With the advent of new design methodologies in computing power, propulsion systems, materials, and manufacturing processes, there is a tremendous potential to develop revolutionary hypersonic vehicle configurations that meet mission requirements. Traditional analysis and design methods face challenges due to complex interaction of different sub-disciplines such as propulsion, aerodynamics, structures, controls, and heat transfer. Research efforts are required to yield higher-fidelity vehicle configurations that will enable new tactical capabilities for the warfighter.

Our research advances design methodologies by incorporating multi-fidelity physics-based models representing nonlinear behavior of engineering disciplines. Multidisciplinary design optimization is conducted by incorporating cost-effective meta models, sensitivity analysis, uncertainty quantification, and AI tools for facilitating large-scale computational models. 

References:

1. Ramunno, M., Boyd, I., Camberos, J., and Grandhi, R.V., "Integrated Hypersonic Aero-Propulsion Model for Multidisciplinary Vehicle Analysis and Optimization," AIAA Journal of Propulsion and Power, Vol. 38, No.3, 2022, pp. 478-488.

2. Beachy, A., Bae, H., Boyd, I., and Grandhi, R.V., "Emulataor Embedded Neural Networks for Multi-Fidelity Conceptual Design Exploration of Hypersonic Vehicles," Journal of Structural and Multidisciplinary Optimization, Vol. 64, No.5, 2021, pp. 1-18.

3. Fischer,C.C., Grandhi, R.V., and Beran, P.S., "Bayesian Enhanced Low-Fidelity Correction Approach to Multi-Fidelity Aerospace Design," AIAA Journal, Vol. 56, No. 8, 2018, pp. 1-12.

key words

Multidisciplinary design optimization, structures, aerodynamics, heat transfer, propulsion, meta models, Controls, AI

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral and Senior applicants