Theory-informed deep neural network-based time-dependent flexural reliability assessment of corroded PC structures

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成果类型：

期刊论文

作者：

Yang, Yiming;Zhou, Chengkun;Peng, Jianxin;Li, Hai;Dong, You;...

通讯作者：

Peng, JX

作者机构：

[Yang, Yiming; Li, Hai; Zhou, Chengkun] Hunan City Univ, Sch Civil Engn, Yiyang 413000, Hunan, Peoples R China.

[Peng, Jianxin] Changsha Univ Sci & Technol, Sch Civil Engn, Changsha 410114, Hunan, Peoples R China.

[Dong, You] Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong, Peoples R China.

[Cai, C. S.] Southeast Univ, Sch Transportat, Dept Bridge Engn, Nanjing 211189, Jiangsu, Peoples R China.

[Cai, C. S.] Louisiana State Univ, Dept Civil & Environm Engn, Baton Rouge, LA 70803 USA.

通讯机构：

[Peng, JX ] C

Changsha Univ Sci & Technol, Sch Civil Engn, Changsha 410114, Hunan, Peoples R China.

语种：

英文

关键词：

Corroded prestressed concrete structure;Reliability;Flexural capacity;Deep neural network;Theory-informed model;Uncertainty analysis

期刊：

Engineering Structures

ISSN：

0141-0296

年：

2025

卷：

329

页码：

119819

DOI：

10.1016/j.engstruct.2025.119819

基金类别：

National Natural Science Foundation of China [52208166, 52378125, 52078056]; Science and Technology Innovation Program of Hunan Province [2022RC1186]; Hunan Provincial Natural Science Foundation of China [2025JJ50239]; Research Foundation of Education Bureau of Hunan Province [24A0580]; Open Fund of Key Laboratory of Safety Control of Bridge Engineering, Ministry of Education (Changsha University of Science Technology) [21KB03]; Aid program for Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Province

机构署名：

本校为第一机构

院系归属：

土木工程学院

摘要：

Reasonable assessment of flexural capacity and reliability is an important prerequisite for ensuring the normal use of corroded prestressed concrete (PC) structures. In this paper, a theory-informed deep neural network (TIDNN)-based model is first developed to predict the flexural capacity of corroded PC beams. Then, a TIDNN-based time-dependent reliability analysis method is proposed considering the aleatory uncertainty of input parameters and the epistemic uncertainty of model. In addition, the effectiveness of the proposed prediction method ...

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Theory-informed deep neural network-based time-dependent flexural reliability assessment of corroded PC structures

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