Uncertainty quantification of PWR spent fuel due to nuclear data and modeling parameters

Ebiwonjumi, Bamidele; Kong, Chidong; Zhang, Peng; Cherezov, Alexey; Lee, Deokjung

doi:10.1016/j.net.2020.07.012

Cited by 18 publications

(6 citation statements)

References 18 publications

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“…Time evolution of isotope inventory, particularly fuel composition, is calculated from the Bateman equation (see Eq. 1), in which the variation of the quantity N i of a nuclide i over a period Δt is a balance between its disappearance and its creation by decay or neutron interaction of some other nuclides j. Solution to the Bateman equation requires the calculation, usually using the Boltzmann (or transport) equation, of the neutron spectrum ϕ(E,t) at each time step, which depends on the medium and its composition.…”

Section: Methodsmentioning

confidence: 99%

“…In addition, it also allows for accurate modeling of the radial reflector. The CASMO5 default burnup mesh was used for the calculations 1 . For all the SA, color-set and full core calculations presented in this paper, the default options of CASMO5 have been considered, except for the following options which were used and are not part of the default options.…”

Section: Casmo5mentioning

confidence: 99%

“…Therefore, it is crucial to accurately estimate radionuclide inventory, as well as the uncertainties associated with this inventory. Furthermore, it should be stressed that the estimation of uncertainties associated with in-core isotopic inventories is a vast and non-trivial subject [1] [2]. Indeed, the calculations of nuclear fuel depletion under irradiation require complex simulations, which include many sources of bias and uncertainty.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of biases and uncertainties on PWR nuclide inventories for severe accidents analyses

et al. 2023

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The work presented in this paper deals with bias and uncertainty quantification on nuclear fuel inventory in a pressurized water reactors core during normal operation. This actinides and fission products inventory is used as input data for radiological releases evaluation in case of a severe accident. The different sources of bias and uncertainty, as well as their impacts for UO2 and MOX fuel at the assembly and core levels, are discussed. Uncertainty sources include technological uncertainties (e.g. dimensions, irradiation history, temperatures), modeling assumptions, uncertainties related to the resolution methods used in the calculation tools and nuclear data uncertainties. For each source of uncertainty investigated in this paper, an evaluation of the associated biases and uncertainties on nuclide inventory is performed. It is shown that, among the sources of bias and uncertainties studied, spread due to nuclear data as well as the bias and uncertainties due to “infinite lattice approximation” are the most significant ones, for the isotopes of interest.

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Section: Methodsmentioning

confidence: 99%

Section: Casmo5mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of biases and uncertainties on PWR nuclide inventories for severe accidents analyses

et al. 2023

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“…Moreover, Reference 10 revealed that nuclear data uncertainties are comparable to the uncertainties produced by technological parameters of the reactor (eg, boron concentration, pellet size, or fuel/moderator densities). In this line, more recent works have revealed that they have an impact on spent fuel quantities like decay heat or neutron and gamma emissions 11‐13 . Hence, it is not unreasonable to expect that nuclear data will also play an important role in fuel cycle simulations.…”

Section: Introductionmentioning

confidence: 99%

“…In this line, more recent works have revealed that they have an impact on spent fuel quantities like decay heat or neutron and gamma emissions. [11][12][13] Hence, it is not unreasonable to expect that nuclear data will also play an important role in fuel cycle simulations. This was studied in Reference 14 showing that nuclear data seem to have a significant impact on Pu and minor actinides (MA) inventories for different electronuclear scenarios, but it has been reported that the effect is probably small when compared to other uncertainty sources.…”

Section: Introductionmentioning

confidence: 99%

Comparison of nuclear data uncertainties with other nuclear fuel cycle uncertainty sources

Skarbeli

Eusebio-Yebra

Romojaro

et al. 2021

Intl J of Energy Research

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Nuclear data uncertainties have proven to be crucial in many areas of nuclear science such as the reactor or isotopic calculations. Nevertheless, when it comes to fuel cycle simulations (which are nowadays including uncertainty analyses), their relevance is discussed. Although it has been reported that they have an impact on the inventories, it is not clear if their effect can be negligible when compared with uncertainties produced by other fuel cycle parameters and consequently, if nuclear data uncertainties have to be considered in the fuel cycle studies. In this work, this comparison has been addressed for an open fuel cycle. First, the nuclear data uncertainties contained in the covariance matrices have been propagated with a Monte Carlo methodology, which has been verified with an integral experiment. After that, the results have been compared with uncertainties typically taking part in fuel cycle simulations from two different perspectives: an unknown future fuel cycle with relatively large uncertainties and a past known fuel cycle with small uncertainties.Results show that even for the most conservative cases based on open fuel cycles using PWR technologies, the uncertainties due to nuclear data are larger or at least comparable to the fuel cycle uncertainties due to parameters. Henceforth, with the adoption of advanced nuclear fuel cycles using newer technologies, it is expected that nuclear data uncertainties will play even more relevance in fuel cycle analyses. With these results, it has been concluded that nuclear data cannot be disregarded in uncertainty assessments in fuel cycle studies.

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On the use of criticality and depletion benchmarks for verification of nuclear data

Fiorito

Romojaro

Cabellos

et al. 2021

Annals of Nuclear Energy

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Uncertainty quantification of PWR spent fuel due to nuclear data and modeling parameters

Cited by 18 publications

References 18 publications

Estimation of biases and uncertainties on PWR nuclide inventories for severe accidents analyses

Estimation of biases and uncertainties on PWR nuclide inventories for severe accidents analyses

Comparison of nuclear data uncertainties with other nuclear fuel cycle uncertainty sources

On the use of criticality and depletion benchmarks for verification of nuclear data

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