Probabilistic modelling of the bond deterioration of fully-grouted rock bolts subject to spatiotemporally stochastic corrosion
Developing predictive models for quantitative assessment of the deterioration of rock bolts exposed to corrosive environments is essential for rational planning of maintenance activities for anchorage structures. This article presents a probability-based computational model for predicting the time-d...
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Published in | Structure and infrastructure engineering Vol. 9; no. 11; pp. 1161 - 1176 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Taylor & Francis
01.11.2013
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Subjects | |
Online Access | Get full text |
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Summary: | Developing predictive models for quantitative assessment of the deterioration of rock bolts exposed to corrosive environments is essential for rational planning of maintenance activities for anchorage structures. This article presents a probability-based computational model for predicting the time-dependent deterioration of bond capacity of corroding rock bolts due to the attack of chlorides. The inherent stochastic nature involved in the corrosion and degradation process is identified and simulated. A method is developed based on fundamental Mohr-Coulomb theory to evaluate the effect of corrosion on the bond strength due to a failure mode involving splitting of grout cover. Parameters affecting both strength and stress state at the bolt-grout interface are quantitatively related to the degree of corrosion. Integrating the realised corrosion stochastic process and the developed bond loss evaluation method, a computational algorithm based on Monte Carlo simulation is presented for evaluating the bond deterioration in a probabilistic framework. The presented model is used in an illustrative example to show its capability to trace the evolution, throughout the entire design life, of several representative performance indicators of rock bolts as a structure unit or of the interested location within the anchor length. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1573-2479 1744-8980 |
DOI: | 10.1080/15732479.2012.670649 |