Article
Engineering, Multidisciplinary
Rixin Wang, Xianmin Zhang, Benliang Zhu
Summary: The paper introduces a projective transformation-based topology optimization method using moving morphable components to improve manufacturability of optimal results without being affected by background mesh quality. The proposed method can handle components that are difficult to describe and has been verified effective through numerical examples.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Benliang Zhu, Rixin Wang, Nianfeng Wang, Hao Li, Xianmin Zhang, Shinji Nishiwaki
Summary: This paper presents a structural topology optimization method using moving wide Bezier components with constrained ends, which connects components by constraining the ends to avoid structurally invalid designs and smooth the optimization process.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Computer Science, Interdisciplinary Applications
T. Shannon, T. T. Robinson, A. Murphy, C. G. Armstrong
Summary: This paper presents the development of generalized Bezier components in the Moving Morphable Components optimization framework and discusses methods for enhancing component parameterization. By using control points and Bezier curves to represent structural components, the shape flexibility and parameterization compatibility with commercial CAD packages are achieved. The paper also includes methods for calculating analytical derivatives and numerical examples to demonstrate the integration of these structural components in the optimization framework.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Engineering, Multidisciplinary
Quhao Li, Guowei Liang, Yunfeng Luo, Fengtong Zhang, Shutian Liu
Summary: Topology optimization is widely used in engineering for innovative designs, but the optimized results often lack manufacturability. This study proposes an explicit and general method to control the minimum length scale in topology optimization, which is accurate and easily implemented. By computing the average density of elements in a small circular region, all local constraints are aggregated into a single constraint, and the sensitivity analysis of the constraint function is derived. Numerical examples demonstrate the effectiveness of the proposed algorithm.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Jun Yan, Qi Xu, Zhirui Fan, Zunyi Duan, Hongze Du, Dongling Geng
Summary: This study investigates structural topology optimization of thermoelastic structures considering two kinds of objectives with a specified available volume constraint. The moving morphable components (MMC) framework is adopted to explicitly express the configuration evolution and can substantially reduce the number of design variables. The optimization results show that the objective function with the minimum structural strain energy can achieve a better performance than that from structural compliance design for thermoelastic structural strength optimization.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2021)
Article
Materials Science, Multidisciplinary
Tianchen Cui, Zongliang Du, Chang Liu, Zhi Sun, Xu Guo
Summary: In this article, an explicit topology optimization approach with components-growing ability is proposed under the MMC framework. The approach optimizes the shape and topology layout of structures by the growth evolution of moving morphable components. It eliminates the initial design dependency by allowing the addition of new components or modification of the current layout.
ACTA MECHANICA SOLIDA SINICA
(2022)
Article
Computer Science, Interdisciplinary Applications
Ki Hyun Kim, Gil Ho Yoon
Summary: In this study, an acoustic topology optimization method using moving morphable components (MMCs) was developed for the design of 2D sound reduction structures. By changing the parameters and overlapping of MMCs, the shape of the structure is formed to improve the acoustic performance of sound reduction structures. Various designs were evaluated under different conditions and optimization settings, and additional design procedures were devised to enhance the acoustic performance of sound reduction structures.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Engineering, Multidisciplinary
Shuai Zheng, Haojie Fan, Ziyu Zhang, Zhiqiang Tian, Kang Jia
Summary: This study introduces a real-time structural topology optimization method based on a convolutional neural network, replacing traditional iterative calculations with residual learning and attention mechanisms, significantly improving accuracy.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Construction & Building Technology
Lifu Wang, Dongyan Shi, Boyang Zhang, Guangliang Li, Peng Liu
Summary: The moving morphable component (MMC) method is an important engineering structural optimization algorithm that achieves structural optimization through the migration and superposition of a series of moving morphable display components. In this research, a Pyramid Attention U-Net (PA-U-Net) deep learning model is proposed to improve the optimization design and avoid intermediate iterative computations. Experimental results show that the method has high accuracy and low computational time cost, and it shows potential for application in the design optimization of large engineering structures.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Automation & Control Systems
Thomas Rochefort-Beaudoin, Aurelian Vadean, Jean-Francois Gamache, Sofiane Achiche
Summary: In this paper, a deep learning model is trained on the moving morphable components (MMC) framework to directly generate geometric design variables, addressing the limitations of existing machine learning accelerated topology optimization methods trained on datasets with limited diversity of boundary conditions. The model achieves scalability by being independent of the finite element mesh used for structural analysis. However, the generated topologies have poor mechanical performance, which is improved by using the trained model to generate improved initial designs for conventional optimization.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Hampus Hederberg, Carl-Johan Thore
Summary: This paper combines density-based topology optimization with a moving morphable component to achieve fail-safe designs, minimizing compliance for worst damage and optimizing the position of MMC for maximum compliance. Multiple location initialization of MMC in a non-convex problem is handled using a gradient-based solver to obtain more robust structures. The proposed method can produce fail-safe designs with reasonable computational cost.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Zongliang Du, Tianchen Cui, Chang Liu, Weisheng Zhang, Yilin Guo, Xu Guo
Summary: This study proposes an efficient and easy-to-extend three-dimensional topology optimization method, which improves the efficiency and performance of the optimization process by introducing new numerical techniques and optimizing the load transmission path.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Yanfang Zhao, Van-Nam Hoang, Gang-Won Jang, Wenjie Zuo
Summary: This paper introduces a three-dimensional moving morphable bar method to obtain hollow structures directly, which effectively achieves optimized designs. The method involves projecting geometric features and performing Boolean subtraction of two solid bars to obtain three-dimensional hollow moving morphable bars.
ADVANCES IN ENGINEERING SOFTWARE
(2021)
Article
Computer Science, Interdisciplinary Applications
Yanfang Zhao, Guikai Guo, Jiantao Bai, Wenjie Zuo
Summary: This paper proposes a hollow structural topology optimization method considering geometrical nonlinearity using three-dimensional moving morphable bars. Numerical examples demonstrate the effectiveness of this method under large deformation conditions.
ENGINEERING WITH COMPUTERS
(2022)
Article
Mechanics
Wendong Huo, Chang Liu, Zongliang Du, Xudong Jiang, Zhenyu Liu, Xu Guo
Summary: This article proposes an integrated paradigm for topology optimization on complex surfaces using structural components and computational conformal mapping technique. Numerical examples demonstrate the effectiveness and efficiency of the proposed approach, which outperforms traditional methods.
JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME
(2022)
Article
Computer Science, Interdisciplinary Applications
Rixin Wang, Xianmin Zhang, Benliang Zhu, Hongchuan Zhang, Bicheng Chen, Haonan Wang
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2020)
Article
Engineering, Multidisciplinary
Rixin Wang, Xianmin Zhang, Benliang Zhu
Summary: The paper introduces a projective transformation-based topology optimization method using moving morphable components to improve manufacturability of optimal results without being affected by background mesh quality. The proposed method can handle components that are difficult to describe and has been verified effective through numerical examples.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Engineering, Mechanical
Rixin Wang, Xianmin Zhang, Benliang Zhu, Fahua Qu, Bicheng Chen, Junwen Liang
Summary: This paper presents a new method for the integrated design of compliant mechanisms and piezoelectric actuators, which incorporates the projective transformation-based moving morphable components method with the parametric level set method. The effectiveness of the proposed method is verified considering numerical examples.
MECHANISM AND MACHINE THEORY
(2022)
Article
Engineering, Multidisciplinary
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)