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Showing 1 to 8 of 8 for “"numerical homogenization"”.

  1. Topology Optimization and Analysis of Thermal and Mechanical Metamaterials

    … mechanical stress analysis formulation based on homogenization theory is developed and is used in a regional scaled aggregation stress constraint method, and a method of worst-case stress minimization is also included to efficiently address load uncertainty. It is shown that the two stress-based …

    embry-riddle Repository record for Topology Optimization and Analysis of Thermal and Mechanical Metamaterials (opens in a new tab)

  2. Exploring Immersed FEM, Material Design, and Biological Tissue Material Modeling

    … materials with desired effective properties. Numerical homogenization evaluates effective properties, and level set-based topology optimization evolves boundaries within the unit cell to generate optimal periodic microstructures. The design space is parameterized using radial basis functions, …

    vt Repository record for Exploring Immersed FEM, Material Design, and Biological Tissue Material Modeling (opens in a new tab)

  3. Monte Carlo-Based Predictive Modeling of Geometric Defects in Cellular Truss Structures Manufacturing

    … space for each topology is computed using numerical homogenization and finite ele- ment analysis and is validated experimentally via micro-compression testing. To support scalable studies, an automated data-generation pipeline is introduced that takes in nodal coordinates, connectivity …

    uic

  4. FEMxDEM double scale approach with second gradient regularization applied to granular materials modeling

    The multi-scale FEMxDEM approach is an innovative numerical method for geotechnical problems involving granular materials. The Finite Element Method (FEM) and the Discrete Element Method (DEM) are simultaneously applied to solve, respectively, the structural problem at the macro-scale and the …

    liege Repository record for FEMxDEM double scale approach with second gradient regularization applied to granular materials modeling (opens in a new tab)

  5. Optimization and Supervised Machine Learning Methods for Inverse Design of Cellular Mechanical Metamaterials

    … underlying geometries of metamaterials, it is numerically intractable to obtain optimal material designs that satisfy multiple user-defined performance criteria at the same time. Nevertheless, a deep learning method called conditional generative adversarial networks (CGANs) is capable of …

    vt Repository record for Optimization and Supervised Machine Learning Methods for Inverse Design of Cellular Mechanical Metamaterials (opens in a new tab)

  6. Homogenization of a Cracked Poroelastic Medium - Numerical calculation of the coefficients and damage

    … asymptotic expansions and the posterior use of numerical tools in order to get the coe cients for an homogeneous macroscopic model starting from heterogeneous microscopic description. The particular problem of this project is a cracked poroelastic medium, that is a Biot-type problem both in the …

    liege Repository record for Homogenization of a Cracked Poroelastic Medium - Numerical calculation of the coefficients and damage (opens in a new tab)