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multi-material Topology Optimization of 2D Structures Using Convolutional Neural Networks

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 design.However,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 lacking.Therefore,this paper proposes the framework of multiphase topology optimization using deep learning to accelerate MMTO design.The 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 iterations.The 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 accuracy.Additionally,in order to find a more reasonable modeling method for MMTO,this paper studies the characteristics of surrogate modeling as regression task and classification task.Through the training of 297 models,our findings show that the regression task yields slightly better results than the classification task in most cases.Furthermore,The results indicate that the prediction accuracy is primarily influenced by factors such as the TO problem,material category,and data scale.Conversely,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

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multi-material magnetic field-assisted additive manufacturing system for flexible actuators with programmable magnetic arrangements

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Frontiers of Mechanical Engineering 2024年第2期19卷 109-120页

作者： Yujie HUANG Haonan SUN Chengqian ZHANG Ruoxiang GAO Hongyao SHEN Peng ZHAO The State Key Laboratory of Fluid Power and Mechatronic Systems College of Mechanical EngineeringZhejiang UniversityHangzhou 310027China The Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province College of Mechanical EngineeringZhejiang UniversityHangzhou 310027China Center for X-Mechanics Department of Engineering MechanicsZhejiang UniversityHangzhou 310027China

Manufacturing flexible magnetic-driven actuators with complex structures and magnetic arrangements to achieve diverse functionalities is becoming a popular trend.Among various manufacturing technologies,magnetic-assisted digital light processing(DLP)stands out because it enables precise manufacturing of macro-scale structures and micro-scale distributions with the assistance of an external magnetic field.Current research on manufacturing magnetic flexible actuators mostly employs single materials,which limits the magnetic driving performance to some extent.Based on these characterizations,we propose a multi-material magnetic field-assisted DLP technology to produce flexible actuators with an accuracy of 200μm.The flexible actuators are printed using two materials with different mechanical and magnetic properties.Considering the interface connectivity of multi-material printing,the effect of interfaces on mechanical properties is also explored.Experimental results indicate good chemical affinity between the two materials we selected.The overlap or connection length of the interface moderately improves the tensile strength of multi-material structures.In addition,we investigate the influence of the volume fraction of the magnetic part on deformation.Simulation and experimental results indicate that increasing the volume ratio(20%to 50%)of the magnetic structure can enhance the responsiveness of the actuator(more than 50%).Finally,we successfully manufacture two multi-material flexible actuators with specific magnetic arrangements:a multi-legged crawling robot and a flexible gripper capable of crawling and grasping actions.These results confirm that this method will pave the way for further research on the precise fabrication of magnetic flexible actuators with diverse functionalities.

关键词： multi-material magnetic field-assisted manufacturing digital light processing flexible actuators magnetic arrangement

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An Efficient Strategy for Non-probabilistic Reliability-Based multi-material Topology Optimization with Evidence Theory

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Acta Mechanica Solida Sinica 2019年第6期32卷 803-821页

作者： Qinghai Zhao Hongxin Zhang Tiezhu Zhang Qingsong Hua Lin Yuan Wenyue Wang National and Local Union Engineering Research Center of Electric Vehicle Intelligent Power Integration Technology Qingdao UniversityQingdao 266071China Mechanical and Electrical College Qingdao UniversityQingdao 266071China

It is essential to consider the effects of incomplete measurement,inaccurate information and inadequate cognition on structural topology optimization.For the multi-material structural topology optimization with non-probability uncertainty,the multi-material interpolation model is represented by the ordered rational approximation of mat erial properties(ordered RAMP).Combined with structural compliance minimization,the multi-material topology optimization with reliability constraints is established.The corresponding non-probability uncertainties are described by the evidence theory,and the uniformity processing method is introduced to convert the evidence variables into random variables.The first-order reliability method is employed to search the most probable point under the reliability index constraint,and then the random variables are equivalent to the deterministic variables according to the geometric meaning of the reliability index and sensitivity information.Therefore,the non-probabilistic reliability-based multi-material topology optimization is transformed into the conventional deterministic optimization format,followed by the ordered RAMP method to solve the optimization problem.Finally,through numerical examples of 2D and 3D structures,the feasibility and effectiveness of the proposed method are verified to consider the geometrical dimensions and external loading uncertainties.

关键词： multi-material Topology optimization Non-probabilistic Reliability Evidence theory

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A hybrid subcell-remapping algorithm for staggered multi-material arbitrary Lagrangian-Eulerian methods

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Applied Mathematics and Mechanics(English Edition) 2019年第10期40卷 1487-1508页

作者： Haihua YANG Ping ZHANG Institute of Applied Physics and Computational Mathematics

A new flux-based hybrid subcell-remapping algorithm for staggered multimaterial arbitrary Lagrangian-Eulerian (MMALE) methods is presented. This new method is an effective generalization of the original subcell-remapping method to the multi-material regime (LOUBERE, R. and SHASHKOV,M. A subcell remapping method on staggered polygonal grids for arbitrary-Lagrangian-Eulerian methods. Journal of Computational Physics, 209, 105–138 (2005)). A complete remapping procedure of all fluid quantities is described detailedly in this paper. In the pure material regions, remapping of mass and internal energy is performed by using the original subcell-remapping method. In the regions near the material interfaces, remapping of mass and internal energy is performed with the intersection-based fluxes where intersections are performed between the swept regions and pure material polygons in the Lagrangian mesh, and an approximate approach is then introduced for constructing the subcell mass fluxes. In remapping of the subcell momentum, the mass fluxes are used to construct the momentum fluxes by multiplying a reconstructed velocity in the swept region. The nodal velocity is then conservatively recovered. Some numerical examples simulated in the full MMALE regime and several purely cyclic remapping examples are presented to prove the properties of the remapping method.

关键词： multi-material arbitrary Lagrangian-Eulerian (MMALE) subcell remapping method hybrid remapping method

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Robust topology optimization of multi-material lattice structures under material and load uncertainties

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Frontiers of Mechanical Engineering 2019年第2期14卷 141-152页

作者： Yu-Chin CHAN Kohei SHINTANI Wei CHEN Department of Mechanical Engineering Northwestern UniversityEvanstonIL 60208USA

Enabled by advancements in multi-material additive manufacturing,lightweight lattice structures consisting of networks of periodic unit cells have gained popularity due to their extraordinary performance and wide array of functions.This work proposes a density-based robust topology optimization method for meso-or macroscale multi-material lattice structures under any combination of material and load uncertainties.The method utilizes a new generalized material interpolation scheme for an arbitrary number of materials,and employs univariate dimension reduction and Gauss-type quadrature to quantify and propagate uncertainty.By formulating the objective function as a weighted sum of the mean and standard deviation of compliance,the tradeoff between optimality and robustness can be studied and controlled.Examples of a cantilever beam lattice structure under various material and load uncertainty cases exhibit the efficiency and flexibility of the approach.The accuracy of univariate dimension reduction is validated by comparing the results to the Monte Carlo approach.

关键词： robust topology optimization lattice structures multi-material material uncertainty load uncertainty univariate dimension reduction

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Robust Topology Optimization of Periodic multi-material Functionally Graded Structures under Loading Uncertainties

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Computer Modeling in Engineering & Sciences 2021年第5期127卷 683-704页

作者： Xinqing Li Qinghai Zhao Hongxin Zhang Tiezhu Zhang Jianliang Chen College of Mechanical and Electrical Engineering Qingdao UniversityQingdao266071China Power Integration and Energy Storage System Engineering Technology Center Qingdao UniversityQingdao266071China

This paper presents a robust topology optimization design approach for multi-material functional graded structures under periodic constraint with load uncertainties.To characterize the random-field uncertainties with a reduced set of random variables,the Karhunen-Lo`eve(K-L)expansion is adopted.The sparse grid numerical integration method is employed to transform the robust topology optimization into a weighted summation of series of deterministic topology optimization.Under dividing the design domain,the volume fraction of each preset gradient layer is extracted.Based on the ordered solid isotropic microstructure with penalization(Ordered-SIMP),a functionally graded multi-material interpolation model is formulated by individually optimizing each preset gradient layer.The periodic constraint setting of the gradient layer is achieved by redistributing the average element compliance in sub-regions.Then,the method of moving asymptotes(MMA)is introduced to iteratively update the design variables.Several numerical examples are presented to verify the validity and applicability of the proposed method.The results demonstrate that the periodic functionally graded multi-material topology can be obtained under different numbers of sub-regions,and robust design structures are more stable than that indicated by the deterministic results.

关键词： multi-material topology optimization robust design periodic functional gradient sparse grid method

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Advanced Welding Technology for Highly Stressable multi-material Designs with Fiber-Reinforced Plastics and Metals

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Open Journal of Composite materials 2017年第3期7卷 166-177页

作者： Holger Seidlitz Sebastian Fritzsche Marcello Ambrosio Alexander Kloshek Department of Lightweight Structures and Structural materials Brandenburg University of Technology Cottbus Germany

Organic sheets made out of fiber-reinforced thermoplastics are able to make a crucial contribution to increase the lightweight potential of a design. They show high specific strength- and stiffness properties, good damping characteristics and recycling capabilities, while being able to show a higher energy absorption capacity than comparable metal constructions. Nowadays, multi-material designs are an established way in the automotive industry to combine the benefits of metal and fiber-reinforced plastics. Currently used technologies for the joining of organic sheets and metals in large-scale production are mechanical joining technologies and adhesive technologies. Both techniques require large overlapping areas that are not required in the design of the part. Additionally, mechanical joining is usually combined with “fiber-destroying” pre-drilling and punching processes. This will disturb the force flux at the joining location by causing unwanted fiber- and inter-fiber failure and inducing critical notch stresses. Therefore, the multi-material design with fiber-reinforced thermoplastics and metals needs optimized joining techniques that don’t interrupt the force flux, so that higher loads can be induced and the full benefit of the FRP material can be used. This article focuses on the characterization of a new joining technology, based on the Cold Metal Transfer (CMT) welding process that allows joining of organic sheets and metals in a load path optimized way, with short cycle times. This is achieved by redirecting the fibers around the joining area by the insertion of a thin metal pin. The path of the fibers will be similar to paths of fibers inside structures found in nature, e.g. a knothole inside of a tree. As a result of the bionic fiber design of the joint, high joining strengths can be achieved. The increase of the joint strength compared to blind riveting was performed and proven with stainless steel and orthotropic reinforced composites in shear-tests based on the DIN EN ISO 14273. Every specimen joined

关键词： multi-material Design Fiber Reinforced Plastics Lightweight Automotive Structures Joining

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Joining Technology of Dissimilar materials for Automotive Components(Ⅱ)

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Journal of Rare Earths 2004年第Z2期22卷 35-37页

作者： Meung Ho Rhee Jong Ho Song Woo Young Chung Young Myoung Kim Korea Automotive Technology Institute 74 Yongjung-RiPungse-MyunChonanChungnam330-912KOREA Korea Automotive Technology Institute74 Yongjung-RiPungse-MyunChonanChungnam330-912KOREA Korea Automotive Technology Institute74 Yongjung-RiPungse-MyunChonanChungnam330-912KOREA Korea Automotive Technology Institute74 Yongjung-RiPungse-MyunChonanChungnam330-912KOREA

Joining techniques of dissimilar materials for lightweight multi-material automotive body structure were discussed. The joining of 1 .4 mm thickness steel and 2 mm thickness of Al were performed by the new method that is hybrid laser welding system. After aluminum and steel were welded by laser hybrid welding process, the micro-structure investment and the micro-hardness test were carried out. Hybrid laser welding promises a bright future in joining technology of dissimilar materials for automotive components.

关键词： multi-material automotive body dissimilar materials hybrid laser welding

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Recent advances and challenges in materials for 3D bioprinting

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Progress in Natural Science:materials International 2020年第5期30卷 618-634页

作者： Hongli Mao Li Yang Haofang Zhu Lihuang Wu Peihong Ji Jiquan Yang Zhongwei Gu College of materials Science and Engineering Nanjing Tech University Research Institute for Biomaterials Tech Institute for Advanced Materials Nanjing Tech University NJTech-BARTY Joint Research Center for Innovative Medical Technology Nanjing Industry Institute for Advanced Intelligent Equipment Jiangsu Key Lab of 3D Printing Equipment and Manufacturing Nanjing Normal University

3 D bioprinting has been developed as a promising technology in a wide variety of biomedical applications.However, the successful implementation of bioprinting is still heavily restricted by the relatively narrow range of printable and biocompatible materials. Recently, many comprehensive reviews of the main bioprinting methods,commonly used bioprinting materials and the trending bioprinting applications have been carried out. In this review, we focused on the trends in the development of materials for 3 D bioprinting. The significance and recent advances of ECM-based materials, multi-material and stimuli-responsive materials for bioprinting were summarized successively. Moreover, the challenges in current studies and future perspectives of materials for 3 D bioprinting were discussed.

关键词： 3D bioprinting ECM-based materials multi-material Composite and hybrid materials Stimuli-responsive materials

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High temperature co-firing of 3D-printed AleZnO/Al_(2)O_(3) multimaterial two-phase flow sensor

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Journal of Materiomics 2022年第3期8卷 710-718页

作者： Danwei Zhang Win Jonhson Tun Seng Herng Xi Xu Xiaojing Liu Liang-ming Pan Hui He Jun Ding Department of materials Science and Engineering Faculty of EngineeringNational University of Singapore9 Engineering Drive 1117576Singapore Institute of materials Research and Engineering Agency for ScienceTechnology and Research2 Fusionopolis Way138635Singapore Institute of Flexible Electronics Xi'an Key Laboratory of Flexible ElectronicsNorthwestern Polytechnical UniversityXi'an710072China School of Nuclear Science and Engineering Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of Low-Grade Energy Utilization Technologies and Systems(Chongqing University) Ministry of EducationChongqing400044China

Sensors are crucial in the understanding of machines working under high temperatures and highpressure conditions.Current devices utilize polymeric materials as electrical insulators which pose a challenge in the device's lifespan.Ceramics,on the other hand,is robust and able to withstand high temperature and pressure.For such applications,a co-fired ceramic device which can provide both electrical conductivity and insulation is beneficial and acts as a superior candidate for sensor devices.In this paper,we propose a novel fabrication technique of complex multi-ceramics structures via 3D printing.This fabrication methodology increases both the geometrical complexity and the device's shape precision.Structural ceramics(alumina)was employed as the electrical insulator whilst providing mechanical rigidity while a functional ceramic(alumina-doped zinc oxide)was employed as the electrically conductive material.The addition of sintering additives,tailoring the printing pastes'solid loadings and heat treatment profile resolves multi-materials printing challenges such as shrinkage disparity and densification matching.Through high-temperature co-firing of ceramics(HTCC)technology,dense high quality functional multi-ceramics structures are achieved.The proposed fabrication methodology paves the way for multi-ceramics sensors to be utilized in high temperature and pressure systems in the near future.

关键词： 3D printing multi-material Robocasting Sensors Ceramics

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