Random coincidence and angular correlation corrections in the sum-peak method using Monte Carlo simulations. (February 2021)
- Record Type:
- Journal Article
- Title:
- Random coincidence and angular correlation corrections in the sum-peak method using Monte Carlo simulations. (February 2021)
- Main Title:
- Random coincidence and angular correlation corrections in the sum-peak method using Monte Carlo simulations
- Authors:
- Nemeš, T.
Mrdja, D.
Bikit, I. - Abstract:
- Abstract: The sum-peak method is a technique for measuring the absolute activity of gamma cascade emitting sources with a single gamma spectrometer. The effects of angular correlations and random coincidences, if not taken into account, can significantly reduce the accuracy of the method. However, we show that Monte Carlo simulations can reproduce the spectral data with a sufficient quality to perform the required corrections. In this work, we introduced a novel approach for data corrections for angular correlations and pile-up using Monte Carlo simulations. Furthermore, the new method for forming the count rate equations leads to a new formula for the sum-peak method, including random coincidences of any order. Highlights: A novel approach using Monte Carlo simulations is developed for spectral data corrections due to pile-up and the angular correlations. A new formula for the sum peak method including random coincidences of any order is deduced. The method is verified by the activity measurement of the 60 Co source.
- Is Part Of:
- Applied radiation and isotopes. Volume 168(2021)
- Journal:
- Applied radiation and isotopes
- Issue:
- Volume 168(2021)
- Issue Display:
- Volume 168, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 168
- Issue:
- 2021
- Issue Sort Value:
- 2021-0168-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-02
- Subjects:
- Random coincidences -- Pile-up -- Angular correlations -- Monte Carlo simulations -- Sum-peak
Radiology -- Periodicals
Radiation -- Industrial applications -- Periodicals
Nuclear chemistry -- Periodicals
Internet resource
Periodical
660.298 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09698043 ↗
http://catalog.hathitrust.org/api/volumes/oclc/27456684.html ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.apradiso.2020.109557 ↗
- Languages:
- English
- ISSNs:
- 0969-8043
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1576.565000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 15410.xml