Definition of the assessment strategy

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Table of contents

CHAPTER 1: INTRODUCTION
1.1 Problem statement
1.2 Scope of thesis
1.3 Objective and general research methodology
CHAPTER 2: CONCRETE STRENGTH ASSESSMENT IN THE EXISTING STRUCTURES: LITERATURE REVIEW
2.1 Introduction
2.2 Strength assessment using cores only
2.2.1 Planning an investigation program: number and location of cores
2.2.2 Drilling cores
2.2.3 Testing cores
2.2.4 Interpreting the core strengths
2.2.5 Conclusion of the assessment methodology when using cores only
2.3 Strength assessment using nondestructive tests only
2.3.1 Rebound hammer method
2.3.2 Ultrasonic pulse velocity method
2.4 Strength assessment using cores and single nondestructive technique
2.4.1 Model identification approaches: Regression approach
2.4.2 Model identification approaches: Calibration approach
2.4.3 Types of models
2.4.4 Factors affecting the quality of assessment
2.4.5 Sources of uncertainty
2.4.6 Quality of assessment
2.4.7 Conclusion of assessing concrete strength using cores and single nondestructive technique
2.5 Strength assessment using cores and combination of nondestructive techniques
2.5.1 Model identification approaches
2.5.2 Types of models
2.5.3 Factors affecting the quality of assessment
2.5.4 Sources of uncertainty
2.5.5 Quality of assessment
2.5.6 Efficiency of combination
2.5.7 Conclusion of assessing concrete strength using cores and combination of nondestructive techniques
2.6 Conclusions
CHAPTER 3: MEANS AND TOOLS
3.1 Introduction
3.2 Definition of the assessment strategy
3.3 Sources of data
3.3.1 In-situ on structure and laboratory studies data
3.3.2 Synthetic data
3.4 The simulator developed in the present thesis
CHAPTER 4: ANALYSIS OF CURRENT METHODOLOGY FOR CONCRETE STRENGTH ASSESSMENT
4.1 Introduction
4.2 Studying the effect of several key influencing factors
4.2.1 Effect of number of test locations for cores
4.2.2 Effect of quality of measurements
4.2.3 Effect of in-situ concrete strength variability
4.2.4 Effect of type of model (linear or nonlinear)
4.2.5 Effect of combining NDT techniques
4.2.6 Conclusions
4.3 Analyzing several assessment strategies presented in an international benchmark
4.3.1 The benchmark in brief
4.3.2 Simulation of the assessment strategies
4.3.3 Analysis of simulation results
4.3.4 Conclusions
4.4 Analyzing the existing model identification approaches
4.4.1 Comparing the prediction capacity of the existing model identification approaches
4.4.2 Conclusions
CHAPTER 5: DEVELOPING NEW MODEL IDENTIFICATION APPROACH: BIOBJECTIVE APPROACH
5.1 Introduction
5.2 Development of the bi-objective approach
5.2.1 Derivation of the model parameters for the case of linear model
5.2.2 Derivation of the model parameters for the case of nonlinear model
5.3 Validation of the bi-objective approach
5.3.1 Case of linear model
5.3.2 Case of power model
5.3.3 Failure of the model identified by each approach
5.4 Conclusions
CHAPTER 6: QUALITY OF ASSESSMENT AND RECOMMENDATIONS FOR BETTER PRACTICE
6.1 Introduction
6.2 Analysis of quality of assessment using synthetic datasets
6.2.1 Datasets
6.2.2 Assessing mean strength and strength standard deviation (concrete variability) and developing the cumulative distribution functions (CDF)
6.2.3 Assessing the quality of estimation by developing “Risk Curves”
6.2.4 Studying the effect of the quality of measurements on the quality of assessment
6.2.5 Studying the effect of the way of selection the NC test locations on the quality of assessment
6.2.6 What is the minimum number of test locations for cores that can ensure a specific quality of assessment?
6.3 Analysis of quality of assessment using real datasets
6.4 Conclusions
6.5 Recommendations for better practice
CHAPTER 7: CONCLUSIONS AND PERSPECTIVES INTRODUCTION GÉNÉRALE
REFERENCES