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Related papers: Phase-Field Modeling of Fracture with Physics-Info…

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We present a new physics informed neural network (PINN) algorithm for solving brittle fracture problems. While most of the PINN algorithms available in the literature minimize the residual of the governing partial differential equation, the…

Machine Learning · Statistics 2019-07-08 Somdatta Goswami , Cosmin Anitescu , Souvik Chakraborty , Timon Rabczuk

Variational phase-field methods have been shown powerful for the modeling of complex crack propagation without a priori knowledge of the crack path or ad hoc criteria. However, phase-field models suffer from their energy functional being…

Computational Engineering, Finance, and Science · Computer Science 2021-09-15 O. Lampron , D. Therriault , M. Lévesque

Numerical modeling of localizations is a challenging task due to the evolving rough solution in which the localization paths are not predefined. Despite decades of efforts, there is a need for innovative discretization-independent…

Computational Engineering, Finance, and Science · Computer Science 2023-07-06 Jonghyuk Baek , Jiun-Shyan Chen

In this paper we focus on the finite-dimensional approximation of quasi-static evolutions of critical points of the phase-field model of brittle fracture. In a space discretized setting, we first discuss an alternating minimization scheme…

Numerical Analysis · Mathematics 2019-03-07 Stefano Almi , Sandro Belz

A field theory is presented for predicting damage and fracture in quasi-brittle materials. The approach taken here is new and blends a non-local constitutive law with a two-point phase field. In this formulation, the material displacement…

Materials Science · Physics 2025-10-07 Semsi Coskun , Davood Damircheli , Robert Lipton

A moving mesh finite element method is studied for the numerical solution of a phase-field model for brittle fracture. The moving mesh partial differential equation approach is employed to dynamically track crack propagation. Meanwhile, the…

Numerical Analysis · Mathematics 2018-01-17 Fei Zhang , Weizhang Huang , Xianping Li , Shicheng Zhang

Fracture is a fundamental mechanism of materials failure. Propagating cracks can exhibit a rich dynamical behavior controlled by a subtle interplay between microscopic failure processes in the crack tip region and macroscopic elasticity. We…

Materials Science · Physics 2015-05-18 R. Spatschek , E. Brener , A. Karma

In the field of brittle fracture animation, generating realistic destruction animations using physics-based simulation methods is computationally expensive. While techniques based on Voronoi diagrams or pre-fractured patterns are effective…

Graphics · Computer Science 2025-02-21 Yuhang Huang , Takashi Kanai

This paper presents eXtended Physics-Informed Neural Network (X-PINN), a novel and robust framework for addressing fracture mechanics problems involving multiple cracks in fractured media. To address this, an energy-based loss function,…

Machine Learning · Computer Science 2025-09-18 Amin Lotfalian , Mohammad Reza Banan , Pooyan Broumand

The phase field paradigm, in combination with a suitable variational structure, has opened a path for using Griffith's energy balance to predict the fracture of solids. These so-called phase field fracture methods have gained significant…

Computational Engineering, Finance, and Science · Computer Science 2022-03-08 P. K. Kristensen , C. F. Niordson , E. Martínez-Pañeda

Variational phase-field models of fracture are widely used to simulate nucleation and propagation of cracks in brittle materials. They are based on the approximation of the solutions of free-discontinuity fracture energy by two smooth…

Numerical Analysis · Mathematics 2023-02-14 Frederic Marazzato , Blaise Bourdin

High-fidelity fracture mechanics simulations of multiple microcracks interaction via physics-based models quickly become computationally expensive as the number of microcracks increases. This work develops a Graph Neural Network (GNN) based…

Materials Science · Physics 2022-05-12 Roberto Perera , Davide Guzzetti , Vinamra Agrawal

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

The classical variational phase-field model for brittle fracture effectively predicts the growth of large pre-existing cracks. However, the modeling of crack nucleation continues to be a significant challenge. Crack nucleation under uniform…

Materials Science · Physics 2025-02-10 Umar Khayaz , Aarosh Dahal , Aditya Kumar

Materials with network-like microstructure, including polymers, are the backbone for many natural and human-made materials such as gels, biological tissues, metamaterials, and rubbers. Fracture processes in these networked materials are…

Soft Condensed Matter · Physics 2020-01-29 Ahmed Ghareeb , Ahmed Elbanna

Real-time simulation of elastic structures is essential in many applications, from computer-guided surgical interventions to interactive design in mechanical engineering. The Finite Element Method is often used as the numerical method of…

Machine Learning · Computer Science 2021-09-21 Alban Odot , Ryadh Haferssas , Stéphane Cotin

Artificial Neuronal Networks are models widely used for many scientific tasks. One of the well-known field of application is the approximation of high-dimensional problems via Deep Learning. In the present paper we investigate the Deep…

Numerical Analysis · Mathematics 2021-10-06 F. Calabrò , S. Cuomo , F. Giampaolo , S. Izzo , C. Nitsch , F. Piccialli , C. Trombetti

This contribution presents a diffuse framework for modeling cracks in heterogeneous media. Interfaces are depicted by static phase-fields. This concept allows the use of non-conforming meshes. Another phase-field is used to describe the…

Materials Science · Physics 2020-05-11 Arne Claus Hansen-Dörr , Franz Dammaß , René de Borst , Markus Kästner

Failure trajectories, identifying the probable failure zones, and damage statistics are some of the key quantities of relevance in brittle fracture applications. High-fidelity numerical solvers that reliably estimate these relevant…

Machine Learning · Computer Science 2022-02-16 Somdatta Goswami , Minglang Yin , Yue Yu , George Karniadakis

Catastrophic failure in brittle materials is often due to the rapid growth and coalescence of cracks aided by high internal stresses. Hence, accurate prediction of maximum internal stress is critical to predicting time to failure and…