Assessment of Response Surface Models Using Independent Confirmation Point Analysis

This paper highlights various advantages that confirmation-point residuals have over conventional model design-point residuals in assessing the adequacy of a response surface model fitted by regression techniques to a sample of experimental data. Particular advantages are highlighted for the case of design matrices that may be ill-conditioned for a given sample of data. The impact of both aleatory and epistemological uncertainty in response model adequacy assessments is considered.

[1]  P. A. Parker.  Response surface methods for force balance calibration modeling , 2001, ICIASF 2001 Record, 19th International Congress on Instrumentation in Aerospace Simulation Facilities (Cat. No.01CH37215).

[2]  Richard DeLoach,et al.  Tailoring wind tunnel data volume requirements through the formal design of experiments , 1998 .

[3]  Richard DeLoach,et al.  Using Modern Design of Experiments to Create a Surface Pressure Database From a Low Speed Wind Tunnel Test , 2004 .

[4]  Laura Painton Swiler,et al.  Aleatory and Epistemic Uncertainty Quantification for Engineering Applications , 2007 .

[5]  Douglas C. Montgomery,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[6]  J. Brian Gray,et al.  Introduction to Linear Regression Analysis , 2002, Technometrics.

[7]  Richard F. Gunst,et al.  Applied Regression Analysis , 1999, Technometrics.

[8]  R. H. Myers,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[9]  P A Parker,et al.  A Single-Vector Force Calibration Method Featuring the Modern Design of Experiments , 2001 .

[10]  Richard DeLoach,et al.  Applications of modern experiment design to wind tunnel testing at NASA Langley Research Center , 1998 .

[11]  Andrew D. Cutler,et al.  APPLICATION OF MODERN DESIGN OF EXPERIMENTS TO CARS THERMOMETRY IN A SUPERSONIC COMBUSTOR , 2002 .

[12]  George E. P. Box,et al.  Empirical Model‐Building and Response Surfaces , 1988 .

[13]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[14]  Arthur P. Dempster,et al.  A Generalization of Bayesian Inference , 1968, Classic Works of the Dempster-Shafer Theory of Belief Functions.

[15]  Richard DeLoach,et al.  A Comparison of Two Balance Calibration Model Building Methods , 2007 .