English
Related papers

Related papers: A time multiscale based data-driven approach in cy…

200 papers

The concept of concurrent material and structure optimization aims at alleviating the computational discovery of optimum microstructure configurations in multiphase hierarchical systems, whose macroscale behavior is governed by their…

Computational Physics · Physics 2022-04-15 Tarun Gangwar , Dominik Schillinger

There is a class of problems that exhibit smooth behavior on macroscopic scales, where only a microscopic evolution law is known. Patch dynamics scheme of `equation-free multiscale modelling' is one of the techniques, which aims to extract…

Numerical Analysis · Mathematics 2024-01-17 T. K. Karmakar , D. C. Dalal

We propose in this paper a Proper Generalized Decomposition (PGD) solver for reduced-order modeling of linear elastodynamic problems. It primarily focuses on enhancing the computational efficiency of a previously introduced PGD solver based…

Computational Engineering, Finance, and Science · Computer Science 2024-05-15 Clément Vella , Pierre Gosselet , Serge Prudhomme

Developing a macroscopic theory of elasto-plasticity in amorphous solids calls for (i) identifying the relevant macro state-variables and (ii) discriminating the different time-scales which characterize these variables. In current theories…

Statistical Mechanics · Physics 2009-11-25 Laurent Boue , Peter Harrowell , Smarajit Karmakar , Edan Lerner , Itamar Procaccia , Ido Regev , Jacques Zylberg

While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and their applicability over macroscopic time scales of physical…

Machine Learning · Statistics 2016-09-08 P. S. Koutsourelakis , Elias Bilionis

This paper presents a first implementation of the LArge Time INcrement (LATIN) method along with the model reduction technique called Proper Generalized Decomposition (PGD) for solving nonlinear low-frequency dynamics problems when dealing…

Computational Engineering, Finance, and Science · Computer Science 2024-08-12 Sebastian Rodriguez , Pierre-Etienne Charbonnel , Pierre Ladevèze , David Néron

In recent years, there has been a growing interest in understanding complex microstructures and their effect on macroscopic properties. In general, it is difficult to derive an effective constitutive law for such microstructures with…

Computational Engineering, Finance, and Science · Computer Science 2023-10-18 Theron Guo , Ondřej Rokoš , Karen Veroy

Accelerated proximal gradient methods have recently been developed for solving quasi-static incremental problems of elastoplastic analysis with some different yield criteria. It has been demonstrated through numerical experiments that these…

Optimization and Control · Mathematics 2020-11-13 Yoshihiro Kanno

In this letter, we develop a framework to study the mechanical response of athermal amorphous solids via a coupling of mesoscale and microscopic models. Using measurements of coarse grained quantities from simulations of dense disordered…

Soft Condensed Matter · Physics 2021-04-07 Chen Liu , Suman Dutta , Pinaki Chaudhuri , Kirsten Martens

Dynamic Mode Decomposition (DMD) is a data-driven technique to identify a low dimensional linear time invariant dynamics underlying high-dimensional data. For systems in which such underlying low-dimensional dynamics is time-varying, a…

Signal Processing · Electrical Eng. & Systems 2020-04-09 Mustaffa Alfatlawi , Vaibhav Srivastava

The macroscopic response of short fiber reinforced composites is dependent on an extensive range of microstructural parameters. Thus, micromechanical modeling of these materials is challenging and in some cases, computationally expensive.…

Machine Learning · Computer Science 2022-10-04 J. Friemann , B. Dashtbozorg , M. Fagerström , S. M. Mirkhalaf

We present a data-driven method for separating complex, multiscale systems into their constituent time-scale components using a recursive implementation of dynamic mode decomposition (DMD). Local linear models are built from windowed…

Systems and Control · Computer Science 2019-06-26 Daniel Dylewsky , Molei Tao , J. Nathan Kutz

Discrete automated processes in industrial and cyber-physical systems often exhibit a repetitive structure in which successive repetitions follow a common trajectory while differing in duration, amplitude, and fine-scale dynamics. Such…

Machine Learning · Statistics 2026-05-14 Elias Reich , Saverio Messineo , Stefan Huber

We propose a general hybrid physics-informed machine learning framework for modeling nonlinear, history-dependent viscoelastic behavior under multiaxial cyclic loading. The approach is built on a generalized internal state variable-based…

Soft Condensed Matter · Physics 2025-07-18 Alireza Ostadrahimi , Amir Teimouri , Kshitiz Upadhyay , Guoqiang Li

Thermal cycle environments involving repeated temperature changes are common conditions observed in modern engineering processes. Under such conditions, materials undergo repeated thermal expansion and contraction, forming complex thermal…

Materials Science · Physics 2026-05-20 Haruki Ohashi , Yoshiteru Aoyagi

The Discrete Dislocation (DD) analysis and its computional modeling have been advanced significantly over the past decade. This progress has been further magnified by the idea to couple DD with continuum mechanics analysis in association…

Materials Science · Physics 2007-05-23 H. M. Zbib , M. Hiratani , M. Shehade

Plastic deformation in microscale differs from the macroscopic plasticity in two respects: (i) the flow stress of small samples depends on their size (ii) the scatter of plasticity increases significantly. In this work we focus on the…

Materials Science · Physics 2015-03-10 Olga Kapetanou , Vasilis Koutsos , Efstathios Theotokoglou , Daniel Weygand , Michael Zaiser

The quasistatic rate-independent damage combined with linearized plasticity with hardening at small strains is investigated. The fractional-step time discretisation is devised with the purpose to obtain a numerically efficient scheme…

Numerical Analysis · Mathematics 2015-06-05 Tomáš Roubíček , Jan Valdman

We propose in this paper a Proper Generalized Decomposition (PGD) approach for the solution of problems in linear elastodynamics. The novelty of the work lies in the development of weak formulations of the PGD problems based on the…

Computational Engineering, Finance, and Science · Computer Science 2023-01-26 Clément Vella , Serge Prudhomme

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix…

Plasma Physics · Physics 2018-05-23 Roy Taylor , J. Nathan Kutz , Kyle Morgan , Brian Nelson