81 citations · 160 across the 12 of their papers we have counts for
12 papers
Interpolation-based reproducing kernel particle method
Jennifer E. Fromm, John A. Evans, J. S. Chen
Meshfree methods, including the reproducing kernel particle method (RKPM), have been widely used within the computational mechanics community to model physical phenomena in materia…
Image-Based RKPM for Accessing Failure Mechanisms in Composite Materials
Yanran Wang, Yichun Tang, Jing Du +2
Stress distributions and the corresponding fracture patterns and evolutions in the microstructures strongly influence the load-carrying capabilities of composite structures. This w…
A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling
Christophe Bonneville, Xiaolong He, April Tran +10
Numerical solvers of partial differential equations (PDEs) have been widely employed for simulating physical systems. However, the computational cost remains a major bottleneck in…
Interpolation-based immersogeometric analysis methods for multi-material and multi-physics problems
Jennifer E. Fromm, Nils Wunsch, Kurt Maute +2
Immersed boundary methods are high-order accurate computational tools used to model geometrically complex problems in computational mechanics. While traditional finite element meth…
N-Adaptive Ritz Method: A Neural Network Enriched Partition of Unity for Boundary Value Problems
Jonghyuk Baek, Yanran Wang, J. S. Chen
Conventional finite element methods are known to be tedious in adaptive refinements due to their conformal regularity requirements. Further, the enrichment functions for adaptive r…
Data-Driven Modeling of an Unsaturated Bentonite Buffer Model Test Under High Temperatures Using an Enhanced Axisymmetric Reproducing Kernel Particle Method
Jonghyuk Baek, Yanran Wang, Xiaolong He +3
In deep geological repositories for high level nuclear waste with close canister spacings, bentonite buffers can experience temperatures higher than 100 °C. In this range of extrem…
A Multi-Resolution Physics-Informed Recurrent Neural Network: Formulation and Application to Musculoskeletal Systems
Karan Taneja, Xiaolong He, Qizhi He +1
This work presents a multi-resolution physics-informed recurrent neural network (MR PI-RNN), for simultaneous prediction of musculoskeletal (MSK) motion and parameter identificatio…
Support Vector Machine Guided Reproducing Kernel Particle Method for Image-Based Modeling of Microstructures
Yanran Wang, Jonghyuk Baek, Yichun Tang +3
This work presents an approach for automating the discretization and approximation procedures in constructing digital representations of composites from Micro-CT images featuring i…
A Quasi-Conforming Embedded Reproducing Kernel Particle Method for Heterogeneous Materials
Ryan T. Schlinkman, Jonghyuk Baek, Frank N. Beckwith +2
We present a quasi-conforming embedded reproducing kernel particle method (QCE-RKPM) for modeling heterogeneous materials that makes use of techniques not available to mesh-based m…
Certified data-driven physics-informed greedy auto-encoder simulator
Xiaolong He, Youngsoo Choi, William D. Fries +2
A parametric adaptive greedy Latent Space Dynamics Identification (gLaSDI) framework is developed for accurate, efficient, and certified data-driven physics-informed greedy auto-en…
Thermodynamically Consistent Machine-Learned Internal State Variable Approach for Data-Driven Modeling of Path-Dependent Materials
Xiaolong He, Jiun-Shyan Chen
Characterization and modeling of path-dependent behaviors of complex materials by phenomenological models remains challenging due to difficulties in formulating mathematical expres…
gLaSDI: Parametric Physics-informed Greedy Latent Space Dynamics Identification
Xiaolong He, Youngsoo Choi, William D. Fries +2
A parametric adaptive physics-informed greedy Latent Space Dynamics Identification (gLaSDI) method is proposed for accurate, efficient, and robust data-driven reduced-order modelin…