scholarly journals Effect of discontinuity dip direction on hard rock pillar strength

Transactions ◽  
2018 ◽  
Vol 344 (1) ◽  
pp. 25-30
Author(s):  
K.V. Jessu ◽  
T.R. Kostecki ◽  
A.J.S. Spearing ◽  
G.S. Esterhuizen
Keyword(s):  
Hard Rock ◽  
Rock Pillar ◽  
Pillar Strength

scholarly journals Predicting Hard Rock Pillar Stability Using GBDT, XGBoost, and LightGBM Algorithms

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 765 ◽  
Author(s):  
Weizhang Liang ◽  
Suizhi Luo ◽  
Guoyan Zhao ◽  
Hao Wu
Keyword(s):  
Large Scale ◽  
Prediction Models ◽  
Hard Rock ◽  
Gradient Boosting ◽  
Pillar Stability ◽  
Rock Pillar ◽  
Light Gradient ◽  
Gradient Boosting Machine ◽  
Extreme Gradient Boosting ◽  
Hard Rock Mines

Predicting pillar stability is a vital task in hard rock mines as pillar instability can cause large-scale collapse hazards. However, it is challenging because the pillar stability is affected by many factors. With the accumulation of pillar stability cases, machine learning (ML) has shown great potential to predict pillar stability. This study aims to predict hard rock pillar stability using gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM) algorithms. First, 236 cases with five indicators were collected from seven hard rock mines. Afterwards, the hyperparameters of each model were tuned using a five-fold cross validation (CV) approach. Based on the optimal hyperparameters configuration, prediction models were constructed using training set (70% of the data). Finally, the test set (30% of the data) was adopted to evaluate the performance of each model. The precision, recall, and F1 indexes were utilized to analyze prediction results of each level, and the accuracy and their macro average values were used to assess the overall prediction performance. Based on the sensitivity analysis of indicators, the relative importance of each indicator was obtained. In addition, the safety factor approach and other ML algorithms were adopted as comparisons. The results showed that GBDT, XGBoost, and LightGBM algorithms achieved a better comprehensive performance, and their prediction accuracies were 0.8310, 0.8310, and 0.8169, respectively. The average pillar stress and ratio of pillar width to pillar height had the most important influences on prediction results. The proposed methodology can provide a reliable reference for pillar design and stability risk management.

scholarly journals An in situ monitoring campaign of a hard rock pillar at great depth within a Canadian mine

2020 ◽  
Vol 12 (3) ◽  
pp. 427-448
Author(s):  
Bradley Forbes ◽  
Nicholas Vlachopoulos ◽  
Mark S. Diederichs ◽  
Andrew J. Hyett ◽  
Allan Punkkinen
Keyword(s):  
Hard Rock ◽  
Great Depth ◽  
In Situ Monitoring ◽  
Monitoring Campaign ◽  
Rock Pillar

scholarly journals A Parametric Study of Blast Damage on Hard Rock Pillar Strength

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1901 ◽  
Author(s):  
Kashi Jessu ◽  
Anthony Spearing ◽  
Mostafa Sharifzadeh
Keyword(s):  
Parametric Study ◽  
Hard Rock ◽  
Numerical Models ◽  
Underground Mines ◽  
Pillar Stability ◽  
Pillar Strength ◽  
Blast Damage ◽  
Rock Pillars ◽  
Economic Standpoint ◽  
Safe Working

Pillar stability is an important factor for safe working and from an economic standpoint in underground mines. This paper discusses the effect of blast damage on the strength of hard rock pillars using numerical models through a parametric study. The results indicate that blast damage has a significant impact on the strength of pillars with larger width-to-height (W/H) ratios. The blast damage causes softening of the rock at the pillar boundaries leading to the yielding of the pillars in brittle fashion beyond the blast damage zones. The models show that the decrease in pillar strength as a consequence of blasting is inversely correlated with increasing pillar height at a constant W/H ratio. Inclined pillars are less susceptible to blast damage, and the damage on the inclined sides has a greater impact on pillar strength than on the normal sides. A methodology to analyze the blast damage on hard rock pillars using FLAC3D is presented herein.

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