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Probabilistic Damage Models for Detailed Risk Analysis of Buildings with Reliability Methods

Aghababaei Shahrestani, Mohammad | 2017

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 49569 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Mahsuli, Mojtaba
  7. Abstract:
  8. A probabilistic approach to modeling the seismic damage incurred by structural and nonstructural components is developed in this study. For this purpose, Bayesian linear regression is employed to characterize the epistemic uncertainty in the model. In this approach, regressors are constructed based on the mechanics of damage. In turn, the probability distributions of the model parameters and the model error are quantified by Bayesian regression using real-life data from laboratory experiments and/or post-earthquake inspections of damaged components. The study presents the stepwise procedure of collecting the observations, quantifying the repair costs, developing model forms, performing model diagnostics, and conducting model reduction in detail. Subsequently, a library of damage models are developed for structural components, such as concrete moment frame joints, and nonstructural components, such as partition walls and traction elevators. For this purpose, the data of a host of past experimental studies are collected for Bayesian regression analysis. The proposed modeling approach provides a number of insights on the influential parameters on damage, which are thoroughly discussed for each example model. In the next step, the proposed damage models are employed in conjunction with a library of other models to conduct detailed risk analysis. This library comprises occurrence model, magnitude model, location model, intensity model, structural response model, repair cost model, downtime model, casualty model, and discounting model. Two risk analysis methods are introduced: scenario sampling analysis and load combination analysis. These methods are employed in an illustrative risk analysis of a four-story building. The results include loss curves and insights into the most important sources of uncertainty, the most important design variables, the most loss-making components, and the most influential sources of seismicity
  9. Keywords:
  10. Monetary Loss ; Risk Analysis ; Reliability Model ; Linear Regression ; Bayesian Analysis ; Nonstructural Components (NSC) ; Damage Model ; Downtime ; Casualty

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