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Development of a CFD‐Based Hover Performance Prediction Tool for Engineering Analysis

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This paper concerns the development of a second‐generation implementation of the vorticity embedding method for the prediction of rotor hover performance. The basic method, encoded in the HELIX‐IA code, is an Eulerian‐Lagrangian, computational fluid dynamics (CFD)‐based procedure that utilizes an Eulerian potential flow solution combined with a Lagrangian wake convection. The blade(s) can be represented either as a lifting‐surface or as a lifting‐line with a specified circulation (loading) distribution. Furthermore, the basic method is hybridized with a Reynolds averaged Navier‐Stokes (RANS) code, TURNS. The HELIX‐IA code provides the wake convection and associated induced inflow while the TURNS code provides the surface viscous flow. The method is grid point efficient because the CFD solver is not burdened with resolving the entire shed wake. The importance of recent enhancements to the basic HELIX‐IA methodology is demonstrated by a good comparison of predictions (performance, loading and wake trajectory) with available model scale data. Application of the new hybrid option of HELIX‐IA to the UH‐60A Black Hawk rotor provides a first demonstration of this method. Convergence of the hybrid solution is good, showing the basic viability of the approach. Preliminary computations show a strong dependence of wake trajectory on tip loading, and the need for tip grid improvement in order to attain better accuracy.
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Document Type: Research Article

Affiliations: ELORET Corp., Ames Research Center, Moffett Field, CA

Publication date: 01 July 2007

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  • The Journal of the American Helicopter Society is the world's only scientific journal dedicated to vertical flight technology. It is a peer-reviewed technical journal published quarterly by AHS International and presents innovative papers covering the state-of-the-art in all disciplines of rotorcraft design, research and development. (Please note that AHS members receive significant discounts on articles and subscriptions.)

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