Scope and Objectives. Codes and Relevance. Topics. Which is better? Project Supervisor(s)

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1 Development of BFBT benchmark models for sub-channel code COBRA-TF versus System Code TRACE MSc Proposal 1 Fuel Assembly Thermal-Hydraulics Comparative Assessment of COBRA-TF and TRACE for CHF Analyses Development of automated modelling and analysis routines (pre-processors, code launchers, post-processors, etc.) Validation of void distributions and Critical Heat Flux (CHF) predictions in TRACE vs COBRA-TF against BFBT experimental data Quantify the added-value of using Sub-Channel versus System Code for CHF and Strategy for Coupling to Core Analysis Codes TRACE (System Code) COBRA-TF (Sub-Channel Code) Thermal Limits and Transient CHF Multi-Phase Flow and Heat Transfer Thermal Core Design Safety of Nuclear Power Plants A. Epiney Sub-channel code: Detailed model, but slow running Which is better? System code: Corse models, but fast running

2 Plant System Thermal-Hydraulics Codes Key Actor in Reactor Safety Analysis, Design and Licensing MSc Proposal 2 Plant System Thermal-Hydraulics Direct Generation of Plant System Simulation Models using CAD Geometry Creating plant system simulation models (TRACE, RELAP, etc.) is typically by hand (slow, cumbersome and error-prone) Development of advanced methods for creating plant system simulation models directly from 3D CAD (solid model) geometry Verification and Application for e.g. Nodalization Studies TRACE (System Code) SOLIDWORKS (3D CAD) Safety and Accident Analysis Multi-Phase Flow and Heat Transfer Nuclear Power Plant Design and Safety Systems Safety of Nuclear Power Plants I. Clifford

3 TRACE (System Code) Python and R statistical programming Safety and Accident Analysis Safety of Nuclear Power Plants Multiphase Flows Uncertainty Quantification and Statistics D. Wicaksono MSc Proposal 3 Plant System Thermal-Hydraulics Second-Order Global Sensitivity Analysis of Reflooding Model in TRACE Scope and Objectives Reflood Simulation in TH system code is based on parameterized phenomenological model. Model of FEBA Separate Effect Test Facility was developed at LRS for sensitivity and uncertainty analysis. 26 input parameters variation result in time-dependent output variation. Given such model: Can the model be simplified in terms of the number of parameters? How to characterize functional variation of the output? What is parameter sensitivity and their interactions w.r.t to the output? Uncertain Inputs Higher-order effects Sampling Uncertain (functional) Output Sensitivity Analysis Transient Sobol Sensitivity Indices

4 MSc Proposal 4 Core Physics and Neutronics Nuclear Data Uncertainty Propagation with Serpent Monte-Carlo Code Establishment and Enlargement of NUSS Nuclear Data (ND) Uncertainty Quantification (UQ) Methodology to Continuous-Energy Stochastic Transport + Depletion/Decay Code Serpent Conduct fuel depletion/decay calculations for selected cases to quantify Reactivity and Isotopic Uncertainties Benchmark Serpent/NUSS Results against PSI deterministic CASMO/SHARK-X methodology and TSUNAMI Study the effects from different nuclear data libraries (ENDF/B-VII.1, JENDL-4.0) and energy group structure. SERPENT (Monte-Carlo Transport) CASMO (Deterministic Transport) Fuel/Core Design and Safety, Spent Fuel Characterization Neutronics and Nuclear Data Special in Reactor Physics Uncertainty Quantification and Statistics D. Rochman and J. Herrero Method Development and Verification Comparisons of Contributors to K-eff uncertainty for OECD/NEA UAM BWR BOL Hot-Zero-Power Pin-Cell Serpent/NUSS? Code Validation with UQ Comparison of Average Differences against measured Isotopics for Swiss Irradiated Fuel Minor Actinides Uncertainties in Calculations from ND?

5 MSc Proposal 5 Core Physics and Neutronics Validation of MCNP for BWR Dosimetry with Uncertainty Assessments High-Fidelity 3-D Estimations of Fast Neutron Irradiation on Reactor structures for quantification of embrittlement levels Refinements of MCNPX Model for optimized flux predictions at specific locations of a Swiss BWR Coupling to 3-D core analysis models for volumetric source transfer and validation against dosimeter data Sensitivity Analysis and Uncertainty Quantifications (UQ) related to model parameters and neutron data libraries MCNPX (Monte-Carlo Neutron Transport) CASMO/SIMULATE (Core Analysis) Reactor design Fuel design Operation data Measurements Methodology Validation Studies Embrittlement and Ageing Safety Analyses (e.g. PTS) Neutronics Special in Reactor Physics Uncertainty Quantification and Statistics A. Vasiliev Reference CASMO/ SIMULATE Core models Neutron source Reference MCNPX model

6 MSc Proposal 6 Establishment of UQ Methodology for Falcon V1 Scope and Objectives LRS/STARS Part of the EPRI Development Team for the re-designed new Falcon V1 state-of-the-art FEM Fuel Performance Code Establishment of Falcon V1 Methodology for Base Irradiation within FMSYS Swiss Fuel Platform and Conduct Verification Studies Development of Post-Processing Interface to new Falcon V1 HDF5 file Output Structure Fuel Behaviour and Thermo-Mechanics Coupling to URANIE Platform for Uncertainty Quantification (UQ) related to manufacturing tolerances Falcon V1 (Fuel Thermo-Mechanics) URANIE (Uncertainty/Sensitivity Platform) Fuel Safety and Reliability FMSYS: Check/Enlarge FMSYS database Build Falcon Input Uranie: Define the manufacturing tolerances Make a Matrix of Falcon Input files Nuclear Fuels and Materials Heat Transfer and Structural Mechanics Uncertainty Quantification and Statistics Project Supervisor C. Cozzo Postprocess Falcon output Uncertainty quantification (e.g. T fuel = f(bu)