Dispersed Two-Phase Flow Modelling for Nuclear Safety in the NEPTUNE_CFD Code. (3rd December 2017)

• Record Type: Journal Article
• Authors: Mimouni, Stephane; Benguigui, William; Fleau, Solène; Foissac, Arnaud; Guingo, Mathieu; Hassanaly, Mickael; Lavieville, Jérôme; Malet, Jeanne; Méchitoua, Namane; Mérigoux, Nicolas; Vincent, Stéphane
• Other Names: Tiselj Iztok Academic Editor.
• Is Part Of: Science and technology of nuclear installations. Volume 2017(2017)
• Publication Date: 2017-12-03
• Subjects: Nuclear engineering -- Periodicals; Nuclear facilities -- Periodicals; Nuclear engineering; Nuclear facilities; Electronic journals; Periodicals; 621.48
• DOI: 10.1155/2017/3238545
• Languages: English
• ISSNs: 1687-6075

Abstract

Abstract : The objective of this paper is to give an overview of the capabilities of Eulerian bifluid approach to meet the needs of studies for nuclear safety regarding hydrogen risk, boiling crisis, and pipes and valves maintenance. The Eulerian bifluid approach has been implemented in a CFD code named NEPTUNE_CFD. NEPTUNE_CFD is a three-dimensional multifluid code developed especially for nuclear reactor applications by EDF, CEA, AREVA, and IRSN. The first set of models is dedicated to wall vapor condensation and spray modelling. Moreover, boiling crisis remains a major limiting phenomenon for the analysis of operation and safety of both nuclear reactors and conventional thermal power systems. The paper aims at presenting the generalization of the previous DNB model and its validation against 1500 validation cases. The modelling and the numerical simulation of cavitation phenomena are of relevant interest in many industrial applications, especially regarding pipes and valves maintenance where cavitating flows are responsible for harmful acoustics effects. In the last section, models are validated against experimental data of pressure profiles and void fraction visualisations obtained downstream of an orifice with the EPOCA facility (EDF R&D). Finally, a multifield approach is presented as an efficient tool to run all models together.