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Related papers: Characterizing failure morphologies in fiber-reinf…

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We present a computational framework to explore the effect of microstructure and constituent properties upon the fracture toughness of fibre-reinforced polymer composites. To capture microscopic matrix cracking and fibre-matrix debonding,…

Applied Physics · Physics 2020-11-03 Wei Tan , Emilio Martínez-Pañeda

One of the key aspects governing the mechanical performance of composite materials is debonding: the local separation of reinforcing constituents from matrix when the interfacial strength is exceeded. In this contribution, two strategies to…

Materials Science · Physics 2009-08-12 P. Gruber , J. Zeman , J. Kruis , M. Sejnoha

This paper presents an accelerated spherical K-means clustering algorithm for large-scale and high-dimensional sparse document data sets. We design an algorithm working in an architecture-friendly manner (AFM), which is a procedure of…

Machine Learning · Statistics 2024-11-19 Kazuo Aoyama , Kazumi Saito

Honeycomb-like microstructures have been shown to exhibit local elastic buckling under compression, with three possible geometric buckling modes, or pattern transformations. The individual pattern transformations, and consequently also…

Soft Condensed Matter · Physics 2020-04-14 O. Rokoš , M. M. Ameen , R. H. J. Peerlings , M. G. D. Geers

The favored phase field method (PFM) has encountered challenges in the finite strain fracture modeling of nearly or truly incompressible hyperelastic materials. We identified that the underlying cause lies in the innate contradiction…

Numerical Analysis · Mathematics 2022-05-04 Fucheng Tian , Jun Zeng , Mengnan Zhang , Liangbin Li

The application of hybrid composites in lightweight engineering enables the combination of material-specific advantages of fiber-reinforced polymers and classical metals. The interface between the connected materials is of particular…

Applied Physics · Physics 2021-08-19 Franz Hirsch , Erik Natkowski , Markus Kästner

Clustered federated learning (CFL) is proposed to mitigate the performance deterioration stemming from data heterogeneity in federated learning (FL) by grouping similar clients for cluster-wise model training. However, current CFL methods…

Machine Learning · Computer Science 2024-04-01 Yuxin Zhang , Haoyu Chen , Zheng Lin , Zhe Chen , Jin Zhao

This study presents a novel integration of unsupervised learning and decision-making strategies for the advanced analysis of 4D-STEM datasets, with a focus on non-negative matrix factorization (NMF) as the primary clustering method. Our…

Machine Learning · Computer Science 2025-11-18 Junhao Cao , Nicolas Folastre , Gozde Oney , Edgar Rauch , Stavros Nicolopoulos , Partha Pratim Das , Arnaud Demortière

Federated Learning (FL) enables edge devices to collaboratively learn a global model, but it may not perform well when clients have high data heterogeneity. In this paper, we propose a dynamic clustering algorithm for personalized federated…

Machine Learning · Computer Science 2025-08-05 Heting Liu , Junzhe Huang , Fang He , Guohong Cao

Multi-material lightweight designs, e.g. the combination of aluminum with fiber-reinforced composites, are a key feature for the development of innovative and resource-efficient products. The connection properties of such bi-material…

Materials Science · Physics 2021-08-20 Franz Hirsch , Markus Kästner

The simulation of fracture using continuum ductile damage models attains a pathological discretization dependence caused by strain localization, after loss of ellipticity of the problem, in regions whose size is connected to the spatial…

Computational Engineering, Finance, and Science · Computer Science 2021-04-21 M. Magri , S. Lucarini , G. Lemoine , L. Adam , J. Segurado

A micromorphic computational homogenization framework has recently been developed to deal with materials showing long-range correlated interactions, i.e. displaying patterning modes. Typical examples of such materials are elastomeric…

Soft Condensed Matter · Physics 2024-06-21 S. Maraghechi , O. Rokoš , R. H. J. Peerlings , M. G. D. Geers , J. P. M. Hoefnagels

The goal of this paper is to develop a reliable analytical approach to finding the effective elastic-plastic response of metal matrix composites (MMC) and porous metals (PM) with a predefined particle or void distribution, as well as to…

Materials Science · Physics 2024-08-12 Kamil Bieniek , Michał Majewski , Paweł Hołobut , Katarzyna Kowalczyk-Gajewska

The computational analysis of fiber network fracture is an emerging field with application to paper, rubber-like materials, hydrogels, soft biological tissue, and composites. Fiber networks are often described as probabilistic structures of…

Numerical Analysis · Mathematics 2022-07-20 Vedad Tojaga , Artem Kulachenko , Soren Ostlund , T. Christian Gasser

Recently, deep matrix factorization has been established as a powerful model for unsupervised tasks, achieving promising results, especially for multi-view clustering. However, existing methods often lack effective feature selection…

Machine Learning · Statistics 2024-12-04 Yasser Khalafaoui , Basarab Matei , Martino Lovisetto , Nistor Grozavu

A new procedure for simultaneously finding the optimal cluster structure of multivariate functional objects and finding the subspace to represent the cluster structure is presented. The method is based on the $k$-means criterion for…

Methodology · Statistics 2014-02-11 Michio Yamamoto , Yoshikazu Terada

In traditional phase-field modeling of multiphase materials, a significant challenge arises from the non-local nature of fracture energy regularization, where interfacial toughness is inherently coupled with the properties of the…

Computational Physics · Physics 2026-04-14 Ye-Hang Qin , Ye Feng

This paper presents a combined numerical-theoretical study of the macroscopic behavior and local field distributions in a special class of two-dimensional periodic composites with viscoplastic phases. The emphasis is on strongly nonlinear…

Materials Science · Physics 2009-07-09 Martin I. Idiart , Francois Willot , Yves-Patrick Pellegrini , Pedro Ponte Castaneda

Efficient structural damage localization remains a challenge in structural health monitoring (SHM), particularly when the problem is coupled with uncertainty of conditions and complexity of structures. Traditional methods simply based on…

Optimization and Control · Mathematics 2025-09-29 Owais Saleem , Tim Suchan , Natalie Rauter , Kathrin Welker

A novel numerical approach to analyze the mechanical behavior within composite materials including the inelastic regime up to final failure is presented. Therefore, a second-gradient theory is combined with phase-field methods to fracture.…

Computational Engineering, Finance, and Science · Computer Science 2021-04-20 Maik Dittman , Jonathan Schult , Felix Schmidt , Christian Hesch