Application of Parallel Processing to PWR Plant Predictive Simulator

Kazunori Sasaki, Hiroo Kanamaru, Hironori Kasahara, Seinosuke Narita

Research output: Contribution to journalArticle

Abstract

A parallelism analysis integrated system(PARIS) with an MIMD multiprocessor scheme has been developed to analyze a simulation program which can execute anomaly effect prediction in nuclear power plants and to make the simulation program for parallel processing. The PARIS system analyzes task parallelism and processing time of each task when a user divides a program developed for a single processor into many tasks that are the elementary assignment units. Next, this system assigns tasks to processors using the static scheduling algorithm CP/ MISF to minimize the overall processing time, and makes a parallel execution program which can be executed with a tightly coupled multiprocessor. The PARIS system was assessed by nuclear power plant analyzer code (NUPAC-1) consisting of a reactor coolant system model, a steam generator model and so forth. the results showed that processing time of NUPAC-1 with 7 processors was 3.5 times as fast as with a single processor, and fast running capability was 4.8 times as fast as the real physical time even in accident analyses such as small LOCA. Furthermore, the results showed the PARIS system with the MIMD multiprocessor scheme on the tightly coupled multiprocessor to be efficient for realizing the predictive simulator.

Original languageEnglish
Pages (from-to)1009-1022
Number of pages14
JournalNippon Genshiryoku Gakkaishi/Journal of the Atomic Energy Society of Japan
Volume32
Issue number10
DOIs
Publication statusPublished - 1990
Externally publishedYes

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Keywords

  • multi instruction multi data
  • operator support system
  • parallel processing
  • power plants
  • prediction
  • PWR type reactors
  • scheduling algorithm
  • simulation codes
  • simulators
  • thermal hydraulic model
  • tightly coupled multiprocessor

ASJC Scopus subject areas

  • Nuclear Energy and Engineering

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