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Fast implicit update schemes for Cahn–Hilliard-type gradient flow in the context of Fourier-spectral methods Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-17 A. Krischok, B. Yaraguntappa, M.-A. Keip
This work discusses a way of allowing fast implicit update schemes for the temporal discretization of phase-field models for gradient flow problems that employ Fourier-spectral methods for their spatial discretization. Through the repeated application of the Sherman–Morrison formula we provide a rule for approximations of the inverted tangent matrix of the corresponding Newton–Raphson method with a
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DHRDE: Dual-population hybrid update and RPR mechanism based differential evolutionary algorithm for engineering applications Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-16 Gang Hu, Changsheng Gong, Bin Shu, Zhiqi Xu, Guo Wei
In this paper, an enhanced differential evolution algorithm based on dual population hybrid update and random population replacement strategy (namely RPR mechanism) is proposed, which is called DHRDE. DHRDE algorithm involves three key improvements, first, the elite reverse population is constructed according to the original population before the update phase to uncover more potential areas to be searched
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Discontinuous Galerkin approximations of the heterodimer model for protein–protein interaction Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-14 Paola F. Antonietti, Francesca Bonizzoni, Mattia Corti, Agnese Dall’Olio
Mathematical models of protein–protein dynamics, such as the heterodimer model, play a crucial role in understanding many physical phenomena, e.g., the progression of some neurodegenerative diseases. This model is a system of two semilinear parabolic partial differential equations describing the evolution and mutual interaction of biological species. This article presents and analyzes a high-order
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A transfer learning physics-informed deep learning framework for modeling multiple solute dynamics in unsaturated soils Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-14 Hamza Kamil, Azzeddine Soulaïmani, Abdelaziz Beljadid
Modeling subsurface flow and transport phenomena is essential for addressing a wide range of challenges in engineering, hydrology, and ecology. The Richards equation is a cornerstone for simulating infiltration, and when coupled with advection–dispersion equations, it provides insights into solute transport. However, the complexity of this coupled model increases significantly when dealing with multiple
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Computationally-efficient locking-free isogeometric discretizations of geometrically nonlinear Kirchhoff–Love shells Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-13 Kyle Dakota Mathews, Hugo Casquero
Discretizations based on the Bubnov-Galerkin method and the isoparametric concept suffer from membrane locking when applied to Kirchhoff–Love shell formulations. Membrane locking causes not only smaller displacements than expected, but also large-amplitude spurious oscillations of the membrane forces. Continuous-assumed-strain (CAS) elements were originally introduced to remove membrane locking in
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A fully explicit isogeometric collocation formulation for the dynamics of geometrically exact beams Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-12 Giulio Ferri, Josef Kiendl, Alessandro Reali, Enzo Marino
We present a fully explicit dynamic formulation for geometrically exact shear-deformable beams. The starting point of this work is an existing isogeometric collocation (IGA-C) formulation which is explicit in the strict sense of the time integration algorithm, but still requires a system matrix inversion due to the use of a consistent mass matrix. Moreover, in that work, the efficiency was also limited
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A stabilization-free hybrid virtual element formulation for the accurate analysis of 2D elasto-plastic problems Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-12 F.S. Liguori, A. Madeo, S. Marfia, G. Garcea, E. Sacco
A plasticity formulation for the Hybrid Virtual Element Method (HVEM) is presented. The main features include the use of an energy norm for the VE projection, a high-order divergence-free interpolation for stresses and a piecewise constant interpolation for plastic multipliers within element subdomains. The HVEM does not require any stabilization term, unlike classical VEM formulations which are affected
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Deep material network for thermal conductivity problems: Application to woven composites Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-12 Dongil Shin, Peter Jefferson Creveling, Scott Alan Roberts, Rémi Dingreville
The thermal conductivity of materials dictates their functionality and reliability, especially for materials with complex microstructural topologies, such as woven composites. In this paper, we develop a physics-informed machine-learning architecture built specifically for solving thermal conductivity problems. Originally developed for mechanical problems, we extend and develop a deep material network
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Maximum energy dissipation-based incremental approach for structural analyses involving discrete fracture propagation in quasi-brittle materials Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-12 Saeed Mohammadzadeh Chianeh, Daniel Dias-da-Costa
A maximum energy dissipation-based incremental approach (MEDIA) is proposed to overcome limit points, e.g. strong snap-backs, in the fracture analysis of quasi-brittle materials. An optimisation step is applied using an expression proposed to compute the change of dissipated energy within the discretised body when moving from one state of equilibrium to another. This expression is developed at the
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Physics-informed discretization-independent deep compositional operator network Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-09 Weiheng Zhong, Hadi Meidani
Solving parametric Partial Differential Equations (PDEs) for a broad range of parameters is a critical challenge in scientific computing. To this end, neural operators, which predicts the PDE solution with variable PDE parameter inputs, have been successfully used. However, the training of neural operators typically demands large training datasets, the acquisition of which can be prohibitively expensive
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A critical review/look at “Optimal implicit single-step time integration methods with equivalence to the second-order-type linear multistep methods for structural dynamics: Accuracy analysis based on an analytical framework” Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-09 Kumar K. Tamma, Yazhou Wang, Dean Maxam
A critical look and review of the so-called generalized single-step time integration method by Zhang (, 418(2024), 116503) is proved and demonstrated to be not new, but identical to and within the existing GS4-II computational framework. The following are addressed: (1) Firstly, it is claimed that 16 parameters were introduced (somewhat misleading as evident in what follows) to obtain a more generalized
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Two and three dimensional [formula omitted]-conforming finite element approximations without [formula omitted]-elements Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-09 Mark Ainsworth, Charles Parker
We develop a method to compute -conforming finite element approximations in both two and three space dimensions using readily available finite element spaces. This is accomplished by deriving a novel, equivalent mixed variational formulation involving spaces with at most -smoothness, so that conforming discretizations require at most -continuity. The method is demonstrated on arbitrary order -splines
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SeAr PC: Sensitivity enhanced arbitrary Polynomial Chaos Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-08 Nick Pepper, Francesco Montomoli, Kyriakos Kantarakias
This paper presents a method for performing Uncertainty Quantification in high-dimensional uncertain spaces by combining arbitrary polynomial chaos with a recently proposed scheme for sensitivity enhancement (Kantarakias and Papadakis, 2023). Including available sensitivity information offers a way to mitigate the in Polynomial Chaos Expansions (PCEs). Coupling the sensitivity enhancement to arbitrary
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Interpretable physics-encoded finite element network to handle concentration features and multi-material heterogeneity in hyperelasticity Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-08 Xi Wang, Zhen-Yu Yin
Physics-informed neural networks (PINNs) have recently prevailed as differentiable solvers that unify forward and inverse analysis in the same formulation. However, PINNs have quite limited caliber when dealing with concentration features and discontinuous multi-material heterogeneity, hindering its application when labeled data is missing. We propose a novel physics-encoded finite element network
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Multistep asymptotic pre-training strategy based on PINNs for solving steep boundary singular perturbation problems Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-08 Fujun Cao, Fei Gao, Dongfang Yuan, Junmin Liu
The singularly perturbed problem is characterized by the presence of narrow boundary layers, which poses challenges for traditional numerical methods due to complexity and high costs. The contemporary deep learning physics-informed neural networks (PINNs) suffer from accuracy issues while learning initial conditions, fail to capture the sharp gradient behaviors, and provide inadequate approximations
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Conservative immersed-type algorithm with a Cartesian grid-based smoothed finite element method for the 2D fluid-structure interaction Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-07 S.H. Huo, Y. Hong, G. Wang, C. Jiang, G.R. Liu, Z.Q. Li
The Cartesian grid, which is highly popular in Computational Fluid Dynamics (CFD), has the characteristics of high mesh quality and easy generation. However, due to the limit of shape functions, the Cartesian grid with hanging nodes (CGHN) was rarely used in finite element method based CFD algorithm. Based on the framework of the immersed boundary method, a smoothed finite element method based on CGHN
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Topology optimization for hybrid additive-subtractive manufacturing incorporating dynamic process planning Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-07 Shuzhi Xu, Jikai Liu, Kentaro Yaji, Lin Lu
Hybrid additive–subtractive manufacturing (HASM) is a revolutionary technique that, the interplay between additive and subtractive processes within an integrated machine tool allows for the fabrication of traditionally challenging complex geometries with excellent quality. However, part design for hybrid manufacturing has mostly been done by experts with rare support from computational design algorithms
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A mean-strain estimate for plastic particles intended for distinct-particle simulations at high relative density Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-07 Göran Frenning
The kinematics of polydisperse granular materials comprised of overlapping spheres is carefully analysed. A single-particle strain estimate is developed that summaries the deformation experienced by each particle in terms of a mean deformation gradient. This strain estimate accounts for material displaced at interparticle contacts as well as a compensatory motion of the free particle surface. Forces
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Efficient AMG reduction-based preconditioners for structural mechanics Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-07 Àdel Alsalti-Baldellou, Andrea Franceschini, Gianluca Mazzucco, Carlo Janna
Structural problems play a critical role in many areas of science and engineering. Their efficient and accurate solution is essential for designing and optimising civil engineering, aerospace, and materials science applications, to name a few. When appropriately tuned, Algebraic Multigrid (AMG) methods exhibit a convergence that is independent of the problem size, making them the preferred option for
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Third medium finite element contact formulation for pneumatically actuated systems Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-06 Ondřej Faltus, Martin Horák, Martin Doškář, Ondřej Rokoš
Active mechanical metamaterials are artificially engineered microstructures that can be externally controlled to exhibit novel and switchable mechanical behavior on the macroscopic scale. Pneumatically actuated variants of these metamaterials can then change their mechanical, acoustic, or other types of effective behavior in response to applied pressure with possible applications ranging from soft
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FSGe: A fast and strongly-coupled 3D fluid–solid-growth interaction method Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-06 Martin R. Pfaller, Marcos Latorre, Erica L. Schwarz, Fannie M. Gerosa, Jason M. Szafron, Jay D. Humphrey, Alison L. Marsden
Equilibrated fluid–solid-growth (FSGe) is a fast, open source, three-dimensional (3D) computational platform for simulating interactions between instantaneous hemodynamics and long-term vessel wall adaptation through mechanobiologically equilibrated growth and remodeling (G&R). Such models can capture evolving geometry, composition, and material properties in health and disease and following clinical
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A high-order conservative cut finite element method for problems in time-dependent domains Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-06 Sebastian Myrbäck, Sara Zahedi
A mass-conservative high-order unfitted finite element method for convection–diffusion equations in evolving domains is proposed. The space–time method presented in [P. Hansbo, M. G. Larson, S. Zahedi, Comput. Methods Appl. Mech. Engrg. 307 (2016)] is extended to naturally achieve mass conservation by utilizing Reynolds’ transport theorem. Furthermore, by partitioning the time-dependent domain into
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A domain decomposition method employing displacement-only partitioned equations for quasi-static structural analysis Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-05 Seung-Hoon Kang, K.C. Park, José A. González, SangJoon Shin
The present study reports a family of iterative domain decomposition method for the static structural analysis, labeled as and its variants ( and ), all of which employ a recently developed Displacement-Only (DO) partitioned formulation (Park et al., 2023). The DO partitioned equation () consists of the applied force , the block-diagonal stiffness matrix () for each partition, the coupling projection
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A hyperreduced reduced basis element method for reduced-order modeling of component-based nonlinear systems Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-05 Mehran Ebrahimi, Masayuki Yano
We introduce a hyperreduced reduced basis element method for model reduction of parameterized, component-based systems in continuum mechanics governed by nonlinear partial differential equations. In the offline phase, the method constructs, through a component-wise empirical training, a library of archetype components defined by a component-wise reduced basis and hyperreduced quadrature rules with
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Neural Operator induced Gaussian Process framework for probabilistic solution of parametric partial differential equations Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-03 Sawan Kumar, Rajdip Nayek, Souvik Chakraborty
The study of neural operators has paved the way for the development of efficient approaches for solving partial differential equations (PDEs) compared with traditional methods. However, most of the existing neural operators lack the capability to provide uncertainty measures for their predictions, a crucial aspect, especially in data-driven scenarios with limited available data. In this work, we propose
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An entirely SPH-based FSI solver and numerical investigations on hydrodynamic characteristics of the flexible structure with an ultra-thin characteristic Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-03 Tingting Bao, Jun Hu, Sijie Wang, Can Huang, Yong Yu, Ahmad Shakibaeinia
The fluid-flexible-structure interaction (FFSI) is characterized by the large deformation, the thin structure, and the complex turbulent flow field. Accurately simulating FFSI poses three challenges, which are the modeling of the thin structure, the capture of moving interface, and the numerical stability of multi-physics field coupling, respectively. In this study, the FFSI is simulated by the entirely
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Optimal design of unimorph-type cantilevered piezoelectric energy harvesters using level set-based topology optimization by considering manufacturability Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-03 Ken Miyajima, Takayuki Yamada
In this study, we propose a design methodology for a piezoelectric energy-harvesting device optimized for maximal power generation at a designated frequency using topology optimization. The proposed methodology is adapted to the design of a unimorph-type piezoelectric energy harvester, wherein a piezoelectric film is affixed to a singular side of a silicon cantilever beam. Both the substrate and the
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Concurrent topology optimization of multiscale composites with differentiable microstructures Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-02 Jie Gao, Zepeng Wen, Xiaoya Zhai, Falai Chen, Hongmei Kang
To capitalize on the advantages of concurrent topology optimization while alleviating computational burdens, this paper introduces a novel design methodology termed (TVCTO) with differentiable microstructures. The filled differentiable microstructures represent a collection of parametrically controlled microstructures that are differentiable with respect to geometric and physical properties. This paper
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An isogemetric analysis formulation for the dynamics of geometrically exact viscoelastic beams and beam systems with arbitrarily curved initial geometry Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-02 Giulio Ferri, Enzo Marino
We present a novel formulation for the dynamics of geometrically exact Timoshenko beams and beam structures made of viscoelastic material featuring complex, arbitrarily curved initial geometries. An -consistent and second-order accurate time integration scheme for accelerations, velocities and rate-dependent viscoelastic strain measures is adopted. To achieve high efficiency and geometrical flexibility
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Modelling finite deformation and progressive failure of hyperelastic solid with implicit BA-NOSB-PD Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-02 Luyu Wang, Zhen-Yu Yin
Deformation and failure in hyperelastic materials exhibit unique characteristics that are absent in purely elastic materials. The presence of pre-existing cracks and holes further increases these complications. To study this phenomenon, an implicit hyperelastic non-ordinary state-based peridynamics (NOSB-PD) is developed for modelling finite deformation and damage under quasi-static conditions. Highlights
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EKF–SINDy: Empowering the extended Kalman filter with sparse identification of nonlinear dynamics Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-01 Luca Rosafalco, Paolo Conti, Andrea Manzoni, Stefano Mariani, Attilio Frangi
Measured data from a dynamical system can be assimilated into a predictive model by means of Kalman filters. Nonlinear extensions of the Kalman filter, such as the Extended Kalman Filter (EKF), are required to enable the joint estimation of (possibly nonlinear) system dynamics and of input parameters. To construct the evolution model used in the prediction phase of the EKF, we propose to rely on the
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Microstructure models for extreme material responses Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-01 M. Grigoriu
Numerical methods have to be used to solve most stochastic problems. Since these methods apply only to finite dimensional (FD) problems, i.e., problems involving finite sets of random variables, and stochastic problems are usually infinite dimensional, only FD versions of the posed problems can be solved numerically. FD versions result by representing the random functions in the definitions of posed
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A time-adaptive finite element phase-field model suitable for rate-independent fracture mechanics Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-01 Felix Rörentrop, Samira Boddin, Dorothee Knees, Jörn Mosler
The modeling of cracks is an important topic — both in engineering as well as in mathematics. Since crack propagation is characterized by a free boundary value problem (the geometry of the crack is not known beforehand, but part of the solution), approximations of the underlying sharp-interface problem based on phase-field models are often considered. Focusing on a rate-independent setting, these models
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Adaptive topology optimization for enhancing resistance to brittle fracture using the phase field model Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-01 Qi Zhang, Yang Liu, Nhon Nguyen-Thanh, Weidong Li, Shaofan Li, Kun Zhou
Computational cost is one of the challenges in the field of fracture resistance topology optimization. An efficient topology optimization approach is proposed for enhancing resistance to structural fracture based on the adaptive isogeometric–meshfree method. The mesh can be adaptively refined in the computational and design domains simultaneously to capture the fracture and structural boundary delicately
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Regularization in space–time topology optimization for additive manufacturing Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-01 Weiming Wang, Kai Wu, Fred van Keulen, Jun Wu
In additive manufacturing, the fabrication sequence has a large influence on the quality of manufactured components. While planning of the fabrication sequence is typically performed after the component has been designed, recent developments have demonstrated the possibility and benefits of simultaneous optimization of both the structural layout and the corresponding fabrication sequence. This is particularly
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High-order 3D virtual element method for linear and nonlinear elasticity Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-30 Bing-Bing Xu, Wei-Long Fan, Peter Wriggers
In this work, we develop a general high-order virtual element method for three-dimensional linear and nonlinear elastic problems. Applications of the virtual element method (VEM) in three-dimensional mechanics include linear elasticity problems, finite elastic strain problems, finite deformation plasticity problems, etc. But besides linear elastic problems, see e.g. Visinoni, 2024, the numerical schemes
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An approximate block factorization preconditioner for mixed-dimensional beam-solid interaction Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-30 Max Firmbach, Ivo Steinbrecher, Alexander Popp, Matthias Mayr
This paper presents a scalable approximate block factorization preconditioner for mixed-dimensional models in beam-solid interaction and their application in engineering. In particular, it studies the linear systems arising from a regularized mortar-type approach for embedding geometrically exact beams into solid continua. Due to the lack of block diagonal dominance of the arising 2 × 2 block system
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A novel neural-network non-ordinary state-based peridynamic method for large deformation and fracture analysis of hyperelastic membrane Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-30 Yang Yang, Yujie Chen, Yijun Liu
This paper presents a novel neural network non-ordinary state-based peridynamic (NOSB PD) algorithm for large deformation and fracture analysis of hyperelastic membranes. A non-local membrane theory has been developed by approximating the curved horizon of the membrane as a flat surface and applying the plane stress assumption locally. This allows the simulation of the membrane structure using a single
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MODNO: Multi-Operator learning with Distributed Neural Operators Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-30 Zecheng Zhang
The study of operator learning involves the utilization of neural networks to approximate operators. Traditionally, the focus has been on single-operator learning (SOL). However, recent advances have rapidly expanded this to include the approximation of multiple operators using foundation models equipped with millions or billions of trainable parameters, leading to the research of multi-operator learning
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DMT-OMPA: Innovative applications of an efficient adversarial Marine Predators Algorithm based on dynamic matrix transformation in engineering design optimization Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-29 Zhen Zhang, Shu-Chuan Chu, Trong-The Nguyen, Xiaopeng Wang, Jeng-Shyang Pan
This paper introduces an innovative variant of the Marine Predators Algorithm (MPA), termed the Dynamic Matrix Transformation-based Oppositional Marine Predators Algorithm (DMT-OMPA), aimed at enhancing the efficiency of engineering optimization strategies. Traditional MPAs have several shortcomings, including insufficient solution diversity and coverage in the initialization phase, a tendency to become
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The Shifted Boundary Method in Isogeometric Analysis Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-19 Nicolò Antonelli, Ricky Aristio, Andrea Gorgi, Rubén Zorrilla, Riccardo Rossi, Guglielmo Scovazzi, Roland Wüchner
This work presents a novel application of the Shifted Boundary Method (SBM) within the Isogeometric Analysis (IGA) framework, applying it to two-dimensional and three-dimensional Poisson problems with Dirichlet and Neumann boundary conditions. The SBM boundary condition imposition is achieved by means of a fully penalty-free formulation, eliminating the need for penalty calibration. The numerical experiments
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Highly efficient iterative method for multiple scattering with high order local ABC Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-19 Vianey Villamizar, Tahsin Khajah, Jonathan H. Hale
An iterative numerical method for time-harmonic acoustic multiple scattering from complexly shaped obstacles is devised. The classical formulation of multiple scattering problem is transformed into a set of single scattering boundary value problems (BVPs) coupled at their scatterer boundaries. By introducing iterative procedures, the single scattering BVPs are decoupled and a convenient domain truncation
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An asynchronous discontinuous Galerkin method for massively parallel PDE solvers Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-19 Shubham K. Goswami, Konduri Aditya
The discontinuous Galerkin (DG) method is widely being used to solve hyperbolic partial differential equations (PDEs) due to its ability to provide high-order accurate solutions in complex geometries, capture discontinuities, and exhibit high arithmetic intensity. However, the scalability of DG-based solvers is impeded by communication bottlenecks arising from the data movement and synchronization
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Operator inference driven data assimilation for high fidelity neutron transport Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-19 Wei Xiao, Xiaojing Liu, Jianhua Zu, Xiang Chai, Hui He, Tengfei Zhang
This paper presents a novel reduced-order model (ROM) based data assimilation framework for parametric high-fidelity time-dependent neutron transport equations (TNTE). The ROM is constructed utilizing affine-parametric operator inference, a scientific machine learning that learns operators of the subspace dynamical system through a non-intrusive data-driven approach. The affine-parametric structure
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Improving the joint quality in density-based multi-material topology optimization with minimum length scale control Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-19 Longlong Song, Tong Gao, Weihong Zhang
In this paper, we delve into the appearance of sharp ‘V’ features at joint areas in multi-material topology optimization, originating from independent minimum length scale control. To mitigate these undesirable features, three approaches have been studied: a hybrid strategy combining independent control with entire void control for parallel distributions, a fusion of independent control and entire
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Thermodynamics-informed super-resolution of scarce temporal dynamics data Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-19 Carlos Bermejo-Barbanoj, Beatriz Moya, Alberto Badías, Francisco Chinesta, Elías Cueto
We present a method to increase the resolution of measurements of a physical system and subsequently predict its time evolution using thermodynamics-aware neural networks. Our method uses adversarial autoencoders, which reduce the dimensionality of the full order model to a set of latent variables that are enforced to match a prior, for example a normal distribution. Adversarial autoencoders are seen
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Proper generalized decomposition in the context of minimum compliance topology optimization for problems with separable geometries Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-18 Tomas Pauwels, Geert Degrande, Mattias Schevenels
Many applications of density-based topology optimization require a very fine mesh, either to obtain high-resolution designs, or to resolve physics in sufficient detail. Solving the discretized state and adjoint equation in every iteration step then becomes computationally demanding, restricting the applicability of the method. Model Order Reduction (MOR) offers a solution for this computational burden
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Interpolation methods for orthotropic fourth-order fiber orientation tensors in context of virtual composites manufacturing Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-17 Johannes Mitsch, Constantin Krauß, Luise Kärger
The objective of this work is to develop and investigate interpolation methods for fourth-order fiber orientation tensors. The developed methods aim to minimize information loss during mapping in the virtual manufacturing process for fiber-reinforced composites. The strategy of decomposing features that describe tensor shape and orientation, followed by separate interpolation, has been found to be
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Dual-horizon peridynamics modeling of coupled chemo-mechanical-damage for interface oxidation-induced cracking in thermal barrier coatings Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-16 Yehui Bie, Huilong Ren, Tinh Quoc Bui, Erdogan Madenci, Timon Rabczuk, Yueguang Wei
The interface oxidation-induced cracking process in thermal barrier coatings (TBCs) is rather complex. It involves the material changes of chemical reactions, dynamic migration and diffusion of BC/TGO (bond coat/thermally grown oxide) interface, delamination of TC (top coat)/TGO and BC/TGO interfaces, multiple delamination cracks and their interactions within the TGO layer, etc. The complex process
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Physics-informed deep learning of rate-and-state fault friction Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-15 Cody Rucker, Brittany A. Erickson
Direct observations of earthquake nucleation and propagation are few and yet the next decade will likely see an unprecedented increase in indirect, surface observations that must be integrated into modeling efforts. Machine learning (ML) excels in the presence of large data and is an actively growing field in seismology. However, not all ML methods incorporate rigorous physics, and purely data-driven
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Exact enforcement of temporal continuity in sequential physics-informed neural networks Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-15 Pratanu Roy, Stephen T. Castonguay
The use of deep learning methods in scientific computing represents a potential paradigm shift in engineering problem solving. One of the most prominent developments is Physics-Informed Neural Networks (PINNs), in which neural networks are trained to satisfy partial differential equations (PDEs). While this method shows promise, the standard version has been shown to struggle in accurately predicting
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SECRET: Statistical Emulation for Computational Reverse Engineering and Translation with applications in healthcare Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-15 L. Mihaela Paun, Mitchel J. Colebank, Alyssa Taylor-LaPole, Mette S. Olufsen, William Ryan, Iain Murray, James M. Salter, Victor Applebaum, Michael Dunne, Jake Hollins, Louise Kimpton, Victoria Volodina, Xiaoyu Xiong, Dirk Husmeier
There have been impressive advances in the physical and mathematical modelling of complex physiological systems in the last few decades, with the potential to revolutionise personalised healthcare with patient-specific evidence-based diagnosis, risk assessment and treatment decision support using digital twins. However, practical progress and genuine clinical impact hinge on successful model calibration
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CNN-based prediction of microstructure-derived random property fields of composite materials Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-14 Panagiotis Gavallas, George Stefanou, Dimitrios Savvas, Cécile Mattrand, Jean-Marc Bourinet
The simulation of random spatial variation in the mechanical properties of composite materials using random fields derived from their microstructure can be computationally demanding, since it often requires numerical homogenization of a large number of stochastic volume elements (SVEs). These SVEs are usually extracted from an initial image of the composite microstructure by using a moving window technique
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Strength-based collaborative topology optimization for continuous fiber reinforced composites Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-14 Guixing Li, Yuan Chen, Qing Li
The diverse and complex failure modes of carbon fiber reinforced plastic (CFRP) composites impose a significant challenge on optimization of both structural topology and fiber path. This study aims to develop a novel strength-based collaborative optimization of topological layout and fiber path (namely SCOTF) for continuous fiber reinforced composite structures through a level set algorithm with a
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Asynchronous global–local non-invasive coupling for nonlinear monotone patches: Application to plasticity problems Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-14 Ahmed El Kerim, Pierre Gosselet, Frédéric Magoulès
This article presents the asynchronous global–local non-invasive coupling in the case of nonlinear monotone patches as encountered when inserting elastoplastic components in a global linear elastic model. The convergence of the method is theoretically established in a general framework using the paracontractions technique and illustrated in academic examples with a weak scalability study considering
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A deep learning‒genetic algorithm approach for aerodynamic inverse design via optimization of pressure distribution Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-13 Ahmad Shirvani, Mahdi Nili-Ahmadabadi, Man Yeong Ha
Conventional aerodynamic inverse design (AID) methods have major limitations in terms of optimality and actuality of target parameter distribution. In this research, the target pressure distribution (TPD) of the FX63–137 airfoil was manually corrected to enhance its lift-to-drag ratio from a design perspective, and the corresponding geometry was obtained by the elastic surface algorithm (ESA) inverse
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Versatile data-adaptive hyperelastic energy functions for soft materials Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-11 Simon Wiesheier, Miguel Angel Moreno-Mateos, Paul Steinmann
Applications of soft materials are customarily linked to complex deformation scenarios and material nonlinearities. In the bioengineering field, soft materials typically mimic the low stiffness of biological matter subjected to extreme deformations. Computational frameworks surge as a versatile tool to assist the design of functional applications. The constitutive model lies at the core of such frameworks
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Topology optimization of curved thick shells using level set method and non-conforming multi-patch isogeometric analysis Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-11 Fernando Hübner Scherer, Malek Zarroug, Hakim Naceur, Andrei Constantinescu
We present a novel framework for topological shape optimization of curved non-conforming multi-patch and trimmed thick-shells subjected to external loads. Our method integrates the level set method (LSM) with a diffuse interface, a Hadamard shape derivative, and multi-patch isogeometric analysis (IGA) into a gradient descent algorithm to systematically capture the evolution of the shape. This integration
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Linear numerical schemes for a [formula omitted]-tensor system for nematic liquid crystals Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-10 Justin Swain, Giordano Tierra
In this work, we present three linear numerical schemes to model nematic liquid crystals using the Landau-de Gennes -tensor theory. The first scheme is based on using a truncation procedure of the energy, which allows for an unconditionally energy stable first order accurate decoupled scheme. The second scheme uses a modified second order accurate optimal dissipation algorithm, which gives a second
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Topology optimization of continuum structures for buckling resistance using a floating projection method Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-07-10 Tao Xu, Xiaodong Huang, Xiaoshan Lin, Yi Min Xie
Buckling resistance is crucial in structural design. This study addresses challenges associated with enhancing buckling resistance through topology optimization, focusing on avoiding incorrect buckling analyses and reducing reliance on parameter tuning. To eliminate pseudo buckling modes in low-density elements, this research employs a linear material model and a stress relaxation function, demonstrating