Integrated optimization of geometrical parameters and flow variables for industrial incinerator performance improvement

Abstract

Industrial incinerators play a vital role in waste disposal, yet their operations carry significant environmental and efficiency consequences. The current study aimed to optimize an industrial incinerator using a multi-objective algorithm in which the influence of geometrical parameters and flow variables were considered simultaneously. While the initial optimization reduced the waste temperature non-uniformity from 14.63 % to 5.14 % and the waste disposed temperature from 1510 to 1760.23 [K], the disadvantages of the noted approach were found to be the direct user interference as well as optimizing just one parameter per case. Therefore, the Central Composite Design (CCD) is employed to generate the necessary experiments from a statistical perspective instead of the user preference. Later, based on the obtained results from the CCD experiments, the sensitivity analysis calculated the degree of importance for each input parameter. As an instance, the location corresponding to the air injector was found to have 84 % influence on NOX generation, 61 % on the waste temperature uniformity, 90 % on the waste disposal temperature, 11 % impact on the incinerator efficiency, and 13 % COX generation. Other parameters, such as inlet fuel location and equivalence ratio, have a comparably lower impact (3–20 %) in different conditions. By further acknowledging the flow situation, the Genetic Algorithm (GA) was applied to consider the effective parameters from a multi-objective optimization perspective. Employing the input values proposed by GA, the waste disposed of temperature increased from 1760.23 to 2800 [K] while the temperature non-uniformity of waste surface reduced from 5.14 % to 3.17 %. Moreover, the efficiency was improved by 2 % compared to the initial optimization by producing lower environmental emissions by 43 % compared to the equivalent cases in the Design Of Experiment (DOE) chart.