Vibration Simulation Method to Control Stability in the Northeast Corner of Escondida Mine

Valdivia, César Humberto Guzmán; Vega, Márcia Peixoto; Scherpenisse, C. R.; Adamson, W.R.

doi:10.1076/frag.7.2.63.15897

Cited by 6 publications

(4 citation statements)

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“…However, the amount of explosives detonated per delay (as a controllable parameter) can be estimated using an empirical formula that can account for geological and blast design conditions 10 . Valdivia et al 14 and Rossmanith et al 15 demonstrated the significance of a number of variables whose modifications can affect vibration reduction and blasting operation enhancement. Several literature works revealed a plethora of papers on blast-induced effects, most of which described ground vibration as a difficult byproduct of explosive use in the mine as a technique for rock excavation.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the ground vibration during blasting in mining projects using different computational approaches

Hosseini,

Khatti,

Taiwo

et al. 2023

Sci Rep

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The investigation compares the conventional, advanced machine, deep, and hybrid learning models to introduce an optimum computational model to assess the ground vibrations during blasting in mining projects. The long short-term memory (LSTM), artificial neural network (ANN), least square support vector machine (LSSVM), ensemble tree (ET), decision tree (DT), Gaussian process regression (GPR), support vector machine (SVM), and multilinear regression (MLR) models are employed using 162 data points. For the first time, the blackhole-optimized LSTM model has been used to predict the ground vibrations during blasting. Fifteen performance metrics have been implemented to measure the prediction capabilities of computational models. The study concludes that the blackhole optimized-LSTM model PPV11 is highly capable of predicting ground vibration. Model PPV11 has assessed ground vibrations with RMSE = 0.0181 mm/s, MAE = 0.0067 mm/s, R = 0.9951, a20 = 96.88, IOA = 0.9719, IOS = 0.0356 in testing. Furthermore, this study reveals that the prediction accuracy of hybrid models is less affected by multicollinearity because of the optimization algorithm. The external cross-validation and literature validation confirm the prediction capabilities of model PPV11. The ANOVA and Z tests reject the null hypothesis for actual ground vibration, and the Anderson–Darling test rejects the null hypothesis for predicted ground vibration. This study also concludes that the GPR and LSSVM models overfit because of moderate to problematic multicollinearity in assessing ground vibration during blasting.

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Section: Introductionmentioning

confidence: 99%

Assessment of the ground vibration during blasting in mining projects using different computational approaches

Hosseini,

Khatti,

Taiwo

et al. 2023

Sci Rep

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“…In a larger blast it's impossible to completely avoid the superposition and amplification of the vibrations. This is because the period of the vibration is always significantly higher than the effective delays used between the charges in smaller blasts [6].…”

Section: Introductionmentioning

confidence: 99%

Airblast and Ground Vibration Monitoring at Chimiwungo Pit

Kabwe¹,

Wang²

2016

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Impacts of airblast and vibrations arise from blasting, a dangerous activity if not designed and performed to standard. This paper evaluates airblast and ground vibration levels and its potential impact on the neighbouring communities. Two calibrated seismographs were used to monitor potential airblast and ground vibration generated from the blast at Chimiwungo Pit. The blast complied with the set limits for infrastructures and slopes monitoring. Vibrations recorded from the trial shot PPV were predicted at 2.46 mm/s and Airblast of 10 mm/s with a maximum of 134 dB at the mine boundary, all remained well below accepted industry standards and guidelines. The airblast and ground vibration levels monitored and recorded were considered to be normal for surface blasting operations and had no negative impact on the nearby township of Manyama.

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“…It differs from the ground vibrations caused by earthquakes in terms of seismic source, amount of available energy and travelled distances (Giraudi et al, 2009). Over years, many studies have been conducted to assess and control ground vibration due to blasting operations (Blair and Jiang, 1995;Bhandari, 1997;Siskind, 2000;Kahriman, 2002;Valdivia et al, 2003;Kahriman, 2004;Kuzu and Ergin, 2005;Singh et al, 2006;Uysal et al, 2007;Kuzu, 2008;Ozer et al, 2008;Ak et al, 2009;Mesec et al, 2010;Singh and Verma, 2010). The intensity of ground vibration arising from rock blasting depends on various parameters.…”

Section: Introductionmentioning

confidence: 99%

Development of a fuzzy model for predicting ground vibration caused by rock blasting in surface mining

Ghasemi

Ataei

Hashemolhosseini

2012

Journal of Vibration and Control

128

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Ground vibration is an integral part of the rock blasting process in surface mines, which may cause severe damages to structures and plants in the nearby environment. Therefore, its prediction plays an important role in the minimization of environmental impacts. The peak particle velocity (PPV) is an important predictor for ground vibration. In this paper, first a fuzzy logic model was developed to predict PPV based on collected data from blasting events in Sarcheshmeh copper mine, located in the southwest of Iran. The predictive fuzzy model was implemented on the fuzzy logic toolbox of MATLAB using the Mamdani algorithm. Then, the PPV was predicted by conventional empirical predictors used in blasting practice and also by multiple regression analysis. Finally, a comparative analysis between the results obtained by the fuzzy model and common vibration predictors was carried out. The results indicated the high predictive capacity of fuzzy model, which can be used as a reliable predictor of ground vibration for the studied mine.

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Vibration Simulation Method to Control Stability in the Northeast Corner of Escondida Mine

Cited by 6 publications

References 0 publications

Assessment of the ground vibration during blasting in mining projects using different computational approaches

Assessment of the ground vibration during blasting in mining projects using different computational approaches

Airblast and Ground Vibration Monitoring at Chimiwungo Pit

Development of a fuzzy model for predicting ground vibration caused by rock blasting in surface mining

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