Evaluation of geo-mechanical properties of very weak and weak rock materials by using non-destructive techniques: Ultrasonic pulse velocity measurements and reflectance spectroscopy

Engineering Geology 160 (2013) 8–20

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Evaluation of geo-mechanical properties of very weak and weak rock materials by using non-destructive techniques: Ultrasonic pulse velocity measurements and reflectance spectroscopy Hakan A. Nefeslioglu ⁎ Cumhuriyet University, Faculty of Engineering, Department of Geological Engineering, 58140 Sivas, Turkey

a r t i c l e

i n f o

Article history: Received 13 August 2012 Received in revised form 16 March 2013 Accepted 30 March 2013 Available online 16 April 2013 Keywords: Modulus of elasticity Reflectance spectroscopy Ultrasonic pulse velocity Unconfined compressive strength Weak rock

a b s t r a c t The main purpose of this study is to evaluate the geo-mechanical properties of very weak and weak rock materials by using ultrasonic pulse velocity measurements and considering specifically detailed mineralogical compositions. For the purpose, P-wave velocity (Vp) measurements of 66 core samples of the sedimentary rocks including claystones and mudstones collected from Firuzkoy area of Istanbul (Turkey) were carried out. Unconfined Compressive Strength (UCS) tests were then conducted. The axial deformations recorded during the UCS tests were also evaluated and the elastic moduli of the rock materials (Ei) were calculated. Statistical relations were investigated between the values of P-wave velocity measurements and the UCS and Ei. In order to evaluate the effects of detailed mineralogical compositions on the prediction performances of the empirical equations Vp-UCS and Vp-Ei, the reflectance spectroscopy was introduced. 1035 spectral measurements were taken from smooth and fresh surfaces of the failed core samples. Different genetic rock types were defined according to crystal field effect and charge transfer absorptions of transition elements, and water and OH vibrational spectral diagnostics. The statistical relations were reinvestigated, and the individual empirical equations were reproduced for each genetic rock type. The mean values of the multiple coefficients of correlations (R) were obtained to be 0.904 and 0.916 for the equations of Vp-UCS and Vp-Ei. Considering the maximum values of R, the increment rates for the values of the explained variances reach up to 14.3% and 13.5% for the equations, respectively. Additionally, according to the results of the analysis of variance (ANOVA) evaluations, the empirical equations of Vp-UCS and Vp-Ei reproduced for each genetic rock type were found to be statistically significant at the significance level of 0.05. As a consequence, the nondestructive techniques Vp measurements and reflectance spectroscopy could be efficiently used together for the evaluation of the geo-mechanical properties of very weak and weak rock materials in particular. © 2013 Elsevier B.V. All rights reserved.

1. Introduction The geo-mechanical properties of rock material are the most crucial input variables for the critical geo-engineering design problems. The problematic issues mostly arise from the sampling procedures particularly due to sampling difficulties encountered throughout the boundary — strength conditions of the weak rock materials. Considering laboratory Unconfined Compressive Strength (UCS) values of the rock materials, International Society of Rock Mechanics (ISRM, 1981) defines the weak rocks to be the earth materials having the UCS values in a range of 5–25 MPa. In more detail, according to the ISRM (1981), the strength boundaries for the transition zones including extremely weak rocks and weak rocks are given between the values of 0.25 and 25 MPa UCS. Hawkins (2000) also defines a group of earth materials which do not conveniently fall into the well-established categories

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of engineering soils or rocks, and suggests strength criteria on which a category might be described. According to the classification given by Hawkins (2000), the materials having undrained triaxial strength values between 0.32 and 0.64 MPa are defined to be hard soils while the ranges of the UCS values between 1.25–2.5 MPa and 2.5–5 MPa are explained to be very weak rocks and weak rocks, respectively. According to British Standard Institution (1981) hard soils are the materials having undrained triaxial strength values greater than 0.15 MPa and very weak rocks are defined to be the materials having the UCS values up to 1.25 MPa. Even though there is still no internal consistency in definition of hard soils and weak rocks in the literature (Hawkins, 2000), it could be interpreted that the rock materials having the compressive strength values between approximately 0.6 and 1.25 MPa might be defined to be very weak rocks, and the materials having the UCS values up to 5 MPa could be described to be weak rocks. Poor bonding and potential presence cavities and discontinuities constitute the main reasons for the considerably low strength values of these earth materials (Nassif, 2003). Hence, the undisturbed sampling for the laboratory experiments such as strength and deformation

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tests is considerably difficult for these materials (Gokceoglu and Aksoy, 2000; Alber and Kahraman, 2009). For this reason, in recent engineering geology literature there are several scientific researches investigating empirical equations in order to estimate strength and deformation parameters for geo-engineering design problems (Kahraman, 2001; Leite and Ferland, 2001; Lashkaripour, 2002; Quane and Russel, 2003; Tsiambaos and Sabatakakis, 2004; Yasar and Erdogan, 2004; Kahramana et al., 2005; Zorlu et al., 2008). Considering recent engineering geology literature given thus far, it could be clearly realized that the UCS test is one of the most used methods to define the strength of rock material. Although the method is relatively simple, it is time consuming and expensive; and it requires well-prepared core samples, which are very difficult particularly for very weak and weak rock materials (Zhang, 2005). For this reason, indirect methods such as point load index, Schmidt hammer, sonic velocity tests, etc., are often implemented to estimate the UCS by using empirical equations. Additionally, there are also some innovative approaches such as block punch index, cone indentor, and core strangle index in the literature for this purpose (Ulusay and Gokceoglu, 1997; Leite and Ferland, 2001; Ulusay et al., 2001; Yilmaz, 2009). However, the measurement accuracy of the tests particularly those of point load, Schmidt hammer, block punch index, cone indenter, and core strangle index is not enough to apply for considerably weak rocks, especially for the strength range in the transition zone of very weak rocks to weak rocks. On the other hand, considering the non-destructive nature of the method, among these techniques the sonic velocity applications seem to be the most appropriate indirect technique in determination of the strength and deformation characteristics of the rock materials involved in the transition zone of very weak rocks to weak rocks in particular. The main purpose of this study is to evaluate the geo-mechanical properties of the rock materials, which are interpreted to be very weak rocks and weak rocks in terms of material strengths, by using ultrasonic pulse velocity measurements and considering specifically detailed mineralogical compositions. For the purpose, P-wave velocity (Vp) measurements of 66 core samples of the sedimentary rocks including claystones and mudstones were carried out. Unconfined compressive strength tests were then conducted by using the core samples. The axial deformations recorded during the UCS tests were also evaluated and the elastic moduli of the rock materials (Ei) were calculated. Statistical relations were investigated between the values of P-wave velocity measurements and the UCS and Ei. The empirical equations of Vp-UCS and Vp-Ei were produced. The prediction performances and statistical significances of the empirical equations were evaluated by considering the multiple coefficients of correlations (R) and analysis of variance (ANOVA) tests, respectively. Additionally, in order to evaluate the effects of detailed mineralogical compositions of the materials on the prediction performances of the empirical equations, the reflectance spectroscopy was introduced. For the purpose, 1035 spectral measurements were taken from smooth and fresh surfaces of the failed core samples, and different genetic rock types were defined according to crystal field effect and charge transfer absorptions of transition elements, and water and OH vibrational spectral diagnostics. Supplementary X-ray diffraction analyses were also conducted for the samples of the characteristic genetic rock type in order to verify the source of these specific absorption diagnostics in the reflectance spectra of the rock materials. Finally, the investigations of the statistical relations were repeated, and the individual empirical equations were reproduced for each genetic rock type, and the prediction performances and statistical significances of the equations were reevaluated. 2. Sampling The samples implemented in this study were provided from 5 bore holes (Gokceoglu et al., 2010) drilled in the Firuzkoy area of Istanbul, in Turkey (Figure 1). The bore holes cut the Late Miocene

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aged Bakirkoy formation including limestones and claystones, Middle Eocene aged Ergene formation including sandstones and gravelly sandstones, and Early Miocene aged the Acmalar member of Danisment formation (Boer, 1954; Sayar, 1977; Umut et al., 1983; after Duman et al., 2004). The Acmalar member of Danisment formation mainly consists of claystones and mudstones which could be interpreted to be very weak rocks and weak rocks in terms of material strengths (Duman et al., 2004, 2006). Considering the purpose of this study, the samples employed in the research were collected from the layers of the Acmalar member of Danisment formation. 3. Laboratory studies The first stage in the laboratory studies is the sample preparations for further experimental researches. Sample preparations were performed by considering the suggestions given by ASTM (1994) and ISRM (2007). Accordingly, the cores recovered from the drillings were cut by core cutting machine by keeping the length/diameter (L/D) ratios between 2.5 and 3.0, and insuring about the flatness and parallelism of both upper and lower parts of the samples. Additionally, considering the drilling numbers and sampling depths, each sample prepared in the laboratory was coded during this stage (Table 1). For example, the code “B1-2-18-19.5-U1” means that the number of the bore hole is 1, the number of the core box is 2, the sampling depth is between 18 m and 19.5 m, and the sample is the first sample for further experimental researches for this layer. Further experimental researches were carried out in three main stages; (i) P-wave velocity measurements, (ii) UCS tests, and (iii) spectroscopic measurements. Supplementary X-ray diffraction analyses accompanying the spectroscopic measurements were also performed during the laboratory studies. 3.1. P-wave velocity measurements The lengths and diameters of the core samples employed in this study vary between 119.79–149.63 mm and 47.25–60.52 mm, respectively. A Pundit Plus ultrasonic test equipment having 24 kHz– 1 MHz frequency range was implemented for the P-wave velocity measurements in the research. In order to provide full coupling of the transducers-transmitter and receiver with the lower and upper parts of the core samples, the grease was applied to the core end surfaces during the measurements. After loading the samples axially by a stress of about 10 N/cm 2 as suggested by ISRM (2007) P-wave velocity measurements were taken. As a result of the Vp measurements of 66 samples, the minimum and maximum P-wave velocity values were obtained to be 0.47 km/s and 1.37 km/s, respectively (Table 2). The mean value of 66 measurements was calculated to be 0.90 km/s (Table 2). 3.2. Unconfined compressive strength tests The core samples employed during the P-wave measurements were then subjected to the UCS tests in the laboratory. Since, the samples investigated in this study were considered to be very weak rocks and weak rocks in terms of rock strength, a load cell having 50 kN load capacity with an accuracy of 0.01255 × kN was implemented. The failures of the samples occurred within 5–10 min as suggested by ISRM (2007) with a loading rate of 1 mm/min. The axial deformations were also recorded from a deformation gauge having a reading accuracy of 0.01 × mm established in the experimental set up. Some example views of the failure modes are given in Fig. 2. As a result of the tests, the UCS values were obtained between 0.68 MPa and 4.06 MPa with a mean value of 1.92 MPa (Table 2). Considering the variation range of the UCS values, the samples investigating in this study are just in the range of very weak rocks and weak rocks in terms of rock strength as expected. Additionally, considering the axial deformations measured

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Fig. 1. Location map of the bore holes (B1-5) (Gokceoglu et al., 2010) drilled in the Firuzkoy area of Istanbul in Turkey (“Toda” is the Early Miocene aged Acmalar member of Danisment formation; “Tme” is the Middle Eocene aged Ergene formation; “Tmb” is the Late Miocene aged Bakirkoy formation (Boer, 1954; Sayar, 1977; Umut et al., 1983; after Duman et al., 2004)).

during the tests, the elastic moduli of the samples were also evaluated. The values of the minimum and maximum elastic moduli were calculated to be 0.030 GPa and 0.309 GPa, respectively (Table 2). The mean elastic modulus of the intact rocks was obtained to be 0.123 GPa (Table 2). 3.3. Spectroscopic measurements The failed samples remained after the UCS tests were collected separately by keeping the sampling code and used in the spectroscopic measurements. In order to apply the spectrometer probe to the samples, smooth and fresh material surfaces closing to failure zones were cut by using core cutting machine. FieldSpec 2 (ASD Inc.) portable spectroradiometer having a spectral range between the wavelengths 350 nm and 2500 nm was implemented during the spectral measurements. Total 1035 measurements were taken from smooth and fresh surfaces of 66 samples employed in this study. In order to determine the specific absorption diagnostics, the measured spectra for each sample were evaluated by applying the spectral feature search analysis in the software SPECMIN PRO (Version 3.1). Some example views of the characteristic reflectance spectra for the samples are given in Fig. 3. Considering the spectral feature search analyses performed by using SPECMIN PRO (Version 3.1), total 7 diagnostic

spectral absorption bands (625–699 nm, 700–748 nm, 900–985 nm, 1042–1161 nm, 1411–1415 nm, 1908–1912 nm, and 2208–2213 nm) were determined (Table 1). The absorption bands (625–699 nm, 700–748 nm, 900–985 nm, 1042–1161 nm) are typical spectral diagnostics arise from crystal field effect and charge transfer properties of transitions elements, particularly ferrous (Fe2+) and ferric (Fe 3+) ions in the rock materials (Hunt, 1977; Clark, 1999). Additionally, the rest of those diagnostics (1411–1415 nm, 1908–1912 nm, and 2208– 2213 nm) are typical water and OH vibrational absorptions. A mineral having a spectral diagnostic absorption at 1.9 μm contains water; however the absorption observed at 1.4 μm and the absence of this diagnostic at 1.9 μm indicate that only hydroxyl exists (Clark, 1999). Clark (1999) stated that the OH commonly occurs in multiple crystallographic sites of a specific mineral and is typically attached to metal ions; hence there may be more than one OH feature. The spectral absorptions occurring near 2.2 to 2.3 μm due to the combination metal-OH bend plus OH stretch are very diagnostic of mineralogy (Clark et al., 1990; after Clark, 1999). However, it should be also paid attention here that the spectral diagnostics observed in the rock materials investigated in this study arise from completely intimate mixtures of the minerals involved in the rock samples. For this reason, depending on the compositional variations, the diagnostic absorptions may also vary more or less in previously defined specific absorption intervals (Clark, 1999). As a

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Table 1 The data produced in this study. Sample

Water Content (%)

Unit weight (kN/m3)

Vp (km/s)

UCS (MPa)

Ei (GPa)

Diagnostic spectral absorption bands

B1-7–52.5-U1 B1-8-57-59-U1 B1-8-57-59-U2 B3-2-21-22.5-U1 B5-3-25.5-27-U1 B5-3-28.5-30-U2 B1-9-58.5-60-U1 B1-9-58.5-60-U2 B1-9-58.5-60-U3 B3-3-25.5-27-U1 B3-3-30-31.5-U1 B3-4-31.5-33-U1 B3-4-31.5-33-U2 B1-3-24-25-U2 B2-4-22.5-24-U1 B2-5-28.5-30-U2 B4-3-26.5-27-U1 B4-6-43.5-45-U1 B5-1-15-16.5-U1 B5-3-27-28.5-U1 B5-3-27-28.5-U2 B5-3-28.5-30-U1 B1-3-24-25-U1 B1-3-25.5-27-U1 B2-3-18-19.5-U2 B2-5-28.5-30-U1 B2-5-30-31.5-U1 B4-6-40.5-42-U1 B1-2-18-19.5-U1 B2-1-6.5-8-U1 B2-1-8-9.5-U1 B2-3-18-19.5-U1 B2-6-36-37.5-U1 B4-2-19-21-U1 B4-3-26.5-27-U2 B2-6-33-34.5-U1 B4-2-18-19-U1 B4-2-18-19-U2 B4-3-25-26.5-U1 B5-2-19.5-21-U1 B5-2-24–U1 B2-3-19.5-21-U1 B2-5-30-31.5-U2 B2-7-39-40.5-U1 B3-4-39-42-U2 B4-4-28-29.5-U1 B4-4-32.5-34-U1 B4-5-39–U1 B5-3-25.5-27-U2 B1-10-72-73.5-U1 B2-2-12.5-14-U1 B2-3-16.5-18-U1 B2-3-16.5-18-U2 B2-4-26-27-U1 B2-4–27-U1 B2-5-28.5-30-U3 B2-6-34.5-36-U1 B2-6-37.5–U1 B3-4-39-40.5-U1 B3-4-39-40.5-U2 B3-4-39-42-U1 B4-3-24-25-U1 B4-6-42-43.5-U1 B5-2-19.5-21-U2 B5-2-22.5-24-U1 B5-2-24–U2

6.14 5.39 4.67 7.53 7.21 7.43 4.04 3.91 5.00 4.30 3.55 3.75 2.43 4.66 6.07 6.74 5.34 7.23 6.05 6.67 6.55 5.44 4.99 4.35 4.44 5.21 4.63 7.25 3.70 5.16 3.93 3.89 5.58 4.61 5.56 5.18 4.50 4.47 6.29 5.55 6.22 5.88 4.50 7.98 4.36 7.31 8.36 5.97 6.63 3.53 6.20 5.46 5.76 4.77 6.52 5.18 5.04 7.47 5.13 4.08 4.79 7.12 5.35 6.07 4.10 6.31

18.59 17.52 17.12 17.94 17.89 18.18 16.63 16.25 17.81 19.75 19.52 20.08 20.12 17.62 19.72 17.41 18.24 17.30 18.44 17.50 17.88 19.32 17.96 17.59 17.26 17.91 17.89 18.00 18.01 17.97 18.25 16.84 17.07 17.91 18.63 17.27 18.39 18.16 18.13 17.22 18.50 17.82 18.63 17.96 18.99 19.22 19.14 17.97 18.38 19.83 17.50 18.45 18.22 18.16 18.81 17.66 17.21 17.68 18.74 19.03 18.55 19.13 17.53 17.76 18.32 18.79

0.978 1.178 1.064 0.565 1.061 0.730 0.844 0.809 1.092 1.034 0.720 1.090 1.170 0.793 1.291 0.832 0.671 1.064 0.915 0.719 0.889 0.949 0.902 0.468 1.353 1.114 1.041 0.927 0.971 0.925 1.139 0.594 0.563 1.207 0.570 0.478 1.132 1.012 0.633 0.670 0.792 0.478 1.138 0.556 1.156 0.739 0.827 1.116 0.742 0.810 0.610 1.366 0.981 1.008 1.187 0.747 0.567 0.636 1.043 1.076 0.726 0.621 1.235 0.946 0.931 0.987

2.168 1.875 2.021 0.822 1.381 0.952 1.082 1.187 2.986 2.750 1.512 3.269 2.587 1.017 4.058 1.910 1.105 2.069 1.901 0.824 2.366 2.142 1.214 0.918 2.356 2.620 2.513 1.661 1.497 1.826 2.492 0.893 0.882 2.019 0.680 1.331 3.148 2.544 0.800 1.195 1.728 0.913 2.695 1.544 3.686 1.991 1.525 2.830 1.341 1.939 1.086 3.431 2.033 2.542 2.902 1.803 1.578 1.744 2.667 2.578 1.834 1.424 2.464 2.089 1.834 2.046

0.204 0.256 0.117 0.056 0.126 0.046 0.068 0.097 0.112 0.160 0.073 0.133 0.175 0.057 0.309 0.084 0.044 0.174 0.177 0.051 0.095 0.174 0.065 0.043 0.195 0.092 0.116 0.100 0.100 0.101 0.179 0.048 0.030 0.251 0.031 0.057 0.288 0.217 0.037 0.064 0.107 0.051 0.190 0.087 0.207 0.079 0.076 0.192 0.056 0.102 0.066 0.223 0.142 0.120 0.177 0.135 0.073 0.070 0.199 0.220 0.119 0.051 0.140 0.110 0.136 0.183

– – – – – – – – – – – – – – – – – – – – – – – – – – – – 654–661 653–682 679–691 657–681 681–691 625–642 638 683–684 625–637 631–634 684–687 681–690 687–690 697–698 676–681 697 698 691 690–697 687–695 692 659–691 691–697 687–698 698–699 687–698 697 690 690–699 692 697 691 671–691 681–698 695 693–697 685–697 690–693

– – – – – – – – – – – – – 717–737 704–715 715–724 712 709–716 704–705 716–726 702–714 706–714 715–727 711–748 701–712 710–717 700–717 701–721 – – – – – – – – – – – – – 700–711 700–715 706–714 700–719 703–705 713–714 701–706 708–724 724–731 707–712 701 700–726 701–714 708–728 701–708 707 713–718 711–722 700–717 705–728 718 700–709 707–710 701–717 704–709

consequence, according to the presence and absence of the relevant absorption information in the intimate mixtures, the samples were re-coded in binary format. Depending on the binary values representing the diagnostic spectral absorptions, 8 different genetic rock types were defined (Table 1).

– – – – – – 906–919 902–924 922–939 955–968 962–968 962–982 965–969 – – – – – – – – – 962 926 925–952 927 919 970 902–916 900–925 944–958 905–911 938–965 921–938 926 915–981 954 931–959 921 922–945 922 – – – – – – – – 961–968 927–933 929–980 944–949 928 932 922–985 952 955 966 924–929 923–935 969 932 956 912–936 966

1084–1152 1091–1101 1073–1144 1148–1152 1101–1118 1152 – – – – – – – 1083–1152 1150–1156 1084–1117 1153 1085–1101 1059 1106–1150 1083–1144 1101–1150 1099–1127 1093–1146 1052–1144 1093–1146 1056–1110 1066–1150 – – – – – – – 1144 1118–1151 1080 1059 1071 1074 1075–1142 1101–1126 1081–1156 1049–1150 1055–1157 1048–1154 1067–1093 1051–1106 1067–1150 1066–1097 1091–1101 1065–1150 1058–1148 1077–1152 1092–1111 1058–1117 1083–1152 1077–1150 1066–1086 1070–1148 1042–1152 1067–1090 1048–1152 1067–1110 1057–1150

Genetic rock type 1412 1412 1411–1412 1413 1413 1413–1414 1412–1413 1412–1413 1413 1413 1413 1413 1413 1412 1413–1414 1413 1414 1412–1413 1414 1413 1413–1414 1413 1412 1411–1412 1412–1413 1412–1413 1413 1413 1412–1413 1412–1413 1413 1412 1413 1413–1414 1414 1413 1413–1414 1413–1414 1414 1413 1413 1412–1413 1413 1413 1413 1414–1415 1413 1413 1413 1413 1413 1413 1413 1413 1413 1413 1413 1413 1412–1413 1412–1413 1412–1413 1415 1413 1413 1413–1414 1413–1414

1909–1910 1908–1910 1908–1910 1909–1910 1910 1910 1908–1910 1909–1910 1910 1910 1910 1910 1910 1908–1910 1910 1910 1912 1909–1910 1910–1912 1910 1910 1910 1908–1910 1908 1910 1908–1910 1910 1910 1910 1909–1910 1910 1908–1909 1910 1910 1912 1910 1910–1912 1910 1912 1910 1910 1910 1910 1910 1910 1910–1912 1910 1910 1910 1910 1910 1910 1910 1910 1910 1910 1910 1910 1910 1910 1909–1910 1912 1910 1910 1910–1911 1910–1912

2210–2211 2209 2209–2210 2210 2211 2211–2212 2209 2209 2209 2208–2209 2208–2209 2208–2209 2209 2209–2210 2211–2212 2211–2212 2211 2210 2211–2212 2211 2211 2210–2211 2209–2210 2208–2209 2211–2212 2211 2211–2212 2211–2212 2208–2209 2210–2211 2210 2211–2212 2210-2212 2211-2213 2211 2211–2212 2210–2212 2212–2213 2210–2211 2211–2212 2211 2211 2209–2210 2211–2212 2210–2211 2211 2210–2211 2211–2212 2211 2208–2209 2210 2210–2211 2211–2212 2211–2212 2211–2212 2211–2212 2211–2212 2211–2212 2210 2210–2211 2210–2211 2211–2212 2211 2211–2212 2211–2212 2211

0001111 0001111 0001111 0001111 0001111 0001111 0010111 0010111 0010111 0010111 0010111 0010111 0010111 0101111 0101111 0101111 0101111 0101111 0101111 0101111 0101111 0101111 0111111 0111111 0111111 0111111 0111111 0111111 1010111 1010111 1010111 1010111 1010111 1010111 1010111 1011111 1011111 1011111 1011111 1011111 1011111 1101111 1101111 1101111 1101111 1101111 1101111 1101111 1101111 1111111 1111111 1111111 1111111 1111111 1111111 1111111 1111111 1111111 1111111 1111111 1111111 1111111 1111111 1111111 1111111 1111111

Additionally, to establish quantitative comparisons of the specific absorption depths, the continuum removed calculations were also performed (Eq. (1)). D ¼ 1−ðRb =Rc Þ

ð1Þ

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Table 2 Descriptive statistics for the physical properties of the rock materials investigated in this study. Property

Min.

Max.

Mean

Median

Mode

Std. deviation

Variance

Skewness

Kurtosis

Water Content (%) Unit Weight (kN/m3) Vp (km/s) UCS (MPa) Ei (GPa)

2.430 16.250 0.468 0.680 0.030

8.360 20.120 1.366 4.058 0.309

5.447 18.171 0.897 1.922 0.123

5.345 18.005 0.926 1.888 0.109

4.500 17.500 0.478 1.834 0.051

1.252 0.820 0.232 0.771 0.067

1.567 0.673 0.054 0.595 0.005

0.202 0.396 −0.067 0.475 0.722

−0.452 0.097 −0.917 −0.183 −0.182

where, D is the absorption depth, Rb is the reflectance at the band bottom, and Rc is the reflectance continuum at the same wavelength as Rb (Clark and Roush, 1984; after Clark, 1999). The depth of absorption indicates the abundance of the absorber as well as the grain size of the rock material (Clark, 1999). The continuum-removal process isolates the spectral features and puts them on a reference level hence they may be compared with each other (Clark, 1999). When the continuum removed spectra of the samples are compared (Figure 4), the distinctions between different genetic rock types could be clearly realized. In addition to the diagnostic absorptions, the abundance and grain size properties of the absorbers also vary depending on the genetic rock type. Some example macroscopic views of different genetic rock types are also represented in Fig. 5. In order to verify the source of these specific absorption diagnostics in the reflectance spectra, supplementary X-ray diffraction analyses were also conducted. Since all spectral absorption diagnostics are observed, the genetic rock type 1111111 was selected to be the characteristic sample for the purpose. The analyses were carried out by using Rigaku DMAX III model diffractometer having Cu X-Ray tube with a goniometer speed of 2°/min. An example view of typical XRD pattern of the powdered sample of the genetic rock type 1111111 is given in Fig. 6a. The resultant XRD patterns were evaluated by considering the method suggested by Gundogdu (1982). According to the whole rock analyses of the powdered samples it is revealed that the genetic rock type 1111111 mainly consists of clay minerals, and less amounts of calcite, quartz, mica, dolomite, and feldspar (Table 3). Additionally, trace amounts of hematite and amphibole were also recognized (Figure 6a). In order to investigate the clay fraction (b 0.002 mm), the XRD analyses were also repeated by using three forms of the same samples: (i) oriented-untreated, (ii) ethylene glycol-treated, and (iii) oriented-heated to 500 °C for 2 h (Figure 6b–d). According to the results of the analyses for the oriented samples, the clay fraction mainly consists of smectite, chlorite kaolinite, and illite (Table 4). It is well known that the reflectance spectroscopy is more sensitive to the presence of clay minerals, iron oxides, iron hydroxides, and other minerals except for quartz with strong absorption diagnostics at levels significantly lower than other methods (Farmer, 1974; after Clark, 1999). Hence, when the source of the crystal field effect and charge transfer absorptions observed in the rock materials are investigated by considering the mineral constituents, it could be realized that they arise from Fe 2+ and Fe 3+ ion constituents in chlorite, Fe 2+–F 3+, Fe 2+ ion constituents in illite, Fe 2+ constituent in mica (biotite), and

Cr3+ ion constituent in mica (muscovite) (Clark et al., 2007). Additionally, even though it is observed in trace amounts, the hematite constituent in the samples should also affect the strength of these absorptions. On the other hand, the source of the water and OH vibrational absorptions are essentially caused by H2O constituents in smectite (montmorillonite) and illite, OH constituents in kaolinite, illite, mica (muscovite), and amphibole, and Al–OH constituents in illite (Clark et al., 2007). 4. Development of empirical equations Two-stage curve fitting was performed in order to evaluate the empirical equations of Vp-UCS and Vp-Ei in this study. Linear, power, and exponential models were investigated (Figure 7). In the first stage, the overall data were evaluated together, and the empirical equations of Vp-UCS and Vp-Ei were written for the unclassified rock material consisting of sedimentary rock claystones and mudstones (Table 5). The exponential models produce the best equations with the multiple coefficients of correlations 0.815 and 0.851 for the equations of Vp-UCS and Vp-Ei, respectively. Additionally, in order to investigate the statistical significances of the equations, analysis of variance tests was carried out. The F values were calculated to be 126.95 and 167.60 for the equations of Vp-UCS and Vp-Ei, respectively, and considering the significance level of 0.05 they were found to be statistically significant. In the second stage, the data were classified according to the genetic rock types defined in this study. Linear, power, and exponential models for the equations of Vp-UCS and Vp-Ei were reinvestigated for each genetic rock type separately (Figures 8 and 9). According to the results of the curve fitting, it is revealed that different types of models could produce different types of empirical equations depending on the nature of the genetic rock type (Table 5). However, it is also remarkably revealed that the multiple coefficients of correlations increase. The mean values of the multiple coefficients of correlations were obtained to be 0.904 and 0.916 for the best equations of Vp-UCS and Vp-Ei, respectively. Considering the values of those for the equations produced from overall unclassified rock materials, the explained variances are increased at the rates of 8.9% and 6.5%. Furthermore, considering the maximum values of R, the increment rates for the values of the explained variances reach up to 14.3% and 13 .5% for the equations, respectively. Additionally, according to the results of the analysis of variance evaluations, the best fit equations of Vp-UCS and Vp-Ei produced for each genetic rock type were also found to be statistically significant at the significance level of 0.05.

Fig. 2. Some example views of the failure modes observed during the UCS tests (a) B3-3-30-31.5-U1, (b) B3-4-39-40.5-U1, and (c) B4-6-42-43.5-U1.

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Fig. 3. Some example views of the characteristic reflectance spectra for the samples (a) B2-2-12.5-14-U1, (b) B2-5-30-31.5-U2, (c) B4-2-18-19-U1, (d) B2-1-8-9.5-U1, (e) B2-5-28.5-30-U1, (f) B4-3-26.5-27-U1, (g) B3-3-25.5-27-U1, and (h) B1-8-57-59-U1.

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Fig. 4. Some example views of the characteristic continuum removed spectra for the samples (a) B2-2-12.5-14-U1, (b) B2-5-30-31.5-U2, (c) B4-2-18-19-U1, (d) B2-1-8-9.5-U1, (e) B2-5-28.5-30-U1, (f) B4-3-26.5-27-U1, (g) B3-3-25.5-27-U1, and (h) B1-8-57-59-U1.

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Fig. 5. Macroscopic views of different genetic rock types (a) B2-2-12.5-14-U1, (b) B2-5-30-31.5-U2, (c) B4-2-18-19-U1, (d) B2-1-8-9.5-U1, (e) B2-5-28.5-30-U1, (f) B4-3-26.5-27-U1, (g) B3-3-25.5-27-U1, and (h) B1-8-57-59-U1.

5. Discussions and conclusions In this study, the geo-mechanical properties of claystones and mudstones collected from Firuzkoy area of Istanbul (Turkey) were investigated. According to Folk (1974), the term mudstone includes both rock types of siltstone and claystone together. In case the abundant grain size is silt the rock material is named to be siltstone while if the abundant grain size is clay then the rock material is named to be claystone (Folk, 1974). Folk (1974) also mentioned that in case the grain size proportions of silt and clay are almost equal the rock material could be named to be mudstone. Mudstones consist of more than

50% of sedimentary rocks; hence they are the most common rock type encountered during geo-engineering constructions (Lashkaripour, 2002). However, Lashkaripour (2002) emphasized that there is a considerable lack of research on the geo-mechanical properties of these weak rocks in the literature. As mentioned previously, due to economical and practical reasons, and mostly difficulties in sample preparation, the geo-mechanical properties of rock material tend to be obtained by indirect techniques with empirical equations in geoengineering design problems. The empirical equations of different relations between the geo-mechanical properties and various indirect techniques were compiled by Zhang (2005). In this context, 41

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Fig. 6. Some example views of typical XRD patterns for the sample B5-2-24–U2 (a) whole rock sample, (b) oriented-untreated sample, (c) ethylene glycol-treated sample, and (d) oriented-heated sample.

empirical equations between the UCS and point load index, 16 empirical equations predicting the UCS by using the Schmidt hammer rebound number, and 12 empirical equations of the UCS and ultrasonic pulse velocity were reviewed by Zhang (2005). Furthermore, 8 empirical equations for the evaluation of the modulus of elasticity by using the Schmidt hammer rebound number were also reported by Zhang (2005). When the point load index is taken to be 1 MPa for the equations, the lowest UCS value among them is calculated to be 5 MPa for chalk and porous limestones (Kahraman, 2001). On the other hand, when investigating the study performed by Deere and Miller (1966), the minimum UCS value which could be predicted by using the Schmidt hammer rebound number was approximately given to be 10 MPa. Actually, when considering weak rocks and particularly very weak rocks, even any reading could not be obtained from these rock materials by using the point load and Schmidt hammer tests. As mentioned previously, among these indirect techniques, the main advantage of the ultrasonic pulse velocity measurement is to be a non-destructive technique. When we evaluate the studies performed by using the ultrasonic pulse velocity measurements, it could be realized that the lowest strength values among them were

Table 3 The results of the whole rock XRD evaluations for the characteristic samples. Sample

Table 4 The clay fraction for the characteristic samples.

Mineral (%) Quartz

B2-3-16.5-18-U2 B3-4-39-40.5-U1 B5-2-24–U2

evaluated in the study performed by Golubev and Rabinovich (1976) after Zhang, (2005) for schists. The minimum P-wave velocity was given to be approximately 2 km/s for schists by Schön (1996) after Zhang, (2005). Even considering the minimum P-wave velocity value to be 1 km/s, the lowest UCS value could be obtained to be about 2.8 MPa (Golubev and Rabinovich, 1976; after Zhang, 2005). Considering the other indirect technique block punch, cone indenter, and core strangle tests, either sample preparation for the tests or reading accurate loadings from these tests are very difficult for very weak and weak rocks as well. When the block punch index value is taken to be approximately 1 MPa, the minimum values are obtained to be 5.5 MPa and 5.1 MPa for the empirical equations given by Ulusay and Gokceoglu (1997) and Ulusay et al. (2001), respectively. According to the MRDE (1977), the minimum rock material strength value which could be obtained by using the cone indenter is 10 MPa. The main reason for this limitation for the lowest strength which could be evaluated for very weak and weak rocks is obviously the difficulty in appropriate sample preparation for the test. Even though the cone indenter test was modified for considerably weak rocks, the limitations did not allow evaluating indirect strength values for very weak and weak rocks by using this technique. On the other

9.58 20.33 10.46

Feldspar group

Mica group

Calcite

3.15 4.03 3.63

7.62 10.84 13.89

16.12 8.91 18.65

Dolomite 6.61 1.24 2.58

Clay mineral 56.92 54.65 50.79

Sample

B2-3-16.5-18-U2 B3-4-39-40.5-U1 B5-2-24–U2

Mineral (%) Smectite

Illite

Kaolinite

Chlorite

31.35 32.90 31.09

10.86 15.28 10.41

24.92 19.93 26.19

32.87 31.89 32.31

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Fig. 7. The empirical equations of (a) Vp-UCS and (b) Vp-Ei for the unclassified rock material consisting of sedimentary rocks claystones and mudstones.

hand, the lowest strength value evaluated in the core strangle test is 21.70 MPa (Yilmaz, 2009). The researcher mentions that any load reading in core strangle test may not be obtained for very weak and weak rocks, the cutting device may not work properly, the samples may squeeze, and for this reason there may be no proper failure in the test for very weak and weak rocks in particular (I. Yilmaz, personal communication, March 8, 2013). As a consequence, it could be concluded that a very unique rock material was evaluated in this study. As mentioned previously, the minimum and maximum UCS values

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were obtained to be 0.68 MPa and 4.06 MPa for claystones and mudstones together. This compressive strength range was also defined to be typical lowest strength boundary for non-durable and durable rock material (Grainger, 1984). This study is the first research which provides a well-documented data for the geo-mechanical properties of these very weak and weak rocks having the compressive strength values within this boundary condition in the literature. Zhang (2005) also mentioned that different empirical equations result drastically different strength values even for individual rock types, for this reason the author suggests that some additional tests should be done for specific sites to calibrate the empirical equations and obtain more reliable results. For this purpose, the main rock types of igneous, metamorphic, and sedimentary rocks were evaluated separately by Kahraman and Gunaydin (2009). The researchers reported that the multiple coefficients of correlations obtained for the empirical equations of the UCS and point load index for different rock types increase. However, actually, it would be expected to be a routine to separate the main rock types in the evaluation of the relevant empirical equations in such cases. On the other hand, the main problem arises during the evaluation of the empirical equations for unique rock types (Zhang, 2005). For example even though claystones and mudstones include a large amount of clay minerals, this clay mineral constituent is not taken into account during rock definition (Folk, 1974). Hence, even in an individual rock type, the ratios between the UCS and other indirect indices may vary drastically in a wide range (Zhang, 2005). In this study, it is revealed that unique rock material could be differentiated into its genetic types, and these genetic rock types could be efficiently used to improve and calibrate the empirical equations for the relevant geo-mechanical properties. Considering the high sensitivity property of the reflectance spectroscopy to clay minerals (Farmer, 1974; after Clark, 1999), the reflectance spectroscopy was used to be a classification tool in order to differentiate the genetic rock types of claystones and mudstones. The increment rates for the values of the explained variances in the empirical equations reach up to approximately 14% while the values of the multiple coefficients of correlations reach up to 0.958 in the evaluations where the genetic rock types were differentiated. As a consequence, the reflectance spectroscopy is suggested to be a classification tool in the evaluation of the empirical equations for the geo-mechanical properties of very weak and weak rocks, particularly those of including abundant clay mineral constituents. The X-ray diffraction analyses might be an alternative technique for the purpose. However, it should be paid attention here that if anyone desires to achieve such type of classification by using

Table 5 The results of the statistical evaluations with respect to unclassified rock material consisting of sedimentary rocks claystones and mudstones and the genetic rock types. Rock type

Unclassified 1111111 1101111 1011111 1010111 0111111 0101111 0010111 0001111 Unclassified 1111111 1101111 1011111 1010111 0111111 0101111 0010111 0001111

Multiple coefficients of correlation (R) for the models Linear

Power

Exponential

0.814 0.916 0.903 0.915 0.940 0.825 0.922 0.866 0.808 0.818 0.836 0.914 0.951 0.943 0.874 0.958 0.846 0.794

0.809 0.900 0.904 0.814 0.958 0.865 0.893 0.849 0.873 0.844 0.866 0.866 0.895 0.981 0.900 0.950 0.854 0.842

0.815 0.903 0.913 0.862 0.950 0.864 0.883 0.858 0.864 0.851 0.842 0.905 0.930 0.986 0.935 0.931 0.859 0.861

Empirical equation

UCS UCS UCS UCS UCS UCS UCS UCS UCS Ei Ei Ei Ei Ei Ei Ei Ei Ei

= = = = = = = = = = = = = = = = = =

0.457983 2.258013 0.499138 3.313262 1.779459 1.902589 4.751294 4.585574 1.642474 0.015478 0.146710 0.228951 0.391869 0.006272 0.018725 0.441939 0.018831 0.010768

e1.504268 (Vp) (Vp) + 0.060749 e1.575529 (Vp) (Vp) − 0.814776 (Vp)1.409563 (Vp)1.031474 (Vp) − 2.354974 (Vp) − 2.230556 (Vp)1.277730 e2.135656 (Vp) (Vp)1.418268 (Vp) − 0.075984 (Vp) − 0.179741 e2.979848 (Vp) e1.638227 (Vp) (Vp) − 0.269430 e1.832345 (Vp) e2.520890 (Vp)

Analysis of variance (ANOVA) for the equation Degree of freedom for regression (ν1)

Degree of freedom for residuals (ν2)

F

Sig. F

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

64 15 6 4 5 4 7 5 4 64 15 6 4 5 4 7 5 4

126.95379 78.32845 30.21048 20.56516 56.19001 11.92603 39.94013 15.04201 12.85012 167.59776 44.81389 30.39703 37.78633 170.03450 27.62721 77.44508 14.09843 11.50000

0.0000 0.0000 0.0015 0.0105 0.0007 0.0260 0.0004 0.0117 0.0231 0.0000 0.0000 0.0015 0.0036 0.0000 0.0063 0.0000 0.0132 0.0275

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Fig. 8. The empirical equations of Vp-UCS for the genetic rock types (a) 1111111, (b) 1101111, (c) 1011111, (d) 1010111, (e) 0111111, (f) 0101111, (g) 0010111, and (h) 0001111.

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Fig. 9. The empirical equations of Vp-Ei for the genetic rock types (a) 1111111, (b) 1101111, (c) 1011111, (d) 1010111, (e) 0111111, (f) 0101111, (g) 0010111, and (h) 0001111.

the XRD method, he has to perform a large number of analyses. Obviously, it should be very expensive as well as time consuming that means completely unrealistic. Additionally, the main drawback of

the XRD method for the purpose is sample preparation. The reflectance spectroscopy does not need sample preparation; hence it is a non-destructive method in application. The historical disadvantage

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of the reflectance spectroscopy is that it is too sensitive to small changes in the chemistry and/or structure of the rock material (Clark, 1999). However, today depending on the increment of the knowledge about the spectroscopy, the historical disadvantage turns out to be a huge advantage allowing us to investigate ever more detail about the chemistry of our environment (Clark, 1999). There are a few applications of the reflectance spectroscopy in engineering geology in the literature. Particularly, the weathering degrees of igneous rocks were investigated (Riaza et al., 2001; Michalski et al., 2006; Hyun and Park, 2011). On the other hand, this study constitutes the first experimental research investigating the geo-mechanical properties of rock material by using the reflectance spectroscopy in the literature. As a recommendation for future studies, thermal infrared spectroscopy should also be investigated by considering additional quartz content in the rock materials and increasing the number of samples for statistical evaluations. Acknowledgment The core samples were provided by the Hacettepe University Scientific Research Unit Ankara, Turkey with the project 07 01 602 001, and used with the permission of the project leader Prof. Dr. Candan Gokceoglu. The author also would like to gratefully thank to Mr. Murat Koruyucu and Dr. Engin O. Sumer for providing necessary conditions in order to implement spectroscopic measurements and XRD analyses. References Alber, M., Kahraman, S., 2009. Predicting the uniaxial compressive strength and elastic modulus of a fault breccia from texture coefficient. Rock Mechanics and Rock Engineering 42, 117–127. ASTM (American Society for Testing Materials), 1994. Annual Book of ASTM Standards — Construction: Soil and Rock. ASTM Publication, V. 04.08, 978 pp. Boer, N.P. de, 1954. Report on a geological reconnaissance in Turkish thrace. September– December G.A., Report No: 25373. British Standard Institution, 1981. Code of practice for site investigation. BS 5930. HMSO, London. Clark, R.N., 1999. Chapter 1: spectroscopy of rocks and minerals, and principles of spectroscopy, In: Rencz, A.N. (Ed.), Remote sensing for Earth sciences, Third edition. Manual of Remote Sensing, vol. 3. Wiley, New York, pp. 3–58. Clark, R.N., Roush, T.L., 1984. Reflectance spectroscopy: quantitative analysis techniques for remote sensing applications. Journal of Geophysical Research 89, 6329–6340. Clark, R.N., King, T.V.V., Klejwa, M., Swayze, G., Vergo, N., 1990. High spectral resolution reflectance spectroscopy of minerals. Journal of Geophysical Research 95 (B8), 12653–12680. Clark, R.N., Swayze, G.A., Wise, R., Livo, E., Hoefen, T., Kokaly, R., Sutley, S.J., 2007. USGS Digital Spectral Library Splib06a: U.S. Geological Survey, Digital Data Series 231. http://speclab.cr.usgs.gov/spectral.lib06. Deere, D.U., Miller, R.P., 1966. Engineering classification and index properties for intact rock. Air Force Weapons Lab. Tech. Report, AFWL-TR 65–116, Kirtland Base, New Mexico, 300 pp. Duman, T.Y., Kecer, M., Ates, S., Emre, O., Gedik, I., Karakaya, F., Durmaz, S., Olgun, S., Sahin, H., Gokmenoglu, O., 2004. Istanbul Metropolu Batisindaki (KucukcekmeceSilivri-Catalca Yoresi) Kentsel Gelisme Alanlarinin Yer Bilim Verileri. MTA Special Publication Series No: 3, 249 pp. (In Turkish). Duman, T.Y., Can, T., Gokceoglu, C., Nefeslioglu, H.A., Sonmez, H., 2006. Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey. Environmental Geology 51, 241–256. Farmer, V.C. (Ed.), 1974. The infra-red spectra of minerals. : Mineralogical Society Monograph, vol. 4. The Mineralogical Society of Great Britain and Ireland, London, 539 pp. Folk, R.L., 1974. Petrology of Sedimentary Rocks. Hemphill Publishing Company, Austin, Texas, 184 pp. Gokceoglu, C., Aksoy, H., 2000. New approaches to the characterization of clay-bearing, densely jointed and weak rock masses. Engineering Geology 58, 1–23. Gokceoglu, C., Sonmez, H., Tunusluoğlu, M.C., Gorum, T., Gultekin, N., Dagdevirenler, G., 2010. Yuksek Sismik Aktiviteye Sahip Bir Bolgede Heyelan Tehlikesinin Degerlendirilmesi. Hacettepe Universitesi, Bilimsel Arastirmalar Birimi, Kapsamli Arastirma Projesi Sonuc Raporu, Proje No: 07 01 602 001, 82 pp. (In Turkish).

Golubev, A., Rabinovich, G.J., 1976. Resultaty primenenia apparatury akusticeskogo karotasa dlja predelenia procnostych svoistv gornych porod na mestorosdeniach tverdych iskopaemych. Prikladnaja Geofizika Moskva, 73 109–116 (In Russian). Grainger, P., 1984. The classification of mudrocks for engineering purposes. Quarterly Journal of Engineering Geology & Hydrogeology 17, 381–387. Gundogdu, M.N., 1982. Neojen Yasli Bigadic Sedimanter Baseninin Jeolojik Mineralojik ve Jeokimyasal Incelenmesi. Hacettepe Universitesi, Jeoloji Muhendisligi Bolumu, Doktora Tezi, Ankara, Turkey, 386 pp. (In Turkish). Hawkins, A.B., 2000. General report: The nature of hard rocks/soft soils. In: Evangelista, A., Picarelli, L. (Eds.), The Geotechnics of Hard Soils — Soft Rocks. Balkema, Rotterdam, pp. 1391–1401. Hunt, G.R., 1977. Spectral signatures of particulate minerals, in the visible and nearinfrared. Geophysics 42 (3), 501–513. Hyun, C.U., Park, H.D., 2011. Assessment of chemical weathering of granite stone monuments using reflectance spectroscopy. Bulletin of Engineering Geology and the Environment 70, 63–78. I.S.R.M. (International Society for Rock Mechanics), 1981. Rock characterization, testing and monitoring: I.S.R.M. In: Brown, E.T. (Ed.), Suggested Methods. Pergamon Press, Oxford, 217 pp. I.S.R.M. (International Society for Rock Mechanics), 2007. In: Ulusay, R., Hudson, J.A. (Eds.), The Complete ISRM Suggested Methods for Rock Characterization, Testing and Monitoring: 1974–2006. TUKMD, Ankara, 628 pp. Kahraman, S., 2001. Evaluation of simple methods for assessing the uniaxial compressive strength of rock. International Journal of Rock Mechanics and Mining Sciences 38, 981–994. Kahraman, S., Gunaydin, O., 2009. The effect of rock classes on the relation between uniaxial compressive strength and point load index. Bulletin of Engineering Geology and the Environment 68, 345–353. Kahramana, S., Gunaydin, O., Fener, M., 2005. The effect of porosity on the relation between uniaxial compressive strength and point load index. International Journal of Rock Mechanics and Mining Sciences 42, 584–589. Lashkaripour, G., 2002. Predicting mechanical properties of mudrock from index parameters. Bulletin of Engineering Geology and the Environment 61 (1), 73–77. Leite, M.H., Ferland, F., 2001. Determination of unconfined compressive strength and Young's modulus of porous materials by indentation tests. Engineering Geology 59, 267–280. Michalski, J.R., Kraft, M.D., Sharp, T.G., Christensen, P.R., 2006. Effects of chemical weathering on infrared spectra of Columbia River Basalt and spectral interpretations of martian alteration. Earth and Planetary Science Letters 248 (3–4), 822–829. MRDE, 1977. MRDE Handbook No. 5 NCB Cone Indenter. National Coal Board, London. Nassif, A., 2003. Stress–strain relationship for weak rocks. In: Di Benedetto, H., Doanh, T., Geoffroy, H., Sauzèat, C. (Eds.), Deformation Characteristics of Geomaterials. Swets & Zeitinger, Lisse, pp. 415–419. Quane, S.L., Russel, J.K., 2003. Rock strength as a metric of welding intensity in pyroclastic deposits. European Journal of Mineralogy 15, 855–864. Riaza, A., Strobl, P., Müller, A., Beisl, U., Hausold, A., 2001. Spectral mapping of rock weathering degrees on granite using hyperspectral DAIS 7915 spectrometer data. International Journal of Applied Earth Observation and Geoinformation 3 (4), 345–354. Sayar, C., 1977. Istanbul Yeni Iskan Yoreleri Geoteknik ve Sismik Etudu. Basilmamis Rapor, Cilt I, Buyukcekmece-Kucukcekmece Goller Arasi Yore. B.U. Deprem Muhendisligi Arastirma Enstitusu Raporu, 14–27 (In Turkish). Schön, J.H., 1996. Physical Properties of Rocks: Fundamentals and Principles of Petrophysics. Pergamon, Oxford. Tsiambaos, G., Sabatakakis, N., 2004. Considerations on strength of intact sedimentary rocks. Engineering Geology 72, 261–273. Ulusay, R., Gokceoglu, C., 1997. The modified block punch index test. Canadian Geotechnical Journal 34 (6), 991–1001. Ulusay, R., Gokceoglu, C., Sulukcu, S., 2001. Draft ISRM suggested method for determining block punch strength index (BPI). International Journal of Rock Mechanics and Mining Sciences 38 (8), 1113–1119. Umut, M., Kurt, Z., Imik, M., Ozcan, I., Sarikaya, H., Sarac, G., Keskin, I., 1983. Tekirdag, Silivri (Istanbul), Pinarhisar Alaninin Jeolojisi. MTA Report, Report No: 7349 (In Turkish). Yasar, E., Erdogan, Y., 2004. Correlating sound velocity with the density, compressive strength and Young's modulus of carbonate rocks. International Journal of Rock Mechanics and Mining Sciences 41 (5), 871–875. Yilmaz, I., 2009. A new testing method for indirect determination of the unconfined compressive strength of rocks. International Journal of Rock Mechanics and Mining Sciences 46, 1349–1357. Zhang, L., 2005. In: Hudson, J.A. (Ed.), Engineering Properties of Rocks. : Elsevier GeoEngineering Book Series, vol. 4. Elsevier, Oxford, 290 pp. Zorlu, K., Gokceoglu, C., Ocakoglu, F., Nefeslioglu, H.A., Acikalin, S., 2008. Prediction of uniaxial compressive strength of sandstones using petrography-based models. Engineering Geology 96, 141–158.