کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10694338 | 1020037 | 2014 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A model for predicting the radiation exposure for mission planning aboard the international space station
ترجمه فارسی عنوان
یک مدل برای پیش بینی تابش برای برنامه ریزی ماموریت در ایستگاه فضایی بین المللی
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
علوم فضا و نجوم
چکیده انگلیسی
The International Space Station Cosmic Radiation Exposure Model (ISSCREM) has been developed as a possible tool for use in radiation mission planning as based on operational data collected with a tissue equivalent proportional counter (TEPC) aboard the ISS since 2000. It is able to reproduce the observed trapped radiation and galactic cosmic radiation (GCR) contributions to the total dose equivalent to within ±20% and ±10%, respectively, as would be measured by the onboard TEPC at the Zvezda Service Module panel 327 (SM-327). Furthermore, when these contributions are combined, the total dose equivalent that would be measured at this location is estimated to within ±10%. The models incorporated into ISSCREM correlate the GCR dose equivalent rate to the cutoff rigidity magnetic shielding parameter and the trapped radiation dose equivalent rate to atmospheric density inside the South Atlantic Anomaly. The GCR dose equivalent rate is found to vary minimally with altitude and TEPC module location however, due to the statistics and data available, the trapped radiation model could only be developed for the TEPC located at SM-327. Evidence of the variation in trapped radiation dose with detector orientation and the East-West asymmetry were observed at this location.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Space Research - Volume 53, Issue 7, 1 April 2014, Pages 1125-1134
Journal: Advances in Space Research - Volume 53, Issue 7, 1 April 2014, Pages 1125-1134
نویسندگان
Samy El-Jaby, Brent J. Lewis, Leena Tomi,