31 citations · 119 across the 6 of their papers we have counts for
6 papers
Machine Learning Product State Distributions from Initial Reactant States for a Reactive Atom-Diatom Collision System
Julian Arnold, Juan Carlos San Vicente Veliz, Debasish Koner +3
A machine learned (ML) model for predicting product state distributions from specific initial states (state-to-distribution or STD) for reactive atom-diatom collisions is presented…
A General Drag Coefficient for Flow over a Sphere
Narendra Singh, Michael Kroells, Chenxi Li +4
A generalized physics-based expression for the drag coefficient of spherical particles moving in a fluid is derived. The proposed correlation incorporates essential rarefied physic…
Machine Learning for Observables: Reactant to Product State Distributions for Atom-Diatom Collisions
Julian Arnold, Debasish Koner, Silvan Käser +3
Machine learning-based models to predict product state distributions from a distribution of reactant conditions for atom-diatom collisions are presented and quantitatively tested.…
Non-Boltzmann Vibrational Energy Distributions and Coupling to Dissociation Rate
Narendra Singh, Thomas Schwartzentruber
In this article, we propose a generalized model for nonequilibrium vibrational energy distribution functions. The model can be used, in place of equilibrium (Boltzmann) distributio…
Consistent Kinetic-Continuum Dissociation Model II: Continuum Formulation and Verification
Narendra Singh, Thomas Schwartzentruber
In this article, we implement a recently developed non-equilibrium chemical kinetics model \cite{singhmodeldevelopment2019} based on \textit{ab initio} simulation data and perform…
Consistent Kinetic-Continuum Dissociation Model I: Kinetic Formulation
Narendra Singh, Thomas Schwartzentruber
In this article, we propose a generalized non-equilibrium chemical kinetics model from \textit{ab initio} simulation data obtained using accurate potential energy surfaces develope…