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首页> 外文期刊>Journal of Environmental Radioactivity >Site-specific (Multi-scenario) validation of ensemble Kalman filter-based source inversion through multi-direction wind tunnel experiments
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Site-specific (Multi-scenario) validation of ensemble Kalman filter-based source inversion through multi-direction wind tunnel experiments

机译:通过多方向风洞实验对基于集合卡尔曼滤波器的源反演进行特定地点(多场景)验证

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摘要

Source inversion uses air dispersion models and environmental measurements to determine the atmospheric radionuclide release rate, which is critical in formulating an emergency response to nuclear incidents. Because source inversion methods are vulnerable to multiple uncertainties, site-specific validations that consider multiple air dispersion scenarios are important in ensuring their correct implementation. To comprehensively evaluate the ensemble Kalman filter (EnKF) for source inversion, a site-specific validation based on six wind tunnel experiments was performed for a highly heterogeneous nuclear power plant site in China. The six experiments cover the typical meteorology of the site and various topography types, providing abundant air dispersion scenarios for validation. The sensitivity of the EnKF to the initial guess, inflation factor, and positionumber of measurements is also investigated. The results demonstrate that EnKF offers stable convergence and a reasonably bounded error in all experiments. Furthermore, the EnKF is insensitive to the initial guess, inflation factor, and number of measurements. However, it is sensitive to the position of the measurements and the air dispersion scenario. This sensitivity results from the complicated biases in air dispersion models, which highlight the key to improving the performance of EnKF.
机译:源反演使用空气扩散模型和环境测量结果来确定大气中放射性核素的释放速率,这对于制定对核事件的应急响应至关重要。由于源反演方法易受多种不确定因素的影响,因此考虑多种空气扩散场景的针对特定地点的验证对于确保正确实施至关重要。为了全面评估集成卡尔曼滤波器(EnKF)的源反演,针对六座风洞实验对中国一个高度异质的核电站进行了针对特定地点的验证。这六个实验涵盖了站点的典型气象学和各种地形类型,为验证提供了丰富的空气扩散场景。还研究了EnKF对初始猜测,膨胀系数和测量位置/测量次数的敏感性。结果表明,EnKF在所有实验中均提供稳定的收敛性和合理的误差范围。此外,EnKF对初始猜测,膨胀系数和测量次数不敏感。但是,它对测量的位置和空气扩散情况很敏感。这种敏感性源于空气扩散模型中的复杂偏差,这突出了提高EnKF性能的关键。

著录项

  • 来源
    《Journal of Environmental Radioactivity 》 |2019年第2期| 90-100| 共11页
  • 作者单位

    Tsinghua Univ, Key Lab Adv Reactor Engn & Safety, Collaborat Innovat Ctr Adv Nucl Energy Technol, Inst Nucl & New Energy Technol,Minist Educ, Beijing 100084, Peoples R China;

    Tsinghua Univ, Key Lab Adv Reactor Engn & Safety, Collaborat Innovat Ctr Adv Nucl Energy Technol, Inst Nucl & New Energy Technol,Minist Educ, Beijing 100084, Peoples R China;

    Tsinghua Univ, Key Lab Adv Reactor Engn & Safety, Collaborat Innovat Ctr Adv Nucl Energy Technol, Inst Nucl & New Energy Technol,Minist Educ, Beijing 100084, Peoples R China;

    Res Inst Chem Def, Beijing 100000, Peoples R China;

    Tsinghua Univ, Key Lab Adv Reactor Engn & Safety, Collaborat Innovat Ctr Adv Nucl Energy Technol, Inst Nucl & New Energy Technol,Minist Educ, Beijing 100084, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Source inversion; Ensemble Kalman filter; Wind tunnel experiment; Air dispersion model; Sensitivity analysis;

    机译:源反演;集合卡尔曼滤波;风洞实验;空气扩散模型;灵敏度分析;

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