Application of an Expert System for the Assessment of Blast Vibration

Khandelwal, Manoj

doi:10.1007/s10706-011-9463-4

Cited by 17 publications

(2 citation statements)

References 21 publications

(17 reference statements)

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“…Neurons are basic operating units, and they are connected to the next layer by weights. The number of input and output neurons is equal to the number of input and output variables (Khandelwal 2012). In our architecture, there are four input neurons and two output neurons.…”

Section: Prediction Of Peak Particle Velocity and Frequencymentioning

confidence: 99%

Prediction and evaluation of blast-induced ground vibrations for structural damage and human response

Hudaverdi

Akyildiz

2021

Arab J Geosci

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This research focuses on blast-induced structural damage and human response to vibrations. Frequency is one of the important parameters that affect damage probability and human perception. The first and primary target of the study is to predict ground vibration and frequency simultaneously. A feed-forward back propagation neural network was created for modeling. Three operational parameters and vibration measurement distance were used as input parameters. The developed model was compared to the regression equations. Different error measures were considered to perform a vigorous model validation. Ten different blasting level charts were used to estimate structural damage probability. The regulations from North America, Europe, and Southern Hemisphere were examined and compared. Variation in the vibration regulations was also discussed. Some suggestions were put forward for the development of an international regulation. Two practical charts were created to predict human response to vibrations. A specific graph, which was proposed for pile driving induced vibrations, was considered for evaluation of blast vibrations. The developed soft computing framework can forecast probability of structural damage and human perception of vibrations effectively.

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Section: Prediction Of Peak Particle Velocity and Frequencymentioning

confidence: 99%

Prediction and evaluation of blast-induced ground vibrations for structural damage and human response

Hudaverdi

Akyildiz

2021

Arab J Geosci

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“…Ground Vibration is a seismic wave that spread out from the blast hole when detonated in a confined manner Khandelwal, (2012 ). Among all the ill effects of blasting, ground vibration is major concern to the planners, designers and environmentalists (Hagan, 1973 (Wiss and Linehan, 1978).…”

Section: Ann In Ground Vibrationsmentioning

confidence: 99%

Application of Artificial Neural Network for Blast Performance Evaluation

Trivedi¹

2014

IJRET

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Blasting pattern optimization using gene expression programming and grasshopper optimization algorithm to minimise blast-induced ground vibrations

Bayat

Monjezi

Mehrdanesh

et al. 2021

Engineering with Computers

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Blast-induced ground vibration is considered as one of the most hazardous phenomena of mine blasting, which can even cause casualties and severe damages to the adjacent properties. Measuring peak particle velocity (PPV) is helpful to know the actual vibration level but prediction of blast vibration prior to the blast is a tedious job due to involvement of blast design, explosive and rock parameters. Nowadays, efficient application of intelligent systems has been approved in different branches of science and technology. In this paper, a gene expression programming (GEP) model was developed to predict PPV using various blasting patterns as model inputs, which showed a high level of accuracy for the implemented model. Also, to optimize blast pattern attaining minimum ground vibration during blasting operation, the developed functional GEP model was taken as objective function for grasshopper optimization algorithm (GOA). Construction of GOA model was performed using a trial and error mechanism to find out the best possible pertinent GOA parameters. Finally, it was observed that utilizing GOA technique, PPV can be reduced by 67% with optimized blast parameters including burden of 3.21m, spacing of 3.75m, and charge per delay of 225Kg. A sensitivity analysis was also performed to understand the influence of each input parameters on the blast vibrations. Response to Reviewers:Please see the attached response letter

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Application of an Expert System for the Assessment of Blast Vibration

Cited by 17 publications

References 21 publications

Prediction and evaluation of blast-induced ground vibrations for structural damage and human response

Prediction and evaluation of blast-induced ground vibrations for structural damage and human response

Application of Artificial Neural Network for Blast Performance Evaluation

Blasting pattern optimization using gene expression programming and grasshopper optimization algorithm to minimise blast-induced ground vibrations

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