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This paper presents a comprehensive computational framework for investigating thermo-elastic fracture in transversely isotropic materials, where classical linear elasticity fails to predict physically realistic behavior near stress…

Numerical Analysis · Mathematics 2025-10-08 Saugata Ghosh , Dambaru Bhatta , S. M. Mallikarjunaiah

A thorough in situ characterization of materials at extreme conditions is challenging, and computational tools such as crystal structural search methods in combination with ab initio calculations are widely used to guide experiments by…

Materials Science · Physics 2018-11-14 Maximilian Amsler , Vinay I. Hegde , Steven D. Jacobsen , Chris Wolverton

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

A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications,…

Materials Science · Physics 2016-08-29 Logan Ward , Ankit Agrawal , Alok Choudhary , Christopher Wolverton

Coherent X-ray scattering (CXS) techniques are capable of interrogating dynamics of nano- to mesoscale materials systems at time scales spanning several orders of magnitude. However, obtaining accurate theoretical descriptions of complex…

Data-driven material models have many advantages over classical numerical approaches, such as the direct utilization of experimental data and the possibility to improve performance of predictions when additional data is available. One…

Computational Engineering, Finance, and Science · Computer Science 2020-06-11 Dengpeng Huang , Jan Niklas Fuhg , Christian Weißenfels , Peter Wriggers

Many, if not most, systems of interest in science are naturally described as nonlinear dynamical systems. Empirically, we commonly access these systems through time series measurements. Often such time series may consist of discrete random…

Machine Learning · Computer Science 2024-06-10 Manuel Brenner , Florian Hess , Georgia Koppe , Daniel Durstewitz

Crystal-graph attention networks have emerged recently as remarkable tools for the prediction of thermodynamic stability and materials properties from unrelaxed crystal structures. Previous networks trained on two million materials…

We extend the scope of our approach for unsupervised automated discovery of material laws (EUCLID) to the case of a material belonging to an unknown class of behavior. To this end, we leverage the theory of generalized standard materials,…

Materials Science · Physics 2023-01-18 Moritz Flaschel , Siddhant Kumar , Laura De Lorenzis

Crystal plasticity models connect macroscopic deformation with the physics of microscale slip in polycrystalline materials. These models can be calibrated using global stress-strain curves, but the resulting parametrization is often not…

Materials Science · Physics 2026-03-24 Joshua D. Pribe , Patrick E. Leser , Saikumar R. Yeratapally , George Weber

A variational model to simultaneously treat Stress-Driven Rearrangement Instabilities, such as boundary discontinuities, internal cracks, external filaments, edge delamination, wetting, and brittle fractures, is introduced. The model is…

Analysis of PDEs · Mathematics 2020-06-24 Shokhrukh Yu. Kholmatov , Paolo Piovano

In many modern applications, a carefully designed primary study provides individual-level data for interpretable modeling, while summary-level external information is available through black-box, efficient, and nonparametric…

Methodology · Statistics 2026-04-07 Chi-Shian Dai , Jun Shao

We construct a mean-field elastoplastic description of the dynamics of amorphous solids under arbitrary time-dependent perturbations, building on the work of Lin and Wyart [Phys. Rev. X 6, 011005 (2016)] for steady shear. Local stresses are…

Soft Condensed Matter · Physics 2020-12-14 Jack T. Parley , Suzanne M. Fielding , Peter Sollich

Fatigue simulation requires accurate modeling of unloading and reloading. However, classical ductile damage models treat deformations after complete failure as irrecoverable -- which leads to unphysical behavior during unloading. This…

Computational Engineering, Finance, and Science · Computer Science 2023-12-06 Leon Herrmann , Alireza Daneshyar , Stefan Kollmannsberger

Molecular dynamics (MD) has served as a powerful tool for designing materials with reduced reliance on laboratory testing. However, the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely…

Materials Science · Physics 2023-01-12 Huaiqian You , Xiao Xu , Yue Yu , Stewart Silling , Marta D'Elia , John Foster

The Marginally Rigid State is a candidate paradigm for what makes granular material a state of matter distinct from both liquid and solid. Coordination number is identified as a discriminating characteristic, and for rough-surfaced…

Statistical Mechanics · Physics 2007-05-23 R. C. Ball , R. Blumenfeld

The fundamental ideas and tools of the global geometric formulation of stress and hyper-stress theory of continuum mechanics are introduced. The proposed framework is the infinite dimensional counterpart of statics of systems having finite…

Mathematical Physics · Physics 2019-04-24 Reuven Segev

The study is devoted to geometrically non-linear modelling of viscoplastic structures with residual stresses. We advocate and develop a special approach to residual stresses based on the transition between reference configurations. The…

Materials Science · Physics 2021-04-06 I. I. Tagiltsev , A. V. Shutov

Problems of flexible mechanical metamaterials, and highly deformable porous solids in general, are rich and complex due to nonlinear mechanics and nontrivial geometrical effects. While numeric approaches are successful, analytic tools and…

Soft Condensed Matter · Physics 2022-06-08 Yohai Bar-Sinai , Gabriele Librandi , Katia Bertoldi , Michael Moshe

Bayesian model updating facilitates the calibration of analytical models based on observations and the quantification of uncertainties in model parameters such as stiffness and mass. This process significantly enhances damage assessment and…

Applications · Statistics 2024-08-06 Taro Yaoyama , Tatsuya Itoi , Jun Iyama