Effects of rock water content on CERCHAR Abrasivity Index

• Published in: Wear 2016-12, Vol.368-369, p.132-145
• Main Authors: Abu Bakar, M.Z., Majeed, Y., Rostami, J.
• Format: Article
• Language: English
• Subjects: Abrasion; CERCHAR Abrasivity Index (CAI); Correlation analysis; Equivalent quartz content (EQC); Excavation; Laboratory tests; Moisture content; Properties (attributes); Quartz content (QC); Regression analysis; Rock abrasivity index (RAI); Rock properties; Schimazek׳s F-value; Sedimentary geology; Sedimentary rocks; Statistical analysis; Statistical methods; Tool wear; Uniaxial compressive strength (UCS)
• ISSN: 0043-1648; 1873-2577
• DOI: 10.1016/j.wear.2016.09.007

Cerchar Abrasivity Index (CAI) has been commonly used to represent rock abrasion for estimation of tool wear in rock excavation applications. This test is a simple and effective measure of rock abrasion but operating parameters can impact its results. This paper focuses on the influence of water saturation on CAI values based on laboratory testing of 33 sedimentary rock units collected from different regions of Pakistan. The tests include CAI measurements as well as engineering rock properties on both dry and saturated rocks. It was found that overall 79% of CERCHAR abrasivity index values measured on saturated rock surfaces “CAIsat” were less than the CERCHAR abrasivity index values measured on dry rock surfaces “CAIdry”. Meanwhile, 52% of CAIsat values showed significant reduction from CAIdry values in the statistical analysis of CAI results with significance level of 15% (α=0.15). Regression analysis was used to correlate CAIsat values with CAIdry, normally measured in CERCHAR testing. The proposed formula can be used to estimate CAIsat from result of laboratory testing where CAI reported is often CAIdry. This could lead into more accurate estimation of tool wear and related adjustments when CAI is used for estimation of tool wear when excavation is done under wet conditions. Multiple regression was also used to establish a predictive model of CAIsat with petrographical, wear indices and geotechnical rock properties of saturated rock samples. In addition, the validity of correlations of CAI with rock properties that are already published was evaluated. •CERCHAR tests on moist rocks showed 79% reduction in CAI as compared to dry ones.•A developed correlation shows CAI(sat) to be 0.8 times the CAI(dry).•A multiple regression model is proposed to predict CAI(sat) from rock properties.•Existing correlations were used to estimate CAI(sat) using the data of this work.