Predicting continuum breakdown with deep neural networks
The multi-scale nature of gaseous flows poses tremendous difficulties for theoretical and
numerical analysis. The Boltzmann equation, while possessing a wider applicability than …
numerical analysis. The Boltzmann equation, while possessing a wider applicability than …
Structure-Preserving Operator Learning: Modeling the Collision Operator of Kinetic Equations
This work explores the application of deep operator learning principles to a problem in
statistical physics. Specifically, we consider the linear kinetic equation, consisting of a …
statistical physics. Specifically, we consider the linear kinetic equation, consisting of a …
A Deterministic Dynamical Low-rank Approach for Charged Particle Transport
Deterministically solving charged particle transport problems at a sufficient spatial and
angular resolution is often prohibitively expensive, especially due to their highly forward …
angular resolution is often prohibitively expensive, especially due to their highly forward …
[HTML][HTML] Artificial intelligence and machine learning in aerodynamics
With the increasing availability of flow data from simulation and experiment, artificial
intelligence and machine learning are revolutionizing the research paradigm in …
intelligence and machine learning are revolutionizing the research paradigm in …