Optimization of Load-Carrying Hierarchical Stiffened Shells: Comparative Survey and Applications of Six Hybrid Heuristic Models
暂无分享,去创建一个
Kuo Tian | Shun-Peng Zhu | Nguyen-Thoi Trung | Behrooz Keshtegar | Shun‐Peng Zhu | B. Keshtegar | K. Tian | N. Trung | Shun‐Peng Zhu
[1] Salim Heddam,et al. Modeling daily dissolved oxygen concentration using modified response surface method and artificial neural network: a comparative study , 2017, Neural Computing and Applications.
[2] Christian Hühne,et al. Robust knockdown factors for the design of cylindrical shells under axial compression: Analysis and modeling of stiffened and unstiffened cylinders , 2018, Thin-Walled Structures.
[3] Liang Gao,et al. Analysis of gene expression programming for approximation in engineering design , 2012 .
[4] Anthony T. C. Goh,et al. Multivariate adaptive regression splines for analysis of geotechnical engineering systems , 2013 .
[5] R. Webster,et al. Kriging: a method of interpolation for geographical information systems , 1990, Int. J. Geogr. Inf. Sci..
[6] Enying Li,et al. Fast cylinder variable-stiffness design by using Kriging-based hybrid aggressive space mapping method , 2017, Adv. Eng. Softw..
[7] Fan Yang,et al. Optimal design of hierarchical grid-stiffened cylindrical shell structures based on linear buckling and nonlinear collapse analyses , 2017 .
[8] Riccardo Poli,et al. Particle swarm optimization , 1995, Swarm Intelligence.
[9] Dan Wang,et al. Streamline stiffener path optimization (SSPO) for embedded stiffener layout design of non-uniform curved grid-stiffened composite (NCGC) structures , 2019, Computer Methods in Applied Mechanics and Engineering.
[10] Ke Zhang,et al. Tailoring the optimal load-carrying efficiency of hierarchical stiffened shells by competitive sampling , 2018, Thin-Walled Structures.
[11] Siuli Mukhopadhyay,et al. Response surface methodology , 2010 .
[12] Bo Wang,et al. Generatrix shape optimization of stiffened shells for low imperfection sensitivity , 2014 .
[13] Jae-Sang Park,et al. Derivations of Knockdown Factors for Cylindrical Structures Considering Different Initial Imperfection Models and Thickness Ratios , 2018, International Journal of Aeronautical and Space Sciences.
[14] Kincho H. Law,et al. A computational framework for regional seismic simulation of buildings with multiple fidelity models , 2016, Adv. Eng. Softw..
[15] Bo Wang,et al. A high-fidelity approximate model for determining lower-bound buckling loads for stiffened shells , 2017, International Journal of Solids and Structures.
[16] Yan Zhang,et al. Maximizing natural frequencies of inhomogeneous cellular structures by Kriging-assisted multiscale topology optimization , 2020 .
[17] D. Fang,et al. Fabrication and testing of composite hierarchical Isogrid stiffened cylinder , 2018 .
[18] Hailong Chen,et al. Blast response of hierarchical anisogrid stiffened composite panel: Considering the damping effect , 2018 .
[19] Liang Gao,et al. A combined projection-outline-based active learning Kriging and adaptive importance sampling method for hybrid reliability analysis with small failure probabilities , 2019, Computer Methods in Applied Mechanics and Engineering.
[20] Chao-Chao Wang,et al. A multi-fidelity information fusion metamodeling assisted laser beam welding process parameter optimization approach , 2017, Adv. Eng. Softw..
[21] Jae-Sang Park,et al. Postbuckling analyses and derivations of Knockdown factors for hybrid-grid stiffened cylinders , 2018, Aerospace Science and Technology.
[22] Liang Gao,et al. A system active learning Kriging method for system reliability-based design optimization with a multiple response model , 2020, Reliab. Eng. Syst. Saf..
[23] Yunlong Ma,et al. Numerically and experimentally predicted knockdown factors for stiffened shells under axial compression , 2016 .
[24] Bo Wang,et al. Hybrid optimization of hierarchical stiffened shells based on smeared stiffener method and finite element method , 2014 .
[25] Adrian Murphy,et al. Stiffened panel stability behaviour and performance gains with plate prismatic sub-stiffening , 2009 .
[26] S Sapna,et al. Backpropagation Learning Algorithm Based on Levenberg Marquardt Algorithm , 2012 .
[27] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[28] Haiping Du,et al. Time series prediction using evolving radial basis function networks with new encoding scheme , 2008, Neurocomputing.
[29] J. Friedman. Multivariate adaptive regression splines , 1990 .
[30] Cui Yan,et al. Multi-functional SiC/Al Composites for Aerospace Applications , 2008 .
[31] Bo Wang,et al. Optimum design of hierarchical stiffened shells for low imperfection sensitivity , 2014 .
[32] Shang-Liang Chen,et al. Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.
[33] Weihong Zhang,et al. Sensitivity analysis for optimization design of non-uniform curved grid-stiffened composite (NCGC) structures , 2018, Composite Structures.
[34] Jie Wang,et al. A computational strategy to establish algebraic parameters for the Reference Resistance Design of metal shell structures , 2017, Adv. Eng. Softw..
[35] Peng Hao,et al. Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy , 2017, Applied Composite Materials.
[36] Adrian Murphy,et al. Non-Prismatic Sub-Stiffening for Stiffened Panel Plates — Stability Behaviour and Performance Gains , 2010 .
[37] Yunlong Ma,et al. Grid-pattern optimization framework of novel hierarchical stiffened shells allowing for imperfection sensitivity , 2017 .
[38] D. Basak,et al. Support Vector Regression , 2008 .
[39] Hao Wu,et al. Carbon fiber reinforced hierarchical orthogrid stiffened cylinder: Fabrication and testing , 2018 .
[40] P. Hao,et al. Buckling surrogate-based optimization framework for hierarchical stiffened composite shells by enhanced variance reduction method , 2019, Journal of Reinforced Plastics and Composites.
[41] Yuanming Xu,et al. Study on the thermal buckling and post-buckling of metallic sub-stiffening structure and its optimization , 2016 .
[42] Chih-Jen Lin,et al. A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.