Evaluation of blast-induced ground vibration predictors

Khandelwal, Manoj; Singh, T. N.

doi:10.1016/j.soildyn.2006.06.004

Cited by 227 publications

(105 citation statements)

References 5 publications

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“…Nevertheless, as a result, these empirical approaches are not good enough, whereas high degree of PPV estimation is required to determine blast safety area. This is maybe due to incorporation of only limited numbers of influential parameters on PPV (maximum charge per delay and distance from the blast face) in these predictors, whereas it is also influenced by other controllable or non-controllable parameters like burden, spacing, stemming, and powder factor (Singh and Singh 2005;Khandelwal and Singh 2007). Apart from empirical predictors, statistical techniques have been widely utilized for PPV prediction (e.g.…”

Section: Introductionmentioning

confidence: 99%

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Faradonbeh

Armaghani

Majid

et al. 2016

Int. J. Environ. Sci. Technol.

149

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Blasting is a widely used technique for rock fragmentation in opencast mines and tunneling projects. Ground vibration is one of the most environmental effects produced by blasting operation. Therefore, the proper prediction of blast-induced ground vibrations is essential to identify safety area of blasting. This paper presents a predictive model based on gene expression programming (GEP) for estimating ground vibration produced by blasting operations conducted in a granite quarry, Malaysia. To achieve this aim, a total number of 102 blasting operations were investigated and relevant blasting parameters were measured. Furthermore, the most influential parameters on ground vibration, i.e., burden-to-spacing ratio, hole depth, stemming, powder factor, maximum charge per delay, and the distance from the blast face were considered and utilized to construct the GEP model. In order to show the capability of GEP model in estimating ground vibration, nonlinear multiple regression (NLMR) technique was also performed using the same datasets. The results demonstrated that the proposed model is able to predict blast-induced ground vibration more accurately than other developed technique. Coefficient of determination values of 0.914 and 0.874 for training and testing datasets of GEP model, respectively show superiority of this model in predicting ground vibration, while these values were obtained as 0.829 and 0.790 for NLMR model.

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Section: Introductionmentioning

confidence: 99%

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Faradonbeh

Armaghani

Majid

et al. 2016

Int. J. Environ. Sci. Technol.

149

View full text Add to dashboard Cite

show abstract

“…DIN 41-50 1975;Khandelwal and Singh 2007;Lu et al 2002), that for the artificial seismic effects, like blasts in queries, pile hammering, traffic vibrations, the role of a "good" measure of intensity is played by peak ground velocity (PGV), sometimes called Peak Particle Velocity (PPV). It is so because acceleration records of seismic effects originating at very short distances are usually dominated by high frequencies.…”

Section: Rockbursts and Measures Of Their Intensity On The Ground Surmentioning

confidence: 99%

“…Dowding 1996; Khandelwal and Singh 2007), traffic vibrations excite buildings in the vicinity of roads or railways (e.g. Paolucci and Spinelli 2006), rockbursts originating from deep mining or reservoir induced seismicity (Knoll 1992;Gibowicz and Kijko 1994) also produce ground motion.…”

Section: Introductionmentioning

confidence: 99%

How to model rockburst seismic loads for civil engineering purposes?

Zembaty

2011

Bull Earthquake Eng

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Usually rockbursts from underground mining induce minor quakes of MM intensity up to V. Sometimes however the surface tremors reach level of MM epicentral intensity I 0 = VI to VIII. Since a fast industrial development often takes place in the mining areas then some seismic design rules for new buildings are needed. The main obstacle is then lack of respective design response spectrum and an unclear definition of the level of design acceleration to apply. Particularly the latter one is difficult to overcome because the rockburst ground motion records differ from natural earthquakes when it comes to their spectral properties as well as return periods. This paper presents a method how to rationally define the design acceleration so that a seismic code, e,g, Eurocode 8, can be applied in practical design procedures in the mining areas.

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“…Rao and Rao (2007) used NFT to predict the ground vibrations and frequencies caused by an explosion in an open pit mine. Khandelwal et al (2005) and Singh (2007 and In this paper, the effects of the vibrations caused by blasting on the nearby concrete structures at GOD were studied by 3-dimensional seismographs. Using the scaled distance parameter, a relation was proposed to predict the PPV caused by an explosion; and finally, the permissible amount of the explosive to be used for the explosion was estimated.…”

Section: Introductionmentioning

confidence: 99%

Safe Vibrations of Spilling Basin Explosions at “Gotvand Olya Dam” Using Artificial Neural Network

Amnieh¹,

Bahadori²

2014

Archives of Mining Sciences

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Ground vibration is an undesirable outcome of an explosion which can have destructive effects on the surrounding environment and structures. Peak Particle Velocity (PPV) is a determining factor in evaluation of the damage caused by an explosion. To predict the ground vibration caused by blasting at the Gotvand Olya Dam (GOD) spilling basin, thirty 3-component records (totally 90) from 19 blasts were obtained using 3 VIBROLOC seismographs. Minimum and the maximum distance from the center of the exploding block to the recording station were set to be 11 and 244 meters, respectively. To evaluate allowable safe vibration and determining the permissible explosive charge weight, Artificial Neural Networks (ANN) was employed with Back Propagation (BP) and 3 hidden layers. The mean square error and the correlation coefficient of the network in this study were found to be 1.95 and 0.995, respectively, which compared to those obtained from the known empirical correlations, indicating substantially more accurate prediction. Considering the network high accuracy and precision in predicting vibrations caused by such blasting operations, the nearest distance from the center of the exploding block at this study was 11 m, and considering the standard allowable vibration of 120 mm/sec for heavy concrete structures, the maximum permissible explosive weight per delay was estimated to be 47.00 Kg. These results could be employed in subsequent safer blasting operation designs. Keywords: Ground vibration, Safe explosion, Gotvand Olya Dam, Artificial Neural Network (ANN)Wibracje gruntu to niepożądany skutek prowadzenia prac strzałowych, które mogą negatywnie wpływać na otaczające środowisko oraz znajdujące się w sąsiedztwie budowle. Głównym wskaźnikiem używanym przy określaniu szkód spowodowanych przez wybuchy jest wskaźnik maksymalnej prędkości cząstek (PPV). Przy prognozowaniu wibracji terenu wskutek prac strzałowych prowadzonych na tamie Gotvand Olya i w zbiorniku zbadano zapisy 3-składnikowych prędkości ( w sumie 90 zapisów) z 13 wybuchów zarejestrowane przy użyciu sejsmografu 3 VIBROLOC. Maksymalna i minimalna odległość pomiędzy środkiem rozkruszanego bloku a stacją rejestrującą ustawiona została na poziomie 244 i 11 m. W celu określenia bezpiecznego poziomu drgań oraz dopuszczalnej wagi ładunku, zastosowano podejście wykorzystujące sieci neuronowe, z wykorzystaniem metody propagacji wstecznej i trzech warstw ukrytych. Błąd średniokwadratowy i współczynnik korelacji sieci wyniosły 1.95 i 0.95, co pozostaje w zgodności z danym uzyskiwanymi z obserwacji empirycznych, wskazując na poprawność i dokładność prognoz. Zakładając wysoki poziom dokładności sieci oraz wysoką dokładność w prognozowaniu poziomu drgań wywołanych przez prace strzałowe, przyjęto że najbliższa odległość od środka rozkruszanego bloku wyniesie 11 m. Uwzględniając standardowe dopuszczalne w przypadku ciężkich budowli betonowych poziomy drgań w wysokości 120 m/s, oszacowano że maksymalna dopuszczalna masa ładunku wyniesie 47.00 Kg, w przeliczeniu na jeden okres zwłok...

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Evaluation of blast-induced ground vibration predictors

Cited by 227 publications

References 5 publications

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

How to model rockburst seismic loads for civil engineering purposes?

Safe Vibrations of Spilling Basin Explosions at “Gotvand Olya Dam” Using Artificial Neural Network

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