拉格朗日烟团模型的大气扩散系数自适应修正

Diffusion Coefficient Adaptive Correction in Lagrangian Puff Model

在核事故后果实时评价系统中,拉格朗日烟团模型作为大气扩散模型得到了广泛应用。大气扩散系数是影响烟团模型的重要参数之一,本文提出一种动态修正拉格朗日烟团模型的大气扩散系数的自适应方法,以提高放射性核素浓度分布计算的准确性。该方法利用观测的核素浓度数据、气象数据和源项释放数据,以最小二乘法实时地对大气扩散系数进行了估计。使用大气扩散模型验证工具MVK中的Kincaid实验数据,将动态大气扩散系数自适应修正方法与传统的以Pasquill-Gifford(P-G)曲线为基础的方法相比较,结果表明,大气扩散系数自适应修正方法能提高拉格朗日烟团模型计算结果的准确性。

Lagrangian puff model is widely used in the decision support system for nuclear emergency management .The diffusion coefficient is one of the key parameters impacting puff model .An adaptive method was proposed in this paper ,which could correct the diffusion coefficient in Lagrangian puff model ,and it aimed to improve the accuracy of calculating the nuclide concentration distribution . This method used detected concentration data , meteorological data and source release data to estimate the actual diffusion coefficient with least square method .The diffusion coefficient adaptive correction method was evaluated by Kincaid data in MVK ,and was compared with traditional Pasquill-Gifford （P-G ） diffusion scheme method .The results indicate that this diffusion coefficient adaptive correction method can improve the accuracy of Lagrangian puff model .