kwak, tae young master course seoul national university

Assessment of Shear Band Characteristics in Cohesive Soils using Digital Image Analysis

Technique for Plane Strain Tests

- Concept & Evaluation of accuracy for DIC-

Kwak, Tae young Master course

Seoul National University

Wednesday seminar

Contents

1. Introduction

2. Digital Image Correlation

3. Evaluation of Accuracy for DIC

4. Summary

Introduction

Assessment of Shear Band

Expansion of shear band by loading is related to failure mode of soil

Traditional methods measure overall soil behavior- Difficult to assessment of shear band

Evaluation of internal soil behavior near shear band - Importance of the digital image analysis

Introduction

Object of This Research– Internal deformation of specimen during compression shearing

• Internal behavior with stress-strain response• Spatial distribution for deformation

– Assessing the shear band characteristics for cohesive soil• Generation of shear band, corresponding to the stress state and strain level• Characteristics of shear band for soil type (NC vs. OC)

Introduction

Methodology– Plane strain test for the observation of failure surface

• Internal behavior of the soil follows the surface behavior at plane strain condi-tion.

• Occurrence of shear band characteristics is clear at plane strain test.

– Digital image analysis for the internal deformation of specimen• Quantitative measurement for internal deformation value of specimen• Available for high accuracy and continuous evaluation during shearing

Introduction

Flow Chart of the Research– Specimen: EPK Kaolinite– Test Procedure Specimen preparation

Internal deformation and Shear band characteristics with shearing level

Transducers in test apparatus

digital image acquisition

Plane strain test

Internal deformation using digital image analysis

Overall stress-strain behavior

Concept of Digital Image Correlation– Evaluation of displacement between two digital images

• Determine displacement vector for selected subset

Digital Image Correlation

AfterBefore

?

Digital Image Correlation Procedure– Select the subset pixel from the first picture. And then consider ex-

pected deformation of the selected subset pixel– Perform cross correlation for each pixel by moving 1pixel, so correlation

between two subset pixels can be found out– Determine the location of highest correlation peak– Interpolate the surrounding of highest correlation peak


Influence Factor for DIC Method


Image resolution

Size of pixel subset

Deformation condition

Image pattern

Determined by pixel of digital camera

Higher pixel of digital camera, higher image resolution



Image resolution



Image pattern

Determined by size of pixel subset

Larger size of pixel subset, higher uniqueness

Difficulty in observing the behavior for

each location of the soil at too large size of pixel subset



Image resolution



Image pattern

Rigid body movement / Deformation

Higher accuracy for rigid body movement

Lower accuracy for high deformation - Set-up DIC analysis interval shorter!



Image resolution



Image pattern

Image pattern classification

Grid pattern (Alshibli et al.) - Same pattern makes difficult to classify

Color of soil particle (Jang et al.) Arbitrary pattern by spray (Kim et al.)

Evaluation of Accuracy for DIC Method (Jang et al, 2009)– Comparison between criterion displacement and analyzed displacement

• Criterion displacement : Exact particle movement › Make a particle movement by DEM program

• Analyzed displacement : Measured movement by DIC method› Use initial digital image and deformed digial image by DEM program

Evaluation of Accuracy for DIC

DEM DEM

DIA DIA

(u ,v ):Displacement by DEM program(u ,v ):Displacement by DIC method

2 2[( ) ( ) ]_

N

DIA DEM DIA DEMi

u u v vStd Err

N

Evaluation of Accuracy for DIC Method (Jang et al. 2009)– Image resolution

• Higher image resolution, lower standard error !– Deformation condition

• Larger deformation, higher standard error !– Size of pixel subset

• Larger size of pixel subset, lower standard error !– Image pattern

• Distribution of soil particles with different color


Image resolu-tion

(mm/pixel)

Volume change Distortion

0.5% 1.5% 5.0% 0.5% 1.5% 5.0%

150×150 0.0852 0.1477 0.2335 0.0978 0.1531 0.1212

300×300 0.0283 0.0521 0.1171 0.0258 0.0557 0.0941

600×600 0.0147 0.0408 0.1067 0.0116 0.0101 0.0585

Limitation for DIC method for granular soils with DEM program

However, DEM program is not available for cohesive soil

Evaluation for cohesive soil in plane strain test is needed With alternative methodology instead of DEM program

Evaluation of DIC method in cohesive soil for PS test


Image resolution Size of pixel subset Deformation condi-tion Image pattern

Digital camera: 12-million pixels (4288 x 2848 Pixels) digital camera Nikkon D90

Arbitrary pattern for cohesive soil by spray(Kim et al.,2011)

Adequate pixel subset sizeUniqueness ↔ Spatial distribution

Small deformation intervalAccuracy & Precision for Analysis ↔ Analysis efficiency

OK OK


Evaluation of DIC method in cohesive soil for PS test1) Evaluation by void-ratio

Almost rigid body movement

Comparison between void ratio change and digital image analysis( e ↔△ △εv)

Exclude upper & near shear band section

- Consideration of soil disturbence


Evaluation of DIC method in cohesive soil for PS test2) Evaluation by LVDT

Volume change during consolidation

Comparison between LVDT and digital image analysis(△εLVDT ↔△εDIA)

Summary

Assessment of shear band localization– Importance of digital image analysis– Investigate overall stress-strain behavior and observe deformation of specimen

during shearing

Introduction of digital image correlation – Concept of the digital image correlation– Influence factors for accuracy of the DIC method

Evalation of accuracy for DIC– Literature review about Evaluation of accuracy in granular soil– Suggestion about method for evaluation of accuracy in cohesive soil

Thank You!

kwak, tae young master course seoul national university

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