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We present a high-fidelity three dimensional computational framework for simulating the bulk mechanical behavior of granular aggregates composed of deformable brittle grains. Departing from classical discrete element methods (DEM), our…

Soft Condensed Matter · Physics 2025-07-16 Debdeep Bhattacharya , Davood Damircheli , Robert P. Lipton

We propose a novel variational phase-field model for fracture and fatigue in pseudoelastic shape memory alloys (SMAs). The model, developed in a one-dimensional setting, builds upon the Auricchio-Petrini constitutive formulation for SMAs…

Applied Physics · Physics 2026-05-28 Alma Brambilla , Laura De Lorenzis , Lorenza Petrini

Accurate prediction of fracture toughness under complex loading conditions, like mixed mode I/II, is essential for reliable failure assessment. This paper aims to develop a machine learning framework for predicting fracture toughness and…

Computational Physics · Physics 2025-03-04 Amir Mohammad Mirzaei

We propose a neural network-based computational framework for the simultaneous optimization of structural topology, curved layers, and path orientations to achieve strong anisotropic strength in fiber-reinforced thermoplastic composites…

Machine Learning · Computer Science 2025-05-08 Tao Liu , Tianyu Zhang , Yongxue Chen , Weiming Wang , Yu Jiang , Yuming Huang , Charlie C. L. Wang

In this article, we propose a data-driven methodology for combining the solutions of a set of competing turbulence models. The individual model predictions are linearly combined for providing an ensemble solution accompanied by estimates of…

Fluid Dynamics · Physics 2023-01-24 Maximilien de Zordo-Banliat , Grégory Dergham , Xavier Merle , Paola Cinnella

Uncertainties in a structure is inevitable, which generally lead to variation in dynamic response predictions. For a complex structure, brute force Monte Carlo simulation for response variation analysis is infeasible since one single run…

Machine Learning · Statistics 2020-05-08 Kai Zhou , Jiong Tang

FFT-based solvers are increasingly used by many researcher groups interested in modelling the mechanical behavior associated to a heterogeneous microstructure. A development is reported here that concerns the viscoelastic behavior of…

Classical Physics · Physics 2020-12-07 Stéphane André , Julien Boisse , Camille Noûs

This study evaluates four widely used fracture simulation methods, comparing their computational expenses and implementation complexities within the Finite Element (FE) framework when employed on heterogeneous solids. Fracture methods…

Computational Engineering, Finance, and Science · Computer Science 2024-11-19 Rasoul Najafi Koopas , Shahed Rezaei , Natalie Rauter , Richard Ostwald , Rolf Lammering

In this study, the reliability of identified risk factors associated with osteoporosis is investigated using a new clustering-based method on electronic medical records. This study proposes utilizing a new CLustering Iterations Framework…

Machine Learning · Computer Science 2024-05-28 Mikayla Calitis

Fatigue fracture is one of the main causes of failure in structures. However, the simulation of fatigue crack growth is computationally demanding due to the large number of load cycles involved. Metals in the low cycle fatigue range often…

Computational Physics · Physics 2024-11-11 Martha Kalina , Tom Schneider , Haim Waisman , Markus Kästner

The aim of this study was to check how efficient can be smoothed finite element method (FEM) for solution of the linear fracture mechanics problems. Accuracy of stress intensity factor (SIF) computation were investigated using three types…

Computational Engineering, Finance, and Science · Computer Science 2019-03-28 I. V. Rokach

Estimating the number of clusters (K) is a critical and often difficult task in cluster analysis. Many methods have been proposed to estimate K, including some top performers using resampling approach. When performing cluster analysis in…

Methodology · Statistics 2019-09-05 Yujia Li , Xiangrui Zeng , Chien-Wei Lin , George Tseng

Design and analysis of inelastic materials requires prediction of physical responses that evolve under loading. Numerical simulation of such behavior using finite element (FE) approaches can call for significant time and computational…

Materials Science · Physics 2025-07-08 Indrashish Saha , Ashwini Gupta , Lori Graham-Brady

Understanding the fracture mechanisms in composite materials across scales, from nano- to micro-scales, is essential for an in-depth understanding of the reinforcement mechanisms and designing the next generation of lightweight,…

Materials Science · Physics 2024-11-25 Qinghua Zhang , Navid Valizadeh , Mingpeng Liu , Xiaoying Zhuang , Bohayra Mortazavi

Exotic behaviour of mechanical metamaterials often relies on an internal transformation of the underlying microstructure triggered by its local instabilities, rearrangements, and rotations. Depending on the presence and magnitude of such a…

Soft Condensed Matter · Physics 2020-04-16 Ondřej Rokoš , Jan Zeman , Martin Doškář , Petr Krysl

This paper presents an inverted-file k-means clustering algorithm (IVF) suitable for a large-scale sparse data set with potentially numerous classes. Given such a data set, IVF efficiently works at high-speed and with low memory…

Machine Learning · Statistics 2020-02-24 Kazuo Aoyama , Kazumi Saito , Tetsuo Ikeda

The accurate and efficient prediction of crack propagation in dielectric materials is a critical challenge in structural health monitoring and the design of smart systems. This work presents a hybrid modeling framework that combines an…

Computational Physics · Physics 2026-02-03 Aamir Dean , Jaykumar Mavani , Betim Bahtiri , Behrouz Arash , Raimund Rolfes

We study the fatigue fracture of disordered materials by means of computer simulations of a discrete element model. We extend a two-dimensional fracture model to capture the microscopic mechanisms relevant for fatigue, and we simulate the…

Disordered Systems and Neural Networks · Physics 2009-11-11 H. A. Carmona , F. Kun , J. S. Andrade , H. J. Herrmann

We investigate compressive failure of heterogeneous materials on the basis of a continuous progressive damage model. The model explicitely accounts for tensile and shear local damage and reproduces the main features of compressive failure…

Materials Science · Physics 2012-05-03 Lucas Girard , Jerome Weiss , David Amitrano

We introduce in this paper a new way of optimizing the natural extension of the quantization error using in k-means clustering to dissimilarity data. The proposed method is based on hierarchical clustering analysis combined with multi-level…

Machine Learning · Statistics 2012-05-02 Brieuc Conan-Guez , Fabrice Rossi