Analysis of The Influence of Models of Individual Physical Processes and Phenomena on the Calculation Time of the Source Term in Severe Accidents

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Resumo

Dependence of the CPU time needs for calculation of the source term during a severe accident at nuclear power plants with WWER reactors from the individual physical processes and phenomena used as part of the calculation tools similar to the SOСRAT/V3 severe accident code is investigated. This analysis allows revealing the most expensive models in terms of runtime. The simplification of these models can ensure the greatest acceleration of the calculation. The relevance of the task draws from the need to develop new or adapt existing calculation tools for assessing the intensity of radioactive emission sources for the tasks of emergency preparedness and response considering the specific requirements for the accuracy of numerical estimates and time to obtain them. The paper demonstrates the possibility of reducing CPU time without significant loss of accuracy of the numerical estimates by simplifying the spectrum of aerosols sizes. The efficiency of the proposed approach is demonstrated by the example of modeling the Phebus FPT1 experiment.

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Sobre autores

M. Philippov

Nuclear Safety Institute of the Russian Academy of Sciences (IBRAE RAN)

Email: delovami@ibrae.ac.ru
Rússia, Moscow

M. Delova

Nuclear Safety Institute of the Russian Academy of Sciences (IBRAE RAN)

Autor responsável pela correspondência
Email: delovami@ibrae.ac.ru
Rússia, Moscow

K. Dolganov

Nuclear Safety Institute of the Russian Academy of Sciences (IBRAE RAN)

Email: delovami@ibrae.ac.ru
Rússia, Moscow

A. Kiselev

Nuclear Safety Institute of the Russian Academy of Sciences (IBRAE RAN)

Email: delovami@ibrae.ac.ru
Rússia, Moscow

S. Krasnoperov

Nuclear Safety Institute of the Russian Academy of Sciences (IBRAE RAN)

Email: delovami@ibrae.ac.ru
Rússia, Moscow

V. Semenov

Nuclear Safety Institute of the Russian Academy of Sciences (IBRAE RAN)

Email: delovami@ibrae.ac.ru
Rússia, Moscow

D. Tomashchik

Nuclear Safety Institute of the Russian Academy of Sciences (IBRAE RAN)

Email: delovami@ibrae.ac.ru
Rússia, Moscow

Bibliografia

  1. Hage M., Kowalik M., Sören J., Löffler H. Source Term Prediction Software in Case of Severe Accidents: FaSTPro for Shutdown States, Probabilistic Safety Assessment and Management PSAM 14, September 2018, Los Angeles, CA.
  2. Knochenhauer M., Hedtjärn Swaling V., Alfheim P. Using Bayesian Belief Network (BBN) Modelling for Rapid Source Term Prediction – RASTEP Phase 1, NKS-267, NKS, September 2012.
  3. McKenna T.J., Giitter J.G. Source Term Estimation during Incident Response to Severe Nuclear Power Plant Accidents, NUREG-1228, U.S. Nuclear Regulatory Commission, Washington DC, 1988.
  4. Herviou K. Development of a methodology and of a computer tool for source term estimation in case of nuclear emergency in a light water reactor (ASTRID), CONTRACT FIKR – CT-2001–00171, Report ASTRID/04.39 v1.1, January 2005.
  5. Bolshov L.A., Dolganov K.S., Kiselev A.E., Strizhov V.F. Results of SOCRAT code development, validation and applications for NPP safety assessment under severe accidents, Nuclear Engineering and Design, Volume 341, 2019. P. 326–345.
  6. Uncertainty analyses using the MELCOR severe accident code. In: Evaluation of uncertainties in relation to severe accidents and level 2 probabilistic safety analysis. Workshop proceedings. Aix-en-Provence –Randall O. Gauntt – 2005. https://www.irsn.fr/EN/Research/publications-documentation/Publications/DPAM/SEMIC/Pages/Fission-product-transport-modelling-in-the-ASTEC-integral-code-SOPHAEROS-module-3008.aspx
  7. Final Report FPT1, CD-ROM.
  8. March P., Simondi-Teisseire B. Overview of the facility and experiments performed in Phébus FP, Annals of Nuclear Energy, V. 61 (2013), P. 11–22.
  9. Validation of severe accident codes against Phebus FP for plant applications: Status of the PHEBEN2 project, Nuclear engineering and design 221, April 2003, P. 225–240.

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2. Fig. 1. Schematic representation of the Phebus installation.

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3. Fig. 2. Fuel temperature at the level of 400 mm in the Phebus FPT1 experiment.

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4. Fig. 3. Integral hydrogen production in the Phebus FPT1 experiment.

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5. Fig. 4. Linear density of 137Cs isotope activity in hot and cold filaments in the Phebus FPT1 experiment.

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6. Fig. 5. Linear activity density of isotope 131I in hot and cold filaments in the Phebus FPT1 experiment.

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7. Fig. 6. The integral mass of iodine received under the PO in the Phebus FPT1 experiment.

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8. Fig. 7. Pressure under the PO in the Phebus FPT1 experiment.

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9. Fig. 8. The temperature of the gas phase under the PO in the Phebus FPT1 experiment.

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10. Fig. 9. The mass concentration of caesium in the gas phase under the PO in the Phebus FPT1 experiment, obtained for various numbers of aerosol size groups (6, 11, 16 and 21 groups).

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