Flow Physics and Distillation of the Gust-Induced Stall of a Low Aspect Ratio Wing
Abstract
A three-year program is proposed to investigate, classify and develop tools for the estimation of forceson low aspect ratio wings during gust encounters. The performance of lightweight next-generationaircraft is more strongly affected by incident gusts than their larger and heavier antecedents, andparticularly by large amplitude gusts that induce stall. Progress in this area has been impeded by thelack of a canonical gust structure (e.g. vertical jet, vortex, oscillating free stream) that encompasses asufficiently wide range of operating conditions and is achievable in both experimental facilities and incomputational frameworks. Through a joint experimental, computational and theoretical investigation,the proposed research program aims to develop a new taxonomy of gusts based primarily on theaerodynamic response they induce rather than on their original structure. By classifying in this fashion,gusts of different nominal structure but similar response would be directly comparable across a diversespectrum of facilities. A novel gust wind tunnel facility will be developed and used to build a database ofgust flow responses. State-of-the-art pattern recognition algorithms from machine learning will betrained on these data, as well as those from high-fidelity computational and low-order vortex-modelingstudies, to classify gusts based on pre-chosen criteria, to estimate their force response, and to proposenew classifications from the features detected in, for example, their surface measurements. Tools fromcontrol theory will be used to compute optimal worst-case gusts from among the identified classes.Experiments will explore the effectiveness of two different forms of actuation for controlling the wingresponse. The proposing team comprises expertise spanning fundamental flow physics and modernmachine learning and control-theoretic optimization techniques, and is well situated to address thissubject with unprecedented thoroughness.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 28, 2018
- Source ID
- FA95501810440
Entities
People
- Jeffrey Eldredge
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of California, Los Angeles