Grigorios Delipei

A Framework for Multi-Physics Modeling, Design Optimization and Uncertainty Quantification of Fast-Spectrum Liquid-Fueled Molten-Salt Reactors

APPLIED SCIENCES-BASEL, 14(17).

A component diagnostic and prognostic framework for pump bearings based on deep learning with data augmentation

RELIABILITY ENGINEERING & SYSTEM SAFETY, 247.

A system diagnostic and prognostic framework based on deep learning for advanced reactors

PROGRESS IN NUCLEAR ENERGY, 170.

Fuel performance code to code comparative analysis for the OECD/NEA MPCMIV benchmark

NUCLEAR ENGINEERING AND DESIGN, 430.

International fuel performance study of fresh fuel experiments for PCMI effects during RIA experiments

NUCLEAR ENGINEERING AND DESIGN, 430.

Modeling a generic Pebble Bed High-Temperature Gas-Cooled Reactor to perform load-following using Simulink

NUCLEAR ENGINEERING AND DESIGN, 428.

Reinforcement Learning-Based Control Sequence Optimization for Advanced Reactors

JOURNAL OF NUCLEAR ENGINEERING, 5(3), 209–225.

Fuel performance uncertainty quantification and sensitivity analysis in the presence of epistemic and aleatoric sources of uncertainties

FRONTIERS IN ENERGY RESEARCH, 11.

CTF-PARCS Core Multi-Physics Computational Framework for Efficient LWR Steady-State, Depletion and Transient Uncertainty Quantification

ENERGIES, 15(14).

Predictions of component Remaining Useful Lifetime Using Bayesian Neural Network

PROGRESS IN NUCLEAR ENERGY, 146.

Summary of comparative analysis and conclusions from OECD/NEA LWR-UAM benchmark Phase I

NUCLEAR ENGINEERING AND DESIGN, 384.