A novel uncertainty propagation method for robust aerodynamic design

Padulo, M., Campobasso, M.S. and Guenov, M.D. (2011) A novel uncertainty propagation method for robust aerodynamic design. AIAA Journal, 49(3), pp. 530-543. (doi: 10.2514/1.J050448)

Abstract

This article addresses two modelling aspects of wind turbine aerofoil aerodyna-mics based on the solution of the Reynolds-averaged Navier–Stokes (RANS) equations. One of these is the effect of an a priori method for structured grid adaptation aimed at improving the wake resolution. The presented results emphasize that the proposed adaptation strategy greatly improves the wake resolution in the far field, whereas the wake is completely diffused by the non-adapted grid with the same number and spacing patterns of grid nodes. The proposed adaptation approach can be easily included in the structured generation process of both commercial and in-house-structured mesh generators. The other numerical aspect examined herein is the impact of particular choices for turbulence modelling on the predicted solution. This includes the comparative analysis of numerical solutions obtained by using different turbulence models, and also aims at quantifying the solution inaccuracy arising from not modelling the laminar-to-turbulent transition. It is found that the drag forces obtained by considering the flow as transitional or fully turbulent may differ by 50 per cent. All these issues are investigated using a special-purpose hyperbolic grid generator and two multi block structured finite volume RANS codes. The numerical experiments consider the flow field past a wind turbine aerofoil for which an exhaustive campaign of steady and unsteady experimental measurements was conducted. The predictive capabilities of the CFD solvers are validated by comparing experimental data and numerical predictions for selected flow regimes. The incompressible analysis and design code XFOIL is also used to support the findings of the comparative analysis of numerical RANS-based results and experimental d

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Campobasso, Dr Michele
• Authors: Padulo, M., Campobasso, M.S., and Guenov, M.D.
• Subjects: T Technology > TL Motor vehicles. Aeronautics. Astronautics
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: AIAA Journal
• Publisher: American Institute of Aeronautics and Astronautics, Inc.
• ISSN: 0001-1452
• ISSN (Online): 1533-385X