Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/116084
Title: Flutter simulation and prediction with CFD-based reduced-order model
Authors: Lai, K.L. 
Won, K.S. 
Koh, E.P.C. 
Tsai, H.M. 
Issue Date: 2006
Source: Lai, K.L.,Won, K.S.,Koh, E.P.C.,Tsai, H.M. (2006). Flutter simulation and prediction with CFD-based reduced-order model. Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 7 : 5229-5245. ScholarBank@NUS Repository.
Abstract: The paper presents an approach for the simulating and predicting flutter of complex configurations. One of the major difficulties in direct numerical simulation is the extensive computational time required. A hybrid approach combining CFD and reduced-order model (ROM) on the other hand takes advantage of the accuracy of CFD-based computations and the efficiency of a ROM model. In this work, the CFD-based aeroelastic computations involve a Cartesian-based Euler solver with embedded multi-grid sequencing for flow computations, using the small perturbation techniques to implement the unsteady boundary conditions on the stationary grid. The structural response of the system is computed using the mode superposition technique. Data communication between the non-matching fluid and structure domains is performed using the Constant Volume Tetrahedron (CVT) interpolation method. For a given set of flight conditions, the CFD solver is first performed to compute the flow solutions for a prescribed input that are needed to construct the reduced-order model of the system. The ROM results are compared with the CFD-solver results. The prediction of flutter boundary for the AGARD 445.6 wing is presented. Copyright © 2006 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
Source Title: Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/116084
ISBN: 1563478080
ISSN: 02734508
Appears in Collections:Staff Publications

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