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Virani, S. N.

Publications and source records attributed to Virani, S. N..

Modeling Chandra Space Environment

This paper describes the development of an environmental risk-mitigation tool for the Chandra X-ray Observatory's Advanced CCD Imaging Spectrometer (ACIS). Because exposure to 100-200 keV protons appears to have degraded the front-illuminated CCD's charge transfer inefficiency (CTI), an accurate tool for predicting encounters with magnetospheric regions rich in these particles is required. We implement standard models to predict bow-shock, magnetopause, and plasma-sheet boundaries. Using these models and solar-wind databases compiled from IMP-8 and ACE measurements, we then calculate the probability that Chandra is located in one of these regions, along with predicted particle flux, to arrive at appropriate safing times for the ACIS detector. Finally, we validate this tool by comparing the model's boundary-crossing and proton flux predictions with measurements from Chandra's on-board particle detector and with data from other spacecraft operating in the Earth's magnetosphere.

Blackwell, W. C.

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.

Observed On-Orbit Background of the ACIS Detector on the Chandra X-Ray Observatory

We have analyzed calibration data acquired during the Orbital Activation and Checkout (OAC) phase of the Chandra X-ray Observatory (CXO) mission in order to characterize the background of the Advanced CCD Imaging Spectrometer (ACIS) produced by charged particles and non-cosmic X-rays. The ACIS instrument contains 8 Front-Illuminated (FI) CCDs and 2 Back-Illuminated (BI) CCDs. The FI and BI CCD)s exhibit dramatically different responses to enhancements in the particle flux. The F1 CCDs show relatively little increase in the overall count rate, typical increases are 1 - 3 counts/s; the BI CCDs show large excursions to as high as 100 counts/s. The duration of these intervals of enhanced background are highly variable ranging from 100 s to 5000 s. The spatial distribution of these background events is relatively flat across the power-law. The events produce morphologies which are similar to cosmic X-ray events, so that morphology alone cannot be used as a rejection criterion. We explore the correlation of these times of high background with the data from Chandra's on-board radiation monitor, the EPHIN (Electron, Proton, Helium Instrument particle detector) instrument and archival data from the Advanced Composition Explorer (ACE) satellite. We discuss strategies for observers to identify and exclude times of high background and to model and subtract the background events from their data.

Plucinsky, P. P.