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The present study was conducted to present the comparative modeling, predictive and generalization abilities of response surface methodology (RSM) and artificial neural network (ANN) for the thermal structure of stabilized confined jet diffusion flames in the presence of different geometries of bluff-body burners. Two stabilizer disc burners tapered at 30˚ and 60˚ and another frustum cone of 60˚/30˚ inclination angle were employed all having the same diameter of 80 (mm) acting as flame holders. The measured radial mean temperature profiles of the developed stabilized flames at different normalized axial distances () j x d were considered as the model example of the physical process. The RSM and ANN methods analyze the effect of the two operating parameters namely () r , the radial distance from the center line of the flame, and () j x d on the measured temperature of the flames, to find the predicted maximum temperature and the corresponding process variables. A three-layered Feed Forward Neural Network in conjugation with the hyperbolic tangent sigmoid (tansig) as transfer function and the optimized topology of 2:10:1 (input neurons: hidden neurons: output neurons) was developed. Also the ANN method has been employed to illustrate such effects in the three and two dimensions and shows the location of the predicted maximum temperature. The results indicated the superiority of ANN in the prediction capability as the ranges of R 2 and F Ratio are 0.868-0.947 and 231.7-864.1 for RSM method compared to 0.964-0.987 and 2878.8 7580.7 for ANN method beside lower values for error analysis terms.

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The Response Surface Methodology (RSM) has been applied to explore the thermal structure of the experimentally studied catalytic combustion of stabilized confined turbulent gaseous diffusion flames. The Pt/γAl 2 O 3 and Pd/γAl 2 O 3 disc burners were situated in the combustion domain and the experiments were performed under both fuel-rich and fuel-lean conditions at a modified equivalence (fuel/air) ratio (Ø) of 0.75 and 0.25 respectively. The thermal structure of these catalytic flames developed over the Pt and Pd disc burners were inspected via measuring the mean temperature profiles in the radial direction at different discrete axial locations along the flames. The RSM considers the effect of the two operating parameters explicitly (r), the radial distance from the center line of the flame, and (x), axial distance along the flame over the disc, on the measured temperature of the flames and finds the predicted maximum temperature and the corresponding process variables. Also the RSM has been employed to elucidate such effects in the three and two dimensions and displays the location of the predicted maximum temperature.

Performance of a combustion system is often constrained by limits of pollutant emissions such as CO. Catalytic combustion over noble metals promotes efficient combustion with minimum pollutant formation. In this study, the volumetric percentage of carbon-monoxide distribution along the catalytic flames operating over noble metal disc burners Pt, Pd, and (Pt C Pd) supported on -Al 2 O 3 discs are analyzed through non-linear exponential model function. The numerical prediction correlates the response variable (CO %) with two explanatory (independent) variables: the axial mean temperature and axial distances over each catalytic burner simultaneously. The fitting process indicates high adequacy matching with the experimental data. The response surface construction, with corresponding contour maps, has been established to visually analyze the proposed model equations and to fully identify the extent of the estimated relationship in the combustion domain. These constructions reveal clearly that the response variable (CO %) is mainly dependant on the axial mean temperature distribution and slightly on the axial distances along the catalytic flames and also indicate the effectiveness of the three noble disc burners in reducing CO emissions along the catalytic flames minimizing the environmental pollution.