CAREER: Effect of subgrid-scale anisotropy on wall-modeled large-eddy simulations for complex flows

Turbulent fluid flow plays a central role in technologies encountered in daily life, including aircraft, automobile, and energy systems. The ability to predict the behavior of a turbulent flow near solid surfaces is important, because it affects drag, efficiency, and stability. The flow can separate from a solid surface in many practical situations. Separation creates complex motions that are difficult to predict. Current modeling tools often struggle in these conditions, which limits their usefulness as a design tool. This CAREER project will improve the reliability of turbulence modeling. It will address how small motions near surfaces influence the overall flow behavior. The outcomes will strengthen predictive models and keep their computational costs manageable. The project will integrate research and education by training students in fluid dynamics and modeling techniques and by engaging audiences in outreach activities that promote scientific literacy. The project aligns with NSF priorities by supporting advanced manufacturing of engineering applications such as aircraft, ships, and energy systems. The research will focus on understanding how the directionality of unresolved small-scale turbulent motion affects models used for large-scale flow prediction near walls. The project will begin by analyzing high-resolution flow data to examine how these small motions behave under different conditions, including both attached flows and flows that separate from surfaces. This analysis will reveal which features of the small-scale motion are most important for accurate modeling. Guided by these findings, new modeling approaches will be developed that incorporate these effects into existing near-wall frameworks. The models will be evaluated using a range of challenging flow configurations relevant to engineering applications and assessed against experimental measurements and high-fidelity reference data. This project will support a sustained research and education program, providing hands-on research experiences for undergraduate and graduate students, developing course and training materials in turbulence modeling, and hosting outreach activities for local high school students and teachers. The outcomes will contribute to increase the education of engineering students while advancing tools that benefit aerospace, automotive, and energy industries. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2543406 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Jane Bae | Institution: California Institute of Technology, PASADENA, CA | Award Amount: $575,000 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2543406 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2543406.html