Data-Driven Self-consistent Clustering Analysis of Heterogeneous Materials with Crystal Plasticity

To analyze complex, heterogeneous materials, a fast and accurate method is needed. This means going beyond the classical finite element method, in a search for the ability to compute, with modest computational resources, solutions previously infeasible even with large cluster computers. In particular, this advance is motivated by composites design. Here, we apply similar principle to another complex, heterogeneous system: additively manufactured metals.

[1]  Pierre Suquet,et al.  Computational analysis of nonlinear composite structures using the Nonuniform Transformation Field Analysis , 2004 .

[2]  Zeliang Liu,et al.  A statistical descriptor based volume-integral micromechanics model of heterogeneous material with arbitrary inclusion shape , 2015 .

[3]  R. McGinty.  Multiscale representation of polycrystalline inelasticity , 2001 .

[4]  Miguel A. Bessa,et al.  Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials , 2016 .

[5]  Zeliang Liu,et al.  An extended micromechanics method for probing interphase properties in polymer nanocomposites , 2016 .

[6]  Ted Belytschko,et al.  Multiscale aggregating discontinuities: A method for circumventing loss of material stability , 2008 .

[7]  Pierre Suquet,et al.  Nonuniform transformation field analysis of elastic–viscoplastic composites , 2009 .

[8]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[9]  Wei Chen,et al.  A framework for data-driven analysis of materials under uncertainty: Countering the curse of dimensionality , 2017 .

[10]  J. Marsden,et al.  Dimensional model reduction in non‐linear finite element dynamics of solids and structures , 2001 .

[11]  Philip Eisenlohr,et al.  An elasto-viscoplastic formulation based on fast Fourier transforms for the prediction of micromechanical fields in polycrystalline materials , 2012 .

[12]  Jacob Fish,et al.  Eigendeformation-based reduced order homogenization for failure analysis of heterogeneous materials , 2007 .

[13]  B. A. Le,et al.  Computational homogenization of nonlinear elastic materials using neural networks , 2015 .

[14]  R. Hill.  A self-consistent mechanics of composite materials , 1965 .

[15]  T. Bieler,et al.  Overview of constitutive laws, kinematics, homogenization and multiscale methods in crystal plasticity finite-element modeling: Theory, experiments, applications , 2010 .

[16]  S. Shtrikman,et al.  A variational approach to the theory of the elastic behaviour of multiphase materials , 1963 .

[17]  Julien Yvonnet,et al.  The reduced model multiscale method (R3M) for the non-linear homogenization of hyperelastic media at finite strains , 2007, J. Comput. Phys..

[18]  Julien Yvonnet,et al.  COMPUTATIONAL HOMOGENIZATION METHOD AND REDUCED DATABASE MODEL FOR HYPERELASTIC HETEROGENEOUS STRUCTURES , 2013 .

[19]  Ventola Cl.  Medical Applications for 3D Printing: Current and Projected Uses. , 2014 .

[20]  Amine Ouaar,et al.  Homogenization of two-phase elasto-plastic composite materials and structures: Study of tangent operators, cyclic plasticity and numerical algorithms , 2003 .

[21]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .

[22]  J. D. Eshelby.  The determination of the elastic field of an ellipsoidal inclusion, and related problems , 1957, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.