• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to previous page

Construction of novel principle for knowledge discovery in particle methods for fluid dynamics using statistical models

Research Project

Project/Area Number 15H05303
Research Category

Grant-in-Aid for Young Scientists (A)

Allocation TypeSingle-year Grants
Research Field Statistical science
Research InstitutionMeiji University

Principal Investigator

NAKAMURA Kazuyuki  明治大学, 総合数理学部, 専任准教授 (40462171)

Project Period (FY) 2015-04-01 – 2018-03-31
Project Status Completed (Fiscal Year 2017)
Budget Amount *help
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2017: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2016: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2015: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Keywords粒子法 / データ同化 / 統計モデル / ベイズ推定
Outline of Final Research Achievements

In the particle methods for fluid analysis, fluids are represented by many particles and analyzed. In this study, we constructed the framework and principles for the error of the particle methods in the form of distribution through construction of estimation method of prediction errors, measurements of water tank experiments, and evaluation of statistical error. Especially, we obtained the effectiveness of bounded Gaussian and uniform mixture distribution for error model of macroscopic parameters and the effectiveness of the use of heavy-tailed distributions for error distribution. In addition, we obtained visualization results in which we can easily confirm key physical quantities and check the validity of the analysis. We also obtained evaluation results of errors in stochastic cellular automata model and relationship between local noise sensitivity and particle methods analysis.

Report

(4 results)
  • 2017 Annual Research Report   Final Research Report ( PDF )
  • 2016 Annual Research Report
  • 2015 Annual Research Report
  • Research Products

    (14 results)

All 2017 2016 2015

All Journal Article (3 results) (of which Peer Reviewed: 3 results,  Open Access: 2 results,  Acknowledgement Compliant: 2 results) Presentation (10 results) (of which Int'l Joint Research: 2 results,  Invited: 3 results) Book (1 results)

  • [Journal Article] Prediction System of Subway Traffic Flow and Appropriate Parameters Shifting2017

    • Author(s)
      Yutaka Kono, Kazuyuki Nakamura
    • Journal Title

      Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications

      Volume: 2017 Issue: 0 Pages: 168-173

    • DOI

      10.5687/sss.2017.168

    • NAID

      130006192999

    • ISSN
      2188-4730, 2188-4749
    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Fast and stable estimation of macroscopic parameters in particle systems by data assimilation2016

    • Author(s)
      Kazuyuki Nakamura and Yutaka Kono
    • Journal Title

      Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications

      Volume: 2016 Issue: 0 Pages: 132-136

    • DOI

      10.5687/sss.2016.132

    • NAID

      130005277628

    • ISSN
      2188-4730, 2188-4749
    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] Local noise sensitivity: Insight into the noise effect on chaotic dynamics2016

    • Author(s)
      Nina Sviridova and Kazuyuki Nakamura
    • Journal Title

      Chaos

      Volume: 26 Issue: 12 Pages: 123102-123102

    • DOI

      10.1063/1.4970322

    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Presentation] データサイエンスにおける数理と実問題との関係ならびに応用2017

    • Author(s)
      中村和幸
    • Organizer
      スーパーセンシングフォーラム
    • Related Report
      2017 Annual Research Report
    • Invited
  • [Presentation] Application of data assimilation to particle simulation and point process2017

    • Author(s)
      Kazuyuki Nakamura, Yutaka Kono, Noriho Fujioka
    • Organizer
      EcoSta2017
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 動的システムにおける不確かさとデータサイエンス2017

    • Author(s)
      中村和幸
    • Organizer
      日本行動計量学会第45回大会
    • Related Report
      2017 Annual Research Report
  • [Presentation] ベイズ型時系列・時空間解析による自然現象・社会現象の理解2017

    • Author(s)
      中村和幸
    • Organizer
      愛媛大学談話会
    • Related Report
      2017 Annual Research Report
  • [Presentation] データ同化による不確かさを持つ現象の理解と予測ならびにモデリングへの展開2016

    • Author(s)
      中村和幸
    • Organizer
      RIMS研究集会
    • Place of Presentation
      京都
    • Related Report
      2016 Annual Research Report
  • [Presentation] 粒子系物理モデルのマクロパラメータ推定と統計モデリング2016

    • Author(s)
      中村和幸,河野穣
    • Organizer
      2016年度統計関連学会連合大会
    • Place of Presentation
      金沢
    • Related Report
      2016 Annual Research Report
  • [Presentation] アンサンブル型データ同化におけるノイズ項モデリングとマクロパラメータ推定への応用2016

    • Author(s)
      中村和幸
    • Organizer
      第6回理研・京大合同データ同化研究会
    • Place of Presentation
      神戸
    • Related Report
      2016 Annual Research Report
    • Invited
  • [Presentation] Fast and stable estimation of macroscopic parameters in particle systems by data assimilation2015

    • Author(s)
      Kazuyuki Nakamura and Yutaka Kono
    • Organizer
      The 47th ISCIE International Symposium on Stochastic Systems Theory and Its Applications
    • Place of Presentation
      米国ハワイ州
    • Year and Date
      2015-12-07
    • Related Report
      2015 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 静的・動的システムにおける不確かさの定量化2015

    • Author(s)
      中村和幸
    • Organizer
      第22回信頼性設計技術WS & 第35回最適設計研究会
    • Place of Presentation
      岡山
    • Year and Date
      2015-09-14
    • Related Report
      2015 Annual Research Report
    • Invited
  • [Presentation] 粒子法流体解析における誤差統計モデルについて2015

    • Author(s)
      中村和幸
    • Organizer
      2015年度統計関連学会連合大会
    • Place of Presentation
      岡山
    • Year and Date
      2015-09-06
    • Related Report
      2015 Annual Research Report
  • [Book] 統計学2017

    • Author(s)
      中村和幸
    • Total Pages
      224
    • Publisher
      東京図書
    • ISBN
      9784489022579
    • Related Report
      2017 Annual Research Report

URL: 

Published: 2015-04-16   Modified: 2019-03-29  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi