The nuclear fuel cycle code ANICCA: Verification and a case study for the phase out of Belgian nuclear power with minor actinide transmutation

Rodríguez, Iván Merino; Hernández-Solís, Augusto; Messaoudi, Nadia; Eynde, Gert Van den

doi:10.1016/j.net.2020.04.004

Cited by 8 publications

(5 citation statements)

References 12 publications

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“…Those calculations were performed aiming to generate a database to train a Deep Learning model capable of predicting the final isotopic inventory for PWR spent nuclear fuel (UOX and/or MOX) employing as general inputs, the initial fuel composition (enrichment or plutonium content) and the target discharge burnup [6] . The model is part of the irradiation module of ANICCA [7] , the in-house fuel cycle analysis tool from SCK CEN.…”

Section: Objectivementioning

confidence: 99%

Dataset of observables for UOX and MOX spent fuel extracted from Serpent2 fuel depletion calculations for PWRs

Casas-Molina,

Hernandez-Solis,

Romojaro

et al. 2023

Data in Brief

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Section: Objectivementioning

confidence: 99%

Dataset of observables for UOX and MOX spent fuel extracted from Serpent2 fuel depletion calculations for PWRs

Casas-Molina,

Hernandez-Solis,

Romojaro

et al. 2023

Data in Brief

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“…ANICCA [1] (a recursive acronym for Advanced Nuclear Inventory Cycle Code: ANICCA) is a fuel cycle analysis tool developed at SCK CEN to monitor the flow of nuclear material between facilities. It is a flexible and modular code written in the Python programming language that allows easily setting up, modifying and comparing different fuel cycle strategies.…”

Section: Advanced Nuclear Inventory Cycle Code: Aniccamentioning

confidence: 99%

“…The nuclide data needed for the simulation of fuel cycle scenarios, such as isotope masses and different decay modes with their associated half-life, daughter products, yields, etc., are obtained from the JEFF-3.1/-3.1.1 radioactive decay data and fission yields sub-libraries [3] that are adapted to the internationally adopted ENDF-6 (Evaluated Nuclear Data File) format. The in-core irradiation of nuclear fuel assemblies can be simulated by means of pre-built libraries containing information about the averaged flux, effective full-power days of irradiation and averaged isotopic cross-sections and fission yields for a select number of burnup steps [1]. These libraries are generated by a post-processing of ALEPH2 [4] calculation results, an in-house SCK CEN Monte Carlo depletion code.…”

Section: Advanced Nuclear Inventory Cycle Code: Aniccamentioning

confidence: 99%

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Development of a MOX equivalence Python code package for ANICCA

Vermeeren

Druenne

2021

EPJ Nuclear Sci. Technol.

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The basis of the MOX (Mixed OXide) energy equivalence principle is keeping the in-core fuel management characteristics (cycle length, feed size, etc.) of a nuclear reactor unchanged when replacing UOX (Uranium OXide) fuel assemblies by MOX. If the effect of the loading pattern is neglected, such an equivalence is obtained by tuning the Pu content in the MOX fuel, while considering the specific Pu isotopic vector at the time of the core reload to obtain a crossing of the reactivity curves of UOX and MOX at the end-of-cycle core average burnup. It is proposed in this work to extend the fuel cycle analysis tool ANICCA (Advanced Nuclear Inventory Cycle Code) with a MOX equivalence Python code package, which automatically governs the supply and demand of Pu vector isotopes required to obtain MOX equivalence. This code package can determine the reactivity evolution for any given Pu vector by means of a multidimensional interpolation on a directive grid of pre-calculated data tables generated by WIMS10, covering the physically accessible Pu vector space. A fuel cycle scenario will be assessed for a representative evolution of the Pu vector inventory available in spent UOX fuel as a demonstration case, defining the interim fuel storage building dimensional requirements for different reprocessing strategies.

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“…About 30 codes for simulating the nuclear fuel cycle have previously been developed by various research institutes, and some international benchmark studies have been conducted in the last decade [3][4][5]. Table 1 shows the nuclear fuel cycle simulation codes of each institute in the report published by the Nuclear Energy Agency (NEA, under the Organization for Economic Co-operation and Development) in 2012 [5], as well as the fuel cycle code ANICCA, developed by SCK CEN [6]. It can be said that each of the codes excels at tracking actinide nuclides and performing nuclear fuel cycle simulation, particularly in relation to the front-end and reactor.…”

Section: Introductionmentioning

confidence: 99%

NMB4.0: development of integrated nuclear fuel cycle simulator from the front to back-end

Okamura

Katano

Oizumi

et al. 2021

EPJ Nuclear Sci. Technol.

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Nuclear Material Balance code version 4.0 (NMB4.0) has been developed through collaborative R&D between TokyoTech&JAEA. Conventional nuclear fuel cycle simulation codes mainly analyze actinides and are specialized for front-end mass balance analysis. However, quantitative back-end simulation has recently become necessary for considering R&D strategies and sustainable nuclear energy utilization. Therefore, NMB4.0 was developed to realize the integrated nuclear fuel cycle simulation from front- to back-end. There are three technical features in NMB4.0: 179 nuclides are tracked, more than any other code, throughout the nuclear fuel cycle; the Okamura explicit method is implemented, which contributes to reducing the numerical cost while maintaining the accuracy of depletion calculations on nuclides with a shorter half-life; and flexibility of back-end simulation is achieved. The main objective of this paper is to show the newly developed functions, made for integrated back-end simulation, and verify NMB4.0 through a benchmark study to show the computational performance.

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The nuclear fuel cycle code ANICCA: Verification and a case study for the phase out of Belgian nuclear power with minor actinide transmutation

Cited by 8 publications

References 12 publications

Dataset of observables for UOX and MOX spent fuel extracted from Serpent2 fuel depletion calculations for PWRs

Dataset of observables for UOX and MOX spent fuel extracted from Serpent2 fuel depletion calculations for PWRs

Development of a MOX equivalence Python code package for ANICCA

NMB4.0: development of integrated nuclear fuel cycle simulator from the front to back-end

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