Feature Selective Validation (FSV) for Validation of Computational Electromagnetics (CEM). Part I—The FSV Method

TLDR

The FSV technique enables quantitative comparison of EMC data, tracks model‑iteration differences, captures team variability, and promises improved validation, with a follow‑up visual assessment comparison in Part II. The study aims to deliver a straightforward computational method for predicting EMC assessment, analyzes the FSV approach within prior comparison methods, and proposes applicability tests for CEM validation. The authors analyze the FSV method, situate it among existing comparison techniques, link validation of graphical data to visual perception psychology, and propose applicability tests for computer‑based CEM validation.

Abstract

A goal for the validation of computational electromagnetics (CEM) is to provide the community with a simple computational method that can be used to predict the assessment of electromagnetic compatibility (EMC) data as it would be undertaken by individuals or teams of engineers. The benefits of being able to do this include quantifying the comparison of data that has hitherto only been assessed qualitatively, to provide the ability to track differences between model iterations, and to provide a means of capturing the variability and range of opinions of groups and teams of workers. The feature selective validation (FSV) technique shows great promise for achieving this goal. This paper presents a detailed analysis of the FSV method, setting it firmly in the context of previous comparison techniques; it suggests the relationship between validation of graphically presented data and the psychology of visual perception. A set of applicability tests to judge the effectiveness of computer-based CEM validation techniques is also proposed. This paper is followed by a detailed comparison with visual assessment, which is presented in Part II