TY - JOUR
T1 - Probabilistic failure analysis, performance assessment, and sensitivity analysis of corroded reinforced concrete structures
AU - Guo, Hongyuan
AU - Dong, You
AU - Bastidas-Arteaga, Emilio
AU - Gu, Xiang Lin
N1 - Funding Information:
Funding: The study has been supported by National Key R&D Program of China (No. 2019YFB1600702), Research Grants Council of the Hong Kong Special Administrative Region, China (No. T22-502/18-R, No. PolyU 15219819, and France/HK Joint Research Scheme F-PolyU505/18), and National Natural Science Foundation of China (Grant No. 51808476). The third author gratefully acknowledges the financial support from the Regional Council of ‘Pays de la Loire’ within the framework of the BUENO 2018-2021 research program (Durable Concrete for Offshore Wind Turbines).
Publisher Copyright:
© 2021 Elsevier Ltd
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/6
Y1 - 2021/6
N2 - A better understanding of the mechanical performance and the failure modes of corroded reinforced concrete (RC) structures is crucial for implementing measures that reduce failure risk. Therefore, this paper proposes a probabilistic numerical framework to estimate the structural performance and to identify the failure modes as well as the main parameters affecting the safety of corroded RC structures. This framework comprehensively combines experimental data, finite element method (FEM), and polynomial chaos expansion (PCE) modeling. First, the FEM for failure analysis is developed and verified with a 26-year-old corroded RC beam. The investigated case considers the effects of corrosion degree and bond behavior of the steel–concrete interface on the mechanical properties and failure mode of the corroded RC beam. Second, PCE surrogate models for serviceability and ultimate limit states are established by combining the sampling technique (e.g., Sobol sequences) and the validated FEM model. Finally, a global sensitivity analysis is conducted using the PCE model. Several illustrative cases are presented to analyze, in deterministic and probabilistic manners, the failure modes and the sensitivities of material properties and geometry characteristics for both serviceability and ultimate limit states. The results of this study could provide useful insights for understanding the main failure modes of RC structures under different corrosion scenarios.
AB - A better understanding of the mechanical performance and the failure modes of corroded reinforced concrete (RC) structures is crucial for implementing measures that reduce failure risk. Therefore, this paper proposes a probabilistic numerical framework to estimate the structural performance and to identify the failure modes as well as the main parameters affecting the safety of corroded RC structures. This framework comprehensively combines experimental data, finite element method (FEM), and polynomial chaos expansion (PCE) modeling. First, the FEM for failure analysis is developed and verified with a 26-year-old corroded RC beam. The investigated case considers the effects of corrosion degree and bond behavior of the steel–concrete interface on the mechanical properties and failure mode of the corroded RC beam. Second, PCE surrogate models for serviceability and ultimate limit states are established by combining the sampling technique (e.g., Sobol sequences) and the validated FEM model. Finally, a global sensitivity analysis is conducted using the PCE model. Several illustrative cases are presented to analyze, in deterministic and probabilistic manners, the failure modes and the sensitivities of material properties and geometry characteristics for both serviceability and ultimate limit states. The results of this study could provide useful insights for understanding the main failure modes of RC structures under different corrosion scenarios.
KW - Corrosion
KW - Failure analysis
KW - Failure modes
KW - Global sensitivity analysis
KW - Polynomial chaos expansion
KW - Reinforced concrete structures
UR - http://www.scopus.com/inward/record.url?scp=85102969301&partnerID=8YFLogxK
U2 - 10.1016/j.engfailanal.2021.105328
DO - 10.1016/j.engfailanal.2021.105328
M3 - Journal article
AN - SCOPUS:85102969301
SN - 1350-6307
VL - 124
JO - Engineering Failure Analysis
JF - Engineering Failure Analysis
M1 - 105328
ER -