Towards Real-Time, 3D Coherent Structure Estimation for Flow Over Finite Wings

Abstract

Coherent flow structures significantly influence the unsteady lift characteristics of a maneuvering aircraft. The formation, dynamics of evolution, and breakup of coherent structures are still not well understood, even though dynamic interaction with these flow structures promises gains in lift enhancement, efficiency, and maneuverability. A long-term goal is to achieve accurate, real-time estimation of 3D coherent flow structures over a finite wing. Estimation of coherent structures evolving over a wing may provide insight into how the physical flow field produces the aerodynamic forces, and it may provide a method for flow field interrogation when volumetric flow measurements are not available. Further, coherent flow structure estimation is a prerequisite for effective, model-based flow control that targets coherent structures. The state-of-the-art in data-driven estimation of unsteady flows utilizes surface pressure measurements to infer the nearby flow over a wing. However, to-date, data-driven flow-field estimation is only 2D, suffers from a strong dependence on the training dataset, and does not provide a method for optimally placing sensors for inference of coherent structures. The objective of this project is to construct a principled framework for optimal pressure sensor placement and subsequent real-time estimation of 3D coherent flow structures that is extensible beyond operating points of the training data. The technical approach is to combine tools from data science, experimental fluid mechanics, and estimation theory to yield a novel and accurate estimation framework. Three specific research tasks to achieve this objective are: (1) construct dynamic models for 3D coherent flows structures over a finite wing, (2) create a design methodology for sparse, optimal sensor placement, and (3) experimentally demonstrate 3D coherent structure estimation in real-time. The anticipated outcomes of the proposed research include significant progress on the fundamental understanding of coherent structure estimation and eventual long-term performance gains for vehicles of the U.S. Air Force.

Document Details

Document Type
DoD Grant Award
Publication Date
Jan 21, 2022
Source ID
FA95502110307XX0

Entities

People

  • Francis D Lagor

Organizations

  • Air Force Office of Scientific Research
  • Research Foundation for the State University of New York
  • United States Air Force

Tags

Fields of Study

  • Engineering
  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Fluid Dynamics (CFD)
  • Fluid Mechanics and Fluid Dynamics.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference