Prediction of reactor vessel water level using GMDH in severe accidents due to LOCA

Soon Ho Park, Jae Hwan Kim, M. Na
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引用次数: 1

Abstract

In certain circumstances of the severe accident, it is essential to confirm major parameters of a nuclear power plant. The reason of confirmation is to check the status of a nuclear power plant and to respond appropriately to each situation. Particularly, the reactor vessel water level is important data in order to confirm the reactor core condition. Therefore, in preparation for the uncertainty of a sensor in severe accident situations, the reactor vessel water level was predicted using a group method of data handling (GMDH) algorithm. The prediction model of a reactor vessel water level was developed based upon numerical simulation data such as development data and test data. These data were generated by simulating the severe accidents of a total of 810 cases using MAAP4 code about the OPR1000 nuclear power plant. As a result of predictions, the prediction performance of the developed GMDH model was quite satisfactory. Therefore, the developed GMDH model could be successfully applied for providing effective information for operators in severe accident situations.
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利用GMDH预测因LOCA引起的重大事故反应堆容器水位
在某些严重事故的情况下,确定核电站的主要参数是必要的。确认的原因是为了检查核电站的状态,并对每种情况作出适当的反应。其中,反应堆容器水位是确定堆芯状态的重要数据。因此,为了应对传感器在严重事故情况下的不确定性,采用数据处理分组方法(GMDH)算法对反应堆容器水位进行了预测。基于研制数据和试验数据等数值模拟数据,建立了反应堆容器水位预测模型。这些数据是利用MAAP4程序对OPR1000核电站共810例严重事故进行模拟得出的。预测结果表明,所建立的GMDH模型具有较好的预测效果。因此,所建立的GMDH模型可以成功地应用于在严重事故情况下为操作人员提供有效的信息。
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