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To test the impact of different mixture ratios on backfilling strength in Fankou lead–zinc mine, various mixture ratio designs have been conducted. Meanwhile, to improve the strength of ultra-fine tailings-based cement paste backfill (CPB), two kinds of fibers were utilized in this study, namely polypropylene (PP) fibers and straw fibers. To achieve these, a total of 144 CPB backfilling scenarios with different combinations of influenced factors were tested by uniaxial compressive tests. The test results indicated that polypropylene fibers improve the strength of CPB, while in some scenarios the addition of straw fibers decreases the strength of CPB. In this research, the support vector machine (SVM) technique coupled with three heuristic algorithms, namely genetic algorithms, particle swarm optimization and salp swarm algorithm (SSA), was developed to predict the strength of fiber-reinforced CPB. Also, the optimal performance of metaheuristic algorithms was compared with one fundamental search method, i.e., grid search (GS). The overall performance of four optimal algorithms was calculated by the ranking system. It can be found that these four approaches all presented satisfactory predictive capability. But the metaheuristic algorithms can capture better hyper-parameters for SVM prediction models compared with GS-SVM method. The robustness and generalization of SSA-SVM methods were the most prominent with the R2 values of 0.9245 and 0.9475 for training sets and testing sets. Therefore, SSA-SVM will be recommended to model the complexity of interactions for fiber-reinforced CPB and predict fiber-reinforced CPB strength.

To reduce the workload and misjudgment of manually discriminating microseismic events and blasts in mines, an artificial intelligence model called PSO-ELM, based on the extreme learning machine (ELM) optimized by the particle swarm optimization (PSO) algorithm, was applied in this study. Firstly, based on the difference between microseismic events and mine blasts and previous research results, 22 seismic parameters were selected as the discrimination feature parameters and their correlation was analyzed. Secondly, 1600 events were randomly selected from the database of the microseismic monitoring system in Fankou Lead-Zinc Mine to form a sample dataset. Then, the optimal discrimination model was established by investigating the model parameters. Finally, the performance of the model was tested using the sample dataset, and it was compared with the performance of the original ELM model and other commonly used intelligent discrimination models. The results indicate that the discrimination performance of PSO-ELM is the best. The values of the six evaluation indicators are close to the optimal value, which shows that PSO-ELM has great potential for discriminating microseismic events and blasts. The research results obtained can provide a new method for discriminating microseismic events and blasts, and it is of great significance to ensure the safe and smooth operation of mines.

A 3D numerical model was presented to investigate the blast-induced damage characteristics of highly stressed rock mass. The RHT (Riedel, Hiermaier, and Thoma) model in LS-DYNA was used to simulate the blast-induced damage and its parameters were calibrated by a physical model test. Based on the calibrated numerical model, the influences of confining pressure and free surface span on the blast-induced damage characteristics were investigated. The results show that under uniaxial loading, the crater volume increases with confining pressure increases. The uniaxial static load can change the optimal burden and the critical embedding depth of charge. In stressed rock, the variation law of the crater shape affected by radial tensile fractures is opposite to that affected by reflected tensile fractures. Under the biaxial static load, the crater volume of the borehole placed on the side of the max static load is greater than the other side. The explosion crater can be improved by increasing the free surface span on the same side. Finally, it is suggested that the blasting efficiency can be improved by preferentially detonating the charge on the side of the max static load, and then the charge on the other side can be detonated with a wider free surface span.

The indirect and accurate determination of blast-induced rock movement has important significance in the reduction of ore loss and dilution and in the protection of environment. The present paper aims to predict blast-induced rock movement resulting from the Husab Uranium Mine, Namibia, the Coeur Rochester Mine, USA, and the Phoenix Mine, USA, and three new hybrid models using a genetic algorithm (GA), an artificial bee colony algorithm (ABC), a cuckoo search algorithm (CS) and support vector regression (SVR), namely the GA-SVR, ABC-SVR and CS-SVR models, are proposed. Eight typical blasting parameters rock type, number of free faces, first centerline distance, hole diameter, power factor, spacing, subdrill and initial depth of monitoring were chosen as the input variables to establish the intelligent model, and horizontal blast-induced rock movement (MH) was the output variable after conducting the available analyses of the database. Three performance metrics, including the correlation coefficient (R2), mean square error and variance account for, were used to assess the predictive performances of the aforementioned models. Based on the obtained results, the performance metrics show that the GA-SVR, ABC-SVR and CS-SVR model can provide satisfactory performance in estimating blast-induced rock movement, and GA-SVR model can achieve better results than the GWO-SVR, CS-SVR and ANN models when considering both predictive performance and calculation speed.

Prediction of slope stability is one of the most crucial tasks in mining and geotechnical engineering projects. The accuracy of the prediction is very important for mitigating the risk of slope instability and enhancing mine safety in preliminary design. However, existing methods such as traditional statistical learning models are unable to provide accurate results for slope instability due to the complexity and uncertainties of multiple related factors with small unbalanced data samples thus requiring complex data processing algorithms. To address this limitation, this paper presents a novel prediction method that utilizes the gradient boosting machine (GBM) method to analyze slope stability. The GBM-based model is developed by the freely available R Environment software, trained and tested with the parameters obtained from the detailed investigation of 221 different actual slope cases between 1994 and 2011 with circular mode failure available in the literature. The stability of the circular slope accounts for the unit weight (γ), cohesion (c), angle of internal friction (φ), slope angle (β), slope height (H) and pore water pressure coefficient (ru). A fivefold cross-validation procedure is implemented to determine the optimal parameter values during the GBM modeling and an external testing set is employed to validate the prediction performance of models. Area under the curve (AUC), classification accuracy rate and Cohen’s Kappa coefficient have been employed for measuring the performance of the proposed model. The analysis of AUC, accuracy together with kappa for the dataset demonstrate that the GBM model has high credibility as it achieves a comparable AUC, classification accuracy rate and Cohen’s kappa values of 0.900, 0.8654 and 0.7324, respectively for the prediction of slope stability. Also, variable importance and partial dependence plots are used to interpret the complex relationships between the GBM predictive results and predictor variables.

This experimental study was carried out to investigate the influence of polypropylene (PP) fibre on the compressive behavior and microstructural properties of tailings (classified as CL – lean clay) cemented paste backfill (CPB). The compressive behavior was determined by the unconfined compressive strength (UCS), and structural changes in CPB were evaluated by macrostructural failure analysis and microstructural tests with scanning electron microscopy (SEM) analysis. Orthogonal tests were designed to research the influences and significance of the cement content, solid mass concentration, fibre content and fibre length on CPB. The results indicate that although the fibre parameters are not as significant as the cement content and solid mass concentration for CPB strength, they are also important factors for improving the UCS of CPB, and the effect of PP fibre on the early (3 days curing time) and later (28 days curing time) stage strength of the backfill is much more obvious than that on the medium stage (7 days curing time) strength. And fibre can enhance the stiffness and ductility of CPB with increasing strain and E50. In addition, the fibre content is much more important than the fibre length, there is no linear relationship between UCS and the fibre parameters (fibre content and fibre length), and the best fibre parameter levels are a fibre content of 0.15% and a fibre length of 6 mm in this study. Moreover, macrostructural failure analysis and SEM microstructural tests indicated that PP fibre tend to bridge the cracks, which can reduce the porosity of the CPB matrix and improve its compactness, integrity and residual strength with some calcium silicate hydrate (C-S-H) gelling trapped on its surface.

A simple and accurate evaluation method of broken rock zone thickness (BRZT), which is usually used to describe the broken rock zone (BRZ), is meaningful, due to its ability to provide a reference for the roadway stability evaluation and support design. To create a relationship between various geological variables and the broken rock zone thickness (BRZT), the multiple linear regression (MLR), artificial neural network (ANN), Gaussian process (GP) and particle swarm optimization algorithm (PSO)-GP method were utilized, and the corresponding intelligence models were developed based on the database collected from various mines in China. Four variables including embedding depth (ED), drift span (DS), surrounding rock mass strength (RMS) and joint index (JI) were selected to train the intelligence model, while broken rock zone thickness (BRZT) is chosen as the output variable, and the k-fold cross-validation method was applied in the training process. After training, there validation metrics including variance account for (VAF), determination coefficient (R2) and root mean squared error (RMSE) were applied to describe the predictive performance of these developed models. After comparing performance based on a ranking method, the obtained results show that the PSO-GP model provides the best predictive performance in estimating broken rock zone thickness (BRZT). In addition, the sensitive effect of collected variables on broken rock zone thickness (BRZT) can be listed as JI, ED, DS and RMS, and JI was found to be the most sensitive factor.

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.

The accurate determination of postblast ore boundaries can significantly help to control ore loss and dilution in opencast mines. Determining the boundaries is difficult using methods other than direct and expensive blast-induced rock movement monitoring, so many mines directly use the preblast ore boundary to guide the shovel. A new postblast ore boundary determination method using a soft computing technique and stochastic modelling method is proposed. Based on a case study and performance comparison, a high-precision hybrid metaheuristic model combined with the sine cosine algorithm and random forest technique (SCA-RF) was developed and used in a Monte Carlo simulation to analyse the probability distribution and parameter sensitivity. Mining engineers can obtain a more accurate postblast ore boundary by moving the preblast ore boundary toward the free face by a certain distance after considering the probability distribution of blast-induced rock movement, which is significantly better than using the preblast ore boundary.

In order to reduce the undesired phenomenon including brow damage, over crushing and bulking yield in the ring blasting which are owning to the unreasonable distribution of blasting energy, a new optimization method is proposed to improve the charge scheme based on the Scaled Heelan (SH) model. First, the traversal algorithm for an arrangement of regular holes (holes charged to the collar) is proposed based on the analysis of the current interval charge design method in ring blasting. Second, a new developed mathematical model based on the SH model is introduced to predict the fragment size of the column charge. Then, the optimization method according to two key parameters of the blasted fragment prediction, D 50 and D 90 − D 10 , is discussed. Finally, a case study is introduced to illustrate the usage and optimization procedure of the program. Sixty trial blasts were conducted in the Tonglvshan copper mine to verify the feasibility and effectiveness of the optimization algorithm. The frequency of occurrence of brow damage was reduced from 36.7% to 16.7% using the proposed method in our sixty field tests, and the loading efficiency was also improved by 11.3% due to the more uniform distribution of muck pile fragment size.

This experimental investigation was conducted to research the properties of polypropylene (PP) fiber-reinforced cemented paste backfill (CPB). The unconfined compressive strength (UCS) of the fiber-reinforced CPB showed a significant improvement with average UCS increase ratios of 141.07%, 57.62% and 63.17% at 3, 7 and 28 days, respectively. The macroscopic failure mode and SEM analysis indicated that fibers prevented the formation of large tensile and shear cracks during the pull-out and pull-off failure modes. A linear fitting function for the UCS at a curing time of 3 days and two polynomial fitting functions for the UCS at curing times of 7 and 28 days were established to characterize the relationship between the UCS of the fiber-reinforced and unreinforced CPB. Moreover, based on composite mechanics, nonlinear models related to the UCS and fiber reinforcement index were obtained. The estimated functions containing the fiber reinforcement index &lambda, which consists of the fiber content and aspect ratio of fiber, could evaluate the UCS. Furthermore, the fiber reinforcement index &lambda, quantifies the enhancement by the fibers. Both estimation results indicated that the UCS values were estimated accurately at curing times of 3, 7 and 28 days in this study. Additionally, the estimation models could be used to guide the strength design of fiber-reinforced CPB. Besides this, the results showed that fiber-reinforced CPB can be used more widely in mine backfills and meets the requirements of controlled low-strength material (CLSM) for broader applications.

Delay blasting with relatively long-delay intervals is widely used in mining engineering since the former detonated blast-holes can produce new free surfaces for the later detonated blast-holes. With the application of electronic detonators, which have a minimum delay and a delay accuracy of 1 ms, a new blasting pattern using short-delay intervals is proposed in the present study in order to improve rock breaking and control blast-induced vibrations in cutting blasting with single free surface in underground mines. Theoretical analyses are firstly conducted to investigate the mechanisms of blasting crater formation and vibration reduction of short-delay blasting. Then a series of blasting crater tests with different delay intervals are performed to compare the characteristics of blasting craters and blast-induced vibrations produced by short-delay and simultaneous blastings. The results of crater sizes show that it is possible to form a common blasting crater only when the delay intervals are shorter than the formation time of a new free surface. It is also found that the short-delay blasting can effectively reduce PPV compared with the simultaneous blasting, particularly in the near-field. Spectral analysis indicates that there is less energy in the low-frequency content in short-delay blasting than simultaneous blasting. The possibility and feasibility of reducing vibration via short-delay blasting in underground mines are also discussed in this study.

Earthquakes have always attracted civil and geotechnical engineers’ attention, especially when it comes to the liquefaction potential of soil. This paper investigates the feasibility of cla...

A new optimization method for optimal charge scheme calculation is proposed to reduce undesired phenomenon in ring blasting, including brow damage, overcrushing, and bulking yield, which ar...

It is essential to control the damage to the surrounding rock and engineering structures in the process of cut blasting with a single free surface in underground mining. To reduce vibration induced by cut blasting, this paper proposes short-delay cut blasting, in which blast holes that are near each other are sequentially initiated with short-delay times. Experimental tests of cut blasting were conducted in a roadway in the Shaxi copper mine to compare the peak particle velocity (PPV) and frequency characteristics of simultaneous blasting and short-delay blasting. Numerical modelling was then developed to study the influence of short-delay times on blast vibration. The accuracy of the numerical simulation was verified by the comparison of the test and simulated data of single-hole blasting. The results show that the amplitude reduction ratio (ARR) value increases gradually with the increase in delay intervals, and the vibration reduction for delay intervals smaller than 6 ms is very limited, particularly in the near field. The principal frequencies (PFs) for short-delay blasting are similar to those for simultaneous blasting, which implies that the frequencies do not increase directly with the decrease of the delay intervals. The experimental tests also show that the mean frequencies (MFs) for the 8 ms delay are slightly higher than those for the 0 ms delay blast. In the case of ensuring the rock breaking of cut blasting, longer delay intervals of 8∼10 ms are beneficial to further reduce PPV in practical blasting.

Controlling rock damage induced by lateral blasting excavation is a source of concern. In underground mines, large-diameter-hole lateral blasting excavation often causes engineering disasters such as large blocks falling and overall collapse of the remaining rock mass. Because of their high cost and cumbersome operation, conventional contour blasting techniques, such as smooth and presplit blasting, are unsuitable for production boreholes. In this paper, based on the large-diameter-hole lateral blasting excavation of the Shaxi underground mine in China, a field lateral blast test with a single row was initially conducted, and the sonic wave speeds and goaf boundaries were measured to evaluate the damage degree to the remaining rock mass. A numerical model with three rows of boreholes was developed and calibrated against the lateral blast test with a single row. The calibrated numerical model was used to simulate the blasting process. The blast-induced damage characteristics with different charge structures in different rows were investigated, and the optimal charge structure for each row was obtained. The results indicate that the rock damage control effect can be achieved by a reasonable combination of charge structures and number of blasted rows, and it is more satisfactory with an increasing number of blasted rows and a reasonable decrease in the charge coefficient row by row. The rock breaking pattern at Cut X2 shows that most of the boulders are caused by the collapse of the remaining rock mass under the impact of blasting excavation. The ratio of broken rock in Part 4 indicates that the blast impact of the last row plays a dominant role in the damage to the remaining rock mass. Two optimized schemes were applied to the field of large-diameter-borehole lateral blasting, and satisfactory effects were achieved in the blast-induced damage control of the remaining rock mass.

Owing to the complex features of blasting vibration damage assessment systems, a gradient boosted machine (GBM) model is developed for the classification of residential structure damage (RSD) due to blasting vibrations of open pit mining. Twelve indicators are defined as the indices for the prediction of RSD in the proposed model. These are: peak particle velocity, dominant frequency, dominant frequency duration, distance, maximum safe charge per delay, compressive strength of mortar joints, ratio of brick area to house area, height of residential house, roof structures, beam-column frames, quality of construction, and site conditions. The GBM model is achieved by training 108 sets of measured data of blasting vibration. A 10-fold cross-validation procedure was applied to determine the optimal parameter values during modeling, and an external testing set was employed to validate the prediction performance of the model. Two performance measures – classification accuracy rate and Cohen’s kappa – have been employed. The analysis of accuracy together with kappa for the dataset demonstrate that the GBM model has high credibility as it achieves a comparable median classification accuracy rate and Cohen’s kappa values of 91.7% and 0.875 for the prediction of RSD, respectively.

The database of 254 rockburst events was examined for rockburst damage classification using stochastic gradient boosting (SGB) methods. Five potentially relevant indicators including the stress condition factor, the ground support system capacity, the excavation span, the geological structure and the peak particle velocity of rockburst sites were analyzed. The performance of the model was evaluated using a 10 folds cross-validation (CV) procedure with 80% of original data during modeling, and an external testing set (20%) was employed to validate the prediction performance of the SGB model. Two accuracy measures for multi-class problems were employed: classification accuracy rate and Cohen's Kappa. The accuracy analysis together with Kappa for the rockburst damage dataset reveals that the SGB model for the prediction of rockburst damage is acceptable.

The accurate identification of delay time in millisecond blasting plays an important role in the optimization of blasting design and reduction of vibration effect. Through a case study of a surge shaft blasting project, the capability of the EMD (empirical mode decomposition) method in identifying the delay time of short millisecond blasting with precise initiation was compared with the instantaneous energy method based on Hilbert-Huang transform (HHT). The recognition rate of the EMD method was more than 80%, while the instantaneous energy method was less than 25%. By analyzing the instantaneous energy of single-hole blasting signal, it was found that the instantaneous energy method was adaptable to millisecond blasting with delay time longer than half of the energy peak period. The EMD method was used to identify delay time of millisecond blasting in Zijinshan open-pit mine. According to the identification results, the blasting parameters were optimized for controlling the blast-induced vibration and reducing the large block ratio. The field data showed that the velocity peak of ground vibration was reduced by more than 30% under almost the same maximum charge per delay by the optimization of delay time and detonating detonators. Combining with slag-remaining blasting and burden optimization of the first row, the large block ratio was reduced to less than 3%. The research results proved that the identification method based on HHT was feasible to optimize the blasting design. The identification method is also of certain reference value for design optimization of other similar blasting projects.

Ground vibrations originating from bench blasting may cause damage to slopes, structures, and underground workings in close proximity to an operating open-pit mine. It is important to monitor and predict ground vibration levels induced by blasting and to take measures to reduce their hazardous effects. The aims of this paper are to determine the weaker protection objects by comparatively studying bench blasting induced vibrations obtained at surface and in an underground tunnel in an open-pit mine and thus to seek vibration control methods to protect engineering objects at the site. Vibrations arising from measurement devices at surface and in an underground tunnel at the Zijinshan Open-Pit Mine were obtained. Comparative analysis of the peak particle velocities shows that, in the greatest majority of cases, surface values are higher than underground values for the same vibration distance. The transmission laws of surface and underground vibrations were established depending on the type of rock mass, the explosive charge, and the distance. Compared with the Chinese Safety Regulations for Blasting (GB6722-2014), the bench blasting induced vibrations would not currently cause damage to the underground tunnel. According to the maximum allowable peak particle velocities for different objects, the permitted maximum charges per delay are obtained to reduce damage to these objects at different distances.

It is generally believed that stress wave superposition does occur and plays an important role in cutting blasting with a single free surface, in which explosive columns of several blast holes with short spacing are simultaneously initiated. However, considering the large scatter of pyrotechnic delay detonators that are used in most underground metal mines in China, the existence of stress wave superposition and the influence of this effect on rock fragmentation are questionable. In the present study, the stress wave interaction in short-delay blasting with a single free surface was studied through the use of the LS-DYNA code. Stress waves induced by two blast holes blasting with different delays were compared with the single blast hole case, and the effects of delay time, detonating location and spacing on stress wave superposition were investigated. The numerical results showed that for blast holes with a 1 m spacing, stress wave interaction only occurs when the delay time is 0 ms and does not occur for blasting with delays of more than 1 ms. An increase in the duration of a stress wave via optimizing the detonation location does not improve the stress wave interaction. For a 1 ms delay, stress wave superposition only occurs when the spacing is more than 4 m, which is a rare case in practice. The results indicated that the occurrence of stress wave superposition for blasting with a single free surface is strictly limited to conditions that would be difficult to achieve under the existing delay accuracy of detonators. Therefore, it is unrealistic to improve fragmentation via the stress wave interaction in field blasting. Furthermore, the numerical results of the stress wave interaction also show that there would be a great potential to reduce the hazardous vibrations induced by short-delay blasting by using electronic detonators with better control of delays in an order of several milliseconds.

To eliminate undesired phenomena such as brow damage and excessive fines owing to the energy concentration on the collar of the ring, a fragment simulation using a charge scheme optimization algorithm is proposed based on modified Harries model in this article. First, the traversal algorithm for an arrangement of regular holes (holes charged to the collar) is proposed based on the analysis of the current interval charge design method in ring blasting. Second, a new developed mathematical model based on Harries model is introduced to predict the fragment size of the column charge using the superposition method. Then, the optimization criteria based on the calculated blasted fragment matrix are discussed. Finally, a case study is introduced to illustrate the usage and optimization procedure of the program. Ten trial blastings were conducted in the Tonglvshan copper mine to verify the feasibility and effectiveness of the optimization algorithm. The findings reveal that the probability of brow damage was reduced efficiently.

The analysis of liquefaction potential of soil due to an earthquake is a classical problem for civil and geotechnical engineers. In this paper, Friedman’s stochastic gradient boosting (FSGB) method is introduced and investigated for the prediction of seismic liquefaction potential of soil based on the cone penetration test (CPT) data. The SGB models were developed and validated on a relatively large dataset comprising 226 field records of liquefaction performance and CPT measurements. The database contains the information about effective vertical stress, cone tip resistance, total vertical stress, sleeve friction ratio, depth of potentially liquefiable soil layer, earthquake magnitude and maximum horizontal ground surface acceleration. To find the most suitable model, several different combinations of above input parameters were tested to assess the usefulness of SGBs for liquefaction assessment using CPT data. SGBs are based on classification & regression trees with ensemble learning strategy and found to work well in comparison to artificial neural network and support vector machine models. The developed SGB provides a viable tool for practicing engineers to determine the liquefaction potential of soil.

The charge structure is an important factor in the adjustment of the energy distribution of explosives and the control of the blasting effect, especially in an underground large-diameter longhole, for interval charge millisecond blasting design. To achieve a reasonable charge structure, a multi-planar detection optimization (MDO) algorithm for charge structures is proposed based on the Harries mathematical model and the superposition method. The vector size of a fragment is transformed into a scalar ruler, and the definition of the spatial non-uniformity evaluation factor is used in the MDO algorithm. A detailed methodology is implemented using a Visual LISP program and validated for a case study of the Fankou lead–zinc mine in China. The results reveal that the MDO algorithm can improve the rock fragmentation and increase the energy utilization rate of explosives in large-diameter longhole blasting operations. This algorithm could be extremely helpful in the process of underground mine blast optimization.

Ground settlements above a tunnel as a result of tunnel construction can be predicted with the help of input variables that have direct physical significance. Several empirical and artificial intelligence methods for estimating ground settlements have been established by researchers. However, these methods have some limitations because the large number of influential factors involved makes tunnel–ground interaction complicated. In this work, a random forest (RF) was developed and employed to predict ground settlements above tunnels. To achieve this goal, tunnel geometry, geological properties, and construction parameters were investigated as input variables to utilize in the RF modeling, resulting in the maximum surface settlement value (Smax) and trough width (i) as the ground surface settlement index. To demonstrate the applicability of the RF model, two data sets associated with different features, which were obtained from a detailed investigation of different tunnel projects published in litera...

A three-dimensional backfill pipeline transport model is developed using the computational fluid dynamics (CFD) technique, which is applied to study the pipeline transport properties of three-phase foam slurry backfill (TFSB). Based on rheological property tests and CFD simulations, the foam phase, pressure, and velocity in the pipeline system are investigated using the CFD mixture method for different bubble volume fractions and bubble diameters. The simulation results indicate that TFSB can maintain a steady state during pipeline transport, experience a markedly reduced pipeline transport resistance, and exhibit better liquidity than conventional cement slurry. Furthermore, as the bubble volume fraction increases, the resistance of the pipeline decreases and the fluidity improves. By contrast, the bubble diameter has little effect on the transport properties of TFSB. The combined results of CFD simulations, slump tests, and strength tests indicate that, when the bubble volume fraction is 15–20 vol %, TFSB can satisfy the necessary strength requirements and exhibit self-flowing transport. The CFD technique provides an intuitive and accurate basis for pipeline transport research and has the potential for wider application in studies of mine backfill.