Values Of Peak Particle Velocity Research Articles

Numerical analysis on dynamic response and damage threshold characterization of deep rock mass under blasting excavation

The excessive destruction of surrounding rock in deep tunnel will change the original environmental state and destroy the natural ecological balance. Research on the dynamic response characteristics and damage thresholds of rock masses in deep environments plays a crucial role in determining the excavation range of blasted rock and establishing safety construction scheme. This study employs numerical simulation techniques to investigate the dynamic response characteristics of surrounding rock under different ground stress conditions. By introducing the dynamic ultimate tensile strength criterion, critical fracture stress threshold, and maximum damage radius of rock under coupled dynamic-static loading conditions are determined. The research shows that under uniaxial ground stress condition, increasing ground stress inhibits damage to the surrounding rock and the extension of cracks in the excavation area, while imposing restrictions on the attenuation rate of explosive stress. Under bidirectional equal ground stress condition, an increase in lateral pressure coefficient inhibits the development of damage zones along the excavation contour, yet enhances the extension of cracks in the maximum principal stress direction. Moreover, when lateral pressure coefficient becomes excessively large, the attenuation rate of explosive stress significantly increases. Based on the threshold values of peak particle velocity (PPV), the functional relationship is established to predict safety criteria for deep blasting excavation.

Evaluation of Anti-Burst Performance in Mining Roadway Support System

The hazardous effect of a mine earthquake on a roadway is not only related to its energy scale but also to its distance from the roadway. In this study, a signal attenuation model and a disaster-causing model were established to evaluate the mine earthquake effects based on peak particle velocity (PPV) data recorded for 37221-1 upper roadway of the Dongxia Coal Mine, China. The characteristic of dynamic loads due to mine earthquake propagation to roadway surfaces was researched, and critical PPV values were identified using FLAC3D numerical simulation, which can be used to evaluate the roadway anti-burst performance under the existing support system. The results show that the support system is able to resist a mine earthquake with energy below 2.33 × 103 J; however, considering the energy accumulation volume of surrounding rocks and the range of source fracture, the maximum resistible mine earthquake energy can be up to 7.09 × 106 J when the roadway is 50 m away from the source. The validity and applicability of the disaster-causing models was verified by two rockburst cases that occurred during the excavation of the working face.

Impact of orientation of blast initiation on ground vibrations

The blast-induced ground vibrations can be significantly controlled by varying the location and orientation of point of interest from blast site. The blast waves generated due to individual holes get superimposed and resultant peak particle velocity (PPV) generates. With the orientation sequence of holes blasts on site, the superimposition angle of wave changes and hence results in significant variation in resultant PPV. The orientation with respect to the initiation of blasts resulting in lowest PPV needs to be identified for any site. By knowing the PPV contour of vibration waves in mine sites, it is possible to reduce the vibration on the structures by changing the initiation sequence. In this paper, experimental blasts were conducted at two different mine sites and the PPV values were recorded at different orientations from the blast site and its initiation sequence. The PPV contours were drawn to identify the orientation with least and highest PPV generation line. It was found that by merely changing the initiation sequence of blasts with respect to the sensitive structure or point of interest, the PPV values can be reduced significantly up to 76.9%. • The sensitive structure or point of interest should not be aligned along the direction of initiation of production blasts. • The PPV contouring method helps in identification of the orientation of least and highest PPV generation line. • PPV contour will help in better understanding of ground vibration generation in the particular geology of any mine site. • By merely changing the orientation of blast initiation with respect to the sensitive structure PPV may be reduced up to 76.9%.

Applications of Two Neuro-Based Metaheuristic Techniques in Evaluating Ground Vibration Resulting from Tunnel Blasting

Peak particle velocity (PPV) caused by blasting is an unfavorable environmental issue that can damage neighboring structures or equipment. Hence, a reliable prediction and minimization of PPV are essential for a blasting site. To estimate PPV caused by tunnel blasting, this paper proposes two neuro-based metaheuristic models: neuro-imperialism and neuro-swarm. The prediction was made based on extensive observation and data collecting from a tunnelling project that was concerned about the presence of a temple near the blasting operations and tunnel site. A detailed modeling procedure was conducted to estimate PPV values using both empirical methods and intelligence techniques. As a fair comparison, a base model considered a benchmark in intelligent modeling, artificial neural network (ANN), was also built to predict the same output. The developed models were evaluated using several calculated statistical indices, such as variance account for (VAF) and a-20 index. The empirical equation findings revealed that there is still room for improvement by implementing other techniques. This paper demonstrated this improvement by proposing the neuro-swarm, neuro-imperialism, and ANN models. The neuro-swarm model outperforms the others in terms of accuracy. VAF values of 90.318% and 90.606% and a-20 index values of 0.374 and 0.355 for training and testing sets, respectively, were obtained for the neuro-swarm model to predict PPV induced by blasting. The proposed neuro-based metaheuristic models in this investigation can be utilized to predict PPV values with an acceptable level of accuracy within the site conditions and input ranges used in this study.

Blast-induced ground vibrations: a dynamic analysis by FEM

The peak particle velocities (PPV) are fundamental for understanding and managing the levels of blast-induced ground vibrations and their effects on adjacent structures. Given that numerical analysis of seismic vibrations has been demonstrated to be a method that can significantly contribute to predicting PPV, this study adopts a numerical approach using the finite element method (FEM) to assess blasting-induced ground vibration in rock masses. A dynamic module of the stress-strain analysis based on the FEM displacement formulation is developed in ANLOG software to estimate the variations of displacement, velocity, strain, and stress induced by blasting. The dynamic modulus implemented is verified using two verification examples. After, ANLOG is used in an application example to estimate seismic vibrations induced by blasting and to define the attenuation law for a limestone quarry near an urbanized area in Spain. The effect of Rayleigh damping coefficients (α and β) on the PPV levels estimated by ANLOG was investigated, and the most appropriate numerical attenuation law is then obtained. The numerical analysis presents satisfactory results for elastic-wave propagation induced by blasting and the peak particle velocity values obtained shows good agreement with field and the numerical results available in the specialized literature. The results indicate that ANLOG can perform personalized analysis of rock mass under blast-induced dynamic stress taking into consideration the geological and geomechanical characteristics particular to each medium as well as the blast parameters.

Prediction of Peak Particle Velocity of Blast-induced Ground Vibrations using Boosted Regression Trees Authored

Loosening of rockmass during its excavation in an infrastructure project is carried by rock blasting. The blast-induced ground vibrations pose a major challenge to the blasting engineers, whose main objective is to control their potential to cause any damage to the buildings in the vicinity. The research reported in this paper explains how the error in the prediction of the Peak Particle Velocity (PPV) by the United States Bureau of Mines (USBM)-based approach can be minimised using machine learning techniques. The complex correlation between the blast parameter and the PPV value has been modelled using the least square boosted decision tree approach after the selection of the best suitable feature has been selected based on the correlation matrix. The proposed model automatically maps the input blast feature (SD) with the target PPV values by aggregating the decision of various weak learners. The generalization of the proposed model has been validated through a 5-fold cross-validation approach using a dataset comprising of two hundred blast records generated by monitoring the blasts at International airport site, Navi Mumbai, India. The assessment of the prognostic ability of the proposed model demonstrates that it has outperformed the USBM-based approach for PPV prediction. The results establish that the predictions by the proposed model are closer to the measured values than the other regression models.

Prediction of Blast-Induced Ground Vibration with ANN and Prediction Performance

In this study, ground vibrations caused by blasting applications in a quarry were recorded and these values were evaluated and estimated by using an artificial neural network (ANN) model. Of the 28 vibration data measured, 20 were used for ANN training, 4 for validation and the remaining 4 for testing. In the model, peak particle velocity (PPV) was used as the output parameter, and the maximum explosive amount per delay and scaled distance were used as input parameters. In addition, MAPE, RMSE and R2 performance criteria were calculated from the realized, predicted by ANN and PPV values obtained from the field equation. The maximum amount of explosives used per delay and the sensitivity analysis of the scaled distance on the highest particle velocity were also determined. As a result, when the vibration data calculated from the field equation and estimated from the ANN model were compared with the realized vibration data, it was seen that the values obtained by the ANN model had a higher correlation.

Effect of Pile Driving on Ground Vibration in Clay Soil: Numerical and Experimental Study

In this study, peak particle velocity (PPV) values for driving three piles with diameters of 40 cm, 50 cm, and 70 cm in a clayey soil through the impact piling method are investigated by an experimental study and a numerical simulation. An experimental study is carried out on a scale of 1:20 of the operation. Numerical simulation is performed by using an axisymmetric model in PLAXIS 2D finite element software. Properties of the soil and the piles used in the experimental study are obtained from geotechnical tests and employed in the numerical simulation. The model has been verified by comparing the acquired PPV values with those measured in the experimental study. The results show a good agreement between the computed values and the experimental data. Moreover, measured peak particle velocities in the experimental study indicate that an increase in the diameter of the pile can increase the level of ground vibration. Some sensitivity analyses have been performed by numerical modeling to determine the effect of soil and pile properties on the changes of PPV. Also, increase in friction angle of the soil and pile diameter and reduction in elastic modulus of soil will increase the level of ground vibration. The results indicate that the amount of PPV at a distance of 100 cm is about 10.33% of the amount of PPV at a distance of 25 cm from the impact site to the pile with a diameter of 3.5 cm. In addition, this amount of reduction for pile with a diameter of 2.5 and 2 cm is equal to 8.31% and 12.77%, respectively.

Quantitative Assessment of BIGV and Structural Response Based on Velocity and Frequency Around an Opencast Mine

Blast-induced ground vibration (BIGV) velocities and frequencies are of major concern due to their adverse effects and damage to structures. Therefore, it becomes essential to assess the velocities and frequencies induced by blasting in terms of quantitative and qualitative assessment to overcome the problems. There is a need for scientific studies using devices like triaxial geophone associated with a seismograph to measure the peak particle velocity (PPV) and dominant frequency which cause damage to domestic or residential structures near an opencast mine. Each mine has specific geo-mining conditions, and scientific studies provide appropriate results. In total, 32 number of blasting data sets were recorded at every 50 m from the blast site to the last observation point near the village. Ground vibration associated damage criteria is defined in terms of the PPV at different frequency levels and the strength of the structures under study. The permissible limits of BIGV has been provided by the Directorate General of Mines Safety, Dhanbad, India. The permissible PPV values of the BIGV in India is 2, 5, 10 for the historical and sensitive structures, 5, 10, 15 for domestic houses and 10, 20, 25 for industrial buildings at 25 Hz dominant excitation frequencies respectively. The recorded dataset has been proposed through standard models. The velocity amplitude versus frequency gives a reliable relationship about damage criteria of structures. The structures were analysed vis-a-vis PPV and dominant frequency to correlate the damage possibility. The present study carried out in a mega opencast project provides the basic knowledge to assess the safe distance from blasting site for specific charge of explosive, waves which are responsible for more damage to nearby structures and to determine the correlation coefficient between measured and predicted PPV values.

Prediction of Peak Particle Velocity Caused by Blasting through the Combinations of Boosted-CHAID and SVM Models with Various Kernels

This research examines the feasibility of hybridizing boosted Chi-Squared Automatic Interaction Detection (CHAID) with different kernels of support vector machine (SVM) techniques for the prediction of the peak particle velocity (PPV) induced by quarry blasting. To achieve this objective, a boosting-CHAID technique was applied to a big experimental database comprising six input variables. The technique identified four input parameters (distance from blast-face, stemming length, powder factor, and maximum charge per delay) as the most significant parameters affecting the prediction accuracy and utilized them to propose the SVM models with various kernels. The kernel types used in this study include radial basis function, polynomial, sigmoid, and linear. Several criteria, including mean absolute error (MAE), correlation coefficient (R), and gains, were calculated to evaluate the developed models’ accuracy and applicability. In addition, a simple ranking system was used to evaluate the models’ performance systematically. The performance of the R and MAE index of the radial basis function kernel of SVM in training and testing phases, respectively, confirm the high capability of this SVM kernel in predicting PPV values. This study successfully demonstrates that a combination of boosting-CHAID and SVM models can identify and predict with a high level of accuracy the most effective parameters affecting PPV values.

ANALISIS GROUND VIBRATION DENGAN METODE PEAK PARTICLE VELOCITY (PPV)

<p><em>Measurement of Peak Particle Velocity (PPV) mm / sec in the Sabo dam construction project was carried out using seismic accelerometers. This study is to determine the value of PPV produced by construction equipment and then compared with the BS 6472-2: 2008 standard. The measurement method is carried out based on the applicable rules. PPV measurement results produced by each machine are different. In heavy equipment dump trucks, excavators, and front end loaders show PPV values at distances of 50 m, 100 m, 150 m and 200 m under safe conditions referring to the standard which is still in the range of 0.2 - 0.4 mm / sec. while for the pile driving device, demolition, vibrator pile driver at a distance of 50 meters are in unsafe conditions, because more than the range of 0.2 - 0.4 mm / sec, but at a distance of 100, 150, and 200 m PPV values are at safe condition</em></p><p><em><br /></em></p><p>Key words<strong>: </strong><em>PPV, Ground Vibration, Dam sabo</em></p><p><strong> </strong></p><p><em><br /></em></p>

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

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.

An Analytical Approach to Measure the Probable Overlapping of Holes Due to Scattering in Initiation System and Its Effect on Blast-Induced Ground Vibration in Surface Mines

Rock breakage using blasting is one of the important operations of the mining industry. The delay timing decides the initiation sequence of holes in the blasts and is a crucial factor to improve the overall blast performance. Blast-induced ground vibration is an undesired yet unavoidable outcome of blasting. Peak particle velocity (PPV) is commonly used to measure the magnitude of blast-induced ground vibration. Channelization and better utilization of explosive energy delay are provided between blast holes using initiating systems. The use of different initiation systems even on the same site results in a very significant difference in the values of PPV generated. Due to scattered delay timings of pyrotechnic detonators, the scaled distance predictor equations obtained become unreliable. The error/scatter in delay timing leads to overlapping of holes and hence increases in maximum charge per delay. In this paper, an analytical approach has been discussed to measure the overlapping of holes during blasting with initiation systems having inherent cap scatter. The analytical approach will be calculating the probable overlapping of holes due to scatter in delay timing and will help blasting engineers to understand the variation in maximum charge per delay due to pyrotechnic based initiating systems. In this study, a total number of 102 blasts were conducted using different initiation systems at two different opencast coal mine and 221 corresponding blast vibrations events were recorded.

Modified Scaled Distance Equation Used for Estimation of Peak Particle Velocity

Scaled distance equations used for estimating peak particle velocity have been developed by some researchers. The most widely used equation among these is the equation developed by Duvall and Fogelson. However, the equation has not exactly estimated the peak particle velocity correctly. In this study, peak particle velocity values were measured by a number of blast tests that were conducted in four different sites by using a vibration meter. Scaled distance values for each blast test were calculated according to the equation proposed by Duvall and Fogelson. Subsequently, a new equation that calculates the scaled distance was proposed. The proposed equation gave more realistic values than the equation proposed by Duvall and Fogelson.

Study on the effects of blast damage factor and blast design parameters on the ground vibration using 3D discrete element method

Ground vibration is one of the most critical undesirable factors of blasting. In this study, the effects of the blast damage factor and blast design parameters in a rock slope through applying the dynamic blast loading on ground vibration are investigated. Modelings were conducted considering three major geological discontinuities with a spacing of 15 m and a 45 degrees dip relative to slope face. A 3D discrete element code (3DEC Version 5.2) was used for this purpose. The pressure-decay function was used to simulate the dynamic pressure of detonation. Peak particle velocity (PPV) was selected as the main indicator to evaluate the effects of each one of these parameters by utilizing FISH programming language. Therefore, the PPV values were recorded continuously from the blast hole collar to the end of the model. The effects of rock mass quality (which is affected by the reduction in blast damage factor) and the parameters of hole diameter, burden, and spacing, stemming length, and blast delay time on the PPVs are investigated. The obtained results from numerical simulation indicated that the blast damage factor has a significant effect on ground vibrations. Moreover, it was also found that delay time is less effective than other blast design parameters on ground vibrations.

Effective Assessment of Blast-Induced Ground Vibration Using an Optimized Random Forest Model Based on a Harris Hawks Optimization Algorithm

Most mines choose the drilling and blasting method which has the characteristics of being a cheap and efficient method to fragment rock mass, but blast-induced ground vibration damages the surrounding rock mass and structure and is a drawback. To predict, analyze and control the blast-induced ground vibration, the random forest (RF) model, Harris hawks optimization (HHO) algorithm and Monte Carlo simulation approach were utilized. A database consisting of 137 datasets was collected at different locations around the Tonglvshan open-cast mine, China. Seven variables were selected and collected as the input variables, and peak particle velocity was chosen as the output variable. At first, an RF model and a hybrid model, namely a HHO-RF model, were developed, and the prediction results checked by 3 performance indices to show that the proposed HHO-RF model can provide higher prediction performance. Then blast-induced ground vibration was simulated by using the Monte Carlo simulation approach and the developed HHO-RF model. After analyzing, the mean peak particle velocity value was 0.98 cm/s, and the peak particle velocity value did not exceed 1.95 cm/s with a probability of 90%. The research results of this study provided a simple, accurate method and basis for predicting, evaluating blast-induced ground vibration and optimizing the blast design before blast operation.

Ground Vibration Induced by Moving Vehicle on Soft Soil

This research was conducted to gain more knowledge and investigate the ground vibration induced by vehicle at five different bridge approach location in Batu Pahat, Johor. This research also to illustrate and specify the ground vibration value based on identifying the location of an influence class of vehicle, speed of vehicle and zone of vehicle on bridge approach which are passing through to the bridge approach A (BAA) and bridge approach B (BAB). In describing vibration in the ground and in structures, the motion of the particle is utilized. This research describes the concepts of particle displacement, velocity and acceleration that are used to depict how the ground or structure reacts to excitation. This research observed the ground vibration motion, that is commonly described by identifying the peak particle velocity (PPV). Also presented, a description of the measurement technique, procedures and field data collection. From the sight of view of the result of this research, it indicated that the vibration value is more significant by all the variables. As a result, by the comparison of the variables that had been conducted with respect to the value of this vibration, it was found that the zone near the sensor shows a higher PPV value compared to the zone that is far apart from the sensor location and also vehicle class also plays a role which class IV is higher than class III and class II. The research shows potential to provide and improve the knowledge towards the importance of ground vibration from the vehicle loading by specific evaluation.

Quantifying and addressing uncertainties in empirical vibration attenuation relationship for underground blast by re-sampling

For efficient and timely execution of deep excavations, tunnelling or mining activities in rock, controlled blasting often becomes essential. For design of the controlled blasting operation, scaled distance regression analysis of trial blast data, namely, distance, charge weight, and peak particle velocity (PPV), is the regular industrial practice. Due to limited number of input data from trial blasts, and further due to variability of underlying media, multiple uncertainties creep into expressions thus developed. To account for these uncertainties in design of safe controlled blasting, therefore, 95 percent confidence expression obtained from trail blast data is generally preferred in industry. However, this approach lacks statistical quantification or treatment of the parameter uncertainty and there is no methodology suggested in literature, codes or standards to address this aspect. The present article proposes to estimate the parameter uncertainties in the empirical vibration attenuation relationship for underground blast using re-sampling approach. With blast data from literature, multiple samples are randomly selected and empirical parameters are evaluated for each set by least square principle. It is found that both empirical parameters in power form of expression (popular in industry) follow Normal distribution. Using the 95 percentile value for each parameter, the safe charges are calculated and thereafter are compared to the traditional industrial practice of employment of 95 percent confidence expression from trail blast data. Re-sampling approach yielded conservative charge weight for lower limiting values (PPV ≤ 15 mm/s) and efficient charge weights for higher limiting values (PPV ≥ 50 mm/s) of PPV.

An innovative technique of simplified signature hole analysis for prediction of blast-induced ground vibration of multi-hole/production blast: an empirical analysis

Prediction and control of blast-induced ground vibration is a matter of concern in mining industry since long. Several approaches ranging from scaled distance regression, different numerical methods to wave superimposition theories have been tried by many researchers for better prediction and control of blast-induced ground vibration. Signature hole analysis is one of the popular simulation methods to predict the ground vibration generated due to production blast. It superimposes the recorded signature hole waveform using a computer program to predict the production blast-induced vibration. The technique inputs the designated time of detonation of each hole and superimposes the waves generated by each hole to predict the nearest value of peak particle velocity and frequency of blast-induced ground vibration. Although a very useful approach, it requires a computer program to simulate the linear superimposition of waveforms. The simulation is not possible for every blast as it takes time and also is difficult for field engineers to simulate every time, whereas it is always easy for blasting engineers to adapt and use an empirical equation/approach for prediction and control of blast-induced ground vibration than simulation. In this paper, an attempt has been made to develop an innovative and simplified analytical approach of signature hole analysis. The simplified sinusoidal wave equation is obtained from recorded signature hole ground vibration waveform properties and is superimposed mathematically according to the multi-hole blast design to predict the production blast-induced ground vibrations. The validation of the developed approach was done in three different sites, and up to 15% more accuracy in prediction of the blast, vibrations are achieved in comparison with signature hole analysis prediction.

Effects of Quarry Blasting Towards the Residential Area at Kangkar Pulai, Johor, Malaysia

The drill and blast technique have been widely used recently due to demand for natural building materials like rock aggregates. However, the intensity of blasting effects has been questioned on its validity towards the nearby residential areas. In this study, the blasting effects from Quarry A and B has been assessed based on constant location of the residential areas (Taman Pulai Hijauan and Taman Bandar Baru Kangkar Pulai, respectively) using the empirical formulations only. The blasting effects are highly dependent on the maximum instantaneous charge in blast holes (Q) which are dependent on parameters like number of blast holes, charge per column, Powder Factor and number of blast per delay. This study was able to show that with an increase of the independent variables, the Q value rises significantly. The average Q value from Quarry A (181.07 kg) was slightly higher than Quarry B (180.22 kg). The correlations made for each quarry showed that Quarry A had a better regression line with lower standard error due to the high number of blast data obtained during the monitoring period of about 1 year and 8 months. Meanwhile, the impact assessments showed higher PPV (Peak Particle Velocity) value at higher Q holding blast holes in Quarry A compared to Quarry B and decreases with increasing distance. The similar relationship was observed for the air blast assessments. Yet, all of the blasts produced are relatively within safe limits which are less than 5 mm/s Mineral & Geosciences Department (JMG) and less than 125 dBL United States Bureau of Mining (USBM). Thus, extra precaution can be taken by estimating the suitable Q value such as A (97.66 kg) and B (271.68 to 495.01 kg) to maintain safe blasting operations and prevent damages to the nearby residential areas.