Random Heterogeneous Materials

By Hakobyan Yeranuhi. 2008

401 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/7f6036f90e97209efa2a02f1ff4f9f6676790525

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Citations in the corpus

Apparent and effective physical properties of heterogeneous materials: Representativity of samples of two materials from food industry (2006, background): “The effective physical properties of heterogeneous materials strongly depend on the morphology of phase distribution in space [20,40].”
Theories and simulations of polymer-based nanocomposites: From chain statistics to reinforcement (2008, background): “This approach is extensively reviewed in the book by Torquato [139].”
Evaluating structural indices by reversing forest structural analysis (2006, methodology): “The last two phases of this modelling approach are similar to the idea of the simulated annealing reconstruction as described by Torquato (2002).”
Structure–property linkages using a data science approach: Application to a non-metallic inclusion/steel composite system (2015, background): “In practice, rigorously formulated homogenization theories are currently available only for a fairly limited class of effective properties [1,8,19,20].”
Edge-correction needs in estimating indices of spatial forest structure (2006, background): “form an infinite lattice (Torquato 2002).”
Thermo-mechanical reactivation of locked crystal mushes: Melting-induced internal fracturing and assimilation processes in magmas (2011, methodology): “(2011), doi:1 script refers to the number of phases involved, crystals, melt and volatiles) (Hashin and Shtrikman, 1963; Torquato, 2001).”
New concepts of homogenization applied in rough surface hydrodynamic lubrication (2007, unknown): “[17, 18] and the references given there.”
Reconstruction of three-dimensional porous media using generative adversarial neural networks (2017, methodology): “While for the classical Boolean model, the centers of the grains are uniformly distributed in space and grains can arbitrarily overlap, more complicated models with rigid hard sphere grains and more complex grain interaction functions have been developed [7–10].”
On the Size of RVE in Finite Elasticity of Random Composites (2006, background): “the randommedium is described by a distribution of phases, such that B1 (w) [ B2 (w) = B (w) and B1 (w) \ B2 (w) = 0 [24], which can be set up on the basis of point fields.”
Key computational modeling issues in Integrated Computational Materials Engineering (2013, background): “A number of different measures of the spatial correlations in the microstructure have been proposed and utilized in literature [19,20].”
A Unified Theory for Constitutive Modeling of Composites (2016, methodology): “…the rules of mixtures [Hill 1952], Hashin– Shtrikman bounds [Hashin and Shtrikman 1962], third-order bounds [Milton 2002], and higher-order bounds [Torquato 2002]; or approximate predictions such as Mori–Tanaka method [Mori and Tanaka 1973], the method of cells [Aboudi 1982; 1989] and its…”