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Mechanically consistent continuum damage model for anisotropic composites including damage deactivation Int. J. Damage Mech. (IF 4.0) Pub Date : 2025-02-10 Claudio Findeisen, Jörg Hohe
Due to crack bridging effects, ceramic matrix composites (CMCs) have outstanding properties that combine a quasi-ductile material behaviour with the high-temperature properties of ceramics. Combined with their high specific strength, this makes them perfectly suitable for high temperature safety relevant components. In view of the design process of CMC components elaborated continuum damage models
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Coupled semi-Lagrangian and poroelastic peridynamics for modeling hydraulic fracturing in porous media Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-07 Zirui Lu, Fan Zhu, Yosuke Higo, Jidong Zhao
A novel peridynamics-based computational approach is proposed for modeling hydraulic fracturing in porous media with consideration of leak-off effect. The approach features the use of the semi-Lagrangian peridynamics (PD) formulation which simulates fluid, and the poroelastic PD formulation which simulates deformation and fracture of porous solid with seepage flow. A new porous flow equation, which
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Study on shear fatigue damage behavior and evolution of Fe-Pb thin walled heterogeneous welded material components under hot isostatic pressure Int. J. Fatigue (IF 5.7) Pub Date : 2025-02-07 Siyuan Ding, Jianhua Liu, Jinfang Peng, Hechang Li, Bo Li, Minhao Zhu
For the first time, 45 steel and Pb were welded to form Fe-Pb thin-walled heterogeneous welding material components, which can be used in heavy-duty and radiation resistant environments. This study conducted comparative shear fatigue tests under different alternating loads under the conditions of hot isostatic pressing (HIP) control technology. The experimental results are as follows: after HIP treatment
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Isothermal and thermomechanical fatigue of 316H stainless steel: Damage mechanism and life prediction Int. J. Fatigue (IF 5.7) Pub Date : 2025-02-07 Jingyu Yang, Yiming Zheng, Fang Wang, Kang Wang, Xi Yuan, Xu Chen, Bingbing Li
In-phase and out-of-phase thermomechanical fatigue (TMF) tests with the temperature cycling from 300 °C to 650 °C were carried out on 316H stainless steel. The isothermal fatigue (IF) tests at 650 °C were performed for comparison. A wide range of strain amplitudes from 0.185 % to 1.0 % were used. Results showed that TMF loading resulted in the more pronounced cyclic hardening than IF loading, and the
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Damage evaluation of interfacial materials based on M-integral Int. J. Damage Mech. (IF 4.0) Pub Date : 2025-02-07 Jun Li, Xiaoman Feng, Junling Hou, Yaohua Liu, Binglei Wang
The paper investigates the issue of damage in interfacial materials using M-integral. It demonstrates that the integration path of M-integral can cross the material interface. The numerical calculation of M-integral is realized by using domain integral method. The accuracy of the model was verified using analytical solutions. The factors affecting the M-integral of the interfacial material are explored
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Topology optimization considering shielding and penetrating features based on fictitious physical model Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-06 Daiki Soma, Kota Sakai, Takayuki Yamada
This paper proposes topology optimization for considering shielding and penetrating features. Based on the fictitious physical model, which is a useful approach to control geometric features, the proposed method analyzes fictitious steady-state temperature fields and interprets target geometric features by examining the temperature change. First, the concept of topology optimization based on the level
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An extensible set of parent elements to facilitate the isoparametric concept for polygons at finite strains: A scaled boundary finite element approach Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-06 E.T. Ooi, B. Sauren, S. Natarajan, C. Song
We present a generalisation of the isoparametric concept to construct finite element interpolation functions on any star-convex polygonal parametric space. The approach is based on the solution to Laplace’s equation by employing the scaled boundary finite element method (SBFEM). We construct these interpolation functions for generic shapes of polygons, leading to a family of parent elements. By employing
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Microstructural origins of cycle hardening behaviors and fracture mechanisms of 304L stainless steel during low-cycle fatigue Int. J. Fatigue (IF 5.7) Pub Date : 2025-02-06 Wei Jiang, Shaojia Shi, Heng Wang, Kang Wei, Yonghao Zhao
Low-cycle fatigue behaviors of 304L stainless steel were investigated under different strain amplitudes (0.25 %, 0.3 %, 0.4 %, 0.5 %) and number of cycles to establish the relationship between macro-properties and micro-mechanisms. In all cases of strain amplitude, the 304L stainless steel displays a slight degree of cycle softening subsequent to the initial hardening in the cyclic stress–strain response
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The coupling effects of oxidation and temperature on the low cycle fatigue deformation behavior of CM 247 DS LC alloy Int. J. Fatigue (IF 5.7) Pub Date : 2025-02-06 S. Chandra, N. Paulose, R.K. Rai
The role of environmental degradation, particularly oxidation, on the low cycle fatigue response of rotating blades of aero-engine operating at significantly high temperatures is extremely important as it adversely affects its performance. The present work investigates the coupling effect of prior cyclic oxidation and temperature on the low cycle fatigue (LCF) fatigue behaviour of CM 247 DS LC Ni-based
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Improved Greedy Identification of latent dynamics with application to fluid flows Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-05 R. Ayoub, M. Oulghelou, P.J. Schmid
Model reduction is a key technology for large-scale physical systems in science and engineering, as it brings behavior expressed in many degrees of freedom to a more manageable size that subsequently allows control, optimization, and analysis with multi-query algorithms. We introduce an enhanced regression technique tailored to uncover quadratic parametric reduced-order dynamical systems from data
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Deep Ritz - Finite element methods: Neural network methods trained with finite elements Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-05 Georgios Grekas, Charalambos G. Makridakis
While much attention of neural network methods is devoted to high-dimensional PDE problems, in this work we consider methods designed to work for elliptic problems on domains Ω⊂Rd, d=1,2,3 in association with more standard finite elements. We suggest to connect finite elements and neural network approximations through training, i.e., using finite element spaces to compute the integrals appearing in
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MSFPSO: Multi-algorithm integrated particle swarm optimization with novel strategies for solving complex engineering design problems Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-05 Bin Shu, Gang Hu, Mao Cheng, Cunxia Zhang
Particle swarm optimization (PSO) is considered among the best seminal meta-heuristic algorithms,boasting merits of minimal parameter requirements, straightforward implementation, and highly accelerated convergence capacity, lower computational complexity, etc. Nevertheless, it also has drawbacks, for instance, it tends to converge prematurely at local optima, lack of diversity, and low accuracy. In
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On adaptive sampling techniques for metamodels based on NURBS entities from unstructured data Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-05 M. Zani, E. Panettieri, M. Montemurro
The paper investigates the influence of adaptive sampling strategies on the generation of a metamodel based on Non-Uniform Rational Basis Spline (NURBS) entities, obtained from unstructured data, with the purpose of improving accuracy while minimising computational resources. The metamodel is defined as solution of a constrained non-linear programming problem and it is solved through a three-step optimisation
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Continuum-kinematics-inspired peridynamics for transverse isotropy Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-05 A.M. de Villiers, J. Stadler, G. Limbert, A.T. McBride, A. Javili, P. Steinmann
Accounting for the combined effects of mechanical anisotropy and nonlocality is critical for capturing a wide range of material behaviour. Continuum-kinematics-inspired peridynamics (CPD) provides the essential underpinning theoretical and numerical framework to realise this objective. The formalism of rational mechanics is employed here to rigorously extend CPD to the important case of transverse
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A model learning framework for inferring the dynamics of transmission rate depending on exogenous variables for epidemic forecasts Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-04 Giovanni Ziarelli, Stefano Pagani, Nicola Parolini, Francesco Regazzoni, Marco Verani
In this work, we aim to formalize a novel scientific machine learning framework to reconstruct the hidden dynamics of the transmission rate, whose inaccurate extrapolation can significantly impair the quality of the epidemic forecasts, by incorporating the influence of exogenous variables (such as environmental conditions and strain-specific characteristics). We propose a hybrid model that blends a
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Parthenocissus tricuspidata tendril: A mechanically robust structural design with multiple functions J. Mech. Phys. Solids (IF 5.0) Pub Date : 2025-02-04 Jin-Hui Zhou, Lin Zhang, Sen-Zhen Zhan, Qiao Zhang, Yuxin Sun, Xi-Qiao Feng, Zi-Long Zhao
Through an array of spatially distributed tendril pads, Parthenocissus tricuspidata adheres itself firmly to the surfaces of targets such as trees and walls. The tendril pads, which form unique and intriguing layouts, play a critical role in supporting plant organs. However, the relationship between their geometric forms and mechanical properties remains inadequately understood. In this paper, we combine
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A stable second-order splitting method for incompressible Navier–Stokes equations using the scalar auxiliary variable approach Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-03 Anouar Obbadi, Mofdi El-Amrani, Mohammed Seaid, Driss Yakoubi
We propose a novel second-order fractional-step method for the numerical solution of incompressible Navier–Stokes equations. This fractional-step method consists of two splitting steps and it employs the second-order implicit backward differentiation formula for the time integration. Unlike most of the projection methods for solving incompressible Navier–Stokes equations, the proposed method is free
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Gaussian process regression + deep neural network autoencoder for probabilistic surrogate modeling in nonlinear mechanics of solids Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-03 Saurabh Deshpande, Hussein Rappel, Mark Hobbs, Stéphane P.A. Bordas, Jakub Lengiewicz
Many real-world applications demand accurate and fast predictions, as well as reliable uncertainty estimates. However, quantifying uncertainty on high-dimensional predictions is still a severely under-investigated problem, especially when input–output relationships are non-linear. To handle this problem, the present work introduces an innovative approach that combines autoencoder deep neural networks
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Variational Physics-informed Neural Operator (VINO) for solving partial differential equations Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-03 Mohammad Sadegh Eshaghi, Cosmin Anitescu, Manish Thombre, Yizheng Wang, Xiaoying Zhuang, Timon Rabczuk
Solving partial differential equations (PDEs) is a required step in the simulation of natural and engineering systems. The associated computational costs significantly increase when exploring various scenarios, such as changes in initial or boundary conditions or different input configurations. This study proposes the Variational Physics-Informed Neural Operator (VINO), a deep learning method designed
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Online multi-fidelity data aggregation via hierarchical neural network Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-02 Chunlong Hai, Jiazhen Wang, Shimin Guo, Weiqi Qian, Liquan Mei
In many industrial applications requiring computational modeling, the acquisition of high-fidelity data is often constrained by cost and technical limitations, while low-fidelity data, though cheaper and easier to obtain, lacks the same level of accuracy. Multi-fidelity data aggregation addresses this challenge by combining both types of data to construct surrogate models, balancing modeling accuracy
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A universal surrogate modeling method based on heterogeneous graph neural network for nonlinear analysis Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-01 Yongcheng Li, Changsheng Wang, Wenbin Hou
Nonlinear finite element analysis (FEA) is typically time-consuming, primarily due to its reliance on incremental solution schemes which require repeated stiffness matrix assembly and inversion at each step. In scenarios like structural optimization, where numerous FEA iterations are needed, deep learning-based surrogate models are usually employed as alternatives owing to their extremely high inference
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Multi-domain topology optimization of connectable lattice structures with tunable transition patterns Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-01 Peng Wei, Xinglong Chen, Hui Liu
The connectivity issue has always been a critical topic in multi-domain topology optimization of lattice structures. In this work, a novel multi-domain topology optimization approach is proposed, in which a set of transitional unit cells that follow a particular varying pattern is introduced between adjacent base microstructures to achieve optimized, multi-class, and well-connected multi-scale structures
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History-Matching of imbibition flow in fractured porous media Using Physics-Informed Neural Networks (PINNs) Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-01 Jassem Abbasi, Ben Moseley, Takeshi Kurotori, Ameya D. Jagtap, Anthony R. Kovscek, Aksel Hiorth, Pål Østebø Andersen
In this work, we propose a workflow based on physics-informed neural networks (PINNs) to model multiphase fluid flow in fractured porous media. After validating the workflow in forward and inverse modeling of a synthetic problem of flow in fractured porous media, we applied it to a real experimental dataset in which brine is injected at a constant pressure drop into a CO2 saturated naturally fractured
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Accelerating high-fidelity simulations of chemically reacting flows using reduced-order modeling with time-dependent bases Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-02-01 Ki Sung Jung, Cristian E. Lacey, Hessam Babaee, Jacqueline H. Chen
Direct numerical simulations (DNS) of chemically reacting flows are extraordinarily expensive due to the large number of partial differential equations representing the transport of chemical species and stringent resolution requirements imposed by turbulence and flame scales. The present study extends a novel on-the-fly reduced-order modeling strategy based on time-dependent bases and CUR factorization
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Equivalent initial damage sizes for PBF-LB Ti-6Al-4V notched geometries Int. J. Fatigue (IF 5.7) Pub Date : 2025-02-01 Zlatan Kapidžić, Stefan B. Lindström, Johan Moverare, Thomas Lindström, Carl-Johan Thore, Daniel Leidermark, Manja Franke
We propose a fracture mechanics based method for determination of equivalent initial damage size (EIDS) distribution in as-built additively manufactured (AM) Ti-6Al-4V notched geometries. The crack growth model is shown to correctly capture the effect of the stress raisers and load ratio on the fatigue life of notched specimens. Results of constant amplitude fatigue tests on notched round bar specimens
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Synergistic toughening mechanisms of macro- and micro-structures in nacre: Effects of T-stresses J. Mech. Phys. Solids (IF 5.0) Pub Date : 2025-02-01 Yi Yan, Xi-Qiao Feng
Through long-term evolution, biological tissues have optimized their components and structures at multiple length scales to meet the requirements of mechanical properties and biological functions. In this study, we explore how the shell macrostructure of nacre and its brick–mortar microstructure are synergistically designed to adapt to external mechanical conditions. We found that the T-stress effect
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The deformation mode transition of indented elastic thin shell induced by localized curvature imperfection J. Mech. Phys. Solids (IF 5.0) Pub Date : 2025-02-01 Chongxi Jiao, Xinming Qiu
Numerous studies have indicated that spherical thin shells exhibit imperfection sensitivity under external pressure or top-indentation, which can greatly impair their loading strength and stability. In this paper, a surprising shift in buckling behavior is achieved for elastic thin shell by locally manipulating the annular imperfection of curvature on a sphere, which reverses the harmfulness wrought
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Influence of micro-shot peening and traditional shot peening on fatigue performance and fracture behaviors of Ti-6Al-4V alloy Int. J. Fatigue (IF 5.7) Pub Date : 2025-01-31 Dongdong Ji, Haodong Chen, Jiwang Zhang, Kaixin Su, Xingyu Chen
Ti-6Al-4V alloy is subjected to complex environmental conditions, often requiring enhanced fatigue performance in engineering applications. This study provides a comparative analysis of the effects of micro-shot peening (MSP) and traditional shot peening (TSP) on the fatigue performance of Ti-6Al-4V alloy. The results indicate that TSP specimens develop a work-hardened layer with high hardness and
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Enhanced strength but deteriorated fatigue crack propagation behaviors of an aviation Al-Li alloy sheet caused by solid-solution time extension Int. J. Fatigue (IF 5.7) Pub Date : 2025-01-31 Xu-feng Cai, Hui Xiang, Zhen-zhen Liu, Guang-jun Zeng, Tian-le Liu, Zhi-min Cai, Hua Zhou, Bao Qi, Dan-Yang Liu, Jin-feng Li
The fatigue crack propagation (FCP) property and strength in T8-aged Al-Li alloy sheets with varying solid-solution time were investigated and the influence mechanism of the secondary phase on fatigue crack initiation was revealed. The results demonstrate that both grain dimension and recrystallization texture of the alloys with different solid-solution time are similar, but the average diameter of
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Effect of tempered sorbite/bainite microstructures on fatigue crack propagation and closure in Fe-Cr-Mo-Mn steel Int. J. Fatigue (IF 5.7) Pub Date : 2025-01-31 Ning Guo, Kuantao Sun, Bingtao Tang, Fu Guo, Guangchun Xiao, Jilai Wang
The large-scale wind power spindles are prone to fatigue failure under cyclic loading, particularly, due to microstructure inhomogeneity of tempered large-scale forgings, it is of great significance to explore the influence of non-uniform tempered sorbite/bainite (TS/B) on fatigue crack propagation and closure effects. In this paper, the fatigue crack propagation behavior of coarse TS/B and fine TS/B
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Electromechanical buckling of periodic patterns on stiff film bonded to a compliant substrate – Analytical and numerical postbuckling analyses J. Mech. Phys. Solids (IF 5.0) Pub Date : 2025-01-31 Samy Abu-Salih
In this work, the analytical and numerical analyses of the electromechanical buckling and postbuckling states of a planar film bonded to a compliant dielectric substrate are presented. The film is a stiff thin metal layer and forms an elastic electrode. The compliant substrate is attached to a bottom fixed and rigid electrode. The film is simultaneously subjected to in-plane compression stresses, which
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Magnetothermal dehydration induced deformation of hydrogel structures: Modelling and experiment J. Mech. Phys. Solids (IF 5.0) Pub Date : 2025-01-31 Jingda Tang, Huangsan Wei, Wenjie Zhang, Jiayi Lin, Chao Yuan, Tiejun Wang
Magnetic hydrogels have found broad applications in soft robotics and bioengineering, due to their facile actuation response and good biocompatibility. However, the actuation of magnetic hydrogels embedded with superparamagnetic nanoparticles remains challenging because of the low magnetization. In this work, we investigate the magnetothermal dehydration induced deformation of magnetic hydrogel-elastomer
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A chemo-thermo-mechanically coupled theory of photo-reacting polymers: Application to modeling photo-degradation with irradiation-driven heat transfer J. Mech. Phys. Solids (IF 5.0) Pub Date : 2025-01-31 Keven Alkhoury, Shawn A. Chester
Recent years have seen extensive research on advanced materials, including stimuli-responsive, renewable/degradable, multi-functional materials, and more, offering opportunities for advances in engineering technology. In general, these materials are expected to undergo chemical reactions during their service life. This work formulates a comprehensive thermodynamically consistent, frame-indifferent
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A NURBS-based level set method for the manufacturing-oriented thermal buckling optimization of curvilinear fiber composite panels with cut-outs Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-30 Haoqing Ding, Ruqi Sun, Haocheng Tian, Yutao Hu, Xin Zhang, Bin Xu
Laminate composite panels with arbitrary cut-outs in a thermal environment may suffer buckling failure because of thermal stress. To address this issue, a manufacturing-oriented thermal-buckling optimization model is proposed for the design of curvilinear fiber paths. Furthermore, instead of using the traditional finite element method (FEM) with high computational costs, a cut non-uniform rational
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A semi-implicit exactly fully well-balanced relaxation scheme for the Shallow Water Linearized Moment Equations Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-30 C. Caballero-Cárdenas, I. Gómez-Bueno, A. Del Grosso, J. Koellermeier, T. Morales de Luna
When dealing with shallow water simulations, the velocity profile is often assumed to be constant along the vertical axis. However, since in many applications this is not the case, modeling errors can be significant. Hence, in this work, we deal with the Shallow Water Linearized Moment Equations (SWLME), in which the velocity is no longer constant in the vertical direction, where a polynomial expansion
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Energy-based physics-informed neural network for frictionless contact problems under large deformation Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-30 Jinshuai Bai, Zhongya Lin, Yizheng Wang, Jiancong Wen, Yinghua Liu, Timon Rabczuk, YuanTong Gu, Xi-Qiao Feng
Numerical methods for contact mechanics are of great importance in engineering applications, enabling the prediction and analysis of complex surface interactions under various conditions. In this work, we propose an energy-based physics-informed neural network (PINN) framework for solving frictionless contact problems under large deformation. Inspired by microscopic Lennard-Jones potential, a surface
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Multiphysics simulation of crystal growth with moving boundaries in FEniCS Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-30 Arved Wintzer, Bilen Emek Abali, Kaspars Dadzis
Crystal growth processes and the Czochralski process in particular involves various physical phenomena such as heat transfer, phase change or liquid flows and requires a coupled multiphysical model for realistic numerical simulations. In this work, a new and extendable model is developed using the open-source software FEniCS. Basic equations for electromagnetic induction, heat conduction and radiation
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Interval Isogeometric Analysis for coping with geometric uncertainty Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-30 Nataly A. Manque, Jan Liedmann, Franz-Joseph Barthold, Marcos A. Valdebenito, Matthias G.R. Faes
Geometric uncertainty poses a significant challenge in many engineering sub-disciplines ranging from structural design to manufacturing processes, often attributed to the underlying manufacturing technology and operating conditions. When combined with geometric complexity, this phenomenon can result in substantial disparities between numerical predictions and the actual behavior of mechanical systems
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A coupled FEM-VEM approach for crack tracking in quasi-brittle materials Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-30 Antonino Spada, Marianna Puccia, Elio Sacco, Giuseppe Giambanco
The numerical simulation of crack propagation in quasi-brittle materials has historically been mainly faced by means of consolidated approaches in the framework of the finite element method (FEM). However, the very recently developed virtual element method (VEM) is a new promising technique whose strong point is the possibility to model polygonal meshes, characterized by any number of edges. This paper
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Generative reduced basis method Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-30 Ngoc Cuong Nguyen
We present a generative reduced basis (RB) approach for the rapid and reliable solution of parametrized linear partial differential equations. Central to this approach is the construction of generative RB spaces that provide rapidly convergent approximations of the solution manifold. We propose a generative snapshot method to generate significantly larger sets of snapshots from a small initial set
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Creep-fatigue behavior of a friction stir welding 7050-T7451 aluminum alloy: Microstructure evolution and microscopic damage mechanisms Int. J. Fatigue (IF 5.7) Pub Date : 2025-01-30 Huan Wang, Weifeng Xu, Yanfei Wang, Hongjian Lu
Creep-fatigue behavior of a friction stir welding (FSW) Al-Zn-Mg-Cu alloy at different temperatures was investigated. The results show that creep damage is much higher than fatigue damage when a holding time is introduced at the peak load. After creep-fatigue, η’ and η phases are reprecipitated in the weld nugget zone (WNZ) and coarsen with increasing temperature. When the creep-fatigue temperature
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Normal dynamic adhesion of an infinite elastomer layer on a statistically rough substrate J. Mech. Phys. Solids (IF 5.0) Pub Date : 2025-01-30 ZiJian Chen, Peng Zhang, Tao Wang, XiaoPing Wu, Zhong Zhang, Yang Zhao, Ping Gu
The dynamic adhesion properties under different pulling speeds on rough substrates have potential value in practical applications. Our primary objective is to ascertain the influence of the pulling speed on the normal stress required for delamination when an infinite elastomer layer delaminates from a statistically random rough rigid substrate. We decouple the interface delamination velocity from the
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Godunov loss functions for modelling of hyperbolic conservation laws Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-29 Rami Cassia, Rich Kerswell
Machine learning techniques are being used as an alternative to traditional numerical discretization methods for solving hyperbolic partial differential equations (PDEs) relevant to fluid flow. Whilst numerical methods are higher fidelity, they are computationally expensive. Machine learning methods on the other hand are lower fidelity but can provide significant speed-ups. The emergence of physics-informed
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Empirically corrected cluster cubature (E3C) Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-29 Stephan Wulfinghoff
In computational homogenization, the microscopic problem is regularly solved via Galerkin-projection methods to speed up the computation. By evaluating the involved integrals by hyper-reduction techniques, a very high efficiency can be achieved. Here, a novel hyper-reduction method is proposed and applied to magnetostatics. The method combines the ideas of microstructural clustering with the empirical
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MS-IUFFNO: Multi-scale implicit U-net enhanced factorized fourier neural operator for solving geometric PDEs Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-29 Shengjun Liu, Hanchao Liu, Ting Zhang, Xinru Liu
Geometric partial differential equations (geometric PDEs) are defined on manifolds in Riemannian space, specifically tailored for modeling the temporal evolution of surfaces in natural sciences and engineering. For varying initial surfaces (initial conditions), traditional numerical methods require re-solving the equation even for the same geometric PDE, which significantly hinders the efficiency of
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A snapshot-free reduced-order peridynamic model for accelerating fracture analysis of composites Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-28 Han Dong, Hongjiang Wang, Jiahao Zhong, Chaohui Huang, Weizhe Wang, Yingzheng Liu
A reduced-order peridynamic (PD) model is developed to accelerate fracture simulations of composite materials. This reduced-order PD model is constructed based on a set of projection basis functions extracted from the flexibility matrix corresponding to the initial configuration, rather than from snapshots. Thus, this approach eliminates dependence on datasets with prior knowledge, resulting in superior
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Facet cracking mechanism of Ti-2Al-2.5Zr alloy under high-cycle fatigue loadings at room temperature and 350°C Int. J. Fatigue (IF 5.7) Pub Date : 2025-01-28 Jingtai Yu, Bingbing Li, Zuoliang Ning, Xiang Guo, Jun Wu, Gang Chen
The interesting phenomenon of facet cracking of Ti-2Al-2.5Zr alloy exposed to high-cycle fatigue (HCF) loading at the high temperature of 350 °C was reported for the first time. Moreover, the HCF tests at room temperature were also conducted for comparison. The crack nucleation mechanisms with essential differences at both room and elevated temperatures were comparatively studied based on the elaborate
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Fatigue behaviors and cellular damages of bead-welded foam of poly(ether-b-amide) under cyclic compression Int. J. Fatigue (IF 5.7) Pub Date : 2025-01-28 Ping Zhu, Johannes Meuchelböck, Chao Qiu, Quanxiao Dong, Xia Dong, Dujin Wang, Volker Altstädt, Holger Ruckdäschel
Two polymer foams with density of 0.10 and 0.13 g/cm3 (F10 and F13) respectively were fabricated by steam-welding of expanded beads, obtained from super-critical foaming of poly(ether-b-amide). The compression fatigue behaviors were first characterized by step-increase strain tests up to −60 %, with an increment of 10 %. The stress relaxation rates during every one thousand cycles of compression was
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A theory of fatigue fracture in viscoelastic solids J. Mech. Phys. Solids (IF 5.0) Pub Date : 2025-01-28 Guillaume Lostec, Julien Caillard, Davide Colombo, Rong Long
Crack propagation in viscoelastic solids under cyclic loading is a fundamental problem underlying the fatigue fracture of elastomers. We present a continuum theory to determine the crack extension per loading cycle for various loading amplitudes, loading frequencies and viscoelastic properties. This is achieved by examining the energy dissipated through viscous effects and the energy available for
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Neural network solvers for parametrized elasticity problems that conserve linear and angular momentum Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-27 Wietse M. Boon, Nicola R. Franco, Alessio Fumagalli
We consider a mixed formulation of parametrized elasticity problems in terms of stress, displacement, and rotation. The latter two variables act as Lagrange multipliers to enforce the conservation of linear and angular momentum. The resulting system is computationally demanding to solve directly, especially if various instances of the model parameters need to be investigated. We therefore propose a
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A Least-Squares-Based Neural Network (LS-Net) for Solving Linear Parametric PDEs Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-27 Shima Baharlouei, Jamie M. Taylor, Carlos Uriarte, David Pardo
Developing efficient methods for solving parametric partial differential equations is crucial for addressing inverse problems. This work introduces a Least-Squares-based Neural Network (LS-Net) method for solving linear parametric PDEs. It utilizes a separated representation form for the parametric PDE solution via a deep neural network and a least-squares solver. In this approach, the output of the
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Unified Eulerian method for fluid-immersed self- and multi-body solid contact Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-27 Teo Lara, Ken Kamrin
We introduce a general simulation approach to model fluid-submerged solid contact of highly deformable objects within the Eulerian Incompressible Reference Map Technique (RMT) for fluid-solid interaction. Our approach allows solid bodies to undergo finite deformations, contact, and, importantly, self-contact while immersed in a fluid satisfying the Navier–Stokes equations. All solid boundaries are
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A generalized theory for physics-augmented neural networks in finite strain thermo-electro-mechanics Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-27 R. Ortigosa, J. Martínez-Frutos, A. Pérez-Escolar, I. Castañar, N. Ellmer, A.J. Gil
This manuscript introduces a novel neural network-based computational framework for constitutive modeling of thermo-electro-mechanically coupled materials at finite strains, with four key innovations: (i) It supports calibration of neural network models with various input forms, such as Ψnn(F,E0,θ), enn(F,D0,η), Υnn(F,E0,η), or Γnn(F,D0,θ), with F representing the deformation gradient tensor, E0 and
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A non-intrusive nonlinear structural ROM for partitioned two-way fluid–structure interaction computations Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-27 Riccardo Pellegrini, Zhaoyuan Wang, Frederick Stern, Matteo Diez
This paper introduces a nonlinear structural reduced order model (ROM) specifically developed for fluid–structure interaction (FSI) simulations involving high impact loads and large deflections, such as those arising in water slamming of flexible structures. The model is based on a nonlinear modal expansion trained offline using prestressed eigenfrequency analyses performed by nonlinear full-order
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Simultaneous and meshfree topology optimization with physics-informed Gaussian processes Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-27 Amin Yousefpour, Shirin Hosseinmardi, Carlos Mora, Ramin Bostanabad
Topology optimization (TO) provides a principled mathematical approach for optimizing the performance of a structure by designing its material spatial distribution in a pre-defined domain and subject to a set of constraints. The majority of existing TO approaches have (1) a nested nature, and (2) leverage numerical solvers for design evaluations during the optimization and hence rely on discretizing
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Damage analysis of CVI SiCf/SiCm ceramic matrix composites under thermal shock Int. J. Fatigue (IF 5.7) Pub Date : 2025-01-27 Xiaopeng Hu, Qing Liu, Liang Chen, Sai Liu, Jinwei Guo, Wang Zhu
The low density, high strength, and excellent high-temperature resistance of ceramic matrix composites (CMCs) determine their significant application value in the extreme environments of advanced aero-engines. In this paper, the thermal shock performance and internal damage evolution of CMCs materials are investigated by X-ray computed tomography (XCT), infrared thermal imaging and acoustic emission
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Influence of the eutectic interface on the fatigue behaviour of friction stir spot welds of aluminum with copper Int. J. Fatigue (IF 5.7) Pub Date : 2025-01-27 E. Tognoli, K. Schricker, E. Bassoli, J.P. Bergmann
The development of hybrid bonds between copper and aluminum is being pursued for reasons of cost, functionality, and weight, particularly in the field of electromobility, to achieve near net-zero emissions. Joining aluminum to copper is a challenge, as interfacial intermetallic compounds have a negative impact on the strength, ductility, and electrical properties of the joint. The development of brittle
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t-PiNet: A thermodynamics-informed hierarchical learning for discovering constitutive relations of geomaterials J. Mech. Phys. Solids (IF 5.0) Pub Date : 2025-01-27 Pin Zhang, Konstantinos Karapiperis, Oliver Weeger
More attention has been paid to integrating existing knowledge with data to understand the complex mechanical behaviour of geomaterials, but it incurs scepticism and criticism on its generalizability and robustness. Moreover, a common mistake in current data-driven modelling frameworks is that history internal state variables and stress are known upfront and taken as inputs, which violates reality
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Frequency-adaptive multi-scale deep neural networks Comput. Methods Appl. Mech. Eng. (IF 6.9) Pub Date : 2025-01-26 Jizu Huang, Rukang You, Tao Zhou
Multi-scale deep neural networks (MscaleDNNs) with downing-scaling mapping have demonstrated superiority over traditional DNNs in approximating target functions characterized by high frequency features. However, the performance of MscaleDNNs heavily depends on the parameters in the downing-scaling mapping, which limits their broader application. In this work, we establish a fitting error bound to explain
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Influence of sintering process on high temperature cyclic deformation behavior and fatigue creep damage mechanism of sintered silver Int. J. Fatigue (IF 5.7) Pub Date : 2025-01-26 Dao-Hang Li, Wen-Jing Xu, Tian-Yi Liu, Bowen Zhang, Yi Liu, Yun-Hui Mei
In this paper, the influence of sintering process on the high temperature cyclic deformation behavior and fatigue creep damage mechanism of sintered silver is revealed. Under cyclic shear loading at high temperatures, quasi cleavage fracture that symbolizes creep damage is induced in sintered silver, leading to a decrease in its fatigue life. With the increase of sintering temperature/time, the material