Characterizing the variability of bauxite mine tailings from CPTU test results

Abstract

In geotechnical engineering, there is a high degree of uncertainty associated with soil parameters, since soil materials are variable due to mineralogy, stress history, and deposition processes in the same layer of soil profile. Given the high degree of variability, there are limitations when calculating and simulating models based on deterministic parameters extracted from the field. Mine tailings are part of this scenario, to which must be added the difficulty of extracting samples and characterizing them in the laboratory, making field investigation crucial for basing geomechanical models. This study aims to quantify statistical properties such as mean, standard deviation, probability density function, and scale of fluctuation obtained from the analysis of direct measurements of piezocone tests, such as tip resistance, lateral friction, and pore pressure. A set of data from a bauxite tailing deposit will be used in the analysis, which which was done by implementing an algorithm in Python to calculate the statistical parameters. Q-Q plots and histograms were presented for the most variable CPTu data to evaluate the probability density function that best fits. The results found indicate a material with high variability with statistical parameters that are close to those pointed out by the literature for other mine tailings. By elucidating the statistical properties of the soil parameters, this study contributes to a better understanding of the geomechanical behavior of mine tailings deposits, aiding in the development of more accurate predictive models. Furthermore, the methodology employed underscores the importance of robust field investigations and advanced statistical analysis techniques in geotechnical engineering research.