Explore the vast range of titles available.

The surrounding rock is divided into elastic zone and plastic zone according to the motion and deformation characteristics of medium in rock blasting. Cylindrical charge blasting vibration is framed based on past research related to blasting elastic–plastic theory, and the influence of detonation velocity on cylindrical blasting vibration is considered, especially for long charge length. A superposition model is used to calculate the vibration characteristics of long cylindrical charge blasting while considering the influence of charge length. The analysis results show that when the charge length reaches a certain length, the peak particle velocity (PPV) no longer increases with an increase in charge length, which is not consistent with the traditional theory for PPV calculation. In current practice, the calculation method for spherical charge blasting is used to calculate PPV values for a cylindrical charge. This approach, however, is inaccurate. As such, a new modified PPV calculation formula that considers the characteristics of cylindrical blasting is proposed in this paper after comparing with the spherical blasting PPV calculation method, and the influencing factor of charge length is introduced. The new PPV calculation formula can better characterize cylindrical charge blasting vibration attenuation laws.

This paper reviews the modelling approaches and outstanding issues with regard to non-cohesive sediment transport which has been experimentally and numerically studied for many decades owing to its importance to hydraulic structures, morphology and related areas. About 311 papers are reviewed that included laboratory experiments, field observations, and analytical and numerical modelling studies. The reviewed papers cover the period 1938–2020. Of 311, 95 papers are included in this paper. The modeling approaches include empirical, physics-based, spatially averaged, and soft methods. The empirical models have oversimplified the process while the physics-based models are indispensable when the detailed analysis is required. On the other hand, when the objective is to obtain cumulative sediment loads, it would be advantageous to employ the spatial averaging modelling and/or the soft computing methods due to less computational burden and data requirements. The outstanding issues are related to the particle fall velocity, particle velocity, incipient motion, and transport function that require further experimental investigations especially for unsteady non-uniform transport processes.

This paper analyses the results of trial, construction and quarry blasting, carried out in sediment rock deposits, mainly limestone and dolomite, at different locations in the Republic of Croatia. The division of the three test groups was based on the lithology changes and GSI values of the rock units at these locations. The peak particle velocity measurements with 246 recorded events, was conducted during a long period of six years. Based on the results of seismic measurements, the empirical relationships between peak particle velocity and scaled distance were established for each group. In order to establish a useful relationship between peak particle velocity and scaled distance, simple regression analysis was conducted with the Blastware software program from Instantel. The results of this study can be used to characterize ground vibration levels to the environment, through the geological strength index (GSI).

In this study, vibration sensors were used to measure blast-induced ground vibration (PPV). Different evolutionary algorithms were assessed for predicting PPV, including the particle swarm optimization (PSO) algorithm, genetic algorithm (GA), imperialist competitive algorithm (ICA), and artificial bee colony (ABC). These evolutionary algorithms were used to optimize the support vector regression (SVR) model. They were abbreviated as the PSO-SVR, GA-SVR, ICA-SVR, and ABC-SVR models. For each evolutionary algorithm, three forms of kernel function, linear (L), radial basis function (RBF), and polynomial (P), were investigated and developed. In total, 12 new hybrid models were developed for predicting PPV in this study, named ABC-SVR-P, ABC-SVR-L, ABC-SVR-RBF, PSO-SVR-P, PSO-SVR-L, PSO-SVR-RBF, ICA-SVR-P, ICA-SVR-L, ICA-SVR-RBF, GA-SVR-P, GA-SVR-L and GA-SVR-RBF. There were 125 blasting results gathered and analyzed at a limestone quarry in Vietnam. Statistical criteria like R2, RMSE, and MAE were used to compare and evaluate the developed models. Ranking and color intensity methods were also applied to enable a more complete evaluation. The results revealed that GA was the most dominant evolutionary algorithm for the current problem when combined with the SVR model. The RBF was confirmed as the best kernel function for the GA-SVR model. The GA-SVR-RBF model was proposed as the best technique for PPV estimation.

Copper-coated graphite and copper mixture powders were deposited on AZ31B magnesium alloy and 6061 T6 aluminum alloy substrates under different process parameters by a solid-state cold spray technique. The microstructure of the copper-coated graphite and copper composite coatings was visually examined using photographs taken with an optical microscope and a scanning electron microscope. The surface roughness of the coatings was investigated with a 3D profilometer. The thickness of the coatings was determined through the analysis of the microstructure images, while the adhesion of the coatings was characterized using the scratch test method. The results indicate that the surface roughness of the coatings sprayed on the two different substrates gradually decreases as gas temperature and gas pressure increase. Additionally, the thickness and adhesion of the coatings deposited on the two different substrates both increase with an increase in gas temperature and gas pressure. Comparing the surface roughness, thickness, and adhesion of the coatings deposited on the two different substrates, the surface roughness and adhesion of the coatings on the soft substrate are greater than those of the coatings on the hard substrate, while the thickness of the coatings is not obviously affected by the hardness of the substrate. Furthermore, it is noteworthy that the surface roughness, thickness, and adhesion of the copper-coated graphite and copper composite coatings sprayed on the two different substrates exhibit a distinct linear relationship with particle velocity.

Earth’s core is less dense than iron, and therefore it must contain “light elements,” such as S, Si, O, or C. We use ab initio molecular dynamics to calculate the density and bulk sound velocity in liquid metal alloys at the pressure and temperature conditions of Earth's outer core. We compare the velocity and density for any composition in the (Fe–Ni, C, O, Si, S) system to radial seismological models and find a range of compositional models that fit the seismological data. We find no oxygen-free composition that fits the seismological data, and therefore our results indicate that oxygen is always required in the outer core. An oxygen-rich core is a strong indication of high-pressure and high-temperature conditions of core differentiation in a deep magma ocean with an FeO concentration (oxygen fugacity) higher than that of the present-day mantle.

A new relationship called the mass/peak particle velocity (PPV)-frequency relation in mining blast is introduced in this study. Two well-known formulae of mining engineering and geophysical engineering are joined to create a new formula which relates ‘explosive charge’ to ‘PPV-frequency’ at a target location. The meaning of the frequency computed from the newly proposed formula is thoroughly analysed and discussed for its validity and limits. This frequency is named as the ‘PPV accompanying frequency’ or simply ‘PPV-frequency’ as an alternative to the known ‘dominant’ and ‘zero-cross frequencies’. The paper also points to the importance of the geophone properties like resonance frequency, damping factor and response curve, for safe dominant frequency determinations.

This study presents a new input parameter selection and modeling procedure in order to control and predict peak particle velocity (PPV) values induced by mine blasting. The first part of this study was performed through the use of fuzzy Delphi method (FDM) to identify the key input variables with the deepest influence on PPV based on the experts’ opinions. Then, in the second part, the most effective parameters on PPV were selected to be applied in hybrid artificial neural network (ANN)-based models i.e., genetic algorithm (GA)-ANN, particle swarm optimization (PSO)-ANN, imperialism competitive algorithm (ICA)-ANN, artificial bee colony (ABC)-ANN and firefly algorithm (FA)-ANN for the prediction of PPV. Many hybrid ANN-based models were constructed according to the most influential parameters of GA, PSO, ICA, ABC and FA optimization techniques and 5 hybrid ANN-based models were proposed to predict PPVs induced by blasting. Through simple ranking technique, the best hybrid model was selected. The obtained results revealed that the FA-ANN model is able to offer higher accuracy level for PPV prediction compared to other implemented hybrid models. Coefficient of determination (R 2 ) results of (0.8831, 0.8995, 0.9043, 0.9095 and 0.9133) and (0.8657, 0.8749, 0.8850, 0.9094 and 0.9097) were obtained for train and test stages of GA-ANN, PSO-ANN, ICA-ANN, ABC-ANN and FA-ANN, respectively. The results showed that all hybrid models can be used to solve PPV problem, however, when the highest prediction performance is needed, the hybrid FA-ANN model would be the best choice.

Faults are one of the most common geological structures in underground mining. Affected by mining activities, fault-slip events will release large amounts of energy and trigger seismic waves, which could induce rock burst events and endanger mining operations. In this study, a longwall panel intersecting with a fault is introduced, as well as field microseismic (MS) monitoring. Static and dynamic numerical analyses are conducted to investigate the fault parameters’ effects on the behaviors of the fault. The results show that the friction angle (φf) significantly affects the shear displacement, magnitude and distribution of the seismic moment; the fault stiffness has a great effect on the magnitude of the seismic moment but smaller effects on the shear displacement and the distribution of the seismic moments. Based on the influence of the fault stiffness and φf on the seismic moment, reasonable fault parameters can be determined. By employing the calibrated parameters, the dynamic responses and the rock burst potential of the surrounding rocks were analyzed by means of the peak particle velocity (PPV) and stress distribution. The propagation of the seismic waves released by fault-slip events excites the particle velocity of the rock mass, and there is a strong correlation between the particle velocity and rock mass damage. As the working face advances toward the fault, the PPV and stress fluctuation of the peak abutment stress rise significantly, which result in a great increase in the rock burst potential. The rock burst potential changes with the mining activities; therefore, corresponding measures must be applied to prevent and control rock burst events. This study contributes to deepening our understanding of the fault parameters in numerical simulations and the dynamic responses and rock burst potential of the surrounding rocks due to mining activities and provides a back-analysis calibration method for the fault parameters.

The state of a suspension is crucial with regard to processing pathways, functionality and performance of the end product. In the past decade, substantial progress has been made in designing highly specialized and functionalized particles. In current particle technology, besides classic particle properties such as particle size distribution, shape and density, surface properties play an essential role for processing, product specification and use. For example, in medical therapy, analytical diagnostic applications, as well as in separation processing and harvesting of high-valued materials, magnetic micro- and nanoparticles play an increasing role. In addition to traditional parameters such as size, the particle magnetization has to be quantified here.Sedimentation techniques have been used for hundreds of years to determine the geometrical characteristics of dispersed particles. Numerous national and international standards regarding these techniques have been published. Mainly due to the fast growing market share of laser scattering techniques over the past two decades, most customers these days are not aware of some advantageous features of particle characterization via a first-principle fractionating approach such as sedimentation. This is unfortunate as sedimentation techniques have made huge technological leaps forward regarding electronics, sensors and computing abilities.This paper aims to give a short review about different cumulative and incremental sedimentation approaches to measure the particle size distribution. It focuses mainly on the in-situ visualization (STEP-Technology®) of particle migration in gravitational and centrifugal fields. It describes the basics of the new multi-sample measuring approaches to quantify the separation kinetics by spatial and time-resolved particle concentration over the entire sample height. Based on these data, the sedimentation velocity and particle size distribution are elucidated and estimates of accuracy, precision and experimental uncertainties are discussed. Multi-wavelength approaches, correction of higher concentration, and the influence of rheological behavior of continuous phase will also be discussed. Applications beyond the traditional scope of sedimentation analysis are presented. This concerns the in-situ determination of hydrodynamic particle density and of magnetophoretic velocity distributions for magnetic particulate objects.