Design Optimization of a Two-Stage Porous Radiant Burner through Response Surface Modeling

Abstract

Model-based design optimization is a ubiquitous and powerful tool in many engineering disciplines. Its application to industrial combustion has been quite limited, however, due in part to the computational–expense of combustion simulations and, in the case of premixed combustion, noise in the objective function induced by the stiffness of the governing equations. This article presents an optimization technique based on response surface modeling, in which the true objective function is minimized by generating and then minimizing a series of interpolating low–order polynomial surfaces centered on the current design iteration. The technique is demonstrated by optimizing the radiant efficiency of a two-stage porous ceramic burner, with the downstream stage pore size and porosity as design parameters. The optimization algorithm identifies solutions that produce statistically significantly improvements in the burner efficiency, and also highlights the importance of considering nonlinear interactions between variables when carrying out the optimization.

Acknowledgments

This research was supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada. The authors are also grateful to Mr. Graham Watson of McGill University, Mr. Alan Runstedtler of the CANMET Energy Technology Centre Ottawa, and Prof. Janet Ellzey at the University of Texas at Austin for their helpful comments.

Notes

*Properties of crystalline PSZ.