A new hybrid next-event estimator for photon-based Monte Carlo dose rate calculations

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作者
Ettore Guadagni
Cindy Le Loirec
Yannick Pénéliau
Jean Michel Létang
Davide Mancusi
Cheikh Diop
机构
[1] Cadarache,CEA, DES, IRESNE, DER, Service de Physique des Réacteurs et du Cycle
[2] Cadarache,CEA, IRFM
[3] Univ Lyon,Centre Léon Bérard, CNRS, Inserm, CREATIS UMR 5220 U1206
[4] INSA-Lyon,CEA, Service d’Etudes des Réacteurs et de Mathématiques Appliquées
[5] Université Claude Bernard Lyon 1,undefined
[6] Université Paris-Saclay,undefined
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This work describes the implementation of a deterministic-like straight-line transport routine inside the TRIPOLI-4®\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {TRIPOLI-4}^{\circledR }$$\end{document} Monte Carlo code, aimed at developing a hybrid estimator that can speed up the MC calculation while retaining its precision. The algorithm is based on the exponential track length estimator or eTLE, a next-event estimator that has already been investigated for medical applications. In this implementation, the eTLE is paired with a forced detection algorithm. We describe the implementation of the method in TRIPOLI-4®\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {TRIPOLI-4}^{\circledR }$$\end{document}, then we present the first results obtained over some test cases and compare them with the classic track-length estimator already implemented in TRIPOLI-4®\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {TRIPOLI-4}^{\circledR }$$\end{document}. These results show that the forced detection technique drastically improves the eTLE performance.
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