Development of a Core Management Tool for the MYRRHA Irradiation Research Facility

Research output: ThesisDoctoral thesis

Standard

Development of a Core Management Tool for the MYRRHA Irradiation Research Facility. / Jaluvka, David.

Leuven, Belgium : KUL - Katholieke Universiteit Leuven, 2015. 296 p.

Research output: ThesisDoctoral thesis

Harvard

Jaluvka, D 2015, 'Development of a Core Management Tool for the MYRRHA Irradiation Research Facility', KUL - Katholieke Universiteit Leuven , Leuven, Belgium.

APA

Jaluvka, D. (2015). Development of a Core Management Tool for the MYRRHA Irradiation Research Facility. Leuven, Belgium: KUL - Katholieke Universiteit Leuven.

Vancouver

Jaluvka D. Development of a Core Management Tool for the MYRRHA Irradiation Research Facility. Leuven, Belgium: KUL - Katholieke Universiteit Leuven, 2015. 296 p.

Author

Jaluvka, David. / Development of a Core Management Tool for the MYRRHA Irradiation Research Facility. Leuven, Belgium : KUL - Katholieke Universiteit Leuven, 2015. 296 p.

Bibtex - Download

@phdthesis{0211a18483c94c0988c8b9bedc129532,
title = "Development of a Core Management Tool for the MYRRHA Irradiation Research Facility",
abstract = "This dissertation develops a core management to ol called RELOAD-M capable of optimizing reactor-core fuel loadings for MYRRHA, the future fast-spectrum research facility currently under development at SCK• CEN, Belgium. Such a tool is needed for designing highly efficient loading patterns that reflect various performance objectives of the multipurpose machine. RELOAD-M can solve the single-cycle loading pattern optimization problem, using different metaheuristic optimization methods and reactor analysis codes. Two iterative population-based metaheuristics are implemented to solve the loading pattern optimization problem: Genetic Algorithm (GA) (with or without elitism) and Ant Colony Optimization (ACO). Both methods are applied to a simple core-reload problem with a known global optimum and the optimization results are compared. It is found that the elitist GA gives the most consistent results and performs best. MYRRHA reactor-core models are described and used for the neutronics evaluation of different loading patterns by reactor analysis codes tailored to fast-spectrum systems. A simple thermal-hydraulics module is implemented for the calculation of the maximum fuel-cladding temperature. All employed models give results that are sufficiently accurate and fast enough for optimization purposes.",
keywords = "MYRRHA, Loading-Pattern-Optimisation, Core design",
author = "David Jaluvka",
note = "Score = 6",
year = "2015",
month = "2",
day = "2",
language = "English",
publisher = "KUL - Katholieke Universiteit Leuven",
school = "KUL - Katholieke Universiteit Leuven",

}

RIS - Download

TY - THES

T1 - Development of a Core Management Tool for the MYRRHA Irradiation Research Facility

AU - Jaluvka, David

N1 - Score = 6

PY - 2015/2/2

Y1 - 2015/2/2

N2 - This dissertation develops a core management to ol called RELOAD-M capable of optimizing reactor-core fuel loadings for MYRRHA, the future fast-spectrum research facility currently under development at SCK• CEN, Belgium. Such a tool is needed for designing highly efficient loading patterns that reflect various performance objectives of the multipurpose machine. RELOAD-M can solve the single-cycle loading pattern optimization problem, using different metaheuristic optimization methods and reactor analysis codes. Two iterative population-based metaheuristics are implemented to solve the loading pattern optimization problem: Genetic Algorithm (GA) (with or without elitism) and Ant Colony Optimization (ACO). Both methods are applied to a simple core-reload problem with a known global optimum and the optimization results are compared. It is found that the elitist GA gives the most consistent results and performs best. MYRRHA reactor-core models are described and used for the neutronics evaluation of different loading patterns by reactor analysis codes tailored to fast-spectrum systems. A simple thermal-hydraulics module is implemented for the calculation of the maximum fuel-cladding temperature. All employed models give results that are sufficiently accurate and fast enough for optimization purposes.

AB - This dissertation develops a core management to ol called RELOAD-M capable of optimizing reactor-core fuel loadings for MYRRHA, the future fast-spectrum research facility currently under development at SCK• CEN, Belgium. Such a tool is needed for designing highly efficient loading patterns that reflect various performance objectives of the multipurpose machine. RELOAD-M can solve the single-cycle loading pattern optimization problem, using different metaheuristic optimization methods and reactor analysis codes. Two iterative population-based metaheuristics are implemented to solve the loading pattern optimization problem: Genetic Algorithm (GA) (with or without elitism) and Ant Colony Optimization (ACO). Both methods are applied to a simple core-reload problem with a known global optimum and the optimization results are compared. It is found that the elitist GA gives the most consistent results and performs best. MYRRHA reactor-core models are described and used for the neutronics evaluation of different loading patterns by reactor analysis codes tailored to fast-spectrum systems. A simple thermal-hydraulics module is implemented for the calculation of the maximum fuel-cladding temperature. All employed models give results that are sufficiently accurate and fast enough for optimization purposes.

KW - MYRRHA

KW - Loading-Pattern-Optimisation

KW - Core design

UR - http://ecm.sckcen.be/OTCS/llisapi.dll/open/ezp_138388

M3 - Doctoral thesis

PB - KUL - Katholieke Universiteit Leuven

CY - Leuven, Belgium

ER -

ID: 194050