IEEE 1597.2-2010 PDF
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IEEE Recommended Practice for Validation of Computational Electromagnetics Computer Modeling and Simulations
IEEE , 02/25/2011
IEEE 1597.2-2010 PDF
This recommended practice is a companion document for IEEE Std 1597.1-2008.1 It provides examples and problem sets to be used in the validation of computational electromagnetics (CEM) computer modeling and simulation techniques, codes, and models. It is applicable to a wide variety of electromagnetic (EM) applications including but not limited to the fields of electromagnetic compatibility (EMC), analysis of radar cross section (RCS), signal integrity (SI), and the analysis of antennas. This document shows how to validate a particular solution data set by comparing it to the data set obtained by measurements, alternate codes, canonical, or analytic methods.
This recommended practice serves as an aid to CEM modelers and analysts in the selection and application of appropriate computer modeling and simulation methodologies, physics, and solution techniques to achieve accurate results. It also serves to complement measurements and EM design tasks for a range of progressively complex problems through the use of modeling problem examples for small-to-large scale canonical, benchmark, and standard validation problems. Finally, this recommended practice provides a detailed description of a validation process, i.e., the Feature Selective Validation (FSV) method, which compares a particular solution data set to a reference data set.
New IEEE Standard – Inactive-Reserved. This recommended practice is a companion document for IEEE Std 1597.1-2008. Examples and problem sets to be used in the validation of computational electromagnetics (CEM) computer modeling and simulation techniques, codes, and models are provided. It is applicable to a wide variety of electromagnetic (EM) applications including but not limited to the fields of antennas, signal integrity (SI), radar cross section (RCS), and electromagnetic compatibility (EMC). This document shows how to validate a particular solution data set by comparing it to themdata set obtained by measurements, alternate codes, canonical, or analytic methods.
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