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

被引:4
|
作者
Garzon-Roca, Julio [1 ]
Torrijo, F. Javier [1 ]
Alonso-Pandavenes, Olegario [2 ]
Alija, Santiago [3 ]
机构
[1] Univ Politecn Valencia, Dept Geotech Engn, Camino Vera S-N, E-46022 Valencia, Spain
[2] GEOTOP ECUATORIAL, Rumipamba e2-30, Quito, Ecuador
[3] Univ Int La Rioja, Dept Geotech Engn, Ave Gran Via Rey Juan Carlos I 41, Logrono 28002, Spain
关键词
Cerchar abrasivity index; Andesitic rock; Petrographical properties; Artificial neural network; GRANITIC-ROCKS; TOOL WEAR; PREDICTION; REGRESSION; STRENGTH; BEHAVIOR; MASONRY; CAI;
D O I
10.1061/(ASCE)GM.1943-5622.0001632
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
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 (R-2 equal to 97%) is identified and a detailed process to estimate CAI value using the network developed is described.
引用
收藏
页数:9
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