Validating numerical models - Quantifying error

Alistair Duffy; Dawn Coleby; Anthony Martin; Malcolm Woolfson; Trevor Benson

Validating numerical models - Quantifying error

Alistair Duffy, Dawn Coleby, Anthony Martin, Malcolm Woolfson, Trevor Benson

Research output: Contribution to specialist publication › Article

Abstract

The validation of numerical models often progresses incrementally from previous models or other numerical solutions or is undertaken by comparison with experimentally obtained reference measurements. Notwithstanding the accuracy of the reference results, quantification of the error between the two is important information in deciding the quality of the model. It is frequently the case that this estimate of error is done by eye. However, for purposes of traceability and objectivity, interest has started to focus on techniques to quantify this error in an algorithmic manner in a way that agrees with the general observations of experienced engineers. This paper reviews two of the most promising techniques, namely Feature Selective Validation (FSV) and Integrated Error against Logarithmic Frequency (IELF), putting them in the context of correlation and reliability functions.

Original language	English
Pages	11-16
Number of pages	6
Volume	19
No.	1
Specialist publication	Applied Computational Electromagnetics Society Newsletter
Publication status	Published - Mar 2004
Externally published	Yes

Keywords

Algorithms
Correlation methods
Fourier transforms
Graph theory
Mathematical models
Probability density function
Reliability

ASJC Scopus subject areas

Media Technology
Physics and Astronomy(all)

Access to Document

http://www.aces-society.org/search.php?vol=19&no=1&type=3

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Cite this

Duffy, A., Coleby, D., Martin, A., Woolfson, M., & Benson, T. (2004). Validating numerical models - Quantifying error. Applied Computational Electromagnetics Society Newsletter, 19(1), 11-16.

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language = "English",

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AU - Coleby, Dawn

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AU - Woolfson, Malcolm

AU - Benson, Trevor

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N2 - The validation of numerical models often progresses incrementally from previous models or other numerical solutions or is undertaken by comparison with experimentally obtained reference measurements. Notwithstanding the accuracy of the reference results, quantification of the error between the two is important information in deciding the quality of the model. It is frequently the case that this estimate of error is done by eye. However, for purposes of traceability and objectivity, interest has started to focus on techniques to quantify this error in an algorithmic manner in a way that agrees with the general observations of experienced engineers. This paper reviews two of the most promising techniques, namely Feature Selective Validation (FSV) and Integrated Error against Logarithmic Frequency (IELF), putting them in the context of correlation and reliability functions.

AB - The validation of numerical models often progresses incrementally from previous models or other numerical solutions or is undertaken by comparison with experimentally obtained reference measurements. Notwithstanding the accuracy of the reference results, quantification of the error between the two is important information in deciding the quality of the model. It is frequently the case that this estimate of error is done by eye. However, for purposes of traceability and objectivity, interest has started to focus on techniques to quantify this error in an algorithmic manner in a way that agrees with the general observations of experienced engineers. This paper reviews two of the most promising techniques, namely Feature Selective Validation (FSV) and Integrated Error against Logarithmic Frequency (IELF), putting them in the context of correlation and reliability functions.

KW - Algorithms

KW - Correlation methods

KW - Fourier transforms

KW - Graph theory

KW - Mathematical models

KW - Probability density function

KW - Reliability

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EP - 16

JO - Applied Computational Electromagnetics Society Newsletter

JF - Applied Computational Electromagnetics Society Newsletter

SN - 1056-9170

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