Use of Scaled Discrete Element Model of Rubber Tyre Loader Buckets for Draft Prediction
Abstract
The work applies discrete element modelling (DEM) and similitude theory to predict draft on a rubber tyre loader bucket. A DEM model is calibrated and validated using a 1:16 scale model of a rubber tyre loader, followed by simulations at three different speeds (60 mm s−1, 70 mm s−1, and 80 mm s−1) and two different rake angles (5° and 7.5°). The work hypothesised that the simulated peak draft on the 1:16 DEM model should be able to predict the peak draft on a 1:8 scaled model. A 1:8 scaled model was used to verify the predictions from DEM model. The results show that the predicted peak draft based on DEM results are reasonable when compared to the peak draft observed during the physical experiments on bigger scaled models. The slope of the regression line between the predicted and measured values was 0.9708 and the correlation coefficient 0.5524. There was under-prediction at lower speeds and over-prediction at a higher speeds of operation indicating that the DEM model is sensitive to loading rate. A complete methodology to help original equipment manufacturers (OEMs) in mining, construction and agriculture develop valid and computationally efficient DEM models that can help predict draft for rubber tyre loader design and analysis. Similar techniques can be applied to other ground-engaging tools.
Recommended Citation
A. Ur Rehman et al., "Use of Scaled Discrete Element Model of Rubber Tyre Loader Buckets for Draft Prediction," Biosystems Engineering, vol. 214, pp. 1 - 10, Elsevier, Feb 2022.
The definitive version is available at https://doi.org/10.1016/j.biosystemseng.2021.12.003
Department(s)
Mining Engineering
Keywords and Phrases
Discrete element methods; Draft; Front end loader; Load haul dump; Rubber tyre loaders; Scaled model testing
International Standard Serial Number (ISSN)
1537-5110
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2023 Elsevier, All rights reserved.
Publication Date
01 Feb 2022