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RECONSTRUCTION OF CORE OVERHEATING DAMAGE FRACTION BASED ON NEURAL NETWORK METHOD

机译:基于神经网络方法的岩心过热损伤分数重构

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Core damage assessment is of great importance to the emergency response of nuclear power plants. In this paper, the neural network method is introduced into the core damage assessment process. The hydrogen concentration, together with the temperature and pressure in the containment, are taken as the input parameters of the model. With the simulated result of MAAP codes as the sample data, a neural network model is developed to reconstruct the core overheating damage fraction. According to the calculation of the neural network model, the deviations of the reconstructed results are quite small compared with the simulation results, and one of the typical errors is 1.76%. It can be concluded that the model based on neural network method satisfies the analysis accuracy requirements and can be used as a diverse analytical tool in the core damage assessment of nuclear power plant.
机译:核心损害评估对于核电厂的应急响应至关重要。本文将神经网络方法引入到核心损伤评估过程中。氢气浓度以及安全壳中的温度和压力被用作模型的输入参数。以MAAP代码的仿真结果作为样本数据,建立了神经网络模型以重建堆芯过热损伤率。根据神经网络模型的计算,与模拟结果相比,重建结果的偏差很小,典型误差之一为1.76%。可以得出结论,基于神经网络方法的模型满足分析精度要求,可作为核电厂核心损伤评估中的多种分析工具。

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