تخمین غیرمستقیم مقاومت فشاری تک‌محورۀ سنگ بااستفاده از الگوریتم‌های جدید فراابتکاری

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشکده مهندسی علوم زمین، دانشگاه صنعتی اراک

چکیده

پارامتر مقاومت فشاری تک‌محوره یک پارامتر مهم و کلیدی در مهندسی ژئومکانیک است که در طبقه‌بندی مهندسی سنگ، بررسی معیارهای شکست سنگ و در مرحلۀ طراحی بسیاری از پروژه‌های عمرانی و معدنی کاربرد دارد. در بسیاری از موارد به‌دلیل عدم دسترسی به مغزه‌های باکیفیت، تعیین این پارامترها در آزمایشگاه با سختی‌های زیادی همراه است و اغلب این پارامتر به‌صورت غیرمستقیم از روابط رگرسیونی تخمین زده می‌شود که این روابط از دقت بالایی برخوردار نیستند. هدف از این تحقیق، استفاده از الگوریتم‌های جدید فراابتکاری گرگ خاکستری (GWO) و الگوریتم مگس میوه (FFOA) به‌منظور تخمین غیرمستقیم مقاومت فشاری تک‌محوره می‌باشد. برای رسیدن به این هدف، از داده‌های 124 نمونه سنگ گرانیت از پروژۀ تونل انتقال آب شیرین ایالت سلانگور در مالزی استفاده شده‌است. در انتها برای ارزیابی و اعتبارسنجی مدل‌های به‌دست‌آمده توسط الگوریتم‌های فراابتکاری از شاخص‌های آماری مختلفی استفاده شده‌است. باتوجه به نتایج به‌دست‌آمده در این مقاله و هم‌چنین اعتبارسنجی مدل‌ها، مقادیر پیش‌بینی‌شدۀ مقاومت فشاری تک‌محوره توسط الگوریتم‌های جدید فراابتکاری مذکور با مقادیر واقعی منطقه بسیار نزدیک است که نشان‌دهندۀ خطای کم مدل‌های به‌دست‌آمده می‌باشد. به‌علاوه در این مقاله آنالیز حساسیت برروی پارامترهای مؤثر در تخمین مقاومت فشاری تک‌محوره نیز انجام شد که نتایج بررسی‌ها نشان داد مقادیر برگشتی چکش اشمیت (Rn)، در میان سایر پارامترهای ورودی، بیشترین تأثیر را برروی مقاومت فشاری تک‌محوره دارد.
 

کلیدواژه‌ها


عنوان مقاله [English]

Indirect Estimation of Uniaxial Compressive Strength of Rock Using New Meta-Heuristic Algorithms

نویسندگان [English]

  • Hadi Fattahi
  • Farshad Malekmahmoudi
  • Hossein Ghaedi
Faculty of Earth Sciences Engineering, Arak University of Technology, Iran.
چکیده [English]

The uniaxial compressive strength parameter is an important and key parameter in geomechanical engineering that is used in rock engineering classification, study of rock fracture criteria and in the design stage of many construction and mining projects. In many cases, due to the lack of access to quality cores, determining these parameters in the laboratory is associated with many difficulties, and often this parameter is indirectly estimated from regression relationships that these relationships are not very accurate. The aim of this study is to use the new meta-heuristic algorithms of gray wolf (GWO) and fruit fly algorithm (FFOA) to indirectly estimate uniaxial compressive strength. To achieve this goal, data from 124 granite rock samples from the Selangor freshwater transfer tunnel project in Malaysia, have been used. Finally, to evaluate and validate the models obtained by intelligent algorithms, the indices of statistical are used. According to the results obtained in this paper as well as the validation of the models, the predicted values ​​of uniaxial compressive strength are very close to the real values ​​of the region, indicating the low error of the models in indirect estimation. In addition, in this paper, sensitivity analysis was performed on the effective parameters in estimating uniaxial compressive strength. The results showed that the return values ​​of Schmidt hammer (Rn), among other input parameters, have the greatest effect on uniaxial compressive strength.

کلیدواژه‌ها [English]

  • Granite rock
  • Uniaxial compressive strength
  • Indirect estimation
  • FFOA
  • GWO
  1. D'Andrea, D.V., Fischer, R., and Fogelson, D., "Prediction of Compressive Strength from other Rock Properties", US Department of the Interior, Bureau of Mines, Vol. 6702, pp. 155-188, (1965).
  2. Cargill, J. S., and Shakoor, A., "Evaluation of Empirical Methods for Measuring the Uniaxial Compressive Strength of Rock", in International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, Elsevier, Vol. 27, pp. 495-503, (1990).
  3. Tuğrul, A., and Zarif, I., "Correlation of Mineralogical and Textural Characteristics with Engineering Properties of Selected Granitic Rocks from Turkey", Engineering geology, 51, pp. 303-317, (1999).
  4. Karakus, M., and Tutmez, B., "Fuzzy and Multiple Regression Modelling for Evaluation of Intact Rock Strength Based on Point Load, Schmidt Hammer and Sonic Velocity", Rock mechanics and rock engineering, 39, pp. 45-57, (2006).
  5. Basu, A., and Aydin, A., "Predicting Uniaxial Compressive Strength by Point Load Test: Significance of Cone Penetration", Rock Mechanics and Rock Engineering, 39, pp. 483-90, (2006).
  6. Kahraman, S., and Gunaydin, O., "The Effect of Rock Classes on the Relation between Uniaxial Compressive Strength and Point Load Index", Bulletin of engineering geology and the environment, 68, pp. 345-353, (2009).
  7. Basu, A., and Kamran, M., "Point Load Test on Schistose Rocks and Its Applicability in Predicting Uniaxial Compressive Strength", International journal of rock mechanics and mining sciences (1997), Vol. 47, pp. 823-828, (2010).
  8. Yagiz, S., "P-wave Velocity Test for Assessment of Geotechnical Properties of some Rock Materials", Bulletin of Materials Science, 34, pp. 947-953, (2011).
  9. Singh, T., Kainthola, A., and Venkatesh, A., "Correlation between Point Load Index and Uniaxial Compressive Strength for Different Rock Types", Rock Mechanics and Rock Engineering, 45, pp. 259-264, (2012).
  10. Aladejare, A. E., "Evaluation of Empirical Estimation of Uniaxial Compressive Strength of Rock Using Measurements from Index and Physical Tests", Journal of Rock Mechanics and Geotechnical Engineering, 12, pp. 256-268, (2020).
  11. Gokceoglu, C., "A Fuzzy Triangular Chart to Predict the Uniaxial Compressive Strength of the Ankara Sgglomerates from their Petrographic Composition", Engineering Geology, 66, pp. 39-51, (2002).
  12. Tiryaki, B., "Predicting Intact Rock Strength for Mechanical Excavation Using Multivariate Statistics, Artificial Neural Networks, and Regression Trees", Engineering Geology, 99, pp. 51-60, (2008).
  13. Sarkar, K., Tiwary, A., and Singh, , "Estimation of Strength Parameters of Rock Using Artificial Neural Networks", Bulletin of engineering geology and the environment, Vol. 69, pp. 599-606, (2010).
  14. Manouchehrian, A., Sharifzadeh, M., and Moghadam, R.H., "Application of Artificial Neural Networks and Multivariate Statistics to Estimate UCS Using Textural Characteristics", International Journal of Mining Science and Technology, 22, pp. 229-236, (2012).
  15. Singh, T. N., and Verma, A. K., "Comparative Analysis of Intelligent Algorithms to Correlate Strength and Petrographic Properties of Some Schistose Rocks", Engineering with Computers, 28, pp. 1-12, (2012).
  16. Yagiz, S., Sezer, E., and Gokceoglu, C., "Artificial Neural Networks and Nonlinear Regression Techniques to Assess the Influence of Slake Durability Cycles on the Prediction of Uniaxial Compressive Strength and Modulus of Elasticity for Carbonate Rocks", International Journal for Numerical and Analytical Methods in Geomechanics, 36, pp. 1636-1650, (2012).
  17. Singh, R., et al., "A Comparative Study of Generalized Regression Neural Network Approach and Adaptive nNeuro-fuzzy Inference Systems for Prediction of Unconfined Compressive Strength of Rocks", Neural Computing and Applications, 23, pp. 499-506, (2013).
  18. Yesiloglu-Gultekin, N., Gokceoglu, C., and Sezer, E. A., "Prediction of Uniaxial Compressive Strength of Granitic Rocks by Various Nonlinear Tools and Comparison of their Performances", International Journal of Rock Mechanics and Mining Sciences, 62, pp. 113-122, (2013).
  19. Armaghani, D. J., et al., "Uniaxial Compressive Strength Prediction through a New Technique Based on Gene Expression Programming", Neural Computing and Applications, 30, pp. 3523-3532, (2018).
  20. Saedi, B., Mohammadi, S. D., and Shahbazi, H., "Prediction of Uniaxial Compressive Strength and Elastic Modulus of Migmatites Using Various Modeling Techniques", Arabian Journal of Geosciences, 11, pp. 1-14, (2018).
  21. Wang, M. and Wan, W., "A New Empirical Formula for Evaluating Uniaxial Compressive Strength Using the Schmidt Hammer Test", International Journal of Rock Mechanics and Mining Sciences, 123, pp. 104094, (2019).
  22. Broch, E., and Franklin, J., "The Point-load Strength Test", in International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, Elsevier, Vol. 9, pp. 669-676, (1972).
  23. Mishra, D., and Basu, A., "Use of the Block Punch Test to Predict the Compressive and Tensile Strengths of Rocks", International Journal of Rock Mechanics and Mining Sciences, 51, pp. 119-127, (2012).
  24. Smith, H. J., "The Point Load Test for Weak Rock in Dredging Applications", International Journal of Rock Mechanics and Mining Sciences, 34, pp. 295. e1-295. e13, (1997).
  25. Lashkaripour, G. R., "Predicting Mechanical Properties of Mudrock from Index Parameters", Bulletin of Engineering Geology and the Environment, 61, pp. 73-77, (2002).
  26. Forster, I., "The Influence of Core Sample Geometry on the Axial Point-load Test", Intl J of Rock Mech & Mining Sci & Geomechanic Abs, 20, pp. 291-295, (1983).
  27. Fener, M., et al., "A Comparative Evaluation of Indirect Methods to Estimate the Compressive Strength of Rocks", Rock Mechanics and Rock Engineering, 38, pp. 329-343, (2005).
  28. Ulusay, R., Türeli, K., and Ider, M" ,.Prediction of Engineering Properties of a Selected Litharenite Sandstone from its Petrographic Characteristics Using Correlation and Multivariate Statistical Techniques", Engineering Geology, 38, pp. 135-157, (1994).
  29. Hassani, F., Scoble, M., and Whittaker, B., Application of the Point Load Index Test to Strength Determination of Rock and Proposals for a New Size-correction Chart, in The 21st US Symposium on Rock Mechanics (USRMS). OnePetro, (1980).
  30. Çobanoğlu, İ. and Çelik, S.B., "Estimation of Uniaxial Compressive Strength from Point Load Strength, Schmidt Hardness and P-wave Velocity", Bulletin of Engineering Geology and the Environment, 67, pp. 491-498, (2008).
  31. Xu, S., Grasso, P., and Mahtab, A., "Use of Schmidt Hammer for Estimating Mechanical Properties of Weak Rock", in International congress international association of engineering geology. 6. (1990).
  32. Sachpazis, C., "Correlating Schmidt Hardness with Compressive Strength and Young’s Modulus of Carbonate Rocks", Bulletin of the International Association of Engineering Geology-Bulletin de l'Association Internationale de Géologie de l'Ingénieur, 42, pp. 75-83, (1990).
  33. Singh, R., Hassani, F., and Elkington, P., "The Application of Strength and Deformation Index Testing to the Stability Assessment of Coal Measures Excavations", in The 24th US Symposium on Rock Mechanics (USRMS), American Rock Mechanics Association, (1983).
  34. Yagiz, S., "Predicting Uniaxial Compressive Strength, Modulus of Elasticity and Index Properties of Rocks Using the Schmidt Hammer", Bulletin of engineering geology and the environment, 68, pp. 55-63, (2009).
  35. Shalabi, F.I., Cording, E.J., and Al-Hattamleh, O.H., "Estimation of Rock Engineering Properties Using Hardness Tests", Engineering Geology, Vol. 90, 138-147, (2007).
  36. Yaşar, E. and Erdoğan, Y., "Estimation of Rock Physicomechanical Properties Using Hardness Methods", Engineering Geology, 71, pp. 281-288, (2004).
  37. Aufmuth, R. E., A Systematic Determination of Engineering Criteria for Rock, (1974).
  38. Yılmaz, I. and Sendır, H., "Correlation of Schmidt Hardness with Unconfined Compressive Strength and Young's Modulus in Gypsum from Sivas (Turkey)", Engineering Geology, 66, pp. 211-219, (2002).
  39. Gupta, V., "Non-destructive Testing of Some Higher Himalayan Rocks in the Satluj Valley", Bulletin of Engineering Geology and the Environment, 68, pp. 409-416, (2009).
  40. Sharma, P. and Singh, T., "A Correlation between P-wave Velocity, Impact Strength Index, Slake Durability Index and Uniaxial Compressive Strength", Bulletin of Engineering Geology and the Environment, 67, pp. 17-22, (2008).
  41. Armaghani, D.J., et al., "An Adaptive Neuro-fuzzy Inference System for Predicting Unconfined Compressive Strength and Young’s Modulus: A Study on Main Range Granite", Bulletin of engineering geology and the environment, 74, pp. 1301-1319, (2015).
  42. Moradian, Z., and Behnia, M., "Predicting the Uniaxial Compressive Strength and Static Young’s Modulus of Intact Sedimentary Rocks Using the Ultrasonic Test", International Journal of Geomechanics, 9, pp. 14-19, (2009).
  43. Diamantis, K., Gartzos, E., and Migiros, G., "Study on Uniaxial Compressive Strength, Point Load Strength Index, Dynamic and Physical Properties of Serpentinites from Central Greece: Test Results and Empirical Relations", Engineering Geology, 108, pp. 199-207, (2009).
  44. Khandelwal, M., "Correlating P-wave Velocity with the Physico-mechanical Properties of Different Rocks", Pure and Applied Geophysics, Vol. 170, 507-514, (2013).
  45. Entwisle, D., et al., "The Relationships between Effective Porosity, Uniaxial Compressive Strength and Sonic Velocity of Intact Borrowdale Volcanic Group Core Samples from Sellafield", Geotechnical & Geological Engineering, 23, pp. 793-809, (2005).
  46. Minaeian, B. and Ahangari, K., "Estimation of Uniaxial Compressive Strength Based on P-wave and Schmidt Hammer Rebound Using Statistical Method", Arabian Journal of Geosciences, 6, pp. 1925-1931, (2013).
  47. Horsrud, P., "Estimating mMechanical Properties of Shale from Empirical Correlations", SPE Drilling & Completion, 16, pp. 68-73, (2001).
  48. Khandelwal, M. and Singh, T., "Correlating Static Properties of Coal Measures Rocks with P-wave Velocity", International Journal of Coal Geology, 79, pp. 55-60, (2009).
  49. Meulenkamp, F. and Grima, M.A., "Application of Neural Networks for the Prediction of the Unconfined Compressive Strength (UCS) from Equotip Hardness", International Journal of rock mechanics and mining sciences, 36, pp. 29-39, (1999).
  50. Gokceoglu, C. and Zorlu, K., "A Fuzzy Model to Predict the Uniaxial Compressive Strength and the Modulus of Elasticity of a Problematic Rock", Engineering Applications of Artificial Intelligence, 17, pp. 61-72, (2004).
  51. Zorlu, K., et al., "Prediction of Uniaxial Compressive Strength of Sandstones Using Petrography-based Models", Engineering Geology, 96, pp. 141-158, (2008).
  52. Yılmaz, I. and Yuksek, A., "An Example of Artificial Neural Network (ANN) Application for Indirect Estimation of Rock Parameters", Rock Mechanics and Rock Engineering, 41, pp. 781-795, (2008).
  53. Yilmaz, I. and Yuksek, G., "Prediction of the Strength and Elasticity Modulus of Gypsum Using Multiple Regression, ANN, and ANFIS Models", International journal of rock mechanics and mining sciences (1997), 46, pp. 803-810, (2009).
  54. Dehghan, S., et al., "Prediction of Uniaxial Compressive Strength and Modulus of Elasticity for Travertine Samples Using Regression and Artificial Neural Networks", Mining Science and Technology (China), 20, pp. 41-46, (2010).
  55. Rezaei, M., Majdi, A., and Monjezi, M., "An Intelligent Approach to Predict Unconfined Compressive Strength of Rock Surrounding Access Tunnels in Longwall Coal Mining", Neural Computing and Applications, 24, pp. 233-241, (2014).
  56. Mohamad, E.T., et al., "Prediction of the Unconfined Compressive Strength of Soft Rocks: A PSO-based ANN Approach", Bulletin of Engineering Geology and the Environment, 74, pp. 745-757, (2015).
  57. Mishra, D. and Basu, A., "Estimation of Uniaxial Compressive Strength of Rock Materials by Index Tests Using Regression Analysis and Fuzzy Inference System", Engineering Geology, 160, pp. 54-68, (2013).
  58. Ceryan, , Okkan, U., and Kesimal, A., "Prediction of Unconfined Compressive Strength of Carbonate Rocks Using Artificial Neural Networks", Environmental earth sciences, Vol. 68, pp. 807-819, (2013).
  59. Rabbani, E., et al., "Application of Neural Network Technique for Prediction of Uniaxial Compressive Strength Using Reservoir Formation Properties", International journal of rock mechanics and mining sciences (1997), 56, pp. 100-111, (2012).
  60. Pan, W.-T., "A New Fruit Fly Optimization Algorithm: Taking the Financial Distress Model as an Example", Knowledge-Based Systems, 26, pp. 69-74, (2012).
  61. Mirjalili, S. and Lewis, A., "The Whale Optimization Algorithm", Advances in engineering software, 95, pp. 51-67, (2016).
  62. Mirjalili, S., Mirjalili, S.M., and Lewis, A., "Grey Wolf Optimizer", Advances in engineering software, 69, pp. 46-61, (2014).
  63. Mech, L.D., "Alpha Sstatus, Dominance, and Division of Labor in Wolf Packs", Canadian Journal of Zoology, 77, pp. 1196-1203, (1999).
  64. Armaghani, D.J., et al., "Application of Several Non-linear Prediction Tools for Estimating Uniaxial Compressive Strength of Granitic Rocks and Comparison of their Performances", Engineering with Computers, 32, pp. 189-206, (2016).
  65. Hatheway, A.W., The Complete ISRM Suggested Methods for Rock Characterization, Testing and Monitoring; 1974–2006. 2009, Association of Environmental & Engineering Geologists.
  66. Fattahi, H., Varmazyari, Z., and Babanouri, N., "Feasibility of Monte Carlo Simulation for Predicting Deformation Modulus of Rock Mass", Tunnelling and Underground Space Technology, 89, pp. 151-156, (2019).

 

 

 

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