Correlating the Unconfined Compressive Strength of Rock with the Compressional Wave Velocity Effective Porosity and Schmidt Hammer Rebound Number Using Artificial Neural Networks-Reference-Cited by-同舟云学术

Correlating the Unconfined Compressive Strength of Rock with the Compressional Wave Velocity Effective Porosity and Schmidt Hammer Rebound Number Using Artificial Neural Networks

Published:2022-07-29 Issue:11 Volume:55 Page:6805-6840
ISSN:0723-2632
Container-title:Rock Mechanics and Rock Engineering
language:en
Short-container-title:Rock Mech Rock Eng

Author:

Le Tien-Thinh,Skentou Athanasia D.,Mamou Anna,Asteris Panagiotis G.^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Geology,Geotechnical Engineering and Engineering Geology,Civil and Structural Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00603-022-02992-8.pdf

Reference138 articles.

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2. Aggistalis G, Alivizatos A, Stamoulis D, Stournaras G (1996) Correlating uniaxial compressive strength with Schmidt hardness, point load index, young’s modulus, and mineralogy of gabbros and basalts (Northern Greece). Bull Int Assoc Eng Geol. https://doi.org/10.1007/BF02600650

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4. Akram MS, Farooq S, Naeem M, Ghazi S (2017) Prediction of mechanical behaviour from mineralogical composition of Sakesar limestone, Central Salt Range, Pakistan. Bull Eng Geol Environ 76:601–615. https://doi.org/10.1007/s10064-016-1002-3

5. Altindag R (2012) Correlation between P-wave velocity and some mechanical properties for sedimentary rocks. J South Afr Inst Min Metall 112:229–237

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