The development of a linear cutting machine used to characterise fem modelling parameters for cutting ug2 reef

Abstract

Mining is still an important industry in South Africa. Traditional mining methods involving drilling and blasting have steadily been replaced by mechanised mining systems in soft rock environments but not in hard rock environments. Mechanised mining systems can lead to continuous mining, which lead to improved rates of face advance and better utilization of the invested capital. A fundamental understanding of the tool-rock interaction, for rock found in gold and platinum mines in South Africa, and potential solutions to problems in mechanised mining methods in narrow reef hard rock mines, are required. South Africa has two main platinum reef deposits namely the Merensky reef and the UG2 reef. A renewed effort is required to study the problem of mechanical mining, and develop numerical models, that take the rock properties into account. This will allow optimisation of the mechanised cutting in hard rock environments. In this dissertation a linear cutting machine (LCM) was designed and manufactured to conduct laboratory scale cutting tests on both sandstone and UG2 reef samples. Firstly sandstone was cut to ensure that the LCM functions as expected. By conducting tests on sandstone, it ensured that all the functions of the LCM could be optimized. The comparison between the samples showed that there are similarities between the results from the different rock types, but some inconsistencies were found. The key difference is that the sandstone considered here has little to no variance in strength on a millimetre scale whereas the UG2 reef sample has large variance in strength on a millimetre scale. This introduces uncertainty in the results due to added variance. Another problem is the inconsistency in rock properties of the UG2 reef. The rock properties of the UG2 reef changes a lot from reef to reef as well as different areas in the mine.

The results showed that the optimal cutting parameters are similar for sandstone and UG2, but there are some differences. The depth of cut has a larger influence on the results of UG2 reef samples than for the sandstone samples. Therefore if the sandstone data was used to make design decisions for new mining equipment the decision might have been incorrect due to the assumption that sandstone

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and UG2 cut similarly. An important difference between cutting sandstone and UG2 reef is the size of the chips formed. At 2 mm cutting depth, for both samples, the force signals were impulsive and the material produced was fine fragmentations. At a cutting depth of 4 mm, for both samples, the force signals had a saw tooth shape. This implies larger fragment sizes were formed. The sandstone produced large fragments whereas the UG2 still produced fine fragmentations. This fine fragmentations is undesirable in underground mining conditions as this causes that material can not be easily cleaned and removed from the stopes.

A fast Fourier transform (FFT) analysis on the cutting signal showed that the sandstone had a peri- odic cutting force signal whereas the UG2 does not have a periodic cutting force signal. Also for the

sandstone a good relationship was present between the size of the chips formed and the dominant frequencies of the FFT. The numerical simulations showed that there are various model parameters that influence the results and while other have little effect. Thus, there are many choices that need to be made about model parameters, such as element size, element type, boundary conditions, contact parameters and model parameters. Some are based on material properties and other are obtained through trial and error. It is possible to model rock cutting of UG2 reef samples using the Ansys LS-DYNA multi-physics simulation software and the continuous surface cap model (CSCM). But this is only possible by editing the model parameters through trial and error for one set of cutting parameters. When the cutting parameters are changed, the model does not give acceptable results. Future work is required to improve the ability of models to generalise when the cutting parameters change.