TY - JOUR
T1 - 基于贝叶斯修正的FRP约束混凝土极限压应变计算方法研究
AU - Xu, Jinjun
AU - Chen, Wenguang
AU - Huang, Xinliang
AU - Chen, Zongping
AU - Tan, Cheng
N1 - Publisher Copyright:
© 2022, The Editorial Board of Journal of Basic Science and Engineering. All right reserved.
PY - 2022/8
Y1 - 2022/8
N2 - Ultimate compressive strain is one of the important criterion to evaluate the mechanical properties of FRP-confined concrete, and developing its calculation approach has prominent scientificity and practicalness. The existing ultimate compressive strain calculation models of FRP-confined concrete were obtained based on the empirical formulas using mathematical fitting or regression supported by limited test results.Such models generally have poor universality, low prediction accuracy and low stability, which means that those models cannot be directly employed in engineering.In order to improve the prediction accuracy of the existing models, with the Bayesian information updating concept, 15 categories of models were evaluated using the established extensive experimental database and the calculation formulas proposed by Sadeghian and Fam, Jiang and Teng were selected as the Bayesian prior models, respectively.Bayesian theory was used to make statistical inferences on these two types of information, and a probabilistic model of ultimate compressive strain of FRP-confined concrete was constructed. The unknown model parameters were selected and eliminated for modifying the models and developing the new ones.Based on 471 sets of test data used to modify the model, the computational models modified by Bayesian statistical inference were verified. The results showed that compared to the existing empirical models, the calculated values are much closer to the experimental ones based on the Bayesian probability model; moreover, the deviation and randomness are significantly decreased. The modification process of FRP-confined concrete ultimate compressive strain model exhibits the rationality of Bayesian statistical inference ensuring the accuracy and stability of prediction results.
AB - Ultimate compressive strain is one of the important criterion to evaluate the mechanical properties of FRP-confined concrete, and developing its calculation approach has prominent scientificity and practicalness. The existing ultimate compressive strain calculation models of FRP-confined concrete were obtained based on the empirical formulas using mathematical fitting or regression supported by limited test results.Such models generally have poor universality, low prediction accuracy and low stability, which means that those models cannot be directly employed in engineering.In order to improve the prediction accuracy of the existing models, with the Bayesian information updating concept, 15 categories of models were evaluated using the established extensive experimental database and the calculation formulas proposed by Sadeghian and Fam, Jiang and Teng were selected as the Bayesian prior models, respectively.Bayesian theory was used to make statistical inferences on these two types of information, and a probabilistic model of ultimate compressive strain of FRP-confined concrete was constructed. The unknown model parameters were selected and eliminated for modifying the models and developing the new ones.Based on 471 sets of test data used to modify the model, the computational models modified by Bayesian statistical inference were verified. The results showed that compared to the existing empirical models, the calculated values are much closer to the experimental ones based on the Bayesian probability model; moreover, the deviation and randomness are significantly decreased. The modification process of FRP-confined concrete ultimate compressive strain model exhibits the rationality of Bayesian statistical inference ensuring the accuracy and stability of prediction results.
KW - Bayesian theory
KW - Eliminating parameters
KW - FRP-confined concrete
KW - Model updating
KW - Ultimate compressive strain
UR - http://www.scopus.com/inward/record.url?scp=85135742200&partnerID=8YFLogxK
U2 - 10.16058/j.issn.1005-0930.2022.04.015
DO - 10.16058/j.issn.1005-0930.2022.04.015
M3 - 文章
AN - SCOPUS:85135742200
SN - 1005-0930
VL - 30
SP - 974
EP - 986
JO - Yingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering
JF - Yingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering
IS - 4
ER -