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research-article

Model Validation of Functional Responses Across Experimental Regions Using Functional Regression Extensions to the CORA Objective Rating System

[+] Author and Article Information
Scott Storm

Department of Operational Sciences, Air Force Institute of Technology, Wright-Patterson AFB, Ohio 45433
scott.storm@us.af.mil

Raymond Hill

Professor, Department of Operational Sciences, Air Force Institute of Technology, Wright-Patterson AFB, Ohio 45433
raymond.hill@afit.edu

Joseph J. Pignatiello

Professor, Department of Operational Sciences, Air Force Institute of Technology, Wright-Patterson AFB, Ohio 45433
joseph.pignatiello@afit.edu

G. Geoff Vining

Professor, Department of Statistics, Virginia Tech, Blacksburg, Virginia 24061
vining@vt.edu

Edward D. White

Professor, Department of Mathematics and Statistics, Air Force Institute of Technology, Wright-Patterson AFB, Ohio 45433
edward.white@afit.edu

1Corresponding author.

ASME doi:10.1115/1.4039303 History: Received August 14, 2017; Revised February 01, 2018

Abstract

As we continue to model more complex systems, the validation of dynamical responses has come to the forefront of modeling and simulation. One form of dynamic response is when the output is a function of time. The proper evaluation of functional data over an array of desired input parameters is critical to achieving a robust validation assessment of a simulation model. We extend the Correlation Analysis (CORA) objective rating system to validate functional data across experimental regions. Functional regression analysis is used to generate surrogate estimations of the system response functions at points within the region where experimental observations are absent. These CORA scores provide a measure of disagreement at each desired parameter configuration. An overall score for model validity is achieved using a weighted linear combination of the individual CORA scores. Lastly, an improved CORA size scoring metric is introduced.

Copyright (c) 2018 by ASME
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