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Results for “Van Allen belts”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1965

Scientific Findings from Explorer VI

Scientific data acquired by Explorer satellite measurements - astronomy and celestial mechanics, ionospheric physics, and energetic particles in Van Allen belt and magnetic fields

VAN ALLEN BELT↗
NASA NTRS2005

The Radiation Environment for the LISA/Laser Interferometry Space Antenna

The purpose of this document is to define the radiation environment for the evaluation of degradation due to total ionizing and non-ionizing dose and of single event effects (SEES) for the Laser Interferometry Space Antenna (LISA) instruments and spacecraft. The analysis took into account the radiation exposure for the nominal five-year mission at 20 degrees behind Earth's orbit of the sun, at 1 AU (astronomical unit) and assumes a launch date in 2014. The transfer trajectory out to final orbit has not yet been defined, therefore, this evaluation does not include the impact of passing through the Van Allen belts. Generally, transfer trajectories do not contribute significantly to degradation effects; however, single event effects and deep dielectric charging effects must be taken into consideration especially if critical maneuvers are planned during the van Allen belt passes.

Barth, Janet L.↗
NASA NTRS1966

Trapped-radiation detectors

Trapped radiation detectors for use on Mariner IV to measure radiation belts in vicinity of Mars and remeasure Van Allen belts and interplanetary cosmic rays

MARINER IV SPACE PROBE↗
NASA NTRS1965

Final Report on the Relay I Program

Relay I satellite program to carry out communications experiments with spacecraft, to detect radiation particles in Van Allen belt, and to determine radiation damage to components.

VAN ALLEN BELT↗
NASA NTRS2000

Chandra X-Ray Observatory's Radiation Environment and the AP-8/AE-8 Model

The Chandra X-ray Observatory (CXO) was launched on July 23, 1999 and reached its final orbit on August 7, 1999. The CXO is in a highly elliptical orbit, approximately 140,000 km x 10,000 km, and has a period of roughly 63.5 hours (approx. 2.6 days). It transits the Earth's Van Allen belts once per orbit during which no science observations can be performed due to the high radiation environment. The Chandra X-ray Observatory Center (CXC) currently uses the National Space Science Data Center's "near Earth" AP-8/AE-8 radiation belt model to predict the start and end times of passage through the radiation belts. However, our scheduling software only uses a simple dipole model of the Earth's magnetic field. The resulting B, L magnet coordinates, do not always give sufficiently accurate predictions of the start and end times of transit of the Van Allen belts. We show this by comparing to the data from Chandra's on-board radiation monitor, the EPHIN (Electron, Proton, Helium Instrument particle detector) instrument. We present evidence that demonstrates this mis- of the radiation belts as well as data that also demonstrate the significant variability of one radiation belt transit to the next as experienced by the CXO. We present an explanation for why the dipole implementation of the AP-8/AE-8 gives inaccurate results. We are also investigating use of the Magnetospheric Specification and Forecast Model (MSM) - a model that also accounts for radiation belt variability and geometry.

Virani, S. N.↗
NASA NTRS2016

A Neural Network Approach for Identifying Particle Pitch Angle Distributions in Van Allen Probes Data

Analysis of particle pitch angle distributions (PADs) has been used as a means to comprehend a multitude of different physical mechanisms that lead to flux variations in the Van Allen belts and also to particle precipitation into the upper atmosphere. In this work we developed a neural network-based data clustering methodology that automatically identifies distinct PAD types in an unsupervised way using particle flux data. One can promptly identify and locate three well-known PAD types in both time and radial distance, namely, 90deg peaked, butterfly, and flattop distributions. In order to illustrate the applicability of our methodology, we used relativistic electron flux data from the whole month of November 2014, acquired from the Relativistic Electron-Proton Telescope instrument on board the Van Allen Probes, but it is emphasized that our approach can also be used with multiplatform spacecraft data. Our PAD classification results are in reasonably good agreement with those obtained by standard statistical fitting algorithms. The proposed methodology has a potential use for Van Allen belt's monitoring.

Souza, V. M.↗