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Optimizing Nuclide Sets for Efficient Monte Carlo Simulations in Large-Scale and Multiphysics Nuclear Reactor Models

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F24%3A00381193" target="_blank" >RIV/68407700:21730/24:00381193 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://www.djs.si/nene2024proceedings/pdf/NENE2024_115.pdf" target="_blank" >https://www.djs.si/nene2024proceedings/pdf/NENE2024_115.pdf</a>

  • DOI - Digital Object Identifier

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Optimizing Nuclide Sets for Efficient Monte Carlo Simulations in Large-Scale and Multiphysics Nuclear Reactor Models

  • Popis výsledku v původním jazyce

    The paper presents an extensive evaluation of the influence of individual nuclides on key nuclear reactor parameters such as fuel reactivity, decay heat, and radiation sources, with the ultimate goal of identifying an optimized, reduced set of nuclides that maintain accuracy while enhancing computational efficiency in Monte Carlo simulations for large-scale nuclear models. Employing Monte Carlo simulation tools like MCNP or Serpent, which typically face challenges of slowed performance or increased memory demand when using extensive nuclide lists, this research investigates strategies to streamline these simulations without compromising essential details. Using the Teplator heavy water Small Modular Reactor (SMR) core as a detailed case study, the paper examines the effects of nuclide selection at various stages of the reactor cycle — Beginning of Cycle (BOC), Middle of Cycle (MOC) and End of Cycle (EOC). The paper assesses the trade-offs between simulation detail and computational demands by studying deterministic and Monte Carlo calculation approaches. The findings demonstrate the feasibility of significantly reducing the number of nuclides in simulations and highlight how such reductions can be implemented in practice, ensuring that computational resources are judiciously used while retaining a high degree of accuracy in predicting reactor behavior throughout its lifecycle. This approach offers a practical pathway for enhancing the Monte Carlo simulations' efficiency in designing and analyzing large, complex, three-dimensional nuclear reactor models or multiphysics simulations coupling neutronics and thermal hydraulics.

  • Název v anglickém jazyce

    Optimizing Nuclide Sets for Efficient Monte Carlo Simulations in Large-Scale and Multiphysics Nuclear Reactor Models

  • Popis výsledku anglicky

    The paper presents an extensive evaluation of the influence of individual nuclides on key nuclear reactor parameters such as fuel reactivity, decay heat, and radiation sources, with the ultimate goal of identifying an optimized, reduced set of nuclides that maintain accuracy while enhancing computational efficiency in Monte Carlo simulations for large-scale nuclear models. Employing Monte Carlo simulation tools like MCNP or Serpent, which typically face challenges of slowed performance or increased memory demand when using extensive nuclide lists, this research investigates strategies to streamline these simulations without compromising essential details. Using the Teplator heavy water Small Modular Reactor (SMR) core as a detailed case study, the paper examines the effects of nuclide selection at various stages of the reactor cycle — Beginning of Cycle (BOC), Middle of Cycle (MOC) and End of Cycle (EOC). The paper assesses the trade-offs between simulation detail and computational demands by studying deterministic and Monte Carlo calculation approaches. The findings demonstrate the feasibility of significantly reducing the number of nuclides in simulations and highlight how such reductions can be implemented in practice, ensuring that computational resources are judiciously used while retaining a high degree of accuracy in predicting reactor behavior throughout its lifecycle. This approach offers a practical pathway for enhancing the Monte Carlo simulations' efficiency in designing and analyzing large, complex, three-dimensional nuclear reactor models or multiphysics simulations coupling neutronics and thermal hydraulics.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    20305 - Nuclear related engineering; (nuclear physics to be 1.3);

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/TN02000012" target="_blank" >TN02000012: Centrum pokročilých jaderných technologií II</a><br>

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Ostatní

  • Rok uplatnění

    2024

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    Proceedings of 33rd International Conference Nuclear Energy for New Europe

  • ISBN

    978-961-6207-59-1

  • ISSN

  • e-ISSN

  • Počet stran výsledku

    8

  • Strana od-do

  • Název nakladatele

    Nuclear Society of Slovenia

  • Místo vydání

    Ljubljana

  • Místo konání akce

    Portorož

  • Datum konání akce

    9. 9. 2024

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku