatedcarbon didn’t have sufficient adsorption capacity
compare to virgin activated carbon. So spentactivated carbon was proposed to be used as energy
source.
Based on the experimental data obtained from thisstudy, the possible range of residue ratioαwr,Th was
calculated. In some cases, excess amount ofpyroligneous acid and activated carbon could beobtained. The process was proposed to solve theenvironment problems in rubberwood sawmilling
process.
References[1] Rizafizah OTHAMAN, Kean Giap LIM, Shunsuke KONISHI,
Masayuki SATO, Nan SHI and Ryuichi EGASHIRA, “Thermal
Treatment of Wood Residues and Effective Utilization of Its
Products to Improve Rubberwood Manufacturing Process,” Journalof Chemical Engineering of Japan, pp. 1149–1158 (2008)[2] Rizafizah Binti Othaman, Doctor Thesis, Tokyo Institute ofTechnology (2009)[3] Mitani Saori, Master Thesis, Tokyo Institute of Technology(2011)[4] 真田雄三・鈴木基之・藤元薫；活性炭 基礎と応用，講談社サイエンティフィック（2007）

Recycling of valuable metals by solvent extraction using carboxylic acid as extractant
Student number: 12M18100

Name: Kazuma NAKAMURA

Supervisor: Ryuichi EGASHIRA

カルボン酸抽出剤を用いた溶媒抽出法による有価金属のリサイクル
中村 数馬
安価であり分子中にリンを含ないことで廃溶媒の焼却処分が可能なカルボン酸の一種であるネオデカン酸を抽出剤として，希土類磁石構成金属元素であるジスプロシウム，ネオジム，コバルト，および鉄の回分平衡抽出を行った．他の金属と比較して鉄の分配比は著しく高く容易に除去でき，この性能は現在工業的に利用されている有機リン酸系抽出剤の場合に比較して高かった．また，有機溶媒相からの金属の逆抽出に利用する酸の量を低減できた．最後に，希土類磁石リサイクルにおけるカルボン酸抽出剤の利用を提案した．

1. INTRODUCTION

2. EXPERIMENTAL

Recovery of valuable metals such as rare metals isgreatly attracted because of increasing their demands
and escalating their prices. But recycling them is difficult and costly. Therefore, large number of research
activities has been reported to improve the recycling
technology [1] [2]. The recovery of valuable metals from
Nd-Fe-B magnets scrap is a representative example,
andthesolvent
extraction
withacidicorganophosphorous ester as extractant has been intensively studied. Table1 shows the typical compositionof Nd-Fe-B magnets[3]. Acidic organophosphorous
ester, such as PC-88A and D2EHPA are most popular
extractants in the industrial application and they havehigh selectivity between rare earth metals, but theycause waste water pollution because they has phosphor
in their structure. Moreover, due to their strong affinity
with major impurity, Fe3+, the recovery of Fe3+ fromthe loaded organic solution should require large
amount of acids.
In this study, the recovery of valuable metals in
Nd-Fe-B magnet was studied by the solvent extraction
with carboxylic acid as extractant. Carboxylic acid canbe incinerated, and stripping of Fe3+ was easier thanthat with organophosphorous ester extractants[1]. Fe3+,
Dy3+, Nd3+ and Co2+ were selected as representative
elements in the magnet to investigate the solvent extraction with neo-decanoic acid, one of carboxylic acid. The extraction equilibria of single and binary metal
solutions were measured to study the effects of theexperimental conditions on the extraction and stripping behaviors for the purpose to make the valuable
metal recycle process from Nd-Fe-B magnet scrap byusing carboxylic acid as extractant.

The experimental conditions of extraction equilibrium are shown in Table 2. Neo-decanoic and naphthenic acids are mixtures of carboxylic acids. PC-88A(2-ethylhexyl phosphonic acid mono-2-ethylhexyl ester) and D2EHPA (Bis(2-ethylhexyl) phosphoric acid)are acidic organophosphorous ester extractants. Kerosene was used as the diluent of the extractant. The
aqueous solutions of the metals were prepared by dissolution of metal chloride in deionized water. The pH
in the aqueous phase was adjusted by NaOH and HCl.
The experimental condition of stripping equilibrium isshown in Table 3. The feed organic phases of 10vol%extractant loaded by single metal ion were prepared byextracting the metal from the aqueous solution. HCl or
HNO3 was used as stripping reagent.
All experiments were carried out in a 50mL conical flask with screw top. Equal volumes (10mL) of
aqueous and organic solutions were stirred with thermostatic bath for 3hours at 303K to attain the equilibrium. After equilibrium, these two phases were separated by separating funnel. The pH value in the aqueous phase was measured by digital pH meter (F-52,
HORIBA). The concentration of metal in aqueous
phase was determined using ICP-AES (SPS7800, SII
Nano Technology), and that in organic phase was calculated by material balance.
Table2 Experimental conditions of batch extraction equilibrium
Mn+(Fe3+,Dy3+,Nd3+,Co2+ )chloride
Neo-decanoic, naphthenic (NA)
PC-88A, D2EHPA
Diluent
kerosene
Initial metal concentration in aqueous phase ,Ci,aq,0[kmol･m-3]: 0.001
Extractant concentration in organic phase [vol%]: 10~30

SoluteExtractant

Table1 Typical composition of Nd-Fe-B magnets

Table3 Experimental conditions of stripping experiment

Rare eart h

Fe

B

Co

Cu

ave[wt%]

66

1

2

0

max

69.6

1.11

3.66

0.23

27.6

min

61.6

0.95

0.54

0.11

18.6

Nd

Dy

Pr

Tb

23

5

3

0

7.67

6.48

1.61

2.97

0.26

0

SoluteMn+(Fe3+,Dy3+,Nd3+, Co2+ )chloride
Extractant
Neo-decanoic acid, PC-88A
Stripping agent
HCl, HNO3
Initial metal concentration in organic phase,Ci,org,2[kmol･m-3]: 0.001
Initial extractant concentration in organic phase [vol%]: 10
Initial concentration of stripping agent,CHCl,aq,2 orCHNO3,aq,2 [kmol･m-3]:
0.01~731

1105

In this experiment, the concentrations of metal weremuch lower than that of extractant, CRH,org were assumed to be a constant. The logCi,org was plottedagainst (logCi,aq+nipH) in Fig. 1(a), and xi was decided
as unity. However, the plot of Fe3+, Dy3+ and Nd3+ results didn’t follow the slope in high acidity region.
Different reaction might occur and the extraction wasenhanced in this region. When xi=1, Eq(7) can be
written as,

3. RESULTS AND DISSCUSSTION
3.1. Solvent extraction with various extractant
The material balance equations for extraction andstripping equilibrium measurements can be expressedas,Ci,aq,0Vaq+Ci,org,0Vorg = Ci,aq,1Vaq+Ci,org,1Vorg
Ci,aq,2Vaq+Ci,org,2Vorg = Ci,aq,3Vaq+Ci,org,3Vorg
The distribution ratio, extraction yield, and strippingyield of component i, were defined respectively as,
Eq(1)

Eq(8)

Eq(2)

The mi and Kex,i could be obtained from the slope andintercept of the plots of logDi-nipH against logCRH,org,(Fig.1. (b)) and they are listed in Table 5.
Eq(4) can be rewrite using Kex,i as,

Eq(3)

Eq(9)

Ci,org,1 and Ci,org,3 were calculated with an assumptionthat the volumes of aqueous and organic phases wereconstant before and after the experiment.
The separation factor of component i relative tocomponent j, i,j was defined as,
Eq(4)Separation factor can be obtain by substitute Kex,i andni,nj.

The half extraction pH values (pH1/2) for the extraction with single metal solutions with various
extractant are listed in Table 4. The pH1/2 was definedas the pH value at Di=1. Neo-decanoic acid could
preferably extract Fe3+ in the range of high acidity relative to other metal ions, such as Dy3+, Nd3+ and Co2+.
PC-88A showed the better performance to separate
Dy3+ and Nd3+.

= 2.25×106 (obtained by substitute CRH,org=0.32, pH=5)

The separation factor of Fe3+ to Dy3+, and that of
Nd to Co2+ were enough large to be possible to separate each other. Dy3+ and Nd3+ can be separated byusing multistage extraction system.
3+

Fe
Dy3+
Nd3+
Co2+

Neo-decanoic
2.36
4.64
5.01
6.39

NA
2.21
4.47
4.89
6.21

PC-88A
-0.15
0.54
1.29
3.37

(a)

0

logCi,org

(b)

3+

Fe
Dy3+
Nd3+
Co2+

Fe3+
Dy3+
Nd3+
2+
Co

logDi - nipH

1

Table4 List of pH1/2 with each extractant (10vol%) on extraction of Fe3+, Dy3+, Nd3+, Co2+.
3+

-5

2

-10

-1
-2
-3

D2EHPA
-0.48
0.09
0.60
2.79

-15

-4
-5

5
10
logCi,aq+ni pH

-0.8

-0.6

-0.4
-0.2
logCRH,org

0

Fig.1 Extraction of Fe3+, Dy3+, Nd3+ and Co2+ with
neo-decanoic acid as extractant

3.2. Extraction equilibrium with neo-decanoic acidAs reported in previous paper [4], extraction equilibrium with carboxylic acid can be represented by
Eq(5).

Table5. Composition of extracted species and obtained Kex,i

i
Fe3+
Dy3+
Nd3+
Co2+

Eq(5)

where xi, mi, and ni stand for polymerization number ofextracted species, solvation number of extractant to
extracted species, valence of metal, respectively. The
extractants were assumed to exist as dimmer in theorganic solution. The extraction equilibrium constantcan be expressed as,Extracted species
FeR3･3RH
DyR3･3RH
NdR3･3RH
CoR2･2RH

Kex,i6.43×10-6
1.26×10-13
1.74×10-14
4.37×10-12

3.3. Extraction of binary metal solution with
neo-decanoic acid
Extraction of binary metal solution in some representative systems, such as (i) Fe3+ and Dy3+, (ii) Fe3+
and Co2+, (iii) Dy3+ and Nd3+, (iv) Dy3+ and Co2+ werecarried out to investigate the effect of coexistence
metal on extraction equilibrium.
F.M.Doyle et.al.[5] reported that extraction of somemetal ions(Ni2+, Zn2+, Cu2+ etc) increased with Fe3+
extraction in sulfuric acid solution at high acidity re-Eq(6)Eq. (6) can be written as,
Eq(7)

2

106

neo-decanoic acid solution was larger than that from
PC-88A solution. The yields of Co2+ were same between neo-decanoic acid and PC-88A. It means that
stripping from neo-decanoic acid solution was easierthan that from PC-88A. Stripping of Fe3+ from
PC-88A solution required higher acidity solution.
However higher acidity solution should degrade thequality of organic solution and corrosion-resistanceequipment should be necessary.

gion when neo-decanoic acid was used as extractant.
Figures 2~5 show the effects of the acidity on theextraction yield and distribution ratio of metals. Whiteand black plots represent the extraction results withsingle metal solution, and binary solution, respectively.
Distribution of Co2+ increased with distribution of Fe3+
and Dy3+ in high acidity region and separation efficiency was reduced. It means that Co2+ is co-extractedwith other metal such as Fe3+, Dy3+, and Nd3+.
3

0.8

2

logDi [-]

1
1.0

0.4

0

-1

0

-2

3

4
pH

5

6

7

1

2

3 pH 4

5

6

0.2

3+

Fig. 2 Extraction behavior of Fe and Dy from binary or single metal solution by using neo-decanoic acid
1
1.0
1
0

logDi [-]

Ei [-]

0
0

1

-1
-2

0
1

-3
1

2

3

4 5
pH

6

7

2

3

4 5
pH

6

7

1

logDi [-]

E [-]

0.6
0.4

0.6
0.5
0

Dy(binary)Nd(binary)Dy(single)
Nd(single)

0.8
0

0.8
0.7

Fig.3 Extraction behavior of Fe3+ and Co2+ from binary or single metal solution by using neo-decanoic acid1.0
1

Neo-decanoic(HCl)Neo-decanoic(HNO3)
PC-88A(HCl)
PC-88A(HNO 3)

0.9

YNd [-]

0.2

2
4
6
8
CHCl,aq,2, CHNO3,aq,2 [kmol・m-3]

Fig.6 The effect of acid concentration on striping yield of Fe3+
Stripping reagent: HCl, HNO3Fe(binary)Co(binary)Fe(single)
Co(single)

0.8

0.4

0.6
0.4

3+

0.6

Neo-decanoic (HCl)Neo-decanoic (HNO3)
PC-88A (HCl)
PC-88A (HNO 3)

0.8

1

0.2
2

1

YFe [-]

Ei [-]

0.6

Fe(binary)Dy(binary)Fe(single)
Dy(single)

2
4
6
CHCl,aq,2 ,CHNO3,aq,2 [kmol/m 3]

8

Fig.7 The effect of acid concentration on striping yield of Dy3+.
Stripping reagent: HCl, HNO3
1

-1

Neo-decanoic(HCl)Neo-decanoic(HNO3)
PC-88A(HCl)
PC-88A(HNO 3)

0.2
0.8

4

4.5
pH

5

4

4.5
pH

5
YCo [-]

0

Fig.4 Extraction behavior of Dy3+ and Nd3+ from binary or single metal solution by using neo-decanoic acid

0.6

0.4

1
1.0

1

Dy(binary)Co(binary)Dy(single)
Co(single)

0.8

0.2
0

logDi [-]

0Ei [-]

0.6
0.4

Fig.8 The effect of acid concentration on striping yield of Co 2+.
Stripping reagent: HCl, HNO3

-1

0.2
0

3.5. Separation process
From the experimental results, we made a proposalof the separation process of Fe3+, Dy3+, Nd3+ and Co2+
from Nd-Fe-B magnets by using neo-decanoic acid as
extractant, as shown in Figure 9. This separation process was proposed by the following rules; (i) to use
low amount of NaOH or HCl to adjust the pH, (ii) to
use relatively weak acid to strip the metal from organic
phase, (iii) to remove major impurity, Fe3+, first, (iv) toseparate Dy3+ and Nd3+ in the last stage because it’s

-2
4

5
pH

6

1
2
3
4
5
CHCl,aq,2, CHNO3,aq,2 [kmol/m 3]

4

5
pH

6

3+

Fig.5. Extraction behavior of Dy and Co2+ from binary or
single metal solution by using neo-decanoic acid.

3.4. Stripping
Figures 6~8 show the effect of acid concentrationon the stripping yields with neo-decanoic acid andPC-88A. The stripping yield of Fe3+ and Dy3+ from

3

107

β
Separation factor
V
VolumettimeTTemperature
xi
Polymerization degree of extract species of iniValence of imi
Solvation number of extract species of i
<Subscript>

the most difficult in this process, (v) to consider theeffects of co-extraction of Co2+ with Fe3+.
After leaching the magnet scrap with 0.1~1.0M
HCl, the major impurity, Fe3+, and Co2+ are removed at
pH2~2.5. Co2+ is co-extracted with Fe3+. After stripping them, NaOH are added to the aqueous solution
and Fe(OH)3 are precipitated and Co2+ remain in the
aqueous solution. Dy3+ and Nd3+ are separated by solvent extraction at pH5~5.5. Dy can be recovered fromorganic phase by stripping with 0.1M HCl.

0
1
2
3
aq
org
RH
Fe
Dy
Nd
Co
H
HCl
HNO3
NaCl
i
j

4. CONCLUSIOIN･ Using neo-decanoic acid as extractant could remove
Fe3+ from other valuable metals (Dy3+, Nd3+, Co2+)
easier than using PC-88A.
･ Separation factor between Dy3+ and Nd3+ wasenough for separation.
･ Stripping from metal loaded organic solution of
neo-decanoic acid using hydrochloric acid or nitricacid was easy and it will suppress the decreasing of
quality of organic solution.
･ Co2+ was co-extracted with other metals.
･ From the above, we made proposal of the separation
process of valuable metals from Nd-Fe-B magnet using neo-decanoic acid as extractant.
Acknowledgement
PC-88A was supplied by Daihachi chemical industry
corporation.

Concentration of i
Extraction equilibrium constant of iDistribution ratio of i
Extraction yield of i
Stripping yield of i

at initial state of batch extraction experimentequilibrium state of batch extraction experiment
at initial state of stripping experimentequilibrium state of stripping experiment
Aqueous phase
Organic phase
Extractant
Fe3+
Dy3+
Nd3+
Co2+
Hydroxide
Hydrochloric acid
Nitric acidsodium chloride
Solute i
Solute jReferences[1] 小山和也，田中幹也; レアアースの最新技術動向と資源戦略，
第三章，2(工場内)磁石廃材の湿式リサイクル技術 127-131[2] 襷田榮一: リサイクル金属資源回収プロセスにおける溶媒抽
出，レアメタル資源の分離回収技術と溶媒抽出，化学工学シンポ
ジウムシリーズ60 101-110[3] 平成22年度 廃棄物資源循環学会 レアメタルリサイクルに関する合同講演会 資料[4] J.S.Preston, Solvent extraction of metals by carboxylic acids, Hydrometallurgy, 14(1985) 171-188[5] F.M.Doyle, D.pouillon, Solvent extraction of metals withcarboxylic acid acid-coextraction of base metals with Fe(Ⅲ)
and characterization of selected carboxylate complexes, Hydrometallurgy,19(1988)289-308

Nomenclatures
Ci
Kex,i
Di
Ei
Yi

[-]
[m3]
[min]
[K]

[kmol･m-3]
[-]
[-]
[-]
[-]

Nd-Fe-B magnet scrap

Aqueous solution
Organic solution

0.1~1M HCl

Leaching

NaOH

Neo-decanoic

NaOH

HCl 1.0M(pH2~2.5).

Solvent
Fe, CoStrippingFe3+,Co2+

Precipitation

Co2+

extraction

acid

Fe(OH)3
Dy, NdHCl 0.1M(pH5~5.5)

NaOH

Solvent
extraction

Dy

Stripping

Neo-decanoic
acid

Nd3+

Dy3+

Fig.9. Separation process of Fe3+, Dy3+, Nd3+ and Co2+ from Nd-Fe-B magnet scrap.
4108Evaluation of UWB-BAN Coordinator with Multiple Antennas
Student Number: 12M18086

Name: Sho KOBAYASHI Supervisor: Jun-ichi TAKADA

複数アンテナを有する UWB-BAN コーディネータに関する評価小林翔

ボディエリアネットワークは体内，体表，人体周辺での通信ネットワークを指し，医療等の様々な分野への応用が期待されている．その応用の一つであるセンサとコーディネータを利用したバイタルセンサネットワークでは，信頼性を向上させる手段として，遅延波を合成する rake ダイバーシチや，複数アンテナを用いたアンテナダイバーシチが利用される．本研究では BAN コーディネータノードに着目し，ベルト状に複数アンテナを取り付けた場合のダイ
バーシチ効果を評価した．

1

Introduction

transmit
receive

BAN is the communication between sensors locatedin, on or around the human body. This is expected
to manage wide applications in medical/health-care,sports, entertainment, and so forth. IEEE 802.15 TG6standardized not only for the speciﬁcation of narrow
band system like typical vital sensors but also ultra
wide band (UWB) system to provide high speed transmission to the wide band systems like capsule endoscope [1]. The UWB utilizes bandwidth of more than
500 MHz, and can realize high speed data transmission with low power within a short distance. Further,since UWB signals have very short pulse width, themultipath signals are resolvable.
In BAN systems, the channel response between thetransmitter and receiver is inevitably inﬂuenced by the
body posture and movement. Therefore a dynamic
model of the propagation channel is required for proper
evaluation of the system. In practice, BAN sensor nodeis restricted by installation space and battery life, so
it is called reduced function device (RFD). However,the coordinator node is usually a full function device(FFD), hence it has much room for space and power.
In this regard, diversity technique such as rake diversity which combines the delayed signals coherently, or
antenna diversity which combines the independently
received signals at diﬀerent antennas can be used in
the coordinator node to improve the performance. Ifsuch systems are applied, the antennas should be positioned optimally to achieve the best performance.
Existing studies discussed the propagation model
when the coordinator antennas are attached at various places under static [2] and dynamic scenarios [3].
Moreover, the use of bracelets and waist belts are considered to attach the antennas on the body. However,
the eﬀect of the antenna position in a dynamic condition has not been discussed. Thus, this study investigates the eﬀect of rake reception and antenna diversity
when several antennas are attached on a waist belt. In
UWB BAN system, the rake reception oﬀers more reliable transmission by combining the multi-path signals.
However, some signiﬁcant multipath signals can still beshadowed due to any body movement and posture, andhence outage events can occur. Therefore, this study
evaluate the performance gain of the antenna diversity
as well as the rake reception for even more improving
the outage performance.
109

front
chest

wrist

L-F

R-F

L-B
ankle

(a) Front view

Tx

head

thigh

R-B
back
(b) Top view

Figure 1: Antenna position
This study measured the channel responses between multiple antennas of the coordinator node on
a waist belt and the the sensor nodes. Then, several
parameters were estimated from measured data. As
well, the eﬀect of rake reception and antenna diversity
at each position are compared by evaluating outage
probability.

2

Measurement Setup

In this study, a digital storage oscilloscope (DSO) wasused to acquire a UWB pulse waveform. This system
directly obtained the snapshots of the impulse responseby measurement of UWB pulse signal in the time domain. Multiple on-body channels were measured using
above the measurement system. Figure 1 presents the
position of the sensor nodes (antennas). The transmit
antennas of sensor nodes were attached on the wrist,
ankle, thigh and chest. On the other hand, four receive antennas of the coordinator node were attachedalong the torso as shown in Figure 1. The antenna
has an omni-directional radiation pattern in the horizontal plane. These antennas are attached about 1 cm
away from the body surface by using polystyrene foam.
This measurements were conducted two times for two
subjects (165 cm, 68 kg and 180 cm, 65 kg) in the following scenarios. Two body movement scenarios wereconsidered; one is walking on the spot, and the otheris standing up/sitting down. This measurement wasdone in an experiment room which can be regarded as
an oﬃce environment. Figure 3 shows the ﬂoor plan of
the measurement room of which size is 5.5 m × 6.5 m,
and its ceiling height is 2.7 ∼ 3.3 m. Table 1 presents
the other measurement parameters.

Table 1: Parameters
Sampling rate
25 Gsample/sec
Number of samples
1000/ 1 snapshot
Number of snapshot
100/sec
Measurement time duration
5 sec
Frequency
3.4∼4.8 GHz−60

direct

L−B
L−F
R−B
R−F

floor
wall

Path Gain[dB]−70

Figure 2: Scene of experiment
door

door

−80

−90

shelf

desk

−100
0

desk

220

10

desk

20
delay[ns]30

40

Figure 4: Delay proﬁle
550
300

3.2

shelf desk

shelf
desk

650

Figure 3: Measurement environment

3

Measurement result

This study obtained the waveform of the received
signal in the measurement. By matched ﬁltering of
the received signal, the channel impulse responses were
estimated.

3.1

Delay Profile

Figure 4 shows the delay proﬁle when the transmit
antenna is attached on the wrist which was calculated
by averaging the power of the impulse responses overtime. As can be seen, dominant arrival paths can beobserved at 1 ns, 7 ns, and 22 ns. These signals are
regarded as direct path, reﬂected path from the ﬂoor,
and reﬂected path from wall based on the calculation of
the arrival times for the corresponding travel distancesof the waves. Since the distance between transmit antenna and receive antennas is about 15 ∼ 30 cm, thearrival time of the direct path falls into 1 ns. Similarly,
the arrival time of the reﬂected path from the ﬂoor isabout 7 ns because the distance was about 1 m. The
reﬂected path from the wall arrived around 22 ns, andthis corresponds distance of about 6.5 m. Here, dominant path is considered as the reﬂected signal from thewall of the lower side of Figure 3. This study deal withthese three dominant arrival paths.

110

Path Gain

The path gain of each path were obtained. Firstly,
the impulse response were calculated from measured
data. Then, the 3 largest values were obtained, andsorted these based on arrival time. Figure 5 shows cumulative distribution function (CDF) of path gain ofeach arrival path in the case of wrist. For the direct
path (ﬁrst arrival path) case, the antennas attached in
front of the body (R-F, L-F) tend to have higher average value than those far from the transmit antenna(R-B, L-B). This is because the swing width of the arm
when the arm is in front of the body is larger than whenarm is at the back. Therefore, these antennas are lessattenuated by shadowing of the body when the arm isin front of the body. Reﬂected path from the ﬂoor (second arrival path) also shows the same tendency. On
the other hand, reﬂected path from the wall (third arrival path) of each have almost the same average value.
Furthermore, this path has lower variance than othertwo paths. Therefore, this path may contribute less forrake diversity.

3.3

Cross Correlation

If the diversity technique is applied, it is important to keep independence between each path. Therefore the cross correlation were calculated among thedelayed paths and among the antennas Cross correlation value is calculated using Equation (1) [4], whereh represents the path gain, x and y denote antennaindices, and i and j indicate delay tap indices. E[·] denotes the expectation operator. Figure 6(a) shows thecorrelation among the delayed paths at R-F antenna’scase. This shows very low correlation value among thedelayed paths. It can be seen that the correlation between two paths of the same antenna are low due todiﬀerent propagation mechanism. Thus, rake diversity
can be applied for this situation. Next, the correlation between each pair of antenna were considered .
Figure 6(b) shows the correlation between ﬁrst arrival

1

1
L−B
L−F
R−B
R−F

0.6

0.4

0.2

0.2

−90

−80 −70 −60
Path Gain[dB]

−50

−40

Table 2: Parameters in calculation

0.6

0.4

0
−100

L−B
L−F
R−B
R−F

0.8

CDF

CDF

0.8

0
−100

(a) Direct path−90

−80 −70 −60
Path Gain[dB]−50

Parameter
Bandwidth
Modulation scheme−40(b) Path from ﬂoor

Packet size(Nb )Noise ﬁgure(NF)
Implementation loss(Loss)
Bit rate (BR)

1
L−B
L−F
R−B
R−F

CDF

0.8
0.6

Value
499.2 MHz
DBPSK
(Synchronous detection)
250 Bytes
12 dB
8 dB
487 kbps

0.4
0.2
0
−100

−90

−80 −70 −60
Path Gain[dB]−50

where γb represent SNR per bit. This γb is expressed
as
Pr
Eb
1
=
(3)
γb =
·
N0
BR N0

−40

(c) Path from wall

Figure 5: CDF of path gain
1

Pr is receive power, Eb is energy per bit, N0 is noise
power density, and BR is bit rate. Then, Pr can becalculated by path gain P G from experiment, and isexpressed as following equation.

1
L−B

1st
0.5

0.5
L−F

2nd

0

0

PrdB = PtdB − N F − Loss + P GdB

R−B
−0.5
3rd

This is processed in dB scale. Pt , N F , and Loss denotethe transmit power , noise ﬁgure, and implementation
loss, respectively. Path gain indicates the combined
one of 3 paths (3-ﬁnger rake) or 4 diﬀerent antennas.
Also, N0 can be obtained by multiplication of Boltzmann’s constant(1.38 × 10−23 [J/K]) and the temperature(25 ℃). Next, PER Pp is calculated using Pb .

R−F
1st

2nd

3rd

(a) Correlation ofpaths (wrist, R-F)

−1

(4)

−0.5

L−B

L−F

R−B

R−F

−1

delayed (b) Correlation of each antenna(wrist, direct path)

Figure 6: Cross correlation
paths of each antenna when the transmit antenna is
on wrist . It was found that in most cases the crosscorrelations indicated low value, even if L-B and R-B
were highly correlated. Also, the pair of L-F and L-B
and the pair of L-F and R-B show inverse correlation.
This is probably due to the arm swinging. This meansthat it may be ineﬀective to use the pairs of antennas located on the same side of the body in case of
the arm swinging to improve performance by diversity
combining.

4

Evaluation of transmission

4.1

Calculation method

Pp = 1 − (1 − Pb )Nb

Nb is the packet size. Outage probability Pout is obtained as the probability that Pp become lower thanthreshold Γp .
Pout = prob(Γp < Pp )ResultThis study speciﬁcally evaluates the outage probability when the maximum allowed radiated power of
UWB is used. According to the regulation of Federal
Communications Commission (FCC) the power levelis limited to −41.3 dBm/MHz. Since this research use
the bandwidth of 500 MHz, it becomes −14.3 dBm.
Therefore, this study obtained the outage probability
at −14.3 dBm.
Figure 7 represents the outage probability when notusing any special scheme. R-F antenna shows good
performance. This can achieve an outage probabilityof less than 10% for all transmit antennas. This is because this antenna has high path gain. On the other
hand, the antennas attached on the back side (R-B, LB) has high outage probability for all antennas (moreE[(|hix |dB − E[|hix |dB ])(|hjy |dB − E[|hjy |dB ])]ρ(ix,jy) = √E[(|hix |dB − E[|hix |dB ])2 ]E[(|hjy |dB − E[|hjy |dB ])2 ]
111

(6)

This study set Γp to 0.05. Figure 2 represents parameters which are used in calculation.

4.2

This section evaluates the outage probability for
rake and antenna diversity. Outage probability means
the probability that the signal-to-noise ratio (SNR) becomes lower than a threshold by fading and shadowing. The error probability were calculated based on
the measurement results [5]. Modulation scheme isassumed to be diﬀerential binary phase shift keying(DBPSK). Firstly, bit-error ratio Pb is calculated asfollowing√(2)
Pb = erfc( γb ),

(5)

(1)

80

Ankle
Chest
Thigh
Wrist

60

Outage Probability[%]

Outage Probability[%]

80

40

Ankle
Chest
Thigh
Wrist

60

40

20

20
0

0

L−B

L−F
R−B
Antenna

LB,LF LB,RF LB,RB LF,RF LF,RB RF,RB
Antenna

R−F

Figure 9: Outage probability using 2 antennas diversity

Figure 7: Outage probability without any scheme

100
No diversity
Rake
Antenna Diversity

Ankle
Chest
Thigh
Wrist

60

Outage Probability[%]

Outage Probability[%]

80

40

20

80
60
40
20
0

0

L−B

L−F
R−B
Antenna

Ankle

R−F

Chest
Thigh
Antenna

Wrist

Figure 10: Comparison of both scheme

Figure 8: Outage probability using rake diversity

5
than 20 %). Next, 3 delayed signals of each antenna
were combined to consider the eﬀect of rake diversity.
Figure 8 presents the result. Improvement of each antenna can be observed due to low correlation. Notably,
the front side antennas (R-F, L-F) achieve less than 1%
for all transmit antenna. However, the back side antennas (R-B, L-B) do not experience much improvement.
In addition, the eﬀect of diversity combining using multiple antennas were veriﬁed. Figure 9 shows
the result when using two antennas diversity. This
result also shows improvement of each antenna pair.
In many cases, achieve less than 1% outage probability was achieved. However, back side antennas (R-B,
L-B) are not improved much because both antennas
basically have lower gain than others. As well, this isdue to high correlation between the antennas attachedon the same side.
Next, the eﬀect of both scheme were compared. To
see the result clearly, the result at 10 dB below the
maximum power (−24.3 dBm) were compared. Figure 10 represents the result when the best antenna or
the best pair is used for each transmit antenna. This
indicates that 2 antenna diversity can gain more improvement than rake using 3 delayed signal. This isprobably because the gain of delayed paths are lower
than the largest path of each antennas. Antenna diversity results in a relatively large improvement for the
ankle and wrist cases. Antenna diversity results in a
relatively large improvement for the ankle and wrist
cases. Since these two positions move greatly due tobody motion, the eﬀect of attenuation by fading andshadowing at one antenna increases. Therefore, it isobserved that diversity scheme can make up for thisattenuation.
112

Conclusion

In this study, the channel responses were measured incase that the multiple antennas of the coordinator node
on a waist belt receive a signal from the sensor node.
From the received signal, the radio channel properties
such as the delay proﬁle, path gain, and cross correlation were characterized. Further, the eﬀect of rake
and antenna diversity was investigated by evaluation of
the outage probability. As a conclusion, 2 antenna diversity can bring improvements larger than rake using
3 delayed signal. Also, suﬃcient performance cannot
be achieved with two antennas on the back side of the
body. This is due to low path gain and high correlation.

References[1] IEEE 802.15 WPAN Task Group 6 (TG6) Body Area Networks. [Online]. Available : http://www.ieee802.org/15/
pub/TG6.html[2] S. V. Roy, C. Oestges, F. Horlin, and P. D. Doncker, “A
Comprehensive Channel Model for UWB Multisensor Multiantenna Body Area Networks,” IEEE Trans. Antennas.
Propag., Vol. 58, No.1, pp. 163–170, Jan. 2010.
[3] M. Kim, and J. Takada, “Statistical Model for 4.5-GHz
Narrowband On-Body Propagation Channel With Speciﬁc
Actions,” IEEE Antennas Wireless Propag. Let., Vol. 8,
pp.1250–1254, Dec. 2009.
[4] J. Keignart, C. Abou-Rjeily, C. Delaveaud, and N. Daniele,“UWB SIMO Channel Measurements and Simulation”
IEEE Trans. Microw. Theory Tech., Vol. 54, No. 4, pp.
1812–1819, Apr. 2006.
[5] J. Wang, K. Masami, and Q. Wang, “Transmission Performance of an In-body to Oﬀ body UWB Communication
Link,” IEICE Trans. Commun., Vol. E94-B, No. 1, pp.
150–157, Jan. 2011.

Visualization of the propagation channels and interpretation of themechanisms in macro cellular environments at 11 GHz
Student number: 12M18092

Name: Rieko TSUJI

Supervisor: Jun-ichi TAKADA

11 GHz 帯における市街地環境での伝搬特性可視化と伝搬メカニズムの解釈
辻理絵子

本論文では，伝搬測定およびシミュレーションから得られた伝搬特性を環境写真と重層することで，伝搬路の可視化を行った．測定は 11 GHz 帯，市街地環境で実施した．シミュレーションで使用した建物モデルは，伝搬環境における周辺構造物をレーザープロファイラを用いて取得した点群データを基に構築した．両者の比較により，見通し波
や反射波の影響を測定とシミュレーションの両方で確認した．一方，シミュレーションでは再現されないが，測定では無視できない影響を持つ散乱波の存在を確認した．

1

Measurements

Introduction

The demand for high capacity and high bit rates
has been increasing in recent years. To satisfy this demand, MIMO technique can be a key solution. MIMO
technique utilize multi path component. The multiantenna is used in the both of base station (BS) andmobile station (MS), each antenna transmit diﬀerent
signal and through propagation channel, the signals
were received. The performance of MIMO is strongly
depends on accuracy of separation the signal. Thus,
directional properties of propagation channel and its
phenomena are need to be analyzed [1].
On the other hand, there is a methodology enable
comprehensive understandings of angular characteristics of propagation channel. That is ”visualization”.
Visualization means that the 360 degree panoramic
photo which are superimposed angular power spectrum[2]. The conventional methodology such as comparing
power spectrum and environmental information separately is quite laborious and costly. However, only
visualization of measurement data is deﬁcient because
measurements have the limitation to estimate parameters. The resolution of the measuring equipment makeaccurate analysis hard. Thus, simulation that can provide us propagation path information make up the limitation. Ray-tracing method is often used to simulate
propagation characteristics, but ray-tracing simulators
generally model only specular reﬂection, edge diﬀraction and penetration. However, according to the literature [3], the contribution of the scattering is still
signiﬁcant and should not to be ignored. Therefore,
comparing with the measurement and the ray-tracing
simulation results by visualization method is helpful tounderstand the propagation phenomena.
This paper shows that the procedure of building
visualization tool and both of the limitation of measuring equipment and ray-tracing simulation, and interpretation of the propagation phenomena in urban
environments at 11 GHz.

Simulation

1. Measure the transfer
functions

1. Create the building modelwith the point clouds

2. Measure point clouds andtake panoramic photo

2. Calculate the propagation
parameters by ray-tracing
3. Calculate the transfer
functions

Calculate Power Spectrum by beam-forming*
Superimpose to the photo*a technique of calculating angular power spectrum

Figure 1: Flowchartof the objects surrounding the MS by a laser scanner,
the location data by GPS, and panoramic photo. The
obtained point cloud data are then converted into thepolygon data to use in the ray-tracing simulation. After the ray-tracing simulation, the transfer function is
calculated with the path parameters generated by raytracing. Subsequently, for both of the measurement
and the simulation results, angular power spectrum is
calculated by beam-forming method. In this paper, I
consider vertical polarization only at both of the BS
and the MS.
The beam-forming is performed as′′′

G(k, ϕ, ϕ , θ, θ ) =Framework

DPS :p(n) =Figure 1 shows the ﬂowchart of this research. First,
the measurement was carried out and the transfer function was obtained in the urban environment at 11 GHz.
At the same place, also measured the point cloud data113

2

|ak (ϕ′ , θ′ )| |ak (ϕ, θ)|2where G represents the angle-resolved transfer function, and a, H, k, ϕ, ϕ′ , represents the antenna response, the matrix of the transfer function, the numberof the sub-carrier, direction of departure (DoD), anddirection of arrival(DoA), respectively. The Azimuth
Elevation Power Spectrum (AEPS), and Delay PowerSpectrum (DPS) are calculated respectively by
∑∑∑
2
′
′
AEPS :p(n, ϕ, θ) =|g(n, ϕ, ϕ , θ, θ )|
n

2

′

∗
aH
k (ϕ , θ )Hk ak (ϕ, θ)

ϕ
′

′

ϕ′

θ′

∑∑∑∑
θ

ϕ′

′

′

|g(n, ϕ, ϕ , θ, θ )|2

θ′where g(n, ϕ, ϕ , θ, θ ) denotes the impulse response which′
is obtained by the inverse Fourier transform of G(k, ϕ, ϕ ,′θ, θ ).

11.9mm (0.44λ)

Table 1: Measurement speciﬁcations
Parameters
Value
Uniform circular array Dual-polarized patch element
Gain: 6 dBi
UCA spaced by 11.9 mm
Carrier frequency
11 GHzSignal bandwidth
400 MHz
Transmit power
24 dBm
No. tones
2048
Delay resolution
2.5 nsMeasured interval time 1.128 s

denotes
directivity
Circulararray
antenna

45.8mm (1.68λ)Figure 2: detail of the circular antenna array
0Power [dB]

−5

−10

−15

−20
180

120

60

0
−60
Angle [Degree]

−120

MS

−180

Figure 3: Radiation pattern
To superimpose the angular power spectrum to thepanoramic photo, I have to calculate elevation and dodata matching. Panoramic photo were made by capturing a frame the video clip of the measured routeenvironment and each photo have the data of the objects in the photo and GPS location. For calculating
elevation, the distance and height of the objects andPythagorean theorem is utilized. For data matching,location data and also measured data snapshot’s GPS
location data is utilized. calculating the distance between panoramic photo frame and measured data snapshot, the nearest data was chosen. For the simulation
data matching, I just selected the same number of themeasured data snapshot.

3

Measurement Campaign

3.1

Channel sounder

Both of the BS and the MS use the same type ofantennas (12-elements uniform circular antenna array)
as shown in Figure 2. This antenna has both verticaland horizontal polarized elements. Each element isspaced by 11.9 mm (0.44λ). The radiation patternof the antenna by beam-forming is shown in Figure
3. The resolution is approximately 60 degree. The
transmit signal is the unmodulated multi-tone signal
having 2048 tones (2.5 ns resolution in delay domain),center frequency 11 GHz, and 400 MHz bandwidth.
The transmit power is 24 dBm. Table 1 shows themeasurement parameters. More detailed speciﬁcationsof the channel sounder are presented in [4].

3.2

Figure 4: View from the BS
at 5 km/h and transmit signal with 1.128 s interval
along the route denoted as the arrow in Figure 5. The
distance between the BS and the MS is approximately
ranging from 330 m to 450 m. As shown in Figure 4,
the average height of the building in measured routeis 7 m, and it was the line-of-sight (LoS) environment
throughout the route.

4

Simulation

4.1

Building model

At the same place of the measurement, the buildings
surrounding the MS were scanned by IP-S2 Lite, which
is a 3D laser scanner developed by TOPCON Corp.
The point cloud data obtained from the scanning isconverted into the polygonal data for ray-tracing simulation. In addition, the polygon model is further simpliﬁed by ﬂattening the building surface and removing the small objects such as utility pole and trees asshown in Figure 6, because ray-racing is based on Fresnel zone principal, thus the detailed surface should notconsidered. After the simpliﬁcation, the number of thesurface are reduced from 5616 to 90 as shown in Table
2.

Measured route

The measurement campaign was conducted in thecity of Ishigaki, Japan. The BS antenna was placed in
the roof top of the building approximately 28 m. Figure 4 shows the prospective view from the BS towards
the MS. The MS antenna was placed in approximately
3 m above the roof top of the vehicle which was driven
114

4.2

Ray-tracing simulation

The simulation was carried out by using Wireless Insite, ray-tracing simulator developed by Remcom Inc.
From the simulation, I can obtain received power, delay time, angle of arrival, and angle of departure.

N

Table 2: Number of the surface
Model type
The number of the surface
Surface elements
5616
Flattening surface 841
Non-small objects 90

MS

MS
BS

Building models

50 m

478 m

Figure 5: Measurement area
100 m

Surface elements
model

95 m

Figure 7: Simulation area

The real building

Point clouds
data

BS

respectively. Good agreement between the measurement and the simulation results is observed. However,there are some waves which are not conﬁrmed from thesimulation results.

Flattening surface Non-small objects
model
model

Figure 6: The example of the model simpliﬁcation

5.2
Figure 7 shows the calculation area, in which 13
reconstructed buildings are included. The MS was set
along the red route with 1.67 m interval at 3 m height,
and the BS was set on right lower side at 28 m height
without building model in Figure 7. Thus the numberof the snapshot is 71. All the buildings are assumed
to be made of concrete. The ground material was set
as asphalt [5]. Table 3 shows the parameters of thesimulation.

4.3

Data processing

The matrix of the transfer function is reconstructed
as
Hk =

L
∑

′

′

′

γl ak (ϕl , θl )aTk (ϕl , θl )e−j2πfc τll=1

where the prime denotes the value in receiver, and γl ,L, τl denote l-th path gain, total number of paths, andl-th path delay time, respectively.

5

Results and Discussion

5.1

Distance-delay characteristics

Figure 8 shows distance-delay power spectrum of
the measurement and the simulation results. Two major paths are observed in both the measurement andthe simulation results. From the simulation, these twopaths (Path 1 and Path 2) are conﬁrmed to be the direct wave and the reﬂected wave from the backward
building A as shown in Figure 9. Figure 9 shows thesimulated paths where the left and right side ﬁgures
show the strongest received power of 7 and 25 paths,
115

Angular-power spectrum

Figure 10 and Figure 11 shows a frame of the visualization movie. The angular power spectrum reproduced between 25 degree to −25 degree in elevation,
since the spectrum out of the range is not eﬃcient toanalyze because of the antenna design. Figure 10 shows
the AEPS at the delay time when the direct wave arrived. From this ﬁgure, it is conﬁrmed that ray-tracing
method can reproduce direct wave appropriately.
∑
Figure 11 shows DoD which means n AEPS, atthe point of approximately 370 m away from the BS.
We can observed direct wave at near 0 degree in Figure
11. The path around -180 degree, which is conﬁrmed
to be a reﬂection wave from backward building A as
shown in Figure 9, is also observed in both the measurement and the simulation results.
However, some discrepancies are observed. The
path between −50 degree to −130 degree does not appear in the simulation result. Possible explanations
are as follows. The eﬀect of the reﬂected wave fromthe building B located near −100 degree might be under estimated in simulation. As shown in Figure 9, thereﬂected wave from building B actually exists but too
small under −140 dB because of the parameter settingof the concrete material. Scattering eﬀect also can be
the reason. In addition, the resolution of the antenna
is another candidate. From Figure 3, −3 dB power
reduction resolution of the antenna is approximately
60 degree. If the channel sounder received both of thecoming wave from −50 degree and −120 degree at thesame time, it is possible to measure the spread power
between −50 degree to −130 degree.
Another discrepancy is around 90 degree to 140 degree. It is seen that ray-tracing cannot reproduced thewaves. From this ﬁgure, this might be the eﬀect ofTable 3: Simulation speciﬁcations
Parameters
Value
Carrier frequency 11 GHz
Signal bandwidth 400 MHz
Material constant concrete (σ = 0.015, ϵ = 15)
asphalt (σ = 0.0005, ϵ = 5.72)

Path 1

Path 2

Directwave

A

A-100 dB

B

B-140 dB

Figure 9: Strongest 7 path (left) and 25 path (right)
calculated by the simulation

Reflected
wave by A

BS

Figure 8: Distance-delay power spectrum (left: measurement, right: simulation)

scattering of the trees, but it is needed more detailed
analysis.

6

BS

Conclusion

This paper shows visualization method of the propagation channels both of the measurement and the simulation results. From the results, it is shown that thedirect wave is appropriately reproduced in the simulation. However, were some possibility that the reﬂected
waves are underestimated in simulation and some signiﬁcant scattering eﬀect might not be considered. For
the future work, I plan to ﬁt panoramic photos to themeasurement and the simulation results more accurately, and some high-resolution parameter estimation
algorithm will be applied for more precise evaluation.
And ﬁnally, the eﬀect of the scattering might be modeled.

Figure 10: AEPS at LoS delay time (top: measurement, bottom: simulation)
Discrepancies
of DOD

BS

References[1] M. Kim, Y. Konishi, Y. Chang, and J. Takada“Large Scale Parameters and Double-Directional
Characterization of Indoor Wideband Radio Multipath Channels at 11 GHz,” IEEE Trans. Antennas Propag., vol. 62, no. 1, pp. 430-441, Jan.
2014.
[2] J.M. Conrat, P. Pajusco, and A. Dunand, “On theuse of panoramic photography for understanding
propagation channel physical phenomena,” COST
2100, No. 12024, Bologna, Italy, Nov. 2010.
[3] M. Ghoraishi, J. Takada, and T. Imai, “Identiﬁcation of Scattering Objects in Microcell Urban
Mobile Propagation Channel,” IEEE Antennas
Propag., vol. 54, no. 11, pp. 3473-3480, Nov. 2006.
[4] M. Kim, Y. Konishi, Y. Chang, and J. Takada,“Novel Scalable MIMO Channel Sounding Technique and Measurement Accuracy Evaluation
116

of DODBS

Figure 11: DoD (top: measurement, bottom: simulation)with Transceiver Impairments,” IEEE Trans. Instrum Meas., vol. 61, no. 12, pp. 2546-2550, Dec.
2012.
[5] Remcom Inc., Wireless Insite 2.7.0 Reference
Manual, pp. 97-98, Nov. 2013.

Fracture criterion between a multi-beam structure and rough adhesive surface
Student Number : 12M18028

Name : Kazuhito EMURA Supervisor : Kunio TAKAHASHI

梁集合体構造と粗さのある凝着表面における破壊条件
江村和仁
先端平面とウレタンシートとの間に凝着界面を持つ剛体に様々な角度で力を加え、垂直応力とせん断応力に関する脱離条
件を実験的に求めた。最大凝着力を幾何形状から界面に対する垂直荷重と水平力に分解する。剛体は根元を固定され界面における垂直・せん断応力分布は一様であるとし破壊条件を垂直応力とせん断応力に関して見積もった。この破壊条件をもとに、先端面で凝着する弾性梁の垂直荷重と水平力に関する脱離条件を導出した。

1.

Introduction

Geckos can quickly climb walls and ceilings withadhesion force. They have a lot of micro-nano hairs on
their fingers surface, which are called setae andspatulae. The hairs can absorb surface roughness andgenerate large adhesion force [1]. This adhesion
mechanism was studied well and the application of themechanism was already made [2][3].
This mechanism cannot explain how geckos canmove quickly, because it is difficult to break strong
adhesion interface. A multi-beam structure [4] isinspired from the hairs. The structure consists of manyelastic beams and adhesives applied on the tips of thebeams. The structure is intended to grip a roughsurface with adhesion force and control detachmentfrom the surface. Because adhesion force is generated
at any surfaces, grip and release devices with adhesion
force are expected for application in various
surrounding compared to magnetic chuck and vacuum
chuck. The detachment mechanism of the multi-beam
structure is treated as a superposition of themechanism of single beam. The mechanism of single
beam was discussed with a beam theory and a roughassumption about a fracture criterion of the adhesioninterface [5]. The mechanism was experimentallyinvestigated [6][7]. The experimental result couldn’t
be explained with this model.
In the present study, the fracture criterion isexperimentally investigated with a rigid body andadhesives. With the fracture criterion and the beam
theory, the detachment mechanism of an elastic beam
is suggested.
2.

Figure 1. A multi-beam structure holds an object.
Normal stress distribution is generated at theinterface. The distribution is evaluated from a beam
theory. Using contact area S , section modulus Z ,angle of the beam θ and length of the beam lrespectively, maximum normal stress σ n ,max at theinterface is expressed as Equation 1.

Figure 2. Normal stress distribution at adhesioninterface.
σ n ,max 

ModelFn l cosθ  Ft l sin θ
Fn

S
2Z

(1)

The adhesion interface is broken and the beam detachfrom the surface when σ n ,max is larger than critical

A multi-beam structure that consisted of many elastic
beams and adhesives applied on tips of the beams
holds an object at adhesion interface between a surfaceof the object and the tips as shown in Figure 1. The
detachment mechanism of the structure is treated assuperposition of the mechanism of single beam.
Normal load Fn and tangential force Ft are applied toeach of the beams as shown in Figure 2. Fn iscorresponded to the weight of the object.

value σ cr ( τ ) i.e.,

σ n,max  σ cr (τ )(2)

If Ft is changed, σ n ,max is changed as shown in
Figure 2. The detachment from the surface iscontrolled by Ft . The fracture criterion of the adhesion117interface is defined as σ cr ( τ ) . The detachment

plotted when loading force Flo ad is applied to the flat
surface. The threshold of Flo ad is needed anddetermined as Fload  0.40( N) to keep the same
condition through the experiments.

criterion of an elastic beam is defined as Fn and Ft
when detachment occurs. The fracture criterion is notstudied well. The fracture criterion concern with shear
stress should be investigated experimentally.

(N)
0.6
Adhesion force Fad

3. Experiment
3.1 Experimental system
The experimental system is shown in Figure 3 andTable. The rigid body is fixed firmly to an arm of theof the rotation stage(e) by double nut. Tilting angle ofthe table φ is same as the angle of resultant of Fn and

Ft to the surface.

0.4

Rigid body
=89.8(deg)=89.8(deg)l=9.75(mm)d=1.85(mm)ThresholdFload>0.40(N)

0.2

0

0.2

0.4
0.6
Loading force Fload

0.8

1
(N)

Figure 5. The threshold of Flo ad .
4.

Result(N)

Figure 3. The experimental system.

Maximum adhesion force FadTable Experimental system.
Electric balance(a)AY-220
Resolution:0.1mg
SHIMADZU
Motorized stage(b)KZL060
SURUGA SEIKI Resolution: 1μm
X axis crossed roller guide stage(c)B11-60D
SURUGA SEIKI Resolution: 0.5μm
Manual rotation stage(d)B43-60N(e)B43-38N
Resolution: 0.2
SURUGA SEIKI
Screw, SUS304, 9.75mm length(f)1.85mm in diameter
Adhesives(g)CT-03-500
Urethane sheet 0.2mm thick
EXSEAL Corp.
(h)Tilting table, angle φ :5deg to90deg at 5deg intervals

Rigid body Standard Deviation
=89.8(deg) Sample number:12
0.2 l=9.75(mm)d=1.85(mm)

0.15

0.1

0.05

0

20
40
60
Tilt angle of the table 

80 (deg)

Figure 6. The maximum adhesion force Fad with tilt
angle of the table φ .

3.2 Process of experiment
Experimental result is plotted as relation of Fad andφ in Figure 6. The number of the sample is 12 at

Then experimental process is shown in Figure 4.

each φ . The plotted points are the mean value of Fad .
The error bars is evaluated from standard deviation.
5. Discussion
5.1 Fracture criterion of adhesion interface
Figure 4. The experimental process.
The body is (1)adhered to the surface and loaded
vertically to the surface (2)Removed from the surface
at 1μm sec vertically.

With assumption of fixed end between the rigid bodyand the arm, the effect of the bending moment at theinterface is ignored and the normal and shear stress
distribution is assumed uniform as shown in Figure 7.
The normal stress σ av e and shear stress τ av e is

Figure 5 shows that maximum adhesion force Fad is118τ  Ftevaluated from the mean value of Fad and Equation
3 and 4.

(5)S

From Equation 1 and 5, Fn and Ft are expressedas Equation 6.

S σ n ,ma x  4 l sin 2 θτ
d
Fn 

1  4 l sin θ cosθd
Ft  Sτ

Figure 7. Normal and shear stress distribution
between the rigid body and tilting surface.
 Fr,n  Fad sin φFr,t  Fad cosφ(3)

σ av e  Fr,nSτ av e  Fr, t

S


(4)

detachment criterion when σ n ,max satisfy the proposed
fracture criterion as shown in Figure 8. When the
resultant force of Fn and Ft increases in the
direction φ at the lines or plotted points, the beam is
detached from the surface.
As shown in Figure 9, both Fn and Ft at φ  θtake the largest values in each angle of the detachment
criterion. Because the angle of the resultant of σ n ,maxand τ at φ  θ agrees with θ , the maximum normal(kPa)

Normal stress ave

(6)

When σ n ,max and τ satisfy a fracture criterion, thebeam is detached from the surface and Equation 6
express the detachment criterion. Figure 9 shows thedetachment criterion at (a) θ  30 , (b) θ  45 , (b)θ  60 ; the solid lines show the conventional
detachment criterion when σ n ,max satisfy a fracture
criterion expressed as constant value ofσ cr (τ )  σ cr (0) . The plotted points show the present

The fracture criterion is plotted as relation of σ av eand τ av e as shown in Figure 8. When τ av e is around
20kPa, the detachment occur at many values of σ av e . It
is suggested that the fracture mode is different at eachvalue of σ av e at the detachment point.

80



Rigid body
=89.8(deg)l=9.75(mm)d=1.85(mm)S=2.69(mm2)60load at φ  θ is expressed as Sσ cr . σ cr decreases as
the angle of the stress resultant decreases as shown in
Figure 10. It is suggested that the structure can gripa heavy object when θ is large.

40

6.

ave=20(kPa)

To investigate the detachment mechanism of amulti-beam structure, the fracture criterion of adhesioninterface is experimentally investigated with the rigid
body and the tilting tables. The maximum adhesion
force between the rigid body and the elastic body ismeasured with the electric balance and the fracture
criterion is evaluated from the maximum adhesion
force. The detachment criterion of an elastic beam isevaluated from the proposed fracture criterion and abeam theory. With comparison of the detachment
criterion of various beam angles, it is suggested themulti-beam structure can grip a heavier object when
the angle of the beam is large.

20

0

20

40
60
Shear stress ave

Conclusion

80 (kPa)

Figure 8. The fracture criterion of adhesion interface.
5.2 Detachment criterion of an elastic beam
Using the fracture criterion, the detachment criterionof an elastic beam is modified. The beam is adhered toa surface. When Fn and Ft is applied to the beam,
σ n ,max is expressed as Equation 1. Shear stress is
assumed uniform over the interface, so τ isexpressed as Equation 5.

119

(N)0.15

(kPa)

l/d=5
=30(deg)

The critical normal stress cr

80

60

Normal LoadFn

0.1



e
0(d
=3

g)

40

0.05

20

0

0.05
0.1
Tangential force Ft

0.15
(N)

0

(a)

Figure 10. The fracture criterion about normal stressand the angle of the resultant stress.

(N)0.15

5(
de
g)

l/d=5
=45(deg)

30
60
90
The angle of resultant stress arctan(n,max/) (deg)=4References

[1] K.Autumn, et.al., 2002. PNAS 99(19): 12252-12256

0.1

Normal LoadFn[2]Geim, et.al., Nature Materials.2 (2003): pp.461-463[3] S. Kim, et.al., IEEE Transactions on Robotics, Vol. 24,
February 2008. pp.65-74[4] K.Takahashi, et.al., International journal of adhesion &Adhesive 26 (2006) pp.639-64

0.05[5] J. Watanabe, et.al., 14th symposium on Microjoining andAssembly Tech in Electronics Feb 5-6 2008 Yokohama
pp.369-372

0

0.05
0.1
Tangential force Ft[6]M.Wang, et.al., 16th symposium on Microjoining andAssembly Technology in Electronics, Vol.16
2010
pp.435-438.

0.15
(N)

(b)

[7] K.Emura, et al., The 4th Multidisciplinary International
Student Workshop (MISW2012), pp. 91, 2012, Aug.

(de
60

=

l/d=5
=60(deg)g)(N)0.15

Normal LoadFn

0.1

0.05

0

0.05
0.1
Tangential force Ft

0.15
(N)

(c)
Figure 9. The detachment criterion of an elastic beam
at various beam angles θ .

120

Mechanism of Adhesion Hysteresis in the Elastic Contact between a Silicone Rubber and a Silica Glass Lens
Student Number: 12M18264

Name: Dooyoung BAEKSupervisor: Kunio TAKAHASHI

シリコーンゴムと石英ガラスレンズ間の弾性接触における凝着ヒステリシスのメカニズム白 斗永
シリコーンゴムと石英ガラスレンズ間の接触における凝着ヒステリシスのメカニズムが研究された．実験により変位，力，接触半径の三つのパラメータが厳密に測定された．測定系の剛性を考慮した TMO モデルが実測値の解析に用いられた．三つの測定値が線形弾性理論に基づいた力の釣り合い式を満たすことが確認された．その結果，外部仕事，弾性，界面，剛性，散逸の各々のエネルギー変化項の計算が可能となり，エネルギー散逸が解析され，凝着ヒステリシスのメカニ
ズムは接触部の円周状亀裂長さの変化量に比例するパラメータの導入で説明可能となった．

1 INTRODUCTION
Understanding the adhesion phenomena is significant andessential for designing the application using the adhesive
force, e.g. grip-and-release devices [1]. A point contact
model of contacting between a parabolic punch and a semiinfinite body is the most basic model for analyzing theadhesion phenomenon theoretically and experimentally.
For theoretical analysis of this model, Johnson, Kendall andRoberts suggest the JKR theory [2] which consist incompressing an elastic parabolic punch against a flat rigid
surface or, conversely, a hard parabolic punch against a flat
elastic substrate. This theoretical model rely on basic
assumptions of elastic theory [3]. From this reason, theexperimentalist has to check the theory and experimental
condition strictly before attempting to anlyze theirexperimental results for their reliability. In this perspective,
Takahashi, Mizuno and Onzawa suggest the TMO theory[4] which consider the stiffness of the measurement system.
And, Johnson [5] point out that in many practical situations
the high intensity stress of adhesive forces gives rise toinelastic-viscoelastic or plastic-deformation of the solids,
notably in the separation zone at the edge of the contact.
This influences the apparent work of adhesion and gives
rise to a difference between loading and unloading process
which referred to as an adhesion hysteresis. This adhesion
hysteresis which is different from the mechanical hysteresis
is classified and defined by Silverzan et al. [6], and theysuggest that the adhesion hysteresis is raised from achemical reaction, namely the formation of a hydrogenbond, across the interface. Differences between theoreticalmodel and experimental behavior mainly in the viscoelastic
materials are also reviewed by Shull [7] and Barthel [8].
The adhesion hysteresis has been studied by many authors[3, 5-13], and factors that cause the adhesion hysteresis can
be classified in two types. The first one is raised from thestate of the bulk of the materials. If the bulk is non-elastic
materials such as viscoelasticity, the time dependence andnonlinearity of the materials affects the whole process ofcontact. The second one is raised from the state of theinterface between the materials. In this case, chemical
reaction, molecular bonding, surface roughness anddangling chains could affects the adhesion hysteresis. From
this, the reason of occurring the adhesion hysteresis cannot
be generalized, however, it is clear that the energy is
dissipated during loading and unloading the contact.
The mechanism of the adhesion hysteresis is still on
discussion steps. Therefore, objective of the present study
is to investigate the mechanism of the adhesion hysteresis.

As an approach to achieve our objective, we measured theparameter of the displacement, the force and the contact
radius respectively by experiment, and then evaluating
essential parameters using the TMO theory for calculatingeach energy terms, i.e. elastic energy, interface energy,
stiffness energy and external energy without any
assumption of equilibrium state of total energy. From thisprocess, the energy dissipation as a surplus of total energy
relation can be calculated. And, the mechanism of theadhesion hysteresis is analyzed and discussed from theresults.
2 THEORETICAL CONSIDERATION
Figure 1 shows a schematic illustration of the TMO model
which consider the stiffness of the experimental system [4].
A rigid parabolic punch assumed to contacts on a perfectly
semi-infinite elastic body. The rigid punch is assumed anaxisymmetric parabolic body and the friction of theinterface between two bodies is negligible.

Figure 1. Schematic illustration of the TMO model, where Zt
is gross displacement, k is stiffness of the experimental system,
R1 is radius of curvature of the rigid parabolic punch, R2 is
radius of curvature of the semi-infinite elastic body, F is force
between the rigid parabolic punch and the semi-infinite elastic
body, δ is vertically deformed displacement of the semi-infinite
elastic body, a is radius of contact area raised by contacting.
Notably, direction of the gross displacement here is opposite
direction from the TMO theory.

The theory of the point contact can be expressed using the
JKR theory [2]. We, however, need to consider the practicallimit of a real experimental system theoretically to anlyze
the experimental results. First of all, it is hard to guarantee
the equilibrium state of total energy of experimental results,
because realizing the perfectly static state of anexperimental process is nearly impossible. Secondly, theelastic materials used in the experiment is the polymericmaterials which does not guarantee the perfectly linear
elasticity. Thirdly, the radius of curvature R2 in Figure 1

121

need to be considered, because the surface of polymericmaterials does not guarantee the perfectly flat surface. In
Figure 1, the force between the rigid parabolic punch andthe semi-infinite elastic body are balanced as a relation of
F=PH-PB when the displacement δ is given, where PH is the
Hertz force and PB is the Boussinesq force [4]. So, this force
can be expressed as


2
1





3

radius a are measured simultaneously by the digital balance
and the microscope as shown in Figure 2. The measurement
system was set in the clean bench on the vibration isolationtable. And, room temperature was set in 20°C and humidity
was 35%.

(1)which shows the relationship among the force F, the contact
radius a, and the displacement δ, where E and ν is Young’s
modulus and Poisson’s ratio of the semi-infinite elastic
body, and R is radius of curvature, i.e.
1



1





1

(2)

where R1 and R2 is each of radius of curvature in Figure 1.
And, a force due to the stiffness of the measurement system
can be expressed as    .
(3)
From eliminating the displacement δ using equations (1)and (3), the force in Figure 1 can be derived as


2

  
2  1   
3(4)which means the relations among the force F, the contact
radius a, and the gross displacement Zt considering thestiffness k. Using equation (4), the Young’s modulus E, thestiffness k and the radius of curvature R can be evaluated bymeasuring the three parameters, the force F and the contact
radius a and the gross displacement Zt, simultaneously inthe experiment. In the same manner, the elastic energy
stored in the semi-infinite elastic body can be evaluated as. 

4
451   



1
 .
4

Figure 2. Schematic illustration of the experimental system. (a)Lens: silica glass lens with radius of curvature R1=0.2076m anddiameter of 40mm, (b) Motorized stage: motorized verticalmovement with resolution 1µm/s, (c) Polymer: silicone rubber
sheet with thickness 10mm and Young’s modulus E=0.60.7MPa from tensile tester, (d) Digital balance: strain gauge
type with resolution of 0.01g, (e) Microscope: resolution of
1600×1200pixcel.

(5)

It is important that equations (4) and (5) can be derived
based on the elastic theory without any assumption ofequilibrium state of total energy. The interface energy isdefined as the energy reduction due to the contact,
expressed as.    ∆"(6)
where ∆γ is work of adhesion, i.e. the required work to
separate unit area of the interface. The stiffness energy isdefined as#$. 2

(7)

%.  & d .

(8)which is the energy stored in the stiffness of themeasurement system. And, the external work is defined as
the work given from the outside, expressed as
In the processes of loading and unloading of the grossdisplacement, there exists the energy dissipation, therefore,
the relations of variation of the energy dissipation can beassumed as∆(#.  ∆%.  ∆.  ∆.  ∆#$.
(9)
where ∆Udis., ∆Uext., ∆Uel., ∆Uint., ∆Ustif. is the variation of
the energy dissipation, the external work, the elastic energy,
the interface energy, and the stiffness energy.
3 EXPERIMENTIn the experiments, the gross displacement Zt is controlled
by vertical motorized stage, and the force F and the contact

In the present study, the loading process is defined asincreasing of the gross displacement which means adownward direction of the motorized stage as positive. On
the other hand, the unloading process is defined as
decreasing of the gross displacement. The experiment need
to be performed as static state as possible. So, the grossdisplacement is controlled by a step of 1µm/s, and waiting
duration between steps is 60 seconds. The force and thecontact radius are measured moment to moment per second,and data to be plotted are picked up just before thedisplacement changes. The loading and the unloading
process are measured as a one cycle. And, the maximum
loading displacements are chosen to be 30, 60 and 120µm
for each cycle because there might be the region that thelinear elasticity is not satisfied.
4 RESULTS AND DISCUSSIONSThe experimental results of 30, 60 and 120µm of eachcycle are plotted as a relation of the gross displacementforce in Figure 3 and the gross displacement-contact radiusin Figure 4. In the loading process of Figure 3, the tensile
force is observed as an adhesive force at the initial contact,
and then increasing of compressive forces between the lensand the silicone rubber are observed with increasing of thedisplacement. And, the increasing of the contact radius arealso observed as shown in Figure 4. In the unloading
process of Figure 3, the compressive forces are decreased
until the maximum adhesive forces, and then the lens is
detached from the silicone rubber. And, in the same processof Figure 4, the constant area of contact radius are observed
at first, and progress of decreasing of the contact radius areobserved. From this experimental results, the adhesion
hysteresis, which is the differences in the loading path andthe unloading path, is clearly observed in the each cycle.
And, a dependence of the maximum loading displacementon the adhesion hysteresis is also observed in all the cycles.

122Figure 3. The measurements of the force in control of thegross displacement of the 30, 60 and 120µm cycle.

Figure 5. The most good agreement force curves of equation(4) with the experimental results as a function of the grossdisplacement (a) and the contact radius (b). Almost all plotted
dots with R=0.1965m, E=0.67MPa and k=19500N/m are wellmatched with the measurements in (a) and (b). Also, this resultsmeans that the linear elasticity of the silicone rubber is satisfied
in the deformation range of 120µm cycle or less.

Figure 4. The measurements of the contact radius in controlof the gross displacement of the 30, 60 and 120µm cycle.

4.1 EVALUATION OF R, E, k
Although the results of the each cycle in Figure 3 and 4 are
not the equilibrium state of total energy, the balanced forceof equation (4) as a function of gross displacement andcontact radius must be satisfied in the linear elasticity areaof the silicone rubber. Therefore, the unknown parameters
R, E and k need to be evaluated using equation (4) with themeasurements. First of all, the silicone rubber which is usedin the experiment might not insure a perfectly flat surface.
In case of the perfectly flat surface, R2=∞ in equation (2)and R=R1 is satisfied. If the silicone rubber is not a perfectly
flat surface, however, R2 affect the radius of curvature R.
This affected R can be evaluated using equation (10) which
is derived from equation (4) in condition of F=0 as

4.2 EVALUATION OF ∆γ
Each equation of the elastic energy (5), the stiffness energy(7) and the external work (8) can be calculated from using
the experimental results and the evaluated values of R, E, k
in Figure 5. In case of calculation of the interface energy(6), however, it is necessary to evaluate the work ofadhesion ∆γ previously. So, from equations (6) and (9),equation (11) which have a term of ∆γ can be derived as∆%.  ∆.  ∆#$.
∆(#.
 ∆γ ∆  ∆  
2(11)

where ∆Uext., ∆Uel., ∆Ustif., ∆(πa ) on the left-hand side canbe calculated from using the experimental results and the)(10) evaluated values of R, E, k. The right-hand side of equation
3 *+,(11) can be divided for two term. The first term is the workwhere the contact radius a and the gross displacement Zt are of adhesion ∆γ defined as a physical property which has a
the measured values of when the force F is zero in the gross constant value. And, the second term means the dissipateddisplacement Zt-intercept of Figure 3. Then, the radius of energy per unit changes of the contact area as a function ofcurvature R and R2 are evaluated as shown in table 1.
the contact radius. In briefly, the first term is constant andTable 1. The radius of curvature.
the second term is variable. The right-hand side of equation
R
Lens, R1
Silicone rubber, R2(11) can be observed as its left-hand side is already known.
0.1965m
0.2076m
3.6751m
The work of adhesion might be evaluated from observing
R2 of silicone rubber is larger than R1 about 1700% in table the variation state of the calculation results of equation (11).
1 which shows a reasonable value in practical scale. Second, And, the calculation results of equation (11) as a function
we need to evaluate the parameters of Young’s modulus E of the contact radius is shown as Figure 6. From Figure 6,
and stiffness k. These two values are correlated each other the constant value is observed in the loading process. On
as shown in equation (4). From fitting between the the other hand, the variation is observed in the unloading
experimental results and equation (4) as a function of process. This means that the constant value in the loading
displacement and contact radius with E and k, therefore, process can be assumed as the first term: the work offinding the most well matched results by feedback adhesion ∆γ, because the variation of the second term
adjustment of E and k simultaneously in the valid range of cannot be observed in the loading process although Figure
the E=0.6-0.7MPa. And, the results of fitting between the 6 is plotted as a function of the contact radius. Therefore,
experimental results and equation (4) with evaluated the work of adhesion can be evaluated as a ∆γ=0.021J/m2
parameters R, E, k as a function of displacement and contact from its loading process, and this physical property value
will be constant in all the process of experiment.
radius are shown in Figure 5.
123[4] K. Takahashi, et al.: J. Adhesion Sci. Technol., Vol. 9, No. 11 (1995), 1451
[5] K. L. Johnson: Tribology International, Vol. 31, No.8 (1998), 413[6] P. Silberzan, et al.: Langmuir, 10 (1994), 2466
[7] K. R. Shull: Mater. Sci. Eng. R. 36 (2002), 1[8] E. Barthel: J. Phys. D: Appl. Phys., Vol. 41 (2008), 163001.
[9] Y. L. Chen, et al.: J. Phys. Chem., Vol. 95, No. 26 (1991), 10736[10] G. Y. Choi, et al.: Langmuir, Vol. 13, No. 23 (1997), 6333
[11] H. She, et al.: Langmuir, Vol. 14, No. 11 (1998), 3090
[12] Z. Wei, et al.: J. Adhesion Sci. Technol., Vol. 24, No. 6 (2010), 1045
[13] H. Kesari, et al.: Philos. Mag. Lett., Vol. 90, No. 12 (2010), 891

Figure 6. The calculation results of equation (11) with the eachcycle are plotted as a function of the contact radius. Each of
dotted line A, B, C is the constant area of contact radius of theinitial unloading process as shown in Figure 3. So, thedivergent along the A, B, C is observed, because the variationof contact area ∆(πa2) is extremely small. The constant value
observed in the loading process is circled.

5 ENERGY DISSIPATION AND CONCLUSION
Each equation of the elastic energy (5), the stiffness
energy (7), the interface energy (6) and the external work(8) can be calculated from previous sections. So, the energy
dissipation Udis. can be calculated from an integration ofequation (9) as shown in Figure 7. From the results of
Figure 7, the energy dissipation looks nearly zero in all theloading process. A tendency of linearly increase ofdissipated energy as a function of the contact radius in theunloading process is observed. Therefore, this tendency ofthe energy dissipation can be written as∆(#.
∆2 

Figure 7. The integration results of equation (9) with all thecycles are plotted as a relation of the contact radius. The
dissipated energy is nearly zero in the loading process of eachcycle. On the other hand, the increasing of the energy
dissipation are observed linearly with decreasing of the contact
radius in the unloading process.

(12)

for its physical meaning that the dissipated energy ofproportional to the variation of circumferential crack lengthof the contact area. The calculation results of equation (12)can be plotted as shown in Figure 8. The calculation resultsof equation (12) is nearly zero in the loading process. On
the other hand, the results in the unloading process looks
nearly constant that it can be approximated as a line D.
Therefore, it can be cleared that Figure 8 can schematicallyapproximated to Figure 9. This shows that the energy
dissipation is nearly zero in the loading process from aini. toamax., and then the energy is dissipated as proportion to thecircumferential crack length of the contact area as theconstant value of equation (12) in the unloading processfrom the amax. to adet.. Therefore, the energy is dissipated perunit length of variation of the circumferential crack only inthe unloading process. From the results, the adhesion
hysteresis can be explained as shown in Figure 10, whichmeans that an unknown factor of the contact edge preventthe peeling between the lens and the rubber. This effect is
non-reversible between the loading and unloading
processes, and it can be suggested that this factor might beoccurred due to the state of the interface between thematerials, i.e. molecular bonding, surface roughness,dangling chains. Finally, the predictability of the adhesion
hysteresis can be suggested from introducing the constant.
REFERENCES

Figure 8. The calculation results of the dissipated energy ofproportional to the variation of circumferential crack length(12). In each of dotted line A, B, C shows the divergent along
the line in the constant area of contact radius of the initialunloading process. And, the factors that cause the energy
dissipation in the unloading process of Figure 8 can beapproximated as a line D.

Figure 9. The schematically approximated graph of the factor
that cause the energy dissipation of one cycle, where aini. is
initial contact radius, amax. is the radius when the maximum
loading displacement, adet. is the radius when detached.

Figure 10. Schematic illustration of the adhesion hysteresis
which is raised by the factor of the contact edge on thecircumferential crack in the unloading process.

[1] Y. Sekiguchi, et al.: J. Adhesion Sci. Technol., Vol. 26, No. 23 (2012), 2615
[2] K. L. Johnson, et al.: Proc. R. Soc. London A 324 (1971), 301[3] M. Deruelle, et al.: J. Adhesion Sci. Technol., Vol. 12, No. 2 (1998), 225

124

RADIO CHANNEL PARAMETER ESTIMATIONUSING SAGE ALGORITHM
Student Number: 12M18258

Name: PHAM Van Hue

Supervisor: Jun-ichi TAKADA

SAGE アルゴリズムを用いたチャネルパラメタ推定法
Abstract
新無線伝送技術を開発するにあたり, 時空間電波伝搬特性の解明が重要な基盤となる. それに向け, 本研究では MIMO(Multiple-Input Multiple-Output) チャネルサウンダにおける高分解能伝搬パス推定法を開発した. 具体的には、パラメト
リックモデルと多次元最尤推定を用いた SAGE (Space Alternating Generalized Expectation Maximization) アルゴリズムを用いて, 2.5ns の遅延分解能と 1 度の角度分解能を実現した. さらに, 開発した手法を用いて屋内環境における伝搬路特性を解析した.

1

Introduction

Recently, various applications of wireless services such as
Mobile phones, Wi-Fi, Cellular data service, wireless sensor networks, wireless energy transfer, etc. are occupying
most favorable electromagnetic spectrum for wireless communication (below 6 GHz band). Then, the design of future
mobile radio networks (beyond the fourth generation-4G)
requires research toward the characteristics of channels at
higher frequencies where we could occupy a larger bandwidth. In addition, by using multiple antennas at both thetransmitting and receiving sides of the communication link,
MIMO systems are able to exploit the spatial diversity induced by the rich multipath environment, increase data rates
and improve the quality of wireless link transmission. However, the performance of MIMO communication systems isstrongly dependent on MIMO channel condition. In the radio channel model shows in Fig.1a, although the array antennas part and the propagation environment of the radio
channel are complete different elements, they are treatedas a single model. The array antennas part is a part of thetransceiver and the engineer can design them as they want.
On the other hand, the propagation environment is a natural
phenomenon and we can not design or control it. Therefore,
we come up with double directional channel model (Fig.1b).
In this research, we focus on radio channel parameters estimation, which play a vital role in the process of double
directional channel modeling.

(a) Radio channel modelParameter

Value

Carrier Frequency
Signal Bandwidth
No. of multitones

11 GHz400 MHz
2048

Table 1: Specification of channelsounder2

Figure 2: Channel
Sounder

Radio channel measurement

The channel sounder is a device which is used to measure
the radio channel. By using it, the time-variant impulse response is obtained. The channel sounder (Fig. 2), which has
been used in this research, is prototyped firstly in [1]. Thenit was developed for various purposes such as multilink
channel measurement and double direction measurement.
One of the important properties of this channel sounderis high multipath resolution, which can be seen from two
aspects, spatial resolution and time-delay resolution. By
using Uniform Circular Array (UCA) antennas with optimal design of beam in radiation pattern, it could achievea high spatial resolution and maximum excess delay timeof 5.12µs with very small delay-time resolution of 2.5ns.
An important factor which may affect measurement results
is phase noise in signal source. Assuming that perfect frequency synchronism is possible between transmitter and receiver, the outputs of two quadrature demodulators results ina received signal vector with constant amplitude and fixedphase angle. However, this is in case of ideal frequency
sources, which is almost impossible in implementation. We
tried to reduce this effect as much as possible by using Cesium local oscillator as frequency source. The UCA antennas used in this research are dual-polarized micro-strip,
has 12 vertical-polarized and 12 horizontal-polarized ports,
which allow us to measure 24 × 24 MIMO channel. Radiation pattern is measured in an anechoic chamber in advance,
and is used for radio channel parameter estimation process.

(b) Double directional channel
model

Figure 1: The distinction between radio channel model anddouble directional channel model

125

3

Radio channel estimation

3.1

Wide-band MIMO channel model

We introduce narrow-band MIMO channel model for single
frequency bin [2] as follows
H(f ) =

L
X

aR,l (ϕR,l , θR,l , f ) Γl

l=1

aTT,l (ϕT,l , θT,l , f ) e−j2πf τl ,(1)

where H(f ) ∈ CMR ×MT , L is total number of paths considered in a environment, and MT , MR is number of antennas elements at transmitter and receiver side, respectively.
We also consider about dual-polarized complex path weight
for each l-th path, given in tensor form


γ
γVH,l
Γl = VV,l∈ C2×2 .
(2)γHV,l γHH,lFigure 3: Signal flow chart of SAGE algorithmwith M = MR · MT · Mf . The desired signal is interrupted
by additive white Gaussian noise, then the likelihood function or the probability density function (p.d.f) of x(θ) is


1
1
H
p (x; θ) =
exp
−
(x
−
s(θ))
(x
−
s(θ))
,
(π)M det(σ 2 I)σ2(5)and the maximum likelihood estimation of θ becomeshiHθ̂ = arg min (x − s) (x − s) .
(6)

Notice that the complex path weight Γl , which is dualpolarized complex gain of the l-th path describes all effects
which can be treated as frequency independent such as freespace path loss, loss on scattering or reflection points, andso on. In the channel model (Eq.1), aR (ϕR,l , θR,l , f ) is array response at receiver which is expressed as a function ofreceive-azimuth (ϕR,l ), co-elevation (θR,l ) and frequency f ,and aT (ϕT,l , θT,l , f ) is array response at transmitter whichis expressed as a function of transmit-azimuth (ϕT,l ), coelevation (θT,l ) and frequency f . The delay time τl corresponds to electrical length of propagation path of l-th path.
This model is only applicable to narrow-band channels, but
we are considering the wide-band channel model with bandwidth of interest 2B. By reforming the matrix form of
eq.1 to vector form and defining Mf as number of sampling points in frequency domain, we obtain the wide-band
MIMO channel model as below.
s = B(µ) · γ ∈ CMR .MT .Mf ×1

θIn order to solve Eq. 6, we come up with the SAGE algorithm.
3.2.2

The SAGE algorithm, which is applied for radio channel
parameters estimation [3], is a twofold extension of the Expectation Maximization (EM) algorithm. The basic conceptof SAGE is each iteration is an EM iteration to re-estimate
not all but only a subset component of θl while keeping theestimates of the other components fixed. Figure 3 shows
the signal flow chart of SAGE algorithm. Here, the SAGE
iteration step is one EM iteration for an individual signal
component. The SAGE iteration cycle consists of L SAGE
iteration steps and we repeat SAGE iteration cycle until thelikelihood function (Eq. 5) converges to its maximum value.
There are two major problems of SAGE algorithm. The
first problem is how to initialize parameters as the input of
SAGE. The second problem is how to manage the parameter search procedure. To deal with the first one, we use Successive Interference Cancellation based Initialization Procedure (SIC-SAGE). The basic idea behind the SIC-based
produced is as follows: The parameters vectors of the L
waves are estimated successively. To estimate the parameter
vector of l-th wave, an estimate of the interference causedby the previously estimated waves is calculated and subtracted from the measurement data. To do this, we are using
the first SAGE iteration cycle to detect strong path and remove it from measurement data. The second one could be
solved with Initialization and Search Improved (ISI-SAGE)
by using adaptive grid search, a search procedure with gridsize being decreased during the search produce.

(3a)

MR .MT .Mf ×4L

B(µ) ∈ C

γ ∈ C4L×1
The matrix valued function B(µ) is a description of thestructure of the radio channel. Here, we denote the nonlinTT T
ear parameters µ = τ T , ϕTT , θT
, ϕTR , θR
also as structural parameters. The complex path weights matrix γ =T[γVV , γHV , γVH , γHH ] are linear weight for this model,
which will be referred as linear parameters.
3.2
3.2.1

EM-based SAGE algorithm
Signal model

The general problem of interest here may be characterized
by using the follow modelx = s(θ) + n

(4a)
M ×1

= B(µ) · γ + n ∈ C

SAGE algorithm

(4b)

M ×4L

B(µ) ∈ C

γ ∈ C4L×1

126

point is located on a sphere S2 . This vector has unit radius
as shown in Fig.5. The vector unit Ω is uniquely determined by its spherical coordinates (ϕ, θ) ∈ [−π, π) × [0, π]
according to the relationΩ = e(ϕ, θ) = [cos ϕ sin θ, sin ϕ sin θ, cos θ]

T

.

(7)

The path weight of each direction is normalized by the total
path weight, then the mean direction could be expressed byLµΩ =The mean of azimuth ϕ̄ and the mean of co-elevation θ̄ are
obtained from µΩ as the solution of the nonlinear equation

Direction ofincidencee(ϕ̄, θ̄) =(1,0,0)4.2.2

Measurement campaign

The measurement environment layout is shown in Fig.4.
The measurement campaign was carried out in a wide area,
which could be used for large events. The material of hall
A is reinforced concrete, and some areas have metal plate
flooring. On each route (20m-long route), transmit antennas
are moving on these route, we take a total of 280 snapshots,
and distance between two snapshots is about 7 cm (about2.5λ). We only choose measurement points which has distance of 10λ for further analysis because of computation
complexity. This scenario is considered as a stationary environment, meaning there are no moving objects (the measurement was taken on holiday). The red and blue circles
represent the position of transmitter and receiver antennas,
respectively. The direction of arrows in these circles represent the direction of the first element of UCA, which means
the direction of zero degree direction of each local coordinate.
4.2
4.2.1

(10)
(11)

Cluster Identification

The clustering of paths is a problem that has recently drawn
a lot attention. Visual clustering has been used for longtime, but visual identification of clusters contains a certain
level of uncertainly and interpretation, also very difficult todeal with huge amount of data. In this section, we represent
an automatic clustering algorithm for estimated paths. In
this research, we are using a definition of cluster which wasused in COST 259: A cluster is a group of paths with similar
propagation characteristics. The clustering algorithm will
be used here is K-means clustering algorithm [5]. This algorithm gives a locally optimal solution with the given number of clusters. The idea of this algorithm, an iterative algorithm, is minimizing the total sum of the distance of paths
to their clusters centroid. However, one drawback of thisalgorithms is numbers of cluster should be determined before clustering identification, then we introduce Kim-Parks
Index to decide the number of cluster. This index measures
the ratio between the global intra-cluster spread and intercluster minimum distance, which should be minimized.

We will apply this algorithm and using channel model in
Eq.3a for real channel measurement data in the next section.

4.1

(9)

From Eq. 11, we obtain σΩ = 0 and σΩ = 1, if and only if|µΩ | = 1 and µΩ = 0, respectively.

Figure 5: Characterization of an incidence direction

Indoor environment analysis

1
µΩ .
|µΩ |

The rms direction spread can be finally expressed as
v
u
L n
o
u 1 X
2
σΩ = tke(ϕl , θl ) − µΩ k · Pl
Psn
l=1
q
2
σΩ = 1 − kµΩ k .

(0,1,0)

4

(8)

l=1

Figure 4: Floor plan view of the measurement environment(0,0,1)

1 X{e(ϕl , θl ) · Pl } .
Psn

4.3

ResultIndividual propagation paths have been extracted from measurement snapshots using SAGE algorithm developed in
Section 3. For each measurement snapshot, 100 paths weredetected. We used a global search for initialized parameters, and in order reduce computation time, search grid size
becomes half for each SAGE iteration cycle. Each snapshot
converges after 8-12 SAGE iteration cycles. For Route 1,
the mean of residual power is about 37.8%.

Characterization of radio channel
Direction spread

To characterize the direction spread, we have to consider
both azimuth and co-elevation [4]. We describe a direction
as a unit vector Ω with the initial point at O and the terminal127An example of path extraction is given in Fig. 6 withthe color represent the path weight in power. We lay over
the SAGE-detected paths on the panorama picture of environment and compare between SAGE-detected paths andbeamforming result. We could see that detected paths are almost matched well with beamforming result. Furthermore,
Fig. 7 shows the Delay Power Spectrum (DPS) and the
Azimuth Power Spectrum (APS) of measured channel andreconstructed channel using SAGE estimation result. The
strongest delay bins are estimated correctly in Fig. 7a. Thisis very important because in transmission, only strong signals are used. Figure 7b shows the directivity of channel,
and we could see that the signals mostly come from theLine of Sight direction, reflected by side walls and backwalls. We also did the cluster identification for Route 1;
the result for first snapshot is shown in Fig. 8 with numberof cluster K = 6. The number of clusters vary from 2 to
7. Finally, rms direction spread for intra-cluster and intercluster is shown in Fig. 9. From the cumulative distributionfunction (cdf) of them, we find that rms direction spread for
intra-cluster follows the normal distribution, but rms direction spread of inter-cluster follows the uniform distribution.

Figure 6: Matching SAGE detected-paths with panorama view
from Rx and comparison with beamforming result-80
Measured-DPS
SAGE-DPS
Residual-DPS-80

Azimuth Power Spectrum [dB]

Delay Power Spectrum [dB]

-70

-90
-100
-110
-120
-130

0

50

100
150
Delay [ns]

200

-90
-95
-100
-105
-110

250

Measured-APS
SAGE-APS
Residual-APS

-85

150

100

(a) DPS

50
0
-50
-100
DOA Azimuth [deg]

5

-150

(b) APSAs conclusions in this research, we have shown the implementation of SAGE algorithm for wide-band radio channel
parameters estimation and analysis of indoor radio channel spatial domain based on SAGE estimation result andcluster-based model. For future work, in terms of radio channel estimation, the estimation accuracy could be
increased by reducing the mismatch of proposed channel
model with reality, as well as the calibration of used UCA.
One more point, in terms of estimation algorithm, theSAGE is an iterative algorithm to solve the optimal problem, but the waste of computing resource can not be denied.
Gradient-based algorithm is well known as a better method
to solve this problem mathematically. However, it requires acontinuous information of antennas mathematically, which
is difficult in implementation.

Figure 7: Measured, SAGE reconstructed and the residual DPS
and APS

Elevation [Deg]500Delay [ns]

-50

150

100

50
0
-50
DOA-Azimuth [Deg]

-100

-150

C.1
C.2
C.3
C.4
C.5
C.6

150
100
50
0

150

100

50
0
-50
DOA-Azimuth [Deg]

-100

-150

References[1] Y. Konishi, M. Kim, M. Ghoraishi, J. Takada, S. Suyama, and H.
Suzuki, “Channel Sounding Technique using MIMO Software Radio
Architecture,” Eur. Conf. Antennas Propag., pp. 2546-2550, 2011.

Figure 8: Cluster identification with K = 6

0.8

0.8

0.6

0.6

[2] A. Richter, “Estimation of radio channel parameters: Models and algorithms,” Doctoral Thesis, Ilmenau University of Technology, 2005.
[3] B. H. Fleury, M. Tschudin, R. Heddergott, D. Dahlhaus, and K. I.
Pedersen, “Channel parameter estimation in mobile radio environments using the SAGE algorithm,” IEEE J. Sel. Areas Commun., vol.
17, no. 3, pp. 434-450, 1999.

CDF

1

CDF

1

0.4

0.4

0.2

0.2
Empirical
Normal Dis.

0
0

0.2

0.4
0.6
Directional Spread(a) Intra Cluster

0.8[4] B. H. Fleury and S. Member, “First- and Second-Order Characterization of Direction Dispersion and Space Selectivity in the Radio
Channel,” IEEE Trans. Inf. Theory, vol. 46, no. 6, pp. 2027-2044,
2000.

Empirical
Uniform Dis.
10
0

Conclusions and future work

0.2

0.4
0.6
Directional Spread

0.81(b) Inter Cluster[5] J. MacQueen, “Some methods for classification and analysis ofmultivariate observations,” Proc. fifth Berkeley Symp. Math. Stat.
Probab., vol. 233, no. 233, pp. 281-297, 1967.

Figure 9: CDF of rms direction spread of all clusters on Route 1

128

S TUDY A BOUT ANTENNA DE - EMBEDDING FROM 2- DIMENSIONALP ROPAGATION C HANNEL A ROUND S CATTERING O BJECT
Student Number: 12M18146

Name: Osamu Watanabe

Supervisor: Jun-ichi TAKADA

二次元モデルを用いた散乱体近傍でのアンテナと伝搬路の分離に関する研究
渡邉

修

送受信のアンテナを伝搬環境と切り離す方法であるアンテナディエンベディングを行うために、送信アンテナ、
受信アンテナが互いに非常に接近している状況を考える際に、離れている状況とどのような変化が現れるかを必要になるモードの数と、それによって現れる受信点での推定誤差の変化を観察した。なおシミュレーションには
境界要素法で二次元電磁界シミュレータを構築し利用した。

1

Introduction

order of cylindrical eigenmodes and the channel. PropagaAs one of the method to separate simulation domain into an- tion matrix in terms of Tx and Rx eigenmodes.
tenna domain and environment domain there is a technique 2 Theory of Antenna De-embedding in 2D
called antenna de-embedding. Antenna de-embedding is
Conducting the antenna de-embedding, first Tx antennaa technique to separately model antennas and propagaand Rx antenna is expressed with sum of cylindrical wave
tion channel. Radio channel consists of transmitter (Tx)functions (modes) Next, antenna de-embedded propagation
antenna, propagation channel, and receiver (Rx) antenna.
channel is introduced in the form of the matrix. Then error
Among these three elements, Tx and Rx antennas are theis defined so that accuracy of the method can be estimatedparts of the radio equipments which can be optimally or
quantitatively.
suboptimally designed. In contrast, propagation channel isa kind of natural phenomenon which can not be controlled 2.1 Cylindrical wave function expansion
nor designed. Therefore, the antenna de-embedded propa- As the homogeneous solution of Helmholtz equation in thegation channel can be used to evaluate the influence of an- cylindrical coordinates
tennas to radio channel property.
∞∑
Antenna de-embedded propagation channels have beenE=
qn Zn (k0 ρ)ejnφ(1)modeled as double-directional channel model [Steinbauer],n=−∞represented by direction of departure at Tx antenna and direction of arrival at Rx antenna, assuming plane waves. This E is electromagnetic field, ρ is distance form the centermodel is matching with the representation of antenna radia- of coordinate and φ is its angle. k0 is wave number in ation pattern in angular domain. Recently, an alternative ap- medium. Zn is a nth order of Bessel function and qn is aproach of using spherical wave functions has been proposed coefficient at the order. arbitrary electric field outside the[Nakai, Miao]. In this approach, antenna radiation charac- antenna region can be represented asteristics are represented by sum of spherical wave functions
M∑(mode), and the propagation channel is represented as theφ=
Cn Hn(2) (k0 ρ)ejnφ .
(2)coupling matrix between Tx antenna mode and Rx antenna−M
mode. The advantage of this approach is the natural truncaM is natural number which can be given depend on the sizetion of modes due to the cut-off property of spherical waveof the boundary region. When information of the electrofunction determined by size of antenna.
magnetic field at the boundary is provided, field informaThe objective of this study is to examine the application inside the antenna region is fixed, the theory known asbility of propagation channel modeling by using sphericalfield equivalent theory.
wave function when scatterer is in proximity to either or
Let us set the boundary in a shape of circle and find theboth of antennas. A typical example is a wireless bodycoefficients qn of the electromagnetic field inside antenna
area channel where wearable devices communicate eachregion. When the field at the boundary is written as EBound .
other. Instead of using full three-dimensional (3D) model,
Let us assume we have some F provides transformation
this study handles simplified two-dimensional (2D) model
for fast simulation. The cut off properties of spherical andEBound = FqBound(3)
cylindrical modes are very similar, and results of this study
can be easily applicable for 3D case. Antenna areas are We can obtain qn by solving
modeled by circles, and the fields at the perimeter of themqBound = F−1 EBound(4)
are modeled by using cylindrical wave functions.
Specifically, this study tried to know the influences of F is actually written as
the scatterer in proximity to antenna(s) on 1) the required
Fnm = Zn (ρ)ejnϕm .
(5)number of modes and 2) the required sampling interval on
the circular perimeter, to accurately model the channel reand ϕm is discretized as follows
sponse.
Transmitted wave is decomposed into certain number of
ϕm = (m − 1)∆ϕ, ∆ϕ = 2π/M
(6)129

Bessel function Zn have to be selected depend on the exis(2)tence of singular point inside antenna region. Hn is used
to satisfy the radiation condition at Tx antenna side, while
Jn is used to represent the non-singular field at Rx antennaside.

3 Simulation result
In this section, the error related to the cutoff of the modes
and accuracy of antenna de-embedding in certain situation
will be discussed.

3.1 Calculation of error due to cutoff
Modeling of propagation channel by using modeError related to reconstruction of the electric field at the
to-mode coupling
When Tx and Rx antenna’s radiation characteristic is repre- boundary is largely related to the size of the boundary tosented by modes, we can assume there to be exist mode-to- be used as observation. However even in the case that themode coupling as a relationship between Tx and Rx antenna size of the boundary circle to observe field is fixed, higher
modes. If we have boundary around Tx and Rx antenna to order of modes observed when there is large disturbance ofmeasure the boundary field at the boundary, by naming elec- the field exists near observer. To estimate how many ordertric field at the boundary of Tx antenna as ETX and electric of modes are required at certain situation, parameter study
have conducted. Distance between Tx antenna, Rx antenna
field at Rx antenna as ERX . qTX and qRX is written as
and scattering object have changed.
Study have done changing,
qTX = F−1 ETX(7) 1) Distance between Tx antenna and Rx antenna without
qRX = F−1 ERX .
(8) existence of scattering object.
2) Distance between scatting object and Rx antenna when
Assuming M exists which satisfy mode-to-mode coupling Tx antenna is located at far away.
between qRX and qRX . The equation is written as3) Distance between Tx antenna and Rx antenna with scatRX
TX
q = Mq(9) tering object located near the Tx antenna.
2.2

M becomes the matrix which embed the information of
propagation channel. When this matrix M satisfy arbitralqTX and qRX , once M derived channel propagation will becalculated without simulating Tx and Rx antenna directly.
This matrix M is derived below. When the n th modeis desired number of mode, total number of mode that thefield decomposed into becomes 2n + 1 which is between−n to n. Therefore the size of the each vector qTX , qRX
becomes 2n + 1. Thus M becomes square matrix size of(2n + 1) × (2n + 1) Assuming the M is regular, solving
simultaneous equation,

3.1.1 1) Distance change between Tx antenna and Rx
antenna without scattering object
Figure 1 shows minimum required number of modes to satisfy error NMSE lower than 0.05 and 0.01 each. x axis is
the distance between Tx and Rx antenna. Required numberof modes increases when the distance between Tx and Rx
antenna get closer when the distance is closer than 0.1λ.

(10)

M is obtained.
Using the equations (7) to (9) the relationship between
ETX and ERX can be expressed as
ERX = F(RX) MF(TX)−1 ETX .
2.3

(11)

20
Error 0.01
Error 0.05

18
16
14

modes

RX
TX
TX
(qRX
1 , · · · , q2n+1 ) = M(q1 , · · · , q2n+1 )Error have calculated defined in 2.3. Distance is taken inx axis. Threshold have set in the NMSE values of 0.05 and0.01 and minimum number of mode to satisfy this accuracy
is taken as Y axis.

12
10
8
6

Definition of error

42Errors which can occur related to antenna de-embedding
has some reason. One is due to the cutting off at the choice
10
10
10
10
10
distance [λ]of highest modes. Others is due to error at the calculation of(11) rooted from error at M. To evaluate the accuracy of the Figure 1: Required number of mode with change of distance beantenna de-embedding method, it is reasonable to focus on
tween Rx and Tx antenna (without scatting object)
the error at derived electromagnetic field at the boundaryof Tx and Rx antenna. NMSE(Nomralized Mean Square 3.1.2 2) Distance change between Scatting object andError) is derived as written in equation
Rx antenna when Tx antenna is located at far√∑
away|En−B(rec) − En−B |2
Figure 2 is the case of Tx antenna is located far away then=1√∑(12) distance of (100λ) from scattering object and Rx antenna
NMSE =
both. As a scattering object circular object with diameter of|En−B |22λ perfect electric conductor. Minimum required number
n=1
of modes to satisfy error NMSE lower than 0.05 and 0.01
En−B is ideal electric field at the boundary in a discreet no- each. x axis is the distance between scatting object and−B(rec)tation at the boundary E Bound . En
is reconstructed Rx antenna. Figure 2 does not show huge change in minwave using mode information q
imum required modes for both case of 0.05 and 0.01, with
−2

130

−1

0

1

2

the change of distance between Rx antenna and scattering
object. It can be said that scattering object does not disturb
the field large enough to create higher mode around Tx anmodewave onetenna because the size of scattering object is relatively
large
compare to the wave length.
θ20Error 0.01
Error 0.05

18

TX1

TX

16

modes

14
12
10
8
6
4
2

Figure 4: Location of sampling initial wave
−3

10

−2

−1

10

0

10

1

10

10

2

10

distance [λ]3.2.2 Estimated Matrix
Figure 2: Required number of mode with change of distance between Scatting object and Rx antenna (Tx antenna located far)

3.1.3

Using the vectors qTX 、qRX obtained in 3.2.1, M can bederived. By simply mapping them 5 can be obtained to3) Distance between Tx antenna and Rx antenna represent relationship between Tx antenna and Rx antenna
with scattering object located near the Tx an- modes.
tenna.
−10

Figure 3 is the case of Tx antenna and Scattering object islocated with distance of 0.1λ from Tx antenna. As a scattering object, circular object with diameter of 2λ perfectelectric conductor is used. x axis is the distance between
Tx and Rx antenna.

0.3

Rx Mode

−5

0.25
0.2

0
0.15
0.1

5

20
Error 0.01
Error 0.05

18

0.05

16

10
−10

−5

modes

14

0
Tx Mode

5

10

0

12

Figure 5: Colour map

108This shows which mode is highly related to one mode.

6
42

3.2.3 Reconstruction of waves
−2

10

−1

10

0

10

1

10

2

10

distance [λ]Figure 3: Required number of mode with change of distance between Tx and Rx antenna (Scattering object locatedclose)

Estimation of mode-to-mode coupling matrix

Matrix M is derived here which is the most important forantenna de-embedding process. Then using the obtained
matrix M is used to obtain ERX by using only using ETX
as the Tx antenna information.
3.2.1

Figure 6 is the prepared mode as a sample Tx mode to
conduct estimation of Rx field using antenna de-embedding
method. Estimated wave using antenna de-embedding
method and result of electromagnetic field directly calculated is compared in figure 7

Preparation of initial wave

0.18

To estimate M written in Section2.2, it is necessary to obtain set of vector qTX 、qRX as much as 2n + 1 and they
have to be independent each other. To achieve this initialwave is located as figure 4 shows. By illuminating initialwave at different location one by one, I have tired to create
independent 2n + 1 number of vector.
Radius of 0.1λ is used as observation boundary circle.
Inside the circle sampling initial wave is placed at over thecircle of 0.9 times of the observation boundary. The distance between each sampling initial wave is equally placedby shifting θ. TX1 、TX2 are sample of them.
131

0.16
0.14
0.12

power

3.2

Once matrix is derived shown as 図 5 smaller order of modecan be estimated with Rx antenna. By using it, receiving
mode can be translated into Rx field at the boundary. Thereis a result calculating receiving wave when it is assumed
that the sampling of the wave have done enough dense.

0.1
0.08
0.06
0.04
0.02
0
−10

−5

0

5

10

mode

Figure 6: Sample wave to test antenna de-embedding4 Result and future work

0.08
Ez rec0.07

Required mode considering 2D antenna de-embedding haveestimated for NMSE of 0.01 and 0.05. Shown the antenna de-embedding’s applicability near the scattering object when the sampling point is taken enough dense.
There will be need of conducting research using dielectric material and in the case of 3D situation which is more
realistic situation.

Ez

0.06

Ez

0.05
0.04
0.03
0.02
0.01
0
0

50

100

150

200

250

300

References

350

degree[1] C. A. Balanis, “Advanced Engineering Electromagnetics,” John Wiley Sons, 1989.

Figure 7: Comparison of ideal field and reconstructed field[2] N. Morita et al, “Integral Equation Methods for Electromagnetics,”
Artech House, 1991.

Figure 7 shows the almost perfect fit with estimated field
and ideal field. When the NMSE is calculated in this case,
NMSE =6.1 × 10−7 is obtained which mean perfectly thewave is reconstructed.

132[3] R. E. Collin, “Evaluation of Antenna Q” IEEE Transactions on antennas and propagation., pp. 23-27,1964.
[4] Kenji. N et al, “Double-directional channel with the spherical harmonics” Technical Report of IEICE., pp. 113-117,2010.

Development of MIMO Antenna Evaluation Method using Channel
Capacity and LTE throughput utilizing Extended Kronecker Model
Student Number: 12M18123

Name: Yuta Maruichi Supervisor: Jun-ichi TAKADA

拡張クロネッカモデルを用いたチャネル容量及び LTE スループットによる
MIMO アンテナ評価手法の開発
学籍番号: 12M18123

氏名: 丸一 雄大

指導教官: 高田 潤一

MIMO 技術に使用されるアンテナの性能は、周囲の環境の影響を強く受けるので、アンテナの評価のためには、アンテナ単体だけではなく、通信路容量、スループットなどシステム全体を評価する指標を使う必要がある。本論文では、MIMO チャネルモデルとして拡張クロネッカモデルを用い、LTE シミュレータを使用して MIMO 通信路の固有値とLTE スループットを予め対応表として作成しておくことで LTE スループットを簡易的に推定する方法を提案し、通信路容量と LTE スループットにより MIMO アンテナを評価した。

1

Introduction

Recently, many people use smartphones and tabletsand demand for higher data rate is still growing. To
satisfy this increase in demand, MIMO (Multiple Input
and Multiple Output) technique, which uses multiple
transmitter antennas and receiver antennas, has been
adopted for many systems such as Wireless LAN (Local
Area Network) and LTE (Long Term Evolution). Of
course, to maximize the MIMO system performance ,we have to select the best MIMO antenna from antenna
candidates, so we have to evaluate those antennas bysome antenna evaluation criteria.
Antenna directivity and eﬃciency are widely usedas the fundamental parameter for SISO(Single-Input
Single-Output) antenna evaluation parameters. However, these parameters are not suﬃcient for MIMO antenna evaluation because MIMO system performanceis dependent on the field environment. So, the antennashould be evaluated considering the environment by
the whole system evaluation parameters such as channel capacity, and throughput. Particularly, throughout is a more realistic criterion than capacity, hence
research which calculate the throughput for MIMO antennas evaluation are very actively conducted[1].
To measure the throughput, which are three estimation methods, field measurement, MIMO-OTA(OverThe Air) test, and software simulation, are mainly
used. For the first one, field measurement, we directly
measure the throughput through field measurements.
The throughput is the actual user throughput and amuch more realistic parameter, but it needs a lot of
costs for measurements. Moreover, it is diﬃcult to
get reproducibility in field measurements because theactual user throughput is dependent on the numberof users in a cell. The second one, MIMO-OTA test,
is where we construct a room which models an outdoor environment and measure the throughput in theroom. The room is fixed, so we can get the reproducible throughput, but the room construction cost is
not negligible. The third one, simulation software, iswhere we get throughput by using computing software.
It has flexibility that we can change any environment
parameters, but even simulation software needs software development /purchasing costs. Thus, the cur133

rent estimation methods are not cost eﬃcient to estimate the throughput.
In this research, a simple LTE throughput estimation method that utilizes eigenvalues of the MIMO
channel matrix is proposed. In addition, in the software simulation, it is necessary to model a real environment, and the Kronecker model is one popular method
to simulate a MIMO channel in a NLOS (non-line-ofsight) environment. However, the conventional Kronecker model does not include polarization eﬀects, so
the model should be extended for general usage. Thus,
the extended Kronecker model is introduced. Finally,
the real antennas attached on a car are evaluated by
the proposed method and LTE throughput is comparedwith channel capacity.

2

Antenna evaluation criteria

For single antenna evaluation, directivity and eﬃciency
are used as classical parameters. Directivity is the parameter which expresses the directive gain of an antenna, and eﬃciency expresses the ratio between total
radiated power from an antenna and the power that anantenna receives from the transmitter. Those parameters represent fundamental performance of a single
antenna.
However, for MIMO antenna evaluation, those parameters are not enough to evaluate the performance,
because the whole system performance of MIMO is dependent on the multi-path environment. To include
the multi-path environment, angular power spectrum(APS) should be included in addition to directivity andeﬃciency. Mean eﬀective gain (MEG) and antenna correlation are introduced as parameters which include
the APS model[2]. MEG is calculated by the following
equation,∫ 2π ∫ π{
1
X|Eθ (θ, ϕ)|2 Pθ (θ, ϕ)
Ge =
1+X 0
0
}
+ |Eϕ (θ, ϕ)|2 Pϕ (θ, ϕ) sin θdθdϕ,(1)where X denotes the cross correlation ratio, Eθ andEϕ denote the directivity of vertical polarization andhorizontal polarization respectively, and Pθ and Pϕ denote the normalized vertical APS and horizontal APS,

respectively. In the same manner as MEG, the antennacorrelation can be derived from the following equation,∫ 2π ∫ π {∗Eθi (θ, ϕ)Eθj(θ, ϕ)Pθ (θ, ϕ)1
ρi,j =X
1+X 0
Gei Gej0}2∗
Eϕi (θ, ϕ)Eϕj (θ, ϕ)Pϕ (θ, ϕ)+sin θdθdϕ , (2)Gei GejMonte-Carlo simulation

MIMO Correlation
MatrixMIMO
Channel Matrix

RMIMO =

vec(H) =BS antennacorrelation

UT antennacorrelation

i.i.d.Gaussian
VectorRBS

RUT

hi.i.d.

MIMO
Channel Matrix

SVD

The narrowband MIMO transmission model with NBS
base station antennas and NUT user terminal antennas
is given as

RMIMO = E[vec(H)vec(H)H ],(4)

vec(H) = [h11 , · · · , hNUT 1 , h12 , · · · , hNUT NBS ]T .

(5)

where

MIMO channel capacity

MIMO channel matrix can be decomposed by singularvalue decomposition(SVD) as equivalent multiple SISO
channels as
H = UΣVH ,(6)

where Σ is a real diagonal matrix, V and U are NUT ×
NUT dimensional and NBS × NBS dimensional unitarymatrix respectively. So, the MIMO channel capacity
can be calculated by the sum of multiple SISO channels, which has element gain of Σ2 asγ
C = log2 det(I +
Σ2 ),
NBS

(7)

where γ denotes signal-to-noise ratio (SNR).

Throughput Map

Second eigenvalue

2.5
2

80

Refer the MAP

60

1.5

40

T ( 1, 2)⌃ =case, the RMIMO
correlation
matrix is expressedas the0
MIMO hi.i.d.
Kronecker product between BS and UT correlation maTemporal LTE
Mean LTE
trices as i.i.d.Gaussian
Vectorthroughput
Throughput
2

1
2

0

1

2

Ttmp

1

20

0.5

0
0

1

2
3
4
First eigenvalue

5

6

0

T = E[Ttmp ]Kronecker model∫ 2π ∫ παRi,jEiα (θ, ϕ)Ejα∗ (θ, ϕ)P α (θ, ϕ) sin θdθdϕ,

=
0

0

(9)
where α denotes UT or BS, and i, j denotes the antenna number. Thus, from the directivity and the
APS, MIMO correlation matrix can be evaluated.
By using RMIMO , the channel matrix including antenna characteristics can be easily implemented in theMonte-Carlo simulation as
1
2
vec(H) = RMIMO
hi.i.d. ,

134

(10)

where hi.i.d. is zero mean, unit variance, complex, circular symmetric i.i.d. gaussian random vector. By repeating this loop, the average MIMO channel capacity
can be obtained (See Fig.1).

4

Extended Kronecker model

The classical Kronecker model does not include polarization [3]. In this work, the model is split into 4 independent single polarization combinations to extend
the model as [3]. To simplify the model, it is assumed
that vertical and horizontal polarizations have same
APS and each APS is independently distributed. Fromthese assumptions, Kronecker model can be applied toeach polarization combination as
RVv,Vv = RVV ⊗ Rvv , RHh,Hh = RHH ⊗ Rhh
RVh,Vh = RVV ⊗ Rhh , RHv,Hv = RHH ⊗ Rvv , (11)where capital letters and small letters in the subscript
show the polarization at BS side and UT side respectively. By considering the cross polarization ratio X,
MIMO correlation matrix is expressed as=+

In outdoor NLOS environments, the correlation between the Base Station(BS) and User Terminal(UT)array elements is observed to be independent. In this(8)This is the Kronecker model. Here, each element ofcorrelation matrices can be calculated by the directivity and the normalized APS as [4],R̃MIMO

3.3



(3)

where y(t) denotes the NBS dimensional received signal vector, x(t) denotes the NBS dimensional received
signal vector, n(t) denotes NUT dimensional receivernoise, and H denotes NUT × NBS dimensional MIMO
channel matrix.
In the NLOS environment, each element of H follows
the Rayleigh fading. To characterize the statistics of
H, MIMO fading correlation matrix RMIMO is definedas

3.2

C = E[Ctmp ]3

H = U VH

vec(H) =RMIMO = RBS ⊗ RUT .

Stochastic MIMO channely(t) = Hx(t) + n(t),Temporal MIMO
channel Capacity
Ctmp =✓◆
log2 det I +⌃2
NBS

Monte-Carlosimulation
throughput vs. Eigenvalue Map
Figure 1: Blockchart
of channelLTEcapacity
estimation(Obtained by LTE simulator)

MIMO channel model

3.1

Mean Channel
Capacity

2
RMIMO
hi.i.d.

hi.i.d.

3

SVD

H = U VH

1

RBS ⌦ RUT

Kronecker model

where i, j denotes the antenna number, and ⊗ denotes
the Kronecker product. In general, MIMO antennas
which have high MEG shows better performance, andMIMO antenna combinations which have high antennacorrelation harms the system performance.

Kronecker model

X
X
RVv,Vv +RHh,Hh
X +1
X +1
1
1
RVh,Vh +RHv,Hv . (12)
X +1
X +1

Second
Eigenvalue
第二固有値

60
50

1

40
30

0.5

20
10

0
0

1

2

3

First
Eigenvalue
第一固有値

4

LTE simulator

0

Vienna University
LTE link level Simulator[5]MIMO
2×2 MIMO(Open loop)
Number of user
1 (Single user)
Bandwidth
10 [MHz]
H-ARQ
No
Cyclic prefix
NormalChannelEstimation Monte-Carlo
Soft
Sphere Decoder
Kronecker model
simulation
MIMO
Correlation
MIMO
SVD
Cyclicprefix
NormalMatrixChannel Matrix
H = U VH
Channelvec(H) =
RMIMO
=
Rank
2 (Fixed) Mean
Capacity
RhR⌦
R
i.i.d.
BS
UT
MIMO
Number of trials
25
C = E[Ctmp ]Temporal MIMO
channel Capacityateach eigenvaluei.i.d.Gaussian
BS antenna UT antennaC=correlation
correlation
Vector2✓◆
SNR
normalization
14 log[dB](at Tr(Σ) = 1)
det I +
⌃
R
R
h
1
2

Figure 2: Eigenvalues vs. LTE throughput map(Generated by Vienna University LTE link level simulator)

tmp

BS

UT

i.i.d.

Monte-Carlo simulation
Eigenvalues
Matrix
2

⌃ =



i
1

0

0

MIMO
Channel Matrix

H=U V

H

ViennaUni. LTE
Simulator

Mean LTE
Throughput

T ( i1 ,j
2

Random Unitary
MatrixTemporal LTE
throughput

U, V

Ttmp

j
2 ) = E[Ttmp ]i or j + 1

vec(H) =1
2

RMIMO hi.i.d.

LTE throughput vs. Eigenvalue Map
Throughput
Map simulator)(Obtained
by
LTE
3

SVD

80

H = U VH
⌃2 =



NBS

1

0

0

2

2.5
2

Refer to the MAP

1.5

T ( 1,

1

60
40

2)

20

0.5
0
0

1

2
3
4
First eigenvalue

5i.i.d.Gaussian
VectorTemporal LTE
throughput

hi.i.d.

Mean LTE
Throughput

Ttmp

T = E[Ttmp ]60

Figure 4: Block chart of LTE throughput estimation(Proposed method)

Change Eigenvalues*

i+1

Kronecker model

Monte-Carlo simulation
MIMO
Channel Matrix

22Second eigenvalue

70
1.5

Table 1: Parameter of throughput vs. eigenvalues map

Mean LTE throughput (Mbps)

80

LTEスループット(Mbps)

2j*i : First eigenvalue number, j：Second eigenvalue number

Figure 3: Block chart to bulid throughput vs. eigenvalues map

5

Throughput estimation using
throughput vs. eigenvalues map

As explained above, most of throughput estimation
methods are costly and time consuming, therefore there
is a demand for a simple evaluation method. In thiswork, to satisfy this demand, it is proposed that a
LTE throughput vs. eigenvalues map is generated inadvance using a LTE simulator, and LTE throughput
is estimated by utilizing the map in almost the samemanner as the channel capacity estimation (See Fig.4).

5.1

Throughput vs. eigenvalues map

To use the proposed method, it is necessary tocreate the map by using a LTE simulator. In this work,
Vienna University LTE link level simulator is used[5].
This is a Matlab based simulation software and free
for academic usage. The procedure to make the map
is shown in Fig.3.
1. Decide the target eigenvalues.
2Here, (Eigenvalue) = (Singular value) .

4. Save the average throughput at given eigenvalues, and change eigenvalues.
By repeating steps 1.∼4., the map can be created. The
map created using Table 2 settings is shown in Fig.2.

5.2

After making the map, it is possible to estimate LTE
throughput in the same manner as the calculation of
the channel capacity. The procedure is shown in Fig.4.
After eigenvalues are gotten in the same manner as thechannel capacity estimation, temporal LTE throughput is estimated by referring to the map.
One of the advantages of the proposed method is thatonce the map is created, it is not necessary to use LTE
simulator which needs a long simulation time. Actually, if the map is published, it is possible to estimate
LTE throughput without using LTE simulator. The
disadvantage is the lack of flexibility. The throughputof the map is the average of the LTE throughput, so
the evaluation must be conducted by the average value.
In addition, the throughput is dependent on the simulator settings, so the new map needs to be created
when those simulator parameters are changed .

5.3

2. Make a MIMO channel matrix using the eigenvalues and random unitary matrices, and input
it into the LTE simulator.
3. Calculate the temporal throughput, and repeat
step 2. as a Monte-Carlo simulation to get average throughput.
135

Proposed estimation method

Characteristics of LTE throughput
and channel capacity

The process of proposed method is quite similar tothe channel capacity estimation. To distinguish thoseparameters and show the eﬀect of proposed method,
the relation of those parameters is examined. Figure
5 shows the correlation of those parameters when theInpane V (MEG = -8.96 dBi) Inpane H (MEG = -8.66 dBi)
90

Table 2: Simulation setting

120

Inpane, Shark
Same as Table 2
Measured data (Fig.6)
Taga model
10 [deg]
20 [deg]
6[dB]
20 [dB]
5000−20dBi150

30−40dBi180

0 180

Direction

0

(deg)
330

210

(deg)

300

240

300

270

270

Shark V (MEG = -3.18 dBi)
90

120

20dBi
60
0dBi

−20dBi150

Shark H (MEG = -3.38 dBi)
90

120

−20dBi

150

30

0 180

0

(deg)
330

(deg)
330

210

Correlation：0.276
300

240

300

270

270

---：0dBi, 一 : Vertical Polarization, 一：Horizontal Polarization

50

Figure 6: Characteristic of target MIMO antennas(θ = 0[deg], XPR = 6[dB], and V polarization is main.)40

Channel capacity

20
10

20

40
60
80
Channel Capacity (Mbps)

100

Figure 5: Correlation of Capacity and LTE throuhgput(SNR = 20dB, MIMO channel matrix : i.i.d.Gaussian)

60

100

50

80
60
40
20
0

i.i.d. gaussian channel is inputed as the MIMO channel matrix. From the figure, it is obvious that channel capacity does not correspond to LTE throughput
one-to-one, actually even for the same capacity, there
is about 10∼15Mbps variance in LTE throughput, so
those parameters can be treated as diﬀerent parameters, and from [6], it is shown that higher correlation
and antenna gain imbalance of antenna make the variance larger.
Finally, 2 real MIMO antenna sets, an antenna
attached on the instrumental panel of a car (called“Inpane”) and an antenna attached on the roof of acar (called “Shark”) , are evaluated by the channel capacity and the LTE throughput. The characteristics ofthe antenna sets are summarized in Fig.6. Shark haslarge MEG, but the antenna correlation is higher thanthat of Inpane. Using Table 2 settings, the channel
capacity and LTE throughput are calculated as Fig.7- Fig.8. For both measure, Shark showed better performance and correctly evaluated the MIMO antennasets.

Conclusions

As a conclusion, the research has demonstrated thesimpler LTE throughput estimation method, and the
LTE throughput was compared with the channel capacity and showed little diﬀerence. Finally, real antennas were evaluated by both measures and showed thesame tendency.

LTE throughput

120

Average throughput [Mbps]

30

Average channel capacity [Mbps]

Average throughput (Mbps)

30−40dBi

180

60

20dBi
60

0dBi

−40dBi

240

6

330

210

Correlation：0.021
24030−40dBiMoving

210

0
0

20dBi
60

120

0dBi

−20dBi150

Target antenna
Map setting
Directivity
APS model
MeanStandard deviation
XPR
Average SNR
Number of trials

90

20dBi
60
0dBi

40
30
20
10

InpaneShark

0InpaneShark

Figure 7: Simulation re- Figure 8: Simulation result
sult (Channel capacity) (LTE throughput)

References[1] 小川晃一, “携帯端末アンテナシステムの評価・解析・高性能化技術” , 電子情報通信学会論文誌 B,
Vol. J93-B, No. 9, pp. 1100-1114, 2010.
[2] T. Taga, “Analysis for mean eﬀective gain of mobile antennas in land mobile radio environments,
IEEE Trans. Veh.Technol., vol. 39, No. 2, pp.
117-131, May 1990.
[3] J.P. Kermoal, L. Schumacher, F. Frederiksen,
and P.E. Mogensen,
Polarization diversity in
MIMO radio channels: experimental validation ofa stochastic model and performance assessment,
Proc. 2001 Fall IEEE Veh. Tech. Conf., pp. 22-26,
2001.
[4] J. Takada, “Propagation Modeling for Performance Evaluation of MIMO Antennas,
Microwave Workshop and Exhibition Digest, Yokohama, Japan, 2007, CD-ROM.
[5] C. Mehlfhrer, M. Wrulich, J. C. Ikuno, D.
Bosanska and M. Rupp, “Simulating the Long
Term Evolution Physical Layer,” in Proc. of the
17th European Signal Processing Conference (EUSIPCO 2009), Aug. 2009, Glasgow, Scotland.
[6] 丸一 他, 信学技報, RCS2013-282, Jan. 2014.

136

COOPERATIVE COMMUNICATION IN NARROW-BAND WIRELESS BODY AREA
NETWORK: CHANNEL AND PERFORMANCE STUDY
Student Number: 12M18287

Name: KARMA Wangchuk Supervisor: TAKADA Jun-ichi

狭帯域無線ボディエリアネットワークにおける協調伝送方式の検討
Abstract
To improve the reliability of narrow-band wireless body area network operating at 2.4 GHz ISM band, cooperative
communication is proposed in this work. Using an off-the-shelve ZigBee radio transceiver multi-link channel measurements
in a full mesh topology for most probable sensor node locations on the body were made. After statistically modeling thesechannels the performance gains due to three cooperative schemes, simple decode-and-forward relaying, cooperative decodeand-forward relaying, and incremental decode-and-forward relaying were evaluated. Performance gains in the order of 16
dB with incremental decode-and-forward relaying has been demonstrated when the statistically best cooperator was selected.
These findings will be useful in actual body area network design.

1

Introduction

2

Cellular
Pulse
WLAN

Bluetooth/others

Body Area Network

Figure 1: A conceptual BAN connected to the internet

1. Highly energy efficient: because the sensor nodes
must be small, it will have small batteries that should
last on the order of days to years, which in turn means
low transmit power.

Body Area Network

A network of sensors, actuators and radio transceivers
communicating in the vicinity of, or inside, a human body
(but not limited to humans) is defined as wireless bodyarea network (BAN) [2]. Different from the personal area
networks (PANs) BAN is characterized by the requirement of short-range, low power and highly reliable wireless communication at data rates up to 10 Mbps in close
proximity to or inside a human body, all the while keeping the electromagnetic radiation into the body, given as
specific absorption rate (SAR) at a safe minimum [3]. A
conceptual BAN for healthcare application, in a star topology where various body sensors communicate centrally toa coordinator node which in turn connects to a network or
the internet via a gateway device is illustrated in Fig.1.
2.1

GatewayVi

The continued advancements in wireless communication
technology has meant it has become so ubiquitous it is
now a part of our everyday lives. It is then no surprise thatthe versatility and mobility afforded by wireless communication technology combined with the progresses madein miniaturization of wireless transceivers and electromechanical body sensors is foreseen to revolutionize, besides
others, the healthcare industry - which the finalization of
the IEEE 802.15.6 BAN standard seeks to accelerate. Besides health care there is a huge opportunity for application of BAN in many different fields like sports, military,
space applications, business and entertainment among others [1]. However reliability issues arising due to channel
characteristics, environment, and other factors such as interference needs to be addressed.

2. Very robust against interference: interference from
Wireless LAN, Bluetooth and other sources is a hugeconcern especially for BAN operating at the ISM
band.
3. Capable of meeting wide application requirements:
depending on the application, BAN needs to support
wide range of data rates ranging from 1 Kbps to 10
Mbps, while still satisfying high reliability and lowlatency requirements.
4. Capable to cope with the unique characteristics of
BAN channels: the affect of body, body posture andmotion on radiation pattern of the transmitting andreceiving antenna and on propagation of the electromagnetic waves make BAN channels very unique anddifficult to characterize. This is even more complicated by the affect of the surrounding environment.
Also the on-body BAN channel is dominantly slow
fading and prone to burst errors [4] that can not becorrected with error correction codes of reasonable
complexity.

BAN Challenges

The main challenges in wireless body area network arises
from the fact that for it to be ubiquitously adopted thenodes should be small, comfortable and safe for the subject while being reliable at the same time. Reliability for
BAN healthcare applications is vitally important [?]. The
BAN nodes therefore must be:
137

A
A

J

J
(a)

(b)

Figure 2: (a) Three node BAN showing simple relaying scenario(b) Cooperative diversity combining scenario

Given these challenges a narrow-band BAN could face severe reliability issues, which are exacerbated at ISM bands
due to interference from other wireless systems. We therefore need ways to mitigate this reliability issue.
2.2

Cooperative Communication
Figure 3: Different motion scenarios (from left-right,
clockwise): descending steps, walking along thehallway, standing still, sitting and working at the deskIn wireless networks, signal fading arising due to channel impairment can be mitigated through the use of diversity [5]. Space, time, and frequency diversity and the their
combinations thereof have been shown to offer dramatic
performance gains. In contrast to conventional from ofspace diversity, recently another form of diversity technique known as cooperative diversity have gained huge
popularity [6] [7]. In cooperative communication a nodetakes advantage of the other nodes in the network to relay its message to the final destination by exploiting thebroadcast nature of wireless channels. This has the effectof turning the cooperating nodes into virtual antenna arrays. Therefore the ultimate receiver receives copies of thesame signal over multiple paths which can be combinedusing any of the diversity combining techniques such as
maximal ration combining (MRC), equal gain combining (EGC) and selection combining (SC), resulting in thechannel variations caused by fading, shadowing and otherforms of interference to be averaged.
It has be demonstrated that cooperative diversity can provide full spatial diversity translating into greatly improved
robustness to fading for the same transmit power, or dually
reduced transmit power for the same performance. Powersavings of up to 12 dB for outage probabilities around one
in thousand has also been shown to be possible [6].
2.2.1

Motivation:
BAN

To take this concept further, in Fig.2(b) even when the
direct link from the J:Ankle node to the Navel node is notundergoing deep fading, the node at the A:Wrist to still cooperate and forward the message to the coordinator node.
At the coordinator node there are now two copies of thesame signal, which could be combined using any of thediversity techniques such as MRC, EGC and SC to obtain some performance gains. As mentioned earlier the
possible gains could be stated dually as: improvement indata communication reliability,such as outage probability
or average error rate, at the same transmit power or reduction in the required transmit power to achieve the same reliability. In this work only decode-and-forward operation
at the cooperator and SC at the coordinator are consideredas these are most practical and easily implementable incurrent digital radio transceivers without much modification.

3 Multi-Link Channel Measurement andChannel Modeling
In order to be able to study the performance gains due tocooperative communication in 2.4 GHz BAN the channels
channels between the different nodes needs to be measured and modeled. The conventional approach to measure
on-body BAN channels was to use long cables and multiport Vector network analyzers (VNA) and measure the S12and S21 transmission coefficients. However this approachseverely limits the motion scenarios and environment themeasurements can be made in. To overcome this in thiswork a channel sounder for the 2.4 GHz ISM band using
off-the-shelve ZigBee transceivers was developed. With
this wearable channel sounder, measurements in any environment and any motion scenarios could be made. The
downside of the sounder is that phase information of thechannel can not be obtained. The Fig.3 shows the four
different motion scenarios considered, constituting everyday motion scenarios in a typical office environment. For
health care application the major sensor nodes locations
are already known, as shown in Fig.1, therefore in thisCooperative Communication in

Given that a BAN is expected to have one or more sensor
nodes operating in the vicinity of each other and communicating to a central coordinator, it is quite obvious that one
could make the nodes cooperate and thereby exploit thepossible gains from cooperative diversity. Fig.2(a) illustrates a three node BAN with coordinator located at Naveland the sensor nodes located at J:Ankle and at the A:Wrist.
Now, when the node at the Ankle is trying to communicate with the coordinator node, if because of interference,
environment, body motion and posture or combination ofall, the link is severely attenuated that the nodes are notable to communicate, then the other node in the network
at A:Wrist, could cooperate and relay the message to thecoordinator. This could help improve the reliability of the
network.
138

28.6 cm

D

gn
o

a

BPSK modulation as per the IEEE802.15.6 PHY specifications. In I-DF the coordinator node broadcast a request
for transmission from the cooperator, such as a negativeAcknowledgment(NAK) message, when the direct transmission is received in failure. The cooperator then retransmits the message it received from the source. For illustration the equivalent channel for I-DF relaying is shown in
Fig.6

Modeling

It was found that the modeling of the path-loss components of the channel as a function of distance with some
path loss exponent gave large modeling errors and contradictory results. Also some of the links with longer distance
had lower path loss compared to few links that were separated by shorter distance. Therefore in this work the pathloss values have been taken as deterministic values anddependent on the node position. Unlike in other wirelesschannels in BAN the fading component could not be separated into small scale fading and large scale fading components. This was further complicated because the effectsof the antenna can not be de-embedded from the channel measurement [8]. The fading component of the BAN
channel were therefore modeled as a composite of both thesmall scale and large scale fading. The common approachof fitting statistical distribution to the measurement data
was adopted to model the fading components using lognormal distribution, Rayleigh distribution, Riciean distribution, Nakagami-m distribution, Weibull distribution andGamma distribution.The distribution parameters were extracted using maximum likelihood estimator. For selecting
the model Akaike Information Criterion with correction
AICc was utilized. It was found that the log-normal distribution provided the best fit or the second best fit among thedifferent distribution considered for majority of the links.
For the 45 channels fitted the results are shown in Fig.5
The final channel model consisted of deterministic pathloss component and long-normal fading component.

4

Lo

Figure 5: Number of links described by each statistical
distribution

work all the possible channels between all these nodes andfor few more locations in a full mesh topology were measured. The respective node location and the details of thetwo measurement subjects are given in Fig.4
3.0.2

rm

ei
g
Ra
yl

Figure 4: Subject information and node locations

m

0

am

J

G

5

i

I

h

J

Subject B
22 year
63 Kg

lSubject A
25 Year
68 Kg

10

ul

I

H

N

A

ei
b

G

H

15

W

F

B

Ri
ci
an

165 cm

G

E

al

C

173 cmF

B

Number of Channels

E

A

Best fitnd
2 best fit

20

D

ak
ag
am

25.5 cmC

1st hopRg sr

S

2nd hop
Equivalent Channel
Feedback

gr
d

gsd

SC

D

Figure 6: Equivalent channel for I-DF relaying

4.1 Performance GainAs performance measure we focused on SNR-outage
probability give as:∫ γthPout =pγ (γ)dγ(1)0where γ is the instantaneous received SNR. For equal
power transmission at all the nodes (1) is in fact the valueof cumulative distribution function (CDF) of the channel
gain, substituting g for γ and gth for γth .In this work thisis referred to as SNR-outage performance to differentiate
from the rate outage probability commonly used to compare the efficiency of different cooperative schemes. After comparing the SNR-outage probability due to the statistically best cooperator, not surprisingly the I-DF gave
greater performance gain compared to the S-DF and the
C-DF as seen in Fig.7. The gains due to C-DF and S-DF
when employing the best cooperator are not very different,
especially when the S-DF equivalent channel is better thanthe direct channel. It can therefore be concluded that thegains are mainly because of improvement in path loss due
to relaying and not due to diversity combining. From Fig.7
it is also clear that on average there is always some gain
due to cooperative communication. For instance with I-DF
relaying for any destination (or coordinator) location there
is on average a minimum of 5.58 dB gain over direct transmission and 5.52 dB average gain over direct transmission

Cooperative Transmission Schemes andPerformance Evaluation

For comparison four different transmission schemes: Direct transmission, Simple decode-and-forward (S-DF) relaying, Cooperative decode-and-forward (C-DF) relaying, and Incremental decode-and-forward (I-DF) relaying
were evaluated. The difference between S-DF and CDF was that in C-DF the transmission from the cooperating node and the source were combined at the coordinator using SC. MRC and EGC were not considered as thereal system would only support non-coherent differential
139Future Research
Evaluating the gains and the energy consumptions due tocooperative communication in BAN based on actual hardware would be very useful. Actual implementation of cooperative communication would require more careful considerations not just in the PHY layer but also upper layersof communication protocol. Cross layer optimization oftransmission schemes would be a challenging and usefularea of future work.

9
S−DF
C−DF
I−DF

Average Gain [dB]

8
7
6
5
4
3
2
1
0

H

A

B

E
C
D
F
Destination Location

G

I

J

References[1] M. Chen, S. Gonzalez, A. Vasilakos, H. Cao, andV. C. M. Leung, “Body Area Networks: A Survey,”
Mobile Networks and Applications, vol. 16, pp. 171–
193, Aug. 2010.

Figure 7: Average gain with best cooperator for different
destination locations (at 10% outage probability)H[2] 802.15.6-2012 - IEEE Standard for Local andmetropolitan area networks - Part 15.6: Wireless Body
Area Networks. No. February, 2012.

15 dB

A

Destination NodeB
E

[3] TG6-draft, “IEEE802.15-10-0245-06-0006,” 2010.

10 dB

C

[4] M. Kim and J. Takada, “Experimental investigationand modeling of shadow fading by human movement
on body surface propagation channel,” in 2009 IEEE
Antennas and Propagation Society International Symposium, pp. 1–4, IEEE, June 2009.

D
F
5 dB
G
I
J
H

A

B

E

C
D
F
Source Node

G

I

J

[5] J. Proakis, Digital Communications. McGraw-Hill
Book Company, 2nd ed., 1989.

0

Figure 8: I-DF relaying gain with best cooperator at 10% outage
probability[6] J. N. Laneman, Cooperative Diversity in Wireless Networks : Algorithms and Architectures. PhD thesis,
Massachusetts Institute of Technology, 2002.

for any source location. On checking the improvement in
the outage threshold at 10% outage with all schemes, thethreshold was the highest when the destination node was
located at E: Shoulder. This suggests that if cooperative
communication is employed in BAN the best position forthe coordinator node or the hub is at the shoulder.
In Fig.8 the gains due to I-DF with best cooperator for
all combination of source, cooperator, destination node isshown in It is clear that with carefully selected cooperator
there are almost up to 16 dB gains to be had at 10% outage
probability.

[7] A. Sendonaris, E. Erkip, and B. Aazhang, “User cooperation diversity-part II: implementation aspects andperformance analysis,” IEEE Transactions on Communications, vol. 51, pp. 1939–1948, Nov. 2003.

5[8] J. Takada, T. Aoyagi, K. Takizawa, N. Katayama, T.
Kobayashi, K. Y. Yazdandoost, H. Li and R. Kohno,“Static Propagation and Channel Models in Body
Area,” in Cooperation in Science and Technology(COST), (Lille, France), 2008.

Conclusions and Future Research

In this work its has been demonstrated that in a BAN withrealistically located sensor nodes by employing cooperative communication there is substantial performance gains
in terms of improvement in outage threshold which would
directly translate into SNR or transmit power, or equivalently the reliability. Up to 16 dB improvement in the outage threshold at 10% outage probability and a minimumof 5.58 dB average gain for any coordinator node location can be achieved with I-DF relaying. The best location
for the coordinator node is the shoulder. With carefully
chosen cooperator reliability can be greatly improved in a
BAN with cooperative communication.

140