Peak particle velocity as an indicator of dynamic load exerted on the support of underground workings

Mutke, Grzegorz

doi:10.13168/agg.2016.0019

Cited by 22 publications

(20 citation statements)

References 10 publications

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“…Seismic wave packets generated by blasting in underground mines propagate in rock mass in all directions. The propagation depends on many parameters, such as structure of material, stress/strain state and the frequency of waves [9,10]. Basically, seismic waves are subjected to scattering, reflection etc.…”

Section: Comparison Of Numerical Model With Seismic Measurements Resultsmentioning

confidence: 99%

Seismic Peak Partcile Velocity and Acceleration Response to Mining Faces Firing in a Light of Numerical Modeling and Underground Measurements

Pytel¹,

Mertuszka²,

Lurka³

et al. 2018

SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings

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Extraction of the copper ore deposit in the Legnica-Głogów Copper Basin in Poland is usually associated with high seismic activity. In order to face this threats, a number of organizational and technical prevention methods are utilized, from which blasting works seem to be the most effective. A significant number of recorded dynamic events may be clearly and directly explained by the effects of this approach. It is also expected, that the simultaneous firing of a number of mining faces may provide the amplification of vibrations in a specific location chosen within the rock mass. For better recognition of a such process, formation of an elastic wave generated by the detonation of explosives in a single mining face have been evaluated using the numerical tools and verified by the field measurements of ground particle velocity and acceleration parameters, i.e. PPV and PPA parameters. The primary objective of presented paper was to find the bridge between numerical simulations of the time-dependent seismic particle velocity values induced by blasting and in situ measurements using seismic three component geophones.

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Section: Comparison Of Numerical Model With Seismic Measurements Resultsmentioning

confidence: 99%

Seismic Peak Partcile Velocity and Acceleration Response to Mining Faces Firing in a Light of Numerical Modeling and Underground Measurements

Pytel¹,

Mertuszka²,

Lurka³

et al. 2018

SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings

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show abstract

“…The initial form of blasting radiated energy is a short seismic wave with high intensity accompanied by a gas reaction with high pressure. These two types of energy sources arise in a way that makes it difficult to quantify their contribution to blast damage individually [5]. The strain-induced within a rock mass due to detonation is proportional to the peak of particles velocity (PPV) [62].…”

Section: A Prediction Modelmentioning

confidence: 99%

“…During vibration, each particle has a velocity, and the highest velocity is called peak particle velocity (PPV). These PPV readings are accepted and used as the base for calculating explosion vibration strength [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Development of an Optimized Regression Model to Predict Blast-Driven Ground Vibrations

et al. 2021

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Ground vibrations caused by blasting operations in cement canisters is among the main mining issues that cause significant disruptions to nearby buildings and infrastructure. This research was performed in a limestone quarry situated southeast of Helwan City, Egypt, to investigate the impact of ground motion vibration due to cement blast action in limestone rocks. To reduce the environmental impact of quarry blasting, continuous monitoring, and accurate medium's peak particle velocity (PPV) assessment are required. Recently, machine learning (ML) models are employed in diverse applications. The default hyperparameters of such models must be modified to fit the problem concerned. The hyperparameters optimization for ML models impacts the employed model's performance and efficiency. In this research, different regression models are implemented for predicting the PPV values. A dataset representing 1438 blast incidents in the Helwan area was built and utilized to evaluate the considered ML models. This dataset incorporates the relationship of the ground vibration amplitude to both the explosive charge weight per delay and distance from the blast. The predictive models' output performance has been evaluated using the root-mean-squared error (RMSE) and the coefficient of determination (R 2). The PPV dataset has been divided into training and testing data to produce statistically significant results and to make the dataset more representative to avoid overfitting. The utilized test PPV dataset acts as a proxy for any new PPV data prediction. There was evidence of higher performance in the developed Decision Trees model with the lowest RMSE and the highest R 2 on training and testing data. The decision tree is, therefore, an acceptable algorithm for the construction of a predictive PPV model for other quarry blasting areas with conditions identical to those in Helwan. Finally, comparative experimental results have shown that optimized models can predict PPV values with lower errors and greater prediction accuracy.

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“…Strain and dynamic stress can be determined from the value of PPV [30]. Dynamic stress σ corresponding to the PPV of the material due to blasting was [31,32] σ � K n PPV,…”

Section: Analysis Of Blasting Stress Based On Ppvmentioning

confidence: 99%

Safety Distance of Shotcrete Subjected to Blasting Vibration in Large‐Span High‐Speed Railway Tunnels

Zhang

Fang

et al. 2019

Shock and Vibration

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e drill and blast method is widely used in constructing tunnels in rock. Unfortunately, blasting vibration can damage newly performed shotcrete layers which are major support structures to stabilize surrounding structures. erefore, investigation of the influence of blasting on shotcrete and determining reasonable distance between blasting work face and shotcrete position is of great importance. In this paper, a large-span tunnel excavated by drill and blast method acting as a high-speed railway station has been investigated. Blast vibration in the tunnel was recorded using microseismic monitoring technique. Empirical prediction equations for peak particle velocity (PPV) were obtained through regression analysis based on the obtained monitoring data. e attenuation law of tensile stress imposed on shotcrete layer due to blasting and bond strength of shotcrete-rock interface was also investigated. Minimum safety distance between shotcrete and blasting positions was calculated based on bond failure criterion. Evolution law considering different factors including blasting charge, rock mass class, and setting time of shotcrete was also obtained, which could be applied to determine blast charge shotcrete arrangements for tunnel constructions in future. e obtained results showed that the safety of shotcrete could be ensured and shotcrete falling off the rock could be prevented under current blast constructions.

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Peak particle velocity as an indicator of dynamic load exerted on the support of underground workings

Cited by 22 publications

References 10 publications

Seismic Peak Partcile Velocity and Acceleration Response to Mining Faces Firing in a Light of Numerical Modeling and Underground Measurements

Seismic Peak Partcile Velocity and Acceleration Response to Mining Faces Firing in a Light of Numerical Modeling and Underground Measurements

Development of an Optimized Regression Model to Predict Blast-Driven Ground Vibrations

Safety Distance of Shotcrete Subjected to Blasting Vibration in Large‐Span High‐Speed Railway Tunnels

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