First-order response surface modelling of curvilinear relationships. (1st September 2010) - Bokov, Vladimir B.
Process or product characterisation involves the determination of quantitative estimates of physical quantities from experiment, along with estimates of their associated uncertainties. Herewith a comprehensive model is the key to extracting information from the experimental data. The information obtained depends directly on model performance. With this concern a novel response surface modelling technique has been fashioned by using jointly original explanatory variables and physics-based transformed explanatory variable. It lets us approximate adequately the true unknown model on the considered region of interest for the original explanatory variables using first-order design only. This technique has allowed attaining the advanced level of model precision. Pneumatic gauge candidate models' building, solving, and validation reviled that the first-order response surface model with physics-based transformed explanatory variable permits to attain adequacy and maximum precision.