Parallel computing method of Monte Carlo criticality calculation based on bi-directional traversal

LI Jing; SONG Jing; LONG Pengcheng; LIU Hongfei; JIANG Ping

doi:10.11889/j.0253-3219.2015.hjs.38.060602

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Parallel computing method of Monte Carlo criticality calculation based on bi-directional traversal

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- Parallel computing method of Monte Carlo criticality calculation based on bi-directional traversal
- NUCLEAR TECHNIQUES Vol. 38, Issue 6, Article number: 060602(2015)
- 作者机构：
  
  1. 合肥工业大学数学学院,合肥,230009
  2. 中国科学院核能安全技术研究所中国科学院中子输运理论与辐射安全重点实验室,合肥,230031
- 作者简介：
- 基金信息：
- DOI：10.11889/j.0253-3219.2015.hjs.38.060602
  CLC：
- Published：05 June 2015
- 稿件说明：
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LI Jing, SONG Jing, LONG Pengcheng, et al. Parallel computing method of Monte Carlo criticality calculation based on bi-directional traversal[J]. Nuclear techniques, 2015, 38(6): 060602
DOI：

LI Jing, SONG Jing, LONG Pengcheng, et al. Parallel computing method of Monte Carlo criticality calculation based on bi-directional traversal[J]. Nuclear techniques, 2015, 38(6): 060602 DOI： 10.11889/j.0253-3219.2015.hjs.38.060602.

摘要

在基于蒙特卡罗粒子输运方法的反应堆模拟中，如裂变堆、聚变裂变混合堆等，达到可接受的统计误差需要大量的计算时间，这已成为蒙特卡罗方法的挑战问题之一，需通过并行计算技术解决。为解决现有方法中通信死锁的问题并保证负载均衡性，设计了基于双向遍历的临界计算并行算法。该方法基于超级蒙特卡罗核计算仿真软件系统SuperMC进行实现，以池式钠冷快堆BN600基准模型进行验证，并与MCNP进行对比。测试结果表明，串行和并行计算结果一致，且SuperMC并行效率高于MCNP。

Abstract

Background: It requires much computational time with acceptable statistics errors in reactor simulations including fission reactors and fusion-fission hybrid reactors

which has become one challenge of the Monte Carlo method. Purpose: In this paper

an efficient parallel computing method was presented for resolving the communication deadlock and load balancing problem of current methods. Methods: The parallel computing method based on bi-directional traversal of criticality calculation was implemented in super Monte Carlo simulation program (SuperMC) for nuclear and radiation process. The pool-type sodium cooled fast reactor BN600 was proposed for benchmarking and was compared with MCNP. Results: Results showed that the parallel method and un-parallel methods were in agreement with each other. Conclusion: The parallel efficiency of SuperMC is higher than that of MCNP

which demonstrates the accuracy and efficiency of the parallel computing method. Abstract

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