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Rock Mechanics and Rock Engineering

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01-05-2010 | Original Paper

Application of Fuzzy Set Theory to Rock Engineering Classification Systems: An Illustration of the Rock Mass Excavability Index

Authors: Jafar Khademi Hamidi, Kourosh Shahriar, Bahram Rezai, Hadi Bejari

Published in: Rock Mechanics and Rock Engineering | Issue 3/2010

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Abstract

The characterization of rock masses is one of the integral aspects of rock engineering. Over the years, many classification systems have been developed for characterization and design purposes in mining and civil engineering practices. However, the strength and weak points of such rating-based classifications have always been questionable. Such classification systems assign quantifiable values to predefined classified geotechnical parameters of rock mass. This results in subjective uncertainties, leading to the misuse of such classifications in practical applications. Fuzzy set theory is an effective tool to overcome such uncertainties by using membership functions and an inference system. This study illustrates the potential application of fuzzy set theory in assisting engineers in the rock engineering decision processes for which subjectivity plays an important role. So, the basic principles of fuzzy set theory are described and then it was applied to rock mass excavability (RME) classification to verify the applicability of fuzzy rock engineering classifications. It was concluded that fuzzy set theory has an acceptable reliability to be employed for all rock engineering classification systems.

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Acaroglu O, Ozdemir L, Asbury B (2008) A fuzzy logic model to predict specific energy requirement for TBM performance prediction. Tunn Undergr Space Technol 23:600–608CrossRef

Alvarez Grima M (2000) Neuro-fuzzy modelling in engineering geology. A.A. Balkema, Rotterdam, 244 pp

Alvarez Grima M, Babuska R (1999) Fuzzy model for the prediction of unconfined compressive strength of rock samples. Int J Rock Mech Min Sci 36:339–349CrossRef

Alvarez Grima M, Verhoef PNW (1999) Forecasting rock trencher performance using fuzzy logic. Int J Rock Mech Min Sci 36(4):413–432CrossRef

Alvarez Grima M, Bruines PA, Verhoef PNW (2000) Modeling tunnel boring machine performance by neuro-fuzzy methods. Tunn Undergr Space Technol 15(3):259–269CrossRef

Aydin A (2004) Fuzzy set approaches to classification of rock masses. Eng Geol 74:227–245CrossRef

Barton N, Lien R, Lunde J (1974) Engineering classification of rock masses for the design of tunnel support. Rock Mech 6:189–236CrossRef

Bellman RE, Zadeh LA (1970) Decision-making in a fuzzy environment. Manag Sci 17(4):141–164CrossRef

Bieniawski ZT (1973) Engineering classification of jointed rock masses. Trans S Afr Inst Civil Engrs 15:335–344

Bieniawski ZT (1974) Geomechanics classification of rock masses and its application in tunneling. In: Proceedings of the 3rd International Congress on Rock Mechanics, ISRM, Denver, Colorado, September 1974, pp 27–32

Bieniawski ZT (1976) Rock mass classifications in rock engineering. In: Proceedings of the Symposium on Exploration for Rock Engineering, Johannesburg, November 1976, pp 97–106

Bieniawski ZT (1979) The geomechanics classification in rock engineering applications. In: Proceedings of the 4th International Congress on Rock Mechanics, vol 2, ISRM, Montreux, Switzerland, September 1979, pp 41–48

Bieniawski ZT (1989) Engineering rock mass classifications. Wiley, New York, p 251

Bieniawski ZT (2007) Predicting TBM excavability. Tunnels Tunnel Int 32–35

Bieniawski ZT, Barton N (2007) RMR and Q-setting records. Tunn Tunn Int 26–29

Bieniawski ZT, Tamames BC, Fernandez JMG, Hernandez MA (2006) Rock mass excavability (RME) indicator: new way to selecting the optimum tunnel construction method. In: ITA-AITES World Tunnel Congress and 32nd ITA General Assembly, Seoul, Korea, April 2006

Bieniawski ZT, Celada B, Galera JM (2007) TBM excavability: prediction and machine–rock interaction. In: Proceedings of the Rapid Excavation and Tunneling Conference (RETC), Toronto, Canada, June 2007, pp 1118–1130

Brekke TL, Howard TR (1972) Stability problems caused by seams and faults. In: Proceedings of the Rapid Excavation and Tunneling Conference (RETC), pp 25–41

Chen C, Liu Y (2007) A methodology for evaluation and classification of rock mass quality on tunnel engineering. Tunn Undergr Space Technol 22:377–387CrossRef

Deere DU (1968) Geological considerations. In: Stagg RG, Zienkiewicz DC (eds) Rock mechanics in engineering practice. Wiley, New York, pp 1–20

Deere DU (1989) Rock quality designation (RQD) after 20 years. US Army Corps Engrs contract report GL-89-1. Waterways Experimental Station, Vicksburg, p 67

Deere DU, Hendron AJ, Patton FD, Cording EJ (1967) Design of surface and near surface construction in rock. In: Proceedings of the 8th US Symposium on Rock Mechanics, AIME, New York, pp 237–302

Deketh HJR, Alvarez Grima M, Hergarden IM, Giezen M, Verhoef PNW (1998) Towards the prediction of rock excavation machine performance. Bull Eng Geol Environ 57:3–15CrossRef

Den Hartog MH, Babuska R, Deketh HJR, Alvarez Grima M, Verhoef PNW, Verbruggen HB (1997) Knowledge-based fuzzy model for performance prediction of a rock-cutting trencher. Int J Approx Reason 16(1):43–66CrossRef

Finol J, Guo YK, Jing XD (2001) A rule based fuzzy model for the prediction of petrophysical rock parameters. J Pet Sci Eng 29:97–113CrossRef

Franklin JA, Broch E, Walton G (1971) Logging the mechanical character of rock. Trans Inst Min Metall 80:1–9

Ghose AK, Dutta D (1987) A rock mass classification model for caving roofs. Int J Min Geol Eng 5:257–271CrossRef

Gokay MK (1998) Fuzzy logic usage in rock mass classifications. J Chamb Min Eng Turk 37(4):3–11 (in Turkish)

Gokceoglu C (2002) A fuzzy triangular chart to predict the uniaxial compressive strength of the Ankara agglomerates from their petrographic composition. Eng Geol 66:39–51CrossRef

Gokceoglu C, Zorlu K (2004) A fuzzy model to predict the uniaxial compressive strength and the modulus of elasticity of a problematic rock. Eng Appl Artif Intell 17:61–72CrossRef

Goktan RM, Eskikaya S (1991) Prediction of ripping machine performance in terms of rock mass properties. Civil Eng S Afr 31(1):13–24

Goodman RE (1995) Block theory and its application. Geotechnique 45(3):383–423CrossRef

Habibagahi G, Katebi S (1996) Rock mass classification using fuzzy sets. Iran J Sci Technol 20(3):273–284

Hoek E, Brown ET (1997) Practical estimates of rock mass strength. Int J Rock Mech Min Sci 34(8):1165–1186CrossRef

Iphar M, Goktan RM (2006) An application of fuzzy sets to the Diggability Index Rating method for surface mine equipment selection. Int J Rock Mech Min Sci 43:253–266CrossRef

Jang JSR, Sun CT, Mizutani E (1997) Neuro-fuzzy and soft computing. A computational approach to learning and machine intelligence. Prentice-Hall, Englewood Cliffs, 614 pp

Juang CH, Lee DH (1990) Rock mass classification using fuzzy sets. In: Proceedings of the 10th Southeast Asian Geotechnical Conference, Chinese Institute of Civil and Hydraulic Engineering, Taipei, Taiwan, April 1990, pp 309–14

Karpuz C (1990) A classification system for excavation of surface coal measures. Min Sci Technol 11:157–163CrossRef

Kayabasi A, Gokceoglu C, Ercanoglu M (2003) Estimating the deformation modulus of rock masses: a comparative study. Int J Rock Mech Min Sci 40:55–63CrossRef

Khademi Hamidi J (2008) A model for hard rock TBM performance prediction. PhD thesis, Amirkabir University of Technology (in preparation)

Khademi Hamidi J, Shahriar K, Rezai B (2007a) Fuzzy set theory for selection of tunneling technique using rock mass excavability (RME) indicator. In: Proceedings of the 2nd Symposium on Underground Excavation for Transportation, Istanbul, November 2007, pp 121–127

Khademi Hamidi J, Shahriar K, Shirazi MA, Torkamani A (2007b) Application of fuzzy set theory to rock mass excavability (RME) classification system. In: Proceedings of the 3rd Iranian Rock Mechanics Conference, Tehran, Iran, pp 647–52

Kirsten HAD (1982) A classification system for excavation in natural materials. Civil Eng S Afr 24:293–308

Klose CD (2002) Fuzzy rule-based expert system for short-range seismic prediction. Comput Geosci 28:377–386CrossRef

Lauffer H (1958) Classification for tunnel construction (in German). Geol Bauwes 24(1):46–51

Lee H, Jeon S, Kim J (2003) Development of a fuzzy model to estimate engineering rock mass properties. In: Proceedings of the 10th Congress of the ISRM—Technology Roadmap for Rock Mechanics, Sandton City, South Africa, September 2003, S Afr Inst Min Metall 749–752

Li X, Tso SK (1999) Drill wear monitoring based on current signals. Wear 231:172–178CrossRef

Liu Y, Chen C (2007) A new approach for application of rock mass classification on rock slope stability assessment. Eng Geol 89:129–143CrossRef

Mamdani EH, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man Machine Stud 7(1):1–13CrossRef

Nguyen VU (1985) Some fuzzy set applications in mining geomechanics. Int J Rock Mech Min Sci 22:369–379CrossRef

Nguyen VU, Ashworth E (1985) Rock mass classification by fuzzy sets. In: Proceedings of the 26th US Symposium on Rock Mechanics, Rapid City, South Dakota, June 1985, pp 937–945

Pacher F, Rabcewicz L, Golser J (1974) Zum der seitigen Stand der Gebirgsklassifizierung in Stollen und Tunnelbau. In: Proceedings of the XXII Geomechanical Colloquium, Salzburg, Austria, pp 51–8

Palmstrom A (1995) RMi—a rock mass characterization system for rock engineering purposes. PhD thesis, University of Oslo, 400 pp. Home page at: http://www.rockmass.net

Palmstrom A, Broch E (2006) Use and misuse of rock mass classification systems with particular reference to the Q-system. Tunn Undergr Space Technol 21:575–593CrossRef

Riedmuller G, Schubert W (1999) Rock mass modeling in tunneling versus rock mass classification using rating methods. In: Proceedings of the 37th US Rock Mechanics Symposium, Vail, Colorado, June 1999

Ritter W (1879) Die Statik der Tunnelgewölbe. Springer, Berlin

Ross TJ (1995) Fuzzy logic with engineering applications. McGraw-Hill, New York, 600 pp

Sakurai S, Shimizu N (1987) Assessment of rock slope stability by fuzzy set theory. In: Proceedings of the 6th Congress of the International Society for Rock Mechanics, Montreal, Canada,, pp 503–506

Scoble MJ, Muftuoglu YV (1984) Derivation of a diggability index for surface mine equipment selection. Min Sci Technol 1:305–322CrossRef

Singh B, Goel RK (1999) Rock mass classifications—a practical approach in civil engineering. Elsevier, Amsterdam, p 267

Sonmez H, Gokceoglu C, Ulusay R (2003) An application of fuzzy sets to the Geological Strength Index (GSI) system used in rock engineering. Eng Appl Artif Intell 16(3):251–269CrossRef

Stille H, Palmstrom A (2003) Classification as a tool in rock engineering. Tunn Undergr Space Technol 18:331–345CrossRef

Swart AH, Human JL, Harvey F (2005) Rock engineering challenges. S Afr Inst Min Metall pp 103–106

Terzaghi K (1946) Rock defects and loads on tunnel supports. In: Rock Tunneling with Steel Supports. Commercial Shearing and Stamping Company, Youngstown, Ohio, pp 15–99

Weaver JM (1975) Geological factors significant in the assessment of rippability. Civil Eng S Afr 17(12):313–316

Wei X, Wang CY, Zhoub ZH (2003) Study on the fuzzy ranking of granite sawability. J Mater Process Technol 139:277–280CrossRef

Wickham GE, Tiedemann HR, Skinner EH (1972) Support determination based on geologic predictions. In: Proceedings of the Rapid Excavation and Tunneling Conference (RETC), pp 43–64

Williamson DA, Kuhn CR (1988) The unified classification system. In: Rock Engineering Systems for Engineering Purposes, ASTM STP 984. American Society for Testing Materials, Philadelphia, pp 7–16

Wu C, Hao H, Zhou Y (1999) Fuzzy-random probabilistic analysis of rock mass responses to explosive loads. Comput Geotech 25:205–225CrossRef

Yao Y, Li X, Yuan Z (1999) Tool wear detection with fuzzy classification and wavelet fuzzy neural network. Int J Mach Tools Manuf 39:1525–1538CrossRef

Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353CrossRef

Zadeh LA (1992) Fuzzy logic, neural networks, and soft computing. One-page course announcement of CS 294–4, The University of California at Berkeley

Zadeh LA (2006) Generalized theory of uncertainty (GTU)—principal concepts and ideas. Comput Stat Data Anal 51:15–46CrossRef

Zadeh LA (2008) Is there a need for fuzzy logic? Inf Sci 178:2751–2779CrossRef

Title: Application of Fuzzy Set Theory to Rock Engineering Classification Systems: An Illustration of the Rock Mass Excavability Index
Authors: Jafar Khademi Hamidi
Kourosh Shahriar
Bahram Rezai
Hadi Bejari
Publication date: 01-05-2010
Publisher: Springer Vienna
Published in: Rock Mechanics and Rock Engineering / Issue 3/2010
Print ISSN: 0723-2632
Electronic ISSN: 1434-453X
DOI: https://doi.org/10.1007/s00603-009-0029-1

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