Full-Scale Simulation and Validation of Wear for a Mining Rope Shovel Bucket

• Published in: Minerals
• Main Authors: Andreas Svanberg, Simon Larsson, Rikard Mäki, Pär Jonsén
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2021
• Subjects: mining; simulation; discrete element method; DEM; full-scale; wear; Mineralogy; QE351-399.2; Arctic
• Online Access: https://doi.org/10.3390/min11060623; https://doaj.org/article/dccdf6f064174cf8b76a09631bda7ee2

Failure in industrial processes is often related to wear and can cause significant problems. It is estimated that approximately 1–4% of the gross national product for an industrialized nation is related to abrasive wear. This work aims to numerically predict development of wear for full-scale mining applications in harsh sub-arctic conditions. The purpose is to increase the understanding of wear development in industrial processes and optimize service life and minimize costs related to wear. In the present paper, a granular material model consisting of the discrete element method (DEM) and rigid finite element particles is utilized to study wear in full-scale mining applications where granular materials and steel structures are present. A wear model with the basis in Finnie’s wear model is developed to calculate wear from combined abrasive sliding and impact wear. Novel in situ full-scale experiments are presented for calibration of the wear model. A simulation model of the rope shovel loading process is set up where the bucket filling process is simulated several times, and the wear is calculated with the calibrated wear model. From the full-scale validation, it is shown that the simulated wear is in excellent agreement when compared to the experiments, both regarding wear locations and magnitudes. After validation, the model is utilized to study if wear can be minimized by making small changes to the bucket. One major conclusion from the work is that the presented wear simulator is a suitable tool that can be used for product development and optimization of the loading process.