Optimization of the loading pattern of the PWR core using genetic algorithms and multi-purpose fitness function

• Autorzy: Kubiński Wojciech , Darnowski Piotr , Chęć Kamil

Identyfikatory

DOI

10.2478/nuka-2021-0022

• Konferencja: International Conference on Development and Applications of Nuclear Technologies NUTECH-2020 (04–07.10.2020; Warsaw, Poland)
• Języki publikacji: EN

Abstrakty

EN

The study demonstrates an application of genetic algorithms (GAs) in the optimization of the first core loading pattern. The Massachusetts Institute of Technology (MIT) BEAVRS pressurized water reactor (PWR) model was applied with PARCS nodal-diffusion core simulator coupled with GA numerical tool to perform pattern selection. In principle, GAs have been successfully used in many nuclear engineering problems such as core geometry optimization and fuel confi guration. In many cases, however, these analyses focused on optimizing only a single parameter, such as the effective neutron multiplication factor (keff), and often limited to the simplified core model. On the contrary, the GAs developed in this work are equipped with multiple-purpose fitness function (FF) and allow the optimization of more than one parameter at the same time, and these were applied to a realistic full-core problem. The main parameters of interest in this study were the total power peaking factor (PPF) and the length of the fuel cycle. The basic purpose of this study was to improve the economics by finding longer fuel cycle with more uniform power/flux distribution. Proper FFs were developed, tested, and implemented and their results were compared with the reference BEAVRS first fuel cycle. In the two analysed test scenarios, it was possible to extend the fi rst fuel cycle while maintaining lower or similar PPF, in comparison with the BEAVRS core, but for the price of increased initial reactivity.

Słowa kluczowe

EN

genetic algorithms; fuel loading; loading optimization; PWR; nuclear reactor technology

• Wydawca: Institute of Nuclear Chemistry and Technology
• Czasopismo: Nukleonika
• Rocznik: 2021
• Tom: Vol. 66, No. 4
• Strony: 147--151
• Opis fizyczny: Bibliogr. 17 poz., rys.

Twórcy

autor

Kubiński Wojciech

• Warsaw University of Technology Faculty of Physics Koszykowa 75 Str., 00-665, Warsaw, Poland

• https://orcid.org/0000-0002-5805-367X

autor

Darnowski Piotr

• Warsaw University of Technology Institute of Heat Engineering Nowowiejska 21/25 Str., 00-665 Warsaw, Poland

• https://orcid.org/0000-0003-1602-5379

autor

Chęć Kamil

• Warsaw University of Technology Faculty of Physics Koszykowa 75 Str., 00-665, Warsaw, Poland

Bibliografia

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• 6. Martín-del-Campo, C., Palomera-Pérez, M. Á., & François, J. L. (2009). Advanced and flexible genetic algorithms for BWR fuel loading pattern optimization. Ann. Nucl. Energy, 36(10), 1553–1559. https://doi.org/10.1016/j.anucene.2009.07.013.
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• 12. Kubiński, W., Darnowski, P., & Chęć, K. (2021). The development of a novel adaptive genetic algorithm for the optimization of fuel cycle length. Ann. Nucl. Energy, 155, art. ID 108153. DOI: 10.1016/j.anucene.2021.108153.
• 13. Downar, T., Xu, Y., Seker, V., & Hudson, N. (2010). PARCS v3.0 U.S. NRC Core Neutronics Simulator.Theory manual. USNRC.
• 14. Downar, T., Xu, Y., Seker, V., & Hudson, N. (2010). PARCS v3.0 U.S. NRC Core Neutronics Simulator. User manual. USNRC. Available from https://www.nrc.gov/docs/ML1016/ML101610098.pdf.
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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).