14 citations · 51 across the 12 of their papers we have counts for
13 papers
Physics-Informed Heterogeneous Graph Neural Networks for DC Blocker Placement
Hongwei Jin, Prasanna Balaprakash, Allen Zou +5
The threat of geomagnetic disturbances (GMDs) to the reliable operation of the bulk energy system has spurred the development of effective strategies for mitigating their impacts.…
Preventing mass loss in the standard level set method: New insights from variational analyses
Kaustubh Khedkar, Amirreza Charchi Mamaghani, Pieter Ghysels +2
For decades, the computational multiphase flow community has grappled with mass loss in the level set method. Numerous solutions have been proposed, from fixing the reinitializatio…
An effective preconditioning strategy for volume penalized incompressible/low Mach multiphase flow solvers
Ramakrishnan Thirumalaisamy, Kaustubh Khedkar, Pieter Ghysels +1
The volume penalization (VP) or the Brinkman penalization (BP) method is a diffuse interface method for simulating multiphase fluid-structure interaction (FSI) problems in ocean en…
Deep Learning and Spectral Embedding for Graph Partitioning
Alice Gatti, Zhixiong Hu, Tess Smidt +2
We present a graph bisection and partitioning algorithm based on graph neural networks. For each node in the graph, the network outputs probabilities for each of the partitions. Th…
Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural Networks
Alice Gatti, Zhixiong Hu, Tess Smidt +2
We present a novel method for graph partitioning, based on reinforcement learning and graph convolutional neural networks. Our approach is to recursively partition coarser represen…
Sparse Approximate Multifrontal Factorization with Butterfly Compression for High Frequency Wave Equations
Yang Liu, Pieter Ghysels, Lisa Claus +1
We present a fast and approximate multifrontal solver for large-scale sparse linear systems arising from finite-difference, finite-volume or finite-element discretization of high-f…