Multi-response robust design optimization of natural draft biomass cook stove using response surface methodology and desirability function

Abstract

Cookstove researchers are paying more attention to the improvement in the combustion performance of a biomass cookstove, which requires an understanding of the effects of different parameters on pollutant emissions. Five such important parameters were identified namely, Inlet area ratio, Primary air ratio, Pot gap, Fuel surface to volume ratio and Pot diameter. The work presented here comprises estimating the effects of these five parameters on the energy and emissions performance of natural draft biomass cookstove. A prototype stove was tested to quantify the effects of these parameters on chosen performance parameters like overall efficiency, CO and PM2.5 emissions per MJ of energy delivered to the pot. The data obtained from a proper sequence of designed experiments were coupled with RSM (Response surface Methodology) technique to fit second-order models for predicting the performance of the stove under different conditions. The RSM models were then used with desirability function for robust parameter optimization of stove and confirmation trials were performed for validating the findings. The CCD (Central composite design) combined with RSM and the desirability function was found to be an effective tool for performance optimization of a natural draft biomass cookstove.