Particle Clustering in Turbulence: Prediction of Spatial and Statistical Properties with Deep Learning

Particle Clustering in Turbulence: Prediction of Spatial and Statistical Properties with Deep Learning

We investigate the utility of deep learning for modeling the clustering of particles that are aerodynamically coupled to turbulent fluids. Using a Lagrangian particle module within the Athena++ hydrodynamics code, we simulate the dynamics of particles in the Epstein drag regime within a periodic dom...

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Bibliographic Details
Main Authors: Yan-Mong Chan, Natascha Manger, Yin Li, Chao-Chin Yang, Zhaohuan Zhu, Philip J. Armitage, Shirley Ho
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:The Astrophysical Journal
Subjects:
Hydrodynamical simulations
Protoplanetary disks
Neural networks
Planet formation
Online Access:https://doi.org/10.3847/1538-4357/ad088c

Internet

https://doi.org/10.3847/1538-4357/ad088c

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