Computer Methods in Applied Mechanics and Engineering最新文献

Can KAN CANs? Input-convex Kolmogorov-Arnold Networks (KANs) as hyperelastic constitutive artificial neural networks (CANs) KAN可以吗？作为超弹性本构人工神经网络（can）的输入-凸Kolmogorov-Arnold网络

IF 6.9 1区工程技术

Computer Methods in Applied Mechanics and Engineering Pub Date : 2025-05-29 DOI: 10.1016/j.cma.2025.118089

Prakash Thakolkaran , Yaqi Guo , Shivam Saini , Mathias Peirlinck , Benjamin Alheit , Siddhant Kumar

{"title":"Can KAN CANs? Input-convex Kolmogorov-Arnold Networks (KANs) as hyperelastic constitutive artificial neural networks (CANs)","authors":"Prakash Thakolkaran , Yaqi Guo , Shivam Saini , Mathias Peirlinck , Benjamin Alheit , Siddhant Kumar","doi":"10.1016/j.cma.2025.118089","DOIUrl":"10.1016/j.cma.2025.118089","url":null,"abstract":"<div><div>Traditional constitutive models rely on hand-crafted parametric forms with limited expressivity and generalizability, while neural network-based models can capture complex material behavior but often lack interpretability. To balance these trade-offs, we present monotonic Input-Convex Kolmogorov-Arnold Networks (ICKANs) for learning polyconvex hyperelastic constitutive laws. ICKANs leverage the Kolmogorov-Arnold representation, decomposing the model into compositions of trainable univariate spline-based activation functions for rich expressivity. We introduce trainable monotonic input-convex splines within the KAN architecture, ensuring physically admissible polyconvex models for isotropic compressible hyperelasticity. The resulting models are both compact and interpretable, enabling explicit extraction of analytical constitutive relationships through a monotonic input-convex symbolic regression technique. Through unsupervised training on full-field strain data and limited global force measurements, ICKANs accurately capture nonlinear stress–strain behavior across diverse strain states. Finite element simulations of unseen geometries with trained ICKAN hyperelastic constitutive models confirm the framework’s robustness and generalization capability.</div></div>","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"443 ","pages":"Article 118089"},"PeriodicalIF":6.9,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144166673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A nodal ghost method based on variational formulation and regular square grid for elliptic problems on arbitrary domains in two space dimensions 基于变分公式和正则方形网格的节点鬼影法求解二维任意域上的椭圆问题

IF 6.9 1区工程技术

Computer Methods in Applied Mechanics and Engineering Pub Date : 2025-05-29 DOI: 10.1016/j.cma.2025.118041

Clarissa Astuto , Daniele Boffi , Giovanni Russo , Umberto Zerbinati

引用次数: 0

Integrating discrete-variable anisotropic topology optimization with lamination parameter interpolation-based stiffness tailoring 离散变量各向异性拓扑优化与基于层合参数插值的刚度裁剪的集成

IF 6.9 1区工程技术

Computer Methods in Applied Mechanics and Engineering Pub Date : 2025-05-26 DOI: 10.1016/j.cma.2025.118077

Kai Sun , Gengdong Cheng , Gokhan Serhat

{"title":"Integrating discrete-variable anisotropic topology optimization with lamination parameter interpolation-based stiffness tailoring","authors":"Kai Sun , Gengdong Cheng , Gokhan Serhat","doi":"10.1016/j.cma.2025.118077","DOIUrl":"10.1016/j.cma.2025.118077","url":null,"abstract":"<div><div>This paper introduces a novel computational design framework for topology and fiber path optimization of variable stiffness laminated composites. Based on the finite element discretization of the design domain, the topology and material stiffness are represented using elemental densities and lamination parameters (LPs), respectively. The density distribution is optimized via the discrete-variable topology optimization to obtain a precise structural layout. The recently proposed Topological Derivative-based Sensitivity Analysis is extended to calculate discrete-variable sensitivities for anisotropic materials, where the formulation accuracy is verified by finite difference computations. Elemental stiffness properties are described through the LPs, which are used with discrete-variable topology optimization for the first time. Specifically, the lamination parameter interpolation method (LPIM) is employed to significantly reduce the number of design variables while ensuring smooth variation of fiber angles throughout the laminate. In addition, unlike the previous LPIM-based works involving only master points for LP interpolation, the concept of master lines is introduced to enlarge the design space for stiffness distribution. Elemental densities and LPs are iteratively optimized to avoid solving the mixed integer programming problem directly. The effectiveness of the developed methodology is demonstrated through various case studies where designs providing minimum compliance or maximum directed displacement at specific locations are determined. The results show that the proposed approach can efficiently provide optimal variable stiffness laminate designs with clear density distributions and manufacturable fiber paths.</div></div>","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"443 ","pages":"Article 118077"},"PeriodicalIF":6.9,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A partitioned Lagrangian finite element approach for the simulation of viscoelastic and elasto-viscoplastic free-surface flows 粘弹性和弹粘塑性自由表面流动模拟的分区拉格朗日有限元方法

IF 6.9 1区工程技术

Computer Methods in Applied Mechanics and Engineering Pub Date : 2025-05-26 DOI: 10.1016/j.cma.2025.118071

Giacomo Rizzieri, Liberato Ferrara, Massimiliano Cremonesi

{"title":"A partitioned Lagrangian finite element approach for the simulation of viscoelastic and elasto-viscoplastic free-surface flows","authors":"Giacomo Rizzieri, Liberato Ferrara, Massimiliano Cremonesi","doi":"10.1016/j.cma.2025.118071","DOIUrl":"10.1016/j.cma.2025.118071","url":null,"abstract":"<div><div>Many materials, such as clays, fresh concrete, and biological fluids, exhibit elasto-viscoplastic (EVP) behaviour, transitioning between solid and fluid states under varying stress conditions. Among EVP models, Saramito’s constitutive law stands out for its thermodynamic consistency, smooth solid-to-fluid transition, and ability to accurately represent diverse materials with only four easily determinable parameters. However, computational challenges have mainly confined its application to 2D or axisymmetric confined flows. This work presents an innovative partitioned Lagrangian FEM approach for the simulation of transient free-surface viscoelastic and EVP flows. The Lagrangian framework allows to naturally track free surfaces and simplifies the constitutive equation by eliminating the convective term. The solver decouples the Navier–Stokes equations (solved implicitly) from the EVP constitutive law (solved explicitly), employing an adaptive sub-stepping procedure. An advantageous splitting of the Cauchy stress tensor is used in combination with the Both Sides Diffusion (BSD) stabilization technique to prevent issues linked to the ellipticity loss in the momentum equation, also for low solvent-polymer viscosity ratios. The FEM solver has been integrated within the Particle Finite Element Method (PFEM), an updated Lagrangian formulation equipped with an efficient re-meshing scheme, to simulate free-surface flows, large deformations in soft solids, and topological changes of the domain. Benchmark tests in 2D and 3D, including gravity-induced spreading, impacting drops, and dam-break scenarios are used to validate the framework and highlight the versatility of Saramito’s model, which can also successfully reproduce a wide range of simpler sub-cases, including viscoelastic, viscoplastic, and EVP behaviours.</div></div>","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"443 ","pages":"Article 118071"},"PeriodicalIF":6.9,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FFT-based Galerkin and level-set methods for the homogenized evolution of domain nuclei in ferroelectrics 基于fft的伽辽金和水平集方法研究铁电体畴核的均匀演化

IF 6.9 1区工程技术

Computer Methods in Applied Mechanics and Engineering Pub Date : 2025-05-25 DOI: 10.1016/j.cma.2025.118078

Hsu-Cheng Cheng , Lu Trong Khiem Nguyen , Dennis M. Kochmann

引用次数: 0

Time series clustering adaptive enhanced method for time-dependent reliability analysis and design optimization 时变可靠性分析与设计优化的时间序列聚类自适应增强方法

IF 6.9 1区工程技术

Computer Methods in Applied Mechanics and Engineering Pub Date : 2025-05-24 DOI: 10.1016/j.cma.2025.118099

Dequan Zhang , Ying Zhao , Meide Yang , Chao Jiang , Xu Han , Qing Li

{"title":"Time series clustering adaptive enhanced method for time-dependent reliability analysis and design optimization","authors":"Dequan Zhang , Ying Zhao , Meide Yang , Chao Jiang , Xu Han , Qing Li","doi":"10.1016/j.cma.2025.118099","DOIUrl":"10.1016/j.cma.2025.118099","url":null,"abstract":"<div><div>Adaptive Kriging model has gained growing attention for its effectiveness in reducing the computational costs in time-dependent reliability analysis (TRA). However, the existing methods struggle to identify critical sample regions, leverage parallel computational resources, and assess the value for sample trajectories, thus restricting improvement in accuracy and efficiency. To address the challenges, this study proposes a time series clustering adaptive enhanced method (TSCM). TSCM first employs the time series clustering technique to partition the sample region efficiently. A novel time-dependent Kriging occurrence learning function is then introduced to account for both the uncertainty of sample trajectories and its influence on the approximated limit state boundary. Subsequently, an adaptive sampling strategy is developed to select training samples in parallel, guided by an uncertainty-based assessment of sample regions. After that, a time-dependent error-based stopping criterion is introduced to determine the training stage and terminate the update process. Finally, TSCM is extended to time-dependent reliability-based design optimization problems. Several numerical examples and an engineering case study demonstrate the superior computational efficiency and accuracy of the proposed method.</div></div>","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"443 ","pages":"Article 118099"},"PeriodicalIF":6.9,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144123991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Solving high-dimensional inverse problems using amortized likelihood-free inference with noisy and incomplete data 用有噪声和不完全数据的平摊无似然推理求解高维逆问题

IF 6.9 1区工程技术

Computer Methods in Applied Mechanics and Engineering Pub Date : 2025-05-24 DOI: 10.1016/j.cma.2025.118064

Jice Zeng , Yuanzhe Wang , Alexandre M. Tartakovsky , David A. Barajas-Solano

{"title":"Solving high-dimensional inverse problems using amortized likelihood-free inference with noisy and incomplete data","authors":"Jice Zeng , Yuanzhe Wang , Alexandre M. Tartakovsky , David A. Barajas-Solano","doi":"10.1016/j.cma.2025.118064","DOIUrl":"10.1016/j.cma.2025.118064","url":null,"abstract":"<div><div>We present a likelihood-free probabilistic inversion method based on normalizing flows for high-dimensional inverse problems. The proposed method is composed of two complementary networks: a summary network for data compression and an inference network for parameter estimation. The summary network encodes raw observations into a fixed-size vector of summary features, while the inference network generates samples of the approximate posterior distribution of the model parameters based on these summary features. The posterior samples are produced in a deep generative fashion by sampling from a latent Gaussian distribution and passing these samples through an invertible transformation. We construct this invertible transformation by sequentially alternating conditional invertible neural network and conditional neural spline flow layers. The summary and inference networks are trained simultaneously.</div><div>We apply the proposed method to an inversion problem in groundwater hydrology to estimate the posterior distribution of the log-conductivity field conditioned on spatially sparse time-series observations of the system’s hydraulic head responses. The conductivity field is represented with 706 degrees of freedom in the considered problem. Comparison with the likelihood-based iterative ensemble smoother PEST-IES method demonstrates that the proposed method accurately estimates the parameter posterior distribution and the observations’ predictive posterior distribution at a fraction of the inference time of PEST-IES.</div></div>","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"443 ","pages":"Article 118064"},"PeriodicalIF":6.9,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accurate shakedown analysis of 2D problems based on stabilization-free hybrid virtual elements 基于无稳定混合虚元的二维问题精确安定分析

IF 6.9 1区工程技术

Computer Methods in Applied Mechanics and Engineering Pub Date : 2025-05-23 DOI: 10.1016/j.cma.2025.118075

F.S. Liguori , A. Madeo , S. Marfia , E. Sacco , G. Garcea

{"title":"Accurate shakedown analysis of 2D problems based on stabilization-free hybrid virtual elements","authors":"F.S. Liguori , A. Madeo , S. Marfia , E. Sacco , G. Garcea","doi":"10.1016/j.cma.2025.118075","DOIUrl":"10.1016/j.cma.2025.118075","url":null,"abstract":"<div><div>Shakedown analyses require a precise evaluation of pointwise elastic stresses and, at the same time, an accurate representation of the elastoplastic solution for capturing the ratcheting mechanisms effectively. However, existing discretization methods often face a trade-off: techniques that optimize plasticity performance may compromise elastic accuracy, and vice versa. The Hybrid Virtual Element Method (HVEM), based on divergence-free assumed-stresses and polygonal element shapes, has recently proven accuracy in both linear elastic and incremental elastoplastic analyses. For this reason, this work introduces an HVEM-based formulation for shakedown analysis. The proposed approach is based on Melan’s static theorem, leveraging the equilibrated stress interpolation of HVEM. Its solution is obtained using a well-established method in which the shakedown multiplier is evaluated through a sequence of safe values, as commonly done in incremental elastoplasticity. The proposed approach is validated in a numerical testing campaign consisting in typical benchmark for shakedown analysis. The results highlight the enhanced computational efficiency of HVEM compared to traditional finite elements, and its high accuracy even with coarse mesh discretizations.</div></div>","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"443 ","pages":"Article 118075"},"PeriodicalIF":6.9,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144116416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extending the Lattice Boltzmann Method to non-linear elastodynamics 将点阵玻尔兹曼方法推广到非线性弹性动力学

IF 6.9 1区工程技术

Computer Methods in Applied Mechanics and Engineering Pub Date : 2025-05-23 DOI: 10.1016/j.cma.2025.118076

Henning Müller , Erik Faust , Alexander Schlüter , Ralf Müller

引用次数: 0

Reducing parameter tuning in topology optimization of flow problems using a Darcy and Forchheimer penalization 使用Darcy和Forchheimer惩罚减少拓扑优化中的参数调整

IF 6.9 1区工程技术

Computer Methods in Applied Mechanics and Engineering Pub Date : 2025-05-22 DOI: 10.1016/j.cma.2025.118027

M.J.B. Theulings , L. Noël , M. Langelaar , R. Maas

{"title":"Reducing parameter tuning in topology optimization of flow problems using a Darcy and Forchheimer penalization","authors":"M.J.B. Theulings , L. Noël , M. Langelaar , R. Maas","doi":"10.1016/j.cma.2025.118027","DOIUrl":"10.1016/j.cma.2025.118027","url":null,"abstract":"<div><div>In density-based topology optimization of flow problems, flow in the solid domain is generally inhibited using a penalization approach. Setting an appropriate maximum magnitude for the penalization traditionally requires manual tuning to find an acceptable compromise between flow solution accuracy and design convergence. In this work, three penalization approaches are examined, the Darcy (D), the Darcy with Forchheimer (DF), and the newly proposed Darcy with filtered Forchheimer (DFF) approach. Parameter tuning is reduced by analytically deriving an appropriate penalization magnitude for accuracy of the flow solution. The Forchheimer penalization is found to be required to reliably predict the accuracy of the flow solution. The state-of-the-art D and DF approaches are improved by developing the novel DFF approach, based on a spatial average of the velocity magnitude. In comparison, the parameter selection in the DFF approach is more reliable, as convergence of the flow solution and objective convexity are more predictable. Moreover, a continuation approach on the maximum penalization magnitude is derived by numerical inspection of the convexity of the pressure drop response. Using two-dimensional optimization benchmarks, the DFF approach reliably finds accurate flow solutions and is less prone to converge to inferior local optima.</div></div>","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":"443 ","pages":"Article 118027"},"PeriodicalIF":6.9,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144116417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0