Prediction of Ground Vibration Induced by Rock Blasting Based on Optimized Support Vector Regression Models

Accurately estimating blasting vibration during rock blasting is the foundation of blasting vibration management.In this study,Tuna Swarm Optimization(TSO),Whale Optimization Algorithm(WOA),and Cuckoo Search(CS)were used to optimize two hyperparameters in support vector regression(SVR).Based on these methods,three hybrid models to predict peak particle velocity(PPV)for bench blasting were developed.Eighty-eight samples were collected to establish the PPV database,eight initial blasting parameters were chosen as input parameters for the predictionmodel,and the PPV was the output parameter.As predictive performance evaluation indicators,the coefficient of determination(R2),rootmean square error(RMSE),mean absolute error(MAE),and a10-index were selected.The normalizedmutual information value is then used to evaluate the impact of various input parameters on the PPV prediction outcomes.According to the research findings,TSO,WOA,and CS can all enhance the predictive performance of the SVR model.The TSO-SVR model provides the most accurate predictions.The performances of the optimized hybrid SVR models are superior to the unoptimized traditional prediction model.The maximum charge per delay impacts the PPV prediction value the most.

Influence of millisecond time,charge length and detonation velocity on blasting vibration

The law of blasting vibration caused by blasting in rock is very complex.Traditional numerical methods cannot well characterize all the influencing factors in the blasting process.The effects of millisecond time,charge length and detonation velocity on the blasting vibration are discussed by analyzing the characteristics of vibration wave generated by finite length cylindrical charge.It is found that in multi-hole millisecond blasting,blasting vibration superimpositions will occur several times within a certain distance from the explosion source due to the propagation velocity difference of P-wave and S-wave generated by a short column charge.These superimpositions will locally enlarge the peak velocity of blasting vibration particle.The magnitude and scope of the enlargement are closely related to the millisecond time.Meanwhile,the particle vibration displacement characteristics of rock under long cylindrical charge is analyzed.The results show that blasting vibration effect would no longer increase when the charge length increases to a certain extent.This indicates that the traditional simple calculation method using the maximum charge weight per delay interval to predict the effect of blasting vibration is unreasonable.Besides,the effect of detonation velocity on blasting vibration is only limited in a certain velocity range.When detonation velocity is greater than a certain value,the detonation velocity almost makes no impact on blasting vibration.

Peak Particle Velocity Predicting Equation Associated with the Propagation of Vibrations Induced by Blasting in a Mine and Impacts on the Physical Degradation of Houses: The Case of the Yaramoko Mine, Bagassi, Burkina Faso

This study utilizes empirical equations to describe the propagation of vibrations induced by blasting, with the goal of predicting the attenuation of Peak Particle Velocity (PPV) at the Yaramoko mine in Bagassi, Burkina Faso, a site characterized by granitoid rock. Four empirical PPV prediction equations were employed, so-called Duvall & Fogelson (or the United States Bureau of Mines “USBM”), Langefors and Kihlstrom, Ambressys-Hendron, and the Bureau of Indian Standard. The constant parameters for each of these equations, referred to as site constants, were derived from linear regression curves. The results show that the site constants k, a, and b of 4762, 0.869, and 1.737, respectively, derived from the general prediction equation by Davies, PPV = kQaD−b, based on Duvall & Fogelson, are in good agreement with values of 4690, 0.9, and 1.69, respectively, for similar rock types in Spain. Regarding the impacts of blasting on houses, the findings indicate that houses built from laterite-block bricks in the village of Bagassi are the most vulnerable to vibration waves, followed by those constructed with cinder-block bricks. In contrast, houses made of banco bricks are the most resilient. Additionally, it was determined that during blasting operations, adjusting the blasting parameters to ensure the PPV does not exceed 2 mm/s at the level of nearby dwellings can minimize the appearance of cracks in houses.

Modified scaled distance regression analysis approach for prediction of blast-induced ground vibration in multi-hole blasting

The blast-induced ground vibration prediction using scaled distance regression analysis is one of the most popular methods employed by engineers for many decades. It uses the maximum charge per delay and distance of monitoring as the major factors for predicting the peak particle velocity(PPV). It is established that the PPV is caused by the maximum charge per delay which varies with the distance of monitoring and site geology. While conducting a production blasting, the waves induced by blasting of different holes interfere destructively with each other, which may result in higher PPV than the predicted value with scaled distance regression analysis. This phenomenon of interference/superimposition of waves is not considered while using scaled distance regression analysis. In this paper, an attempt has been made to compare the predicted values of blast-induced ground vibration using multi-hole trial blasting with single-hole blasting in an opencast coal mine under the same geological condition. Further,the modified prediction equation for the multi-hole trial blasting was obtained using single-hole regression analysis. The error between predicted and actual values of multi-hole blast-induced ground vibration was found to be reduced by 8.5%.

Attenuation of rock blasting induced ground vibration in rock-soil interface

Blasting has been widely used in mining and construction industries for rock breaking.This paper presents the results of a series of field tests conducted to investigate the ground wave propagation through mixed geological media.The tests were conducted at a site in the northwestern part of Singapore composed of residual soil and granitic rock.The field test aims to provide measurement data to better understand the stress wave propagation in soil/rock and along their interface.Triaxial accelerometers were used for the free field vibration monitoring.The measured results are presented and discussed,and empirical formulae for predicting peak particle velocity (PPV) attenuation along the ground surface and in soil/rock were derived from the measured data.Also,the ground vibration attenuation across the soil-rock interface was carefully examined,and it was found that the PPV of ground vibration was decreased by 37.2% when it travels from rock to soil in the vertical direction.

Simultaneous investigation of blast induced ground vibration and airblast effects on safety level of structures and human in surface blasting

The significance of studying, monitoring and predicting blast induced vibration and noise level in mining and civil activities is justified in the capability of imposing damages, sense of uncertainty due to negative psychological impacts on involved personnel and also judicial complaints of local inhabitants in the nearby area. This paper presents achieved results during an investigation carried out at Sungun Copper Mine, lran. Besides, the research also studied the significance of blast induced ground vibration and air- blast on safety aspects of nearby structures, potential risks, frequency analysis, and human response. According to the United States Bureau of Mines （USBM） standard, the attenuation equations were devel- oped using field records. A general frequency analysis and risk evaluation revealed that： 94% of generated frequencies are less than 14 Hz which is within the natural frequency of structures that increases risk of damage. At the end, studies of human response showed destructive effects of the phenomena by ranging between 2.54 and 25.40 mm/s for ground vibrations and by the average value of 110 dB for noise levels which could increase sense of uncertainty among involved employees.

Study of blasting vibrations in Sarcheshmeh copper mine

Ground vibration is one of the side effects of blasting, in which way considerable amount of explosive energy is exhausted, and causes decrease in production and even decline in mine development workings. In this study, 57 recorded 3-C seismograms from 11 blasts in Sarcheshmeh copper mine, Kerman, Iran, are processed and analyzed. These data were recorded by digital seismograph PDAS-100 and analyzed by DADISP software. Finally, blasting parameters, such as explosive weight and type, distance between the structures and blasting site, blasting delays, affecting ground vibration are reviewed and their influence on peak particle velocity (PPV) are studied. Based on this study, suitable detonation delays and explosive type is determined. Considering these data, a graph of PPV versus scaled distance for Sarcheshmeh copper mine is prepared, by the help of which, safe distance for structures and accordingly explosive quantity could be determined.

Practical assessment of rock damage due to blasting

Blasting is the most cost effective methodology to break rock for mining or civil engineering applications.A good production blast will break only the rock that is needed to be removed,leaving the host rock with minimal damage.The control of rock damage due to blasting is very important when it comes to mine or construction design,safety,and cost.Damage to the host rock due to a production blast could result in failures,overbreak and unstable ground.Knowing how far the fractures generated by a production blast will go into the host rock is a valuable tool for engineers to design a safe highwall while keeping the actual excavation close to the design.Currently,there are several methods available to predict damage due to blasting.The accuracy of many of these methods is questionable,and in most cases,the methodologies over predict the results.This often leads to inefficient mines and poor construction works.When the current methodologies are reviewed,each one presents sound approaches,but in many cases they also lack consideration of other variables that,according to the authors,need to be included when predicting blast damage.This paper presents a practical methodology to assess the rock damage from blasting by combining other methodologies.The proposed method allows consideration of more variables when compared to available methods,resulting in a more accurate rock damage assessment.The method uses the estimation of the generated levels of peak particle velocity with the distance from a production blast presented by Persson and Holmberg,the peak particle velocity damage ranges proposed by Forsyth and the relationship between the static compressive strength and dynamic compressive strength of rocks from Liu.The new methodology was validated using the data published in a large-scale study performed in granite by Siskind.

Novel Soft ComputingModel for Predicting Blast-Induced Ground Vibration in Open-Pit Mines Based on the Bagging and Sibling of Extra Trees Models

This study considered and predicted blast-induced ground vibration(PPV)in open-pit mines using bagging and sibling techniques under the rigorous combination of machine learning algorithms.Accordingly,four machine learning algorithms,including support vector regression(SVR),extra trees(ExTree),K-nearest neighbors(KNN),and decision tree regression(DTR),were used as the base models for the purposes of combination and PPV initial prediction.The bagging regressor(BA)was then applied to combine these base models with the efforts of variance reduction,overfitting elimination,and generating more robust predictive models,abbreviated as BA-ExTree,BAKNN,BA-SVR,and BA-DTR.It is emphasized that the ExTree model has not been considered for predicting blastinduced ground vibration before,and the bagging of ExTree is an innovation aiming to improve the accuracy of the inherently ExTree model,as well.In addition,two empirical models(i.e.,USBM and Ambraseys)were also treated and compared with the bagging models to gain a comprehensive assessment.With this aim,we collected 300 blasting events with different parameters at the Sin Quyen copper mine(Vietnam),and the produced PPV values were also measured.They were then compiled as the dataset to develop the PPV predictive models.The results revealed that the bagging models provided better performance than the empirical models,except for the BA-DTR model.Of those,the BA-ExTree is the best model with the highest accuracy(i.e.,88.8%).Whereas,the empirical models only provided the accuracy from 73.6%–76%.The details of comparisons and assessments were also presented in this study.

Impact of orientation of blast initiation on ground vibrations

The blast-induced ground vibrations can be significantly controlled by varying the location and orien-tation of point of interest from blast site.The blast waves generated due to individual holes get super-imposed 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 ori-entations 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 initi-ation sequence of blasts with respect to the sensitive structure or point of interest,the PPV values can be reduced significantly up to 76.9%.

Discussion on “Impact of orientation of blast initiation on ground vibrations” [J Rock Mech Geotech Eng 15 (2022) 255e261]

Recently,Garai et al.(2022)published a paper on the impact of orientation of blast initiation on ground vibrations.However,some of the claims are not supported by the results of the given tests.In Fig.1(see Fig.8 in Garai et al.,2022),there are contours of measured vibration velocities in 4 directions(every 90?)and an incorrect interpretation between them.By placing all measured vibration velocity values(Gerai et al.,2022)at well-defined points on a single figure,it was not possible to precisely determine the type of vibration velocity,such as radial,tangential and vertical vibration velocities,with their different shapes.An incorrect conclusion was also drawn about the direction of the highest vibration velocity.The paper by Garai et al.(2022)measured the vibrational velocity of the medium through which the seismic wave passed,but used the incorrect term shock wave.The shock wave would have destroyed the seismic measuring instruments.A superposition of the vibrational velocity was considered,but not combined with the vibrational frequency of the seismic wave.This paper presents a method for selecting the time delay between successively initiated explosive charges to the measured frequency of the seismic wave,so that the direction of initiation of the explosive charges does not affect the vibration velocity of the ground through which the seismic wave passes.The theoretical and measured shapes and waveforms of radial velocity and tangential velocity in an opencast lignite mine are then presented.Moreover,the conditions for the formation of shock wave,transition wave and seismic waves are presented.

Study on influencing factors and prediction of peak particle velocity induced by roof pre-split blasting in underground

Blasting technology is widely used to prevent coal bursts by presplitting the overburden in underground coal mines.The control of blasting intensity is important in achieving the optimal pre-split effectiveness and reducing the damage to roadway structures that are subjected to blasting vibrations.As a critical parameter to measure the blasting intensity,the peak particle velocity(PPV)of vibration induced by blasting,should be accurately predicted,and can provide a useful guideline for the design of blasting parameters and the evaluation of the damage.In this paper,various factors that influence PPV,induced by roof pre-split blasting,were analyzed using engineering blasting experiments and numerical simulations.The results showed that PPV was affected by many factors,including charge distribution design(total charge and maximum charge per hole),spacing of explosive centers,as well as propagation distance and path.Two parameters,average charge coefficient and spatial discretization coefficient were used to quantitatively characterize the influences of charge distribution and spacing of explosive centers on the PPV induced by roof pre-split blasting.Then,a model consisting of the combination of artificial neural network(ANN)and genetic algorithm(GA)was adopted to predict the PPV that was induced by roof presplit blasting.A total of 24 rounds of roof pre-split blasting experiments were carried out in a coal mine,and vibration signals were collected using a microseismic(MS)monitoring system to construct the neural network datasets.To verify the efficiency of the proposed GA-ANN model,empirical correlations were applied to predict PPV for the same datasets.The results showed that the GA-ANN model had superiority in predicting PPV compared to empirical correlations.Finally,sensitivity analysis was performed to evaluate the impacts of input parameters on PPV.The research results are of great significance to improve the prediction accuracy of PPV induced by roof pre-splitting blasting.

公路隧道爆破振动对洞口区域建筑物的影响研究

在贵州省高速公路某隧道进行爆破开挖时,采用现场监测的方法研究隧道爆破振动对洞口区域建筑物的影响。依据测点布设原则,选取爆破振动影响区域具有代表性的4栋区域建筑物开展监测,根据第一次监测结果,结合现场的实际情况,确定区域建筑物的爆破振动安全允许标准为2.0 cm/s,以此推算爆破作业最大段装药量的限定范围为12.3~13.2 kg,据此将最大段装药量调整为13.0 kg。调整爆破方案后的监测结果表明:4个测点的峰值振速均小于2.0 cm/s,结合调整爆破方案前和调整爆破方案后的现场调研情况,验证选定的区域建筑物振动控制标准和最大段装药量取值的建议是合理可行的。

不耦合装药系数对岩体爆破损伤的影响

在爆破工程中,选择合适的装药结构能够有效提高炸药利用率,从而改善爆破效果。基于RHT(Riedel-Hiermaier-Thomamodel)动态响应力学关系,采用ANSYS/LS-DYNA软件研究了偏心不耦合装药条件下不耦合系数K对岩体爆破荷载的影响,以及爆破过程中岩体的损伤情况。通过建立单孔偏心不耦合爆破模型,分析了不耦合系数K为1.0、1.5、2.0、2.5、3.0和3.5条件下的有效应力、振动速度、爆破地震波能量和损伤状况。同时,研究了不同不耦合系数K条件下爆心距(l)与损伤度(D)、质点振动速度(PPV)与爆心距(l),以及振动速度(vpp)与损伤度(D)之间的关系。结果表明:随着不耦合系数K的增大,耦合侧与不耦合侧有效应力和峰值振动速度、地震波峰值能量略微减小;粉碎区和裂隙区范围逐渐减小,且粉碎区损伤半径较裂隙区减小速率更大。岩体损伤程度和质点振动速度(vpp)均随着爆心距的增大而逐渐减小。质点振动速度越大损伤程度也越大,当vpp=50.4 cm/s时,岩体中的损伤变量达到损伤破坏阈值(D=0.19);当vpp>140.6 cm/s时,损伤度D>0.80。

预裂缝宽度对爆破效果影响研究

采用LS-DYNA软件建立数值模型,模拟分析了预裂缝宽度分别为3 cm和5 cm时对爆破效果的影响。结果表明,预裂缝越宽,减振效果越好,相差比例最高可达46%。选择不同孔径预裂爆破进行现场爆破振动监测试验,验证了数值模拟所得规律的正确性。预裂爆破参数的选取需结合现场实际工况和周围建(构)筑物的保护进行综合分析。

爆破震动作用下高地应力巷道动力响应特征与稳定性研究

为了研究爆破震动作用下高地应力巷道的动力响应特征及其稳定性,以淮南潘三矿超前预裂卸压爆破扰动瓦斯综合治理巷为工程背景,通过理论分析建立了爆破作业扰动巷道围岩模型,并根据应力波传播理论及波前动量守恒定理推导出了爆破震动作用下巷道围岩振动方程。使用数值模拟研究了巷道围岩质点峰值振动速度(Peak Particle Velocity,PPV)的衰减特征,从应力分布规律的角度对理论分析进行了补充,并根据模拟结果对巷道围岩稳定性进行了分析。结果表明:巷道围岩振动方程显示,爆炸应力波入射角度的不同会导致巷道围岩不同区域的动态响应特征存在差异。随着爆心距增大,巷道轮廓面附近围岩PPV出现波动,并在自由面处获得最大峰值振速;地应力对巷道围岩PPV具有抑制作用,地应力越大抑制作用越明显,且不同位置围岩的PPV对地应力敏感度存在差异;随着地应力增大,爆破震动作用下巷道围岩受力状态从拉剪变为压剪,最大主应力和剪切应力也随之增大。研究认为随着埋深增加,在对爆破震动作用下巷道围岩的稳定性进行评估时地应力因素不可忽略。对于潘三矿超前预裂卸压爆破工程现场而言,除了巷道的直墙外,墙角、拱墙也是危险区域,应当着重予以加固并加强监测。

白鹤滩水电站坝肩边坡开挖爆破振动概率分布研究

为科学准确判定岩石高边坡开挖爆破振动的概率分布形式,为岩石高边坡爆破振动幅值和频率的不确定性预测提供科学理论基础,以白鹤滩水电站右岸坝肩岩石高边坡开挖工程为研究背景,对典型开挖程序和爆破方案下的岩石高边坡爆破振动幅值和主频实测数据进行了概率统计分析,研究了岩石高边坡开挖爆破振动幅值和主频的概率分布及其主要特征。研究结果表明:正态分布和Gamma分布模型对岩石高边坡开挖预裂和主爆破质点峰值振速概率分布的拟合效果均较好,岩石高边坡开挖预裂和主爆破质点峰值振速的概率分布较好地服从正态或Gamma分布;Gamma分布模型相较于正态分布模型对岩石高边坡开挖预裂和主爆破振动视主频的概率分布存在明显拟合优势,岩石高边坡开挖预裂和主爆破振动视主频概率分布较好地服从Gamma分布。岩石高边坡预裂爆破质点峰值振速和视主频的平均值大于对应主爆破质点峰值振速和视主频的平均值,预裂爆破质点峰值振速和视主频下四分位~上四分位量值范围分别为5.4~11.6 cm/s和36.7~97.6 Hz,主爆破质点峰值振速和视主频下四分位~上四分位量值范围分别为3.8~8.9 cm/s和26.7~97.6 Hz。研究结果显示,经常采用的正态分布并不一定是岩石高边坡开挖爆破振动幅值或主频的最佳概率分布形式,其他典型岩石高边坡工程爆破振动幅值和主频的概率分布有待进一步研究。

基于SSA-BP的爆破振动峰值速度预测研究

为了精准预测爆破振动峰值速度(PPV),有效降低爆破振动的危害,以星光一号露天矿山爆破工程为依托,选取爆心距、堵塞长度、最小抵抗线、炸药单耗、最大单孔装药量、总延期时间、最大单响药量等7个影响因素作为输入变量,采用灰色关联分析法评估各因素与PPV之间的相关性,构建麻雀搜索算法(SSA)优化BP神经网络的爆破峰值振速预测模型,对三向峰值振动速度进行预测,并与BP神经网络模型预测结果进行对比分析,得到SSA-BP神经网络模型预测结果的平均误差分别为6.08%、7.34%、1.91%,BP神经网络模型预测结果的平均误差分别为22.19%、54.01%、25.29%。研究结果表明:SSA-BP神经网络模型全面考虑了多种爆破设计参数对振动峰值速度的影响;麻雀搜索优化算法有效解决了传统BP神经网络模型容易陷入局部最优的问题,预测结果更精确,与振速监测值吻合度更高、误差更小;并且极大地缩短了样本数据的学习训练时间,加快BP神经网络预测模型的收敛速度,可为类似露天爆破工程质点峰值振速的预测提供借鉴。

预留核心土法爆破开挖下隧道初期支护动力响应特性

初期支护是隧道施工阶段的主要承力结构,爆破施工动力扰动下初期支护的响应规律及安全控制对确保隧道安全快速施工有着重要意义。为研究预留核心土法爆破开挖影响下软岩隧道初期支护的动力响应特征及其安全控制,以林场隧道爆破施工为工程背景,依据隧道初期支护现场爆破振动监测结果,利用ANSYS/LSDYNA建立三维有限元数值计算模型,结合预留核心土法爆破作业特点,研究了两个不同距离爆源同时作用下隧道初期支护的应力分布特征,利用萨道夫斯基经验公式获得了预留核心土法爆破振动传播衰减规律,提出了以应力为控制标准的两侧下台阶同时起爆条件下隧道初期支护的爆破振动速度安全判据。结果表明:不同于全断面法和台阶法爆破,预留核心土法两侧下台阶同时起爆时,最大振动速度出现于隧道初期支护拱脚处,而非隧道底板或拱顶;仰拱未回填区域的存在显著影响爆破应力波传播路径,相较于右侧拱脚,隧道初期支护左侧拱脚处的振动速度更大,且随距离增加而衰减的更明显;初期支护结构稳定性受拉应力控制,最大拉应力及剪应力出现于隧道左侧拱脚处,最大拉应力为7.544 MPa,最大的剪应力为2.78 MPa,均超过规范允许值;根据建立的应力-振速线性关系,提出基于极限强度的隧道初期支护爆破振动安全判据;在林场隧道爆破条件下初期支护的爆破振速安全阈值为10 cm/s。研究成果为隧道爆破施工设计以及安全控制提供理论研究基础。

硬岩小净距隧道先行洞的爆破振动响应规律

隧道爆破施工时,爆破破岩产生的振动效应对近邻隧道结构稳定性影响较大。为提高隧道爆破施工的安全性,基于广西某双线硬岩小净距隧道爆破开挖工程,通过现场爆破振动监测,分析后行洞爆破开挖时爆破振动的传播规律与质点峰值振动速度的分布特征,并利用有限元软件LS-DYNA建立相应的数值模型,探索近邻先行隧道径向和轴向上质点峰值振动速度演化特征及分布规律,基于最大主应力原则,构建近邻隧道爆破振动安全判据。研究结果表明:对后行隧道爆破开挖时,水平径向的振动波对近邻隧道的影响起主导作用;在爆心距相同的情况下,隧道未开挖侧的爆破振动衰减速度比已开挖侧的小;近邻隧道迎爆侧边墙、拱脚和底脚是主要受扰动区,边墙的质点峰值振动速度最大,在施工中应当加强边墙的监测和防护。基于近邻隧道质点峰值振动速度与拉应力内在联系的回归分析,并考虑混凝土的动态抗拉强度,建议将本隧道爆破施工的质点峰值振动速度阈值确定为15.7 cm/s,以保证依托工程近邻隧道支护结构的安全。