Dr. Saffet YAGIZ

Nazarbayev University, Astana, Kazakhstan

Professor

E-mail: [email protected]

Qualifications

2002 Ph.D., Colorado School of Mines, Colorado, USA

1997 M.Sc., University of Missouri Rolla, Missouri, USA

1992 B.Sc., Department of Geological Engineering, Ankara, Turkey

Publications(Selected)

1. Ghorbani, E., & Yagiz, S. (2026). Comprehensive models for estimating drag force of conical picks using relieved small-scale LCM tests data. Rock Mechanics and Rock Engineering, 59(9), 7033–7062.
2. Zhou, P., Wong, J., & Song, Z., et al. (2026). Theoretical prediction method for settlement of existing tunnel induced by undercrossing. Transportation Geotechnics, 62, Article 102111.
3. Olaiya, T. D., Yagiz, S., & Adoko, A. C. (2026). TBM penetration rate estimation using rock mass rating (RMR) and machine specifications. Rock Mechanics Bulletin, 5(3), Article 100328.
4. Gad, A., Arman, H., & Yagiz, S., et al. (2025). Strength characterization of limestone lithofacies under different moisture states. Scientific Reports, 15(1), Article 36822.
5. Ghorbani, E., Adoko, A. C., & Yagiz, S. (2025). AI-based TBM performance models to predict the rate of penetration: An overview and perspective. In M. Khandelwal, D. J. Armaghani, P. Samui, & S. Yagiz (Eds.), Advancements in Underground Infrastructures (pp. 319–349). CRC Press.
6. Ghorbani, E., Adoko, A. C., & Yagiz, S. (2025). Disc cutter wear consumption prediction based on rock properties: An overview and perspective. In M. Khandelwal, D. J. Armaghani, P. Samui, & S. Yagiz (Eds.), Advancements in Underground Infrastructures (pp. 350–373). CRC Press.
7. Khandelwal, M., Armaghani, D. J., & Bhatawdekar, R. M., et al. (Eds.). (2025). Advancements in Underground Infrastructures. CRC Press.
8. Yazitova, A., Adoko, A. C., & Hassanpour, J., et al. (2025). Empirical models for estimating penetration rate of tunnel boring machines in rock mass. Bulletin of Engineering Geology and the Environment, 84(1), Article 55.
9. Ghorbani, E., & Yagiz, S. (2024). Estimating the penetration rate of tunnel boring machines via gradient boosting algorithms. Engineering Applications of Artificial Intelligence, 136, Article 108985.
10. Yagiz, S., Hassanpour, J., & Rostami, J. (2024). Introducing the concept of fracture index for performance prediction of hard rock TBMs. Eurock 2024 - ISRM Symposium: New Challenges in Rock Mechanics and Rock Engineering, 1–6.
11. Yagiz, S., Yazitova, A., & Smirnov, G., et al. (2024). Appraisal of boreability characteristics of rocks to estimate the TBM advancement. Proceedings of the 58th US Rock Mechanics/Geomechanics Symposium (ARMA), 1–5.
12. Ghorbani, E., & Yagiz, S. (2024). Predicting disc cutter wear using two optimized machine learning techniques. Archives of Civil and Mechanical Engineering, 24(2), Article 106.
13. Yazitova, A., & Yagiz, S. (2024). Performance analysis of drilling machines based on rock properties and machine's specifications. Bulletin of Engineering Geology and the Environment, 83(1), Article 37.
14. Jafarshirzad, P., Ghasemi, E., & Yagiz, S., et al. (2023). Evaluation of hard rock tunnel boring machine (TBM) performance using stochastic modeling. Geotechnical and Geological Engineering, 41(6), 3513–3529.
15. Hassanpour, J., Goodarzi, S., & Yagiz, S., et al. (2023). Soft sedimentary rocks and their boreability characteristics in mechanised tunnelling projects. Geomechanics and Tunnelling, 16(1), 28–37.
16. Massalov, T., Yagiz, S., & Adoko, A. C. (2022). Application of soft computing techniques to estimate cutter life index using mechanical properties of rocks. Applied Sciences, 12(3), Article 1446.
17. Yang, J., Yagiz, S., & Liu, Y. J., et al. (2022). Comprehensive evaluation of machine learning algorithms applied to TBM performance prediction. Underground Space, 7(1), 37–49.
18. Parsajoo, M., Mohammed, A. S., & Yagiz, S., et al. (2021). An evolutionary adaptive neuro-fuzzy inference system for estimating field penetration index of tunnel boring machine in rock mass. Journal of Rock Mechanics and Geotechnical Engineering, 13(5), 1038–1047.
19. Armaghani, D. J., Yagiz, S., & Mohamad, E. T., et al. (2021). Prediction of TBM performance in fresh through weathered granite using empirical and statistical approaches. Tunnelling and Underground Space Technology, 118, Article 104183.
20. Yermukhanbetov, K., Yazitova, A., & Yagiz, S. (2021). Comparison of strength-based rock brittleness indices with the brittleness index measured via Yagiz's approaches. IOP Conference Series: Earth and Environmental Science, 833(1), Article 012143.

Profile Details
https://research.nu.edu.kz/en/persons/saffet-yagiz/
https://scholar.google.com/citations?user=TCRn1P8AAAAJ&hl=tr
https://www.researchgate.net/profile/Saffet-Yagiz

WOS ResearcherID: W-9543-2019