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Capturing and predicting the effective mechanical properties of highly porous cellular media still represents a significant challenge for the research community, due to their complex structural interdependencies and known size effects.…

Soft Condensed Matter · Physics 2024-07-30 Alexander Malik , Geralf Hütter , Martin Abendroth , Bjoern Kiefer

Mechanical metamaterials feature engineered microstructures designed to exhibit exotic, and often counter-intuitive, effective behaviour. Such a behaviour is often achieved through instability-induced transformations of the underlying…

Computational Engineering, Finance, and Science · Computer Science 2020-09-04 S. E. H. M. van Bree , O. Rokoš , R. H. J. Peerlings , M. Doškář , M. G. D. Geers

Intelligent biological systems are characterized by their embodiment in a complex environment and the intimate interplay between their nervous systems and the nonlinear mechanical properties of their bodies. This coordination, in which the…

Machine Learning · Computer Science 2023-02-02 Deniz Oktay , Mehran Mirramezani , Eder Medina , Ryan P. Adams

Microstructured materials, such as architected metamaterials and phononic crystals, exhibit complex wave propagation phenomena due to their internal structure. While full-scale numerical simulations can capture these effects, they are…

Computational Physics · Physics 2025-05-21 Gianluca Rizzi , Angela Madeo

Cellular metamaterials offer a vast design space for tailoring nonlinear mechanical responses, yet exploring this space with conventional modeling approaches is often infeasible or not scalable. To fully exploit their nonlinear behavior for…

Applied Physics · Physics 2026-02-17 Pu You , Hongshun Chen , Bahador Bahmani , Horacio D. Espinosa

Metamaterials are engineered materials composed of specially designed unit cells that exhibit extraordinary properties beyond those of natural materials. Complex engineering tasks often require heterogeneous unit cells to accommodate…

Machine Learning · Computer Science 2025-11-06 Hongrui Chen , Liwei Wang , Levent Burak Kara

Computational multiscale methods for analyzing and deriving constitutive responses have been used as a tool in engineering problems because of their ability to combine information at different length scales. However, their application in a…

Machine Learning · Statistics 2021-08-03 Jan Niklas Fuhg , Christoph Boehm , Nikolaos Bouklas , Amelie Fau , Peter Wriggers , Michele Marino

The morphology of nanostructured materials exhibiting a polydisperse porous space, such as aerogels, is very open porous and fine grained. Therefore, a simulation of the deformation of a large aerogel structure resolving the nanostructure…

Numerical Analysis · Mathematics 2024-03-04 Axel Klawonn , Martin Lanser , Lucas Mager , Ameya Rege

Computational modeling of the structural behavior of continuous fiber composite materials often takes into account the periodicity of the underlying micro-structure. A well established method dealing with the structural behavior of periodic…

Computational Engineering, Finance, and Science · Computer Science 2017-07-17 Charilaos Mylonas , Valentin Bemetz , Eleni Chatzi

The development of novel materials in recent years has been accelerated greatly by the use of computational modelling techniques aimed at elucidating the complex physics controlling microstructure formation in materials, the properties of…

Materials Science · Physics 2025-11-14 Damien Pinto , Michael Greenwood , Nikolas Provatas

A version of the time-parallel algorithm parareal is analyzed and applied to stochastic models in chemical kinetics. A fast predictor at the macroscopic scale (evaluated in serial) is available in the form of the usual reaction rate…

Numerical Analysis · Mathematics 2009-09-16 Stefan Engblom

The Deep Material Network (DMN) has emerged as a powerful framework for multiscale materials modeling, enabling efficient and accurate prediction of material behavior across different length scales. Unlike conventional data-driven…

Computational Engineering, Finance, and Science · Computer Science 2026-03-23 Ting-Ju Wei , Wen-Ning Wan , Chuin-Shan Chen

Models play an essential role in the design process of cyber-physical systems. They form the basis for simulation and analysis and help in identifying design problems as early as possible. However, the construction of models that comprise…

This study presents a comprehensive theoretical framework to simulate the response of multiscale nonlocal elastic beams. By employing distributed-order (DO) fractional operators with a fourth-order tensor as the strength-function, the…

Computational Engineering, Finance, and Science · Computer Science 2022-07-29 Wei Ding , Sansit Patnaik , Fabio Semperlotti

Simulation in media with multiple continua where each continuum interacts with every other is often challenging due to multiple scales and high contrast. One needs some types of model reduction. One of the approaches is multi-continuum…

Numerical Analysis · Mathematics 2019-06-12 Jun Sur Richard Park , Viet Ha Hoang

Meta-materials are an important emerging class of engineered materials in which complex macroscopic behaviour--whether electromagnetic, thermal, or mechanical--arises from modular substructure. Simulation and optimization of these materials…

Machine Learning · Computer Science 2020-05-18 Alex Beatson , Jordan T. Ash , Geoffrey Roeder , Tianju Xue , Ryan P. Adams

In the present work, we consider multi-scale computation and convergence for nonlinear time-dependent thermo-mechanical equations of inhomogeneous shells possessing temperature-dependent material properties and orthogonal periodic…

Numerical Analysis · Mathematics 2023-08-23 Hao Dong , Xiaofei Guan , Yufeng Nie

We present our ongoing work aimed at accelerating a particle-resolved direct numerical simulation model designed to study aerosol-cloud-turbulence interactions. The dynamical model consists of two main components - a set of fluid dynamics…

Understanding and predicting microstructure evolution is fundamental to materials science, as it governs the resulting properties and performance of materials. Traditional simulation methods, such as phase-field models, offer high-fidelity…

Machine Learning · Computer Science 2026-02-24 Michael Trimboli , Mohammed Alsubaie , Sirani M. Perera , Ke-Gang Wang , Xianqi Li

Constitutive modeling based on continuum mechanics theory has been a classical approach for modeling the mechanical responses of materials. However, when constitutive laws are unknown or when defects and/or high degrees of heterogeneity are…

Machine Learning · Computer Science 2022-07-27 Huaiqian You , Quinn Zhang , Colton J. Ross , Chung-Hao Lee , Yue Yu