Improvement of doses rate prediction using the Kalman Filter-based algorithm and effective decay constant correction
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초록
This study proposes an algorithm that combines a Kalman Filter method with effective decay constant correction to improve the accuracy of predicting radiation dose rate distribution during emergencies. The algorithm addresses the limitations of relying solely on measurement data by incorporating calculation data and refining the estimations. The effectiveness of algorithm was assessed using hypothetical test scenarios, which demonstrated a significant improvement in the accuracy of dose rate prediction compared to the model predictions. The estimates generated by the algorithm showed a good agreement with the measured data, and the discrepancies tend to decrease over time. Furthermore, the application of the effective decay constant correction accelerated the reduction of prediction errors. In conclusion, it was confirmed that the combined use of the Kalman filter method and effective decay constant correction is an effective approach to improve the accuracy of dose rate prediction.
Abstract
This study proposes an algorithm that combines a Kalman Filter method with effective decay constant correction to improve the accuracy of predicting radiation dose rate distribution during emergencies. The algorithm addresses the limitations of relying solely on measurement data by incorporating calculation data and refining the estimations. The effectiveness of algorithm was assessed using hypothetical test scenarios, which demonstrated a significant improvement in the accuracy of dose rate prediction compared to the model predictions. The estimates generated by the algorithm showed a good agreement with the measured data, and the discrepancies tend to decrease over time. Furthermore, the application of the effective decay constant correction accelerated the reduction of prediction errors. In conclusion, it was confirmed that the combined use of the Kalman filter method and effective decay constant correction is an effective approach to improve the accuracy of dose rate prediction.
참고문헌 (4)
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- R. E. Kalman, "A new approach to linear filtering and prediction problem", Journal of Basic Engineering, 82(1) (1960)[DOI]
- D. Sun, "Spatial and temporal prediction of radiation dose rates near Fukushima Daiichi nuclear power plant", J. Environ. Radioact, 251–252, pp.106946~ (2022)
- L. Ke, "A simple data assimilation method to improve atmospheric dispersion based on Lagrangian puff model", Nucl. Eng. Technol, 53(7), pp.2377~2386 (2021)