1 citations · 1 across the 3 of their papers we have counts for
8 papers
Supergranulation as a Tracer of Solar-Cycle Variability
Irina N. Kitiashvili, Andrew A. Ngo, Spiridon Kasapis
Supergranulation is one of the dominant scales of near-surface solar convection and provides an important diagnostic for studying the interaction between convective flows, rotation…
Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations
Rimsha Hameed Syeda, Dustin Kempton, Viacheslav Sadykov +2
Numerical modeling of solar plasma dynamics is affected by the resolution of the computational grid. This often requires the estimation of subgrid processes related to the small-sc…
Cluster-Weighted Training of Deep Surrogate Models for Subgrid Turbulent Transport
Rimsha Hameed Syeda, Dustin Kempton, Viacheslav Sadykov +2
Turbulence in the solar interior and atmosphere plays a crucial role in energy transport, yet modeling its subgrid-scale effects remains a major challenge. This study leverages mac…
Review of Machine Learning Models for Solar Energetic Particle Prediction
Spiridon Kasapis, Pouya Hosseinzadeh, Kathryn Whitman +73
Solar energetic particle (SEP) events have attracted increasing attention due to their significant radiation hazards for aviation, spacecraft electronics, and human missions beyond…
Prediction of Magnetic Flux Evolution During Solar Active Region Emergence using Long Short-Term Memory Networks
Eren Dogan, Spiridon Kasapis, Sarang Patil +5
Solar active regions (ARs) are the primary drivers of space weather events, making their early prediction crucial for operational forecasting systems. We develop machine learning m…
Machine Learning-Ready Data Sets for the Analysis and Nowcasting of Atmospheric Radiation at Aviation Altitudes
Viacheslav M Sadykov, Zachary M Watkins, Dustin Kempton +10
Nowcasting and forecasting of the radiation environment in the Earth's lower atmosphere are critical for the safety of aircraft and spacecraft crews and passengers. Currently, this…