Article
Engineering, Multidisciplinary
Xiaojia Shelly Zhang, Heng Chi, Zhi Zhao
Summary: A general topology optimization framework for designing hyperelastic structures with nonlinear and anisotropic fiber reinforcements has been proposed. The framework optimizes both the material distribution and fiber orientations, and includes methods to improve computational efficiency. Design examples demonstrate the efficiency and effectiveness of the framework in designing anisotropic hyperelastic structures under large deformations.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Materials Science, Multidisciplinary
Raphael Hoeller, Florian Libisch, Christian Hellmich
Summary: This study computes large deflections of suspended circular graphene sheets with simply supported boundaries under various types of vertical axisymmetric forces based on the principle of virtual power. The deflections are approximated using a Fourier series, resulting in a nonlinear algebraic system of equations solved by an iterative Newton-Raphson procedure. The method is validated using experimental nanoindentation measurements.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2022)
Article
Mechanics
Chen Xing, Tiantang Yu, Yulin Sun, Yongxiang Wang
Summary: In this work, an adaptive phase-field method is proposed for modeling fracture of hyperelastic materials at large deformations. The adaptive mesh refinement is facilitated by the variable-node elements, which act as transition elements in the employed quadtree mesh. The combination of phase-field and energetic mesh refinement criterion is used to control the adaptive process. The proposed method is verified through several examples and shows its effectiveness in reproducing complex failure phenomena at large deformations.
ENGINEERING FRACTURE MECHANICS
(2023)
Article
Engineering, Multidisciplinary
Xianda Xie, Aodi Yang, Ning Jiang, Shuting Wang
Summary: The proposed topology optimization method using fully adaptive truncated hierarchical B-splines (ATHB-TO) successfully provides identical optimized designs at a lower computational burden and improved convergence rate. The adaptive mark strategy enhances computational efficiency and structural performance, outperforming TO performed on uniformly refined meshes.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Computer Science, Information Systems
Qinbao Xu, Changda Wang
Summary: The article introduces a data provenance scheme based on multigranularity graphs and stepwise refinement, which can effectively improve the efficiency of data trustworthiness evaluation.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Mathematics, Applied
C. Luthi, M. Afrasiabi, M. Bambach
Summary: This work presents a spatially fully-adaptive smoothed particle hydrodynamics (SPH) scheme and applies it for simulating melt pool behavior in laser powder bed fusion (LPBF) additive manufacturing. By utilizing particle splitting and merging along with a novel sorting algorithm, the code achieves a 5x speed improvement in powder-based AM applications, enabling the simulation of multi-track LPBF processes within reasonable times without parallel computing.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Tianqi Yu, Xianbin Wang, Jianling Hu
Summary: A novel fast hierarchical topology update scheme is proposed for large-scale IoT systems enabled by edge-cloud collaborative architecture. The algorithm significantly reduces topology discovery latency and improves 3D localization accuracy through neighbor updates and a 3D localization algorithm.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2021)
Article
Mathematics, Interdisciplinary Applications
Xiaoxiao Du, Wei Wang, Gang Zhao, Jiaming Yang, Mayi Guo, Ran Zhang
Summary: This paper introduces a framework for solving two dimensional elastic problems on complex topology models using high-order virtual element methods, which involves embedding complex models into a rectangular domain and discretizing them into a structured grid, adaptive refinement using a quad-tree strategy, optimization to avoid tiny elements, and stress recovery schemes for post-processing. The method is thoroughly studied, showing alleviation of burden on meshing complex CAD geometries, accurate results compared with analytical solutions and FEM, and confirmation of convergence and accuracy through convergence studies.
COMPUTATIONAL MECHANICS
(2022)
Article
Chemistry, Analytical
Bowen Hu, Zhenghang Hao, Zhuo Chen, Jing Zhang
Summary: This paper introduces a method for updating and extending the prediction model of power system transient stability assessment based on a data-driven approach. By using the continual learning SCP algorithm, the model can be updated in real-time with limited resources while retaining the prediction ability for old scenarios.
Article
Computer Science, Interdisciplinary Applications
Son H. Nguyen, Dongwoo Sohn, Hyun-Gyu Kim
Summary: This paper presents a new computational strategy for stress-constrained shape and topology optimization using level-set-based trimmed meshes. The proposed hr-adaptive mesh refinement scheme greatly reduces the computational cost and achieves a clear and explicit representation of desired optimal designs with stress constraints.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Engineering, Multidisciplinary
Feng Guo, Tao Yang, Ahmed M. Diab, Seang Shen Yeoh, Serhiy Bozhko, Patrick Wheeler
Summary: The studied ESG system operates at high speed during its generation mode, presenting challenges for neutral-point voltage balance and CMV. The proposed modulation scheme achieves balanced capacitor voltage and reduced CMV by synthesizing new medium and small vectors. Simulation and experimental results confirm the effectiveness of the strategy in more-electric-aircraft applications.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2021)
Article
Chemistry, Multidisciplinary
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
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
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
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.
Article
Engineering, Mechanical
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
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
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
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
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
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
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
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
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
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
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
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)