21 citations · 52 across the 6 of their papers we have counts for
7 papers
Reduced order modeling for micromorphic computational homogenization of mechanical metamaterials with patterning fluctuation fields
Theron Guo, Ondřej Rokoš
Mechanical metamaterials owe some of their exotic effective properties to microstructural instabilities such as buckling and pattern transformation. Their fine-scale geometry, comb…
Residual-Driven Lifting Identification for Nonlinear-Manifold Reduced-Order Models of Parametrized Linear PDEs
Francesco A. B. Silva, Jean C. Ragusa, Theron Guo +1
We introduce a residual-driven procedure for training nonlinear-manifold reduced-order models for parametrized linear partial differential equations that, given prescribed latent a…
Mathematical Modeling and Error Estimation for the Thermal Dunking Problem: A Hierarchical Approach
Theron Guo, Kento Kaneko, Claude Le Bris +1
We consider the thermal dunking problem, in which a solid body is suddenly immersed in a fluid of different temperature, and study both the temporal evolution of the solid and the…
Reduced-order modeling for second-order computational homogenization with applications to geometrically parameterized elastomeric metamaterials
T. Guo, V. G. Kouznetsova, M. G. D. Geers +2
The structural properties of mechanical metamaterials are typically studied with two-scale methods based on computational homogenization. Because such materials have a complex micr…
A reduced order model for geometrically parameterized two-scale simulations of elasto-plastic microstructures under large deformations
Theron Guo, Ondřej Rokoš, Karen Veroy
In recent years, there has been a growing interest in understanding complex microstructures and their effect on macroscopic properties. In general, it is difficult to derive an eff…
Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method: Extension to geometrical parameterizations
Theron Guo, Francesco A. B. Silva, Ondřej Rokoš +1
Understanding structure-property relations is essential to optimally design materials for specific applications. Two-scale simulations are often employed to analyze the effect of t…
Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method
Theron Guo, Ondřej Rokoš, Karen Veroy
In order to optimally design materials, it is crucial to understand the structure-property relations in the material by analyzing the effect of microstructure parameters on the mac…