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2024 Vol.23, Issue 4 Preview Page

Research Article

The Estimation of Uniaxial Compressive Strength from Measured RCD Excavation Speed
Weiwei Zhang1
,
Ki-Il Song2*
,
Jaemyung Kim3
,
Sang-Yun Lee4
1Non-Member, Ph.D. Student, Department of Civil Engineering, INHA University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
2Member, Professor, Department of Civil Engineering, INHA University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
3Member, Project Manager, Infrastructure Business Headquarters, Road Project Division, POSCO Engineering & Construction, 131 Robot Land-ro, Seo-gu, Incheon 22851, Republic of Korea
4Non-Member, Postdoctoral Researcher, Department of Civil Engineering, INHA University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
*Corresponding Author
31 December 2024. pp. 13-21
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Abstract

This study focuses on the classification of rock types encountered during the construction of the Bridge project. The classification is based primarily on excavation speed and uniaxial compressive strength (UCS), with point load strength used as a supplementary parameter. Through detailed analysis of excavation data, an exponential decay relationship between excavation speed and UCS was identified, facilitating the classification of rocks into categories such as weathered rock, soft rock, and hard rock. As depth increases, rock strength generally increases, resulting in a significant reduction in excavation speed. The findings from this study underscore the negative exponential correlation between rock strength and excavation efficiency, offering valuable insights for optimizing construction strategies. Furthermore, the proposed classification system provides a practical framework applicable to other projects involving complex geological conditions. This framework not only enhances the accuracy of load-bearing predictions but also ensures cost-effectiveness and safety in large-scale infrastructure projects. The results of this research offer a reliable method for real-time rock classification during excavation, thereby improving construction efficiency and safety.

Keywords
Rock classification
Excavation speed
Uniaxial Compressive Strength (UCS)
RCD method
Geological conditions
References
1

Aydan, Ö. and Kawamoto, T. (2000), The assessment of mechanical properties of rock masses through RMR rock classification system, ISRM International Symposium.

2

Barton, N., Lien, R. and Lunde, J. (1974), "Engineering classification of rock masses for the design of tunnel support", Rock Mechanics, Vol.6, pp.189-236.

10.1007/BF01239496
3

Bieniawski, Z. (1973), "Engineering classification of jointed rock masses", Civil Engineering Siviele Ingenieurswese, Vol.15, No.12, pp.335-343.

4

Bieniawski, Z. T. (1989), Engineering Rock Mass Classifications: A Complete Manual for Engineers and Geologists in Mining, Civil, and Petroleum Engineering, John Wiley & Sons, New York, pp.51-69.

5

Galbraith, J. H. and Saunders, D. F. (1983), "Rock classification by characteristics of aerial gamma-ray measurements", Journal of 7. Geochemical Exploration, Vol.18, No.1, pp.49-73.

10.1016/0375-6742(83)90080-8
6

Hasegawa, N., Hasegawa, S., Kitaoka, T. and Ohtsu, H. (2019), "Applicability of neural network in rock classification of mountain tunnel", Materials Transactions, Vol.60, No.5, pp.758-764.

10.2320/matertrans.Z-M2019809
7

Hoek, E. (1983), "Strength of jointed rock masses", Geotechnique, Vol.33, No.3, pp.187-223.

10.1680/geot.1983.33.3.187
8

Hoek, E. and Brown, E. T. (1980). Underground Excavations in Rock, CRC Press, Published for the Institution of Mining and Metallurgy, London.

9

Huang, R., Huang, J., Ju, N. and Li, Y. (2013), "Automated tunnel rock classification using rock engineering systems", Engineering Geology, Vol.156, pp.20-27.

10.1016/j.enggeo.2013.01.006
10

Kayabasi, A., Gokceoglu, C. and Ercanoglu, M. (2003), "Estimating the deformation modulus of rock masses: a comparative study", International Journal of Rock Mechanics and Mining Sciences, Vol.40, No.1, pp.55-63.

10.1016/S1365-1609(02)00112-0
11

Khabbazi, A., Ghafoori, M., Lashkaripour, G. R. and Cheshomi, A. (2013), "Estimation of the rock mass deformation modulus using a rock classification system", Geomechanics and Geoengineering, Vol.8, No.1, pp.46-52.

10.1080/17486025.2012.695089
12

Kim, M. G. and Lee, Y. S. (2008), "A Suggestion of a New Rock Mass Classification System," Journal of the Korean Geotechnical Society, Vol.24, No.11, pp.43-53.

13

Ran, X., Xue, L., Zhang, Y., Liu, Z., Sang, X. and He, J. (2019), "Rock classification from field image patches analyzed using a deep convolutional neural network", Mathematics, Vol.7, No.8, p.755.

10.3390/math7080755
14

Singh, T. N., Kainthola, A. and Venkatesh, A. (2012)， "Correlation between point load index and uniaxial compressive strength for different rock types", Rock Mechanics and Rock Engineering, Vol.45, pp.259-264.

10.1007/s00603-011-0192-z
15

Su, C., Xu, S.J., Zhu, K.Y. and Zhang, X.C. (2020), "Rock classification in petrographic thin section images based on concatenated convolutional neural networks", Earth Science Informatics, Vol.13, pp.1477-1484.

10.1007/s12145-020-00505-1
16

Williamson, D. A. (1984), "Unified rock classification system", Bulletin of the Association of Engineering Geologists, Vol.21, No.3, pp.345-354.

10.2113/gseegeosci.xxi.3.345
17

Zhou, Y., Wong, L. N. Y. and Tse, K. K. C. (2023), "Novel rock image classification: the proposal and implementation of HKUDES_Net", Rock Mechanics and Rock Engineering, Vol.56, No.5, pp.3825-3841.

10.1007/s00603-023-03235-0
Information
  • Publisher :Korean Geosythetics Society
  • Publisher(Ko) :한국지반신소재학회
  • Journal Title :Journal of the Korean Geosynthetics Society
  • Journal Title(Ko) :한국지반신소재학회 논문집
  • Volume : 23
  • No :4
  • Pages :13-21
  • Received Date : 2024-10-16
  • Revised Date : 2024-10-22
  • Accepted Date : 2024-10-22
  • DOI :https://doi.org/10.12814/jkgss.2024.23.4.013
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