Probabilistic models of damage and repair cost for reinforced concrete structural members
The context of this thesis is performance-based engineering, in which the prediction of damage is a central theme. In contrast with traditional structural engineering, which focuses on forces and displacements, performance-based engineering entails the consideration of seismic consequences in terms...
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ndltd-LACETR-oai-collectionscanada.gc.ca-BVAU.2429-304772014-03-26T03:37:28Z Probabilistic models of damage and repair cost for reinforced concrete structural members Talachian, Shahrzad The context of this thesis is performance-based engineering, in which the prediction of damage is a central theme. In contrast with traditional structural engineering, which focuses on forces and displacements, performance-based engineering entails the consideration of seismic consequences in terms of direct and indirect cost of damage to structures. To account for unavoidable uncertainties in such predictions, a probabilistic approach is adopted in this thesis. Specifically, a methodology is proposed that is based on reliability analysis in conjunction with probabilistic models. The phrase “unified reliability analysis” is employed to describe the approach. Although the framework of models generally includes hazard, structure, and consequence models, it is the damage models that are of particular concern in this thesis. In a novel approach, the visual damage at the structural component level is predicted. Importantly, such models predict “physical quantities” of damage. This is done because it is recognized that repair action selection is the central link between the predicted damage and its associated direct and indirect costs. Hence, in order to predict the repair cost and time associated with seismic events, this study puts forward damage models that are directly utilized to predict the repair action. In turn, this leads to probabilistic estimates of seismic loss by summing contributions from the components in the structure. The probabilistic model development follows a Bayesian framework. This approach builds on linear regression theory and explicitly accounts for uncertainties. Specifically, the coefficients in the linear regression models are random variables. The probabilistic models developed in this thesis facilitate the unified reliability analysis that ultimately determines final loss probabilities. This thesis describes the overall methodology, which is generic and applicable to a wide range of structural components, and applies it to reinforced concrete components. This specific application includes the development of a probabilistic model of crack length in reinforced concrete shear walls. 2010-12-23T19:43:13Z 2010-12-23T19:43:13Z 2010 2010-12-23T19:43:13Z 2011-05 Electronic Thesis or Dissertation http://hdl.handle.net/2429/30477 eng University of British Columbia |
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NDLTD |
language |
English |
sources |
NDLTD |
description |
The context of this thesis is performance-based engineering, in which the prediction of damage is a central theme. In contrast with traditional structural engineering, which focuses on forces and displacements, performance-based engineering entails the consideration of seismic consequences in terms of direct and indirect cost of damage to structures. To account for unavoidable uncertainties in such predictions, a probabilistic approach is adopted in this thesis. Specifically, a methodology is proposed that is based on reliability analysis in conjunction with probabilistic models. The phrase “unified reliability analysis” is employed to describe the approach. Although the framework of models generally includes hazard, structure, and consequence models, it is the damage models that are of particular concern in this thesis. In a novel approach, the visual damage at the structural component level is predicted. Importantly, such models predict “physical quantities” of damage. This is done because it is recognized that repair action selection is the central link between the predicted damage and its associated direct and indirect costs. Hence, in order to predict the repair cost and time associated with seismic events, this study puts forward damage models that are directly utilized to predict the repair action. In turn, this leads to probabilistic estimates of seismic loss by summing contributions from the components in the structure.
The probabilistic model development follows a Bayesian framework. This approach builds on linear regression theory and explicitly accounts for uncertainties. Specifically, the coefficients in the linear regression models are random variables. The probabilistic models developed in this thesis facilitate the unified reliability analysis that ultimately determines final loss probabilities. This thesis describes the overall methodology, which is generic and applicable to a wide range of structural components, and applies it to reinforced concrete components. This specific application includes the development of a probabilistic model of crack length in reinforced concrete shear walls. |
author |
Talachian, Shahrzad |
spellingShingle |
Talachian, Shahrzad Probabilistic models of damage and repair cost for reinforced concrete structural members |
author_facet |
Talachian, Shahrzad |
author_sort |
Talachian, Shahrzad |
title |
Probabilistic models of damage and repair cost for reinforced concrete structural members |
title_short |
Probabilistic models of damage and repair cost for reinforced concrete structural members |
title_full |
Probabilistic models of damage and repair cost for reinforced concrete structural members |
title_fullStr |
Probabilistic models of damage and repair cost for reinforced concrete structural members |
title_full_unstemmed |
Probabilistic models of damage and repair cost for reinforced concrete structural members |
title_sort |
probabilistic models of damage and repair cost for reinforced concrete structural members |
publisher |
University of British Columbia |
publishDate |
2010 |
url |
http://hdl.handle.net/2429/30477 |
work_keys_str_mv |
AT talachianshahrzad probabilisticmodelsofdamageandrepaircostforreinforcedconcretestructuralmembers |
_version_ |
1716655825876942848 |