2018 Fiscal Year Final Research Report
Development of a quick atmospheric dispersion calculation method in emergency responses to nuclear accidents
| Project/Area Number |
16K01341
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Natural disaster / Disaster prevention science
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| Research Institution | Japan Atomic Energy Agency |
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Principal Investigator |
nakayama hiromasa 国立研究開発法人日本原子力研究開発機構, 原子力科学研究部門 原子力科学研究所 原子力基礎工学研究センター, 研究副主幹 (50535903)
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| Research Collaborator |
Takemi Tetsuya
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Keywords | 大気拡散 / 大気乱流 / 原子力緊急時 / 数値シミュレーション / 局所域 / 重合法 / 即時評価 |
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| Outline of Final Research Achievements |
We propose, in emergency response to nuclear accidents, a practical and quick local-scale atmospheric dispersion calculation method using an overlapping technique. First, we pre-calculated plume dispersion around an actual nuclear facility under idealized atmospheric conditions with 36 wind-direction cases and made a dataset of mean concentrations for each wind direction case. Then, we conducted LESs of plume dispersion under realistic atmospheric conditions using the meteorological data and estimated the spatial distributions of the 1-hour averaged concentrations by overlapping the precalculated concentration data depending on the frequency of the mean wind directions. It is shown that the concentration distribution patterns are well reproduced in comparison to those under the realistic conditions. It is concluded that the atmospheric dispersion calculation method using the overlapping technique has potentially a high performance in emergency responses to nuclear accidents.
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| Free Research Field |
大気拡散
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| Academic Significance and Societal Importance of the Research Achievements |
大気拡散予測手法として、主に、正規分布型プルームモデルと計算流体力学モデルの2つの手法が挙げられる。前者は、簡易拡散方程式に基づく手法であるため、迅速かつ低コストで予測できるが、局所地形や建物の影響を厳密に考慮できないため、正確さに問題がある。一方、後者は地表面起伏や建物の影響を考慮して拡散予測を行えるが、計算負荷は高い。そのため、計算精度を追及すれば計算時間も増大するというトレードオフ問題が生じていた。本研究で開発した手法は、迅速かつ高い精度で拡散予測を行うことができ、従来のトレードオフ問題の概念を覆した画期的な緊急時対応が可能となる。
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