A KD-trees based method for fast radiation source representation for virtual reality dosimetry applications in nuclear safeguards and security

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• 作者：Teó ; filo Moltó ; Caracena^a ; ^{tmolto@gmail.com} ; Eduardo Vendrell Vidal^a ; Joã ; o G.M. Gonç ; alves^b ; Paolo Peerani^b
• 关键词：Simulation ; Dose rate ; Gamma radiation ; Training ; Point kernel
• 刊名：Progress in Nuclear Energy
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：95
• 期：Complete
• 页码：78-83
• 全文大小：1137 K
• 卷排序：95

文摘

With the aim of demonstrating the concrete advantages that novel technologies such as Virtual Reality (VR) can provide to the nuclear industry, the authors of this paper have been working on the development of a VR based simulator of a gamma dose rate detector for training purposes, to be applied in the field of nuclear security and safety.Historically in nuclear science, simulating gamma dose rate transport has had a series of requirements, most importantly the accuracy of the computation. When embedding this dose rate computation in the environment of a VR based application, a second and opposing key requirement appears: real time performance. Meeting this requirement is only possible if a fast method to compute gamma radiation is used.In order to achieve this target the authors have been working in ways of improving the efficiency of the Point-Kernel method by reducing its computational effort. This paper presents the latest step in this pursuit of efficiency; a novel method based on a non-regular kernel approach, combined with a KD-tree based volume division method. Devised to reduce as much as possible the number of points that represent the volume of the source while aiming at retaining sufficient dose computation accuracy.