INTEGRATION AND MATHEMATICAL MODELING OF PROCESSING TECHNOLOGIES OF CONCENTRATING PLANT IRON ORE WASTE

The analysis of existing domestic and international technologies of processing and utilization of iron ore wastes was carried out. For theKemerovoregion, effective technologies of waste recycling were provided for additional products meeting all consumers’ requirements. These technologies were integrated into scenarios that provide a full cycle of rational nature management. The task of waste processing scenarios generation has been formulated. Scenarios for gradual processing of iron ore waste with extraction of useful components by chemical methods, reclamation of disturbed lands and creation of recreation zones in the exempt lands were developed. Recommendations and technological solutions for all-the-year processing, including winter, of iron ore waste by chemical methods are offered. The maps of tailings dumps processing with stage-by-stage processing and reclamation of disturbed lands are presented. The number of stages is determined by investments and annual capacity of waste recycling complex with possible simultaneous operation of several sections. After the complete excavation of iron ore wastes from the tailing dumps, preparatory work was carried out for construction of recreation areas, including searching for a tender, choosing the design of recreation areas, equipment, buildings and structures dismantling and selling, soil reclamation, lawns, trees and shrubs planting. Reclamation of the territory was carried out during the operation of processing plant; commissioning of recreation areas was made after the end of operation. Mathematical modeling of scenarios for concentration plants iron ore wastes processing in theKemerovoregion was carried out based on the following performance indicators: economic effect; reclamation of disturbed lands; pollution; mining area population with normative socio-cultural indicators; prevented pollution per capita. The toolkit of model experiments is a software package for Scilab environment. From the proposed scenarios, Pareto-optimal solutions were selected graphically. Selection of priorities among Pareto-optimal scenarios was carried out by ranking, based on levels of social and environmental safety (low, moderate and high) in theKemerovoregion. 

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