Fuzzy Logic Tools Application to the Characterization of Stress-Strain Processes in Waste Construction Dam Geopolymers: A New Circular Mining.

The ceramics industry dedicated to the manufacture of building materials is a very significant cause of environmental pollution, and various research projects are being carried out to reduce the associated environmental impact. One of the most important research lines is the generation and development of new materials, from waste, through more sustainable production processes. All of this is framed in circular mining. In this research study, geopolymers were developed with biomass bottom ashes and brick dust in order to replace the traditional ceramics used to construct bricks. For this, different families of test tubes were formed with different percentages of both residues, and their physical and mechanical properties were studied. In this way, the properties of geopolymers could be compared with traditional ceramics. In addition, in order to determine the cause-effect relationships between physical properties and compressive strength, data were processed using fuzzy logic and data mining techniques. The results showed the feasibility of geopolymers generation with biomass bottom ashes and brick dust with acceptable properties to replace conventional ceramics. In addition, the fuzzy logic analysis allowed for establishing clear and objective relationships between the physical properties and the compressive strength of the geopolymers, with the aim of developing the highest quality geopolymer.

Application of a Fuzzy Logic Based Methodology to Validate the Hydrochemical Characterization and Determining Seasonal Influence of a Watershed Affected by Acid Mine Drainage.

The Odiel River Basin, located in the Iberian Pyrite Belt (IPB), is heavily affected by acid mine drainage (AMD), which occurs when pyritic minerals from sulfide mining areas are exposed to atmospheric, hydrological or biological weathering. This paper presents a hydrochemical characterization of parameters in the Odiel River Basin by means of Fuzzy Logic and data mining methodologies to determine the seasonal influence of AMD in polluted waters that have not been used before for a basin in this environmental area. This technique was proven to be effective, providing results that could not be achieved by using classic statistics, because it allows us to characterize the different parameters separately and also their relationships in waters affected by AMD in a qualitative manner based on the antecedents and according to the conditions (rules) imposed by the consequents (in this case, the Fe(II) and accumulated rainfall over 30 days). Thus, it was possible to confirm that hydrochemistry is greatly affected by seasonal changes, with a higher pH in the wet season (up to 8.59) compared to 2.12, the minimum pH value reached in the dry season. Accordingly, higher concentrations of most of the metals were observed in the dry season (e.g., up to 4000 mg/L of Fe (II)), with the exception of the values found after the first rains that occur in the early fall. With the use of the Fuzzy Logic technique, it was observed that, during the wet season, lixiviates with a higher Fe content have higher metal concentrations, and in the dry season, the behavior is the opposite.

Presence of As in the fluvial network due to AMD processes in the Riotinto mining area (SW Spain): a fuzzy logic qualitative model.

The Tinto River crosses the mining area of Riotinto (Iberian Pyrite Belt, SW Spain), where it receives the highest contribution of contaminants (AMD). In this paper we apply a fuzzy computer tool, PreFuRGe, which allows qualitative interpretation of the data recorded in a database relating to the chemistry of water. Specifically, we aim to find information not likely to be detected by means of classical statistical techniques, and which can help in characterizing and interpreting the behavior of arsenic in a complex system. The conclusions present that the factors which most directly control the presence of total dissolved As are closely linked to the climate and are temperature and rainfall, and therefore pH. As (III) is also shown to be related to temperature and pH. In terms of temperature As (V) is found to operate in a way which is the opposite of As (III). In terms of pH the relationship is not as clear as for As (III). As for rain, the highest As (V) values are compatible with minimum or non-existent rainfall, while minimum values correspond to any value for rainfall, including very high.