most citedDeep Operator Learning-based Surrogate Models with Uncertainty Quantification for Optimizing Internal Cooling Channel Rib Profiles

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2023

A Physics-Guided Bi-Fidelity Fourier-Featured Operator Learning Framework for Predicting Time Evolution of Drag and Lift Coefficients

Amirhossein Mollaali, Izzet Sahin, Iqrar Raza +3

In the pursuit of accurate experimental and computational data while minimizing effort, there is a constant need for high-fidelity results. However, achieving such results often re…

physics.flu-dyn2023★ 2 cited

Deep Operator Learning-based Surrogate Models with Uncertainty Quantification for Optimizing Internal Cooling Channel Rib Profiles

Izzet Sahin, Christian Moya, Amirhossein Mollaali +2

This paper designs surrogate models with uncertainty quantification capabilities to improve the thermal performance of rib-turbulated internal cooling channels effectively. To cons…