Optimal design of experiments for non‐linear response surface models

Optimal Design For Additive Partially Nonlinear Models

We develop optimal design theory for additive partially nonlinear regression models, and show that D-optimal designs can be found as the products of the corresponding D-optimal designs in one dimension. For partially nonlinear models, D-optimal designs depend on the unknown nonlinear model parameters, and misspeci_cations of these parameters can lead to poor designs. Hence we generalise our res...

Design of Experiments in Nonlinear Models

Optimal Color Design of Psychological Counseling Room by Design of Experiments and Response Surface Methodology

Color is one of the most powerful aspects of a psychological counseling environment. Little scientific research has been conducted on color design and much of the existing literature is based on observational studies. Using design of experiments and response surface methodology, this paper proposes an optimal color design approach for transforming patients' perception into color elements. Six i...

Modelling of Suddenly Expanded Flow Process in Supersonic Mach Regime using Design of Experiments and Response Surface Methodology

The present work is an attempt to model, analyze, and control the flow at the base of an abruptly expanded circular duct by using design of experiments (DOE) and response surface methodology (RSM). Tiny-jets in the form of orifice were positioned at an interval of 900, 6.5 mm from the primary axis of the main jet of the nozzle. Experiments were conducted to measure two responses namely, base pr...

Numerical methods for optimal control problems in design of robust optimal experiments for nonlinear dynamic processes

Optimization of experiments for nonlinear dynamic processes to maximize the reliability of parameter estimates subject to cost and other inequalityconstraints leads to very complex optimal control problems. First, the objective function already depends on a generalized inverse of the Jacobian of the underlying parameter estimation problem. Second, optimization results depend on the assumed para...