Validating numerical models - Quantifying error

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

Research output: Contribution to specialist publicationArticle


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 languageEnglish
Number of pages6
Specialist publicationApplied Computational Electromagnetics Society Newsletter
Publication statusPublished - Mar 2004
Externally publishedYes


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

ASJC Scopus subject areas

  • Media Technology
  • Physics and Astronomy(all)


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