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Faculté des Sciences appliquées
Faculté des Sciences appliquées
MASTER THESIS

Master's thesis and Internship : Design and implementation of a modular modeling framework for the ANICCA nuclear fuel cycle simulation code

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Mouchamps, Antoine ULiège
Promotor(s) : Ernst, Damien ULiège
Date of defense : 29-Jun-2026/30-Jun-2026 • Permalink : http://hdl.handle.net/2268.2/26132
Details
Title : Master's thesis and Internship : Design and implementation of a modular modeling framework for the ANICCA nuclear fuel cycle simulation code
Author : Mouchamps, Antoine ULiège
Date of defense  : 29-Jun-2026/30-Jun-2026
Advisor(s) : Ernst, Damien ULiège
Committee's member(s) : Derval, Guillaume ULiège
AIT ABDERRAHIM, Hamid 
ROMOJARO, Pablo 
Language : English
Number of pages : 79
Keywords : [en] Nuclear fuel cycle
[en] SCK CEN
[en] ANICCA
[en] Nuclear energy
[en] Modeling framework
Discipline(s) : Engineering, computing & technology > Energy
Research unit : Montefiore Research Unit
Institution(s) : Université de Liège, Liège, Belgique
Degree: Master : ingénieur civil en génie de l'énergie à finalité spécialisée en Energy Conversion
Faculty: Master thesis of the Faculté des Sciences appliquées

Abstract

[en] This thesis presents the design and implementation of a new modular simulation framework for ANICCA, the nuclear fuel cycle simulation code developed at the Belgian Nuclear Research Center (SCK CEN). The new framework introduces a three-layer architecture separating graph topology and mass dispatch, facility inventory management, and physical process execution. A nuclear fuel cycle scenario is formally represented as a directed multigraph. The currently implemented mass dispatch algorithm resolves mass flows through a two-pass sequential modular approach: a backward pass propagating demand upstream in reverse topological order, and a forward pass physically transferring packages in topological order. Recycling loops, which break the acyclic assumption required by this algorithm, are handled through a graph-tearing strategy. Four facility cycle types, fixed demand, on demand, variable demand, and none, define how facilities interact with the solver. Radioactive decay and fuel irradiation are both solved using the Chebyshev Rational Approximation Method (CRAM) with LU factorization caching, and the irradiation process is built around a multi-batch reactor core model driven by pre-computed fuel libraries. The framework is validated and demonstrated through four case studies, which also reveal several modeling errors present in the legacy code which are corrected in the new version.


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Author

  • Mouchamps, Antoine ULiège Université de Liège > Mast. ing. civ. gén. énerg. fin. spéc. Energ. conv.

Promotor(s)

Committee's member(s)

  • Derval, Guillaume ULiège Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Smart grids
    ORBi View his publications on ORBi
  • AIT ABDERRAHIM, Hamid
  • ROMOJARO, Pablo








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