Improving Aircraft Design with Machine Learning and a More Efficient Model of Turbulent Airflows

July 28, 2022

Turbulent airflows are chaotic and unpredictable: consider the bumps and jolts one might experience during an airplane flight encountering turbulent air. With increased knowledge of turbulent airflows, airplane designs could become safer, more resilient, and ultimately more fuel efficient.  H. Jane Bae, Assistant Professor of Aerospace, has developed a way to use machine learning to further improve the design process. [Caltech story]

Tags: research highlights GALCIT H. Jane Bae