New kinetic simulation capabilities for Tripoli-4®: Methods and applications

Faucher, Margaux; Mancusi, Davide; Zoia, Andrea

doi:10.1016/j.anucene.2018.05.030

Cited by 36 publications

(12 citation statements)

References 34 publications

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“…Splittings are unbiased for every moments of u. This ensures consistency: this may not be the case for combing [51] for example (which is only unbiased for the first moment, i.e. the mean).…”

Section: The Monte Carlo Resolution Of An Uncertain Eigenvalue Problemmentioning

confidence: 99%

“…M C + = split p end end Algorithm 7: description of uncertainPopulationControl: to make sure we always have about N M C uncertain MC particles within domain D a Combing [51], leading to split p= 0, are only unbiased for the first moment (i.e. the mean u 0 , k 0 eff ): here, we need to be unbiased for every orders {0, ..., P }, i.e.…”

Section: The Monte Carlo Resolution Of An Uncertain Eigenvalue Problemmentioning

confidence: 99%

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Efficient uncertain keff computations with the Monte Carlo resolution of generalised Polynomial Chaos based reduced models

Poëtte

Brun

2022

Journal of Computational Physics

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In this paper, we are interested in taking into account uncertainties for k eff computations in neutronics. More generally, the material of this paper can be applied to propagate uncertainties in eigenvalue/eigenvector computations for the linear Boltzmann equation. In [1,2], an intrusive MC solver for the gPC based reduced model of the instationary linear Boltzmann equation has been put forward. The MC-gPC solver presents interesting characteristics (mainly a better efficiency than non-intrusive strategies and spectral convergence): our aim is to recover these characteristics in an eigenvalue/eigenvector estimation context. This is done in practice at the price of few well identified modifications of an existing Monte Carlo implementation.

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Section: The Monte Carlo Resolution Of An Uncertain Eigenvalue Problemmentioning

confidence: 99%

Section: The Monte Carlo Resolution Of An Uncertain Eigenvalue Problemmentioning

confidence: 99%

Efficient uncertain keff computations with the Monte Carlo resolution of generalised Polynomial Chaos based reduced models

Poëtte

Brun

2022

Journal of Computational Physics

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“…These Monte Carlo codes are coupled with the SCF thermal-hydraulic solver, thus leading to the coupled codes: dynMCNP/SCF, dynTRIPOLI/SCF, dyn-SERPENT/SCF. The code extensions and modifications are described in more detail in [14,19,20]. The coupling schemes must be appropriate for massive HPC-simulations.…”

Section: Time-dependence Capabilities In Monte Carlo Methodsmentioning

confidence: 99%

Advanced numerical simulation and modelling for reactor safety − contributions from the CORTEX, HPMC, McSAFE and NURESAFE projects

Demazière

Sánchez-Espinoza

Chanaron

2020

EPJ Nuclear Sci. Technol.

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Predictive modelling capabilities have long represented one of the pillars of reactor safety. In this paper, an account of some projects funded by the European Commission within the seventh Framework Program (HPMC and NURESAFE projects) and Horizon 2020 Program (CORTEX and McSAFE) is given. Such projects aim at, among others, developing improved solution strategies for the modelling of neutronics, thermal-hydraulics, and/or thermo-mechanics during normal operation, reactor transients and/or situations involving stationary perturbations. Although the different projects have different focus areas, they all capitalize on the most recent advancements in deterministic and probabilistic neutron transport, as well as in DNS, LES, CFD and macroscopic thermal-hydraulics modelling. The goal of the simulation strategies is to model complex multi-physics and multi-scale phenomena specific to nuclear reactors. The use of machine learning combined with such advanced simulation tools is also demonstrated to be capable of providing useful information for the detection of anomalies during operation.

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“…When all particles already hit the time boundary, the time census is completed, and PCT can be performed on the censused particles. More recent applications of PCT include the use of random particle duplication or deletion [4] in Serpent 2 [13], splitting and Russian-Roulette technique [5] in MCATK [14], particle combing technique [15] in TRIPOLI-4 [16,17] and GUARDYAN [9], and a modified combing technique which is most recently introduced in [1].…”

Section: Introductionmentioning

confidence: 99%

“…Sweezy et al [5] propose a normalized SR as an alternative to CO which may suffer from unwanted behavior due to possible correlations in the particle or-der. On the other hand, Faucher et al [17] and Legrady et al [20] prefer the use of CO instead of SR due to the inherent bias [5] in the normalized SR and suggest that the unwanted behavior of CO is unlikely to occur in practice. This support for CO, or, if you will, ctenophilia, is further supported by the finding that-per reports in [19]-CO is at least 2-3 times more efficient than SR [20] in the range of problems considered.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Population Control Techniques for Time-Dependent and Eigenvalue Monte Carlo Neutron Transport Calculations

Ilham¹,

McClarren²

2022

Preprint

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A comprehensive study on population control technique (PCT) for time-dependent and eigenvalue Monte Carlo (MC) neutron transport simulations is presented. We define PCT as a technique that takes a censused population and returns a controlled, unbiased one. A new perspective based on an abstraction of particle census and population control is explored, paving the way to improved understanding and application of the concepts. Five distinct PCTs identified from the literature are reviewed: Simple Sampling (SS), Splitting-Roulette (SR), Combing (CO), modified Combing (COX), and Duplicate-Discard (DD). A theoretical analysis of how much uncertainty is introduced to a population by each PCT is presented. Parallel algorithms for the PCTs applicable for both time-dependent and eigenvalue MC simulations are proposed. The relative performances of the PCTs based on runtime and tally mean error or standard deviation are assessed by solving time-dependent and eigenvalue test problems. It is found that SR and CO are equally the most performant techniques, closely followed by DD.

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New kinetic simulation capabilities for Tripoli-4®: Methods and applications

Cited by 36 publications

References 34 publications

Efficient uncertain keff computations with the Monte Carlo resolution of generalised Polynomial Chaos based reduced models

Efficient uncertain keff computations with the Monte Carlo resolution of generalised Polynomial Chaos based reduced models

Advanced numerical simulation and modelling for reactor safety − contributions from the CORTEX, HPMC, McSAFE and NURESAFE projects

Analysis of Population Control Techniques for Time-Dependent and Eigenvalue Monte Carlo Neutron Transport Calculations

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