Pengpeng Zhi^1,2,3, Zhonglai Wang^1,2,*, Bingzhi Chen³, Ziqiang Sheng⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1001-1022, 2022, DOI:10.32604/cmes.2022.019835

Abstract Although various types of anti-roll torsion bars have been developed to inhibit excessive roll angle of the electric multiple unit (EMU) car body, it is critical to ensure the reliability of structural design due to the complexity of the problems involving time and uncertainties. To address this issue, a multi-objective fuzzy design optimization model is constructed considering time-variant stiffness and strength reliability constraints for the anti-roll torsion bar. A hybrid optimization strategy combining the design of experiment (DoE) sampling and non-linear programming by quadratic lagrangian (NLPQL) is presented to deal with the design optimization model. To characterize the effect of… More >

Jun Yan^1,2, Qianqian Sui¹, Zhirui Fan¹, Zunyi Duan^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 967-986, 2022, DOI:10.32604/cmes.2022.017708

Abstract This study establishes a multiscale and multi-material topology optimization model for thermoelastic lattice structures (TLSs) considering mechanical and thermal loading based on the Extended Multiscale Finite Element Method (EMsFEM). The corresponding multi-material and multiscale mathematical formulation have been established with minimizing strain energy and structural mass as the objective function and constraint, respectively. The Solid Isotropic Material with Penalization (SIMP) interpolation scheme has been adopted to realize micro-scale multi-material selection of truss microstructure. The modified volume preserving Heaviside function (VPHF) is utilized to obtain a clear 0/1 material of truss microstructure. Compared with the classic topology optimization of single-material TLSs,… More >

Yuhang Huo¹, Ye Tian¹, Shiming Pu¹, Tielin Shi¹, Qi Xia^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 1087-1099, 2021, DOI:10.32604/cmes.2021.015694

Abstract In the present study, we propose to integrate the bilateral filter into the Shepard-interpolation-based method for the optimization of composite structures. The bilateral filter is used to avoid defects in the structure that may arise due to the gap/overlap of adjacent fiber tows or excessive curvature of fiber tows. According to the bilateral filter, sensitivities at design points in the filter area are smoothed by both domain filtering and range filtering. Then, the filtered sensitivities are used to update the design variables. Through several numerical examples, the effectiveness of the method was verified. More >

Fusheng Qiu^1,*, Hongliang Liu^1,*, Hongjuan Zhao²

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 43-57, 2021, DOI:10.32604/cmes.2021.014530

Abstract This paper presents a feature modeling approach to address the 3D structural topology design optimization with feature constraints. In the proposed algorithm, various features are formed into searchable shape features by the feature modeling technology, and the models of feature elements are established. The feature elements that meet the design requirements are found by employing a feature matching technology, and the constraint factors combined with the pseudo density of elements are initialized according to the optimized feature elements. Then, through controlling the constraint factors and utilizing the optimization criterion method along with the filtering technology of independent mesh, the structural… More >

Shufang Song^*, Lu Wang, Yuhua Yan

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 383-399, 2020, DOI:10.32604/cmes.2020.09588

Abstract The robust design optimization (RDO) is an effective method to improve product performance with uncertainty factors. The robust optimal solution should be not only satisfied the probabilistic constraints but also less sensitive to the variation of design variables. There are some important issues in RDO, such as how to judge robustness, deal with multi-objective problem and black-box situation. In this paper, two criteria are proposed to judge the deterministic optimal solution whether satisfies robustness requirment. The robustness measure based on maximum entropy is proposed. Weighted sum method is improved to deal with the objective function, and the basic framework of… More >

Hui Zhi^1,2, Sanyang Liu¹

Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 815-825, 2019, DOI:10.31209/2019.100000085

Abstract In this paper, we proposed a hybrid algorithm, which is embedding the genetic operators in the global-best-guided artificial bee colony algorithms called GABCGA to solve the nonlinear design optimization problems. The genetic algorithm has no memory function and good at find global optimization with large probability, but the artificial bee colony algorithm not have selection, crossover and mutation operator and most significant at local search. The hybrid algorithm balances the exploration and exploitation ability further by combining the advantages of both. The experimental results of five engineering optimization and comparisons with existing approaches show that the proposed approach is outperforms… More >

Yingjun Wang¹, Zhongyuan Liao¹, Shengyu Shi^{1, *}, Zhenpei Wang^{2, *}, Leong Hien Poh³

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 433-458, 2020, DOI:10.32604/cmes.2020.08680

Abstract Focusing on the structural optimization of auxetic materials using data-driven methods, a back-propagation neural network (BPNN) based design framework is developed for petal-shaped auxetics using isogeometric analysis. Adopting a NURBS-based parametric modelling scheme with a small number of design variables, the highly nonlinear relation between the input geometry variables and the effective material properties is obtained using BPNN-based fitting method, and demonstrated in this work to give high accuracy and efficiency. Such BPNN-based fitting functions also enable an easy analytical sensitivity analysis, in contrast to the generally complex procedures of typical shape and size sensitivity approaches. More >

Yingjun Wang^1,*, Zhenpei Wang^2,*, Zhaohui Xia³, Leong Hien Poh²

CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.3, pp. 455-507, 2018, DOI:10.31614/cmes.2018.04603

Abstract Isogeometric analysis (IGA), an approach that integrates CAE into conventional CAD design tools, has been used in structural optimization for 10 years, with plenty of excellent research results. This paper provides a comprehensive review on isogeometric shape and topology optimization, with a brief coverage of size optimization. For isogeometric shape optimization, attention is focused on the parametrization methods, mesh updating schemes and shape sensitivity analyses. Some interesting observations, e.g. the popularity of using direct (differential) method for shape sensitivity analysis and the possibility of developing a large scale, seamlessly integrated analysis-design platform, are discussed in the framework of isogeometric shape… More >

Min Hwan Oh, Hee Jun Lee, Minho Chung, Jin Yeon Cho, Do Soon Hwang

The International Conference on Computational & Experimental Engineering and Sciences, Vol.20, No.3, pp. 93-94, 2011, DOI:10.3970/icces.2011.020.093

Abstract Lunar lander may experience various impact loadings when it makes a landing on the lunar surface. Due to the reason, shock absorption system of lunar lander should be designed to absorb the landing energy of lunar lander efficiently for a successful lunar mission. Shock absorption system should be reliable, and the entire landing energy should be absorbed into the shock absorption system to prevent a critical bouncing or turn-over. One the other hand, to protect the payloads, excessive deceleration should be avoided while absorbing the landing energy.

To design an efficient shock absorption system of lunar lander, which satisfies… More >

Y.S. Lian¹, M.S. Liou²

CMES-Computer Modeling in Engineering & Sciences, Vol.8, No.1, pp. 61-72, 2005, DOI:10.3970/cmes.2005.008.061

Abstract This paper focuses on integration of computational methods for design optimization based on data mining and knowledge discovery. We propose to use radial basis function neural networks to analyze the large database generated from evolutionary algorithms and to extract the cause-effect relationship, between the objective functions and the input design variables. The aim is to improve the optimization process by either reducing the computation cost or improving the optimal. Also, it is hoped to provide designers with the salient design pattern about the problem under consideration, from the physics-based simulations. The proposed technique is applied to both academic problems and… More >