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Laminar flow airfoil
Laminar flow airfoil







laminar flow airfoil laminar flow airfoil

Krumbein A., “ En Transition Prediction for 3D Wing Configurations Using Database Methods and a Local, Linear Stability Code,” Aerospace Science and Technology, Vol. 12, No. 8, 2008, pp. 592–598. R., “ Correlation-Based Transition Modeling for Unstructured Parallelized Computational Fluid Dynamics Codes,” AIAA Journal, Vol. 47, No. 12, 2009, pp. 2894–2906. D., “ Computational Fluid Dynamics Compatible Transition Modeling Using an Amplification Factor Transport Equation,” AIAA Journal, Vol. 52, No. 11, 2014, pp. 2506–2512. L., “ The Effect of Forward-Facing Steps on Stationary Crossflow Instability Growth and Breakdown,” AIAA Aerospace Sciences Meeting, AIAA Paper 2018-0817, 2018. Crouch J., “ Modeling Transition Physics for Laminar Flow Control,” AIAA Paper 2008-3832, June 2008. and Kawamura Y., “ Natural-Laminar-Flow Airfoil Development for a Lightweight Business Jet,” Journal of Aircraft, Vol. 40, No. 4, 2003, pp. 609–615. Sacco D., “ Natural Laminar Flow Technology: 20 Years of Piaggio P180 Experience,” Symposium on Applied Aerodynamics and Design of Aerospace Vehicles, SAROD 2009, Dec. 2009. and Imperatore B., “ Design and Test of the UW-5006 Transonic Natural-Laminar-Flow Wing,” Journal of Aircraft, Vol. 47, No. 3, 2010, pp. 783–795. N., “ Building a Practical Natural Laminar Flow Design Capability,” 35th AIAA Applied Aerodynamics Conference, AIAA Paper 2017-3059, 2017. The proposed methods make it possible to perform aerodynamic shape optimization considering laminar-to-turbulent transition in airfoil optimization. The multipoint optimization formulation produces an airfoil with a significant amount of laminar flow that is maintained at several flight conditions. The results show that the optimizer successfully reduces the drag coefficient by increasing the extent of laminar flow. Lift-constrained drag minimizations of airfoils for a single-point design and a multipoint design problem are performed. A coupled-adjoint approach that uses transpose Jacobian-vector products derived via automatic differentiation computes the transition prediction derivatives. The transition prediction is integrated with a Spalart–Allmaras turbulence model through a smoothed intermittency function, which makes it suitable for gradient-based optimization. The core of this framework is a Reynolds-averaged Navier–Stokes solver that is coupled with a simplified e N method to predict Tollmien–Schlichting and laminar separation-induced transition that consists of a laminar boundary-layer code and a database method for flow stability analysis. To address this need, we develop a discrete adjoint-based optimization framework where transition is modeled. However, there is a lack of tools for performing shape optimization of wings based on computational fluid dynamics considering laminar-to-turbulent transition. Natural laminar-flow wings are one of the most promising technologies for reducing fuel burn and emissions for commercial aviation.









Laminar flow airfoil