Characterization of coarse mine waste rockfill using AI-assisted pressuremeter testing, large triaxial testing and CPTu

The mining industry must address a wide range of geotechnical problems, many of which involve coarse materials and large particles, including heap-leach piles, spent-ore dumps, run-of-mine (ROM) piles, open pits, and foundation materials. Over the years, the industry has relied on large-scale laboratory testing, geophysics, and in situ testing. However, no single method appears to consistently dominate practice, as CPTu does for tailings. Pressuremeters can test a large volume of material and have been used worldwide for more than 70 years. Nevertheless, their full potential has been limited by traditional interpretation methods. Today, this limitation can be overcome with advanced numerical modelling and artificial intelligence. This paper presents the use of pressuremeter tests to characterise a 40 m-high spent-ore dump in northern Chile. The tests are back-analysed using advanced constitutive models and an AI-assisted software tool (DAARWIN) to match numerical predictions to measured responses. The resulting material parameters are then used to model the structure, and the predictions are compared with field-monitoring data and the results of CPTu and triaxial tests.