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Method for Importance based Streamline Generation on the Massive Fluid Dynamics Dataset

대용량 유동해석 데이터에서의 중요도 기반 스트림라인 생성 방법

  • 이중연 (한국과학기술정보연구원 국가슈퍼컴퓨팅본부) ;
  • 김민아 (한국과학기술정보연구원 국가슈퍼컴퓨팅본부) ;
  • 이세훈 (한국과학기술정보연구원 국가슈퍼컴퓨팅본부)
  • Received : 2018.06.01
  • Accepted : 2018.06.20
  • Published : 2018.06.28

Abstract

Streamline generation is one of the most representative visualization methods to analyze the flow stream of fluid dynamics dataset. It is a challenging problem, however, to determine the seed locations for effective streamline visualization. Meanwhile, it needs much time to compute effective seed locations and streamlines on the massive flow dataset. In this paper, we propose not only an importance based method to determine seed locations for the effective streamline placements but also a parallel streamline visualization method on the distributed visualization system. Moreover, we introduce case studies on the real fluid dynamics dataset using GLOVE visualization system to evaluate the proposed method.

Keywords

Flow Visualization;Streamline;Seed Points Selection;Science Technology Contents;Scientific Visualization

Acknowledgement

Supported by : 국가과학기술연구회

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