Application of the MOCABA algorithm and the FSTC tool for source term predictions during severe accident scenarios. (May 2023)

• Record Type: Journal Article
• Authors: Stakhanova, A.; Gabrielli, F.; Sanchez-Espinoza, V.H.; Hoefer, A.; Pauli, E.M.
• Is Part Of: Annals of nuclear energy. Volume 184(2023)
• Publication Date: 2023-05
• Subjects: ASTEC -- Fast Source Term Calculation tool -- QUENCH-08 -- KONVOI-1300 -- Source term prediction; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2023.109703
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: Prediction algorithm based on MOCABA framework implemented in the FSTC tool. Prediction algorithm applied to the QUENCH-08 experiment simulations. Prediction algorithm applied to MBLOCA accident simulations at KONVOI NPP. Prediction results of hydrogen and xenon release are satisfactory. Presented results are the proof of concept of the implemented algorithm. Abstract: This paper describes the capabilities of the Fast Source Term Calculation (FSTC) tool developed by the Karlsruhe Institute of Technology (KIT) to perform time series predictions of the radiological source term (ST) during severe accident (SA) scenarios. The prediction algorithm implemented in FSTC is based on the MOCABA data assimilation framework, developed by Framatome, and requires a training database and actual measurements. The training database is assessed by employing coupling FSTC to the European reference Accident Source Term Evaluation Code (ASTEC), developed by IRSN. The prediction capabilities of FSTC is applied to evaluate: 1) the mass of released hydrogen during the QUENCH-08 experiment; 2) the xenon release to the environment during a Medium Break Loss of Coolant Accident (MBLOCA) SA scenario in a generic KONVOI nuclear power plant (NPP). The prediction results show a very promising employment of FSTC and the MOCABA algorithm in view of supporting the emergency response team during SA scenarios.