Capabilities overview of the MORET 5 Monte Carlo code

Cochet, B.; Jinaphanh, Alexis; Heulers, L.; Jacquet, Olivier

doi:10.1016/j.anucene.2014.08.022

Cited by 27 publications

(8 citation statements)

References 7 publications

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“…Results were obtained for several selections (suites) from the ICSBEP Handbook and for additional well-known experiments and applications. The transport codes MCNP, MORET 5 [369] and Tripoli were used with the associated processing codes, including NJOY and GAIA [370]. This variety adds confidence that the library will perform for a wide range of processing routes and application codes.…”

Section: Criticalitymentioning

confidence: 99%

The joint evaluated fission and fusion nuclear data library, JEFF-3.3

et al. 2020

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The joint evaluated fission and fusion nuclear data library 3.3 is described. New evaluations for neutroninduced interactions with the major actinides 235 U, 238 U and 239 Pu, on 241 Am and 23 Na, 59 Ni, Cr, Cu, Zr, Cd, Hf, W, Au, Pb and Bi are presented. It includes new fission yields, prompt fission neutron spectra and average number of neutrons per fission. In addition, new data for radioactive decay, thermal neutron scattering, gamma-ray emission, neutron activation, delayed neutrons and displacement damage are presented. JEFF-3.3 was complemented by files from the TENDL project. The libraries for photon, proton, deuteron, triton, helion and alpha-particle induced reactions are from TENDL-2017. The demands for uncertainty quantification in modeling led to many new covariance data for the evaluations. A comparison between results from model calculations using the JEFF-3.3 library and those from benchmark experiments for criticality, delayed neutron yields, shielding and decay heat, reveals that JEFF-3.3 performes very well for a wide range of nuclear technology applications, in particular nuclear energy.

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Section: Criticalitymentioning

confidence: 99%

The joint evaluated fission and fusion nuclear data library, JEFF-3.3

et al. 2020

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“…We now turn to the case of stochastic simulators, that is, simulators whose output is stochastic, as happens for instance when the computer program relies on a Monte Carlo method (see, e.g., Cochet et al, 2014). Extending the multi-fidelity Bayesian methodology of Sections 2.1 and 2.2 to stochastic simulators is not straightforward in general, since the output at a given input point x i = (u i , δ i ) ∈ X is now a random variable Z i , the distribution of which is in general unknown and different at each point in X.…”

Section: Extension To Stochastic Simulatorsmentioning

confidence: 99%

Sequential design of multi-fidelity computer experiments: maximizing the rate of stepwise uncertainty reduction

Stroh,

Bect,

Demeyer

et al. 2020

Preprint

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This article deals with the sequential design of experiments for (deterministic or stochastic) multi-fidelity numerical simulators, that is, simulators that offer control over the accuracy of simulation of the physical phenomenon or system under study. Very often, accurate simulations correspond to high computational efforts whereas coarse simulations can be obtained at a smaller cost. In this setting, simulation results obtained at several levels of fidelity can be combined in order to estimate quantities of interest (the optimal value of the output, the probability that the output exceeds a given threshold. . . ) in an efficient manner. To do so, we propose a new Bayesian sequential strategy called Maximal Rate of Stepwise Uncertainty Reduction (MR-SUR), that selects additional simulations to be performed by maximizing the ratio between the expected reduction of uncertainty and the cost of simulation. This generic strategy unifies several existing methods, and provides a principled approach to develop new ones. We assess its performance on several examples, including a computationally intensive problem of fire safety analysis where the quantity of interest is the probability of exceeding a tenability threshold during a building fire.

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“…The "Institut de Radioprotection et de Sûreté Nucléaire" (IRSN) has developed, for many years, its own neutron transport Monte Carlo code called MORET [1]. The MORET code is coupled with the APOLLO2 deterministic code [2] in the frame of the CRISTAL package [3].…”

Section: Introductionmentioning

confidence: 99%

“…). Several versions of the MORET code have been delivered, the last one being MORET 5.D.1 [1], which was recently made available at the OECD NEA databank. The continuous energy version of the MORET code has been validated on a suite of more than 2000 criticality benchmarks issued from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook [4] and French proprietary experiments, allowing thus covering the main applications encountered in criticality safety.…”

Section: Introductionmentioning

confidence: 99%

“…In this framework, an experimental validation database targeting reactor physics applications has been created. It is mainly based on benchmarks taken from the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP [5]), and also on the neutron commissioning measurements performed in the CABRI 1 Water Loop reactor prior to the CIP-Q program [6]. Around 175 experimental cases corresponding to 20 IRPhEP evaluations are available so far in the MORET validation database.…”

Section: Introductionmentioning

confidence: 99%

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Validation of the MORET 5 Monte Carlo Transport Code on Reactor Physics Experiments

Leclaire

Duhamel

2021

JNE

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The MORET 5 code, which has been developed over more than 50 years at IRSN, has recently evolved, in its continuous energy version, from a criticality oriented code to a code also focused on reactor physics applications. Some developments such as the implementation of kinetics parameters contribute to that evolution. The aim of the paper is to present the validation of the code for the keff multiplication factor used in criticality studies as well as for other parameters commonly used in reactor physics applications. Special attention will be paid on commission tests performed in the CABRI French Reactor (CABRI is a pool-type research reactor operated by CEA and located in the Cadarache site in southern France used to simulate a sudden and instantaneous increase in power, known as a power transient, typical of a reactivity-initiated accident (RIA).) and the IPEN/MB-01 LCT-077 benchmark.

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Capabilities overview of the MORET 5 Monte Carlo code

Cited by 27 publications

References 7 publications

The joint evaluated fission and fusion nuclear data library, JEFF-3.3

The joint evaluated fission and fusion nuclear data library, JEFF-3.3

Sequential design of multi-fidelity computer experiments: maximizing the rate of stepwise uncertainty reduction

Validation of the MORET 5 Monte Carlo Transport Code on Reactor Physics Experiments

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