Hybrid control variates-based simulation method for structural reliability analysis of some problems with low failure probability

Abstract The safety analysis of systems with nonlinear performance function and small probability of failure is a challenge in the field of reliability analysis. In this study, an efficient approach is presented for approximating small failure probabilities. To meet this aim, by introducing Probability Density Function (PDF) control variates, the original failure probability integral was reformulated based on the Control Variates Technique (CVT). Accordingly, using the adaptive cooperation of the subset simulation (SubSim) and the CVT, a new formulation was offered for the approximation of small failure probabilities. The proposed formulation involves a probability term (resulting from a fast-moving SubSim) and an adaptive weighting term that refines the obtained probability. Several numerical and engineering problems, involving nonlinear performance functions and system-level reliability problems, are solved by the proposed approach and common reliability methods. Results showed that the proposed simulation approach is not only more efficient, but is also robust than common reliability methods. It also presents a good potential for application in engineering reliability problems.

[1]  Karlo Pirić Reliability analysis method based on determination of the performance function’s PDF using the univariate dimension reduction method , 2015 .

[2]  Dirk P. Kroese,et al.  Simulation and the Monte Carlo method , 1981, Wiley series in probability and mathematical statistics.

[3]  A. Olsson,et al.  On Latin hypercube sampling for structural reliability analysis , 2003 .

[4]  Zhenzhou Lu,et al.  Reliability sensitivity method by line sampling , 2008 .

[5]  Zhenzhou Lu,et al.  Structural Reliability Analysis Using Combined Space Partition Technique and Unscented Transformation , 2016 .

[6]  Zhongyi Cai,et al.  Precision design of roll-forging die and its application in the forming of automobile front axles , 2005 .

[7]  Mohsen Ali Shayanfar,et al.  An adaptive directional importance sampling method for structural reliability analysis , 2018 .

[8]  Mohsen Rashki,et al.  Low-cost finite element method-based reliability analysis using adjusted control variate technique , 2017, Structural Safety.

[9]  N. Okasha An improved weighted average simulation approach for solving reliability-based analysis and design optimization problems , 2016 .

[10]  Robert E. Melchers,et al.  Structural system reliability assessment using directional simulation , 1994 .

[11]  M. D. Stefano,et al.  Efficient algorithm for second-order reliability analysis , 1991 .

[12]  Gordon A. Fenton,et al.  Reliability analysis with Metamodel Line Sampling , 2016 .

[13]  Zeng Meng,et al.  A hybrid relaxed first-order reliability method for efficient structural reliability analysis , 2017 .

[14]  Siu-Kui Au,et al.  Engineering Risk Assessment with Subset Simulation , 2014 .

[15]  M. Miri,et al.  A new efficient simulation method to approximate the probability of failure and most probable point , 2012 .

[16]  Nicola Pedroni,et al.  An Adaptive Metamodel-Based Subset Importance Sampling approach for the assessment of the functional failure probability of a thermal-hydraulic passive system , 2017 .

[17]  Mohsen Rashki,et al.  A simulation-based method for reliability based design optimization problems with highly nonlinear constraints , 2014 .

[18]  Qiujing Pan,et al.  An efficient reliability method combining adaptive Support Vector Machine and Monte Carlo Simulation , 2017 .

[19]  Zeng Meng,et al.  A decoupled approach for non-probabilistic reliability-based design optimization , 2016 .

[20]  Manolis Papadrakakis,et al.  Accelerated subset simulation with neural networks for reliability analysis , 2012 .

[21]  David K. E. Green,et al.  Efficient Markov Chain Monte Carlo for combined Subset Simulation and nonlinear finite element analysis , 2017 .

[22]  Yan-Gang Zhao,et al.  Moment methods for structural reliability , 2001 .

[23]  A. Sudjianto,et al.  First-order saddlepoint approximation for reliability analysis , 2004 .

[24]  Jun Xu,et al.  Efficient reliability assessment of structural dynamic systems with unequal weighted quasi-Monte Carlo Simulation , 2016 .