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Compacted Graphite Iron (CGI) is a unique casting material characterized by its graphite form and extensive matrix contact surface. This type of cast iron has a tendency towards direct ferritization and possesses a complex set of intriguing properties. The use of data mining methods in modern foundry material development facilitates the achievement of improved product quality parameters. When designing a new product, it is always necessary to have a comprehensive understanding of the influence of alloying elements on the microstructure and consequently on the properties of the analyzed material. Empirical studies allow for a qualitative assessment of the above-mentioned relationships, but it is the use of intelligent computational techniques that allows for the construction of an approximate model of the microstructure and, consequently, precise predictions. The formulated prognostic model supports technological decisions during the casting design phase and is considered as the first step in the selection of the appropriate material type.
EN
As the urbanisation level increases, due to intensification of car traffic and increased areas of impermeable surfaces, pollution of surface wastewater and a negative impact on water bodies are increasing. Due to the increasing pollution of surface water bodies, the eutrophication process is taking place intensively. One of the technologies of surface wastewater treatment allowing reduction in the amounts of suspended solids (SS), heavy metals and other pollutants is surface wastewater filters. Filters with different fillers have been designed for the treatment of principal surface wastewater pollutants: suspended solids, heavy metals (zinc, cadmium, copper, lead), BOD5, total carbon and nitrogen. The Kriging method was adapted to test the efficiency of filters filled with construction waste and wood waste-derived biochar using distance matrices. The method developed makes it possible to model the characteristics of filters in relation to different fillers, using experimental results. The mathematical model is suitable for other filtrate characteristics, not only the ratio of fillers, but also the length of the filter life, its durability calculations, which allows optimizing filter cleaning efficiency up to 96.93 %.
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