Estimation Complete Combustion Coefficient in Rotary Kilns

This paper presents a model-based analysis of variability of thermodynamic and chemical parameters in a rotary kiln (RK) during thermal treatment of animal waste. The core process of chemical treatment of waste takes place in RKs; the process involves heating, gasification and partial combustion of the waste. Control over these parameters, and especially the level of complete combustion, determines the quality and efficiency of the process. In operational practice, control and analysis of the variability of process parameters is complicated by the high degree of simultaneity of individual transformations, random disruptions of the process and metrological difficulties resulting from high temperature and chemical activity of the materials being processed. The purpose of preparing the model was to obtain a tool for predicting variability of selected process parameters. By definition, model calculations assume no influence of disturbances on output values, which makes it possible to acquire accurate results that can be compared with corresponding empirically obtained data. The result of the analyses conducted is a theoretical model of the analysed process and a graphical presentation of the calculation results in the form of graphs and charts. A formula for calculating the level of complete combustion and the results of calculation of this index on the basis of empirical data from an industrial waste incineration plant are also presented herein. The presented model is a useful tool providing an insight into interdependencies between selected process parameters and facilitating design of corrective actions oriented towards process optimisation.

Automated summary

This paper presents a model-based analysis of the variability of thermodynamic and chemical parameters in a rotary kiln during thermal treatment of animal waste. The purpose of the analysis is to predict and optimize the variability of selected process parameters. The presented model and results provide insights into the interdependencies between the parameters and aid in the design of corrective actions for process optimization.