Development and Application of Particle Transport Monte Carlo Simulation Modeling Toolkit
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Published:2023-05-01
Issue:1
Volume:2508
Page:012040
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ISSN:1742-6588
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Container-title:Journal of Physics: Conference Series
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language:
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Short-container-title:J. Phys.: Conf. Ser.
Author:
Shang Peng,Huang Liu-xing,Zhu Jin-hui,Niu Sheng-li,Liu Li
Abstract
Abstract
In particle transport Monte Carlo simulation, the manual modeling method is not suitable for complex geometric models. A Monte Carlo Simulation Modeling Toolkit (pyMCMT) is developed based on Python language. The toolkit can generate input card in several classical format such as MCNP and GDML format automatically. In this paper, two typical applications are presented based on the pyMCMT toolkit: 1, constructing a multilayer circular geometric model in complex density distribution by pyMCMT toolkit in order to satisfy the requirement of building large-space fine model with the influence of blast wave. A two-dimensional adaptive model is built for non-uniform atmospheric induced by blast wave. The number of the cells in this model is reduced vastly with the same model resolution; 2, producing the optimized weight window parameter using the mesh-based weight window variance reduction combined with density iteration method which is realized to solve the high statistical fluctuation and low counting efficiency problem in deep penetration process. The successful application of pyMCMT shows that pyMCMT is a modularized, parameterized, customizable and easy-to-debug toolkit for particle transport Monte Carlo simulation modeling, which can improve the modeling efficiency tremendously.
Subject
Computer Science Applications,History,Education
Reference19 articles.
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2. Study on Monte Carlo Variance Reduction Method for Thick Shield and Small Detector Problem;Gao;Atomic Energy Science and Technology,2020
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