Compression of aerodynamic databases using high-order singular value decomposition

Lorente, L. S. and Vega de Prada, José Manuel and Velázquez, A. (2010). Compression of aerodynamic databases using high-order singular value decomposition. "Aerospace Science and Technology", v. 14 (n. 3); pp. 168-177. ISSN 1270-9638. https://doi.org/10.1016/j.ast.2009.12.003.

Description

Title: Compression of aerodynamic databases using high-order singular value decomposition
Author/s:
  • Lorente, L. S.
  • Vega de Prada, José Manuel
  • Velázquez, A.
Item Type: Article
Título de Revista/Publicación: Aerospace Science and Technology
Date: May 2010
ISSN: 1270-9638
Volume: 14
Subjects:
Faculty: E.T.S.I. Aeronáuticos (UPM)
Department: Fundamentos Matemáticos de la Tecnología Aeronáutica [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

A methodology based on high-order singular value decomposition is presented to compress multidimensional (with the various dimensions associated with both the spatial coordinates and parameter values) aerodynamic databases. The method is illustrated with a database containing computational fluid dynamics calculations of the outer flow around a wing, with two free parameters, the Mach number and the angle of attack. Comparison is made between the results of compressing just one flow snapshot (for fixed values of the parameters), compressing a one-parameter family of snapshots, and compressing the whole database. Several compressing strategies are also discussed that deal with (a) treating the flow variables separately or considering all flow variables at a time, (b) considering the whole flow domain simultaneously or dividing it into blocks, and (c) using various measures of errors. The main conclusion is that a large compression factor is generally obtained. Furthermore, the compression factor increases exponentially as the dimension of the database increases for any fixed error, namely the compression factor increases by an order of magnitude with each new database dimension for an error level of 1%.

More information

Item ID: 6109
DC Identifier: http://oa.upm.es/6109/
OAI Identifier: oai:oa.upm.es:6109
DOI: 10.1016/j.ast.2009.12.003
Official URL: http://www.elsevier.com/locate/aescte
Deposited by: Memoria de Investigacion 2
Deposited on: 21 Feb 2011 10:46
Last Modified: 20 Apr 2016 14:44
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