Computationally Efficient Transonic and Viscous Potential Flow Aero-Structural Method for Rapid Multidisciplinary Design Optimization of Aeroelastic Wing Shaping Control
Speaker: Eric Ting and Daniel Chaparro, Intelligent Systems Division, NASA Ames Research Center
Presentation
Abstract
The demand for ultra-efficient commercial aircraft has driven wing configurations towards lightweight, highly flexible, high aspect ratio designs. To capitalize on wing flexibility and address adverse aeroelastic concerns, mission adaptive wing technologies have been sought after. One such technology is the Variable Camber Continuous Trailing Edge Flap (VCCTEF) which is a novel, full span, multi-purpose wing shaping control technology capable of adaptive reconfiguration of wing shapes for improved aerodynamic efficiency. Standard Computational Fluid Dynamics (CFD) tools require significant computing resources and the ability to automatically deform the mesh to account for aeroelasticity and wing shape optimization, which make them computationally expensive for large design space explorations. Computationally efficient conceptual aero-structural design tools and frameworks are thus needed in order to fully evaluate the potential of adaptive wing technologies in a multidisciplinary design optimization (MDO) environment.
To address this need, a rapid coupled transonic and viscous potential flow method with nonlinear structural finite element method has been developed. With an architecture combining a potential flow solver with transonic small disturbance (TSD) and integral boundary layer (IBL) codes, the aero-structural tool is capable of computing steady state aerodynamic and static aeroelastic solutions in a fraction of the time required by CFD counterparts. When implemented in an aero-structural framework, there is strong agreement between lift-to-drag ratios (L/D) from the transonic and viscous flow corrected potential flow solver and Reynolds Averaged Navier-Stokes (RANS) solutions provided by LAVA. Drag optimizations are conducted utilizing the rapid aero-structural tool examining different VCCTEF deflection profiles and configurations of inboard and outboard flaps. The results demonstrate the computational efficiency of the aero-structural tool for the initial MDO of the VCCTEF technology. The results can also help narrow the design space for more refined MDO studies that can more efficiently utilize higher order aerodynamic tools such as RANS.
Biographies
Eric Ting is a Research Engineer in the Advanced Control and Evolvable Systems (ACES) Group in the Intelligent Systems Division (Code TI) at NASA Ames Research Center. He first joined NASA Ames in 2012 and is currently conducting cutting edge research into next-generation ultra-efficient commercial aircraft concepts under the current Performance Adaptive Aeroelastic Wing (PAAW) element of the Advanced Air Transport Technology (AATT) Project at NASA. His primary responsibilities include conducting multidisciplinary research including, but not limited to: aerodynamic, structural, and aeroelasticity modeling, formulating and executing optimization, developing flight dynamic simulation systems, and aerospace machine learning and advanced control. He has a B.S. in Aerospace Engineering from the University of California, San Diego and a Master's degree from Santa Clara University in Mechanical Engineering with a specialization in Dynamics and Control. His Master's thesis was in the area of intelligent control for aircraft.
Daniel Chaparro is a Research Engineer in the Intelligent Systems Division at NASA Ames Research Center. He joined NASA Ames in 2015 and has since supported the Performance Adaptive Aeroelastic Wing (PAAW) Concepts element under the Advanced Air Transport Technology (AATT) Project where he is primarily responsible for developing MDAO modeling capabilities to evaluate flexible wing control concepts. Prior to NASA Ames, he was an Aerothermal Engineer for Boulder Wind Power (2012-2014) and Northrop Grumman Marine Systems (2009-2012). He has a B.S. in Aerospace Engineering from the Massachusetts Institute of Technology and an M.S. from Stanford University in Aeronautics and Astronautics.