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
  • [41] Data-driven multiscale finite element method: From concurrence to separation
    Xu, Rui
    Yang, Jie
    Yan, Wei
    Huang, Qun
    Giunta, Gaetano
    Belouettar, Salim
    Zahrouni, Hamid
    Ben Zineb, Tarak
    Hu, Heng
    COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2020, 363
  • [42] Data-Driven Flow Control for Finite Wings at Low Reynolds Numbers
    Burtsev, Anton
    Jariwala, Akshit
    Bakolas, Efstathios
    Goldstein, David
    AIAA AVIATION FORUM AND ASCEND 2024, 2024,
  • [43] Data-driven, robust output regulation in finite time for LTI systems
    de Carolis, Giovanni
    Galeani, Sergio
    Sassano, Mario
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2018, 28 (18) : 5997 - 6015
  • [44] Dynamic data-driven finite element models for laser treatment of cancer
    Oden, J. T.
    Diller, K. R.
    Bajaj, C.
    Browne, J. C.
    Hazle, J.
    Babuska, I.
    Bass, J.
    Biduat, L.
    Demkowicz, L.
    Elliott, A.
    Feng, Y.
    Fuentes, D.
    Prudhomme, S.
    Rylander, M. N.
    Stafford, R. J.
    Zhang, Y.
    NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS, 2007, 23 (04) : 904 - 922
  • [45] A multi-level method for data-driven finite element computations
    Korzeniowski, Tim Fabian
    Weinberg, Kerstin
    COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2021, 379 (379)
  • [46] A data-driven reversible jump for estimating a finite mixture of regression models
    Gustavo Alexis Sabillón
    Luiz Gabriel Fernandes Cotrim
    Daiane Aparecida Zuanetti
    TEST, 2023, 32 : 350 - 369
  • [47] Data-Driven Computing
    Kirchdoerfer, Trenton
    Ortiz, Michael
    ADVANCES IN COMPUTATIONAL PLASTICITY: A BOOK IN HONOUR OF D. ROGER J. OWEN, 2018, 46 : 165 - 183
  • [48] Data-Driven Healthcare
    Chang, Hyejung
    HEALTHCARE INFORMATICS RESEARCH, 2015, 21 (01) : 61 - 62
  • [49] Data-Driven Productivity
    Cannell, Thom
    MANUFACTURING ENGINEERING, 2023, 170 (04): : 72 - 78
  • [50] DATA-DRIVEN ORIGINALISM
    Lee, Thomas R.
    Phillips, James C.
    UNIVERSITY OF PENNSYLVANIA LAW REVIEW, 2019, 167 (02) : 261 - 335