Sampling-based RBDO using the stochastic sensitivity analysis and dynamic kriging method

DOI10.1007/s00158-011-0659-2zbMath1274.90246OpenAlexW2131733133MaRDI QIDQ381619

Mohammad Hasan, H. S. Yoon

Publication date: 15 November 2013

Published in: Structural and Multidisciplinary Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00158-011-0659-2

zbMATH Keywords

copulaMonte Carlo simulationsurrogate modelsampling-based RBDOscore functionsstochastic sensitivity analyses

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Sensitivity, stability, parametric optimization (90C31) Stochastic programming (90C15)

Related Items (10)

Sequential sampling for contour estimation with concurrent function evaluations ⋮ A stability investigation of a simulation- and reliability-based optimization ⋮ Adaptive virtual support vector machine for reliability analysis of high-dimensional problems ⋮ Second-order reliability method-based inverse reliability analysis using Hessian update for accurate and efficient reliability-based design optimization ⋮ Post optimization for accurate and efficient reliability-based design optimization using second-order reliability method based on importance sampling and its stochastic sensitivity analysis ⋮ A hybrid descent mean value for accurate and efficient performance measure approach of reliability-based design optimization ⋮ The method of solving structural reliability with multiparameter correlation problem ⋮ A new sampling-based RBDO method via score function with reweighting scheme and application to vehicle designs ⋮ Modified screening-based kriging method with cross validation and application to engineering design ⋮ Efficient local adaptive Kriging approximation method with single-loop strategy for reliability-based design optimization

Uses Software

• ANSYS

Cites Work

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