Kriging 보간법 기반 작업자 피폭방사선량 예측평가 알고리즘 개발
Development of Worker Radiation Dose Prediction and Assessment Algorithm Based on Kriging Interpolation Method
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In the emergency situations at nuclear power plants, the radiation dose of emergency workers shouldbe analyzed to optimize their radiation dose. However, there may be limitations in obtaining all the necessaryinformation for dose assessment during an emergency. In such cases, spatial interpolation can be used to perform adose assessment using relatively easy-to-obtain dose rate measurements. Kriging interpolation is a representativespatial interpolation method that is known to be relatively high accuracy. The purpose of this study is to developthe dose assessment algorithm based on Kriging interpolation method. For this purpose, the Kriging interpolationmethod was analyzed and the algorithm was developed based on it. The dose assessment results of the developedalgorithm were then compared with those of the Microshield computer code for algorithm validation. Theassessment procedure of the developed algorithm is divided into three steps: 1) experimental variogram evaluation,2) theoretical variogram derivation, and 3) performing interpolation. In the experimental variogram evaluation step,the experimental variogram is evaluated using the distance between measurements and the value differences. Thevariogram is normalized by smoothing the distances between measurements. In the theoretical variogram derivationstep, a Gaussian model is used to fit the experimental variogram. In the interpolation step, both the variogram valuesbetween measurements and those between unknown points and measurements are identified. Weight factors forunknown points are derived based on them, and a weighted average is performed. When deriving weight factors, thealgorithm minimizes the bias of the predicted values. The error of dose assessment result of algorithm for Microshieldwas of 5.24%. The error was relatively high in area where the dose rate was close to zero. The results of this studycan be utilized for dose assessment of emergency workers in nuclear power plants.
Abstract
In the emergency situations at nuclear power plants, the radiation dose of emergency workers shouldbe analyzed to optimize their radiation dose. However, there may be limitations in obtaining all the necessaryinformation for dose assessment during an emergency. In such cases, spatial interpolation can be used to perform adose assessment using relatively easy-to-obtain dose rate measurements. Kriging interpolation is a representativespatial interpolation method that is known to be relatively high accuracy. The purpose of this study is to developthe dose assessment algorithm based on Kriging interpolation method. For this purpose, the Kriging interpolationmethod was analyzed and the algorithm was developed based on it. The dose assessment results of the developedalgorithm were then compared with those of the Microshield computer code for algorithm validation. Theassessment procedure of the developed algorithm is divided into three steps: 1) experimental variogram evaluation,2) theoretical variogram derivation, and 3) performing interpolation. In the experimental variogram evaluation step,the experimental variogram is evaluated using the distance between measurements and the value differences. Thevariogram is normalized by smoothing the distances between measurements. In the theoretical variogram derivationstep, a Gaussian model is used to fit the experimental variogram. In the interpolation step, both the variogram valuesbetween measurements and those between unknown points and measurements are identified. Weight factors forunknown points are derived based on them, and a weighted average is performed. When deriving weight factors, thealgorithm minimizes the bias of the predicted values. The error of dose assessment result of algorithm for Microshieldwas of 5.24%. The error was relatively high in area where the dose rate was close to zero. The results of this studycan be utilized for dose assessment of emergency workers in nuclear power plants.