Abstract

<div>The cracking of Reinforced Concrete (RC) members is a highly random process. However, very few studies are focused on the probabilistic studies of concrete cracking. Second Order Monte Carlo Simulation was applied to determine the reliability index of serviceability limit state for different beam design cases. A proposed equation that has been developed based on a series of experimental work and neural network analysis, to estimate the crack spacing and width in RC members. Model uncertainty was modelled randomly to account for the uncertainties in the chosen crack width model. Monte Carlo subroutine was developed to evaluate the reliability index of the performance function. The results showed that the reliability index for crack width in all generated cases were in the recommended ranges of the acceptable limits that makes the proposed equation adopted in the monitoring strategy at the serviceability limit state as a target limit for monitoring the maximum crack width. The results obtained were compared with previous research work that was performed using First Order Monte Carlo Simulation. The results obtained were similar which indicates that the adopted methodology is reliable. The target limit can be used automatically to make decision for Structural Health Monitoring (SHM) data to repair or inject cracks of RC members. A series of steps were developed to help/guide in the decision-making process, based on the crack width. </div>

Highlights

  • CHAPTER TWO: LITERATURE REVIEWThe aim of the present chapter is to provide a conceptual background and to discuss related theoretical and empirical studies for Structural Health Monitoring (SHM) of Reinforced Concrete (RC) members

  • 1.3 Research Objectives The objective of this research is to calibrate the reliability index of the proposed crack width model to help obtain a reliable decision regarding the condition of a RC member; 1

  • In previous research work for obtaining the reliability index using the First Order Monte Carlo Simulation, C was calculated as a deterministic value in this study, C was modelled as a random variable with lognormal distribution

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Summary

Introduction

The aim of the present chapter is to provide a conceptual background and to discuss related theoretical and empirical studies for Structural Health Monitoring (SHM) of Reinforced Concrete (RC) members. A detailed explanation of the Monte Carlo Simulation concept will be described along with the main differences between First Order and Second Order Monte Carlo. Performing a condition assessment to evaluate its integrity, is essential for decision-making of ageing structures’ maintenance plans. The limit state function (G) is defined as the difference between the loading and the resistance of the structure. The structural performance function is defined by a limit state function and it is expressed as (Ellingwood,2003); G(x) = 0

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