Numerically efficient determination of kinetic parameters of the VR-1 nuclear reactor based on experimental data and ODE-constrained optimization
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00378066" target="_blank" >RIV/68407700:21230/25:00378066 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/68407700:21340/25:00378066
Výsledek na webu
<a href="https://doi.org/10.1016/j.anucene.2024.111023" target="_blank" >https://doi.org/10.1016/j.anucene.2024.111023</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.anucene.2024.111023" target="_blank" >10.1016/j.anucene.2024.111023</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Numerically efficient determination of kinetic parameters of the VR-1 nuclear reactor based on experimental data and ODE-constrained optimization
Popis výsledku v původním jazyce
A method of adjusting nuclear reactor kinetic parameters to experimental data is proposed. The fractions of neutrons delayed via different precursor groups are of interest. Their values originally calculated by Monte Carlo simulations are modified to bring the power output of the reactor predicted by the point kinetics equations closer to the measured values. The measurements were performed on the VR-1 zero-power training reactor in the Czech Republic. Three reactivity patterns were investigated to account for the different reactor transients. The resulting ODE-constrained optimization problem is solved numerically, using the adjoint equations to obtain the gradient of the loss functional and applying a specifically tailored gradient descent technique. The performance of our approach is compared to other variants of gradient-based optimization. As a side result, a gradient descent step size adaptivity algorithm is proposed. Finally, discussion on the physical relevance of the obtained results is provided.
Název v anglickém jazyce
Numerically efficient determination of kinetic parameters of the VR-1 nuclear reactor based on experimental data and ODE-constrained optimization
Popis výsledku anglicky
A method of adjusting nuclear reactor kinetic parameters to experimental data is proposed. The fractions of neutrons delayed via different precursor groups are of interest. Their values originally calculated by Monte Carlo simulations are modified to bring the power output of the reactor predicted by the point kinetics equations closer to the measured values. The measurements were performed on the VR-1 zero-power training reactor in the Czech Republic. Three reactivity patterns were investigated to account for the different reactor transients. The resulting ODE-constrained optimization problem is solved numerically, using the adjoint equations to obtain the gradient of the loss functional and applying a specifically tailored gradient descent technique. The performance of our approach is compared to other variants of gradient-based optimization. As a side result, a gradient descent step size adaptivity algorithm is proposed. Finally, discussion on the physical relevance of the obtained results is provided.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10304 - Nuclear physics
Návaznosti výsledku
Projekt
<a href="/cs/project/EF16_019%2F0000778" target="_blank" >EF16_019/0000778: Centrum pokročilých aplikovaných přírodních věd</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2025
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Annals of Nuclear Energy
ISSN
0306-4549
e-ISSN
1873-2100
Svazek periodika
211
Číslo periodika v rámci svazku
2
Stát vydavatele periodika
GB - Spojené království Velké Británie a Severního Irska
Počet stran výsledku
17
Strana od-do
—
Kód UT WoS článku
001354844300001
EID výsledku v databázi Scopus
2-s2.0-85208227810