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topology optimization of Metamaterial Microstructures for Negative Poisson’s Ratio under Large Deformation Using a Gradient-Free Method

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 2001-2026页

作者： Weida Wu Yiqiang Wang Zhonghao Gao Pai Liu State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of TechnologyDalian116024China

Negative Poisson’s ratio(NPR)metamaterials are attractive for their unique mechanical behaviors and potential applications in deformation control and energy ***,when subjected to significant stretching,NPR metamaterials designed under small strain assumption may experience a rapid degradation in NPR *** address this issue,this study aims to design metamaterials maintaining a targeted NPR under large deformation by taking advantage of the geometry nonlinearity mechanism.A representative periodic unit cell is modeled considering geometry nonlinearity,and its topology is designed using a gradient-free *** unit cell microstructural topologies are described with the material-field series-expansion(MFSE)*** MFSE method assumes spatial correlation of the material distribution,which greatly reduces the number of required design *** conveniently design metamaterials with desired NPR under large deformation,we propose a two-stage gradient-free metamaterial topology optimization method,which fully takes advantage of the dimension reduction benefits of the MFSE method and the Kriging surrogate model ***,we use homogenization to find a preliminary NPR design under a small deformation *** the second stage,we begin with this preliminary design and minimize deviations in NPR from a targeted value under large *** this strategy and solution technique,we successfully obtain a group of NPR metamaterials that can sustain different desired NPRs in the range of[−0.8,−0.1]under uniaxial stretching up to 20% ***,typical microstructure designs are fabricated and tested through *** experimental results show good consistency with our numerical results,demonstrating the effectiveness of the present gradientfree NPR metamaterial design strategy.

关键词： topology optimization microstructural design negative Poisson’s ratio large deformation

topology optimization of Two Fluid Heat Transfer Problems for Heat Exchanger Design

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1949-1974页

作者： Kun Yan Yunyu Wang Jun Yan School of Chemical Engineering Dalian University of TechnologyDalian116024China Jianghuai Advanced Technology Center Hefei230000China State Key Laboratory of Structural Analysis for Industrial Equipment Department of Engineering MechanicsInternational Research Center for Computational MechanicsDalian University of TechnologyDalian116024China

topology optimization of thermal-fluid coupling problems has received widespread *** article proposes a novel topology optimization method for laminar two-fluid heat exchanger *** proposed method utilizes an artificial density field to create two permeability interpolation functions that exhibit opposing trends,ensuring separation between the two fluid ***,a Gaussian function is employed to construct an interpolation function for the thermal conductivity ***,a computational program has been developed on the OpenFOAM platform for the topology optimization of two-fluid heat *** program leverages parallel computing,significantly reducing the time required for the topology optimization *** enhance computational speed and reduce the number of constraint conditions,we replaced the conventional pressure drop constraint condition in the optimization problem with a pressure inlet/outlet boundary *** 3D optimization results demonstrate the characteristic features of a surface structure,providing valuable guidance for designing heat exchangers that achieve high heat exchange efficiency while minimizing excessive pressure *** the same time,a new structure appears in large-scale topology optimization,which proves the effectiveness and stability of the topology optimization program written in this paper in large-scale calculation.

关键词： topology optimization two fluid heat exchanger OpenFOAM large scale

topology optimization of chiral metamaterials with application to underwater sound insulation

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Applied Mathematics and Mechanics(English Edition) 2024年第7期45卷 1119-1138页

作者： Chao WANG Honggang ZHAO Yang WANG Jie ZHONG Dianlong YU Jihong WEN Laboratory of Science and Technology on Integrated Logistics Support National University of Defense Technology

Chiral metamaterials have been proven to possess many appealing mechanical phenomena, such as negative Poisson's ratio, high-impact resistance, and energy absorption. This work extends the applications of chiral metamaterials to underwater sound insulation. Various chiral metamaterials with low acoustic impedance and proper stiffness are inversely designed using the topology optimization scheme. Low acoustic impedance enables the metamaterials to have a high and broadband sound transmission loss(STL), while proper stiffness guarantees its robust acoustic performance under a hydrostatic pressure. As proof-of-concept demonstrations, two specimens are fabricated and tested in a water-filled impedance tube. Experimental results show that, on average, over 95% incident sound energy can be isolated by the specimens in a broad frequency range from 1 k Hz to 5 k Hz, while the sound insulation performance keeps stable under a certain hydrostatic pressure. This work may provide new insights for chiral metamaterials into the underwater applications with sound insulation.

关键词： chiral metamaterial topology optimization underwater sound insulation low acoustic impedance sound transmission loss (STL) O427.5 74J20

topology optimization of modular structures with multiple assemblies and applications to airborne shelves

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Chinese Journal of Aeronautics 2024年第4期37卷 321-332页

作者： Jie WANG Tong GAO Ming LI Jihong ZHU Longlong SONG Weihong ZHANG State IJR Center of Aerospace Design and Additive Manufacturing Northwestern Polytechnical UniversityXi’an 710072China Beijing Specialized Machinery Institute Beijing 100143China

This work is devoted to the aeronautical application of topology optimization for modular structures with multiple assemblies that consist of repeated standard modules and optional *** kinds of structures are widely used owing to their transportability,reconfigurability,low manufacturing and service *** this work,the design of airborne shelves with modular structures characterized by the standard module configuration is formulated for the first time as a topology optimization problem of multiple assemblies and multiple load cases subjected to the volume *** is shown that the weighted compliance design of multiple assemblies is a compromising solution compared to the optimization result of each individual assembly of standard ***,the performance of optimized airborne shelves with the modular structures can effectively be ameliorated with the help of reinforcements.

关键词： topology optimization Modular structures Multiple assemblies Standard modules Airborne shelves

A non-probabilistic reliability topology optimization method based on aggregation function and matrix multiplication considering buckling response constraints

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Applied Mathematics and Mechanics(English Edition) 2024年第2期45卷 321-336页

作者： Lei WANG Yingge LIU Juxi HU Weimin CHEN Bing HAN Institute of Solid Mechanics School of Aeronautic Science and EngineeringBeihang UniversityBeijing 100191China Aircraft and Propulsion Laboratory Ningbo Institute of TechnologyBeihang UniversityNingbo 315100Zhejiang ProvinceChina State Key Laboratory of Navigation and Safety Technology Shanghai Ship and Shipping Research InstituteShanghai 200135China National Engineering Research Center of Ship&Shipping Control System Shanghai Ship and Shipping Research InstituteShanghai 200135China

A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix *** expression of the geometric stiffness matrix is derived,the finite element linear buckling analysis is conducted,and the sensitivity solution of the linear buckling factor is *** a specific problem in linear buckling topology optimization,a Heaviside projection function based on the exponential smooth growth is developed to eliminate the gray *** aggregation function method is used to consider the high-order eigenvalues,so as to obtain continuous sensitivity information and refined structural *** cyclic matrix programming,a fast topology optimization method that can be used to efficiently obtain the unit assembly and sensitivity solution is *** maximize the buckling load,under the constraint of the given buckling load,two types of topological optimization columns are *** variable density method is used to achieve the topology optimization solution along with the moving asymptote optimization *** vertex method and the matching point method are used to carry out an uncertainty propagation analysis,and the non-probability reliability topology optimization method considering buckling responses is developed based on the transformation of non-probability reliability indices based on the characteristic ***,the differences in the structural topology optimization under different reliability degrees are illustrated by examples.

关键词： buckling topology optimization aggregation function uncertainty propagation analysis non-probabilistic reliability

Probabilistic-Ellipsoid Hybrid Reliability Multi-Material topology optimization Method Based on Stress Constraint

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 757-792页

作者： Zibin Mao Qinghai Zhao Liang Zhang College of Mechanical and Electrical Engineering Qingdao UniversityQingdao266071China National Engineering Research Center for Intelligent Electrical Vehicle Power System Qingdao UniversityQingdao266071China

This paper proposes a multi-material topology optimization method based on the hybrid reliability of the probability-ellipsoid model with stress constraint for the stochastic uncertainty and epistemic uncertainty of mechanical loads in optimization *** probabilistic model is combined with the ellipsoidal model to describe the uncertainty of mechanical *** topology optimization formula is combined with the ordered solid isotropic material with penalization(ordered-SIMP)multi-material interpolation *** stresses of all elements are integrated into a global stress measurement that approximates the maximum stress using the normalized p-norm ***,the sequential optimization and reliability assessment(SORA)is applied to transform the original uncertainty optimization problem into an equivalent deterministic topology optimization(DTO)*** response surface and sparse grid technique are combined with SORA to get accurate information on the most probable failure point(MPP).In each cycle,the equivalent topology optimization formula is updated according to the MPP information obtained in the previous *** adjoint variable method is used for deriving the sensitivity of the stress constraint and the moving asymptote method(MMA)is used to update design ***,the validity and feasibility of the method are verified by the numerical example of L-shape beam design,T-shape structure design,steering knuckle,and 3D T-shaped beam.

关键词： Stress constraint probabilistic-ellipsoid hybrid topology optimization reliability analysis multi-material design

Multi-Material topology optimization of 2D Structures Using Convolutional Neural Networks

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1919-1947页

作者： Jiaxiang Luo Weien Zhou Bingxiao Du Daokui Li Wen Yao College of Aerospace Science and Engineering National University of Defense TechnologyChangsha410073China Defense Innovation Institute Chinese Academy of Military ScienceBeijing100071China Intelligent Game and Decision Laboratory Chinese Academy of Military ScienceBeijing100071China

In recent years,there has been significant research on the application of deep learning(DL)in topology optimization(TO)to accelerate structural ***,these methods have primarily focused on solving binary TO problems,and effective solutions for multi-material topology optimization(MMTO)which requires a lot of computing resources are still ***,this paper proposes the framework of multiphase topology optimization using deep learning to accelerate MMTO *** framework employs convolutional neural network(CNN)to construct a surrogate model for solving MMTO,and the obtained surrogate model can rapidly generate multi-material structure topologies in negligible time without any *** performance evaluation results show that the proposed method not only outputs multi-material topologies with clear material boundary but also reduces the calculation cost with high prediction ***,in order to find a more reasonable modeling method for MMTO,this paper studies the characteristics of surrogate modeling as regression task and classification *** the training of 297 models,our findings show that the regression task yields slightly better results than the classification task in most ***,The results indicate that the prediction accuracy is primarily influenced by factors such as the TO problem,material category,and data ***,factors such as the domain size and the material property have minimal impact on the accuracy.

关键词： Multi-material topology optimization convolutional neural networks deep learning finite element analysis

An Overview of Sequential Approximation in topology optimization of Continuum Structure

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 43-67页

作者： Kai Long Ayesha Saeed Jinhua Zhang Yara Diaeldin Feiyu Lu Tao Tao Yuhua Li Pengwen Sun Jinshun Yan State Key Laboratory of Alternate Electrical Power Systemwith Renewable Energy Sources North China Electric Power UniversityBeijing102206China Faculty of Materials and Manufacturing Beijing University of TechnologyBeijing100124China New Energy and Energy Storage Division China Southern Power Grid Technology Co.Ltd.Guangzhou510080China School of Mechanical Engineering Inner Mongolia University of TechnologyHohhot010051China College of Energy and Power Engineering Inner Mongolia University of TechnologyHohhot010051China

This paper offers an extensive overview of the utilization of sequential approximate optimization approaches in the context of numerically simulated large-scale continuum *** structures,commonly encountered in engineering applications,often involve complex objective and constraint functions that cannot be readily expressed as explicit functions of the design *** a result,sequential approximation techniques have emerged as the preferred strategy for addressing a wide array of topology optimization *** the past several decades,topology optimization methods have been advanced remarkably and successfully applied to solve engineering problems incorporating diverse physical *** comparison to the large-scale equation solution,sensitivity analysis,graphics post-processing,etc.,the progress of the sequential approximation functions and their corresponding optimizersmake sluggish ***,particularly novices,pay special attention to their difficulties with a particular ***,this paper provides an overview of sequential approximation functions,related literature on topology optimization methods,and their *** from optimality criteria and sequential linear programming,the other sequential approximate optimizations are introduced by employing Taylor expansion and intervening *** addition,recent advancements have led to the emergence of approaches such as Augmented Lagrange,sequential approximate integer,and non-gradient approximation are also *** highlighting real-world applications and case studies,the paper not only demonstrates the practical relevance of these methods but also underscores the need for continued exploration in this ***,to provide a comprehensive overview,this paper offers several novel developments that aim to illuminate potential directions for future research.

关键词： topology optimization sequential approximate optimization convex linearization method ofmoving asymptotes sequential quadratic programming

A Subdivision-Based Combined Shape and topology optimization in Acoustics

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 847-872页

作者： Chuang Lu Leilei Chen Jinling Luo Haibo Chen CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern MechanicsUniversity of Science and Technology of ChinaHefei230027China College of Intelligent Construction Wuchang University of TechnologyWuhan430223China Henan International Joint Laboratory of Structural Mechanics and Computational Simulation School of Architecture and EngineeringHuanghuai UniversityZhumadian463000China Beijing Aerospace Technology Institute Beijing100074China

We propose a combined shape and topology optimization approach in this research for 3D acoustics by using the isogeometric boundary element method with subdivision *** existing structural optimization methods mainly contain shape and topology schemes,with the former changing the surface geometric profile of the structure and the latter changing thematerial distribution topology or hole topology of the *** the present acoustic performance optimization,the coordinates of the control points in the subdivision surfaces fine mesh are selected as the shape design parameters of the structure,the artificial density of the sound absorbing material covered on the structure surface is set as the topology design parameter,and the combined topology and shape optimization approach is established through the sound field analysis of the subdivision surfaces boundary element method as a *** topology and shape sensitivities of the approach are calculated using the adjoint variable method,which ensures the efficiency of the *** geometric jaggedness and material distribution discontinuities that appear in the optimization process are overcome to a certain degree by the multiresolution method and solid isotropic material with *** examples are given to validate the effectiveness of the presented optimization approach.

关键词： Subdivision surfaces boundary element method topology optimization shape optimization combined optimization