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Modeling and ALARA optimization of maintenance operations in fusion nuclear power plants with Artificial


Thesis topic details

General information

Organisation

The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :
• defence and security,
• nuclear energy (fission and fusion),
• technological research for industry,
• fundamental research in the physical sciences and life sciences.

Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.

The CEA is established in ten centers spread throughout France
  

Reference

SL-DRF-25-0967  

Direction

DRF

Thesis topic details

Category

Corpuscular physics and outer space

Thesis topics

Modeling and ALARA optimization of maintenance operations in fusion nuclear power plants with Artificial Intelligence and Virtual Reality techniques

Contract

Thèse

Job description

In view to the development of future fusion reactors, the maintenance operations in these nuclear facilities will be a diffculty, as part of them will have to be carried out hands-on. Safety rules govern interventions in a radioactive environment. They take into account the level of effective dose received by the operator, a factor that characterizes the risk to which the operator is exposed (dose depending on ambient dose rate and time).
In the aim of optimizing this dose in line with the ALARA principle and the safety constraints associated with these installations, the prior simulation of operations in Virtual Reality is an asset in terms of design optimization and worker training. Calculating dose during these simulations would be an important contribution to discriminating between different options. The simulation methods currently used to calculate dose rates are in some cases imprecise and in others very costly in terms of simulation time.
The aim of this work is to propose a new method for dynamic dose rate estimation in reduced time (or even real time) as a function of the movements of both the activation sources of a fusion installation, the maintenance operator and the shield protecting the latter. These dynamic configurations are representative of real intervention conditions. This method will implement Artificial Intelligence techniques coupled with Neutronics methods, and should be able to be integrated into a Virtual Reality tool based on existing development environments such as Unity3D.

University / doctoral school

Physique et Sciences de la Matière (ED352)
Aix-Marseille Université

Thesis topic location

Site

Cadarache

Requester

Position start date

01/11/2025

Person to be contacted by the applicant

PENELIAU Yannick yannick.peneliau@cea.fr
CEA
DRF/IRFM/SI2P/GISP
Centre de Cadarache
Bâtiment 507
13108 SAINT-PAUL-LEZ-DURANCE Cedex
04.42.25.39.24

Tutor / Responsible thesis director

LE LOIREC Cindy Cindy.LELOIREC@cea.fr
CEA
DES/DER/SPRC/LPN
CEA Cadarache | F-13108 Saint-Paul-lez-Durance Cedex
+33 (0)4 42 25 40 62

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