[HTML][HTML] Thermosphere and satellite drag
S Bruinsma, TD de Wit, T Fuller-Rowell… - Advances in Space …, 2023 - Elsevier
Accurate forecasts of thermosphere densities, realistic calculation of aerodynamic drag, and
propagation of the uncertainty on the predicted orbit positions are required for conjunction …
propagation of the uncertainty on the predicted orbit positions are required for conjunction …
The thermosphere is a drag: The 2022 Starlink incident and the threat of geomagnetic storms to low earth orbit space operations
Abstract On 03 February 2022, SpaceX launched 49 Starlink satellites, 38 of which re‐
entered the atmosphere on or about 07 February 2022 due to unexpectedly high …
entered the atmosphere on or about 07 February 2022 due to unexpectedly high …
Machine‐learned HASDM thermospheric mass density model with uncertainty quantification
A thermospheric neutral mass density model with robust and reliable uncertainty estimates
is developed based on the Space Environment Technologies (SET) High Accuracy Satellite …
is developed based on the Space Environment Technologies (SET) High Accuracy Satellite …
Relativistic electron model in the outer radiation belt using a neural network approach
We present a machine‐learning‐based model of relativistic electron fluxes> 1.8 MeV using a
neural network approach in the Earth's outer radiation belt. The Outer RadIation belt …
neural network approach in the Earth's outer radiation belt. The Outer RadIation belt …
The SET HASDM density database
WK Tobiska, BR Bowman, SD Bouwer, A Cruz… - Space …, 2021 - Wiley Online Library
The SET HASDM density database is available for scientific studies through a SQL database
with open community access. The information in the SET HASDM density database covers …
with open community access. The information in the SET HASDM density database covers …
A deep learning approach to solar radio flux forecasting
The effect of atmospheric drag on spacecraft dynamics is considered one of the predominant
sources of uncertainty in Low Earth Orbit. These effects are characterised in part by the …
sources of uncertainty in Low Earth Orbit. These effects are characterised in part by the …
Uncertainty quantification techniques for data-driven space weather modeling: thermospheric density application
Abstract Machine learning (ML) has been applied to space weather problems with
increasing frequency in recent years, driven by an influx of in-situ measurements and a …
increasing frequency in recent years, driven by an influx of in-situ measurements and a …
Neural networks for operational SYM‐H forecasting using attention and SWICS plasma features
In this work, we present an Artificial Neural Network for operational forecasting of the SYM‐H
geomagnetic index up to 2 hr ahead using the Interplanetary Magnetic Field, the solar wind …
geomagnetic index up to 2 hr ahead using the Interplanetary Magnetic Field, the solar wind …
Deep neural networks with convolutional and LSTM layers for SYM‐H and ASY‐H forecasting
Geomagnetic indices quantify the disturbance caused by the solar activity on a planetary
scale or in particular regions of the Earth. Among them, the SYM‐H and ASY‐H indices …
scale or in particular regions of the Earth. Among them, the SYM‐H and ASY‐H indices …
Qualitative and quantitative assessment of the SET HASDM database
Abstract The High Accuracy Satellite Drag Model (HASDM) is the operational thermospheric
density model used by the US Space Force Combined Space Operations Center. By using …
density model used by the US Space Force Combined Space Operations Center. By using …