Estimation of Radioactivity Release Activity Using Non-Linear Kalman Filter-Based Estimation Techniques

Victor M. Becerra, Vineet Vajpayee, Nils Bausch, T.V. Santhosh, Gopika Vinod and Jiamei Deng
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Victor M. Becerra: School of Energy and Electronic Engineering, University of Portsmouth, Portsmouth PO1 3DJ, UK
Vineet Vajpayee: School of Energy and Electronic Engineering, University of Portsmouth, Portsmouth PO1 3DJ, UK
Nils Bausch: School of Energy and Electronic Engineering, University of Portsmouth, Portsmouth PO1 3DJ, UK
T.V. Santhosh: Reactor Design & Development Group, Bhabha Atomic Research Centre, Mumbai 400 085, India
Gopika Vinod: Reactor Design & Development Group, Bhabha Atomic Research Centre, Mumbai 400 085, India
Jiamei Deng: School of Built Environment, Engineering, and Computing, Leeds Beckett University, Leeds LS6 3QS, UK

Energies, 2020, vol. 13, issue 15, 1-23

Abstract: The estimation of radioactivity release following an accident in a nuclear power plant is crucial due to its short and long-term impacts on the surrounding population and the environment. In the case of any accidental release, the activity needs to be estimated quickly and reliably to effectively plan a rapid emergency response and design an appropriate evacuation strategy. The accurate prediction of incurred dose rate during normal or accident scenario is another important aspect. In this article, three different non-linear estimation techniques, extended Kalman filter, unscented Kalman filter, and cubature Kalman filter are proposed in order to estimate release activity and to improve the prediction of dose rates. Radionuclide release rate, average wind speed, and height of release are estimated using the dose rate monitors data collected in proximity of the release point. Further, the estimates are employed to improve the prediction of dose rates. The atmospheric dispersion phenomenon of radioactivity release is modelled using the Gaussian plume model. The Gaussian plume model is then employed for the calculation of dose rates. A variety of atmospheric and accident related scenarios for single source and multiple sources are studied in order to assess the efficacy of the proposed filters. Statistical measures have been used in order to validate the performance of the proposed approaches.

Keywords: atmospheric dispersion model; dose rate; estimation technique; gaussian plume model; radioactivity release; extended kalman filter; unscented kalman filter; cubature kalman filter (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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