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1. Bi-material topology optimization for energy dissipation with inertia and material rate effects under finite deformations

   https://doi.org/10.1016/j.finel.2019.06.003  

   Alberdi, Ryan ; Khandelwal, Kapil ( October 2019 , Finite Elements in Analysis and Design)
2. Shear Wave Propagation and Estimation of Material Parameters in a Nonlinear, Fibrous Material

   https://doi.org/10.1115/1.4044504  

   Hou, Zuoxian ; Okamoto, Ruth J. ; Bayly, Philip V. ( May 2020 , Journal of Biomechanical Engineering)

   Abstract This paper describes the propagation of shear waves in a Holzapfel–Gasser–Ogden (HGO) material and investigates the potential of magnetic resonance elastography (MRE) for estimating parameters of the HGO material model from experimental data. In most MRE studies the behavior of the material is assumed to be governed by linear, isotropic elasticity or viscoelasticity. In contrast, biological tissue is often nonlinear and anisotropic with a fibrous structure. In such materials, application of a quasi-static deformation (predeformation) plays an important role in shear wave propagation. Closed form expressions for shear wave speeds in an HGO material with a single family of fibers were found in a reference (undeformed) configuration and after imposed predeformations. These analytical expressions show that shear wave speeds are affected by the parameters (μ0, k1, k2, κ) of the HGO model and by the direction and amplitude of the predeformations. Simulations of corresponding finite element (FE) models confirm the predicted influence of HGO model parameters on speeds of shear waves with specific polarization and propagation directions. Importantly, the dependence of wave speeds on the parameters of the HGO model and imposed deformations could ultimately allow the noninvasive estimation of material parameters in vivo from experimental shear wave image data. 

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3. Microstructurally-informed stochastic inhomogeneity of material properties and material symmetries in 3D-printed 316 L stainless steel

   https://doi.org/10.1007/s00466-023-02424-6  

   Chu, Shanshan ; Iliopoulos, Athanasios ; Michopoulos, John ; Birnbaum, Andrew ; Steuben, John ; Stewart, Colin ; Callahan, Patrick ; Rowenhorst, David ; Guilleminot, Johann ( December 2023 , Computational Mechanics)

   Stochastic mesoscale inhomogeneity of material properties and material symmetries are investigated in a 3D-printed material. The analysis involves a spatially-dependent characterization of the microstructure in 316 L stainless steel, obtained through electron backscatter diffraction imaging. These data are subsequently fed into a Voigt–Reuss–Hill homogenization approxima- tion to produce maps of elasticity tensor coefficients along the path of experimental probing. Information-theoretic stochastic models corresponding to this stiffness random field are then introduced. The case of orthotropic fields is first defined as a high-fidelity model, the realizations of which are consistent with the elasticity maps. To investigate the role of material symmetries, an isotropic approximation is next introduced through ad-hoc projections (using various metrics). Both stochastic representations are identified using the dataset. In particular, the correlation length along the characterization path is identified using a maximum likelihood estimator. Uncertainty propagation is finally performed on a complex geometry, using a Monte Carlo analysis. It is shown that mechanical predictions in the linear elastic regime are mostly sensitive to material symmetry but weakly depend on the spatial correlation length in the considered propagation scenario. 

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4. A hybrid material-point spheropolygon-element method for solid and granular material interaction

   https://doi.org/10.1002/nme.6345  

   Jiang, Yupeng ; Li, Minchen ; Jiang, Chenfanfu ; Alonso-Marroquin, Fernando ( January 2020 , International Journal for Numerical Methods in Engineering)
5. Evolution of material properties during the solvent-assisted recycling of thermosetting polymers: to reduce the residual stress and material inhomogeneity

   https://doi.org/10.1016/j.mtsust.2022.100167  

   Shi, X. ; Soule, D. ; Ge, Q. ; Lu, H. ; Yu, K. ( November 2022 , Materials Today Sustainability)