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Method of quick geometric processing for Monte-Carlo particle transport on basis of spatial grid partitioning

A space grid and particle transport technology, applied in complex mathematical operations, etc., can solve problems such as restricted efficiency and low geometric processing efficiency

Active Publication Date: 2015-01-28
HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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Problems solved by technology

Therefore, frequent particle spatial positioning and geometric step calculations are important reasons for time-consuming calculations during Monte Carlo particle transport simulations.
[0004] For the traditional Monte Carlo particle transport geometry processing method, it is usually necessary to traverse all the geometry in the entire model when performing particle spatial positioning, and the time complexity of the processing is O(N), so for Monte Carlo particle When transport geometry deals with large-scale complex geometric models, such as the million-level Pin-by-Pin model of a nuclear reactor, its geometric processing efficiency will be very low, which seriously restricts the efficiency of Monte Carlo particle transport calculations, and has become a Monte Carlo model. One of the bottlenecks in the development of Luo particle transport calculation method to engineering practice

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  • Method of quick geometric processing for Monte-Carlo particle transport on basis of spatial grid partitioning
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  • Method of quick geometric processing for Monte-Carlo particle transport on basis of spatial grid partitioning

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Embodiment Construction

[0049] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0050] A fast geometric processing method for Monte Carlo particle transport based on spatial grid division:

[0051] 1. Calculate the axial bounding box of each geometry in the geometric model:

[0052] The bounding box method is already a very mature method in computer graphics, so the present invention can directly use the internationally developed three-dimensional solid modeling software ACIS to calculate the axial bounding box of each geometry in the geometric model.

[0053] The first step is to create a 3D solid geometry model. like figure 1 As shown, 1 is the geometric model to be processed, and 2 is the filled geometry distributed in the geometric model; according to the size data file of each geometry in the geometric model given by the user, the solid model of each geometry is sequentially created in the ACIS software. , the size d...

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Abstract

The invention discloses a method of quick geometric processing for Monte-Carlo particle transport on basis of spatial grid partitioning and provides a cost function based spatial grid partitioning method on basis of the concept of spatial grid partitioning according to features of geometric processing of Monte-Carlo particle transport. According to the principle of minimum cost, a three-dimensional geometric model is subjected to spatial grid partitioning sequentially according to coordinate axes, geometries included in grids are determined when the cost is minimum, and a spatial grid model finally obtained is an optimal model. When the optimal model is applied to geometric processing of Monte-Carlo particle transport, spatial grid positioning can be performed fast according to particle spatial coordinates, the geometries included in the grids are traversed then, the number of candidate geometries to be searched for is greatly reduced, the geometries where particles locate can be determined fast, analog computation of Monte-Carlo particle transport is accelerated, and efficiency in geometric processing of Monte-Carlo particle transport is improved.

Description

technical field [0001] The invention relates to a fast geometric processing method for Monte Carlo particle transport based on space grid division, and belongs to the research field of Monte Carlo particle transport calculation and numerical simulation in nuclear science. Background technique [0002] The Monte Carlo particle transport method is based on statistical theory, a non-deterministic method to solve the particle transport equation by stochastic simulation of a large number of particle physical events and physical processes with stochastic properties. It is widely used in reactors. Physics, medical physics, high energy physics and nuclear detection and other fields. Compared with the traditional deterministic method, the biggest advantage of the Monte Carlo particle transport method is that it can describe the characteristics and processes of things with random properties very realistically, and has little restrictions on geometric models and materials, and can accu...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/10
Inventor 陈珍平宋婧吴斌郑华庆吴宜灿
Owner HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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