Transport class aircraft produce a significant amount of airframe noise during approach and landing due to exposed geometric discontinuities that are hidden during cruise. The leading-edge slat is a primary contributor to this noise. In previous work, use of a slat-cove filler (SCF) has proven to reduce airframe noise by filling the cove aft of the slat, eliminating the circulation region within the cove. The goal of this work is to extend and improve upon past experimental and computational efforts on the evaluation of a scaled high-lift wing with a superelastic shape memory alloy (SMA) SCF. Recent turbulence measurements of the Texas A&M University 3ft-by-4ft wind tunnel allow for more accurate representation of the flow through the test section in computational fluid dynamics (CFD) analysis. The finite volume models used in CFD analysis are coupled to structural finite element models using a framework compatible with an SMA constitutive model and significant deformation, enabling fluid-structure interaction (FSI) analysis of the SCF. Both fully-deployed and retraction/deployment cases are considered. The displacement of the SCF on the experimental model is measured at various stages of retraction/deployment using a laser displacement sensor and digital image correlation system. Due to a lack of structural stiffness in the 3D-printed plastic slat during retraction and SCF stowage, a rigid steel slat is incorporated into the physical model and preliminary wind tunnel tests are conducted at multiple angles of attack.
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Aerodynamic and Structural Evaluation of an SMA Slat-Cove Filler Using Computational and Experimental Tools at Model Scale
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Scholten, W, Patterson, R, Eustice, M, Cook, S, Hartl, D, Strganac, T, & Turner, T. "Aerodynamic and Structural Evaluation of an SMA Slat-Cove Filler Using Computational and Experimental Tools at Model Scale." Proceedings of the ASME 2018 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation, and Control of Adaptive Systems; Integrated System Design and Implementation. San Antonio, Texas, USA. September 10–12, 2018. V001T04A019. ASME. https://doi.org/10.1115/SMASIS2018-8129
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