Cerchar Abrasivity Index Estimation of Andesitic Rocks in Ecuador from Petrographical Properties Using Artificial Neural Networks

Abstract Rock abrasivity is the main factor that causes erosion of excavation tools and is usually quantified by the Cerchar Abrasivity Index (CAI). Although Cerchar abrasivity tests are easy to perform, they are time consuming and require a relatively high volume of rock samples. Having good correl...

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Bibliographic Details
Published in:International journal of geomechanics 2020-05, Vol.20 (5)
Main Authors: Garzón-Roca, Julio, Torrijo, F. Javier, Alonso-Pandavenes, Olegario, Alija, Santiago
Format: Article
Language:English
Subjects:
Artificial neural networks
Dredging
Excavation
Neural networks
Properties
Rock
Rocks
Sediment samples
Technical Papers
Tool wear
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Summary:Abstract Rock abrasivity is the main factor that causes erosion of excavation tools and is usually quantified by the Cerchar Abrasivity Index (CAI). Although Cerchar abrasivity tests are easy to perform, they are time consuming and require a relatively high volume of rock samples. Having good correlations of CAI values and other faster and simpler tests is therefore of great interest, since it results in time and budget savings when controlling excavating tool wear. Based on the results of 73 andesitic rock samples coming from the central area of Ecuador, this paper presents a series of artificial neural networks developed to find a good estimation of CAI values of andesitic rocks from their petrographical properties. The network showing the best performance (R2 equal to 97%) is identified and a detailed process to estimate CAI value using the network developed is described.
ISSN:1532-3641
1943-5622
DOI:10.1061/(ASCE)GM.1943-5622.0001632