activity
20202022
most citedThe current state and future directions of modeling thermosphere density enhancements during extreme magnetic storms

30 citations · 40 across the 6 of their papers we have counts for

collaborators

7 papers

physics.space-ph20222 cited

Advanced ensemble modeling method for space object state prediction accounting for uncertainty in atmospheric density

Smriti Nandan Paul, Richard J. Licata, Piyush M. Mehta

For objects in the low Earth orbit region, uncertainty in atmospheric density estimation is an important source of orbit prediction error, which is critical for space situational a…

physics.space-ph20221 cited

Stochastic modeling of physical drag coefficient -- its impact on orbit prediction and space traffic management

Smriti Nandan Paul, Phillip Logan Sheridan, Richard J. Licata +1

Ambitious satellite constellation projects by commercial entities and the ease of access to space in recent times have led to a dramatic proliferation of low-Earth space traffic. I…

physics.space-ph20221 cited

Understanding variability in HASDM to support space traffic management

W. Kent Tobiska, Marcin D. Pilinski, Shaylah Mutschler +5

With more commercial constellations planned, the number of Low Earth Orbit (LEO) objects is set to TRIPLE in two years. The growth in LEO objects directly increases the probability…

cs.LG20223 cited

Uncertainty Quantification Techniques for Space Weather Modeling: Thermospheric Density Application

Richard J. Licata, Piyush M. Mehta

Machine learning (ML) has often been applied to space weather (SW) problems in recent years. SW originates from solar perturbations and is comprised of the resulting complex variat…

physics.space-ph202130 cited

The current state and future directions of modeling thermosphere density enhancements during extreme magnetic storms

Denny M. Oliveira, Eftyhia Zesta, Piyush M. Mehta +4

Satellites, crewed spacecraft and stations in low-Earth orbit (LEO) are very sensitive to atmospheric drag. A satellite's lifetime and orbital tracking become increasingly inaccura…

cs.LG20213 cited

Machine-Learned HASDM Model with Uncertainty Quantification

Richard J. Licata, Piyush M. Mehta, W. Kent Tobiska +1

The first thermospheric neutral mass density model with robust and reliable uncertainty estimates is developed based on the SET HASDM density database. This database, created by Sp…