Neural-based time series forecasting of loss of coolant accidents in nuclear power plants
In the last few years, deep learning in neural networks demonstrated impressive successes
in the areas of computer vision, speech and image recognition, text generation, and many …
in the areas of computer vision, speech and image recognition, text generation, and many …
Safety assessment of AP1000: Common transients, analysis codes and research gaps
The commercial operation of the AP1000 in China's Sanmen nuclear power plant
demonstrates the feasibility of reactors with advanced passive safety systems. However …
demonstrates the feasibility of reactors with advanced passive safety systems. However …
A review of neutronics and thermal hydraulics–based screening methods applied to accelerated nuclear fuel qualification
This paper reviews the state-of-the-art engineering approach for using thermal hydraulic
(TH) and neutronics modeling and simulation (M&S) tools to perform rapid screening studies …
(TH) and neutronics modeling and simulation (M&S) tools to perform rapid screening studies …
[HTML][HTML] Demonstration of the E-BEPU methodology for SL-LOCA in a Gen-III PWR reactor
The paper presents the first practical application of the alternative Extended Best Estimate
Plus Uncertainty (E-BEPU) methodology. The E-BEPU is the systematic risk-informed …
Plus Uncertainty (E-BEPU) methodology. The E-BEPU is the systematic risk-informed …
[HTML][HTML] Using machine learning to forecast and assess the uncertainty in the response of a typical PWR undergoing a steam generator tube rupture accident
TCH Nguyen, A Diab - Nuclear Engineering and Technology, 2023 - Elsevier
In this work, a multivariate time-series machine learning meta-model is developed to predict
the transient response of a typical nuclear power plant (NPP) undergoing a steam generator …
the transient response of a typical nuclear power plant (NPP) undergoing a steam generator …
Using machine learning to predict the fuel peak cladding temperature for a large break loss of coolant accident
W Sallehhudin, A Diab - Frontiers in Energy Research, 2021 - frontiersin.org
In this paper the use of machine learning (ML) is explored as an efficient tool for uncertainty
quantification. A machine learning algorithm is developed to predict the peak cladding …
quantification. A machine learning algorithm is developed to predict the peak cladding …
Multiphysics analysis of fuel fragmentation, relocation, and dispersal susceptibility–Part 3: Thermal hydraulic evaluation of large break LOCA under high-burnup …
Increasing the peak rod average burnup of pressurized water reactor (PWR) fuel beyond 62
GWd/tU may increase fuel fragmentation, relocation, and dispersal (FFRD) susceptibility …
GWd/tU may increase fuel fragmentation, relocation, and dispersal (FFRD) susceptibility …
Integrated framework for model assessment and advanced uncertainty quantification of nuclear computer codes under bayesian statistics
A framework for model evaluation and uncertainty quantification (UQ) is presented with
applications oriented to nuclear engineering simulation codes. Our framework is inspired by …
applications oriented to nuclear engineering simulation codes. Our framework is inspired by …
A comprehensive Bayesian framework for the development, validation and uncertainty quantification of thermal-hydraulic models
The development, validation and uncertainty quantification of closure laws used into thermal–
hydraulic system codes is a key issue before applying the BEPU (Best Estimate Plus …
hydraulic system codes is a key issue before applying the BEPU (Best Estimate Plus …
The large-break LOCA uncertainty analysis in a VVER-1000 reactor using TRACE and DAKOTA
O Safarzadeh, A Pourrostam - Nuclear Engineering and Design, 2023 - Elsevier
An uncertainty analysis is inevitable in simulating reactor performance, particularly in the
accident analysis for the estimation of safety borders. In this paper, the application of the …
accident analysis for the estimation of safety borders. In this paper, the application of the …