MPP-Based Dimension Reduction Method for Accurate Prediction of the Probability of Failure of a Performance Function

A hybrid reliability analysis method is proposed to yield very accurate failure rate calculation of a performance function when dealing with highly nonlinear electromagnetic systems in the presence of uncertainties. To achieve this goal, the first-order reliability method called reliability index approach is first conducted for searching a most probable failure point (MPP) at a given design. However, its result may have significant errors especially for nonlinear or multi-dimensional performance functions. To overcome the drawback, the univariate dimension reduction method is additionally executed at the obtained MPP, and then the probability of failure of a performance function is recalculated through additively decomposing an n-dimensional function into n 1-D functions. A mathematical example and TEAM workshop problem 22 are provided to demonstrate numerical efficiency and accuracy of the proposed method by comparison with the existing reliability methods.

[1]  B. Youn,et al.  Adaptive probability analysis using an enhanced hybrid mean value method , 2005 .

[2]  Achintya Haldar,et al.  Probability, Reliability and Statistical Methods in Engineering Design (Haldar, Mahadevan) , 1999 .

[3]  Min Li,et al.  A New Robust Dominance Criterion for Multiobjective Optimization , 2015, IEEE Transactions on Magnetics.

[4]  K. Choi,et al.  Sampling-based RBDO using the stochastic sensitivity analysis and Dynamic Kriging method , 2011 .

[5]  K. Choi,et al.  Inverse analysis method using MPP-based dimension reduction for reliability-based design optimization of nonlinear and multi-dimensional systems , 2008 .

[6]  Dong-Wook Kim,et al.  Assessment of Statistical Moments of a Performance Function for Robust Design of Electromagnetic Devices , 2015, IEEE Transactions on Magnetics.

[7]  Kyung K. Choi,et al.  An Investigation of Nonlinearity of Reliability-Based Design Optimization Approaches , 2004, DAC 2002.

[8]  G.L. Soares,et al.  Robust Multi-Objective TEAM 22 Problem: A Case Study of Uncertainties in Design Optimization , 2009, IEEE Transactions on Magnetics.

[9]  Dong-Wook Kim,et al.  Composite First-Order Reliability Method for Efficient Reliability-Based Optimization of Electromagnetic Design Problems , 2014, IEEE Transactions on Magnetics.

[10]  Kyung K. Choi,et al.  Dimension reduction method for reliability-based robust design optimization , 2006 .

[11]  J. Murzewski,et al.  Probability, Reliability and Statistical Methods in Engineering Design: A. Halder and S. Mahadevan, John Wiley & Sons, New York, 2000, xi+304 pp , 2001 .

[12]  Dong-Wook Kim,et al.  Enriched Performance Measure Approach for Efficient Reliability-Based Electromagnetic Designs , 2017, IEEE Transactions on Magnetics.