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Related papers: Accelerating High-Strain Continuum-Scale Brittle F…

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The availability of precise and accurate simulation is a limiting factor for interpreting and forecasting data in many fields of science and engineering. Often, one or more distinct simulation software applications are developed, each with…

High Energy Physics - Experiment · Physics 2025-02-19 Moritz Wolf , Lars O. Stietz , Patrick L. S. Connor , Peter Schleper , Samuel Bein

A mathematical continuum limit of the interaction energy of a random particle chain is shown to yield new insight into the effect of microscopic heterogeneities on macroscopic fracture laws in brittle materials. We derive a formula which…

Analysis of PDEs · Mathematics 2021-04-20 Laura Lauerbach , Anja Schlömerkemper

The rigorous convergence analysis of adaptive finite element methods for regularized variational models of quasi-static brittle fracture in strain-limiting elastic solids is presented. This work introduces two novel adaptive mesh refinement…

Numerical Analysis · Mathematics 2025-11-19 Ram Manohar , S. M. Mallikarjunaiah

To deploy the airframe digital twin or to conduct probabilistic evaluations of the remaining life of a structural component, a (near) real-time crack-growth simulation method is critical. In this paper, a reduced-order simulation approach…

Applied Physics · Physics 2022-11-14 Xuan Zhou , Shuangxin He , Leiting Dong , Satya N. Atluri

Plasticity, or the ability of an agent to adapt to new tasks, environments, or distributions, is crucial for continual learning. In this paper, we study the loss of plasticity in deep continual RL from the lens of churn: network output…

Machine Learning · Computer Science 2025-06-03 Hongyao Tang , Johan Obando-Ceron , Pablo Samuel Castro , Aaron Courville , Glen Berseth

An image-based deep learning framework is developed in this paper to predict damage and failure in microstructure-dependent composite materials. The work is motivated by the complexity and computational cost of high-fidelity simulations of…

Machine Learning · Computer Science 2022-06-07 Reza Sepasdar , Anuj Karpatne , Maryam Shakiba

The deformation of brittle material is primarily accompanied by micro-cracking and faulting. However, it has often been found that continuum fluid models, usually based on a non-Newtonian viscosity, are applicable. To explain this rheology,…

Materials Science · Physics 2016-12-28 K. Z. Nanjo

Spatial and temporal features are studied with respect to their predictive value for failure time prediction in subcritical failure with machine learning (ML). Data are generated from simulations of a novel, brittle random fuse model (RFM),…

Materials Science · Physics 2022-08-16 Stefan Hiemer , Paolo Moretti , Stefano Zapperi , Michael Zaiser

Phase-field modeling is an elegant and versatile computation tool to predict microstructure evolution in materials in the mesoscale regime. However, these simulations require rigorous numerical solutions of differential equations, which are…

Materials Science · Physics 2023-08-08 Owais Ahmad , Naveen Kumar , Rajdip Mukherjee , Somnath Bhowmick

This paper describes a two-dimensional (2D) finite element simulation for fracture and fatigue behaviours of pure alumina microstructures such as those found at hip prostheses. Finite element models are developed using actual Al2O3…

Medical Physics · Physics 2012-04-03 Kyungmok Kim , Bernard Forest , Jean Géringer

The present work provides an analytic solution for the stiffness to crack length relation in microscopic cantilever shaped fracture specimens based on classical beam theory and substitution of the crack by a virtual rotational spring…

Applied Physics · Physics 2020-09-14 Markus Alfreider , Stefan Kolitsch , Stefan Wurster , Daniel Kiener

Motivated by the inadequacy of conducting atomistic simulations of crack propagation using static boundary conditions that do not reflect the movement of the crack tip, we extend Sinclair's flexible boundary condition algorithm [Philos.…

Computational Physics · Physics 2021-03-10 Maciej Buze , James R. Kermode

The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance…

Morphing materials allow us to create new modalities of interaction and fabrication by leveraging dynamic behaviors of materials. Yet, despite the ongoing rapid growth of computational tools within this realm, current developments are…

Human-Computer Interaction · Computer Science 2020-07-31 Humphrey Yang , Kuanren Qian , Haolin Liu , Yuxuan Yu , Jianzhe Gu , Matthew McGehee , Yongjie Jessica Zhang , Lining Yao

Machine learning techniques are powerful tools for construction of emulators for complex systems. We explore different machine learning methods and conceptual methodologies, ranging from functional approximations to dynamical…

Dynamical Systems · Mathematics 2021-01-01 Hannah Lu , Dinara Ermakova , Haruko Murakami Wainwright , Liange Zheng , Daniel M. Tartakovsky

Machine learning (ML) has emerged as a powerful tool for accelerating the computational design and production of materials. In materials science, ML has primarily supported large-scale discovery of novel compounds using first-principles…

Using a two dimensional lattice model we investigate the crack growth under the influence of remote tensile forces as well as due to an internally applied pressure (hydraulic fracturing). For homogeneous elastic properties we present…

Condensed Matter · Physics 2008-12-18 Frank Tzschichholz

Bone adapts in response to its mechanical environment. This evolution of bone density is one of the most important mechanisms for developing fracture resistance. A finite element framework for simulating bone adaptation, commonly called…

Computational Engineering, Finance, and Science · Computer Science 2020-01-06 Karol Lewandowski , Łukasz Kaczmarczyk , Ignatios Athanasiadis , John F. Marshall , Chris J. Pearce

The strength of quasi-brittle materials depends on the ensemble of defects inside the sample and on the way damage accumulates before failure. Using large scale numerical simulations of the random fuse model, we investigate the evolution of…

Statistical Mechanics · Physics 2015-06-16 Claudio Manzato , Mikko J. Alava , Stefano Zapperi

High-fidelity computational fluid dynamics (CFD) simulations for design space explorations can be exceedingly expensive due to the cost associated with resolving the finer scales. This computational cost/accuracy trade-off is a major…

Fluid Dynamics · Physics 2024-03-14 Peetak Mitra , Majid Haghshenas , Niccolo Dal Santo , Conor Daly , David P. Schmidt