Counterfactual Analysis of the Efficiency of Decontamination of Livestock Production Organic Wastes - Yakov P. Lobachevsky; Alexander V. Shemyakin; Nikolay V. Limarenko; Ivan A. Uspensky; Ivan A. Yukhin (Инженерные технологии и системы, 2023)
Introduction. The implementation of the decree of the President of the Russian Federation is aimed at ensuring the food security of the country and requires the industrialization of the agro-industrial sector. The effectiveness of industrialization depends on the use of automated, intelligent solutions at all stages of implementing technological processes. Livestock is an agro-industrial sector generating the largest amount of organic waste materials, which are potential energy carriers: litter, liquid manure, process effluents, etc. According to the data from the Russian Statistics Committee and the research results, the annual volume of manure generated from farms is from 43.3 to 45.1 million tons, while there is an upward trend. The used energy potential from the entire volume does not exceed 40%. It is possible to increase the efficiency of using the energy potential of organic animal waste materials through implementing digitalized solutions. A strategic tool for the effective industrialization of livestock is the implementation of application software products that ensure the growth of ecological and energy effects. Aim of the Article. The aim of the study is a counterfactual evaluation of the efficiency of the model for decontaminating liquid pig manure in the decontamination activator. Materials and Methods. Counterfactual analysis is a tool for formalizing complex, multifactorial processes to ensure their subsequent digitalization. The essence of the analysis consists in a “surveyˮ of the analyzed model through which the values of variables are determined providing changes that lead to a deviation of the response beyond the boundary conditions during interpretation. The advantage of counterfactual analysis is the stability and transparency of the model to external influences during machine learning. It is known that the representative pathogenic markers of the decontamination efficiency of liquid pig manure are helminth eggs and the number of colony-forming units of common coliform bacteria (CFU CCB). However, for testing and implementing an algorithm for counterfactual analysis of a mathematical model, it is acceptable to use the number of CFU CCB. The object of the study was liquid pig manure with a humidity from 88% to 98%, the subject was a counterfactual analysis of the dependence of the number of CFU CCB on the exposure time in the activator, the concentration of active chlorine, the mass of working bodies, magnetic induction, and liquid manure humidity. Results. The results of counterfactual evaluation and analysis carried with the use of the Python programming language and the PyCharm 2022.2 environment are presented in the tables. The counterfactual evaluation made it possible to identify ranges of variation of factors, the use of which can represent the potential of boundary conditions in solving the optimization problem. The cells of these values are highlighted in grey-blue. The most preferred ranges based on counterfactual evaluation are in the cells highlighted in green. Discussion and Conclusions. There has been substantiated the prospects of using active chlorine in combination with the influence of ferromagnetic working bodies moving in an alternating rotating electromagnetic field as a decontamination activator. On the basis of counterfactual evaluation it was established that the most significant factors for determining the efficiency of decontamination of liquid pig manure by the number of CFU CCB are: magnetic induction in the working zone of the activator inductor, active chlorine concentration and exposure time.