A review of techniques, advances and outstanding issues in numerical modelling for rock mechanics and rock engineering

L Jing - International Journal of Rock Mechanics and Mining …, 2003 - Elsevier
The purpose of this review paper is to present the techniques, advances, problems and
likely future developments in numerical modelling for rock mechanics. Such modelling is …

Numerical methods in rock mechanics

L Jing, JA Hudson - International Journal of Rock Mechanics and Mining …, 2002 - Elsevier
The purpose of this CivilZone review paper is to present the techniques, advances,
problems and likely future development directions in numerical modelling for rock …

Carbon and energy storage in salt caverns under the background of carbon neutralization in China

X Wei, S Ban, X Shi, P Li, Y Li, S Zhu, K Yang, W Bai… - Energy, 2023 - Elsevier
China plans to reach the peak of its CO 2 emissions in 2030 and achieve carbon neutrality
in 2060. Salt caverns are excellent facilities for underground energy storage, and they can …

Tensile strength prediction of rock material using non-destructive tests: A comparative intelligent study

M Parsajoo, DJ Armaghani, AS Mohammed… - Transportation …, 2021 - Elsevier
Tensile strength of rock plays a significant role in the design of tunnels and underground
engineering projects. Due to the inefficiency of direct method in determining rock tensile …

Prediction of seismic slope stability through combination of particle swarm optimization and neural network

B Gordan, D Jahed Armaghani, M Hajihassani… - Engineering with …, 2016 - Springer
One of the main concerns in geotechnical engineering is slope stability prediction during the
earthquake. In this study, two intelligent systems namely artificial neural network (ANN) and …

Prediction of uniaxial compressive strength of rock samples using hybrid particle swarm optimization-based artificial neural networks

E Momeni, DJ Armaghani, M Hajihassani, MFM Amin - Measurement, 2015 - Elsevier
Many attempts have been made to predict unconfined compressive strength (UCS) of rocks
using back-propagation (BP) artificial neural network (ANN). However, BP-ANN suffers from …

Prediction of blast-induced ground vibration using artificial neural network

M Khandelwal, TN Singh - International Journal of Rock Mechanics and …, 2009 - Elsevier
An attempt has been made to evaluate and predict the blast-induced ground vibration and
frequency by incorporating rock properties, blast design and explosive parameters using the …

[HTML][HTML] Comparative evaluation of different statistical tools for the prediction of uniaxial compressive strength of rocks

A Teymen, EC Mengüç - International Journal of Mining Science and …, 2020 - Elsevier
In this study, uniaxial compressive strength (UCS), unit weight (UW), Brazilian tensile
strength (BTS), Schmidt hardness (SHH), Shore hardness (SSH), point load index (Is 50) …

Predicting tunnel boring machine performance through a new model based on the group method of data handling

M Koopialipoor, SS Nikouei, A Marto… - Bulletin of Engineering …, 2019 - Springer
The tunnel boring machine (TBM), developed within the past few decades, is designed to
make the process of tunnel excavation safer and more economical. The use of TBMs in civil …

Anisotropic strength and deformational behavior of Himalayan schists

MHB Nasseri, KS Rao, T Ramamurthy - International Journal of Rock …, 2003 - Elsevier
Anisotropy, which is characteristic of metamorphic rocks such as schists, is due to a process
of metamorphic differentiation. Preferred orientation of minerals like mica and chlorite in …