Characterization of onset of dynamic stall for low Mach number flows

点击翻译按钮获取中文摘要

Dynamic stall is a common occurrence in maneuvering aerodynamic bodies (e.g., insect/bird wings, helicopter/wind turbine blades, aircraft wings) which is characterized by large increases in unsteady aerodynamic loads. Such loads can lead to catastrophic and fatigue failure of aircraft wings and rotor blades in helicopters and wind turbines. The flow physics affecting the onset of dynamic stall remains unclear and is highly dependent on a large parameter space consisting of geometry, type of maneuver, pitch rate, and Reynolds and Mach numbers. The project will utilize a combination of novel data analysis techniques with high fidelity simulations to understand dynamic stall onset. A clear understanding and characterization of stall onset will pave the way for effective strategies to control and mitigate dynamic stall. The project has transformative implications for a broad range of applications including fixed-wing aircraft and rotating machinery. In addition, broader impacts are expected through curricular enhancements and recruiting women and underrepresented minorities.The goal of this project is to understand and characterize the onset of dynamic stall using efficient fluid simulations with data-driven analysis methods and experimental validation. The specific objectives are: (1) identify a universal parameter/marker of stall onset through characterization of stall incipience using a suite of physics-based, data-driven, and machine learning approaches, (2) use novel simulation strategies to effectively explore the large parameter space by employing a novel 4-D, space-time framework to remove transients and significantly reduce computation time and by efficiently exploring the parameter space using an adaptive, asynchronous, Bayesian sampling strategy, and 3) validate the universal parameter using experimental data and additional simulations, and investigate the role of acoustic radiation on stall onset. The proposed work consists of intellectual advances in identifying the underlying physical phenomenon that triggers dynamic stall onset, developing an innovative approach to efficiently remove flow transients, and investigating the effect of acoustics on laminar separation bubble dynamics. The project will leverage outreach and workforce development activities ongoing at Iowa State University.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.