An Investigation of the Effect of Freezing on Strength and Durability of Dimension Stones Using Fuzzy Clustering Technique and Statistical Analysis

نوع مقاله : مقاله پژوهشی

نویسندگان

1 Department of Mining and Metallurgy, Urmia University of Technology, Iran

2 Nour Branch, Islamic Azad University, Iran

3 Young Researchers and Elite Club, Rasht Branch, Islamic Azad University, Iran

چکیده

Western and North-Western regions of Iran feature very cold winters, a lot of snow, and freezing temperatures during most nights in December, January, February, and March. This directly influences the selection and applications of dimension stones in these areas. Freezing influences both mechanical and physical properties of rocks. Therefore, measuring the changes in values of these parameters before and after freezing can be used to study the effects of freezing on rocks. The main objective of this study is to investigate the effect of freezing on the strength and durability of dimension stones. In this research, fourteen types of frequently utilized stones in North-Western parts of Iran were studied. Five freezing and thawing cycles were done on prepared cores. The results of statistical analysis showed that the uniaxial compressive strength and durability of stones respectively reduced by 7.99% and 1.07% after freezing. The uniaxial compressive strength reduced by 3.03% and durability by 0.6% in the case of the best stone. Using the fuzzy clustering technique, all rocks were classified in two separate clusters according to their properties and the reduction rate of uniaxial compressive strength and durability before and after freezing.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

An Investigation of the Effect of Freezing on Strength and Durability of Dimension Stones Using Fuzzy Clustering Technique and Statistical Analysis

نویسندگان [English]

  • Reza Mikaeil 1
  • Alireza Dormishi 2
  • Golsa Sadegheslam 1
  • Sina Shaffiee Haghshenas 3
1 Department of Mining and Metallurgy, Urmia University of Technology, Iran
2 Nour Branch, Islamic Azad University, Iran
3 Young Researchers and Elite Club, Rasht Branch, Islamic Azad University, Iran
چکیده [English]

Western and North-Western regions of Iran feature very cold winters, a lot of snow, and freezing temperatures during most nights in December, January, February, and March. This directly influences the selection and applications of dimension stones in these areas. Freezing influences both mechanical and physical properties of rocks. Therefore, measuring the changes in values of these parameters before and after freezing can be used to study the effects of freezing on rocks. The main objective of this study is to investigate the effect of freezing on the strength and durability of dimension stones. In this research, fourteen types of frequently utilized stones in North-Western parts of Iran were studied. Five freezing and thawing cycles were done on prepared cores. The results of statistical analysis showed that the uniaxial compressive strength and durability of stones respectively reduced by 7.99% and 1.07% after freezing. The uniaxial compressive strength reduced by 3.03% and durability by 0.6% in the case of the best stone. Using the fuzzy clustering technique, all rocks were classified in two separate clusters according to their properties and the reduction rate of uniaxial compressive strength and durability before and after freezing.

کلیدواژه‌ها [English]

  • Freezing
  • Uniaxial Compressive Strength
  • Durability
  • Statistical Analysis
  • Fuzzy clustering

مراجع

[1] Burgess, R. B., & Birle, J. D., Circular sawing granite with diamond saw blades. In Proceedings of the fifth industrial diamond seminar, 1987: p. 3-10.
[2] Wright, D. N., & Cassapi, V. B., Factors influencing stone sawability. Industrial Diamond Review, 1985. 45(2): p. 84-7.
[3] Birle, J. D., & Ratterman, E., An approximate ranking of the sawability of hard building stones based on laboratory tests. Dimensional Stone Magazine, 1986. 3(1): p. 3-29.
[4] Jennings, M., & Wright, D., Guidelines for sawing stone. Industrial Diamond Review, 1989. 49(2): p.70-5.
[5] Clausen, R., et al., Characteristics of acoustic emission during single diamond scratching of granite. Industrial Diamond Review,1996. 56(570): p.96–9.
[6] Wei, X., et al., Study on the fuzzy ranking of granite sawability. Journal of Materials Processing Technology, 2003. 139(1): p.277–80.
[7] Eyuboglu, A. S., et al., Statistical and microscopic investigation of disc segment wear related to sawing Ankara andesites. International Journal of Rock Mechanics and Mining Sciences, 2003. 40(3): p.405-414.
[8] Ersoy, A., & Atıcı, U. (2004). Performance characteristics of circular diamond saws in cutting different types of rocks. Diamond and Related Materials, 2004. 13(1): p. 22-37.
[9] Kahraman, S., et al., Predicting the sawability of carbonate rocks using multiple curvilinear regression analysis. International journal of rock mechanics and mining sciences, 2004. 41(7): p.1123-1131.
[10] Gunaydin O., et al., Sawability prediction of carbonate rocks from brittleness indexes. J. South Afr. Inst. Min. Metall, 2004. 104(1): p. 239-244.
[11] Ozcelik, Y., et al., Investigation of the effects of textural properties on marble cutting with diamond wire. International Journal of Rock Mechanics and Mining Sciences, 2004. 41(1): p. 228-234.
[12] Buyuksagis, I. S., & Goktan, R. M., Investigation of marble machining performance using an instrumented block-cutter. Journal of Materials Processing Technology, 2005. 169(2): p.258-262.
[13] Ersoy, A., et al., Wear characteristics of circular diamond saws in the cutting of different hard abrasive rocks. Wear, 2005. 258(9): p. 1422-1436.
[14] Delgado, N. S., et al. The influence of rock microhardness on the sawability of Pink Porrino granite (Spain). International Journal of Rock Mechanics and Mining Sciences, 2005. 42(1): p. 161-166.
[15] Kahraman, S., et al., Sawability prediction of carbonate rocks from shear strength parameters using artificial neural networks. International Journal of Rock Mechanics & Mining Sciences, 2005. 43(1):p. 157–164.
[16] Fener M, et al., Performance Prediction of Circular Diamond Saws from Mechanical Rock Properties in Cutting Carbonate Rocks, Rock Mech. Rock Engng, 2007. 40 (5): p.505–517.
[17] Kahraman S, et al.,  A quality classification of building stones from P-wave velocity and its application to stone cutting with gang saws. The Journal of the Southern African Institute of Mining and Metallurgy, 2007. 107(1): p.427–430.
[18] Özçelik, Y. The effect of marble textural characteristics on the sawing efficiency of diamond segmented frame saws. Industrial Diamond Review, 2007. 2 (1): p. 65-70.
[19] Tutmez B., et al., Multifactorial fuzzy approach to the sawability classification of building stones. Construction and Building Materials, 2007. 21(8): p. 1672–1679.
[20] Buyuksagis, I. S., Effect of cutting mode on the sawability of granites using segmented circular diamond sawblade. Journal of Materials Processing Technology, 2007. 183(2): p.399-406.
[21] Mikaeil, R., et al. Predicting the production rate of diamond wire saws in carbonate rocks cutting, Industrial Diamond Review. 2008. 68(3): p.28-34.
[22] Mikaeil, R., et al., Application of a fuzzy analytical hierarchy process to the prediction of vibration during rock sawing. Mining Science and Technology (China), 2011. 21(5): p.611-619.
[23] Mikaeil, R., et al., Development of a new classification system for assessing of carbonate rock sawability. Archives of Mining Sciences,2011. 56(1): p.59-70.
[24] Ataei, M., et al., Predicting the production rate of diamond wire saw using statistical analysis. Arabian Journal of Geosciences, 2012. 5(6): p.1289-1295.
[25] Mikaeil, R., et al., Correlation of production rate of ornamental stone with rock brittleness indexes. Arabian Journal of Geosciences, 2013. 6(1): p. 115-121.
[26] Mikaeil, R., et al., Sawability ranking of carbonate rock using fuzzy analytical hierarchy process and TOPSIS approaches. Scientia Iranica, 2011. 18(5); p.1106-1115.
[27] Mikaeil R., et al., Evaluating the Power Consumption in Carbonate Rock Sawing Process by Using FDAHP and TOPSIS Techniques, Efficient Decision Support Systems: Practice and Challenges – From Current to Future / Book 2", ISBN 978-953-307-441-2., 478. 2011.
[28] Mikaeil, R., et al., Correlation of specific ampere draw with rock brittleness indexes in rock sawing process. Archives of Mining Sciences, 2011. 56(4): p.777-788.
[29] Ataei, M., et al., Fuzzy analytical hierarchy process approach for ranking the sawability of carbonate rock. International Journal of Rock Mechanics and Mining Sciences, 2012. 50: p. 83-93.
[30] Ghaysari, N.,et al., Prediction of performance of diamond wire saw with respect to texture characteristics of rock/Prognozowanie Wydajności Pracy Strunowej Piły Diamentowej W Odniesieniu do Charakterystyki Tekstury Skał. Archives of Mining Sciences, 2012. 57(4): p. 887-900.
[31] Mikaeil, R., et al., Ranking the sawability of ornamental stone using Fuzzy Delphi and multi-criteria decision-making techniques. International Journal of Rock Mechanics and Mining Sciences, 2013. 58: p.118-126.
[32] Sadegheslam, G., et al., Predicting the production rate of diamond wire saws using multiple nonlinear regression analysis. Geosystem engineering, 2013. 16(4): p. 275-285.
[33] Mikaeil, R., et al. Predicting the relationship between system vibration with rock brittleness indexes in rock sawing process. Archives of Mining Sciences, 2014. 59(1); p.139-153.
[34] Mikaeil, R., et al., Ranking sawability of dimension stone using PROMETHEE method. Journal of Mining and Environment, 2015.6(2): p. 263-271.
[35] Osanloo, M. Drilling methods. Tehran, Sadra Pub. (1998).
[36] Hoseinie, S. H., et al., A new classification system for evaluating rock penetrability. International Journal of Rock Mechanics and Mining Sciences, 2009. 46(8): p. 1329-1340.
[37] Fhhimifar, A., Soroush, H., Rock Mechanics Tests; Theoretical aspects and standards. Pub. Ministry of Transportation, Teharn. 2002.
[38] Franklin, J. A., et al. Suggested methods for determining water content, porosity, density, absorption, and related properties and swelling and slake durability index properties for ISRM commission on standardization of laboratory and field tests, International Journal of Rock Mechanics & Mining Sciences, 1979. 16: p. 141–156. 
[39] Widmann, R. International society for rock mechanics commission on rock grouting. International journal of rock mechanics and mining sciences & geomechanics abstracts, 1996. 33(8): p. 803-847.
[40] Iranian Institute of Standards & Industrial Researches, Methods of determining the strength of building materials against the freezing, National Iranian Standards No. 578, Tehran, 1992.
[41] Zadeh, L. A. Fuzzy sets. Information and control, 1965. 8(3): p. 338-353.
[42] Rad, M. Y., et al., Analysis of Protection of Body Slope in the Rockfill Reservoir Dams on the Basis of Fuzzy Logic. In IJCCI, 2012. P.367-373.
[43] Haghshenas, S. S., et al., Ranking and Assessment of Tunneling Projects Risks Using Fuzzy MCDM (Case Study: Toyserkan Doolayi Tunnel). 25th International Mining Congress and Exhibition of Turkey, 2017. P. 289-297.
[44] Haghshenas, S. S., et al., Fuzzy and Classical MCDM Techniques to Rank the Slope Stabilization Methods in a Rock-Fill Reservoir Dam. Civil Engineering Journal, 2017. 3(6): p. 382-394.
[45] Haghshenas, S. S., et al., The Risk Assessment of Dam Construction Projects Using Fuzzy TOPSIS (Case Study: Alavian Earth Dam). Civil Engineering Journal, 2016. 2(4): p.158-167.
[46] Bezdek JC, et al., FCM: The fuzzy c-means clustering algorithm. Computers & Geosciences, 1984. 10(2-3): p.191-203.
[47] Basarir, H., & Karpuz, C., A rippability classification system for marls in lignite mines. Engineering geology, 2004. 74(3): p. 303-318.
[48] Haghshenas, S. S., et al., Utilization of Soft Computing for Risk Assessment of a Tunneling Project Using Geological Units. Civil Engineering Journal, 2016. 2(7) : p. 358-364.
[49] Rad, M.Y., et al., Mechanostratigraphy of cretaceous Rocks by Fuzzy Logic in East Arak, Iran. The 4th International Workshop on Computer Science and Engineering, summer, WCSE, 2014.
[50] Mikaeil, R., et al., Performance prediction of circular saw machine using imperialist competitive algorithm and fuzzy clustering technique. Neural Computing and Applications, 2016. 1-10.

فایل ها

سابقه مقاله

  • تاریخ دریافت: 27 اسفند 1393
  • تاریخ بازنگری: 26 تیر 1395
  • تاریخ پذیرش: 04 اردیبهشت 1396

هم رسانی

ارجاع به این مقاله

آمار