Digital twin concepts with uncertainty for nuclear power applications
B Kochunas, X Huan - Energies, 2021 - mdpi.com
Digital Twins (DTs) are receiving considerable attention from multiple disciplines. Much of
the literature at this time is dedicated to the conceptualization of digital twins, and associated …
the literature at this time is dedicated to the conceptualization of digital twins, and associated …
Passive safety systems analysis: A novel approach for inverse uncertainty quantification based on Stacked Sparse Autoencoders and Kriging metamodeling
In passive safety system analysis, it is important to provide the uncertainty quantification of
the Thermal-Hydraulic (TH) code output (eg, the amount of energy exchanged by the …
the Thermal-Hydraulic (TH) code output (eg, the amount of energy exchanged by the …
Scalable inverse uncertainty quantification by hierarchical bayesian modeling and variational inference
Inverse Uncertainty Quantification (IUQ) has gained increasing attention in the field of
nuclear engineering, especially nuclear thermal-hydraulics (TH), where it serves as an …
nuclear engineering, especially nuclear thermal-hydraulics (TH), where it serves as an …
Dimensional decomposition-aided metamodels for uncertainty quantification and optimization in engineering: A review
Quantitative analysis and optimal design under uncertainty are active research areas in
modern engineering structures and systems. A metamodel, as an effective mathematical …
modern engineering structures and systems. A metamodel, as an effective mathematical …
Leveraging Industry 4.0: Deep Learning, Surrogate Model, and Transfer Learning with Uncertainty Quantification Incorporated into Digital Twin for Nuclear System
Industry 4.0 targets the conversion of the traditional industries into intelligent ones through
technological revolution. This revolution is only possible through innovation, optimization …
technological revolution. This revolution is only possible through innovation, optimization …
SAM-ML: Integrating data-driven closure with nuclear system code SAM for improved modeling capability
Advanced reactors often involve complicated thermal-fluid (TF) phenomena. Modeling such
phenomena with the traditional one-dimensional (1-D) system code is a challenging task …
phenomena with the traditional one-dimensional (1-D) system code is a challenging task …
Functional PCA and deep neural networks-based Bayesian inverse uncertainty quantification with transient experimental data
This work focuses on developing an inverse uncertainty quantification (IUQ) process for time-
dependent responses, using dimensionality reduction by functional principal component …
dependent responses, using dimensionality reduction by functional principal component …
[HTML][HTML] Towards the uncertainty quantification of semi-empirical formulas applied to the added resistance of ships in waves of arbitrary heading
The present paper examines a semi-empirical framework for the estimation of added
resistance in arbitrary wave heading under consideration of uncertainty quantification. In this …
resistance in arbitrary wave heading under consideration of uncertainty quantification. In this …
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 …
[HTML][HTML] Global sensitivity analysis for segmented inverse uncertainty quantification in the safety analysis of nuclear power plants
Abstract Within the Best Estimate Plus Uncertainty framework for the safety analysis of
Nuclear Power Plants, the quantification of the uncertainties affecting the Thermal …
Nuclear Power Plants, the quantification of the uncertainties affecting the Thermal …