Postdoctoral Research Associate

The petitioner proposes to continue his research in improving the simulation of turbulent fluid flows using a combination of computational fluid dynamics (CFD), machine learning, and experimental modeling. His work focuses on optimizing aerodynamic and hydrodynamic performance to improve design reliability and reduce fuel consumption in high-performance vehicles and renewable energy systems. He intends to develop machine learning models for CFD to assist major aerospace firms in optimizing aircraft design processes.

The petitioner proposes to develop high-order numerical methods and reduced-order modeling techniques to advance the performance of mechanical and aerospace technologies. This work focuses on creating accurate and efficient simulations of high-speed flows to optimize the design of high-performance aerospace vehicles, such as hypersonic aircraft. The endeavor aims to reduce computational costs while preserving accuracy in multi-parameter analysis for supersonic and hypersonic environments.

The petitioner proposes to develop and utilize innovative techniques based on systems engineering, modeling, and analysis for the design of large-scale, long-term aerospace mission architectures. This work focuses on optimizing the performance and cost of complex aerospace missions through advanced space systems, automation, and robotics research.