Utilizing water, mineralogy and sedimentary properties to predict LCPC abrasivity coefficient
Autor: | Arash Hashemnejad, Mohammad Ghafoori, Sadegh Tarigh Azali |
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Rok vydání: | 2015 |
Předmět: |
Soil test
0211 other engineering and technologies Drilling Geology Excavation 02 engineering and technology 010502 geochemistry & geophysics Geotechnical Engineering and Engineering Geology 01 natural sciences Grain size Soil water Geotechnical engineering Sedimentary rock Tool wear Quartz 021101 geological & geomatics engineering 0105 earth and related environmental sciences |
Zdroj: | Bulletin of Engineering Geology and the Environment. 75:841-851 |
ISSN: | 1435-9537 1435-9529 |
DOI: | 10.1007/s10064-015-0779-9 |
Popis: | Drilling, blasting and mechanical methods using road headers or tunnel boring machines (TBMs) are among the methods used for underground excavation of rock and soil. The interaction between the tools used and the ground leads to fragmentation of rocks and soil grains as well as tool wear. Wear is defined as the loss of tool material as a result of the interaction between rocks (or soil) and the drilling tools. The LCPC abrasivity test is a quick and easy procedure used widely to assess the abrasivity of soil and rock for predicting the rate of wear of cutting and drilling tools. The LCPC test device is designed to measure the abrasivity of particles as small as fine gravel. Various parameters can affect the LCPC abrasivity coefficient (LAC). In this paper, equations relating the index properties and the LAC were applied to 27 different samples. The derivation of models predicting the engineering geological properties of rocks and soils is useful because providing specimens of rocks at depth is difficult and expensive in the preliminary design of underground projects. Regression analysis was applied in developing some models for the LAC based on indirect methods including the equivalent quartz content (EQC), grain shape, grain size, grain angularity and water saturation applied to data from rock and soil samples in Iran. The results showed that EQC is the most important parameter affecting the LAC, with the other parameters having lower levels of importance. |
Databáze: | OpenAIRE |
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