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Fast On-Line Source Term Estimation of Non-Constant Releases in Nuclear Accident Scenario Using Extended Kalman Filter

[+] Author Affiliations
Pierre Tricard, Sheng Fang, Jianlong Wang, Hong Li, Jingyuan Qu, Jiejuan Tong, Dong Fang

Tsinghua University, Beijing, China

Paper No. ICONE21-15125, pp. V003T06A004; 7 pages
  • 2013 21st International Conference on Nuclear Engineering
  • Volume 3: Nuclear Safety and Security; Codes, Standards, Licensing and Regulatory Issues; Computational Fluid Dynamics and Coupled Codes
  • Chengdu, China, July 29–August 2, 2013
  • Conference Sponsors: Nuclear Engineering Division
  • ISBN: 978-0-7918-5580-5
  • Copyright © 2013 by ASME


In nuclear accidents, source estimation methods can be used to assess the amount and status of radioactive materials emission, which is important for nuclear emergency response. Current studies primarily focus on source estimation of a constant release mode, which may not match real nuclear accident scenario.

To solve this problem, a fast on-line source term estimation method for non-constant release mode was proposed in this study. Based on the well-established RIMPUFF dispersion model, the extended Kalman filter algorithm was utilized to perform an online estimation of the total amount and height of the release source simultaneously. To simulate the accidental radioactive release mode, a non-constant function was used as the state description of the release source. Both air dispersion model error and measurement error were considered. To demonstrate the feasibility of the proposed method, twin experiments were performed with release profiles. A sensitivity study was also performed to assess the robustness of the algorithm.

The experiment results demonstrate that the proposed method can provide robust source term estimation for both constant and non-constant release. The estimation accuracy depends on the steepness of the curve in the growth of the release mode and the distribution of simulated monitors.

Copyright © 2013 by ASME



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