Aerodynamic database reconstruction via gappy high order singular value decomposition

López, Ana Isabel Moreno

doi:10.20868/upm.thesis.40613

Cited by 2 publications

(3 citation statements)

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“…From Equation (6.1), CF and s min are related to the gappy reconstruction method and their influence on the reconstruction errors have been proven insignificant [35,36]. Therefore, for now on CF = 0.1 and s min = 4, are set analogically to previous analyses.…”

Section: Chapter 6 Automatic Tuning Of Methods Parametersmentioning

confidence: 99%

“…Therefore, a sampling method can be designed that would allow, for instance, to minimise the number of experimental runs needed to reconstruct the complete domain by applying the methodology presented in [35,36]. This method would iteratively analyse the database showing the highest errors between two consecutive reconstructions and thus identifying them as the crucial points.…”

Section: Maxmentioning

confidence: 99%

“…A substantial increase in computational time efficiency has been shown for reciprocating engines, requiring real-time control [33], and conceptual design of aircraft components [34]. However, from the point of view of this Thesis, the most important application of HOSVD is employing it in reconstructing missing data in multidimensional databases contaminated with noise [35,36]. The method called gappy-noisy-HOSVD method is based on the iterative method to reconstruct lost data in two-dimensional databases invented by Everson and Sirovich, later improved independently by Beckers et al and Venturi et al The main contribution is its expansion to multidimensional databases and the optimisation of the number of retained modes which minimises the noise influence on data reconstruction.…”

Section: Introductionmentioning

confidence: 99%

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Aerodynamic database error filtering via high order singular value decomposition

Jarzabek¹

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Escuela Técnica Superior de Ingenieros Aeronéuticos Departamento de Vehículos Aeroespaciales Doctor of Philosophy Aerodynamic database error filtering via high order singular value decompositionby Artur Andrzej JARZABEK A method is presented to filter errors out in multidimensional databases. The method does not require any a priori information about the nature the errors. In particular, the errors need not to be small, neither random, nor exhibit zero mean. Instead, they are only required to be relatively uncorrelated to the clean information contained in the database. The method is based on an improved extension of a seminal iterative gappy reconstruction method (able to reconstruct lost information at known positions in the database) due to Everson and Sirovich (1995).The improved gappy reconstruction method is evolved as an error filtering method in two steps, since it is adapted to first (a) identify the error locations in the database and then (b) reconstruct the information in these locations by treating the associated data as gappy data. The resulting method filters out O(1) errors in an efficient fashion, both when these are random and when they are systematic, and also both when they concentrated and when they are spread along the database. The performance of the method is first illustrated using a two-dimensional toy model database resulting from discretizing a transcendental function and then tested on two CFD-calculated, three-dimensional aerodynamic databases containing the pressure coefficient on the surface of a wing for varying values of the angle of attack.A more general performance analysis of the method is presented with the intention of quantifying the randomness factor the method admits maintaining a correct performance and secondly, quantifying the size of error the method can detect. Lastly, some improvements of the method are proposed with their respective verification.iii UNIVERSIDAD POLITÉCNICA DE MADRID ResumenEscuela Técnica Superior de Ingenieros Aeronéuticos Departamento de Vehículos Aeroespaciales Doctorado Filtrado de errores en bases de datos aerodinámicas a través de la descomposición en valores sigulares para tensores de alto ordenpor Artur Andrzej JARZABEK Esta Tesis presenta un nuevo método para filtrar errores en bases de datos multidimensionales. Este método no precisa ninguna información a priori sobre la naturaleza de los errores. En concreto, los errrores no deben ser necesariamente pequeños, ni de distribución aleatoria ni tener media cero. El único requerimiento es que no estén correlados con la información limpia propia de la base de datos.Este nuevo método se basa en una extensión mejorada del método básico de reconstrucción de huecos (capaz de reconstruir la información que falta de una base de datos multidimensional en posiciones conocidas) inventado por Everson y Sirovich (1995).El método de reconstrucción de huecos mejorado ha evolucionado como un método de filtrado de errores de dos pasos: en primer lugar, (a) identifica las posiciones en la base de da...

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Section: Chapter 6 Automatic Tuning Of Methods Parametersmentioning

confidence: 99%

Section: Maxmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Aerodynamic database error filtering via high order singular value decomposition

Jarzabek¹

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Balassa-Samuelson Meets South Eastern Europe, the CIS and Turkey: A Close Encounter of the Third Kind?

Égert

2005

SSRN Journal

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This paper investigates the importance of the Balassa-Samuelson effect for two acceding countries (Bulgaria and Romania), two accession countries (Croatia and Turkey) and two CIS countries (Russia and Ukraine). The paper first studies the basic assumptions of the Balassa-Samuelson effect using yearly data, and then undertakes an econometric analysis of the assumptions on the basis of monthly data. The results suggest that for most of the countries, there is either amplification or attenuation, implying that any increase in the open sector's productivity feeds onto changes in the relative price of non-tradables either imperfectly or in an over-proportionate manner. With these results as a background, the size of the Balassa-Samuelson effect is derived. For this purpose, a number of different sectoral classification schemes are used to group sectors into open and closed sectors, which makes a difference for some of the countries. The Balassa-Samuelson effect is found to play only a limited role for inflation and real exchange rate determination, and it seems to be roughly in line with earlier findings for the eight new EU member states of Central and Eastern Europe.

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Aerodynamic database reconstruction via gappy high order singular value decomposition

Cited by 2 publications

References 34 publications

Aerodynamic database error filtering via high order singular value decomposition

Aerodynamic database error filtering via high order singular value decomposition

Balassa-Samuelson Meets South Eastern Europe, the CIS and Turkey: A Close Encounter of the Third Kind?

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