Selective dimension reduction method (DRM) to enhance accuracy and efficiency of most probable point (MPP)–based DRM
Tóm tắt
Từ khóa
Tài liệu tham khảo
Akaike H (1974) A new look at the statistical model identification. In Selected Papers of Hirotugu Akaike (pp. 215–222). Springer, New York, NY
Bae HR, Alyanak E (2016) Sequential subspace reliability method with univariate revolving integration. AIAA J 54(7):2160–2170
Ben-Ari EN, Steinberg DM (2007) Modeling data from computer experiments: an empirical comparison of kriging with MARS and projection pursuit regression. Qual Eng 19(4):327–338
Burnham KP, Anderson DR, Huyvaert KP (2011) AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons. Behav Ecol Sociobiol 65(1):23–35
Cho H, Choi KK, Gaul NJ, Lee I, Lamb D, Gorsich D (2016a) Conservative reliability-based design optimization method with insufficient input data. Struct Multidiscip Optim 54(6):1609–1630
Cho H, Choi KK, Lee I, Lamb D (2016b) Design sensitivity method for sampling-based RBDO with varying standard deviation. J Mech Des 138(1):011405
Hao N, Feng Y, Zhang HH (2018) Model selection for high-dimensional quadratic regression via regularization. J Am Stat Assoc 113(522):615–625
Hao P, Wang Y, Ma R, Liu H, Wang B, Li G (2019) A new reliability-based design optimization framework using isogeometric analysis. Comput Methods Appl Mech Eng 345:476–501
Hasofer AM, Lind NC (1974) Exact and invariant second-moment code format. J Eng Mech Div 100(1):111–121
Jung Y, Cho H, Lee I (2019) MPP-based approximated DRM (ADRM) using simplified bivariate approximation with linear regression. Structural and multidisciplinary optimization 59(5):1761–1773. https://doi.org/10.1007/s00158-018-2160-7
Kang SB, Park JW, Lee I (2017) Accuracy improvement of the most probable point-based dimension reduction method using the hessian matrix. Int J Numer Methods Eng 111(3):203–217
Keshtegar B, Hao P (2018) Enriched self-adjusted performance measure approach for reliability-based design optimization of complex engineering problems. Appl Math Model 57:37–51
Keshtegar B, Hao P, Meng Z (2017) A self-adaptive modified chaos control method for reliability-based design optimization. Struct Multidiscip Optim 55(1):63–75
Lee I, Choi KK, Du L, Gorsich D (2008) Inverse analysis method using MPP-based dimension reduction for reliability-based design optimization of nonlinear and multi-dimensional systems. Comput Methods Appl Mech Eng 198(1):14–27
Lee I, Choi KK, Zhao L (2011) Sampling-based RBDO using the stochastic sensitivity analysis and dynamic kriging method. Struct Multidiscip Optim 44(3):299–317
Lim M, Hastie T (2015) Learning interactions via hierarchical group-lasso regularization. J Comput Graph Stat 24(3):627–654
Lumley T, Scott A (2015) AIC and BIC for modeling with complex survey data. J Surv Stat Methodol 3(1):1–18
Madsen HO, Krenk S, Lind NC (2006) Methods of structural safety. Courier Corporation
Park JW, Lee I (2018) A study on computational efficiency improvement of novel SORM using the convolution integration. J Mech Des 140(2):024501
Penmetsa RC, Grandhi RV (2003) Adaptation of fast Fourier transformations to estimate structural failure probability. Finite Elem Anal Des 39(5–6):473–485
Rahman S, Wei D (2006) A univariate approximation at most probable point for higher-order reliability analysis. Int J Solids Struct 43(9):2820–2839
Rahman S, Xu H (2004) A univariate dimension-reduction method for multi-dimensional integration in stochastic mechanics. Probabilist Eng Mech 19(4):393–408
Shin J, Lee I (2014) Reliability-based vehicle safety assessment and design optimization of roadway radius and speed limit in windy environments. J Mech Des 136(8):081006
Sobol IM (2001) Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Math Comput Simul 55(1–3):271–280
Sues R, Aminpour M, Shin Y (2000) Reliability based MDO for aerospace systems. In 19th AIAA Applied Aerodynamics Conference (p. 1521)
Sugiura N (1978) Further analysts of the data by Akaike’s information criterion and the finite corrections: further analysts of the data by Akaike’s. Commun Stat-Theor M 7(1):13–26
Tu J, Choi KK, Park YH (2001) Design potential method for robust system parameter design. AIAA J 39(4):667–677
Tvedt L (1990) Distribution of quadratic forms in normal space—application to structural reliability. J Eng Mech 116(6):1183–1197
Valdebenito MA, Schuëller GI (2010) A survey on approaches for reliability-based optimization. Struct Multidiscip Optim 42(5):645–663
Venables WN, Ripley BD (2013) Modern applied statistics with S-PLUS. Springer Science & Business Media
Walker JR (1986) The practical application of variance reduction techniques in probabilistic assessments
Wu YT, Shin Y, Sues R, Cesare M (2001) Safety-factor based approach for probability-based design optimization. In 19th AIAA applied aerodynamics conference (p. 1522)
Xu H, Rahman S (2003) A moment-based stochastic method for response moment and reliability analysis. In Computational fluid and solid mechanics 2003 (pp. 2402-2404). Elsevier Science Ltd.
Xu H, Rahman S (2004) A generalized dimension-reduction method for multidimensional integration in stochastic mechanics. Int J Numer Methods Eng 61(12):1992–2019