A simple data assimilation method to improve atmospheric dispersion based on Lagrangian puff model

Ke Li; Weihua Chen; Manchun Liang; Jianqiu Zhou; Yunfu Wang; Shuijun He; Jie Yang; Dandan Yang; Hongmin Shen; Xiangwei Wang

doi:https://doi.org/10.1016/j.net.2021.01.032

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자료유형: 학술저널

저자정보: Ke Li (China Nuclear Power Engineering Co. Ltd) Weihua Chen (China Nuclear Power Engineering Co., Ltd) Manchun Liang (Department of Engineering Physics, Tsinghua University) Jianqiu Zhou (China Nuclear Power Engineering Co., Ltd) Yunfu Wang (China Nuclear Power Engineering Co., Ltd) Shuijun He (Department of Engineering Physics, Tsinghua University) Jie Yang (Beijing Global Safety Technology Co., Ltd) Dandan Yang (Beijing Global Safety Technology Co., Ltd) Hongmin Shen (Beijing Global Safety Technology Co., Ltd) Xiangwei Wang (Department of Engineering Physics, Tsinghua University)

저널정보: 한국원자력학회 Nuclear Engineering and Technology Nuclear Engineering and Technology 제53권 제7호

발행연도: 2021.7

수록면: 2,377 - 2,386 (10page)

DOI: https://doi.org/10.1016/j.net.2021.01.032

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To model the atmospheric dispersion of radionuclides released from nuclear accident is very importantfor nuclear emergency. But the uncertainty of model parameters, such as source term and meteorologicaldata, may significantly affect the prediction accuracy. Data assimilation (DA) is usually used to improvethe model prediction with the measurements. The paper proposed a parameter bias transformationmethod combined with Lagrangian puff model to perform DA. The method uses the transformation ofcoordinates to approximate the effect of parameters bias. The uncertainty of four model parameters isconsidered in the paper: release rate, wind speed, wind direction and plume height. And particle swarmoptimization is used for searching the optimal parameters. Twin experiment and Kincaid experiment areused to evaluate the performance of the proposed method. The results show that the proposed methodcan effectively increase the reliability of model prediction and estimate the parameters. It has theadvantage of clear concept and simple calculation. It will be useful for improving the result of atmosphericdispersion model at the early stage of nuclear emergency

#Nuclear emergency #Atmospheric dispersion model #Data assimilation #Particle swarm optimization #Parameter bias transformation

참고문헌 (25)

참고문헌 신청

IAEA / 2015 / The Fukushima Daiichi Accident

R.L. Lee / 1998 / ARAC-3, A New Modeling System for Real-Time Response and Assessments of Atmospheric release / 10th Joint Conference on the Applications of Air Pollution Meteorology with the A&WMA

J. Ehrhardt / 1997 / The RODOS system: decision support for off-site emergency management in Europe / Radiat. Protect. Dosim 73(1-4):35~40

M. Chino / 1993 / SPEEDI and WSPEEDI : Japanese emergency response systems to predict radiological impacts in local and workplace areas due to a nuclear accident[J] / Radiat. Protect. Dosim 50(2-4):145~152

M. Hutchinson / 2017 / A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors / Inf. Fusion 36:130~148

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