Advanced
CLSM [Confocal Laser Scanning Microscope] Observation of the Surface Roughness of Pressurized Rock Samples During Freeze/Thaw Cycling
CLSM [Confocal Laser Scanning Microscope] Observation of the Surface Roughness of Pressurized Rock Samples During Freeze/Thaw Cycling
The Journal of Engineering Geology. 2015. Jun, 25(2): 165-178
Copyright © 2015, The Korea Society of Engineering Gelology
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons. org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • Received : March 31, 2015
  • Accepted : June 07, 2015
  • Published : June 30, 2015
Download
PDF
e-PUB
PubReader
PPT
Export by style
Share
Article
Author
Metrics
Cited by
TagCloud
About the Authors
Hye-jin Kim
Geologic Environment Division, Korea Institute of Geoscience and Mineral Resources
Junghae Choi
Geologic Environment Division, Korea Institute of Geoscience and Mineral Resources
jhchoi@kigam.re.kr
Byung-gon Chae
Geologic Environment Division, Korea Institute of Geoscience and Mineral Resources
Gyo-won Kim
College of Natural Science, Kyungpook National University

Abstract
Physical and chemical weathering degrades rock, affecting its structural properties and thus the stability of stone buildings or other structures. Confocal laser scan microscopy (CLSM) is used here to observe temporal changes in the surface roughness of rock samples under simulated accelerated weathering. Samples were pressurized to 50, 55, or 70 MPa using a pressure frame, and subjected to freeze/thaw cycling controlled by a thermostat. The temperature was cycled from -20℃ to 40℃ and back. After each 20 cycles, CLSM was used to assess the change in surface roughness, and roughness factors were calculated to quantify the progression of the surface condition over time. Variations in cross-section line-roughness parameters and surface-roughness parameters were analyzed for specific parts of the sample surfaces at 5× and 50× magnification. The result reveals that the highest and lowest values of the roughness factors are changed according to elapsed time. Freezing/thawing at high pressure caused larger changes in the roughness factor than at low pressure.
Keywords
Introduction
Physical and chemical weathering can degrade rock to the point that buildings or structures become unstable, and roughness of the rock surface may affect the deformation of the rock during weathering process. Korea has a climate marked by distinct variations in temperature: the seasonal cycle of freezing and thawing significantly weathers rock and stone (Jang et al., 2004 ; Um et al., 2014) . The rock with fractures can be weathered under even low stress condition and we can recognize weathering by generation of cracks (Park and Bobet, 2010 ; Haeri et al., 2014) . We simulated accelerated weathering by applying large temperature changes in freeze/thaw cycles at high pressure. We recorded the progression of the roughness parameters during the freeze/thaw cycling, because it was expected to show changes in the surfaces of the samples.
Previous experiments have observed weathering through freeze/thaw cycles or pressurization, and roughness is often measured because of its correlation with shear (Lee et al., 1994 ; Hong et al., 2011) . Weathering simulated by freezing/thawing has the following general properties: cracks occur during freezing due to the expansion of water in microcracks or pores, and repeated freezing/thawing results in water flowing into and expanding the newly created cracks to weaken the sample (Yavuz et al., 2006) . Simulated accelerated weathering by repeated freezing/thawing experiments have been conducted by McGreevy and Whalley (1985) , Nicolson and Nicholson (2000) , Chen et al. (2004) , Um and Shin (2009) , and Brotons et al. (2014) . Weathering experiments conducted under high pressure can be used to assess the fundamental mechanical fracture characteristic of rocks (Baek, 1997) . Such experiments have shown that cracks form as a result of weathering caused by pressure (Horii and Nemat-Nasser, 1986 ; Reyes and Einstein, 1991 ; Shen, 1995 ; Lu et al., 2012) , and the weathering can been observed using a microscope (Labuz et al., 1985) . Surface roughness can be assessed either by using a three-dimensional roughness tester (Bae et al., 2002 ; Lee et al., 2007) or by precisely measuring the geometry of the surface by microscopy and correlating the observed roughness with the sample’s shear behavior (Kim et al., 2004) . Calculating the quantitative roughness parameter using JRC (Joint Roughness Coefficient) (Lee et al., 1994 ; Kim et al., 2001) allows experiments to be conducted to examine the way in which a joint affects shear behavior (Leichnitz, 1985 ; Kwan et al., 2003) .
The current work reports the application of freeze/thaw temperature treatment to pressurized samples, following previous experiments, to observe the changes in sample roughness during weathering. Confocal laser scanning microscopy (CLSM) was used for observing the surfaces of the samples during the freeze/thaw cycling, because it allows three-dimensional measurement. It can precisely measure minute displacements that form quickly during freezing-thawing experiments , the observation of which is generally time consuming The use of CLSM images allowed changes in various surface roughness parameters, including 2D and 3D cross-sectional profiles, to be measured during weathering.
Experiment and analysis method
- Samples
The samples tested here from the Mesozoic Daebo granite at 223.6 m depth on the west side of the Okcheon Belt in Daejeon, Korea ( Fig. 1 ). Two-mica granites occupy most of the region, along with aplites and acidic/basic dikes. The two-mica granites coexist with granodiorites that contain biotite and xenoliths that contain large amounts of mafic minerals and foliated granite. The Rb/Sr age of the whole granite 190 Ma (Park et al., 1977 ; Lee et al., 1980) . Two-mica granites generally have a lumpy medium-texture tissue; the minerals identifiable by the naked eye are quartz, feldspar, biotite, and muscovite. Biotite and muscovite are yielded together. The two-mica granites common throughout the research area have aplites distributed in several places. The granite is occurred in a zone trending WNW-ESE including pegmatites, as well as a swarm of acidic, neutral, and basic dikes that trend between N10°W and N10°E (Korea institute of geoscience and mineral resources, 2013) .
PPT Slide
Lager Image
Map showing the area of sample collection in Daejeon on the west side of the Okcheon Belt (Korea Institute of Geoscience and Mineral Resources, 2013).
The samples were prepared with dimensions of 20 × 40 × 5 mm for convenient use in high-pressure environments and CLSM analysis ( Fig. 2 ). Their main surfaces were polished to 0.001% flatness to maximize reflectance for precise measurement. Three samples were used and fixed to a 90 × 150 × 35 mm pressure frame ( Fig. 3 ) manufactured to impose consistent pressure. Pressures of 50, 55, and 70 MPa were tested with all other conditions kept constant.
PPT Slide
Lager Image
Photograph of the three granite samples tested here.
PPT Slide
Lager Image
Photograph of a sample secured in the pressure frame.
- Freeze/thaw experiment
Simulated weathering by freezing/thawing altered stresses in the samples as water in pores or cracks frozen and thawed with the changing temperature, thereby inducing the effects of prolonged exposure. The equipment ( Fig. 4 ) includes a programmable thermostat that can set temperatures in the range of -40 to 100℃ to ± 0.3℃ accuracy; this allows a uniform temperature program to be followed consistently for all samples.
PPT Slide
Lager Image
(Left and center) The pressure frame is filled with distilled water, sealed, and placed in the thermostat-controlled temperature chamber at steady pressure. (Right) The temperature program for freezing/thawing.
Each pressure frame containing a sample was filled with distilled water, pressurized to the required pressure, and sealed to ensure complete water saturation of the sample for the freezing/thawing experiment. The temperature program of -20℃ to 40℃ is representative of the seasonal changes in Korea. Each 6 h cycle included 1 h of heating to 40℃, 2 h of holding at 40℃, 1 h of cooling to -20℃, and 2 h of holding at -20℃ ( Fig. 4 ). After 20 such cycles, the samples were removed and observed by CLSM.
- Roughness analysis using CLSM
An OLYMPUS model OLS4000 was used for CLSM ( Fig. 5 ). This differs from ordinary microscopes in its high power (108× to 17,280× magnification) and ability to create clear three-dimensional images using a confocal lens. Its high resolution is due to the use of short-wavelength lasers that can obtain images of steep slopes and curved surfaces, which make it suitable for analyzing surface changes (e.g., roughness) in this experiment.
PPT Slide
Lager Image
The set-up for confocal laser scanning microscopy (CLSM).
After each 20 freeze/thaw cycles, the CLSM was used to characterize the surface of each sample at a certain constant location ( Fig. 6 ). Observing each surface using 5× and 50× lenses allowed the roughness along a cross-sectional line and across the surface generally to be accurately measured on a micron scale ( Fig. 7 ). The 5× lens allowed observation of a 2560 × 2560 µm 2 area, and the line roughness and surface roughness of each sample were measured using images obtained after each 20 cycle. Roughness was measured along 18 cross-sectional lines: nine vertical and nine horizontal. The 256 × 256 µm 2 area observed by the more powerful 50× lens was also measured for line roughness and surface roughness in a method similar to that for the less powerful 5× lens; however, line roughness was measured along 10 lines: five in each direction ( Fig. 8 ).
PPT Slide
Lager Image
CLSM images showing the central areas of each sample at 5× (left) and 50× (right) magnification.
PPT Slide
Lager Image
Line roughness analysis and analysis parameters (see Fig. 9 and also the text for explanation) in the CLSM system.
PPT Slide
Lager Image
The 18 lines for measuring line roughness superimposed on a 5× image (left) and the 10 lines used at 50× magnification (right).
- Roughness factors of line and surface
The following parameters are considered in the surface evaluation. Rzjis (ten-point mean roughness) is the sum of the average height of the five highest points and the average depth of the five lowest points using the average line edge as a standard ( Fig. 9 a). Rsk (skewness of the roughness profile) indicates the upward or downward deflection of the amplitude distribution curve. The value is positive when the deflection is upwards and negative when down-wards ( Fig. 9 b). Rzn is the sum of the highest point and lowest point between the standard length and the average line when the evaluation curve is divided by the standard length; Rz (maximum height of the roughness profile) is the average value of Rzn ( Fig. 9 c). Rpi is the value of the highest point between the standard length and average line when the evaluation curve is divided by the standard length; Rp (maximum profile peak height of the roughness profile) is the average value of Rpi ( Fig. 9 d). Rƒq (root mean square slope of the roughness profile) is the average square root of the squared values of dZ/dX , which is the local gradient of the evaluation curve ( Fig. 9 e). Rvi is the length between the standard length and the lowest point from the average line after dividing the evaluation curve in standard length intervals; Rv (maximum profile valley depth of the roughness profile) is the average of Rvi ( Fig. 9 f). Rt (total height of the roughness profile) is sum of the maximum value of the profile peak heights and the maximum value of profile valley depth on the profile curve ( Fig. 9 g). Ra (arithmetical mean deviation of the roughness profile) is the average of all the Yi values, which denote the deviation between the average line and the evaluation curve ( Fig. 9 h). Rc (mean height of the roughness profile elements) is the average of all the heights of all profile elements ( Zti ) ( Fig. 9 i). Parts protruding above the average line are called profile element mountains; conversely, dips below the average line are call profile element valleys. A continuous mountain and valley is called a profile element pair. Finally, Rq (root mean square deviation of the roughness profile) is the average square root of the squared values of Yi ( Fig. 9 j).
PPT Slide
Lager Image
Parameters for measuring line roughness.
The parameters SMr 1 ( the load area ratio that separates the protruding peak from the core section ), Sz (maximum height) , Spk (height of protruding peak) , Sv (maximum valley depth) , Sa (arithmetic mean height) , and Svk (height of protruding valley) ] quantitatively describe surface roughness ( Fig. 10 ). First, when a random value is set based on an Rt value of 100% for a line segment parallel to the average line. The equivalent straight line is the straight line at which the secant line of the load curve, calculated for the center of the load curve that includes 40% of the measurement points in the roughness curve, such that the load length ratio difference mr is 40%, has the smallest gradient. The area between the two height positions where this straight line intersects with the ordinate at the 0% and 100% positions in the core section. The point I is where the load curve itself meets the y -axis. The point J on the y -axis is chosen so that the triangle CHJ and the shape made by straight lines CH and CI and the curve HI are of equal area. Spk is the length of line CJ. that the height of the right-angled triangle which is constructed to have the same area as the protruding peak area above the core section. Projecting the depth value of point D back to the load curve gives point E, whose mr value is defined as mr 2 . F is the point on the load curve where it meets the line mr = 100, and G is a point on the line mr = 100 chosen so that the triangle DEG and the shape made by the lines DE and DF and the curve EF are of equal area. Svk is the length of line DG.
PPT Slide
Lager Image
Roughness parameters SMr1, Spk, Svk.
Result and discussion
- 5× Observations
The three-dimensional surface images created by CLSM revealed a large change in the surface height after 200 freeze/thaw cycles ( Fig. 11 ). These variations were quantified by calculating the various roughness parameters from scans using the 5× lens.
PPT Slide
Lager Image
Three-dimensional images of the sample surface after 0 cycles (top) and 200 cycles (bottom).
Line roughness was measured after each 20 freeze/thaw cycles along 18 lines on each sample. The general changes in line edge roughness during freeze/thaw cycling are represented by the average of the 18 measured line roughness factor values. The results for all three samples showed steady variations during cycling of the line roughness factors Rzjis ( ten-point mean roughness ), Rsk ( skewness of roughness profile ), Rz ( maximum height roughness ), and Rp ( maximum peak height of roughness profile ). Plots of the average line roughness factors of the three differently pressurized samples are given in Fig. 12 .
PPT Slide
Lager Image
Progression of line roughness parameters during freeze/thaw cycling: (a) Rzjis, (b) Rz, (c) Rp, and (d) Rsk.
Each line roughness factor increased during freezing/thawing: Rzjis increased by ~0.3 µm, Rz by ~0.24 µm, Rp by ~0.29 µm, and Rsk by ~0.27. The increases in Rzjis and Rz indicate that the length between the highest and lowest points of the surface had increased, and the increase in Rp shows that the surface height had increased. Overall, weathering caused the surface to roughen by increasing the height of the highest parts rather than by deepening the lowest parts. This is also shown by the increase in Rsk . The positive asymmetry value shows that the amplitude deflected in the upward direction rather than downward.
CLSM at 5× magnification measured a 2580 × 2580 µm 2 area. Fig. 13 shows the steady variation in the surface roughness factor SMr 1 ( the load area ratio that separates the protruding peak from the core section ) of all three samples under different pressures as the freezing/thawing proceeded. The figure shows SM r1 increased by 0.33% during freezing/thawing. Similar to the results of line edge roughness, the top point of the surface roughness also increased in height.
PPT Slide
Lager Image
Progression of the surface roughness factor SMr1 during freeze/thaw cycling.
- 50× Observations
Line roughness and surface roughness CLSM measurements using the 50× lens were conducted similarly to those with the 5× lens; however, each sample had 10 line edge roughness measurements taken after every 20 cycles up to 200 cycles. The average of all 10 measurements can represent general trends in the line roughness during cycling.
The three samples under different pressures showed steady variations in their roughness factors as freezing/thawing proceeded: the 10 factors were Rzjis (ten-point mean roughness), RΔq (root mean square gradient of roughness profile), Rsk (skewness of roughness profile), Rt (maximum primary height of roughness profile), Rc (mean height of roughness profile element), Rz (maximum height roughness), Rv (maximum valley depth of roughness profile), Rp (maximum peak height of roughness profile), and Ra (arithmetical mean deviation), and Rq (root mean square roughness). Of these factors, RΔq , Rt , and Rv showed behaviors that depended on the pressure applied to the sample (50, 55, or 70 MPa). Fig. 14 shows the average line roughness factors of the three samples during cycling, and Fig. 15 shows the line roughness factors for each pressure.
PPT Slide
Lager Image
Progression of averaged line roughness factors during freezing/thawing: (a) Rzjis, (b) Rsk, (c) Rc, (d) Rz, (e) Rp, (f) Rq, and (g) Ra.
PPT Slide
Lager Image
Progression of line roughness factors during freezing/thawing for samples under different pressures: (a) RΔq, (b) Rt, and (c) Rv.
All of the line roughness factors increased during freezing/thawing: Rzjis increased by ~0.08 µm, the absolute value of Rsk by ~0.37, Rc by ~0.16 µm, Rz by ~0.26 µm, Rp by ~0.09 µm, Rq by ~0.05 µm, and Ra by ~0.04 µm. RΔq increased by 0.32 µm in the sample pressurized to 50 MPa, by 0.36 µm in the sample at 55 MPa, and 3.7 µm at 70 µm. Rt increased by 0.15 µm in the sample at 50 MPa, 0.36 µm at 55 MPa, and 0.61 µm at 70 MPa. Rv increased by 0.05 µm at 50 MPa, 0.10 µm at 55 MPa, and 0.36 µm at 70 MPa. The increases in Rzjis , Rz , and Rc indicate the increased length between the highest and lowest points on the sample surface. The increase in Rp indicates that the surface height had increased. Likewise, the increases in Ra and Rq indicate the increased deviation value between the evaluation curve and the average line. In other words, freezing/thawing roughened the sample urface and heightened its top part rather than decreasing its lowest part. The initially positive value of Rsk became negative after 80 cycles, and its magnitude increased. This shows that the amplitude deflected in the downward direction rather than upward for surface roughness.
A 258 × 258 µm area was measured by CLSM using the 50× lens to characterize the surface roughness of the samples, showing a steady variation during cycling in the surface roughness factors Sz (maximum height; Sp + Sv ), Spk (reduced peak height), and Sv (maximum pit depth) for all three pressures. SMr 1 , Sa , and Svk varied steadily according to the applied pressure. Surface roughness factors averaged across the three samples and for each sample at different pressure are given in Fig. 16 and Fig. 17 , respectively.
PPT Slide
Lager Image
Progression of surface roughness factors during freezing/thawing: (a) Sz, (b) Spk, and (c) Sv.
PPT Slide
Lager Image
Progression of surface roughness factors during freezing/thawing for samples under different pressures: (a) SMr1, (b) Sa, and (c) Svk.
Each surface roughness factor increased during freezing/ thawing, with Sz increasing by ~1.80 µm, Spk by ~0.03 µm, and Sv by ~1.68 µm. SMr 1 increased by ~0.5% in the sample pressurized at 50 MPa, by ~2.11% at 55 MPa, and ~3.21% at 70 MPa. Sa increased by ~0.001 µm in the sample pressurized at 50 MPa, ~0.006 µm at 55 MPa, and 0.02 µm at 70 MPa. Svk increased by ~0.01, ~0.03, and ~0.08 µm in the samples pressurized at 50, 55, and 70 MPa, respectively. The increase in Sz indicates that the difference between the maximum surface height and maximum surface depth increased during cycling, and thus the surface became increasingly roughened. The increase in Spk indicates that the highest point of the sample surface increased relative to the average height. The increase in Sv indicates that the depth of the sample surface deepened during cycling. The increase in SMr 1 indicates that the highest point of the sample surface increased in height during cycling, as also shown by Spk . The increase in Sa indicates an increase in the difference between the average value and the height and depth of the surface, as also shown by Sz . The increase in Svk indicates that the depth of the sample surface deepened relative to the average height.
Conclusion
Minute surface variations in rock samples were observed by CLSM during their simulated weathering by freeze/thaw cycles at high pressure. Samples were sealed with water in a pressure frame and pressurized before being repeatedly frozen and thawed in cycles controlled by a thermostat. Samples were pressurized at different pressures: their surface roughness variations were observed at 50, 55, and 70 MPa. Each 6 h cycle of the temperature program involved heating from -20℃ to 40℃ and cooling back to -20℃. After 20 cycles, the line edge roughness and surface roughness were measured by CLSM using 5× and 50× lenses.
The simulated weathering of the rock samples affected their roughness. Observation at the higher-magnification 50× lens rather than the 5× lens revealed clear trends in the roughness factors during cycling, as this lens allowed analysis in a small area. We suggest that the surface colors and minute level differences that is fixed onto a pressure frame can make different result when roughness is measured by laser reflection (Bae and Lee, 2002) . And specimens be observed along with more minerals than can be seen at higher magnification. Observations with the 5× lens revealed that the line roughness factors Rzjis , Rsk , Rz , and Rp and the surface roughness factor SMr 1 showed similar tendencies during freezing/thawing. Observations with the 50× lens revealed that the line roughness factors Rzjis , RΔq , Rsk , Rt , Rc , Rz , Rv , Rp , Ra , and Rq , and the surface roughness factors Sz , Spk , Sv , Smr 1 , Sa , and Svk all increased during freezing/thawing, indicating that the vertical displacement also increased, and thus that the rock surface was weathered.
These observations of the changing roughness of rock surfaces during high-pressure freezing/thawing allow a physical analysis of rock weathering. The CLSM observations record the creation and growth of microcracks on the surfaces, and are potentially useful in fields such as the construction of underground facilities and the disposal of high-level radioactive waste. This test considered granite from a certain depth, but we plan to compare rocks of a similar type from different depths and also different rock types to observe experimentally various physical weathering phenomena.
Acknowledgements
This research was supported by the Basic Research Project (Technology Development of Landslide Rapid Detection Based on a Real-Time Monitoring) of the Korea Institute of Geoscience and Mineral Resources (KIGAM), funded by the Ministry of Science, ICT and Future Planning of Korea.
BIO
Hye-jin Kim
Geologic Environment Division, Korea Institute of
Geoscience and Mineral Resources
124 Gwahak-ro, Yuseong-gu, Daejeon 305-350,
Korea
Tel: 042-868-3944
E-mail: hjkim_91@knu.ac.kr
Junghae Choi
Geologic Environment Division, Korea Institute of
Geoscience and Mineral Resources
124 Gwahak-ro, Yuseong-gu, Daejeon 305-350,
Korea
Tel: 042-868-3944
E-mail: jhchoi@kigam.re.kr
Byung-gon Chae
Geologic Environment Division, Korea Institute of
Geoscience and Mineral Resources
124 Gwahak-ro, Yuseong-gu, Daejeon 305-350,
Korea
Tel: 042-868-3052
E-mail: bgchae@kigam.re.kr
Gyo-won Kim
College of Natural Science, Kyungpook National
University
1370 Sankyuk-dong, Buk-gu, Daegu 702-701, Korea
Tel: 053-950-5357
E-mail: gyokim@knu.ac.kr
References
Bae K. Y. , Lee C. I. 2002 Development of a 3D roughness measurement system of rock joint using laser type displacement meter Korean Society for Rock Mechanics (in Korean with English abstract) 12 (4) 268 - 276
Baek H. J. 1997 Characteristics of natural and experimental fracture propagation in rocks The Journal of Engineering Geology (in Korean with English abstract) 7 (1) 53 - 62
Brotons V. , Tomás R. , Ivorra S. , Grediaga A. 2014 Relationship between static and dynamic elastic modulus of calcarenite heated at different temperatures: the San Julián’s stone Bulletin of Engineering Geology and the Environment 73 (3) 791 - 800    DOI : 10.1007/s10064-014-0583-y
Chen T. C. , Yeung M. R. , Mori N. 2004 Effect of water saturation on deterioration of welded tuff due to freeze–thaw action Cold Regions Science and Technology 38 (2-3) 127 - 136    DOI : 10.1016/j.coldregions.2003.10.001
Haeri H. , Shahriar K. , Marji M. F. , Moarefvand P. 2014 Experimental and numerical study of crack propagation and coalescence in pre-cracked rock-like disks International Journal of Rock Mechanics & Mining Sciences 67 20 - 28    DOI : 10.1016/j.ijrmms.2014.01.008
Hong S. I. , Shin H. B. , Kim D. M. , Kim H. S. 2011 Structural behavior evaluation according to roughness of discontinuum surface of stone pagoda Architectural Institute of Korea (in Korean with English abstract). 27 (10) 63 - 70
Horii H. , Nemat-Nasser S. 1986 Brittle failure in compression: splitting, faulting and brittle-ductile transition International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 25 (3) 337 - 374
Jang H. S. , Jang B. A. , Lee J. S. 2004 Variations of engineering geological characteristics of the cretaceous shale from the pungam sedimentary basin in Kangwon-do due to freezing-thawing The Journal of Engineering Geology (in Korean with English abstract) 14 (4) 401 - 416
Kim D. B. , Son B. K. , Lee C. I. 2001 A numerical study of the shear behavior of a rock joint considering quantitative roughness parameters Korean Geotechnical Society (in Korean) 17 (4) 279 - 288
Kim J. T. , Jeong G. C. , Kim M. I. , Song J. Y. , Park C. K. 2004 Characterization of fracture roughness in coarse·medium·fine grained granite The Journal of Engineering Geology (in Korean with English abstract) 14 (2) 147 - 168
Korea Institute of Geoscience and Mineral Resources (KIGAM) 2013 Technical report of development of quantitative assessment technology for long-term geo- logical safety factors KIGAM TR-12-6 1 - 39
Kwag J. Y. , Lee S. E. , Lim H. U. 2003 Anisotropic shear strength of artificially fractured rock joints under low normal stress Journal of Korean Society for Rock Mechanics (in Korean with English abstract) 13 (3) 169 - 179
Labuz J. F. , Shah S. P. , Dowding C. H. 1985 Experimental analysis of crack propagation in granite International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 22 (2) 85 - 98    DOI : 10.1016/0148-9062(85)92330-7
Lee M. H. , Kim J. W. , Chang K. T. 2007 The influence of rock joint roughness and normal stress on shear behavior Korean Society for Rock Mechanics (in Korean with English abstract) 17 (3) 186 - 196
Lee S. D. , Kang J. H. , Lee C. I. 1994 Shear strength and deformation behavior of rock joint with roughness Korean Society for Rock Mechanics (in Korean with English abstract) 4 261 - 273
Lee S. M. , Kim H. S. , Na G. C. 1980 1/50,000 Daejeon map and geologic map guide Korea Institute of Geoscience and Mineral Resources 26 -
Leichnitz W. 1985 Mechanical properties of rock joints International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 22 (5) 313 - 321    DOI : 10.1016/0148-9062(85)92063-7
Lu W. , Chakravarthula S. S. , Chen J. , Qiao Y. 2012 Propagation of a cleavage crack front across a field of persistent grain boundaries International Journal of Solids and Structures 49 (3-4) 584 - 589    DOI : 10.1016/j.ijsolstr.2011.11.003
McGreevy J. P. , Whalley W. B. 1985 Rock moisture content and frost weathering under natural and experimental conditions: a comparative discussion Artic and Alpine Research 17 (3) 337 - 346    DOI : 10.2307/1551022
Nicolson D. T. , Nicholson F. H. 2000 Physical deterioration of sedimentary rocks subjected to experimental freeze-thaw weathering Earth Surface Processes and Landforms 25 (12) 1295 - 1307
Park C. H. , Bobet A. 2010 Crack initiation, propagation and coalescence from frictional flaws in uniaxial compression Engineering Fracture Mechanics 77 (14) 2727 - 2748    DOI : 10.1016/j.engfracmech.2010.06.027
Park H. I. , Lee J. D. , Jeong J. G. 1977 1/50,000 Yuseong map and geologic map guide Korea Institute of Geoscience and Mineral Resources 21 -
Reyes O. , Einstein H. H. 1991 Failure mechanisms of fractured rock - A fracture coalescence model International Society for Rock Mechanics 66 333 - 340
Shen B. 1995 The mechanism of fracture coalescence in compression-experimental study and numerical simulation Engineering Fracture Mechanics 51 (1) 73 - 85    DOI : 10.1016/0013-7944(94)00201-R
Um J. G. , Shin M. K. 2009 Variations of physicomechanical properties of the cretaceous mudstone in Haman, Gyeongnam due to freeze-thaw weathering Tunnel & Underground Space (Journal of Korean Society for Rock Mechanics) (in Korean with English abstract) 19 (2) 146 - 157
Um J. G. , Woo I. , Park H. J. 2014 Engineering Geological Characteristics of Freeze-Thaw Weathered Gneiss in the Wonju Area, Korea The Journal of Engineering Geology 24 (2) 161 - 169    DOI : 10.9720/kseg.2014.2.161
Yavuz H. , Altindag R. , Sarac S. , Ugur I. , Sengun N. 2006 Estimating the index properties of deteriorated carbonate rocks due to freeze-thaw and thermal shock weathering International Journal of Rock Mechanics and Mining Sciences 43 (5) 767 - 775    DOI : 10.1016/j.ijrmms.2005.12.004