INTRODUCTION OF ROAD TECNOLOGY AND
POLICY MAKING- International Joint Seminar of VJU and NILIM November 25th, 2022

On November 25th, 2022, NILIM held the International Joint Seminar online with VJU*,
Hanoi.
The theme of this seminar is “Introduction of Road Technology and Policy Making”.
NILIM presented our technologies about maintenance and management of roadstructures, disaster prevention and recovery, and policies of MLIT. VJU presented
characteristics of soft clays in the red river delta.
To begin with, the Director-General of NILIM and Program Director of VJU delivered
greetings as organizers. Next, there were presentations and Q&A sessions and theseminar concluded with a successful address from VJU at last.
The following is the outline and activities of the seminar. For the details, please see thenext page and beyond.
* Vietnam Japan University was established in Hanoi in 2014 by JICA’s TechnicalCooperation Project. VJU has tried to develop human resources practically on aninternational level by conducting internships at Japanese companies. Japanese language
is also taught as a required subject. VJU has been offering only Master’s Courses but theyalso opened Undergraduate Courses in September, 2022.

1

1. TIME
November 25th, 2022 (Fri)
13:00-15:20 (Vietnam Time)
15:00-17:20 (Japan Time)
2. OUTLINE
Title
Introduction of Road Technology and Policy Making
Attendees
96 (Number of pre-registrations), including 14 from Japanese companies
Venue
Online (ZOOM)
Contents
At the beginning, the Director-General of NILIM gave an opening address as theorganizer and the Director for International Affairs, Planning Division, Road Bureau,
MLIT addressed as the guest of honor. Then, the Road Structures Department gavea presentation on “Maintenance and Management of Road Structures in Japan”, theRoad Traffic Department presented on “Efforts to Identify Passable Roads after
Disasters from Road Traffic Big Data”, and the Sabo Department presented on“Prevention and Mitigation of Sediment Disasters in Japan”. VJU presented on“Compressibility Characteristics of Soft Clays in the Red River Delta”. There werevigorous Q&A sessions in each presentation. The joint seminar finished in great
success with closing remarks by a lecturer from VJU.

Greeting by Director-General of NILIM

Participants of NILIM

Commemorative screenshot of attendees

2

INTRODUCTION OF
ROAD TECHNOLOGYAND POLICY MAKING-International Joint
Seminar of VJU and NILIM-◉TIME

25th Nov 2022 (Fri)
13:00-15:20 (Vietnam Time)
15:00-17:20 (Japan Time)◉VENUE

Online(ZOOM)◉REGISTRATION AND

CONTACT INFO
Email:takeda.s@vju.ac.vn
Register:
https://forms.gle/oiMq
Yu7oQd6MHxCh6◉PROGRAM

1.Opening address & Guest's address
2.Session(1) Maintenance and managementof road structures in Japan:
Decade of road maintenancerevolution(2) Efforts to identify passable
roads after disasters from roadtraffic big data
(3) Prevention and mitigation of
sediment disasters in Japan(4) Compressibility Characteristics
of Soft Clays in the Red River
Delta
3.ClosingTIME TABLE■13:00～13:10 (Vietnam Time), 15:00～15:10 (Japan Time)

Opening Address
Mr. OKUMURA Yasuhiro, Director-General, National Institute for Land andInfrastructure Management (NILIM), Ministry of Land, Infrastructure,
Transport and Tourism, Japan
Prof.Dr. Sc. Nguyen Dinh Duc, Program Director, Master's Program in CIVIL
Engineering(MCE), VNU Vietnam Japan University (VJU), Affiliation: Vietnam
National University (VNU), Hanoi）（■13:10～13:15 (Vietnam Time), 15:10～15:15 (Japan Time)

Guest's Address
Mr. FUKUI Takanori, Director for International Affairs, Planning Division, Road
Bureau, Ministry of Land, Infrastructure, Transport and Tourism, Japan■13:15～15:15 (Vietnam Time), 15:15～17:15 (Japan Time)

Session1: Maintenance and management of road structures in Japan:
Decade of road maintenance revolution
Dr. KATAOKA Shojiro (Research Coordinator for Road Structures
Management, Road Structures Department, NILIM)
Session2: Efforts to identify passable roads after disasters from road traffic big
data
Mr. ISHIHARA Masaaki (Researcher, Intelligent Transport Systems
Division, Road Traffic Department, NILIM)
Session3: Prevention and mitigation of sediment disasters in Japan
Dr. AKIYAMA Kazuya (Research Coordinator for Sediment Disaster
Prevention, Sabo Department, NILIM)
Session4: Compressibility Characteristics of Soft Clays in the Red River Delta
Ms. Khin Phyu Sin (Master's Program in CIVIL Engineering(MCE), VNU
Vietnam Japan University (VJU))■15:15～15:20 (Vietnam Time), 17:15～17:20 (Japan Time)

Closing
Dr. Nguyen Ngoc Vinh, Lecturer, Master's Program in CIVIL Engineering(MCE),VNU Vietnam Japan University (VJU)
Chairman: Dr. Nguyen Tien Dung, Lecturer, Master's Program in CIVIL
Engineering(MCE), VNU Vietnam Japan University (VJU)

国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN

Maintenance and Management ofRoad Structures in Japan:
Decade of Road Maintenance Revolution
KATAOKA Shojiro
Research Coordinator for Road Structures Management
Road Structures Department, NILIM, MLIT, Japan

VJU-NILIM Joint Seminar online, November 25, 2022

Contents

1. Introduction
2. Decade of Revolution from 2012
3. Contribution & Challenge by NILIM

国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN1

Various structures support road traffic
Even small failure of one structure suspends it
Cut
Rockfall protection

Ground anchor

Retaining wall
Banking

Cut

Reinforced
soil wall

Cut
Banking

BridgeBanking
Rockfall protection
Reinforced soil wall
Cut

Rock shed
BridgeRetaining wall

Cut
Retaining wall

国総研 National Institute for Land and Infrastructure Management, MLIT, JAPANTunnelCulvert2

Road structures suffer deterioration
In Japan, we have…

700K+ Bridges

10K Tunnels
CulvertReinforced soil wall

Shed
Various types of Earthworks
国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN

1G m Pavements3

… because they are aging.
Number of bridges built

50 years ago

MLITSuperstructure materials
Other
5%

Expressway companies
PC
36%

Prefectures/Major cities
Municipalities

RC
11%

Total length as of 2017High economic growth period
1955-1973

1964 Tokyo Olympic

Steel
48%

Bridges older than 50 years
2022
2032

https://www.joc.or.jp/past_games/tokyo1964/

国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN4

History of national highway inspection (-2012)
Each Regional Bureau used its own guideline
Uneven inspection methods and results

1988 First common Bridge Inspection Guideline

2004 Revised Bridge Inspection Guideline
Close visual inspection every 5 years
Hokkaido“Evaluation” was introduced for taking action

Close visual inspection of each bridge
every 10 years
Serious deterioration cases were found

I

Good

II

Preventive maintenanceTohokuIII Repair work is required
IV Emergency action is needed
Hokuriku
Kanto
2012 Ceiling panel
Kinki collapse in Sasago Tunnel
Chugoku
Chubu
KyushuShikoku
Okinawa

Chloride (Salt)-induced deterioration

2001 NILIM was established and started
supporting revision of the guideline

国総研 National Institute for Land and Infrastructure Management, MLIT, JAPANDec 2, 20125

Turning Point : Ceiling panel collapse in Sasago tunnel
https://www.mlit.go.jp/road/road_e/pdf/RoadMaintenance.pdf

Ceilingpanel

NILIM supported verification of inspection method and the accident analysis.
国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN

6

Future Direction : Preventive Maintenance
Repeat minor maintenance work for saving life cycle cost compared to leaving
the damage until replacement or major repair work.
[Preventive maintenance]+ Lifetime extension+ LCC minimization

CF Sheet reinforcement etc.
Cost

Minor repair

Replacement

Deterioration

Minor repair
Minor repair

0

20

40

60

80

100

Year
120 経過年数• Replace more often• Traffic has to be stopped• Larger LCC[Follow-up repair]
Replacement
Cost

Replacement

Replacement
Minor repair

Minor repair0

国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN

20

40

60

80

100

120

Year
経過年数

7

Decade of revolution from 2012 (1/3)
2012 Ceiling panel collapse in Sasago Tunnel
2012 Urgent inspection for tunnel equipment2013 Intensive inspection for road stocks
We must- establish a maintenance cycle(obligation of administrators)- establish a mechanism to facilitate the cycle(budget, system, skill, support)

Close visual inspection of tunnel equipment and bridge

2013.6 Amendment of Road Act
2014.3 Public notice of revision to Ordinances

2014.7 into force

Implement a close visual inspection of all tunnels, bridges, etc. every five years
Evaluate structure condition across Japan based on a uniform standard

2014.6 National guidelines for periodic inspection
NILIM contributed to the revisions and draft-making of the guideline.
国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN8

Dramatic changes in inspection

Municipalities must conduct theinspection every 5 years as well.

Distant visual inspection became invalid.

https://www.mlit.go.jp/road/road_e/pdf/RoadMaintenance.pdf

国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN9

2014 National guidelines for periodic inspection
MLIT, with support from NILIM, developed a series of inspection guidelines describing- Types of deformation need attention- Case examples
in order to assist inspection by municipalities .

国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN10

Decade of revolution from 2012 (2/3)
2014.6 National guidelines for periodic inspection
2014.7 First round of the periodic inspection started (-FY2018)
Summary of the first round inspection(bridges)-10yrs-20yrs-30yrsGood-40yrsPreventive maintenance-50yrsRepair work

50yrs-

Emergency action

Unknown*
Total*Mostly short (<15m) bridges administered by municipalities-Older bridges are worse, as expected.
-Quantitative evidence was obtainedfor planning maintenance strategy.

2019.2 Revised national guidelines for periodic inspection
NILIM contributed to the revisions and draft-making.
国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN11

2019 National guidelines for periodic inspection
Issues from the 1st-round inspection (FY2014-2018)- Difficult :Inspections require technical considerations
Reference materials
Reference for checking underwater part
Reference for damage examples and inspection of bridges with tensile elements(Suspension, Cable-stayed, Arch, ….)- Consuming:
Prevent over-checking
Illustrate necessary/unnecessary checking
in the guidelines or references
Construction joint
Lifting/Peeling
Cost-cut by new technology
Alternative method to close visual inspection

Repair part

Crack

Construction
joint

Hammering test area from 2nd-round
国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN12

Support for using new technologies
Questionnaire to municipalities:
The cost required for the inspection is a burden.
Municipalities
Strongly agree

Agree Neutral

DisagreeStrong needs for cost-cut by new technologies
An example (one item)

What technologies are available?
Performance catalog of inspection support technologies
16 items (Feb. 2019)

172 items (Sep. 2022)

Guideline & Examples
国総研 National Institute for Land and Infrastructure Management, MLIT, JAPANhttps://www.mlit.go.jp/road/sisaku/inspection-support/

13

Decade of revolution from 2012 (3/3)
2019.2 Revised national guidelines for periodic inspection
2019.4 Second round of the periodic inspection started (-FY2023)
Overall inspection result is improving from the first round.
716,466 bridges

717,993

719,717

Replace20%

Replace20%

Bridges722,176

Replace
20%

Good
Preventive maintenanceRepair work
Emergency action

20-30 years to erase III･IV.
FY2018(1st round result)

FY2019FY2020

FY20212024.2? Re-revised national guidelines for periodic inspection
国総研 National Institute for Land and Infrastructure Management, MLIT, JAPANNILIM conducts research forthe revisions and draft-making.
14

Contribution & Challenge by NILIM (1/2)
NILIM carried out stochastic analysis using segment-level inspection data of 24,000 bridges.

a-e: Damage extent of segment
Example: Markov chain state transition probabilities for corrosion in steel I-girder beams%
Girder-ends
Span-centers
1.0
100

e

0.8
80

0.00

a

b

c

1s

1s

40
0.4
20
0.2

d

1s

60
0.6

1s

e

d

b

c
a

Girder-ends and span-centers have different deterioration characteristics.
Deterioration & LCC cost estimations have a large uncertainty.
国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN

15

Contribution & Challenge by NILIM (2/2)
NILIM developed “AI image-searching application” for convenient use of inspection big data.
Output similar
image from DB

Input

Inspection images chosen by the AI

Target damage photo

AI imagerecognition

Targetdamage photo

DB
Pick up yourfavorite image
Segment-level database
Inspection &repair work of
39,000 bridges

Output corresponding
inspection & repair
history from DB

Records of similar cases can beeasily picked up as a reference.
国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN16

Summary- Learning precious lessons from the tunnel accident in 2012,
periodic inspection was regulated to all road administratorsand has been conducted since 2014.
- Overall inspection result seems improving but still takes
a few decades to change our major work from “follow-up
repair” to “preventive maintenance”.
- Administrators, especially those in municipalities, feelthe inspection cost is heavy and cost-cut by newtechnologies becomes an urgent issue.
- MLIT continues support for using new technologies.
国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN17

Thank you for your kind attention !
For more about NILIM…
NILIM Website (English)
http://www.nilim.go.jp/english/eindex.htm

Creating future of society

Brochure

http://www.nilim.go.jp/english/about/nilim2022e.pdf

You Tube Channel
https://www.youtube.com/channel/UC5l193hxIF1CrZ85DTBnm8Q

Annual Report

http://www.nilim.go.jp/english/annual/annual2022/ar2022e.html

国総研 National Institute for Land and Infrastructure Management, MLIT, JAPAN18

2022 International Joint Seminar of VJU and NILIM

Efforts to Identify Passable Roads
after Disasters from Road Traffic Big Data

Researcher, Intelligent Transport Systems Division,
Road Traffic Department, NILIM, Japan
ISHIHARA Masaaki

00Contents

1. Introduction
2. Traffic Record Display System
2.1 Outline
2.2 Issues & Improvements
3. Example of applying the system
4. Conclusion
11

1. Introduction• In Japan, flood damage has become more severe, and thedanger of large-scale earthquakes is increasing.
• In the event of a disaster, it is necessary to provide drivers withroad closure information as quickly as possible.
Number of annual occurrences of rainfall(≧50mm/h)(times/year)

Hypocenter distribution of magnitude (≧6)
2012-2021

500
450
400
350
300
250
200
150
100
50
0

1976

1981

1986

1991

1996

2001

2006

2011

2016

2021

https://www.data.jma.go.jp/cpdinfo/extreme/extreme_p.html

https://www.bousai.go.jp/kaigirep/hakusho/pdf/r4_all.pdf

22

1. Introduction• Field studies are necessary to grasp the locations of roadclosures• Lack of immediacy due to the time it takes to collect the initial
information• Demand for a system that provides road administrators withreal-time information on non-passable roads and traffic
restrictions.

https://www.mlit.go.jp/river/sabo/jirei/r2dosha/r2_07gouu_201222.pdf

https://www.hido.or.jp/itsapq/jsp/auth/trab/no97/tokusyu5-10.pdf

33

2. Traffic Record Display System
2.1 Outline
Information overlaid on a map: traffic records derived from vehicle probe data.
Grasp the traffic status of all roads in Japan.
Identify passable routes that can be used to access disaster areas.

Electronic Toll Collection system

Road

・time
・position・speed・acceleration etc.

VehicleＥＴＣ２.０Car Navigation
System44

2. Traffic Record Display System
2.1 Outline
Information overlaid on a map: traffic records derived from vehicle probe data.
Grasp the traffic status of all roads in Japan.
Identify passable routes that can be used to access disaster areas.
80%
70%
60%
50%
40%

ETC2.0 penetration rate (expressway, December 2021)
Number of vehicles equipped with
ETC2.0：About 7.47 million(February, 2020)

Large cars
64.9％

All car models
27.5％

30%
20%
10%
0%

2016.4
H28.4 2016.10
H28.10 2017.4
H29.4 2017.10
H29.10 2018.4
H30.4 2018.10
H30.10 2019.4
H31.4 2019.10
R1.10 2020.4
R2.4 2020.10
R2.10 2021.4
R3.4 2021.10
R3.10

55

2. Traffic Record Display System
2.2 Issues & Improvements

Issues• Lacking in terms of immediacy of data
• Adapting to big data
• Difficulty comparing with past data
• Deterioration and obsolescence

Improvement
I.

Display the traffic record

II.

Segmented display by road type

III. Immediacy of data
IV. Displayable time frame66

2. Traffic Record Display System
Ⅰ. Display the traffic record
Before upgrade

After upgrade

Display roads traveled by one ormore vehicles on a map
Display content cannot be adjusted
according to conditions

Free settings can be madeaccording to traffic conditions andregions

Example of display

77

2. Traffic Record Display System
Ⅰ. Display the traffic record
Improved to display the number of passing vehicles
classified by category(1) Number of categories displayed(2) Classification by number of passing vehicles(3) Display for each road type(color and width of displayed lines)(4) Lines can be shown or hidden

Example display settings for number of passing vehicles

882. Traffic Record Display System
Ⅱ. Segmented display by road type
• Before the upgrade, the system
would display traffic records on themap by road type in two categories.
• Because road type is not segmented,
jurisdiction of the road administrator
cannot be determined on the map.
• Improved the system to allow forsegmented display by road type.
Example of display by road type99

2. Traffic Record Display System
Ⅲ. Immediacy of data
Before

After

12:00
12:10
Disasteroccurs

12:00
12:10

13:00

Number of passing
vehicles×（before the disaster+
after the disaster）

×

12:30
〇
13:00

〇 Number of passing vehicles
only after the disaster
14:00

14:00

Shortened by
up to 1.5 hours: the time when the system can output the number of passing vehicles
after the disaster10102. Traffic Record Display System
Ⅳ. Displayable time frame
BeforeAfter

2 hours ago

2 hours ago
Traffic records
per hour

1 hour ago

Overlapping display(Up to last 8 days)

1 hour ago

Present

Present

Aggregate and display for up to
48 continuous hours(Can be referenced for the past year)

Upgrade of displayable time frame
1111

3. Application Examples

About the 2020 Kyushu Floods
Number of victims
Missing and deadInjured

86

77

Kumamoto, Kyushu

Number of damaged houses
Completely or
Floodedpartially destroyed
6,129

6,825
July 4 at 3:50 a.m.

Put on high alert

July 4 at 4:50 a.m.

Heavy Rain Emergency
Warning

July 4 at 5:00 p.m.

Published Passable
Map on the Internet
1212

3. Application Examples

LegendPassable
Passable (only outbound)Impassable
Landslides

0

10

20 Kilometers

1:500,000 scale
The publicly available Passable Map (first version)

13
13

4. Conclusion• System utilizes vehicle probe data collected by
MLIT• System aggregates and visualizes traffic records• Road administrators can promptly grasp traffic
restrictions• Possible to promptly provide road users withinformation

1414

4. Conclusion

In the future• Gain an understanding of the needs andopinions of users• Evaluate the system• Implement function improvements

15
15

Prevention and mitigation of
sediment disasters in Japan
Kazuya AKIYAMA
Research Coordinator for Sediment Disaster Prevention,
Sabo Department, NILIM

Contents

1. Sediment disasters in Japan
2. Non structural measures(Land-use regulation and control)

21. Sediment disasters in Japan3

What is sediment disasters?
Sediment disasters can be generally classified in a debris flow, a landslide, and aslope failure

Debris flow: flowing earth and sand fromupstream
Sediment
disasterLandslide: moving earth and sand on a
gentle slope
Slope failure : moving earth and sand ona steep slope

Others：Disasters or phenomena supported by Sabo (Sedimentdisaster prevention) Works・Drainage sediment control: prevent sediment from flowing
downstream and rising river bed
・Driftwood disaster: prevent fallen trees from flowing downstream
・Snow avalanche: avalanches damage to community
・Volcanic eruption: volcanic mud flow, debris flow, etc.

4Debris flow
Nachkatuura Town,
Wakayama Pref.

Aso City,
Kumamoto Pref.

Part of soil, stone and gravel making up a hillside and river bed isintermingled with water from long-continuing or localized rainfall, etc.
and is carried instantly downstream. The flow is called a “debris flow”.
The velocity being 20-40 km/hour depending on the magnitude, thedebris flow easily destroy houses and other structures all at once.

5

Landslide

Nagano City,
Nagano Pref.

Joetsu City,
Niigata Pref.

A landslide is a phenomenon in which soil mass on a slope moves
slowly along the slip surface downward the slope under the
influence of ground water and other causes. Since landslides occur
over an extensive area and a large amount of soil mass is moved ingeneral, it can cause serious damages.

6

Slope failure

Asakura City,
Fukuoka Pref.

Minamiaso Village,
Kumamoto Pref.

A slope failure is a phenomenon that a slope collapses abruptly due toweakened self-retainability of the earth under the influence of a rainfall
or an earthquake. Because of sudden collapse of slope, many people failto escape from it if it occurs near a residential area, thus resulting in ahigher rate of fatalities.
7

Outline of sediment disasters
from 2000 to 2021 (for 22 years) in Japan

Data: Sabo (Erosion and Sediment Control)
Department, Ministry of Land, Infrastructure,
Transport and Tourism (MLIT)

8

Sediment disasters caused by the heavy rainfrom August 3 to 5, 2022
ArakawaRiver
Niigata
Prefecture

total rainfall(mm)Figure： Japan Meteorological
Agency(JMA)

Koiwauchi, Murakami City,
Niigata Prefecture
Photos： Sabo (Erosion and SedimentControl) Department MLIT

Debris flow and driftwood disasters in the easternpart of Murakami City, Niigata Prefecture9

Sediment disasters caused by the heavy rainfrom August 3 to 5, 2022

Fukui
Prefecture

National Road No.8

total rainfall(mm)Hokuriku Expressway
Figure： Japan Meteorological
Agency(JMA)

Photos：Explanatory materials for the 3rd meeting，Fukui
Prefectural Disaster Traffic Management Study Group,
Kinki Regional Development Bureau, MLIT

Debris flow disasters in Minamiechizen Town,
Fukui Prefecture

10Changes with the patterns of hourly rainfall
and sediment disasters

Recently 10 years
average327（frequency） Frequency of hourly rainfall over 50mm/

600
500

1000 rainfall measurement points in thepast 30 years

average292

258(average400

for 10 years)

300
200
100
0
（frequency）
4000

Occurrences of sedimentdisasters in the past 30 years
for 10 years)

2000

average1450

average
1150

927(average

3000

Increase and seriousof sediment disaster

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

1998

1996

1994

0

1992

1000

Data: Japan Meteorological Agency(JMA) and Sabo (Erosion and
Sediment Control) Department, MLIT

11

Comparison of flood disaster and sediment disasterFlooddisaster

Sediment
disaster

Keywords of sediment disasters
Keywords of flood disaster
1. Flood points exist inside river (flood area
can be fixed)
2. Basic and trigger factors are limited (rain)
3. Sufficient period of time to evacuate (ex.
rain→rising river water→disaster)
4. Water of rising river can be recognizedand danger degree can be judged

1. Sediment disaster points exist everywhereon slope
2. Basic and trigger factors are various (rain,
rising groundwater level, earthquake,geomorphology, geology, etc.)
3.Unpredictable (sudden) phenomena (ex.
earthquake→slope failure, rain→debris flow)
4. Phenomena can not be recognizedbecause of under ground and danger degree
can not be judged

12

2. Non structural measures(Land-use regulation and control)・Sediment Disaster Prevention Law

13

Three strategies for preventing
sediment disasters (sabo works)
Protect people
Non-structural measures
Warning and evacuation

Land conservation
Disaster mitigation/
Land monitoring

In areas designated as“sediment disaster hazard
areas” based on the Sediment
Disaster Prevention Laws
・Preparation of hazard maps
for sediment disasters
・Strengthening of warningand evacuation system throughpreparation of sedimentdisaster warning informationand their dissemination,
improvement of information
system, etc.

・Sediment Disaster
Prevention Law

Protect people & properties

Structural measures
Facilities against disasters

・Sabo works
・Landslide prevention
works
・Slope failure prevention
works
・Sabo Law
・Landslide Prevention
Law
・Law on Prevention ofDisasters Caused by
Steep Slope Failure

Control development
and protect people

Non-structural measures
Restriction on acts, landdevelopment andbuilding structure

Sabo designated area,
landslide and slope failure
prevention areas
・Restriction on cutting
tree, banking and otheracts considered harmful forthe conservation of land.
Special sediment disasterhazard area (Red-zone)・Restriction on building
structure
・Restriction on specificdevelopment works
・Sabo Law
・Landslide Prevention Law
・Law on Prevention ofDisasters Caused by
Steep Slope Failure
・Sediment Disaster
14
Prevention Law

Urbanization and sediment disasters

Situation of residential land development in Saeki Word, Hiroshima City 15

Sediment disasters in the southwestern part ofHiroshima Prefecture on June 29, 1999

・sediment disasters in the southwesternpart of Hiroshima Prefecture：325
・human damages：31 people died and 59 injured
・house damages：101 houses totally destroyed16Outline of Sediment Disaster Prevention Law

The “Sediment Disaster Prevention Law*” was established with the intention of instituting
土砂災害防止法の概要
comprehensive
non-structural measures to protect people from sediment disasters. These
non-structural measures include public of risk information of areas prone to sediment disaster,development of warning and evacuation system, restriction on new land development for
housing and other specific purposes, and promotion of relocation of existing houses(legislated on May 2000).
* Law concerning the Promotion of Sediment Disaster Prevention in Sediment Disaster Hazard Area

Sediment Disaster under the Scope of the Law： Debris flow, landslide and slope failure
Preparation of basic guidelines for preventing sediment disasters[Minister of the Land, Infrastructure, Transport and Tourism]

・Basic policies for preventing sediment disasters
・Guidelines for basic survey
・Policy in the designation of special sediment disaster hazard areas
・Policy for relocation of buildings in special sediment disaster hazard areas

Implementation of basic survey [Prefectural government]
・Survey for designation of sediment disaster hazard areas andspecial sediment disaster hazard areas

Implement
basic survey

Survey geomorphology, geology
and land use ofareas such as stream
or slope where
suffering sedimentdisasters

Designation of sediment disaster hazard area (area prone to sedimentdisaster)[Governor of prefectural government]
・Establishment of a system for the communication of information, and warning and evacuation
・Publicity of information on warning and evacuation to local people

Designation of special sediment disaster hazard area (area where
damages to building and serious hazards may be posed to residents)[Governor of prefectural government]

・License system for specific land development
License is required for land development for housing and social welfare facilities
・Restriction on building structure (Building certification is required even for buildings outside thecity planning area)
・Recommendation of relocation of buildings that are vulnerable to serious damages in case of asediment disaster・Financing and funding for those who move their residence to a safe area under recommendation

Designate hazard area
Designate areas based on
the basic survey

Sediment disaster hazard area
(Yellow zone)(area prone to sediment disaster)Special sediment disasterhazard area (Red-zone)(area where damages to building andserious hazards may be posed to residents)

17

Determination of sediment disasterhazard area (Yellow Zone)

Debris flow

Area located under a torrent prone to debris flows and having a slope
gradient 2 degrees or more below the crest of the alluvial fan.

Landslide・Landslide area (Area which is currently prone to landslides or possibly
vulnerable to landslide in future)
・Area included within a distance equivalent to the length of the landslide
mass from the bottom end of the landslide area (250m if the length ofthe landslide mass is longer than 250m)

Slope failure

・Area having a slope gradient of 30 degrees or more and slope height of
5m or more・Area included within a 10m horizontal distance from the top end of theslope・Area included within a distance twice the slope height from the bottom
end of the slope (50m if the slope height is more than 50m)

Debris flow

Landslide

Slope failure18Determination of special sediment disasterhazard area (Red Zone)
Area in which the magnitude of force exerted on a building
by the movement of earth and rocks caused by slope failure
exceeds the structural strength that an ordinary building canwithstand without causing injury or death.
Yellow Zone
Red Zone

Debris flow

Landslide*In case of a landslide, theabove-stated force is themagnitude of force that acts
on a building in 30 minutes
after debris and rocks starts to
act on the building by thesliding
land
block.
The
landslide hazard area is an area
included within a 60m-distancefrom the bottom end of thelandslide area.

Slope failure

19Sign board of sediment disaster hazard area
(Yellow zone) and special sediment disasterhazard area (Red zone)

20

Example of sediment disasterhazard area (Yellow & Red Zone)
Sediment disaster hazard area (Yellow zone)
Special sediment disaster hazard area (Red zone)

Debris flow
Debris flow Debris flow
Debris flow
Debris flow
Debris flow
Slope failure

Slope failure

Slope failure
Slope failure

Slope failure

Slope failure21

Sediment disaster hazard map
A hazard map against sediment disaster shows therelation between debris flow, landslide, and slope-failure
hazard areas and evacuation places, evacuation routes,
method of transmitting information at the event of
sediment disaster, and necessary matters in order toensure smooth warning and evacuation.
Slope failure

Debris flow

Sediment disaster hazard area

Evacuation places anddisaster classification

Method of transmitting
22
information

Examples of sediment disaster hazard map

Digital Mapping data

Kouchi district, Saeki Word,
Hiroshima City

Aerial photo (orthophoto)

Kusaka district, Ohi Town, Fukui Prefecture 23

Summary
Three strategies for preventing
sediment disasters Structural measures (Facilities against disasters)Hard measures are important to protect people lifeand properties

 Non structural measures (Warning and evacuation)
Protect people even if properties are damaged

 Non structural measures (Restriction on acts, landdevelopment building structure)Do not increase hazard area24

Thank you for your attention
Kazuya AKIYAMA

Sabo Department, National Institute for Land and InfrastructureManagement, MLIT
Asahi 1, Tsukuba, Ibaraki, 305-0804, JAPANe-mail：akiyama-k92ta@milt.go.jp

25Compressibility Characteristics of Soft
Clays in the Red River Delta
Presented by
Khin Phyu Sin

1

Content
1.
2.
3.

Introduction
Objective of the research
Methods used in this study for the determination of cr,
cv, Cc, Cr, p
4. Location of the Study sites
5. Sample collections
6. Analysis results and procedure
7. Conclusions
References
Appendix2

1. Introduction
Geological condition of the RRD▪ Second largest delta in Vietnam and fourth-largest
delta in Southeast Asia, after the Mekong, Irrawaddy,
and Chao Phraya deltas, in terms of delta plain area
▪ It was formed due to the sedimentation process
throughout the Holocene period (9 kyr BP to date).
▪ Quaternary and Holocene sediments in the delta
were strongly influenced by both fluvial and marine
environments. Stratigraphic cross sections in thedelta show the presence of fluvial sediments,
estuarine sediments and deltaic sediments (Funabiki
et al. 2007)▪ The sediment accumulation curves (attitude vs age)from Tanabe et al., 2006 and Funabiki et al., 2007
indicate that up to the depth of about 40 m (fromthe present MSL), all deposits found from the cores
are Holocene sediments with the age of less than 10
kyr;
Figure 1. Quaternary geological and topographical map
of RRD and adjacent areas (Tanabe et al., 2006)
3

1. Introduction➢ The Red River Delta (RRD) includes many industrial zones(parks) and expressways where soft ground in large scalemust be improved before the construction of facilities.

➢ Consolidation parameters, especially cr and cv, areimportant parameters in estimating ultimate and timedependence settlement values of the ground.

Many industrial Zones in Hai Phong City (similar to otherprovinces in the delta)

Excess Pore water pressure (u) at any time t after loading  2u 1 u 
 2u ucr  2 +Eq. 1. where cr and cv = horizontal and vertical coefficients of consolidation of soil
 + cv 2 =r r 
zt rSettlement of the improved ground at any time t u
St = U t Sc = 1 −  Sc = f ( cr , cv , t ,Sc ) u0 

Eq. 2.

where Sc = ultimate consolidation settlement42. Objectives of the Research
To evaluate horizontal coefficient of consolidation from consolidation testwith central drain (e.g., cr,CD) and with a peripheral drain (e.g., cr,PD) ofclays at some test sites in the delta using existing methods and to rank
the reliability of the methods.

To examine the cr,PD/cr,CD ratios from analytical solution on ideal soil
and from experimental data on actual soil and the influence of someparameters to the ratios.

To evaluate compression index (Cc), recompression index (Cr) andpreconsolidation stress (p) of the clays from the test sites anddevelop possible correlations for the parameters.
5

3. Methods used in this study for the determination of cr, cv, Cc, Cr, and p
Methods to determine radial coefficient of consolidation, cr, vertical coefficient of consolidation, cv,
compression index (Cc), recompression index (Cr) and preconsolidation stress (p) from Oedometer test
Table 1. Existing methods for the determination of cr from Table 2. Existing methods for determination of cr fromradial consolidation test with a CD using incremental loading
radial consolidation test with a PD using incrementalloading
1 Root t method(Berry & Wilkinson, 1969; Sridharan et al., 1996)
1. Root t method (Head and Epps, 1986)
2. Inflection point method (Ganesalingam et al.,2. Matching log(de2/t) vs. Ur method (Sridharan et al. 1996)
2013)
3. Inflection point method (Robinson, 1997)
3. Full-match method (Chung et al., 2019)
4. Non-graphical matching method (Robinson & Allam, 1998)
5. Log-log method (Robinson, 2009)
Table 3. Standardized methods used to determine thevertical coefficient of consolidation, cV
6. Steepest tangent fitting method (Vinod et al., 2010)
7. Log t method Sridhar & (Sridhar and Robinson, 2011)
1. Log t method (Casagrande and Fadum, 1940)
8. Full-match method (Chung et al., 2017)
2. Root t method (Taylor, 1942)
Table 4. Methods to determine compression index (Cc), recompression index (Cr) and preconsolidation stress (p) from
Oedometer test
1.

Casagrande (1936)’s method

2.

Silva (1970)’s method

6

4. Location of the Study sites

Study sites for this research weretaken from supervisor’s research
projects. They are:
1. Kim Chung Residential
Complex (KC)

2. Dinh Vu industrial Zone (DVIZ)
3. Vietnam Singapore Industrial
Park (VSIP)
4. Nam Dinh Thermal Power
Project (TPP)7

5. Sample Collections
5.2. Field tests
At each test site, soil boring and sampling were performed to collectsoil samples for laboratory test. In addition, a CPTu sounding was
also performed adjacent to the borehole (carried out by thesupervisor).

Example of soil boring and sampling at DVIZ site

Example of performance of CPTu test at DVIZ
site

✓ For soil boring and sampling, the borehole was advanced byusing the rotary wash method with the use of bentonite slurry tostabilize the borehole walls.
✓ At a sampling depth, a thin-walled fixed-piston tube sampler of
1.0 m long and 76 mm in inner diameter was hydraulicallypushed down to collect undisturbed clay samples.
✓ Right after the sample tube was retrieved at the ground surface,
the tube ends were cleaned and filled with paraffin and thencarefully sealed by tape to preserve water content as well as
integrity of the soil sample. All the boring and sampling
procedures were carried out in accordance with ASTM D1452–09
and ASTM D1587–09, respectively.
✓ When the sampling at the borehole was finished, the sample
tubes were then carefully transported to the laboratory for lab
tests
85. Sample Collections
5.3. Laboratory tests
75 mm
76
mm
Soil samples for
Physical tests and
CD testSample tubes stored
in the lab

Sample cutting in
the lab

100 mmSoil samples for
Physical tests and
PD testPhysical tests, i.e., watercontent, specific gravity…

Soil samples for
Physical tests and
VD testConsolidation tests withradial drainage (CD, PD, VD)

Parts of the sample
taken for the tests

This central drain was manufactured so that thetheoretical consolidation curves from a CD test
and PD test are the same (n =De/Dc = 2.05).
Actual manufactured ratio: n = 62/28 = 2.214(some difference due to water jet cutting error)

Performing the radial consolidation test in the lab

96. Analysis results and procedure
6.1. From implementation of the 1st objective
Procedure for getting cr values
CD caseNon-graphical method: Finding d100

Time t (min)1.0Time t (min)
10.0

100.0

0.1

0.00

0.00

0.20

0.20

Time t (min)
10.0

100.0

0.1

1.0

10.0

100.0

0.00
0.20

0.40

Settlement (mm)0.40

Settlement (mm)

1.0

0.60
0.80
1.00

0.60
0.80
1.00

1.20
1.40

1.20

0.40

Settlement (mm)0.1

Non-graphical Method

0.60
0.80
1.00
1.20

1.60
1.40

1.80
2.00

1.60

Consolidation
curvesobtained from the radialconsolidation tests in lab(CD)

Methods mentioned in slide
No. 5

1.40
1.60

Exampl from Non-grphical method for analyaing in
Excel to get cr

106. Analysis results and procedure
6.1. From implementation of the 1st objective
8.2. Ranking the methods
Procedures for ranking the methods(or procedures for choosing method which yield the predicted settlement results closest to the reality)

1. For each method, determine cr,CD (or cr,PD) from the time (t) and measured settlement (m) data
curve (as mentioned in slide No.19 and 20).

2. For each method, calculate the estimated settlement of the sample (e) by using the theoreticalconsolidation equation with the inputs of cr, d0, d100 .
3. For each method, plot a graph of m vs e for all data points (of one pressure level) from the 4test sites (VSIP site, DVIZ site, KC site, TPP) and determine R2 and Root Mean Squared Error(RMSE) from the correlation.
4. Rank the methods using R2 and RMSE indicators. The ranking principles are as follows:▪ The higher the R2 value, the better the method. Thus, the method producing the highest R2 value is thebest method ( Rank = 1) and vice versa▪ The lower the RMSE value, the better the method. Thus, the method producing the smallest RMSE value
is the best method (Rank = 1) and vice versa

11

6. Analysis results and procedure
6.1. From implementation of the 1st objective
8.2. Ranking the methods
Ranked position of the methods based on R2 and RMSE values (Intact samples)
CD case9

CD case98

8

Root t7

Root t7

Log de2/t

Rank of R2

6

Inflection point

5

Non-graphical4Log-log
Steepest tangent

3

Log t

2

Full match

1

Rank of RMSE

Log de2/t
6

Inflection point

5

Non-graphical4Log-log
Steepest tangent

3

2

Log t

1

Full match

Best

Best

0

0
10

100

10

1000

PD case

PD case98

8

Root t7

Log de2/t

6

Inflection point

5

Non-graphical4Log-log

3

Steepest tangent

2
1
0
10

100

Pressure range (kPa)1000

Root t7

Log de2/t
Rank of RMSE

Rank of R2

1000

Pressure range (kPa)

Pressure range (kPa)

9

100

6

Inflection point

5

Non-graphical4Log-log

3

Steepest tangent

Log t

2

Log t

Full match

1

Full match

Best

0

Best
10

100

Pressure range (kPa)

1000

12

6. Analysis results and procedure
6.1. From implementation of the 1st objective
8.2. Ranking the methods
Ranked position of the methods based on R2 and RMSE values (Intact samples)
CD case
PD caseNo. Method Name

Reliability
Rank

1. Non-graphical method

HighestNo. Method Name

1. Non-graphical method

2. Matching Log de2/t vs Ur
method

2. Matching Log de2/t vs Ur
method

3. Root t method

3. Root t method

Middle4. Log t method

4. Log t method

5. Full-match method

5. Full-match method

6. Inflection point method

6. Inflection point method

7. Steepest tangent method

7. Steepest tangent method

Lowest8. Log-log method

8. Log-log method

Reliability
Rank
HighestMiddleLowestSimilar result was found on remolded samples.
13

6. Analysis results and procedure
6.2. From implementation of the 2nd objective
Ratio of cr,PD /cr,CD from analytical solution
Theoretical equations for PD case (Barron, 1948)

By using theoretical equations
Time factor, Tr

𝑈𝑟 = 1 − 𝑒𝑥𝑝( − 32𝑇𝑟 )
8
𝑇)
𝐹 𝑛 𝑟
𝑛2
3𝑛2 − 1𝐹 𝑛 = 2ln 𝑛 −𝑛 −1
4𝑛2
𝑈𝑟 = 1 − 𝑒𝑥𝑝( −𝐶𝑟 𝑡𝑇𝑟 = 2𝐷

Degree of consolidation, Ur

Theoretical equations for CD case (Scott, 1963)

0.0001
0
0.2

0.001

0.01

0.1

1

CD (n=2.214)
PD case

0.4
0.6

0.8
1

Where, Ur= degree of consolidation; Tr = time factor; n =1.2
drainage spacing ratio; D = diameter of soil sample
The theoretical curves at n = 2.214 indicate that the two tests(i.e., CD and PD) should result in very similar cr values(cr,PD/cr,CD  1.0).
14

6. Analysis results and procedure
6.2. From implementation of the 2nd objective
Correlation between cr,PD and cr,CDProcedures for the evaluation of correlations
1) For each method, determine the ratio of cr,CD and cr,PD, or cr,CD and cv, or cr,PD and cv for both Intact andRemolded samples.
2) Plot a normal distribution curve by using the probability density function of a normal random variablewith mean (µ) and variance (σ2) as the y-axis and cr,CD/cr,PD , or cr,CD/cv, or cr,CD/cv as the x-axis.
3) Filtering the outliers (cr,CD/cr,PD , or cr,CD/cv, or cr,CD/cv) which are out of the 68% interval area distribution. In
other words, remove the data less than (µ - σ) for the lower boundary and greater than (µ + σ) for theupper boundary.

4) Plot (cr,CD vs cr,PD) graph with the filtered data.

15

6. Analysis results and procedure
6.2. From implementation of the 2nd objective
8.2. Ratio of cr,PD /cr,CD from experimental results

Correlation between cr,PD and cr,CD for the eight methods (Intact samples)
Example of correlation between cr,PD and cr,CD from Root t method (Intact samples)

Before removing the outliers

After removing the outliers

Getting correlation

16

6. Analysis results and procedure
6.2. From implementation of the 2nd objective
8.2. Ratio of cr,PD /cr,CD from experimental results
Summary table for the correlation results between cr,PD and cr,CD for the eight methods (Intact samples)
No.

Method names

1.Root t
2.Log (de2/t)
3.Inflection Point
4.Non-graphical
5.Log-Log
6.Steepest tangent
7.Log t8.Full-match

R2
0.95150.93320.90650.92370.9212cr,PD vs cr,CDa(y=ax)0.78540.708
0.69430.67050.69980.87910.769

233

0.89920.9336

0.7663
0.685

189
161

No. of data point
148
179
214
204
194

Correlation between cr,PD and cr,CD for Intact samples: cr,PD  (0.6 – 0.8) cr,CD
Correlation between cr,PD and cr,CD for Remolded samples: cr,PD  (0.4 – 0.6) cr,CD

17

6. Analysis results and procedure
6.2. From implementation of the 2nd objective
8.3. Ratio of cr,PD /cv from experimental results
Summary table for the correlation results between cr,PD and cv for the two standardized methods(Intact samples)
cr,PD Vs cv
No.
Method names
R2
No. of data pointa(y=ax)1.Root t
0.62051.2446396
2.Log t0.6652
1.7926
388
Correlation between cr,PD and cv for Intact Samples: cr,PD  (1 – 2) cv

Summary table for the correlation results between cr,PD and cv for the two standardized methods(Remolded samples)
cr,PD Vs cv
No.
Method names
R2
No. of data pointa(y=ax)1.
Root t0.95050.6251
17
2.
Log t
0.8616
0.711320
Correlation between cr,PD and cv for Remolded Samples: cr,PD  (0.5 – 1) cv

18

6. Analysis results and procedure
6.2. From implementation of the 2nd objective
8.4. Ratio of cr,CD /cv from experimental results
Summary table for the correlation results between cr,CD and cv for the two standardized methods (Intact
samples)cr,CD Vs cv
No.
Method names
R2
No. of data pointa(y=ax)1.Root t
0.70212.3249344
2.Log t0.69142.7567

348

Correlation between cr,PD and cv for Intact Samples: cr,CD  (2 – 3) cv
Summary table for the correlation results between cr,CD and cv for the two standardized methods(Remolded samples)
cr,CD Vs cv
No.
Method names
R2
No. of data pointa(y=ax)1.Root t
0.8304
1.627825
2.Log t0.90181.778223
Correlation between cr,PD and cv for Remolded Samples: cr,CD  (1 – 2) cv

19

6. Analysis results and procedure
6.2. From implementation of the 2nd objective
8.5. Numerical analysis
Finding influent facts that cause the correlation between cr,PD and cr,CD is not equal to one.
Steps performed under the numerical analysis
1) Construct a soil model in PLAXIS software with the dimension of (60 mm x 20 mm) by inputting typicalrequired parameters for soft clay as mentioned in Table 1a and 1b from Appendix.
•

For CD case, by installing sand-stone in the middle with different n values (slide 28).

2) Apply pressure by inputting various permeability rate in horizontal direction (i.e., kx =ky, 2ky, 3ky, 4ky,5ky) in order to see the variation in correlation between cr,PD and cr,CD is whether due to changes incoefficient of permeability in horizontal direction or not.
3) Find cr,CD with different n values (i.e., n = 2.214, 3, 5, 7, 10) as shown in slide no.28 at kx= 3ky condition(typical case) by analyzing the results obtained from PLAXIS software with Root t method.

4)

Find cr,PD as well by analyzing the results obtained from PLAXIS software with Root t method.

20

6. Analysis results and procedure
6.2. From implementation of the 2nd objective
8.5. Numerical analysis
Configuration of variation in sand drain ratio (n=De/Dc) for CD case (Numerical Analysis)n=3
n = 2.214
n=5
n = 6.6677
Configuration of sand-stone position in PD case (Numerical Analysis)

Example of soil domain from PLAXIS software (CD case, 10 kPa, kx = 3ky)n = 1021

6. Analysis results and procedure
6.2. From implementation of the 2nd objective
8.5. Numerical analysis
Finding influent facts that cause the correlation between cr,PD and cr,CD is not equal to one.
Summary table for the correlation results between cr,PD and cr,CD by using Root t method (10 kPa).
kx (m/day)ky(m/day)cr,CD (mm2/min), n =2.14 casecr,PD (mm2/min)

cr,PD/cr,CD

k

k

2.074

1.632

0.79

2k

k

4.296

3.345

0.78

3k

k

6.247

4.730

0.76

4k

k

8.024

6.324

0.79

5k

k

9.906

7.973

0.80

Correlation between cr,PD and cr,CD from numerical analysis: cr,PD  (0.7 – 0.8) cr,CDThe correlation results from Intact samples and Numerical analysis are almost the same.
22

6. Analysis results and procedure
6.2. From implementation of the 2nd objective
8.5. Numerical analysis
Finding influent facts that cause the correlation between cr,PD and cr,CD is not equal to one.
Table showing the variation in cr,CD and cr,PD/cr,CD results based on different n values (10 kPa).
kx (m/day)ky (m/day)n (De/Dc)

cr,CD (mm2/min)

cr,PD (mm2/min)

cr,PD/cr,CD

3k

k

2.214

6.25

4.730

0.76

3k

k

3

4.30

4.730

1.1

3k

k

5

1.88

4.730

2.52

3k

k

6.6677

1.00

4.730

4.73

3k

k

10

0.72

4.730

6.57

The results from numerical analysis are showing that the correlation ratio (cr,PD/cr,CD ) was found to behighly influenced by n values (i.e., De/Dc). In other words, the drainage length has a high influent
effect on the results of correlation ratio (cr,PD/cr,CD ).

23

6. Analysis results and procedure
6.3. From implementation of the 3rd objective
9.2. Evaluation of compression index (Cc), recompression index (Cr) and preconsolidation stress (p)
DVIZ site
0.0 0.2 0.4 0.6 0.8

e-log p curve

0
Cr

L1

p

1.250

L1
L2

5

1.200

1.050
e log p curve
1.000

e0 line

0.950

Vertical line

0.900

TL2

Cc

10

100

1000

Axial stress, s¢v (kPa)Silver (1970)’s method

L1
0.12

5

L3 10

15

L4

15

L4 15

L5

20

L5 20

25

25

0.02

30

CPTu
0.00
Lab

20

30

Cr
Cc

L6

30

CPTu
Lab

L6

L2

Cr = 0.1208 Cc
R² = 0.81
n = 69

0.10OCR = 1
L3
0.08

10

Horizontal line

0.800

0.14

0

L3

25

TL1

0.850

OCR (CPTu)
0 1 2 3 4 5

10

1.100

Depth (m)Void ratio, e

0

L2

5

1.150

s'p' (kPa, CPTu)
100 200 300

Cr

1.300

0

0.06

L4
L5

0.04

L6

0.00

0.20

Example taken from DVIZ site at
the depth of 20 to 20.5 m

0.40

Cc

0.60

0.80

Summary table for the correlation results between Cc and e0and Cr and Cc
Correlation

R2

No. of data point

Cc = 0.3864 e00.947569

Cr = 0.1208 Cc

0.81

69

24

1.00

6. Analysis results and procedure
6.3. From implementation of the 3rd objective
9.2. Evaluation of compression index (Cc), recompression index (Cr) and preconsolidation stress (p)
CPTu PROFILE, KC SITE (HK-12)

5

Clayey silt,
sandy silt

OCR = 115
20

Silty clay

Depth (m)Depth (m)

10

L5

25
30

Silty sand

L6

10
L4
L4 15
L4

20
15

L5
L5

25
20
30

25
20
L5
L6
L6
30

25

CPTu
CPTu
Lab
Lab

L4L4
L4
L5L5

20
15

25

1.0

5
10
Depth (m)Fill materials

15
20

LL

25

L6L6
L5

CPTu
CPTu
Lab
Lab

Silty sandL2 to medium) L2(looseL3
Silty clay
(soft)

L3

L4
L5
Clayey- Silty sand(medium dense) L4
Silty clay
(firm)

DVIZ site

15000Fill materials

5

Clay with silt
(very soft)
Clay, silty clay
(firm)

L1

L2L2

5

L3L3

L3

L2

L2

L3

L3

5

Clay, silty clay
(soft to firm)

15

20

25

Depth (m)Depth (m)

LL = 1
OCR

10

10
L4L4

L4

Sandy clay
L5
(stiff to very stiff)

15

25

10
Wn

L4

L4

L5

L5

15

20

L5L5

CPTu
Lab

VSIP site

L3
L3

L4

20

25

CPTu
Lab

1.0

eo

2.0

3.0 2.50
L1

Gs
2.75

L3

OCR = 1

10
10

W
L3n

15
15
L4
L4

2020

L4
L4

20
20

10

Clay and silt
mixture,sandy silt
mixed organic
L3

L2

5

20

20

Clay, silty caly
(firm to stiff)
L4

5

5

L1

15
L2

L2

10

OCR = 1
L1

L1

10

15

L5
L5

25
25
CPTu
Lab

10

5

10

LL

L1

L2

L3

15

15
L2

L2

20

20

L5 caly
Clay, sandy lean
L3
(stiff to very stif) 25

25

L4

L3

L2

L3

20

L6L6

30
30

25
CPTu
Lab

30

L6
L6

L5

L6

30 35

30

30

L3

CPTuL6
Lab

L4 25

30

L3

L3

L4

CPTu
Lab

TPP site

3.00
L1➢ In general, the OCR profiles indicate that the clays at the testsites are normally consolidated (OCR  1)
L2

L2

L3

L3

➢ Preconsolidation stress value (p) from Lab test is typicallysmaller than that from CPTu test. This indicate that the p fromlab test is influence from soil disturbance effect.
L4

L4

L5

L5

3.0 2.50

25

L5L5

2525
L6

L2

5

15

L5

KC siteg (kN/m)
PL, Wn, LL(%)
s'p(kPa)
OCR
100
20 200 253000 20
0 140 2603 804 0.0
5
0
PL
L1L1
L1 L1

L2

1010L33030

CPTu PROFILE, VSIP SITE (BH-02)
Soil layers

55

L5

L6
Sandy clay
(medium to stiff) L6

L2
L2

L2L2

L2

55

1515

30

3

CPTu PROFILE, VSIP SITE (BH-02)
3
OCR
g (kN/m)e
PL, Wn, LL (%)
Gss'p (kPa)
100 3.00
200
3 0.0
4 5 1.0 o 2.0
2.50
0 20 0401 602 80
15 0 2.75
20
25 300
0
0
0
L1
L1
L1
PL
Wn

3
layerseSoil
PL, OCR
w, LL (%)
Soil layers Gsg (kN/m)s'p (kPa)o
2.00.0 3.0 2.50
2.75
3.00
5.0
10.0
100 100
20 200 30
0.0 1.0 2.0 3.0
300 00 120 240 360 480 100
5
0 Fill0 0L1
0 0
L1 materials
00 PL
L1
L1
L1
L1L1
LL L1

Depth (m)Silty sand

10
L4 15

0

eo

Depth (m)Silty clay)
PL, Wn, LL (%)
s'gp' (kN/m(kPa, CPTu)
OCR (CPTu)
s'20
402 60150 100p(kPa)
200 25300 0 0201 OCR
3 4805 0.0
300 0 0 1 2 3 4 5
0 0 100 200 L1
L1
L1
PL
L1 0
L1
0
L1
L1
L2L2
L2
L2
L2
5
5
L2
L2
OCR = 1
5
5 Wn
L3
L3
L3L3
L3 10
L3 10
L3

Soil layers

3

Depth (m)CPTu PROFILE, DVIZ ZONE-2 SITE (BH-08)

25

7. Conclusions
Based on the results obtained from the four study sites, some key findings on the compressibility
characteristics of soft clay from RRD can be highlighted as follows:

1. For the 1st objective• cr,PD and cr,CD values were determined from 8 existing methods. The results indicate that Non-graphicalresults in highest reliability and the Log-log and Steepest tangent methods result in lowest reliability. In
addition, the reliability of the methods also depends on applied pressure.
2. For the 2nd objective• Theoretically, the ratio (cr,PD/cr,CD) from analytical solution (at n = 2.214) is approximately 1.0.
Experimental results from intact soil samples show that cr,PD = (0.6 – 0.8 )cr,CD and from remolded sample
cr,PD  (0.4 – 0.6) cr,CD. These results indicate that the drainage length of actual soil has significant
influence to the ratio → for the same soil sample the test with different n value would give different cr,CDvalue.
• Results from numerical study (with n = 2.214) show that cr,PD = 0.76cr,CD, which agree well with theexperimental results.

3. For the 3rd objective• The OCR from laboratory test and CPTu test indicate that the soft clays at the test sites are predominantly
normally consolidated (i.e., OCR  1.0). Primary correlations of Cc = 0.3864 e0 and Cr = 0.1208 Cc could besuggested for the clays at the test sites.

26

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