{"id":6856,"date":"2025-06-19T10:24:22","date_gmt":"2025-06-19T15:24:22","guid":{"rendered":"https:\/\/www.geolabor.com.br\/english\/?p=6856"},"modified":"2025-06-19T10:25:58","modified_gmt":"2025-06-19T15:25:58","slug":"geotechnical-data-and-statistics-in-geotechnics","status":"publish","type":"post","link":"https:\/\/www.geolabor.com.br\/english\/geotechnical-data-and-statistics-in-geotechnics\/","title":{"rendered":"Geotechnical data and statistics in Geotechnics"},"content":{"rendered":"

Stockpile and dam construction\u00a0Geotechnical data<\/b>\u00a0Have undergone digitalization, and over the last few years, they have become prominent topics in mining geotechnics. In fact, they have gained significant importance in this sector and are essential for conducting the work.<\/p>\n

The integration and validation of geotechnical data enables rigorous information management. Additionally, it enables various automated analyses that help ensure the quality of the entire construction process and the management of these structures.<\/p>\n

Utilizing a well-organized database makes it possible to correlate results from several tests and samples, facilitating a broader and more comprehensive study of materials. In this sense, statistics is one tool that has been gaining prominence in geotechnics. It aids in critical analyses to validate data quality and better understand material behavior.<\/p>\n

The study of statistics and the connection with geotechnical data<\/b><\/h2>\n

The study of statistics is widely discussed and applied across several academic and practice fields. In geotechnics, the behavior of materials has traditionally been addressed in a deterministic manner.\u00a0 This can lead to significant errors due to the uncertainties arising from measuring geotechnical parameters, performing and dispersing tests, and observing the natural distribution of soils and tailing.<\/p>\n

The literature, such as Azevedo (2019), Badar\u00f3 (2022), Santos (2019), and Brand\u00e3o and Pinto (2019), address different ways of applying statistics in mining geotechnics, respectively:<\/p>\n

The study of outliers to identify discrepant readings in piezometers in dam monitoring; the use of statistical analyses to compare the performance of different methods of obtaining moisture for the technological control of filtered tailings disposal structures; the application of different methods to slope stability analysis, calculating the probabilities of failure for the dams analyzed in critical conditions; the application of artificial neural networks (ANNs) to estimate the peak undrained resistance of bauxite tailings based on CPTu data.<\/i><\/p>\n

Ferreira (2022) points out that one of the challenges in applying statistics to geotechnics within the mining sector is the amount of information necessary for conducting analyses. Similarly, Santos (2019) concludes that a major difficulty encountered in the case study was the lack of completeness in the information regarding the analyzed constructions.<\/p>\n

Lack of data centralization and the difficulty of automated statistical analysis<\/b><\/h3>\n

The absence of data centralization in an intelligent environment hinders the ability to conduct automated statistical analyses, directly affecting the results\u2019 practical application.\u00a0 The literature recognizes the importance of statistical applications in geotechnics. Therefore,\u00a0a statistical module is being developed in Geolabor<\/b>.<\/p>\n

This aims to allow users to automate contextual analyses, which can aid in critical decision-making during construction.\u00a0 Among several analytical possibilities to be implemented in the Geolabor statistical module, the following stand out:<\/p>\n