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Requirements Engineering enabled by Natural Language Processing and Artificial Intelligence for Nuclear Safety Demonstration

Emir Roumili 1, 2 Jean-François Bossu Vincent Chapurlat 1 Nicolas Daclin 1 Aleksei Iancheruk Robert Plana Jérôme Tixier 3
1 ISOAR - Ingénierie des Systèmes et des Organisations pour les Activités à Risque
LGI2P - Laboratoire de Génie Informatique et d'Ingénierie de Production, LSR - Laboratoire des Sciences des Risques
3 EUREQUA - Etude des Risques et de la Qualité de l’air
LGEI - Laboratoire de Génie de l'Environnement Industriel et des Risques Industriels et Naturels, LSR - Laboratoire des Sciences des Risques
Abstract : This article reports on a new method to elaborate and conduct the safety demonstration phase for Nuclear infrastructures in phase with System Engineering principles. More particularly, this method focus on helping and guiding engineers involved in nuclear safety demonstration into a better assessment considering the increasing complexity and the expectations from the licensing owner who has to accommodate for any new nuclear project. As a first part of this method, this article claims that MBSE coupled to Natural Language Processing (NLP) and Artificial Intelligence (AI) is facilitating the Nuclear safety demonstration process and allowing to early prevent for any issues the project may face during the design, construction, commissioning and exploitation phases.
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Conference papers
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https://hal.mines-ales.fr/hal-02974291
Contributor : Administrateur Imt - Mines Alès <>
Submitted on : Wednesday, October 21, 2020 - 4:56:31 PM
Last modification on : Friday, October 23, 2020 - 3:05:12 AM

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  • HAL Id : hal-02974291, version 1

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Emir Roumili, Jean-François Bossu, Vincent Chapurlat, Nicolas Daclin, Aleksei Iancheruk, et al.. Requirements Engineering enabled by Natural Language Processing and Artificial Intelligence for Nuclear Safety Demonstration. CSDM 2020 - Complex System Design and Management 2020, Dec 2020, Paris, France. ⟨hal-02974291⟩

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