State-dependent stochastic models: A general stochastic framework for modeling deteriorating engineering systems considering multiple deterioration processes and their interactions

被引:84
作者
Jia, Gaofeng [1 ]
Gardoni, Paolo [2 ]
机构
[1] Colorado State Univ, Dept Civil & Environm Engn, Ft Collins, CO 80523 USA
[2] Univ Illinois, Dept Civil & Environm Engn, Urbana, IL 61801 USA
关键词
Stochastic models; Deterioration modeling; Multiple deterioration processes; Reinforced concrete bridges; Seismic damage; Corrosion; PROBABILISTIC CAPACITY MODELS; NUCLEAR-POWER-PLANTS; CONCRETE STRUCTURES; LIFE PREDICTION; RC BRIDGES; RELIABILITY; FRAGILITY; CORROSION; COLUMNS; DEGRADATION;
D O I
10.1016/j.strusafe.2018.01.001
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
For performance analysis of deteriorating engineering systems, it is critical to model and incorporate the various deterioration processes and associated uncertainties. This paper proposes state-dependent stochastic models (SDSMs) for modeling the impact of deterioration on the performance of engineering systems. Within the stochastic framework, the change of the system state variables due to different deterioration processes and their interaction is modeled explicitly. As a candidate model to be used in the framework, a new general age and state dependent stochastic model for gradual deterioration is proposed, and its calibration based on data is also discussed. Once the time-variant system state variables are modeled, proper capacity and demand models that take them as inputs can be adopted to fully capture the impact of deterioration processes on the capacity, demand, and other system performances. The proposed framework is first demonstrated through a simple example, and then is used to model the deterioration of an example reinforced concrete (RC) bridge considering deterioration caused by both corrosion and earthquake including their interaction. The results show the importance of modeling the interaction between different deterioration processes, and also verify the advantages of the proposed framework (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:99 / 110
页数:12
相关论文
共 51 条
[1]  
[Anonymous], 1992, BAYESIAN INFERENCE S, DOI DOI 10.1002/9781118033197.CH4
[2]  
[Anonymous], 2017, RISK RELIABILITY ANA
[3]  
[Anonymous], 1998, DENSITY ESTIMATION S, DOI DOI 10.1201/9781315140919
[4]   Probabilistic lifetime assessment of RC structures under coupled corrosion-fatigue deterioration processes [J].
Bastidas-Arteaga, Emilio ;
Bressolette, Philippe ;
Chateauneuf, Alaa ;
Sanchez-Silva, Mauricio .
STRUCTURAL SAFETY, 2009, 31 (01) :84-96
[5]  
Beck JL, 2007, ECCOMAS THEM C COMP, P413
[6]   Generalized bridge network performance analysis with correlation and time-variant reliability [J].
Bocchini, Paolo ;
Frangopol, Dan M. .
STRUCTURAL SAFETY, 2011, 33 (02) :155-164
[7]   A probabilistic computational framework for bridge network optimal maintenance scheduling [J].
Bocchini, Paolo ;
Frangopol, Dan M. .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2011, 96 (02) :332-349
[8]   Probabilistic capacity models and seismic fragility estimates for RC columns subject to corrosion [J].
Choe, Do-Eun ;
Gardoni, Paolo ;
Rosowsky, David ;
Haukaas, Terie .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2008, 93 (03) :383-393
[9]   Fragility Increment Functions for Deteriorating Reinforced Concrete Bridge Columns [J].
Choe, Do-Eun ;
Gardoni, Paolo ;
Rosowsky, David .
JOURNAL OF ENGINEERING MECHANICS, 2010, 136 (08) :969-978
[10]   Seismic fragility estimates for reinforced concrete bridges subject to corrosion [J].
Choe, Do-Eun ;
Gardoni, Paolo ;
Rosowsky, David ;
Haukaas, Terje .
STRUCTURAL SAFETY, 2009, 31 (04) :275-283