Combustion process optimization by genetic algorithms: reduction of NO{sub}2 emission via optimal post-flame process

摘要

In the present study, the general-purpose tool based on genetic algorithm(GA) which can explore new combustion processes is described. The new tool was used for finding the optimal cooling process to minimize NO-N02 conversion at a post-flame process of combustors. This approach successfully found a new effective cooling process, which has two periods of constant temperature during staged cooling periods. The two optimal retention temperatures of the staged cooling are found to vary with the air ratio of the combustion product. The comparison of two different approaches in selecting optimization target, heat loss rate and temperature, is presented is well as the effect of some GA parameters and techniques.