A case study on the practicability of using linear analysis results in a Bayesian inference model to predict nonlinear responses in performance-based design methods

Compared to traditional methods based on mean response evaluation of seismic parameters with significant confidence margin, the growing use of the new generation of performance-based design methods, which are based on loss and financial assessment, necessitates an increase in accuracy and reliabilit...

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Main Authors: Shima Taheri, Reza Karami Mohammadi
Format: Article
Language:English
Published: K. N. Toosi University of Technology 2021-09-01
Series:Numerical Methods in Civil Engineering
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Online Access:https://nmce.kntu.ac.ir/article_160544_43c753f6be89cba580825efa61f204cd.pdf
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author Shima Taheri
Reza Karami Mohammadi
author_facet Shima Taheri
Reza Karami Mohammadi
author_sort Shima Taheri
collection DOAJ
description Compared to traditional methods based on mean response evaluation of seismic parameters with significant confidence margin, the growing use of the new generation of performance-based design methods, which are based on loss and financial assessment, necessitates an increase in accuracy and reliability in probabilistic evaluation of structural response for all values of seismic parameters. Even with the same limited number of common nonlinear analyses, utilizing the Bayesian approach, which allows the use of diverse and even inaccurate data to form beliefs, is a powerful method to predict and enhance seismic response results. In this paper, the practicability of using linear analysis data in a Bayesian inference model to predict nonlinear responses is evaluated. A 20-story reinforced concrete special moment resisting frame is being considered, and a Bayesian model for prediction of the maximum story drift and the peak floor acceleration has been investigated. The Bayesian model was developed on linear results and finally updated with a limited number of nonlinear results. The predictability power of predictors, Bayesian model comparison among different likelihood functions, and common diagnostics tools in numerical solution of the Bayesian model developed on linear results, have all been examined. The results demonstrate a significant improvement in the outcomes, while proving the practicability of developing a stable and reliable model based on linear analysis data.
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spelling doaj-art-b5f9386740f64d6f95fc88518a619f192024-12-20T08:32:02ZengK. N. Toosi University of TechnologyNumerical Methods in Civil Engineering2345-42962783-39412021-09-0162496510.52547/nmce.6.2.49160544A case study on the practicability of using linear analysis results in a Bayesian inference model to predict nonlinear responses in performance-based design methodsShima Taheri0Reza Karami Mohammadi1Ph.D. Candidate, Faculty of Civil Engineering, K.N. Toosi University of Technology, Tehran, Iran.Associate Professor, Faculty of Civil Engineering, K. N. Toosi University of Technology, Tehran, Iran.Compared to traditional methods based on mean response evaluation of seismic parameters with significant confidence margin, the growing use of the new generation of performance-based design methods, which are based on loss and financial assessment, necessitates an increase in accuracy and reliability in probabilistic evaluation of structural response for all values of seismic parameters. Even with the same limited number of common nonlinear analyses, utilizing the Bayesian approach, which allows the use of diverse and even inaccurate data to form beliefs, is a powerful method to predict and enhance seismic response results. In this paper, the practicability of using linear analysis data in a Bayesian inference model to predict nonlinear responses is evaluated. A 20-story reinforced concrete special moment resisting frame is being considered, and a Bayesian model for prediction of the maximum story drift and the peak floor acceleration has been investigated. The Bayesian model was developed on linear results and finally updated with a limited number of nonlinear results. The predictability power of predictors, Bayesian model comparison among different likelihood functions, and common diagnostics tools in numerical solution of the Bayesian model developed on linear results, have all been examined. The results demonstrate a significant improvement in the outcomes, while proving the practicability of developing a stable and reliable model based on linear analysis data.https://nmce.kntu.ac.ir/article_160544_43c753f6be89cba580825efa61f204cd.pdfbayesian inferencebayesian model comparisondemand parametersprediction of responseslinear response spectrum analysislikelihood function
spellingShingle Shima Taheri
Reza Karami Mohammadi
A case study on the practicability of using linear analysis results in a Bayesian inference model to predict nonlinear responses in performance-based design methods
Numerical Methods in Civil Engineering
bayesian inference
bayesian model comparison
demand parameters
prediction of responses
linear response spectrum analysis
likelihood function
title A case study on the practicability of using linear analysis results in a Bayesian inference model to predict nonlinear responses in performance-based design methods
title_full A case study on the practicability of using linear analysis results in a Bayesian inference model to predict nonlinear responses in performance-based design methods
title_fullStr A case study on the practicability of using linear analysis results in a Bayesian inference model to predict nonlinear responses in performance-based design methods
title_full_unstemmed A case study on the practicability of using linear analysis results in a Bayesian inference model to predict nonlinear responses in performance-based design methods
title_short A case study on the practicability of using linear analysis results in a Bayesian inference model to predict nonlinear responses in performance-based design methods
title_sort case study on the practicability of using linear analysis results in a bayesian inference model to predict nonlinear responses in performance based design methods
topic bayesian inference
bayesian model comparison
demand parameters
prediction of responses
linear response spectrum analysis
likelihood function
url https://nmce.kntu.ac.ir/article_160544_43c753f6be89cba580825efa61f204cd.pdf
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AT shimataheri casestudyonthepracticabilityofusinglinearanalysisresultsinabayesianinferencemodeltopredictnonlinearresponsesinperformancebaseddesignmethods
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