Fereidooni D., Postgraduate Student of Engineering Geology, Bu-Ali Sina University,. Hamedan, Iran. Abstract. Humanity and costs damages due to the failure of ...
32nd International Geological Symposium, August 2003, Florence Italy
Application of Modified Q Classification System for Rock Slope Stability Analysis Purposes
Khanlari G. R., Ass. Prof. of Engineering Geology, Bu-Ali Sina University, Hamedan, Iran. Fereidooni D., Postgraduate Student of Engineering Geology, Bu-Ali Sina University, Hamedan, Iran.
Abstract Humanity and costs damages due to the failure of the rock slope failures along to the roads, highways, railways, urban area and industrials areas are geological hazards and will disturbed buildings, roads, cars and other things when they undergo failure. These shows the importance of the engineering geology and rock mechanics studies when engineering constructions are performed. For this reason the rock masses along the Ganjnameh-Shahrestaneh road are not excepted from this total law. Due to the high potential application of Q system for evaluation of the quality of rock masses, in this research work it was used accompany with the RMR and RQD rock mass classification systems. These three rock mass classification systems were employed for assessment of the quality and potential of failure in different types of rocks in the study area. A new rock mass classification namely Slope Quality Rating (SQR) was proposed based on the former Q Parameters and accounting new parameters such as dip and strike of the layers and the method of drilling. For this purpose, the Q and RMR rock mass classifications should be used. It should be noted that by measuring of SQR it will be possible to measure Slope Mass Rating (SMR) for the rock masses.
1. Introduction For the rock slope stability analysis in roads, highways and open pit mines, application of the rock mass classifications system is useful. Based on the Bieniawaski (1984) [1,4] and Hoek (1974) [9] the main aims of the rock mass classification systems is dividing a particular rock masses into groups of similar behavior and also to provide a basis for understanding the
32nd International Geological Symposium, August 2003, Florence Italy
characteristics of each group so that to yield quantitative data for engineering purposes, and at least to provide a common basis for communications between the Scientifics. Generally the study of rock mass classification will be done before the performing engineering constructions. In this paper, the rock masses of this area have been studied based on the Q rock mass classification system. Figure 1 shows the location of the study area in Iran map.
Figure 1- Location of the study area
Although, several rock mass classification have been done by many researchers but, some of them needed to be modified in order to improve their applications. For this reason, the Q system was modified. In addition,
32nd International Geological Symposium, August 2003, Florence Italy
based on the data analysis from the seven zone chosen in the study area, a new rock mass classification system (SQR) [5] was proposes. The physical and lithological properties of the seven zones have been illustrated in Table 1. Table 1- Physical and lithological properties of the study station Station No.
Lithology type
Slope height (m)
Slope face angle (deg.)
Unite weight (gr/cm3)
1
Diorite
15
71
2.925
2
Hololocogranite
11
61
2.657
3
Hornfels
10
75
2.802
4
Hololocogranite
18
67
2.657
5
Hornfels
17
65
2.762
6
Hornfels
10
49
2.695
7
Hornfels
11
72
2.680
2. The potential of Q system and its comparison with the RMR system With a little bit accuracy in the results of the Q and RMR systems, it will be distinguished that the results of the RMR system is derived from the effects of five parameters, whereas the result of the Q system is derived from the participation of six parameters [5]. So, the number of the parameters participated in the Q system is more than the RMR system. The RMR parameters includes, uniaxial compressive strength ( c ), rock quality designation (RQD), spacing of the joint sets, discontinuities conditions, and ground water condition. In the Q system, in addition to the above parameters, some new parameters such as Jn (factor of joint sets number), Jr (factor related to the joint roughness), Ja (factor related to the joint alteration), and SRF (Stress Reduction Factor) are contributed. As a result, it is possible to say that the Q system can have a good quantitative description of rock mass quality [5].
32nd International Geological Symposium, August 2003, Florence Italy
One of the most important problems in stability of rock slopes is shear strength of discontinuities and joint surfaces which are affected by the block size and the roughness of discontinuities [9]. In additional to the above parameters, weathering of the discontinuity surfaces will have a negative effect on the shear strength of rock masses. Another factor which has negative effect on the shear strength of rock masses is the presence of the water on the discontinuities, that will increased the pore pressure and reduced the shear strength [4]. These conditions will leads to the instability of rock masses. With the study of Q system, results shows that the factor of RQD/J n clearly indicate the effect of block size on the instability of the rock masses. Other parameters such as Jr, Ja, Jw and SRF have very important roles in the behavior of the rock masses. These are shows, the high potential of the Q system in comparison with the RMR system. 3. Relationship between RMR and Q systems In an overall view, the results of both RMR and Q rock mass classification systems in the study area and particularly in the seven selected zones, shows that the rock masses in the study area placed within the good rock class [2,3,4]. Results from the rock mass classifications are showed in Table 2. In this table a quality description of rock mass is provided. For making a correlation between RMR and Q system, the Q and RMR values related to the seven zones have been plotted in Figure 2.
Table 2 - Results of the rock mass classifications in the study area Station No.
RMR values
RMR descriptions
Q values
Q descriptions
1
70.3
Good
10.4
Good
2
76.7
Good
12.1
Good
3
61.8
Good
5.8
Moderately Good
4
72.9
Good
5.9
Moderately Good
32nd International Geological Symposium, August 2003, Florence Italy 5
68.9
Good
12.8
6
66.3
Good
10.2
7
Good
68.4
Good
7.9
Moderately Good
Good
Relationship between RMR and Q 100
RMR
90
y = 11.795Ln(x) + 42.888 R2 = 0.4567
80 70 60 50 5
7
9
11
13
15
Q
Figure 2 - Relationship between RMR and Q systems for the rock masses in the study area
According to the Figure 1, it can be concluded that their relationship will be as follow: RMR = 12 Ln Q + 43 (1) Similar equations such as equation 1 have been proposed by many researchers (Bieniawski, Singh, Hoek and etc.). Due to the low corresponding correlation coefficient for these equations, the confidence of the equation is not sufficient [9]. Nearly, the some equation is proposed by Bieniawski [9]: RMR = 9 Ln Q + 44 4. Modification of Q system for rock slope stability analysis
32nd International Geological Symposium, August 2003, Florence Italy
Rock Mass Rating system (RMR) was modified in 1985 by Romana [9] for using rock slope stability analysis. Romana (1985) proposed some new factors such as discontinuity orientations, pattern of discontinuities and the methods of blasting for RMR system. He proposed Slope Mass Rating (SMR) which is measured from the following equation [6,8]: SMR = RMRbasic – [F1. F2. F3] + F4
(2)
Where: SMR: Slope Mass Rating RMRbasic: Rock Mass Rating F1: Difference between slope face and critical discontinuity strikes F2: Discontinuity dip angle F3: Relationship (difference) between the slope face and dip of the discontinuity F4: Method of excavation In this research, above parameters were used for modification of Q system. Because of some difficulties derived from using of Q system [9] (it was proposed by N. Barton for underground mining and tunneling), now it is using for rock slope stability and open pit mining in some cases. Due to the differences between the stress condition in depth and surface of the rock masses, a distinguish between these two conditions is necessary. For this reason it seems that it is necessary to do some varieties in the amount of SRF parameter. Ajoodani [1] proposed that we can used ( JCS / h ) factor of SRF in order to naturalized the effect of stress differences in difference conditions (depth and surface of the rock masses), such as if; JCS / H < 160 SRF = 0.35
32nd International Geological Symposium, August 2003, Florence Italy
JCS / H 160 SRF = 0.11
Where: JCS: Joint Compressive Strength (MPa)
: Unit weight of rock (gr/cm3) H: Height of sliding (m) Based on this condition, the amount of SRF for the study area was choosed 0.11 and therefore the amount of Q was corrected for the slope stability application. Details of modified Q (Qm), RMR, JCS, SRF and other parameters are illustrated in Table 3. Table 3 - Values of different parameters for calculation of Qm Station
JCS
Qm
2.925
883.8
235.5
11
2.657
1060.3
0.11 0.11
10
2.802
936.6
0.11
131.3
18
2.657
600.7
0.11
201.7
17
2.762
528.0
0.11
289.8
10
2.695
908.3
0.11
231.6
11
2.680
617.4
0.11
180.6
1
70.3
10.4
329.7
15
2
76.7
12.1
304.02
3
61.8
5.8
264.9
4
72.9
5.9
281.8
5
68.9
12.8
243.2
6
66.3
10.2
240.1
7
68.4
7.9
178.6
(MPa)
c
SRF
Q
No.
γ
1
RMR
H (m)
(gr/cm3)
(modified)
274.5
The amounts of RMR and modified Q (Qm), is illustrated in Figure 3.
32nd International Geological Symposium, August 2003, Florence Italy
Relationship between RMR and Q m 80 y = 11.793 Ln(x) + 6.0551 R2 = 0.4566
75 RMR 70 65 60 100
150
200
250
300
Qm
Figure 3 - Relationship between RMR and Qm for the rock masses in the study area
According to the Figure 2, the relationship between two parameters are as follows: RMR = 11.793 Ln Qm + 6.055
(3)
5. Calculation of SQR With mixing equations 2, and 3 it is possible to achieve the amount of SQR base on the below equations: SMR = 11.793 Ln Qm + 6.055 + (F1. F2. |F3| + F4)
F .F . | F | F4 SMR = 11.793 Ln Qm + 6.055 + 11.793 1 2 3 11.793 SMR (4)
=
11.793
F .F . | F | F4 Ln Qm exp 1 2 3 6.055 11.793
32nd International Geological Symposium, August 2003, Florence Italy
As it is clear from equation 4, the amount within [ ] is rating of SMR for the rock masses from the study area which can be calculated from the equation 5. F .F . | F | F4 SQR = Qm .exp 1 2 3 11.793
(5)
As a result, the relationship between SMR and SQR will be as follows. SMR = 11.793 Ln SQR + 6.055 Based on the table proposed by Romana (1985) [5,9], for calculation of F1, F2, F3 and F4 for the rock masses of the study area, their amounts are illustrated in Table 4. Table 4 - SQR value for rock masses in the study area Station No.
Qm
F1
F2
|F3|
F4
SQR
1
235.5
0.15
1
50
0
444.8
2
274.5
0.15
1
50
0
518.6
3
131.3
0.15
1
25
0
180.5
4
201.7
0.15
1
25
0
277.2
5
289.8
0.15
1
6
0
312.8
6
231.6
0.15
1
6
0
250.0
7
180.6
0.15
1
60
0
387.4
6. Conclusions with the performing RMR, SMR and SQR rock mass classification systems and based on Table 3 the achieved results are as follows: 1- Calculated amounts of RMR in seven stations shows that the minimum amount of RMR (61.8) is related to the station 3 and the maximum
32nd International Geological Symposium, August 2003, Florence Italy
amount of RMR (76.7) is related to the station 2. The average amount of RMR will be 69.4 which shows that the rock mass quality is high quality (Class II). 2- Measured SMR for seven stations, shows that the minimum amount of SMR (65.6) is related to station 3 and the maximum amount of SMR (84.2) is related to the station 2. As a result, average amount of SMR will be 74.110 that shows a good quality of rock mass and also a stable condition in these stations(Class II). 3- Calculated amounts of Q for seven stations shows that the minimum amount (5.8) is related to the station 3 and the maximum amount (12.8) is related to the stations 5. As a result an average of Q is 9.6. Results shows that the quality of the rock masses in this station are fair and good rock respectively. 4- Measured SQR for seven stations, shows that the minimum amount of SQR (180.5) is related to the station 3 and the maximum amount of SQR (518.6) is related to the station 2. Results show that the quality of the rock masses are good in this area. 5- Results of SQR shows that the SQR has a good correlation with the SMR that proposed by Romana 1985. 7. References 1- Ajoodani namin, Sh., Proposed a few Method for Rock slope stability Analysis with Modification of Q system, MSc Thesis, Tarbiat Modarres University, 1999. 2- Khanlari, Gh., Engineering Geology (for civil Engineering students). Bu-Ali Sina University pub., second Edition 2001, p. 364. 3- Khanlari, Gh., Heidari, M., and Fereidouni, D., Application of RMR and SMR Rock Mass Classification Systems in Order to Classification of Rock Masses in Margin of the Ganjnameh-Shahrestaneh Road, Proceedings of Third Iranian Engineering Geology and the Environment Conference, 2003, Pp. 477-484.
32nd International Geological Symposium, August 2003, Florence Italy 4-
5-
67-
8-
Fahimifar, A., (Translator), Underground Excavation in Rock, Engineering and Soil Mechanics Laboratory Publication, Ministry of Road and Transportation, Iran, 1997, p. 589. Fereidouni, D., Slope Stability Assessment in the GanjnamehShahrestaneh Road, MSc Thesis, Bu-Ali Sina University, 2004, p. 241. Hoek, E., Rock Engineering, http://rockeng.utoronto.ca/rok/Hoek/Hoeknote2000.htm, 2000, p.313. Norbert, H. Maerz, Highway Rock Cut Stability Assessment in Rock Masses Not Conductive to Stability Calculations, Proceedings of the 51st Annual Highway Geology Symposium, Seattle, Washington, Aug. 29 – Sep. 1, 2000, Pp. 249-259. Osanloo, M., Application of RMR and SMR Rock Mass Classification Systems in Order to Optimization of Rock Slopes in Open Pit Mines, Journal of Mining and Metallurgy Survey of Iran, 1999, Pp. 46-51.
9- Singh B. Goel R.K., Rock Mass Classification (A Practical Approach for Civil Engineering), Elsevier Ltd.
32nd International Geological Symposium, August 2003, Florence Italy
