[HTML][HTML] Application of artificial intelligence to rock mechanics: An overview

AI Lawal, S Kwon - Journal of Rock Mechanics and Geotechnical …, 2021 - Elsevier
Different artificial intelligence (AI) methods have been applied to various aspects of rock
mechanics, but the fact that none of these methods have been used as a standard implies …

State-of-the-art review of machine learning and optimization algorithms applications in environmental effects of blasting

J Zhou, Y Zhang, Y Qiu - Artificial Intelligence Review, 2024 - Springer
The technological difficulties related with blasting operations have become increasingly
significant. It is crucial to give due consideration to the evaluation of rock fragmentation and …

[HTML][HTML] Prediction of blasting mean fragment size using support vector regression combined with five optimization algorithms

E Li, F Yang, M Ren, X Zhang, J Zhou… - Journal of Rock …, 2021 - Elsevier
The main purpose of blasting operation is to produce desired and optimum mean size rock
fragments. Smaller or fine fragments cause the loss of ore during loading and transportation …

Compressive strength of sandy soils stabilized with alkali-activated volcanic ash and slag

N Shariatmadari, H Hasanzadehshooiili… - Journal of Materials in …, 2021 - ascelibrary.org
In recent years, compared with the traditional portland cement, environmentally friendly
geopolymers have gained more attention as construction materials. This paper considered …

[HTML][HTML] A comparative study on the application of various artificial neural networks to simultaneous prediction of rock fragmentation and backbreak

A Sayadi, M Monjezi, N Talebi, M Khandelwal - Journal of Rock Mechanics …, 2013 - Elsevier
In blasting operation, the aim is to achieve proper fragmentation and to avoid undesirable
events such as backbreak. Therefore, predicting rock fragmentation and backbreak is very …

[HTML][HTML] Prediction of UCS and CBR of microsilica-lime stabilized sulfate silty sand using ANN and EPR models; application to the deep soil mixing

A Ghorbani, H Hasanzadehshooiili - Soils and foundations, 2018 - Elsevier
Desert sands in Iran, which usually contain small amounts of silt and sulfate, do not have
significant strength, and thus, are not suitable for foundations or road construction. This …

An uncertainty hybrid model for risk assessment and prediction of blast-induced rock mass fragmentation

S Hosseini, R Poormirzaee, M Hajihassani - International Journal of Rock …, 2022 - Elsevier
Blasting is an important mining operation that usually produce several damaging
consequences. Adverse rock fragmentation due to bench blasting is one of them. Hence …

A rock engineering systems based model to predict rock fragmentation by blasting

F Faramarzi, H Mansouri, MAE Farsangi - International Journal of Rock …, 2013 - Elsevier
A new model for prediction of rock fragmentation by blasting is presented based upon the
basic concepts of rock engineering systems (RES). The newly proposed approach involves …

Support vector machines approach to mean particle size of rock fragmentation due to bench blasting prediction

X Shi, Z Jian, B Wu, D Huang, WEI Wei - Transactions of Nonferrous Metals …, 2012 - Elsevier
Aiming at the problems of the traditional method of assessing distribution of particle size in
bench blasting, a support vector machines (SVMs) regression methodology was used to …

A fractal fragmentation model for rockfalls

R Ruiz-Carulla, J Corominas, O Mavrouli - Landslides, 2017 - Springer
The impact-induced rock mass fragmentation in a rockfall is analyzed by comparing the in
situ block size distribution (IBSD) of the rock mass detached from the cliff face and the …