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11/24/2022
Non-Intrusive Uncertainty Quantification for U3Si2 and UO2 Fuels with SiC/SiC Cladding using BISON for Digital Twin-Enabling Technology
U.S. Nuclear Regulatory Committee (NRC) and U.S. Department of Energy (D...
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11/23/2022
Physics-Informed Multi-Stage Deep Learning Framework Development for Digital Twin-Centred State-Based Reactor Power Prediction
Computationally efficient and trustworthy machine learning algorithms ar...
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11/06/2022
Recent Advances in Uncertainty Quantification Methods for Engineering Problems
In the last few decades, uncertainty quantification (UQ) methods have be...
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10/14/2022
Uncertainty Quantification and Sensitivity analysis for Digital Twin Enabling Technology: Application for BISON Fuel Performance Code
To understand the potential of intelligent confirmatory tools, the U.S. ...
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10/14/2022
Reliability-Based Robust Design Optimization Method for Engineering Systems with Uncertainty Quantification
Robust optimization is a method for optimization under uncertainties in ...
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10/13/2022
Surrogate Modeling-Driven Physics-Informed Multi-fidelity Kriging: Path Forward to Digital Twin Enabling Simulation for Accident Tolerant Fuel
The Gaussian Process (GP)-based surrogate model has the inherent capabil...
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10/13/2022
Data-driven multi-scale modeling and robust optimization of composite structure with uncertainty quantification
It is important to accurately model materials' properties at lower lengt...
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09/30/2022
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 i...
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09/30/2022
Digital Twin and Artificial Intelligence Incorporated With Surrogate Modeling for Hybrid and Sustainable Energy Systems
Surrogate modeling has brought about a revolution in computation in the ...
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09/25/2022