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cs.LG2025
A Kernel-based Resource-efficient Neural Surrogate for Multi-fidelity Prediction of Aerodynamic Field
Apurba Sarker, Reza T. Batley, Darshan Sarojini +1
Surrogate models provide fast alternatives to costly aerodynamic simulations and are extremely useful in design and optimization applications. This study proposes the use of a rece…
cs.LG2022★ 2 cited
Manifold Alignment-Based Multi-Fidelity Reduced-Order Modeling Applied to Structural Analysis
Christian Perron, Darshan Sarojini, Dushhyanth Rajaram +2
This work presents the application of a recently developed parametric, non-intrusive, and multi-fidelity reduced-order modeling method on high-dimensional displacement and stress f…