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A Smooth Bidirectional Evolutionary Structural Optimization of Vibrational Structures for Natural Frequency and Dynamic Compliance
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作者 Xiaoyan Teng Qiang Li Xudong Jiang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第6期2479-2496,共18页
A smooth bidirectional evolutionary structural optimization(SBESO),as a bidirectional version of SESO is proposed to solve the topological optimization of vibrating continuum structures for natural frequencies and dyn... A smooth bidirectional evolutionary structural optimization(SBESO),as a bidirectional version of SESO is proposed to solve the topological optimization of vibrating continuum structures for natural frequencies and dynamic compliance under the transient load.A weighted function is introduced to regulate the mass and stiffness matrix of an element,which has the inefficient element gradually removed from the design domain as if it were undergoing damage.Aiming at maximizing the natural frequency of a structure,the frequency optimization formulation is proposed using the SBESO technique.The effects of various weight functions including constant,linear and sine functions on structural optimization are compared.With the equivalent static load(ESL)method,the dynamic stiffness optimization of a structure is formulated by the SBESO technique.Numerical examples show that compared with the classic BESO method,the SBESO method can efficiently suppress the excessive element deletion by adjusting the element deletion rate and weight function.It is also found that the proposed SBESO technique can obtain an efficient configuration and smooth boundary and demonstrate the advantages over the classic BESO technique. 展开更多
关键词 Topology optimization smooth bi-directional evolutionary structural optimization(SBESO) eigenfrequency optimization dynamic stiffness optimization
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A Modified Bi-Directional Evolutionary Structural Optimization Procedure with Variable Evolutionary Volume Ratio Applied to Multi-Objective Topology Optimization Problem
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作者 Xudong Jiang Jiaqi Ma Xiaoyan Teng 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第4期511-526,共16页
Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective... Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective topological optimization problem considering dynamic stiffness and natural frequency using modified version of bi-directional evolutionary structural optimization(BESO).The conventional BESO is provided with constant evolutionary volume ratio(EVR),whereas low EVR greatly retards the optimization process and high EVR improperly removes the efficient elements.To address the issue,the modified BESO with variable EVR is introduced.To compromise the natural frequency and the dynamic stiffness,a weighting scheme of sensitivity numbers is employed to form the Pareto solution space.Several numerical examples demonstrate that the optimal solutions obtained from the modified BESO method have good agreement with those from the classic BESO method.Most importantly,the dynamic removal strategy with the variable EVR sharply springs up the optimization process.Therefore,it is concluded that the modified BESO method with variable EVR can solve structural design problems using multi-objective optimization. 展开更多
关键词 Bi-directional evolutionary structural optimization variable evolutionary volume ratio multi-objective optimization weighted sum topology optimization
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Structural Optimization of Hatch Cover Based on Bi-directional Evolutionary Structure Optimization and Surrogate Model Method 被引量:3
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作者 LI Kai YU Yanyun +2 位作者 HE Jingyi ZHAO Decai LIN Yan 《Journal of Shanghai Jiaotong university(Science)》 EI 2018年第4期538-549,共12页
Weight reduction has attracted much attention among ship designers and ship owners.In the present work,based on an improved bi-directional evolutionary structural optimization(BESO) method and surrogate model method,w... Weight reduction has attracted much attention among ship designers and ship owners.In the present work,based on an improved bi-directional evolutionary structural optimization(BESO) method and surrogate model method,we propose a hybrid optimization method for the structural design optimization of beam-plate structures,which covers three optimization levels:dimension optimization,topology optimization and section optimization.The objective of the proposed optimization method is to minimize the weight of design object under a group of constraints.The kernel optimization procedure(KOP) uses BESO to obtain the optimal topology from a ground structure.To deal with beam-plate structures,the traditional BESO method is improved by using cubic box as the unit cell instead of solid unit to construct periodic lattice structure.In the first optimization level,a series of ground structures are generated based on different dimensional parameter combinations,the KOP is performed to all the ground structures,the response surface model of optimal objective values and dimension parameters is created,and then the optimal dimension parameters can be obtained.In the second optimization level,the optimal topology is obtained by using the KOP according to the optimal dimension parameters.In the third optimization level,response surface method(RSM) is used to determine the section parameters.The proposed method is applied to a hatch cover structure design.The locations and shapes of all the structural members are determined from an oversized ground structure.The results show that the proposed method leads to a greater weight saving,compared with the original design and genetic algorithm(GA) based optimization results. 展开更多
关键词 hatch cover structure optimization multi-level optimization hi-directional evolutionary structural optimization response surface method
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Topology Optimization with Aperiodic Load Fatigue Constraints Based on Bidirectional Evolutionary Structural Optimization 被引量:2
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作者 Yongxin Li Guoyun Zhou +2 位作者 Tao Chang Liming Yang Fenghe Wu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2022年第1期499-511,共13页
Because of descriptive nonlinearity and computational inefficiency,topology optimization with fatigue life under aperiodic loads has developed slowly.A fatigue constraint topology optimization method based on bidirect... Because of descriptive nonlinearity and computational inefficiency,topology optimization with fatigue life under aperiodic loads has developed slowly.A fatigue constraint topology optimization method based on bidirectional evolutionary structural optimization(BESO)under an aperiodic load is proposed in this paper.In viewof the severe nonlinearity of fatigue damagewith respect to design variables,effective stress cycles are extracted through transient dynamic analysis.Based on the Miner cumulative damage theory and life requirements,a fatigue constraint is first quantified and then transformed into a stress problem.Then,a normalized termination criterion is proposed by approximatemaximum stress measured by global stress using a P-normaggregation function.Finally,optimization examples show that the proposed algorithm can not only meet the requirements of fatigue life but also obtain a reasonable configuration. 展开更多
关键词 Topology optimization bidirectional evolutionary structural optimization aperiodic load fatigue life stress constraint
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Stress Relaxation and Sensitivity Weight for Bi-Directional Evolutionary Structural Optimization to Improve the Computational Efficiency and Stabilization on Stress-Based Topology Optimization 被引量:2
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作者 Chao Ma Yunkai Gao +1 位作者 Yuexing Duan Zhe Liu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2021年第2期715-738,共24页
Stress-based topology optimization is one of the most concerns of structural optimization and receives much attention in a wide range of engineering designs.To solve the inherent issues of stress-based topology optimi... Stress-based topology optimization is one of the most concerns of structural optimization and receives much attention in a wide range of engineering designs.To solve the inherent issues of stress-based topology optimization,many schemes are added to the conventional bi-directional evolutionary structural optimization(BESO)method in the previous studies.However,these schemes degrade the generality of BESO and increase the computational cost.This study proposes an improved topology optimization method for the continuum structures considering stress minimization in the framework of the conventional BESO method.A global stress measure constructed by p-norm function is treated as the objective function.To stabilize the optimization process,both qp-relaxation and sensitivity weight scheme are introduced.Design variables are updated by the conventional BESO method.Several 2D and 3D examples are used to demonstrate the validity of the proposed method.The results show that the optimization process can be stabilized by qp-relaxation.The value of q and p are crucial to reasonable solutions.The proposed sensitivity weight scheme further stabilizes the optimization process and evenly distributes the stress field.The computational efficiency of the proposed method is higher than the previous methods because it keeps the generality of BESO and does not need additional schemes. 展开更多
关键词 Stress-based topology optimization aggregation function stress relaxation sensitivity weight bi-directional evolutionary structural optimization
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Structural Topology Optimization by Combining BESO with Reinforcement Learning 被引量:1
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作者 Hongbo Sun Ling Ma 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2021年第1期85-96,共12页
In this paper,a new algorithm combining the features of bi-direction evolutionary structural optimization(BESO)and reinforcement learning(RL)is proposed for continuum structural topology optimization(STO).In contrast ... In this paper,a new algorithm combining the features of bi-direction evolutionary structural optimization(BESO)and reinforcement learning(RL)is proposed for continuum structural topology optimization(STO).In contrast to conventional approaches which only generate a certain quasi-optimal solution,the goal of the combined method is to provide more quasi-optimal solutions for designers such as the idea of generative design.Two key components were adopted.First,besides sensitivity,value function updated by Monte-Carlo reinforcement learning was utilized to measure the importance of each element,which made the solving process convergent and closer to the optimum.Second,ε-greedy policy added a random perturbation to the main search direction so as to extend the search ability.Finally,the quality and diversity of solutions could be guaranteed by controlling the value of compliance as well as Intersection-over-Union(IoU).Results of several 2D and 3D compliance minimization problems,including a geometrically nonlinear case,show that the combined method is capable of generating a group of good and different solutions that satisfy various possible requirements in engineering design within acceptable computation cost. 展开更多
关键词 structural topology optimization bi-direction evolutionary structural optimization reinforcement learning first-visit Monte-Carlo method ε-greedy policy generative design
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Layout optimization of steel reinforcement in concrete structure using a truss-continuum model
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作者 Anbang CHEN Xiaoshan LIN +1 位作者 Zi-Long ZHAO Yi Min XIE 《Frontiers of Structural and Civil Engineering》 SCIE EI CSCD 2023年第5期669-685,共17页
Owing to advancement in advanced manufacturing technology,the reinforcement design of concrete structures has become an important topic in structural engineering.Based on bi-directional evolutionary structural optimiz... Owing to advancement in advanced manufacturing technology,the reinforcement design of concrete structures has become an important topic in structural engineering.Based on bi-directional evolutionary structural optimization(BESO),a new approach is developed in this study to optimize the reinforcement layout in steel-reinforced concrete(SRC)structures.This approach combines a minimum compliance objective function with a hybrid trusscontinuum model.Furthermore,a modified bi-directional evolutionary structural optimization(M-BESO)method is proposed to control the level of tensile stress in concrete.To fully utilize the tensile strength of steel and the compressive strength of concrete,the optimization sensitivity of steel in a concrete–steel composite is integrated with the average normal stress of a neighboring concrete.To demonstrate the effectiveness of the proposed procedures,reinforcement layout optimizations of a simply supported beam,a corbel,and a wall with a window are conducted.Clear steel trajectories of SRC structures can be obtained using both methods.The area of critical tensile stress in concrete yielded by the M-BESO is more than 40%lower than that yielded by the uniform design and BESO.Hence,the M-BESO facilitates a fully digital workflow that can be extremely effective for improving the design of steel reinforcements in concrete structures. 展开更多
关键词 bi-directional evolutionary structural optimization steel-reinforced concrete concrete stress reinforcement method hybrid model
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Comparison on construction of strut-and-tie models for reinforced concrete deep beams 被引量:2
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作者 仇一颗 刘霞 《Journal of Central South University》 SCIE EI CAS 2011年第5期1685-1692,共8页
With consideration of the differences between concrete and steel,three solutions using genetic evolutionary structural optimization algorithm were presented to automatically develop optimal strut-and-tie model for dee... With consideration of the differences between concrete and steel,three solutions using genetic evolutionary structural optimization algorithm were presented to automatically develop optimal strut-and-tie model for deep beams.In the finite element analysis of the first method,the concrete and steel rebar are modeled by a plane element and a bar element,respectively.In the second method,the concrete and steel are assigned to two different plane elements,whereas in the third method only one kind of plane element is used with no consideration of the differences of the two materials.A simply supported beam under two point loads was presented as an example to verify the validity of the three proposed methods.The results indicates that all the three methods can generate optimal strut-and-tie models and the third algorithm has powerful capability in searching more optimal results with less computational effort.The effectiveness of the proposed algorithm III has also been demonstrated by other two examples. 展开更多
关键词 reinforced concrete deep beam topology optimization strut-and-tie model genetic evolutionary structural optimization
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COMPUTER PROGRAM FOR DIRECTED STRUCTURE TOPOLOGY OPTIMIZATION 被引量:1
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作者 Xianjie Wang Xun'an Zhang Kepeng Cheng 《Acta Mechanica Solida Sinica》 SCIE EI CSCD 2015年第4期431-440,共10页
To compensate for the imperfection of traditional bi-directional evolutionary structural optimization, material interpolation scheme and sensitivity filter functions are introduced. A suitable filter can overcome the ... To compensate for the imperfection of traditional bi-directional evolutionary structural optimization, material interpolation scheme and sensitivity filter functions are introduced. A suitable filter can overcome the checkerboard and mesh-dependency. And the historical information on accurate elemental sensitivity numbers are used to keep the objective function converging steadily. Apart from rational intervals of the relevant important parameters, the concept of distinguishing between active and non-active elements design is proposed, which can be widely used for improving the function and artistry of structures directly, especially for a one whose accurate size is not given. Furthermore, user-friendly software packages are developed to enhance its accessibility for practicing engineers and architects. And to reduce the time cost for large timeconsuming complex structure optimization, parallel computing is built-in in the MATLAB codes. The program is easy to use for engineers who may not be familiar with either FEA or structure optimization. And developers can make a deep research on the algorithm by changing the MATLAB codes. Several classical examples are given to show that the improved BESO method is superior for its handy and utility computer program software. 展开更多
关键词 bi-directional evolutionary structural optimization (BESO) continuum structurescomputer program development improved algorithm directed structure topology optimizationportion construction design
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Structural-acoustic topology optimization analysis based on evolutionary structural optimization approach 被引量:1
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作者 CHEN Luyun WANG Deyu (State Key Laboratory of Ocean Eng.,Shanghai Jiao Tong University Shanghai 200030) 《Chinese Journal of Acoustics》 2009年第4期332-342,共11页
The continuum structural-acoustic topology optimization with external loading is investigated herein. Finite element method (FEM) is used to obtain the structural frequency response and boundary element method (BEM... The continuum structural-acoustic topology optimization with external loading is investigated herein. Finite element method (FEM) is used to obtain the structural frequency response and boundary element method (BEM) is adopted to perform exterior acoustic radiation analysis. The evolutionary structural optimization (ESO) is served as an optimization method in structural-acoustic radiation topology analysis. The acoustic radiation optimization of a plate under harmonic excitation is given for example. The numerical results show that using ESO solution to analyze structural-acoustic topology optimization is feasible and effective. 展开更多
关键词 ESO Structural-acoustic topology optimization analysis based on evolutionary structural optimization approach
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Detail control strategies for topology optimization in architectural design and development 被引量:5
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作者 Xin Yan Dingwen Bao +2 位作者 Yufang Zhou Yimin Xie Tong Cui 《Frontiers of Architectural Research》 CSCD 2022年第2期340-356,共17页
With the ability to generate forms with high efficiency and elegant geometry,topology optimization has been increasingly used in architectural and structural designs.However,the conventional topology optimization tech... With the ability to generate forms with high efficiency and elegant geometry,topology optimization has been increasingly used in architectural and structural designs.However,the conventional topology optimization techniques aim at achieving the structurally most efficient solution without any potential for architects or designers to control the design details.This paper introduces three strategies based on Bi-directional Evolutionary Structural Optimization(BESO)method to artificially pre-design the topological optimized structures.These strategies have been successfully applied in the computational morphogenesis of various structures for solving practical design problems.The results demonstrate that the developed methodology can provide the designer with structurally efficient and topologically different solutions according to their proposed designs with multi-filter radii,multi-volume fractions,and multi-weighting coefficients.This work establishes a general approach to integrating objective topology optimization methods with subjective human design preferences,which has great potential for practical applications in architecture and engineering industry. 展开更多
关键词 Bi-directional evolutionary structural optimization(BESO) Topology optimization Detail control Diverse design Architectural formfinding
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