most citedMachine Learning and Artificial Intelligence-Driven Multi-Scale Modeling for High Burnup Accident-Tolerant Fuels for Light Water-Based SMR Applications

3 citations · 4 across the 4 of their papers we have counts for

collaborators

4 papers

stat.CO20221 cited

Reliability-Based Robust Design Optimization Method for Engineering Systems with Uncertainty Quantification

Richa Verma, Dinesh Kumar, Kazuma Kobayashi +1

Robust optimization is a method for optimization under uncertainties in engineering systems and designs for applications ranging from aeronautics to nuclear. In a robust design pro…

cs.LG2022

Leveraging Industry 4.0 -- Deep Learning, Surrogate Model and Transfer Learning with Uncertainty Quantification Incorporated into Digital Twin for Nuclear System

M. Rahman, Abid Khan, Sayeed Anowar +5

Industry 4.0 targets the conversion of the traditional industries into intelligent ones through technological revolution. This revolution is only possible through innovation, optim…

cs.AI2022

Digital Twin and Artificial Intelligence Incorporated With Surrogate Modeling for Hybrid and Sustainable Energy Systems

Abid Hossain Khan, Salauddin Omar, Nadia Mushtary +3

Surrogate modeling has brought about a revolution in computation in the branches of science and engineering. Backed by Artificial Intelligence, a surrogate model can present highly…

eess.SY20223 cited

Machine Learning and Artificial Intelligence-Driven Multi-Scale Modeling for High Burnup Accident-Tolerant Fuels for Light Water-Based SMR Applications

Md. Shamim Hassan, Abid Hossain Khan, Richa Verma +4

The concept of small modular reactor has changed the outlook for tackling future energy crises. This new reactor technology is very promising considering its lower investment requi…