184 citations · 283 across the 24 of their papers we have counts for
3 papers · 1 filter
Deep Neural Operator Driven Real Time Inference for Nuclear Systems to Enable Digital Twin Solutions
Kazuma Kobayashi, Syed Bahauddin Alam
This paper focuses on the feasibility of Deep Neural Operator (DeepONet) as a robust surrogate modeling method within the context of digital twin (DT) for nuclear energy systems. T…
Improved generalization with deep neural operators for engineering systems: Path towards digital twin
Kazuma Kobayashi, James Daniell, Syed Bahauddin Alam
Neural Operator Networks (ONets) represent a novel advancement in machine learning algorithms, offering a robust and generalizable alternative for approximating partial differentia…
Explainable, Interpretable & Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life
Kazuma Kobayashi, Syed Bahauddin Alam
Artificial intelligence (AI) and Machine learning (ML) are increasingly used in energy and engineering systems, but these models must be fair, unbiased, and explainable. It is crit…