6 citations · 7 across the 4 of their papers we have counts for
4 papers
AI-driven Uncertainty Quantification & Multi-Physics Approach to Evaluate Cladding Materials in a Microreactor
Alex Foutch, Kazuma Kobayashi, Ayodeji Alajo +2
The pursuit of enhanced nuclear safety has spurred the development of accident-tolerant cladding (ATC) materials for light water reactors (LWRs). This study investigates the potent…
Recent Advances in Uncertainty Quantification Methods for Engineering Problems
Dinesh Kumar, Farid Ahmed, Shoaib Usman +2
In the last few decades, uncertainty quantification (UQ) methods have been used widely to ensure the robustness of engineering designs. This chapter aims to detail recent advances…
Data-driven multi-scale modeling and robust optimization of composite structure with uncertainty quantification
Kazuma Kobayashi, Shoaib Usman, Carlos Castano +2
It is important to accurately model materials' properties at lower length scales (micro-level) while translating the effects to the components and/or system level (macro-level) can…
Digital Twin-Centered Hybrid Data-Driven Multi-Stage Deep Learning Framework for Enhanced Nuclear Reactor Power Prediction
James Daniell, Kazuma Kobayashi, Ayodeji Alajo +1
The accurate and efficient modeling of nuclear reactor transients is crucial for ensuring safe and optimal reactor operation. Traditional physics-based models, while valuable, can…