Blast vibration prediction

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Blast vibration prediction. / Trabi, Bernd; Bleibinhaus, Florian.
in: Geophysical prospecting, Jahrgang 71.2023, Nr. 7, 10.04.2023, S. 1312-1324.

Publikationen: Beitrag in FachzeitschriftArtikelForschung(peer-reviewed)

Vancouver

Trabi B, Bleibinhaus F. Blast vibration prediction. Geophysical prospecting. 2023 Apr 10;71.2023(7):1312-1324. Epub 2023 Apr 10. doi: 10.1111/1365-2478.13361

Author

Trabi, Bernd ; Bleibinhaus, Florian. / Blast vibration prediction. in: Geophysical prospecting. 2023 ; Jahrgang 71.2023, Nr. 7. S. 1312-1324.

Bibtex - Download

@article{4024c75483c44057b4c54dcd73105eae,
title = "Blast vibration prediction",
abstract = "Predicting the peak ground velocity of vibrations is essential to blast mining operationsin order to design the charge weights so as not to exceed certain thresholds that pre-vent damage to buildings and other infrastructure. The problem is usually marred by alarge scatter of observed peak ground velocity due to unknown complexities of seismicwave propagation. Classic peak ground velocity prediction methods employ empiricalformulas, the most widespread being the scaled distance approach that has the leastparameters to calibrate and works for a single sensor. In this study, we used data from55 mining production blasts recorded by an array of 81 seismic sensors in an open pitiron ore mine in Austria. We evaluated and compared different methods for predictingpeak ground velocity. The large data set provides sufficient constraint to independentlyresolve the charge weight exponentc, the radial decay constantband local site factors.Thec/b-ratio of 0.2 that we find for our site is far smaller than that implied by the USBureau of Mining scaled distance method, and peak ground velocity predictions madewith the latter approach are significantly worse. This highlights the importance of usingsite-specific data to calibrate predictive models and suggests that relying on arbitrarypriors may lead to inaccurate predictions. For the charge weight exponent, we find avalue of 0.5 which we interpret as expression of the physical relationship among chargeweight, energy and amplitude, suggesting that this may be a global, site-independent,value. This result has probable a broader relevance beyond our specific location andcould improve prediction outcomes on other sites.",
keywords = "blast vibration prediction, blast vibration, Parameter estimation, regression analysis, inversion, production blasts",
author = "Bernd Trabi and Florian Bleibinhaus",
note = "Publisher Copyright: {\textcopyright} 2023 The Authors. Geophysical Prospecting published by John Wiley & Sons Ltd on behalf of European Association of Geoscientists & Engineers.",
year = "2023",
month = apr,
day = "10",
doi = "10.1111/1365-2478.13361",
language = "English",
volume = "71.2023",
pages = "1312--1324",
journal = "Geophysical prospecting",
issn = "0016-8025",
publisher = "Wiley-Blackwell, Gro{\ss}britannien",
number = "7",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Blast vibration prediction

AU - Trabi, Bernd

AU - Bleibinhaus, Florian

N1 - Publisher Copyright: © 2023 The Authors. Geophysical Prospecting published by John Wiley & Sons Ltd on behalf of European Association of Geoscientists & Engineers.

PY - 2023/4/10

Y1 - 2023/4/10

N2 - Predicting the peak ground velocity of vibrations is essential to blast mining operationsin order to design the charge weights so as not to exceed certain thresholds that pre-vent damage to buildings and other infrastructure. The problem is usually marred by alarge scatter of observed peak ground velocity due to unknown complexities of seismicwave propagation. Classic peak ground velocity prediction methods employ empiricalformulas, the most widespread being the scaled distance approach that has the leastparameters to calibrate and works for a single sensor. In this study, we used data from55 mining production blasts recorded by an array of 81 seismic sensors in an open pitiron ore mine in Austria. We evaluated and compared different methods for predictingpeak ground velocity. The large data set provides sufficient constraint to independentlyresolve the charge weight exponentc, the radial decay constantband local site factors.Thec/b-ratio of 0.2 that we find for our site is far smaller than that implied by the USBureau of Mining scaled distance method, and peak ground velocity predictions madewith the latter approach are significantly worse. This highlights the importance of usingsite-specific data to calibrate predictive models and suggests that relying on arbitrarypriors may lead to inaccurate predictions. For the charge weight exponent, we find avalue of 0.5 which we interpret as expression of the physical relationship among chargeweight, energy and amplitude, suggesting that this may be a global, site-independent,value. This result has probable a broader relevance beyond our specific location andcould improve prediction outcomes on other sites.

AB - Predicting the peak ground velocity of vibrations is essential to blast mining operationsin order to design the charge weights so as not to exceed certain thresholds that pre-vent damage to buildings and other infrastructure. The problem is usually marred by alarge scatter of observed peak ground velocity due to unknown complexities of seismicwave propagation. Classic peak ground velocity prediction methods employ empiricalformulas, the most widespread being the scaled distance approach that has the leastparameters to calibrate and works for a single sensor. In this study, we used data from55 mining production blasts recorded by an array of 81 seismic sensors in an open pitiron ore mine in Austria. We evaluated and compared different methods for predictingpeak ground velocity. The large data set provides sufficient constraint to independentlyresolve the charge weight exponentc, the radial decay constantband local site factors.Thec/b-ratio of 0.2 that we find for our site is far smaller than that implied by the USBureau of Mining scaled distance method, and peak ground velocity predictions madewith the latter approach are significantly worse. This highlights the importance of usingsite-specific data to calibrate predictive models and suggests that relying on arbitrarypriors may lead to inaccurate predictions. For the charge weight exponent, we find avalue of 0.5 which we interpret as expression of the physical relationship among chargeweight, energy and amplitude, suggesting that this may be a global, site-independent,value. This result has probable a broader relevance beyond our specific location andcould improve prediction outcomes on other sites.

KW - blast vibration prediction

KW - blast vibration

KW - Parameter estimation

KW - regression analysis

KW - inversion

KW - production blasts

UR - http://www.scopus.com/inward/record.url?scp=85161392070&partnerID=8YFLogxK

U2 - 10.1111/1365-2478.13361

DO - 10.1111/1365-2478.13361

M3 - Article

VL - 71.2023

SP - 1312

EP - 1324

JO - Geophysical prospecting

JF - Geophysical prospecting

SN - 0016-8025

IS - 7

ER -