Data-Driven Finite Elasticity

被引:0
|
作者
S. Conti
S. Müller
M. Ortiz
机构
[1] Universität Bonn,Institut für Angewandte Mathematik
[2] Hausdorff Center for Mathematics,Division of Engineering and Applied Science
[3] California Institute of Technology,undefined
关键词
D O I
暂无
中图分类号
学科分类号
摘要
We extend to finite elasticity the Data-Driven formulation of geometrically linear elasticity presented in Conti et al. (Arch Ration Mech Anal 229:79–123, 2018). The main focus of this paper concerns the formulation of a suitable framework in which the Data-Driven problem of finite elasticity is well-posed in the sense of existence of solutions. We confine attention to deformation gradients F∈Lp(Ω;Rn×n)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F \in L^p(\Omega ;{\mathbb {R}}^{n\times n})$$\end{document} and first Piola-Kirchhoff stresses P∈Lq(Ω;Rn×n)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P \in L^q(\Omega ;{\mathbb {R}}^{n\times n})$$\end{document}, with (p,q)∈(1,∞)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(p,q)\in (1,\infty )$$\end{document} and 1/p+1/q=1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1/p+1/q=1$$\end{document}. We assume that the material behavior is described by means of a material data set containing all the states (F, P) that can be attained by the material, and develop germane notions of coercivity and closedness of the material data set. Within this framework, we put forth conditions ensuring the existence of solutions. We exhibit specific examples of two- and three-dimensional material data sets that fit the present setting and are compatible with material frame indifference.
引用
收藏
页码:1 / 33
页数:32
相关论文
共 50 条
  • [31] Data-driven Electricity Market Price Risk Evaluation Based on Price Elasticity Indicator
    Song, Haotian
    Tang, Qinghu
    Guo, Hongye
    Liu, Jianing
    Su, Zhuo
    Chen, Qixin
    2023 IEEE/IAS INDUSTRIAL AND COMMERCIAL POWER SYSTEM ASIA, I&CPS ASIA, 2023, : 467 - 472
  • [32] Data-driven non-linear elasticity: constitutive manifold construction and problem discretization
    Ibanez, Ruben
    Borzacchiello, Domenico
    Aguado, Jose Vicente
    Abisset-Chavanne, Emmanuelle
    Cueto, Elias
    Ladeveze, Pierre
    Chinesta, Francisco
    COMPUTATIONAL MECHANICS, 2017, 60 (05) : 813 - 826
  • [33] Energy-efficient User-oriented Cloud Elasticity for Data-driven Applications
    Guyon, David
    Orgerie, Anne-Cecile
    Morin, Christine
    2015 IEEE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND DATA INTENSIVE SYSTEMS, 2015, : 376 - 383
  • [34] Data-driven non-linear elasticity: constitutive manifold construction and problem discretization
    Ruben Ibañez
    Domenico Borzacchiello
    Jose Vicente Aguado
    Emmanuelle Abisset-Chavanne
    Elias Cueto
    Pierre Ladeveze
    Francisco Chinesta
    Computational Mechanics, 2017, 60 : 813 - 826
  • [35] Data-driven analysis of spinodoid topologies: anisotropy, inverse design, and elasticity tensor distribution
    Golnary, Farshid
    Asghari, Mohsen
    INTERNATIONAL JOURNAL OF MECHANICS AND MATERIALS IN DESIGN, 2024, 20 (05) : 1029 - 1051
  • [36] A data-driven paradigm to develop and tune data-driven realtime system
    Wabiko, Y
    Nishikawa, H
    PDPTA'2001: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED PROCESSING TECHNIQUES AND APPLICATIONS, 2001, : 350 - 356
  • [37] Data-Driven Controller Synthesis via Finite Abstractions With Formal Guarantees
    Ajeleye, Daniel
    Lavaei, Abolfazl
    Zamani, Majid
    IEEE CONTROL SYSTEMS LETTERS, 2023, 7 : 3453 - 3458
  • [38] A data-driven reversible jump for estimating a finite mixture of regression models
    Sabillon, Gustavo Alexis
    Fernandes Cotrim, Luiz Gabriel
    Zuanetti, Daiane Aparecida
    TEST, 2023, 32 (01) : 350 - 369
  • [39] Data-driven finite element simulation for yarn breaking strength analysis
    Tao J.
    Wang J.
    Zhang J.
    Fangzhi Xuebao/Journal of Textile Research, 2024, 45 (02): : 238 - 245
  • [40] A data-driven finite state machine model for analyzing security vulnerabilities
    Chen, S
    Kalbarczyk, Z
    Xu, J
    Iyer, RK
    2003 INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS, PROCEEDINGS, 2003, : 605 - 614