Description

This project aims to explore the use of multi-fidelity modelling techniques, with a focus on Gaussian Process (GP) modeling, for the analysis and design of aerospace systems. The student will investigate how GP models can be used to combine data from high-fidelity and low-fidelity simulations to improve predictive accuracy while reducing computational costs. The project will involve developing a multi-fidelity framework (or more than one), applying it/them to a selected aerospace application (e.g., aerodynamic performance, structural analysis), and comparing its/theirs performance to single-fidelity models.

Key Objectives

• A review of literature on multi-fidelity modeling and Gaussian Process in aerospace engineering.

• Development and implementation of a multi-fidelity Gaussian Process model for a specific aerospace system or component.

• Comparative analysis of the multi-fidelity approach versus traditional single-fidelity methods.