17 citations · 17 across the 2 of their papers we have counts for
4 papers
Aerodynamic Data Fusion Towards the Digital Twin Paradigm
S. Ashwin Renganathan, Kohei Harada, Dimitri N. Mavris
We consider the fusion of two aerodynamic data sets originating from differing fidelity physical or computer experiments. We specifically address the fusion of: 1) noisy and in-com…
Koopman-Based Approach to Non-intrusive Projection-Based Reduced-Order Modeling with Black-Box High-Fidelity Models. Part II: Application
S. Ashwin Renganathan
A methodology for non-intrusive, projection-based non-linear model reduction originally presented by Renganathan et. al. (2018)~\cite{renganathan2018koopman} is further extended to…
Application of Convolutional Neural Network to Predict Airfoil Lift Coefficient
Yao Zhang, Woong-Je Sung, Dimitri Mavris
The adaptability of the convolutional neural network (CNN) technique for aerodynamic meta-modeling tasks is probed in this work. The primary objective is to develop suitable CNN ar…
A Methodology for Projection-Based Model Reduction with Black-Box High-Fidelity Models
S. Ashwin Renganathan, Yingjie Liu, Dimitri N. Mavris
This paper presents a methodology that enables projection-based model reduction for black-box high-fidelity models such as commercial CFD codes. The methodology specifically addres…