Effectiveness of Similitude Theory for Bucket Design and Analysis for Rubber Tire Loaders
This paper evaluates the effectiveness of similitude theory in predicting the draft of a rubber tire loader's bucket during initial penetration. The work uses 1:16 and 1:8 scale models of an 18-t capacity load haul dump, scaled with the Buckingham Pi Theorem, to evaluate the prediction of draft and penetration under different operating and different dynamic conditions. The authors hypothesize that the observed relationships between draft and longitudinal penetration and the operating and dynamic conditions will hold true for an upscaled model. Similarly, the authors hypothesized that the results of experiments conducted with the smaller scaled model should predict the draft on an upscaled model. The results show that the relationships between draft and longitudinal penetration and operating and dynamic parameters are similar for both scaled models. Similarly, the draft on the upscaled model, predicted by using the experimental results of the small model, is similar to the measured draft on the upscaled model. The mean difference between the two is 1.71 N with 95% confidence interval of [-3.51, 6.93], which is very good given the average draft is approximately 330 N. Thus, the work indicates that both hypotheses are true for draft. However, the work shows that scaling muck pile particle sizes using the Buckingham Pi Theorem is not adequate to ensure good predictions of penetration. This work provides insights that will help design engineers to acquire useful data on scaled models and use it for various analyses on heavy machinery.
A. Ur Rehman and K. Awuah-Offei, "Effectiveness of Similitude Theory for Bucket Design and Analysis for Rubber Tire Loaders," Mining, Metallurgy and Exploration, vol. 38, pp. 2365, article no. 2351, Springer, Oct 2021.
The definitive version is available at https://doi.org/10.1007/s42461-021-00499-4
Keywords and Phrases
Bucket design; Draft; Prototype testing; Rubber tire loaders; Similitude theory
International Standard Serial Number (ISSN)
Article - Journal
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06 Oct 2021