Blast Vibration Prediction

Research output: Contribution to conferenceAbstractpeer-review

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Blast Vibration Prediction. / Trabi, Bernd; Bleibinhaus, Florian.
2023. Abstract from EGU General Assembly 2023, Vienna, Austria.

Research output: Contribution to conferenceAbstractpeer-review

Harvard

Trabi, B & Bleibinhaus, F 2023, 'Blast Vibration Prediction', EGU General Assembly 2023, Vienna, Austria, 23/04/23 - 28/04/23.

APA

Trabi, B., & Bleibinhaus, F. (2023). Blast Vibration Prediction. Abstract from EGU General Assembly 2023, Vienna, Austria.

Vancouver

Trabi B, Bleibinhaus F. Blast Vibration Prediction. 2023. Abstract from EGU General Assembly 2023, Vienna, Austria.

Author

Trabi, Bernd ; Bleibinhaus, Florian. / Blast Vibration Prediction. Abstract from EGU General Assembly 2023, Vienna, Austria.

Bibtex - Download

@conference{06b46ad7971b4129bab98a86ec1b0afe,
title = "Blast Vibration Prediction",
abstract = "Predicting the peak ground velocity (PGV) of blast vibrations is important for blast mining in order to set the right amount of charge weights so that they do not exceed certain thresholds. One problem is the large dispersion in the observed PGV due to unknown complexity of seismic waves spread. Classical prediction methods most often use one of several empirical formulas. One very common method is the Scaled Distance (SD) approach, which has the fewest parameters to calibrate, is widely used and works for a single sensor. In this study, we use a dataset of 55 mining production blasts recorded by 81 seismic sensors to compare the performance of the different methods. The large array allows us to apply multi-sensor inversion, which gives more information about the physical meaning of various parameters. Our results show that classical SD methods are less suitable, at least on the site we reviewed, as the data contradicts the previous link between the radial amplitude decay constant b and the load weight exponent c. For the last we find a value of 0.5, which we express as an expression of the physical relationship between the charge, energy and amplitude, suggesting that it may be a global value independent of the specific site.",
author = "Bernd Trabi and Florian Bleibinhaus",
year = "2023",
month = apr,
language = "English",
note = "EGU General Assembly 2023, EGU 2023 ; Conference date: 23-04-2023 Through 28-04-2023",
url = "https://www.egu23.eu/",

}

RIS (suitable for import to EndNote) - Download

TY - CONF

T1 - Blast Vibration Prediction

AU - Trabi, Bernd

AU - Bleibinhaus, Florian

PY - 2023/4

Y1 - 2023/4

N2 - Predicting the peak ground velocity (PGV) of blast vibrations is important for blast mining in order to set the right amount of charge weights so that they do not exceed certain thresholds. One problem is the large dispersion in the observed PGV due to unknown complexity of seismic waves spread. Classical prediction methods most often use one of several empirical formulas. One very common method is the Scaled Distance (SD) approach, which has the fewest parameters to calibrate, is widely used and works for a single sensor. In this study, we use a dataset of 55 mining production blasts recorded by 81 seismic sensors to compare the performance of the different methods. The large array allows us to apply multi-sensor inversion, which gives more information about the physical meaning of various parameters. Our results show that classical SD methods are less suitable, at least on the site we reviewed, as the data contradicts the previous link between the radial amplitude decay constant b and the load weight exponent c. For the last we find a value of 0.5, which we express as an expression of the physical relationship between the charge, energy and amplitude, suggesting that it may be a global value independent of the specific site.

AB - Predicting the peak ground velocity (PGV) of blast vibrations is important for blast mining in order to set the right amount of charge weights so that they do not exceed certain thresholds. One problem is the large dispersion in the observed PGV due to unknown complexity of seismic waves spread. Classical prediction methods most often use one of several empirical formulas. One very common method is the Scaled Distance (SD) approach, which has the fewest parameters to calibrate, is widely used and works for a single sensor. In this study, we use a dataset of 55 mining production blasts recorded by 81 seismic sensors to compare the performance of the different methods. The large array allows us to apply multi-sensor inversion, which gives more information about the physical meaning of various parameters. Our results show that classical SD methods are less suitable, at least on the site we reviewed, as the data contradicts the previous link between the radial amplitude decay constant b and the load weight exponent c. For the last we find a value of 0.5, which we express as an expression of the physical relationship between the charge, energy and amplitude, suggesting that it may be a global value independent of the specific site.

M3 - Abstract

T2 - EGU General Assembly 2023

Y2 - 23 April 2023 through 28 April 2023

ER -