Computing eigenvalue sensitivity coefficients to nuclear data based on the CLUTCH method with RMC code

Qiu, Yue; She, Ding; Tang, Xiao; Wang, Kan; Liang, Jingang

doi:10.1016/j.anucene.2015.11.007

Cited by 16 publications

(9 citation statements)

References 7 publications

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“…For the deterministic transport methods, perturbation-based sensitivity and uncertainty analysis is always performed by using the 2D forward and adjoint transport solutions, and some well-known lattice codes already have the SU analysis ability, such as the Polaris in SCALE6.2.1 [3], CASMO5 [4], and AutoMOC [5]. For the direct 3D wholecore SU analysis, the Monte Carlo methods are preferred to perform the forward and adjoint calculations, and then the perturbation theory-based SU method is applied, and the SU analysis ability is also developed in some famous Monte Carlo codes in recent years, such as the TSUNAMI-3D module in SCALE [6], RMC [7], and McCARD [8]. Even more important, significant advances in high performance computing clusters have enabled the direct 3D whole-core heterogeneous transport simulation in the subpin level by using the deterministic transport methods, and extending the direct 3D whole-core high-fidelity deterministic transport simulation capabilities to the SU analysis has attracted more and more research efforts in recent years [9].…”

Section: Introductionmentioning

confidence: 99%

Perturbation Theory-Based Whole-Core Eigenvalue Sensitivity and Uncertainty (SU) Analysis via a 2D/1D Transport Code

Hao

Liu

et al. 2020

Science and Technology of Nuclear Installations

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For nuclear reactor physics, uncertainties in the multigroup cross sections inevitably exist, and these uncertainties are considered as the most significant uncertainty source. Based on the home-developed 3D high-fidelity neutron transport code HNET, the perturbation theory was used to directly calculate the sensitivity coefficient of keff to the multigroup cross sections, and a reasonable relative covariance matrix with a specific energy group structure was generated directly from the evaluated covariance data by using the transforming method. Then, the “Sandwich Rule” was applied to quantify the uncertainty of keff. Based on these methods, a new SU module in HNET was developed to directly quantify the keff uncertainty with one-step deterministic transport methods. To verify the accuracy of the sensitivity and uncertainty analysis of HNET, an infinite-medium problem and the 2D pin-cell problem were used to perform SU analysis, and the numerical results demonstrate that acceptable accuracy of sensitivity and uncertainty analysis of the HNET are achievable. Finally, keff SU analysis of a 3D minicore was analyzed by using the HNET, and some important conclusions were also drawn from the numerical results.

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Section: Introductionmentioning

confidence: 99%

Perturbation Theory-Based Whole-Core Eigenvalue Sensitivity and Uncertainty (SU) Analysis via a 2D/1D Transport Code

Hao

Liu

et al. 2020

Science and Technology of Nuclear Installations

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“…12,13,and 14), OpenMC (Refs. 15 and 16), and Reactor Monte Carlo [17][18][19][20] (RMC). However, the applicability of these Monte Carlo methods to analyzing the sensitivities and uncertainties of the k-eigenvalue with respect to the geometric parameters remains an open question because algorithms that are both universal and efficient in arbitrary geometric perturbations are still absent.…”

Section: Introductionmentioning

confidence: 99%

Calculating the k -Eigenvalue Sensitivity to Typical Geometric Perturbations with the Adjoint-Weighted Method in the Continuous-Energy Reactor Monte Carlo Code RMC

Huang

et al. 2019

Nuclear Science and Engineering

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Geometric sensitivity analyses of the k-eigenvalue have many applications in analyses of geometric uncertainty, calculations of differential control rod worth, and searches for critical geometry. The adjoint-weighted first-order geometric sensitivity theory is widely used and has continuously evolved with the Monte Carlo methods. However, the existing adjoint-weighted algorithm can do only uniform isotropic expansions or contractions of surfaces. The adjoint-weighted algorithm also requires computation of adjoint-weighted scattering and fission reaction rates exactly at material interfaces, which has an infinitesimal probability in reality. This paper presents an improved geometry adjoint-weighted perturbation algorithm that is incorporated into the continuous-energy Reactor Monte Carlo (RMC) code. The improvement of the adjoint-weighted algorithm is decomposed into three steps for constructing a cross-section function of geometric parameters using logical expressions, calculating the derivative of the cross-section function, and estimating the adjoint-weighted surface reaction rates. The improved algorithm can accommodate common one-parameter geometric perturbations of internal interfaces or boundary surfaces as well as those of cells as long as the perturbed cells can be described by logical expressions of spatial surface equations. The perturbation algorithm is compared with a direct difference method, the linear least-squares fitting method with central differences, for several typical geometric perturbations including translation, fixed-axis rotation, and uniform isotropic/anisotropic expansion transformations of planar, spherical, cylindrical, and conical surfaces. The differences between the two methods are not more than 3% and not more than 3σ for the majority of the test examples. Even though the perturbation algorithm has higher figures of merit than the direct difference method for the majority of the test examples, there is no guarantee that the former can always be more efficient than the latter. The limitation in the efficiency of the perturbation algorithm was demonstrated by the totally reflecting light water reactor pin model.

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“…Sensitivities are available by energy group and by reaction. The obtained results about sensitivities are compared to iterated fission probability (IFP) calculations [8][9][10]. These sensitivities will be used in uncertainties calculations on reactivity with condensed covariance matrix to determined uncertainty du to nuclear data on BEAVRS core.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of uncertainty neutron transport calculations at an industrial scale

Gaillet

Bonaccorsi

Noguère

et al. 2018

EPJ Nuclear Sci. Technol.

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Evaluating uncertainties on nuclear parameters such as reactivity is a major issue for conception of nuclear reactors. These uncertainties mainly come from the lack of knowledge on nuclear and technological data. Today, the common method used to propagate nuclear data uncertainties is Total Monte Carlo [1] but this method suffers from a long time calculation. Moreover, it requires as many calculations as uncertainties sought. An other method for the propagation of the nuclear data uncertainties consists in using the standard perturbation theory (SPT) to calculate reactivity sensitivity to the desire nuclear data. In such a method, sensitivities are combined with a priori nuclear data covariance matrices such as the COMAC set developed by CEA. The goal of this work is to calculate sensitivites by SPT with the full core diffusion code CRONOS2 for propagation uncertainties at the core level. In this study, COMAC nuclear data uncertainties have been propagated on the BEAVRS benchmark using a two-step APOLLO2/CRONOS2 scheme, where APOLLO2 is the lattice code used to resolve Boltzmann equation within assemblies using a high number of energy groups, and CRONOS2 is the code resolving the 3D full core diffusion equation using only four energy groups. A module implementing the SPT already exists in the APOLLO2 code but computational cost would be too expensive in 3D on the whole core. Consequently, an equivalent procedure has been created in CRONOS2 code to allow full-core uncertainty propagation. The main interest of this procedure is to compute sensitivities on reactivity within a reduced turnaround time for a 3D modeled core, even after fuel depletion. In addition, it allows access to all sensitivites by isotope, reaction and energy group in a single calculation. Reactivity sensitivities calculated by this procedure with four energy groups are compared to reference sensitivities calculated by the iterated fission probability (IFP) method in Monte Carlo code. For the purpose of the tests, dedicated covariance matrix have been created by condensation from 49 to 4 groups of the COMAC matrix. In conclusion, sensitivities calculated by CRONOS2 agree with the sensitivities calculated by the IFP method, which validates the calculation procedure, allowing analysis to be done quickly. In addition, reactivity uncertainty calculated by this method is close to values found for this type of reactor.

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Computing eigenvalue sensitivity coefficients to nuclear data based on the CLUTCH method with RMC code

Cited by 16 publications

References 7 publications

Perturbation Theory-Based Whole-Core Eigenvalue Sensitivity and Uncertainty (SU) Analysis via a 2D/1D Transport Code

Perturbation Theory-Based Whole-Core Eigenvalue Sensitivity and Uncertainty (SU) Analysis via a 2D/1D Transport Code

Calculating the k -Eigenvalue Sensitivity to Typical Geometric Perturbations with the Adjoint-Weighted Method in the Continuous-Energy Reactor Monte Carlo Code RMC

Development and validation of uncertainty neutron transport calculations at an industrial scale

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