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Dynamic and modal analysis of nearly incompressible structures with stabilised displacement-volumetric strain formulations Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-13 Rubén Zorrilla, Riccardo Rossi, Ramon Codina
This paper presents a dynamic formulation for the simulation of nearly incompressible structures using a mixed finite element method with equal-order interpolation pairs. Specifically, the nodal unknowns are the displacement and the volumetric strain component, something that makes possible the reconstruction of the complete stain at the integration point level and thus enables the use of strain-driven
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Structural reliability analysis with parametric p-box uncertainties via a Bayesian updating BDRM Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-13 Jun Xu, Ting Zhang, Long Li, Quanfu Yu
The parametric probability-box model, often abbreviated as “p-box” is frequently used to characterize epistemic uncertainties. However, structural reliability analysis with p-box uncertainties can often be computationally intensive. This paper presents an efficient method to accurately compute the bounds of failure probabilities within this context. The method’s key innovation lies in its ability to
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Tailored Functionally Graded Materials design and concurrent topology optimization with implicit fields Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-13 Lingfeng Li, Qiong Pan, Xiaoya Zhai, Falai Chen
Tailored unctionally raded aterials (FGMs) offer the ability to design and engineer materials with specific properties at a changing volume fraction and are widely used in various fields such as aerospace, biomedical engineering, etc. The precise control of physical properties and the connectivity of microstructural sequences are two main challenges in multiscale problems. This paper constructs a novel
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Quantum computing and tensor networks for laminate design: A novel approach to stacking sequence retrieval Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-12 Arne Wulff, Boyang Chen, Matthew Steinberg, Yinglu Tang, Matthias Möller, Sebastian Feld
As with many tasks in engineering, structural design frequently involves navigating complex and computationally expensive problems. A prime example is the weight optimization of laminated composite materials, which to this day remains a formidable task, due to an exponentially large configuration space and non-linear constraints. The rapidly developing field of quantum computation may offer novel approaches
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Learning macroscopic equations of motion from dissipative particle dynamics simulations of fluids Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-12 Matevž Jug, Daniel Svenšek, Tilen Potisk, Matej Praprotnik
Macroscopic descriptions of both natural and engineered materials usually include a number of phenomenological parameters that have to be estimated from experiments or large-scale microscopic simulations. When dealing with advanced complex materials, these descriptions are sometimes not available or not even known. Using sparsity-promoting techniques one can extract macroscopic dynamic models directly
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Particle inverse method for full-field displacement and crack propagation monitoring from discrete sensor measurements Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-12 A. Kefal, M.H. Bilgin, A. Kendibilir
This study presents the Particle Inverse Method (PIM), a novel structural health monitoring technique for real-time, full-field monitoring of deformations and damages/cracks in structures using discrete sensor data. Towards this end, the PIM mathematically unifies the concepts of the inverse finite element method and peridynamics differential operator for the first time, thus creating a fully meshless
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Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-12 Govinda Anantha Padmanabha, Jan Niklas Fuhg, Cosmin Safta, Reese E. Jones, Nikolaos Bouklas
Most scientific machine learning (SciML) applications of neural networks involve hundreds to thousands of parameters, and hence, uncertainty quantification for such models is plagued by the curse of dimensionality. Using physical applications, we show that sparsification prior to Stein variational gradient descent (+SVGD) is a more robust and efficient means of uncertainty quantification, in terms
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Correlation structures of statistically isotropic stiffness and compliance TRFs through upscaling Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-12 Yaswanth Sai Jetti, Martin Ostoja-Starzewski
This paper reports a procedure to develop random fields of material properties on a mesoscale level, coarser than the microscale level of heterogeneous material microstructure. Since the anisotropy of properties at the mesoscale level is unavoidable, tensor-valued random fields (TRFs) need to be constructed. The construction satisfies three criteria: (i) the passage from the micro to mesoscale must
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Physics informed self-supervised segmentation of elastic composite materials Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-12 Guilherme Basso Della Mea, Cristian Ovalle, Lucien Laiarinandrasana, Etienne Decencière, Petr Dokládal
This work presents the application of Physics Informed Deep Learning models for both surrogate modelling and segmentation of composite materials. The segmentation is performed in a self-supervised manner, where, in the absence of ground truth images, the predicted stress field is used as the target of the deep learning model with a novel loss function. Our surrogate modelling approach prioritises model
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Numerical methods for shape optimal design of fluid–structure interaction problems Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-12 Johannes Haubner, Michael Ulbrich
We consider the method of mappings for performing shape optimization for unsteady fluid–structure interaction (FSI) problems. In this work, we focus on the numerical implementation. We model the optimization problem such that it takes several theoretical results into account, such as regularity requirements on the transformations and a differential geometrical point of view on the manifold of shapes
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A new mixed variational approach for Kirchhoff shells and [formula omitted] discretization with finite element exterior calculus Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-12 Jamun Kumar N., J.N. Reddy, Arun R. Srinivasa, Debasish Roy
We propose a geometrically-inspired mixed variational approach for nonlinear analysis of Kirchhoff shells based on Cartan’s moving frames. We use a two-parameter family of points (the mid-surface) and a two-parameter family of orthonormal frames (Cartan’s moving frames) introduced independently. Compatibility of the mid-surface vis-á-vis the frame field is enforced by appropriately constructing a functional
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An efficient phase-field framework for contact dynamics between deformable solids in fluid flow Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-12 Biswajeet Rath, Xiaoyu Mao, Rajeev K. Jaiman
Elastic contact in hydrodynamic environments is a complex multiphysics phenomenon and can be found in applications ranging from engineering to biological systems. Understanding the intricacies of this coupled problem requires the development of a generalized framework capable of handling topological changes and transitioning implicitly from fluid–structure interaction (FSI) conditions to solid–solid
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Viscous stress approximations in diffuse interface methods for two-phase flow based on mechanical jump conditions Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-12 Martin Reder, Andreas Prahs, Daniel Schneider, Britta Nestler
Diffuse interface approaches for multi-phase flow such as Hohenberg–Halperin type models require the approximation of material properties in the diffuse transition region. Different interpolation schemes achieving this are employed in literature. The present work focuses on such diffuse interface approximation of viscous stress. It is shown, that a viscosity interpolation based on the arithmetic mean
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Two Nitsche-based mixed finite element discretizations for the seepage problem in Richards’ equation Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-10 Federico Gatti, Andrea Bressan, Alessio Fumagalli, Domenico Gallipoli, Leonardo Maria Lalicata, Simone Pittaluga, Lorenzo Tamellini
This paper proposes two algorithms to impose seepage boundary conditions in the context of Richards’ equation for groundwater flows in unsaturated media. Seepage conditions are non-linear boundary conditions, that can be formulated as a set of unilateral constraints on both the pressure head and the water flux at the ground surface, together with a complementarity condition: these conditions in practice
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Mixed displacement–pressure formulations and suitable finite elements for multimaterial problems with compressible and incompressible models Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-10 Chennakesava Kadapa
Multimaterial problems in linear and nonlinear elasticity are some of the least explored using mixed finite element formulations with higher-order elements. The fundamental issue in adapting the mixed displacement–pressure formulations with linear and higher-order continuous elements for the pressure field is their inability to capture pressure and stress jumps across material interfaces. In this paper
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Enhancing topology optimization with colored body-fitted mesh using adaptive filter, dual re-meshing strategy, and OOP programming paradigm Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-10 Zicheng Zhuang, Tong Liu, Wei Tong, Fengming Xu, Yiwei Weng
This study introduces a novel topology optimization approach by employing power law-based material interpolation and adaptive filtering in the framework of the unstructured grids. As an extension of the established Solid Isotropic Material with Penalization (SIMP) method that utilizes the fixed structured mesh, the proposed Colored Body-Fitted Optimization (CBFO) method adopts the body-fitted grids
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Discrepancy-informed quadrature strategy for the nonlocal macro-meso-scale consistent damage model Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-10 Weifan Lv, Guangda Lu, Xiaozhou Xia, Xin Gu, Qing Zhang
The nonlocal macro-meso damage (NMMD) model has shown promising results in simulating the fracture process of materials. However, due to the inherent limitations of the nonlocal methods, its stability depends on whether the number of elements/nodes within the nonlocal region is sufficient. This paper proposes a discrepancy-informed quadrature strategy for NMMD to address its inherent limitations. Concretely
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Thermoelastic topology optimization for stiffened thin-walled structures under design-dependent thermal loading problems Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-08 Shili Xue, Xiangtao Ma, Dachuan Liu, ZeKai Huo, Peng Hao, Bo Wang
Due to their high specific strength and stiffness, stiffened thin-walled structures are extensively utilized in aerospace applications to maintain a high load-bearing capacity in a complex thermo-mechanical coupled environment. Thermal deformation significantly impacts the intake and exhaust performances, aerodynamic profiles, and even structural safety, hence how to design a reasonable stiffener layout
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Data-driven conditional probability to predict fatigue properties of multi-principal element alloys (MPEAs) Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-07 Halid Can Yıldırım, Peter K. Liaw
Traditional fatigue assessment methods for new and unexplored metallic alloys is challenging due to very limited experimental data. To address this, we formulate the assessment within a conditional probability framework, allowing us to capture the complexities of uncertainty in fatigue predictions. We employ advanced probabilistic methods to account for both inherent material variability and model
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On the automatic construction of interface coupling operators for non-matching meshes by optimization methods Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-07 Radim Dvořák, José A. González
We propose a novel optimization technique for the automatic construction of interface operators for coupling non-matching 3D meshes. The core of the method lies in the use of localized Lagrange multipliers and least-squares approximation to find the optimal location of additional interface nodes, allowing the problem to be solved without modifying the meshes of the coupled subdomains and passing the
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A scaled boundary finite element approach for elastoplastic analysis and implementation in ABAQUS Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-05 Yunxuan Cui, Shukai Ya, Chongmin Song
In this study, a revised formulation based on the uniform strain method (Flanagan and Belytschko, 1981) and the scaled boundary finite element method (SBFEM) — a numerical method with arbitrarily shaped polyhedral elements — is introduced for three-dimensional elastoplastic analysis. The proposed formulation uses the average strain of each polyhedral element. By employing the octree decomposition algorithm
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Probabilistic entropy and relative entropy for the effective characteristics of the fiber-reinforced composites with stochastic interface defects Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-05 Marcin Kamiński
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Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-04 Matthaios Chatzopoulos, Phaedon-Stelios Koutsourelakis
We propose Physics-Aware Neural Implicit Solvers (PANIS), a novel, data-driven framework for learning surrogates for parametrized Partial Differential Equations (PDEs). It consists of a probabilistic, learning objective in which weighted residuals are used to probe the PDE and provide a source of data i.e. the actual PDE never needs to be solved. This is combined with a physics-aware implicit solver
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A variational-based non-smooth contact dynamics approach for the seismic analysis of historical masonry structures Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-03 Nicola A. Nodargi, Paolo Bisegna
A variational formulation of the non-smooth contact dynamics method is proposed to address the dynamic response of historical masonry structures modeled as systems of 3D rigid blocks and subjected to ground excitation. Upon assuming a unilateral-frictional contact law between the blocks, the equations of motions are formulated in a time-discrete impulse theorem format in the unknown block velocities
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Attention-based multi-fidelity machine learning model for fractional flow reserve assessment Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-02 Haizhou Yang, Brahmajee K. Nallamothu, C. Alberto Figueroa, Krishna Garikipati
Coronary Artery Disease (CAD) is one of the most common forms of heart disease, caused by a buildup of atherosclerotic plaque in the coronary arteries. When this buildup is extensive, it can result in obstructions in the lumen of the blood vessels (known as stenosis) that lead to insufficient delivery of essential molecules like oxygen to the heart. Fractional Flow Reserve (FFR), defined as the ratio
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Time-variant reliability-based robust optimization for structures with material degradation Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-02 Meide Yang, Hongfei Zhang, Dequan Zhang, Xu Han, Qing Li
Time-variant reliability-based robust design optimization (TRBRDO) has achieved certain progress recently for its ability to ensure both robustness of design and feasibility of time-variant probabilistic constraints. However, the existing TRBRDO methods have not specifically addressed the dynamic uncertainty of material degradation, and there is lack of a universal and efficient approach for this class
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Design and optimization of functionally-graded triangular lattices for multiple loading conditions Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-02 Junpeng Wang, Rüdiger Westermann, Xifeng Gao, Jun Wu
Aligning lattice infills with the principal stress directions in loaded objects is crucial for improving stiffness. However, this principle only works for a single loading condition, where the stress field in 2D is described by two orthogonal principal stress directions. In this paper, we introduce a novel approach for designing and optimizing triangular lattice structures to accommodate multiple loading
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Designing brittle fracture-resistant structures:A tensile strain energy-minimized topology optimization Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-02 Wenke Qiu, Qifu Wang, Liang Xia, Zhaohui Xia
This research proposes a novel method for designing fracture-resistant structures. By analyzing the relationship between tensile strain energy and phase field brittle fracture, it has been found that minimizing tensile strain energy can delay fracture and enhance resistance. Capitalizing on this insight, a new topology optimization method is proposed. This method focuses on minimizing tensile strain
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Parallel isogeometric boundary element analysis with T-splines on CUDA Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-09-02 M.A. Peres, G. Sanches, A. Paiva, P. Pagliosa
We present a framework for parallel isogeometric boundary element analysis (BEA) of elastic solids on CUDA. To deal with traction discontinuities, we propose a BEA model that supports multiple nodes and semi-discontinuous elements. The multiplicity of a node is defined by the number of regions containing any element influenced by the node. A region is a group of connected elements delimited by a closed
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Concurrent topology optimization of sandwich structures with multi-configuration and variable-diameter lattice infill Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-31 Wei Ji, Yingchun Bai, Chao Jiang, Jianhua Liu, Qingdong Yan, Xu Han
The superior stiffness-to-weight and strength-to-weight mechanical advantages of sandwich structures can be fully exploited through concurrent design of entire topology, infill configuration and density, where the high-performance yet complicated structure can be fabricated through additive manufacturing. However, the emerging design challenges are concurrent design updating related to sandwich topology
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Hierarchical rank-one sequence convexification for the relaxation of variational problems with microstructures Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-31 M. Köhler, T. Neumeier, M.A. Peter, D. Peterseim, D. Balzani
This paper presents an efficient algorithm for the approximation of the rank-one convex hull in the context of nonlinear solid mechanics. It is based on hierarchical rank-one sequences and simultaneously provides first and second derivative information essential for the calculation of mechanical stresses and the computational minimisation of discretised energies. For materials, whose microstructure
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Free-Form Deformation as a non-invasive, discrete unfitted domain method: Application to the time-harmonic acoustic response of a saxophone Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-30 Marie Jeanneteau, Théo Sentagne, Paul Oumaziz, Robin Bouclier, Jean-Charles Passieux
The Finite Element method, widely used for solving Partial Differential Equations, may result in suboptimal computational costs when computing smooth fields within complex geometries. In such situations, IsoGeometric Analysis often offers improved per degree-of-freedom accuracy but building analysis-suitable representation of complex shapes is generally not obvious. This paper introduces a non-invasive
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Application of proper orthogonal decomposition to flow fields around various geometries and reduced-order modeling Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-30 Yuto Nakamura, Shintaro Sato, Naofumi Ohnishi
This study is focused on a reduced-order model (ROM) based on proper orthogonal decomposition (POD) for unsteady flow around a stationary object, which allows prediction with different object geometry as a parameter. The conventional POD method is applicable only to data with the same computational grid for all snapshots. This study proposed a novel POD methodology that performs on flow snapshots,
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Dynamical system prediction from sparse observations using deep neural networks with Voronoi tessellation and physics constraint Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-30 Hanyang Wang, Hao Zhou, Sibo Cheng
Despite the success of various methods in addressing the issue of spatial reconstruction of dynamical systems with sparse observations, spatio-temporal prediction for sparse fields remains a challenge. Existing Kriging-based frameworks for spatio-temporal sparse field prediction fail to meet the accuracy and inference time required for nonlinear dynamic prediction problems. In this paper, we introduce
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A mixed-dimensional formulation for the simulation of slender structures immersed in an incompressible flow Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-30 Fabien Lespagnol, Céline Grandmont, Paolo Zunino, Miguel A. Fernández
We consider the simulation of slender structures immersed in a three-dimensional (3D) flow. By exploiting the special geometric configuration of the slender structures, this particular problem can be modeled by mixed-dimensional coupled equations. Taking advantage of the slenderness of the structure and thus considering 3D/1D coupled problems raise several challenges and difficulties. From a mathematical
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Three-dimensional continuum point cloud method for large deformation and its verification Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-30 Peter M. Schaefferkoetter, Young-Cheol Yoon, Jeong-Hoon Song
This study presents a strong form based meshfree collocation method, which is named Continuum Point Cloud Method, to solve nonlinear field equations derived from classical mechanics for deformed bodies in three-dimensional Euclidean space. The method and its implementation are benchmarked against a nonlinear vector field using manufactured solutions. The analysis of mechanical fields firstly focuses
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Unsupervised machine learning classification for accelerating FE[formula omitted] multiscale fracture simulations Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-30 Souhail Chaouch, Julien Yvonnet
An approach is proposed to accelerate multiscale simulations of heterogeneous quasi-brittle materials exhibiting an anisotropic damage response. The present technique uses unsupervised machine learning classification based on k-means clustering to select integration points in the macro mesh within an FE strategy to track redundant micro nonlinear problems and to avoid unnecessary Representative Volume
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Peridynamics-fueled convolutional neural network for predicting mechanical constitutive behaviors of fiber reinforced composites Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-29 Binbin Yin, Jiasheng Huang, Weikang Sun
Despite advancements in predicting the constitutive relationships of composite materials, characterizing the effects of microstructural randomness on their mechanical behaviors remains challenging. In this study, we propose a data-driven convolutional neural network (CNN) to efficiently predict the stress-strain curves containing three key material features (Tensile strength, modulus, and toughness)
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Damage identification method based on interval regularization theory Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-29 Shuwei Qian, Qinghe Shi, Chen Yang, Zhenxian Luo, Liuyang Duan, Fengling Zhao
In the field of damage identification, traditional regularization methods neglect the impact of uncertainty factors on the selection of regularization parameters, leading to a decrease in the accuracy of damage identification. Therefore, this study proposes a damage identification based on interval truncated singular value decomposition (DI-ITSVD) method that considers the uncertainty in the selection
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A novel weight index-based uniform partition technique of multi-dimensional probability space for structural uncertainty quantification Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-28 Hanshu Chen, Yongxin Gao, Dixiong Yang, Zeng Meng, Zhuojia Fu
Accurately and efficiently achieving the uncertainty quantification of engineering structures is a challenging issue. The direct probability integral method (DPIM) provides an effective pathway to address this issue. However, the key partition technique via Voronoi cell of DPIM requires a prohibitive computational burden for multi-dimensional probability space. Moreover, due to the distributed nonuniformity
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Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-27 Ravi Patel, Cosmin Safta, Reese E. Jones
Composite materials with different microstructural material symmetries are common in engineering applications where grain structure, alloying and particle/fiber packing are optimized via controlled manufacturing. In fact these microstructural tunings can be done throughout a part to achieve functional gradation and optimization at a structural level. To predict the performance of particular microstructural
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Topology optimization with a finite strain nonlocal damage model using the continuous adjoint method Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-27 Jike Han, Kozo Furuta, Tsuguo Kondoh, Kazuhiro Izui, Shinji Nishiwaki, Kenjiro Terada
This study presents a unified formulation of topology optimization with a finite strain nonlocal damage model using the continuous adjoint method. For the primal problem to describe the material response including deterioration, we consider the standard Neo–Hookean constitutive model and incorporate crack phase-field theory for brittle fracture within the finite strain framework. For the optimization
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Greedy identification of latent dynamics from parametric flow data Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-27 M. Oulghelou, A. Ammar, R. Ayoub
Projection-based reduced-order models (ROMs) play a crucial role in simplifying the complex dynamics of fluid systems. Such models are achieved by projecting the Navier-Stokes equations onto a lower-dimensional subspace while preserving essential dynamics. However, this approach requires prior knowledge of the underlying high-fidelity model, limiting its effectiveness when applied to black-box data
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CMA-ES-based topology optimization accelerated by spectral level-set-boundary modeling Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-27 Shin Tanaka, Garuda Fujii
Topology optimization commonly encounters several challenges, such as ill-posedness, grayscale issues, interdependencies among design variables, , and . Furthermore, addressing the latter two concurrently presents considerable difficulty. In this study, we introduce a framework aimed at mitigating all the above obstacles . The objective is to achieve optimal configurations in a notably reduced timeframe
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An approximate decoupled reliability-based design optimization method for efficient design exploration of linear structures under random loads Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-27 Lili Weng, Cristóbal H. Acevedo, Jiashu Yang, Marcos A. Valdebenito, Matthias G.R. Faes, Jianbing Chen
Reliability-based design optimization (RBDO) provides a promising approach for achieving effective structural designs while explicitly accounting for the effects of uncertainty. However, the computational demands associated with RBDO, often due to its nested loop nature, pose significant challenges, thereby impeding the application of RBDO for decision-making in real-world structural design. To alleviate
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Mixed-mode thermo-mechanical fracture: An adaptive multi-patch isogeometric phase-field cohesive zone model Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-27 Zhanfei Si, Hirshikesh, Tiantang Yu, Weihua Fang, Sundararajan Natarajan
This work presents an adaptive phase-field cohesive zone model (PF-CZM) for simulating mixed-mode crack nucleation and growth in isotropic rock-like materials subjected to thermo-mechanical interactions. The proposed approach combines an adaptive multi-patch isogeometric analysis (MP-IGA) and length-scale insensitive PF-CZM. The formulation captures the distinct critical energy release rates for Mode-I
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A CAD-oriented parallel-computing design framework for shape and topology optimization of arbitrary structures using parametric level set Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-27 Jiawei Wu, Jiayi Zhu, Jie Gao, Liang Gao, Hui Liu
Recently, the high-resolution topology optimization to promote engineering applicability has gained much more attentions. However, an accurate and highly-efficient design framework for implementing shape and topology optimization of engineering structures with integration of CAD model is still in demand. In the current work, the critical intention is to develop a CAD-oriented parallel-computing design
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A phase-field gradient-based energy split for the modeling of brittle fracture under load reversal Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-26 A.R. Ferreira, A. Marengo, U. Perego
In the phase-field modeling of fracture, the search for a physically reasonable and computationally feasible criterion to split the elastic energy density into fractions that may or may not contribute to crack propagation has been the subject of many recent studies. Within this context, we propose an energy split – or energy decomposition – aimed at accurately representing the evolution of a crack
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An optimally convergent Fictitious Domain method for interface problems Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-26 Francesco Regazzoni
We introduce a novel Fictitious Domain (FD) unfitted method for interface problems associated with a second-order elliptic linear differential operator, that achieves optimal convergence without the need for adaptive mesh refinements nor enrichments of the Finite Element spaces. The key aspect of the proposed method is that it extends the solution into the fictitious domain in a way that ensures high
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Heteroscedastic Gaussian Process Regression for material structure–property relationship modeling Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-26 Ozge Ozbayram, Audrey Olivier, Lori Graham-Brady
Uncertainty quantification is a critical aspect of machine learning models for material property predictions. Gaussian Process Regression (GPR) is a popular technique for capturing uncertainties, but most existing models assume homoscedastic aleatoric uncertainty (noise), which may not adequately represent the heteroscedastic behavior observed in real-world datasets. Heteroscedasticity arises from
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Stochastic symplectic reduced-order modeling for model-form uncertainty quantification in molecular dynamics simulations in various statistical ensembles Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-26 S. Kounouho, R. Dingreville, J. Guilleminot
This work focuses on the representation of model-form uncertainties in molecular dynamics simulations in various statistical ensembles. In prior contributions, the modeling of such uncertainties was formalized and applied to quantify the impact of, and the error generated by, pair-potential selection in the microcanonical ensemble (NVE). In this work, we extend this formulation and present a linear-subspace
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Shape optimization of non-matching isogeometric shells with moving intersections Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-26 Han Zhao, John T. Hwang, Jiun-Shyan Chen
While shape optimization using isogeometric shells exhibits appealing features by integrating design geometries and analysis models, challenges arise when addressing computer-aided design (CAD) geometries comprised of multiple non-uniform rational B-splines (NURBS) patches, which are common in practice. The intractability stems from surface intersections within these CAD models. In this paper, we develop
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Physics-constrained polynomial chaos expansion for scientific machine learning and uncertainty quantification Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-26 Himanshu Sharma, Lukáš Novák, Michael Shields
We present a novel physics-constrained polynomial chaos expansion as a surrogate modeling method capable of performing both scientific machine learning (SciML) and uncertainty quantification (UQ) tasks. The proposed method possesses a unique capability: it seamlessly integrates SciML into UQ and vice versa, which allows it to quantify the uncertainties in SciML tasks effectively and leverage SciML
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Variational consistent one-point integration with Taylor's expansion-based stabilization in the second-order meshfree Galerkin method for strain gradient elasticity Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-26 BingBing Wang, RuoYu Wang, Chunsheng Lu, MingHao Zhao, JianWei Zhang
A generalized variational principle with five independent variables is proposed for strain gradient elasticity, including displacement, strain, strain gradient, stress, and double stress. Based on the principle, a one-point integration scheme is designed for the second order meshfree Galerkin method through nodal smoothed derivatives and their high order derivatives by Taylor's expansion. Since the
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A machine-learning enabled digital-twin framework for next generation precision agriculture and forestry Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-26 T.I. Zohdi
This work utilizes the modern synergy between flexible, rapid, simulations and quick assimilation of data in order to develop next-generation tools for precise biomass management of large-scale agricultural and forestry systems. Additionally, when integrated with satellite and drone-based digital elevation technologies, the results lead to digital replicas of physical systems, or so-called digital-twins
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Incorporating interface effects into multi-material topology optimization by improving interface configuration: An energy-based approach Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-24 Yi Wu
Interfaces between structural multi-materials generally exhibit asymmetric resistance to tension and compression. Given this interface behavior, this work suggests an energy-based approach to improve the interface configuration for multi-material topology optimization. Based on the strain spectral decomposition, we decompose the structural elastic strain energy into tensile and compressive portions
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Discontinuous Galerkin schemes for hyperbolic systems in non-conservative variables: Quasi-conservative formulation with subcell finite volume corrections Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-24 Elena Gaburro, Walter Boscheri, Simone Chiocchetti, Mario Ricchiuto
We present a novel quasi-conservative arbitrary high order accurate ADER (Arbitrary-Derivative) discontinuous Galerkin method allowing to efficiently use a non-conservative form of the considered partial differential system, so that the governing equations can be solved directly in the most physically relevant set of variables. This is particularly interesting for multi-material flows with moving interfaces
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A conforming frictional beam contact model Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-23 Konstantinos Karapiperis, Adrian Widmer, Elias Pescialli, Dennis M. Kochmann
We develop a model for predicting the mechanical behavior of a system of slender one-dimensional bodies (fibers or beams) interacting via frictional contact. Relying on an integral penalty-based formulation, it can robustly capture the behavior in the case of conforming contact occurring over regions of finite size. Two formulations of the model are presented and validated against fully resolved continuum
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A formulation for fluid–structure interaction problems with immersed flexible solids: Application to splitters subjected to flow past cylinders with different cross-sections Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-23 Marcela Cruchaga, Pablo Ancamil, Diego Celentano
In the finite element method framework, a fluid–structure formulation is developed by coupling an Eulerian fixed-mesh fluid approach with a Lagrangian deforming-mesh description for a flexible solid. The coupled formulation is solved using a staggered scheme during time. For the fluid solution stage, the solid walls are considered as a time-variable internal boundary. The velocity and pressure fields
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Model order reduction of time-domain acoustic finite element simulations with perfectly matched layers Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2024-08-23 Yinshan Cai, Sjoerd van Ophem, Shaoqi Wu, Wim Desmet, Elke Deckers
This paper presents a stability-preserving model reduction method for an acoustic finite element model with perfectly matched layers (PMLs). PMLs are often introduced into an unbounded domain to simulate the Sommerfeld radiation condition. These layers act as anisotropic damping materials to absorb the scattered field, of which the material properties are frequency- and coordinate-dependent. The corresponding