Department of Nuclear Engineering
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[Seminar] Pellet Cladding Gap Heat transfer High to Low modeling for Rod Ejection Accident in an Uncertainty Quantification Framework
August 20, 2020 @ 4:00 pm - 5:00 pm
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Postdoctoral Research Scholar
Abstract
High to Low modeling approaches can alleviate the computationally expensive fuel modeling in nuclear reactor’s transient uncertainty quantification. This is especially the case for Rod Ejection Accident (REA) in Pressurized Water Reactors (PWR) where strong multi-physics interactions occur. For this reason we develop and propose a pellet cladding gap heat transfer (Hgap) High to Low modeling methodology for a PWR REA in an uncertainty quantification (UQ) framework. The methodology involves the calibration of a simplified Hgap model based on high fidelity simulations with the fuel-thermomechanics code ALCYONE1. The calibrated model is then introduced into a Best Estimate (BE) multiphysics coupling between APOLLO3® (neutronics) and FLICA4 (thermal-hydraulics). This creates an Improved Best Estimate (IBE) coupling that is then used for an UQ study. The results indicate that with the IBE the distance to boiling crisis uncertainty is decreased from 57 % to 42 %. This is reflected in the decrease of the sensitivity of Hgap. In the BE coupling Hgap was responsible for 50 % of the output variance while in IBE it is close to 0. These results highlight the potential gain of using High to Low approaches for Hgap modeling in REA uncertainty analyses.
Biography
Gregory Kyriakos Delipei, postdoctoral research scholar in the Reactor Dynamics and Fuel Modeling Group. He has a background in Electrical and Computer Engineering (bachelor from Aristotle University of Thessaloniki, Greece) with specialization in Reactor Physics and Engineering (Master from University of Paris Saclay, France) and he recently obtained his PhD (from CEA / École Polytechnique of Paris, France) in the field of transient multiphysics uncertainty quantification. His main research area is multiphysics uncertainty quantification and multifidelity fuel performance modeling. In the former he is interested in the design of experiments, dimension reduction, surrogate models, uncertainty propagation, sensitivity analysis and model calibration. In the latter he is developing methods that use high fidelity fuel performance codes in order to inform lower fidelity codes that can be used efficiently in the uncertainty quantification framework.
Thursday, August 20. 2020
4:00 pm seminar
https://ncsu.zoom.us/j/94957658846
216 Mann Hall
The seminar will be recorded
Due to the current circumstances, refreshments will not be served.
