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High Order Wavelet-Based Multiresolution Technology for Airframe Noise Prediction

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNL04AB13P
Agency Tracking Number: 034424
Amount: $69,975.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 2004
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
215 Wynn Dr.
Huntsville, AL 35805
United States
DUNS: 185169620
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Essam Sheta
 Principal Investigator
 (256) 726-4800
 jls@cfdrc.com
Business Contact
 Ashok Singhal
Title: President & CEO
Phone: (256) 726-4858
Email: jls@cfdrc.com
Research Institution
N/A
Abstract

An integrated framework is proposed for efficient prediction of rotorcraft and airframe noise. A novel wavelet-based multiresolution technique and high-order accurate WENO scheme is proposed for efficient capturing of noise sources and unsteady flowfield. A wavelet compression is used to store the flowfield as a multi-level representation in functional space. The primary solution progresses using a coarse grid. The regularity of the flow field data is used to identify regions of steep variation. These regions are selectively solved recursively in the finer grid-levels and accurate information is injected into the coarse grids to correctly represent all flow features. In Phase I, a three-dimensional wavelet-based multiresolution algorithm, and an acoustic analogy module based on the Kirchhoff-Ffowcs Williams and Hawking methodology will be developed. The feasibility of the proposed technology will be demonstrated by prediction of three-dimensional noise source and acoustic waves of vortex-blade interaction problems. The proposed technology will provide 2-3 orders-of-magnitude reductions in CPU requirements over existing techniques. In Phase II, the wavelet compression methodology will be integrated into a high-fidelity CFD module. An efficient data structure will be developed to store and update the multiresolution data. The modules will be coupled with a nonlinear finite-element structure dynamic module for noise prediction of flexible structures.

* Information listed above is at the time of submission. *

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