Probabilistic calibration of stress-strain models for confined normal-strength concrete

A probabilistic calibration for traditional deterministic stress-strain models of square confined concrete columns was conducted based on the proposed probabilistic stress-strain model and a large number of experimental data. The probabilistic models for both peak stress and peak strain (strain corr...

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Main Authors: Yu, Bo, Qin, Chenghui, Tao, Boxiong, Li, Bing
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/160457
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1604572022-07-22T07:23:33Z Probabilistic calibration of stress-strain models for confined normal-strength concrete Yu, Bo Qin, Chenghui Tao, Boxiong Li, Bing School of Civil and Environmental Engineering Engineering::Civil engineering Peak Strain Bayesian Theory A probabilistic calibration for traditional deterministic stress-strain models of square confined concrete columns was conducted based on the proposed probabilistic stress-strain model and a large number of experimental data. The probabilistic models for both peak stress and peak strain (strain corresponding to peak stress) of confined normal-strength concrete (NSC) were established first based on the Bayesian theory and the Markov chain Monte Carlo method. Then, a probabilistic stress-strain model of confined NSC was established based on the proposed probabilistic models for peak stress and peak strain. Finally, the confidence level and computational accuracy of four typical deterministic stress-train models of confined NSC were calibrated based on the proposed probabilistic models and a large amount of experimental data. The proposed probabilistic models not only describe the probabilistic characteristics of peak stress, peak strain, and the stress-strain curve, but also provide an efficient approach to calibrate the confidence level and computational accuracy of traditional deterministic models. The financial support received from the National Natural Science Foundation of China (Grant Nos. 51668008 and 51738004), the Guangxi Science Fund for Distinguished Young Scholars (2019GXNSFFA245004), and the Natural Science Foundation of Guangxi Province (Grant No. 2018GXNSFAA281344) is gratefully acknowledged. 2022-07-22T07:23:33Z 2022-07-22T07:23:33Z 2021 Journal Article Yu, B., Qin, C., Tao, B. & Li, B. (2021). Probabilistic calibration of stress-strain models for confined normal-strength concrete. Journal of Structural Engineering, 147(8), 04021117-. https://dx.doi.org/10.1061/(ASCE)ST.1943-541X.0003092 0733-9445 https://hdl.handle.net/10356/160457 10.1061/(ASCE)ST.1943-541X.0003092 2-s2.0-85107861206 8 147 04021117 en Journal of Structural Engineering © 2021 American Society of Civil Engineers. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Civil engineering
Peak Strain
Bayesian Theory
spellingShingle Engineering::Civil engineering
Peak Strain
Bayesian Theory
Yu, Bo
Qin, Chenghui
Tao, Boxiong
Li, Bing
Probabilistic calibration of stress-strain models for confined normal-strength concrete
description A probabilistic calibration for traditional deterministic stress-strain models of square confined concrete columns was conducted based on the proposed probabilistic stress-strain model and a large number of experimental data. The probabilistic models for both peak stress and peak strain (strain corresponding to peak stress) of confined normal-strength concrete (NSC) were established first based on the Bayesian theory and the Markov chain Monte Carlo method. Then, a probabilistic stress-strain model of confined NSC was established based on the proposed probabilistic models for peak stress and peak strain. Finally, the confidence level and computational accuracy of four typical deterministic stress-train models of confined NSC were calibrated based on the proposed probabilistic models and a large amount of experimental data. The proposed probabilistic models not only describe the probabilistic characteristics of peak stress, peak strain, and the stress-strain curve, but also provide an efficient approach to calibrate the confidence level and computational accuracy of traditional deterministic models.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Yu, Bo
Qin, Chenghui
Tao, Boxiong
Li, Bing
format Article
author Yu, Bo
Qin, Chenghui
Tao, Boxiong
Li, Bing
author_sort Yu, Bo
title Probabilistic calibration of stress-strain models for confined normal-strength concrete
title_short Probabilistic calibration of stress-strain models for confined normal-strength concrete
title_full Probabilistic calibration of stress-strain models for confined normal-strength concrete
title_fullStr Probabilistic calibration of stress-strain models for confined normal-strength concrete
title_full_unstemmed Probabilistic calibration of stress-strain models for confined normal-strength concrete
title_sort probabilistic calibration of stress-strain models for confined normal-strength concrete
publishDate 2022
url https://hdl.handle.net/10356/160457
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