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Model-Based approach for the study of nuclear waste treatment scenarios

Abstract : In the context of the nuclear industry, engineering of dismantling and waste management projects remain difficult to master and drive. These are increasingly complex from a technical and organisational point of view for a variety of reasons, (large number and multiple roles of the domain actors, long duration) but especially because of the complexity to gather, characterize and freeze a set of dimensioning input data (evolution and change of stakeholders' expectations, knowledge of facility, …). To secure the delivery of decommissioning and waste management projects, it is necessary to identify and respond quickly to changing input data. To address this complexity Model-Based Systems Engineering (MBSE) approaches can replace today's traditional document-centric engineering approach and ease change management during a project. They promote modelling, models and data management principles that are largely used in several other domains with success. Moreover, these approaches enables creation of a structured set of data, organized through various criteria, and above all, enabling request and extraction. Subsequently, those processes enabled us to develop a rule engine automatically computing some of dismantling process key parameters from input data. By applying these principles to nuclear waste management infrastructure projects, we have developed a model-based approach for the study of nuclear waste treatment scenarios. Based on a meta-model and through shared languages we have been able to experiment a 40% time saving on the treatment of changes impacting the design. It represents 10% time saving on the whole project. Based on this first proof of concept and the encouraging results, the scope of the approach will be extended to simulate all types of properties of the scenario under study.
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https://hal.mines-ales.fr/hal-03707309
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Soumis le : mardi 28 juin 2022 - 14:51:28
Dernière modification le : jeudi 30 juin 2022 - 03:06:03

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  • HAL Id : hal-03707309, version 1

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Jeremy Bourdon, Pauline Suchet, Chamane Leuleu, Victor Richet. Model-Based approach for the study of nuclear waste treatment scenarios. EURADWASTE ’22 - 10th Euratom Conference Radioactive Waste Management, May 2022, Lyon, France. , 2022. ⟨hal-03707309⟩

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