4.7 Article

Adaptive multi-material topology optimization with hyperelastic materials under large deformations: A virtual element approach

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.cma.2020.112976

关键词

Multi-material topology optimization; Hyperelastic materials; Large deformations; ZPR update scheme; Virtual Element Method (VEM); Adaptive refinement and coarsening

资金

  1. University of Illinois at UrbanaChampaign, United States
  2. Raymond Allen Jones Chair at the Georgia Institute of Technology, United States

向作者/读者索取更多资源

We introduce a general multi-material topology optimization framework for large deformation problems that effectively handles an arbitrary number of candidate hyperelastic materials and addresses three major associated challenges: material interpolation, excessive distortion of low-density elements, and computational efficiency. To account for many nonlinear elastic materials, we propose a material interpolation scheme that, instead of interpolating multiple material parameters (such as Young's modulus), interpolates multiple nonlinear stored-energy functions. To circumvent convergence difficulties caused by excessive distortions of low-density elements under large deformations, an energy interpolation scheme is revisited to account for multiple candidate hyperelastic materials. Computational efficiency is addressed from both structural analysis and optimization perspectives. To solve the nonlinear state equations efficiently, we employ the lower-order Virtual Element Method in conjunction with tailored adaptive mesh refinement and coarsening strategies. To efficiently update the design variables of the multi-material system, we exploit the separable nature and improve the ZPR (Zhang-Paulino-Ramos) update scheme to account for positive sensitivities and update the design variables associated with each volume constraint in parallel. Four design examples with three types of nonlinear material models demonstrate the efficiency and effectiveness of the proposed framework. (C) 2020 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Chemistry, Multidisciplinary

Optimally-Tailored Spinodal Architected Materials for Multiscale Design and Manufacturing

Fernando Senhora, Emily D. Sanders, Glaucio H. Paulino

Summary: Spinodal architected materials optimize design of multiscale structures by varying spinodal class, orientation, and porosity, leading to efficient material placement along stress trajectories with enhanced mechanical and biological functions.

ADVANCED MATERIALS (2022)

Article Engineering, Mechanical

Design of Single Degree-of-Freedom Triangular Resch Patterns with Thick-panel Origami

Fufu Yang, Miao Zhang, Jiayao Ma, Zhong You, Ying Yu, Yan Chen, Glaucio H. Paulino

Summary: Resch patterns are tessellation origami patterns consisting of more than one type of polygons. They are generally rigid foldable but have a large number of degrees of freedom. In order to achieve one-DOF forms of triangular Resch pattern units, the thick-panel technique is employed to replace spherical linkages with spatial linkages. The compatibility among all the vertices is studied by kinematic analysis, and two design schemes are obtained to form a one-DOF origami structure.

MECHANISM AND MACHINE THEORY (2022)

Article Multidisciplinary Sciences

Digital synthesis of free-form multimaterial structures for realization of arbitrary programmed mechanical responses

Weichen Li, Fengwen Wang, Ole Sigmund, Xiaojia Shelly Zhang

Summary: In this study, a freeform inverse design approach is used to synthesize multiple hyperelastic materials into composite structures, enabling them to achieve arbitrary prescribed responses under large deformations. The digitally synthesized structures exhibit organic shapes and motions with irregular distributions of material phases. By utilizing multi material fabrication and heteroassembly strategies, function-oriented mechanical devices with highly complex yet navigable responses can be designed.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2022)

Article Multidisciplinary Sciences

Soft robotic origami crawler

Qiji Ze, Shuai Wu, Jun Nishikawa, Jize Dai, Yue Sun, Sophie Leanza, Cole Zemelka, Larissa S. Novelino, Glaucio H. Paulino, Ruike Renee Zhao

Summary: Researchers have developed a magnetically actuated small-scale origami crawler with inplane contraction, which can crawl and steer in confined spaces. This crawler has magnetically tunable structural stiffness, allowing it to overcome large resistances, and it has the ability to store and release drugs internally, demonstrating its multifunctionality.

SCIENCE ADVANCES (2022)

Article Engineering, Mechanical

Multimaterial stress-constrained topology optimization with multiple distinct yield criteria

Rahul Dev Kundu, Weichen Li, Xiaojia Shelly Zhang

Summary: This paper proposes a novel yield function interpolation scheme that allows for the simultaneous incorporation of distinct yield criteria and material strengths in stress-constrained topology optimization of composite structures. The optimized composite designs demonstrate advantages enabled by material heterogeneity, including design space enlargement, stress deconcentration effect, and exploitation of tension-compression strength asymmetry. These advantages lead to 10-40% reduced minimized volumes compared to single-material designs and provide new insights for the discovery of more efficient composite structures.

EXTREME MECHANICS LETTERS (2022)

Article Materials Science, Multidisciplinary

On topology optimization with gradient-enhanced damage: An alternative formulation based on linear physics

Jonathan B. Russ, Glaucio H. Paulino

Summary: In order to enhance structural resistance to material failure, numerous topology optimization formulations have been proposed. This research extends the former method by constraining local failure criteria in a manner inspired by typical gradient-enhanced damage models. The proposed formulation relies on linear physics during the optimization procedure, greatly increasing its speed and robustness. Additionally, the study investigates the size effect introduced by using a numerical model and provides select observations, such as spurious fin-like patterns that can emerge depending on the structure and loading conditions. Finally, the load capacity of each optimized design is verified through a post-optimization verification procedure unaffected by the design parameterization and material interpolation schemes.

JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS (2023)

Article Materials Science, Multidisciplinary

Controlling the fracture response of structures via topology optimization: From delaying fracture nucleation to maximizing toughness

Yingqi Jia, Oscar Lopez-Pamies, Xiaojia Shelly Zhang

Summary: It is well-established that simple topology variations can significantly change the fracture response of structures. This paper proposes a density-based topology optimization framework that uses a complete phase-field fracture theory to accurately describe fracture behaviors. The framework optimizes the structure's initial stiffness, the time of fracture nucleation, and the energy dissipated by fracture propagation. The optimized structures exhibit enhanced fracture behaviors compared to conventional stiffness maximization.

JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS (2023)

Article Mechanics

Tuning Buckling Behaviors in Magnetically Active Structures: Topology Optimization and Experimental Validation

Zhi Zhao, Chao Wang, Xiaojia Shelly Zhang

Summary: Buckling, historically considered undesirable, has been harnessed to enable innovative functionalities in materials and structures. However, tuning buckling behaviors in fabricated structures without altering their geometry remains a major challenge. In this study, an inverse design approach is introduced to tune buckling behavior in magnetically active structures through the variation of applied magnetic stimuli.

JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME (2023)

Article Multidisciplinary Sciences

Topology optimization with local stress constraints and continuously varying load direction and magnitude: towards practical applications

Fernando V. Senhora, Ivan F. M. Menezes, Glaucio H. Paulino

Summary: Topology optimization problems often focus on a single or a few discrete load cases, while practical structures are subjected to infinitely many load cases that vary in intensity, location, and direction. This study proposes a locally stress-constrained topology optimization method that considers continuously varying load directions to ensure structural integrity under more realistic loading conditions.

PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2023)

Article Chemistry, Physical

Encoding reprogrammable properties into magneto-mechanical materials via topology optimization

Zhi Zhao, Xiaojia Shelly Zhang

Summary: The properties of materials and structures can now be reprogrammed without changing their geometries or material constitutions. An optimization-driven approach based on multi-objective magneto-mechanical topology optimization is introduced to design magneto-active metamaterials and structures. These systems exhibit different responses under mechanical and magnetic stimuli, allowing for various reprogrammable behaviors. This approach has potential applications in magnetic actuators, soft robots, and energy harvesters.

NPJ COMPUTATIONAL MATERIALS (2023)

Article Mechanics

Stress-based topology optimization for fiber composites with improved stiffness and strength: Integrating anisotropic and isotropic materials

Rahul Dev Kundu, Xiaojia Shelly Zhang

Summary: This article proposes a multimaterial anisotropic stress-constrained topology optimization framework to design stiff, strong, and lightweight fiber-reinforced composite structures. The framework simultaneously optimizes geometry, distribution of anisotropic and isotropic material phases, and local orientations of fiber reinforcements. Both isotropic and anisotropic materials are found to be necessary for high performance in both stiffness and strength, with anisotropic materials preferred in uniaxial members and isotropic materials crucial at multi-axially stressed joints. Multimaterial interpolation schemes are introduced to characterize the stiffness and strength of composites with anisotropic and isotropic materials. The proposed framework effectively reduces stress concentration in fiber composites.

COMPOSITE STRUCTURES (2023)

Article Engineering, Multidisciplinary

Inverse design of magneto-active metasurfaces and robots: Theory, computation, and experimental validation

Chao Wang, Zhi Zhao, Xiaojia Shelly Zhang

Summary: This paper presents a multi-physics topology optimization framework for the design of magneto-active metasurfaces that can undergo programmable shape morphing in 3D under external magnetic fields. The framework considers large-deformation kinematics and optimizes the topologies, magnetization distributions, and external magnetic fields. Experimental tests validate the designed metasurfaces' programmed 3D deformations.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2023)

Article Engineering, Multidisciplinary

Programming and physical realization of extreme three-dimensional responses of metastructures under large deformations

Weichen Li, Yingqi Jia, Fengwen Wang, Ole Sigmund, Xiaojia Shelly Zhang

Summary: This study systematically investigates several precisely programmed nonlinear extreme responses in 3D structures under finite deformations through multimaterial inverse design by topology optimization. Unique complex 3D geometries with deformation capabilities are discovered and utilized to deliver the target responses. The optimized structure is accurately fabricated through a proposed hybrid fabrication method and the design's programmed behavior is validated.

INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE (2023)

Article Engineering, Manufacturing

Additive manufacturing of stiff and strong structures by leveraging printing-induced strength anisotropy in topology optimization

Rahul Dev Kundu, Xiaojia Shelly Zhang

Summary: Anisotropy in additive manufacturing has a crucial impact on structural performance, and this study utilizes this characteristic to design and fabricate stronger and lighter structures. Experimental results show significant improvement in performance.

ADDITIVE MANUFACTURING (2023)

Article Engineering, Multidisciplinary

Arbitrary curvature programming of thermo-active liquid crystal elastomer via topology optimization

Weichen Li, Xiaojia Shelly Zhang

Summary: Inspired by plants' morphological adaptability, this study presents a computational inverse design framework for creating optimized thermo-active liquid crystal elastomers (LCEs) that spontaneously morph into arbitrary programmed geometries upon temperature changes. The framework relies on multiphysics topology optimization and a statistical mechanics-based LCE model, allowing for curvature programming of LCE composites under large deformations. The proposed technique enables accurate morphing into complex target shapes and curvatures, surpassing intuition-based designs and holding promise for various applications.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2023)

Article Engineering, Multidisciplinary

Probabilistic physics-guided transfer learning for material property prediction in extrusion deposition additive manufacturing

Akshay J. Thomas, Mateusz Jaszczuk, Eduardo Barocio, Gourab Ghosh, Ilias Bilionis, R. Byron Pipes

Summary: We propose a physics-guided transfer learning approach to predict the thermal conductivity of additively manufactured short-fiber reinforced polymers using micro-structural characteristics obtained from tensile tests. A Bayesian framework is developed to transfer the thermal conductivity properties across different extrusion deposition additive manufacturing systems. The experimental results demonstrate the effectiveness and reliability of our method in accounting for epistemic and aleatory uncertainties.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

Discovering a reaction-diffusion model for Alzheimer's disease by combining PINNs with symbolic regression

Zhen Zhang, Zongren Zou, Ellen Kuhl, George Em Karniadakis

Summary: In this study, deep learning and artificial intelligence were used to discover a mathematical model for the progression of Alzheimer's disease. By analyzing longitudinal tau positron emission tomography data, a reaction-diffusion type partial differential equation for tau protein misfolding and spreading was discovered. The results showed different misfolding models for Alzheimer's and healthy control groups, indicating faster misfolding in Alzheimer's group. The study provides a foundation for early diagnosis and treatment of Alzheimer's disease and other misfolding-protein based neurodegenerative disorders using image-based technologies.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

A neural network-based enrichment of reproducing kernel approximation for modeling brittle fracture

Jonghyuk Baek, Jiun-Shyan Chen

Summary: This paper introduces an improved neural network-enhanced reproducing kernel particle method for modeling the localization of brittle fractures. By adding a neural network approximation to the background reproducing kernel approximation, the method allows for the automatic location and insertion of discontinuities in the function space, enhancing the modeling effectiveness. The proposed method uses an energy-based loss function for optimization and regularizes the approximation results through constraints on the spatial gradient of the parametric coordinates, ensuring convergence.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

Stabilized mixed material point method for incompressible fluid flow

Bodhinanda Chandra, Ryota Hashimoto, Shinnosuke Matsumi, Ken Kamrin, Kenichi Soga

Summary: This paper proposes new and robust stabilization strategies for accurately modeling incompressible fluid flow problems in the material point method (MPM). The proposed approach adopts a monolithic displacement-pressure formulation and integrates two stabilization strategies to ensure stability. The effectiveness of the proposed method is validated through benchmark cases and real-world scenarios involving violent free-surface fluid motion.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

A unified analytical expression of the tangent stiffness matrix of holonomic constraints

Chao Peng, Alessandro Tasora, Dario Fusai, Dario Mangoni

Summary: This article discusses the importance of the tangent stiffness matrix of constraints in multibody systems and provides a general formulation based on quaternion parametrization. The article also presents the analytical expression of the tangent stiffness matrix derived through linearization. Examples demonstrate the positive effect of this additional stiffness term on static and eigenvalue analyses.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

On the detection of nonlinear normal mode-related isolated branches of periodic solutions for high-dimensional nonlinear mechanical systems with frictionless contact interfaces

Thibaut Vadcard, Fabrice Thouverez, Alain Batailly

Summary: This contribution presents a methodology for detecting isolated branches of periodic solutions to nonlinear mechanical equations. The method combines harmonic balance method-based solving procedure with the Melnikov energy principle. It is able to predict the location of isolated branches of solutions near families of autonomous periodic solutions. The relevance and accuracy of this methodology are demonstrated through academic and industrial applications.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

Machine learning powered sketch aided design via topology optimization

Weisheng Zhang, Yue Wang, Sung-Kie Youn, Xu Guo

Summary: This study proposes a sketch-guided topology optimization approach based on machine learning, which incorporates computer sketches as constraint functions to improve the efficiency of computer-aided structural design models and meet the design intention and requirements of designers.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

Reduced order isogeometric boundary element methods for CAD-integrated shape optimization in electromagnetic scattering

Leilei Chen, Zhongwang Wang, Haojie Lian, Yujing Ma, Zhuxuan Meng, Pei Li, Chensen Ding, Stephane P. A. Bordas

Summary: This paper presents a model order reduction method for electromagnetic boundary element analysis and extends it to computer-aided design integrated shape optimization of multi-frequency electromagnetic scattering problems. The proposed method utilizes a series expansion technique and the second-order Arnoldi procedure to reduce the order of original systems. It also employs the isogeometric boundary element method to ensure geometric exactness and avoid re-meshing during shape optimization. The Grey Wolf Optimization-Artificial Neural Network is used as a surrogate model for shape optimization, with radar cross section as the objective function.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

Volume conservation issue within SPH models for long-time simulations of violent free-surface flows

C. Pilloton, P. N. Sun, X. Zhang, A. Colagrossi

Summary: This paper investigates the smoothed particle hydrodynamics (SPH) simulations of violent sloshing flows and discusses the impact of volume conservation errors on the simulation results. Different techniques are used to directly measure the particles' volumes and stabilization terms are introduced to control the errors. Experimental comparisons demonstrate the effectiveness of the numerical techniques.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

Convolution finite element based digital image correlation for and strain measurements

Ye Lu, Weidong Zhu

Summary: This work presents a novel global digital image correlation (DIC) method based on a convolution finite element (C-FE) approximation. The C-FE based DIC provides highly smooth and accurate displacement and strain results with the same element size as the usual finite element (FE) based DIC. The proposed method's formulation and implementation, as well as the controlling parameters, have been discussed in detail. The C-FE method outperformed the FE method in all tested examples, demonstrating its potential for highly smooth, accurate, and robust DIC analysis.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

Optimization based on performance of lungs in body: Lungs performance-based optimization (LPO)

Mojtaba Ghasemi, Mohsen Zare, Amir Zahedi, Pavel Trojovsky, Laith Abualigah, Eva Trojovska

Summary: This paper introduces Lung performance-based optimization (LPO), a novel algorithm that draws inspiration from the efficient oxygen exchange in the lungs. Through experiments and comparisons with contemporary algorithms, LPO demonstrates its effectiveness in solving complex optimization problems and shows potential for a wide range of applications.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

Integrated optimization of components' layout and structural topology with considering the interface stress constraint

Jingyu Hu, Yang Liu, Huixin Huang, Shutian Liu

Summary: In this study, a new topology optimization method is proposed for structures with embedded components, considering the tension/compression asymmetric interface stress constraint. The method optimizes the topology of the host structure and the layout of embedded components simultaneously, and a new interpolation model is developed to determine interface layers between the host structure and embedded components.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

The anisotropic graph neural network model with multiscale and nonlinear characteristic for turbulence simulation

Qiang Liu, Wei Zhu, Xiyu Jia, Feng Ma, Jun Wen, Yixiong Wu, Kuangqi Chen, Zhenhai Zhang, Shuang Wang

Summary: In this study, a multiscale and nonlinear turbulence characteristic extraction model using a graph neural network was designed. This model can directly compute turbulence data without resorting to simplified formulas. Experimental results demonstrate that the model has high computational performance in turbulence calculation.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

Multi-temporal decomposition for elastoplastic ratcheting solids

Jacinto Ulloa, Geert Degrande, Jose E. Andrade, Stijn Francois

Summary: This paper presents a multi-temporal formulation for simulating elastoplastic solids under cyclic loading. The proper generalized decomposition (PGD) is leveraged to decompose the displacements into multiple time scales, separating the spatial and intra-cyclic dependence from the inter-cyclic variation, thereby reducing computational burden.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)

Article Engineering, Multidisciplinary

Automated translation and accelerated solving of differential equations on multiple GPU platforms

Utkarsh Utkarsh, Valentin Churavy, Yingbo Ma, Tim Besard, Prakitr Srisuma, Tim Gymnich, Adam R. Gerlach, Alan Edelman, George Barbastathis, Richard D. Braatz, Christopher Rackauckas

Summary: This article presents a high-performance vendor-agnostic method for massively parallel solving of ordinary and stochastic differential equations on GPUs. The method integrates with a popular differential equation solver library and achieves state-of-the-art performance compared to hand-optimized kernels.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2024)