Improvement of doses rate prediction using the Kalman Filter-based algorithm and effective decay constant correction

Bibliographic Details
Title: Improvement of doses rate prediction using the Kalman Filter-based algorithm and effective decay constant correction
Authors: Cheol-Woo Lee, Hyo Jun Jeong, Sol Jeong, Moon Hee Han
Source: Nuclear Engineering and Technology, Vol 56, Iss 7, Pp 2659-2665 (2024)
Publisher Information: Elsevier, 2024.
Publication Year: 2024
Collection: LCC:Nuclear engineering. Atomic power
Subject Terms: Dose precition, Dose map, Kalman filter, Data assimilation, Effective decay constant, Nuclear engineering. Atomic power, TK9001-9401
More Details: This study proposes an algorithm that combines a Kalman Filter method with effective decay constant correction to improve the accuracy of predicting radiation dose rate distribution during emergencies. The algorithm addresses the limitations of relying solely on measurement data by incorporating calculation data and refining the estimations.The effectiveness of algorithm was assessed using hypothetical test scenarios, which demonstrated a significant improvement in the accuracy of dose rate prediction compared to the model predictions.The estimates generated by the algorithm showed a good agreement with the measured data, and the discrepancies tend to decrease over time. Furthermore, the application of the effective decay constant correction accelerated the reduction of prediction errors. In conclusion, it was confirmed that the combined use of the Kalman filter method and effective decay constant correction is an effective approach to improve the accuracy of dose rate prediction.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1738-5733
Relation: http://www.sciencedirect.com/science/article/pii/S1738573324000858; https://doaj.org/toc/1738-5733
DOI: 10.1016/j.net.2024.02.025
Access URL: https://doaj.org/article/c4cee5c47e72423a8ac84eb7e5d2f3d0
Accession Number: edsdoj.4cee5c47e72423a8ac84eb7e5d2f3d0
Database: Directory of Open Access Journals
More Details
ISSN:17385733
DOI:10.1016/j.net.2024.02.025
Published in:Nuclear Engineering and Technology
Language:English