In blasting design, blasting parameters poorly match the actual blast area, while manual adjustments result in low efficiency and suboptimal borehole layout. This study therefore proposes a borehole layout optimization algorithm based on the minimum unit of the initiation network. This algorithm determines the optimal borehole spacing and density coefficients through 3D numerical simulation of bench blasting. It combines hole-by-hole initiation layout and uses virtual borehole positioning and the Lloyd algorithm for automated placement and adjustment of borehole positions. This achieves both overall normative design and localized adaptive adjustments of the initiation network in the blast area. Experimental results show that the algorithm enabled rapid and reasonable design of borehole positions in irregular blast areas with fewer iterative optimizations. Additionally, the overall borehole distribution remained uniform during boundary adaptation, with the variation coefficient of the borehole area controlled at a low level. The optimized design and precise execution of the algorithm significantly improve the rationality and adaptability of the blasting layout, while enhancing its operational efficiency.

Stratigraphic interface characterization and strength parameter assessment of geomaterials constitute fundamental research priorities in geological and geotechnical engineering. While measurement while drilling (MWD) and drilling process monitoring (DPM) have emerged as critical techniques for acquiring real-time drilling parameters, inherent limitations in data interpretation persist. The critical challenge of random fluctuations in MWD-derived penetration rate measurements exhibits poor correlation with the stratified homogeneity characteristics of geological formations. Such discrepancies undermine the reliability of stratigraphic classification and mechanical property analysis. Through systematic comparison of MWD and DPM datasets combined with quantitative parameter evaluation, this investigation reveals significant methodological distinctions in data acquisition accuracy. Machine learning-enhanced analysis employing Support Vector Machine (SVM) algorithms demonstrates that DPM-derived parameters provide superior stratigraphic identification capabilities. Our findings indicate that DPM implementations achieve 20.57% and 38.01% higher resolution in interface detection along two drillholes compared to the conventional MWD approaches. This improvement allows for better prediction of stratigraphic profiles and more precise guidance in subsequent geological and geotechnical engineering practices.

Blast hole inspection robots in open-pit mining play a vital role in ensuring the safety of blasting operations and advancing intelligent mining. Traditional manual inspection methods suffer from low efficiency, limited accuracy, and high operational risk, making them inadequate for large-scale and efficient open-pit mining. To address these challenges, a binocular vision-based three-dimensional localization method for blast holes is proposed to provide high accuracy, real-time performance, and robustness for inspection robots. In the method design, a weighted Laplacian equation filling strategy guided by reference images is introduced to overcome the sparsity and severe noise of depth labels during training. This strategy achieves globally consistent completion of invalid depth regions, thereby improving the integrity and reliability of training data. A target detection network is then used to enable rapid detection and identification of blast hole regions, ensuring efficiency and accuracy in the subsequent stereo matching process. During stereo matching, an ECANet channel attention mechanism is incorporated into the iterative geometry encoding volume (IGEV−Stereo) network to enhance feature extraction capability. In addition, an edge-aware loss function based on Canny edge masks is designed to constrain boundary feature matching, effectively reducing matching errors at edges without increasing inference overhead. Finally, precise three-dimensional localization of blast holes is achieved using camera calibration parameters. Experimental results show that, on our self-constructed blast hole dataset, the target detection algorithm achieves an accuracy of 93.9%, and the improved stereo matching algorithm reduces the average end-point error (EPE) by 20.36% compared with the baseline. The single-frame inference latency is 1.8 ms for target detection and 77.44 ms for stereo matching, yielding an end-to-end latency of 79.24 ms, meeting real-time application requirements. In field tests conducted in real open-pit mining scenarios, the 3D depth error of blast holes reached up to 25 mm, highlighting high accuracy and strong robustness under complex blasting conditions. These findings provide new insights and effective technical support for the intelligent development of blast hole inspection robots and offer significant engineering application value for improving the safety and automation of mining operations.

Directional fracture blasting technology is widely applied in blasting engineering. To investigate the fracture mechanisms of three blasting techniques-slit blasting, notched blasting, and coupling blasting-this study employed numerical simulation, a novel digital laser dynamic caustics experimental system, and 3D laser scanning. First, the dynamic fracture characteristics of the three blasting methods were revealed using the digital laser caustics system. The results show that, compared to slit blasting and notched blasting, coupling blasting improves directional fracture propagation effectiveness by at least 153.5 % and 211.3 %, respectively. It also exhibits the highest peak values of stress intensity factor and crack propagation velocity, with the slowest decay rates, indicating the longest duration of crack-driving force. Then, the microstructural characteristics of the directional fracture surface under coupling blasting were analyzed using 3D laser scanning. The surface roughness was found to be highest in the early stage of crack propagation, lowest in the middle stage, and intermediate in the final stage. Finally, the initiation mechanisms of the main directional cracks under the three blasting methods were simulated using AUTODYN, and their respective advantages and disadvantages were compared. The results demonstrate that coupling blasting, through a composite structural design of "notched initiation + slit guidance," significantly enhances crack initiation efficiency and effectively suppresses nondirectional crack propagation. This study provides both theoretical support and experimental reference for the optimized design of directional fracture blasting technology.

ObjectiveDeep rock masses are usually in varying damage degrees induced by excavation disturbance before dynamic catastrophes appear. The complex and ever-changing occurrence environment in deep areas places higher demands on the stability of deeply buried rock masses and the prevention and control of dynamic disasters. In response to the dynamic response of damaged rock masses during dynamic catastrophes, the mechanical characteristics of pre-compressed sandstone under impact compression and splitting tensile loads are studied.MethodsFirstly, acoustic emission is used to monitor the damage degree of sandstone after different upper limit static loads, and tomography was employed to verify the damage degrees. The upper limit of static load is 20%, 40%, 60%, and 80% of the uniaxial compressive strength of sandstone, and the lower limit of cyclic load is uniformly set to 2kN with 6 cycles. Then, the dynamic strength, fracture process, and energy evolution of damaged sandstone under impact compression and splitting tensile loading at impact pressures of 0.30, 0.35, and 0.40 MPa are studied by the split Hopkinson pressure bar (SHPB) and high-speed camera. Finally, the strain field evolution of the damaged sandstone under impact splitting tensile loading and the fragmentation characteristics of the damaged sandstone under impact compressive loading are investigated by adopting digital image correlation (DIC) and fractal dimension, respectively.Results and Discussions Sandstone exhibits varying degrees of damage after being subjected to cyclic static loads with different upper limits. The time-lapse double-difference tomography, based on acoustic emission monitoring, provides clear evidence of this phenomenon and further confirms the heterogeneous distribution of damage within the loaded rock. Due to the effects of cyclic static loads, internal defects in the damaged sandstone influence the propagation of stress waves under impact loads. This results in significant variations in dynamic compressive strength, dynamic splitting tensile strength, and dissipated energy density, with the dynamic strength decreasing as the degree of sandstone damage increases, while the energy dissipation density exhibits the opposite trend. High-speed camera footage of the fracture process of damaged sandstone under impact load reveals four stages: initial deformation, crack initiation, formation of fractured rock blocks, and ejection of fractured rock blocks. The degree of damage significantly affects the fracture process, particularly under high-strain rate impact loads. As the impact pressure or degree of sandstone damage increases, the number and scale of crack initiations also increase, during the crushing and fragmentation stage, the number of broken rock blocks rises, and circumferential cracking may occur. Moreover, the degree of fragmentation of the sandstone also increases, while the fragmentation size decreases, and the quantity of fragmented pieces increases after the application of impact compression load. The stress wave propagates through the sandstone under impact splitting tensile load, creating a strain concentration zone at the center, which then expands radially toward the rock-to-rod contact surface. During this expansion in the strain concentration zone, cracks initiate at the center of the specimen and progressively develop, eventually penetrating the entire sandstone specimen. As impact pressure or the degree of damage increases, the strain caused by initial cracking at the specimen's center also increases. Furthermore, both the strain and the extent of its influence grow with higher impact pressure or greater damage.ConclusionsThe change of dynamic mechanical properties of damaged sandstone is closely related to the damage degree of sandstone after static load. With the increase of impact air pressure or the damage degree of sandstone, the dynamic strength reduction rate and the growth rate of energy dissipation density of the damaged sandstone under impact loading (impact compression and impact split tension) are both Weibull cumulative distribution functions related to the ratio of static load upper limit to static strength. The fragmentation degree of damaged sandstone after impact compression loading and the strain at the center of the specimen at the same moment under impact splitting tensile loading increase with the increase of sandstone damage degree, and the higher the impact air pressure, the smaller the variability of the crushing degree and strain concentration caused by the distinct damage degrees. Moreover, sandstones with higher damage degrees showed circumferential rupture and spall under higher impact compression and split tensile loading, respectively. The research results provide some references for studying dynamic strength, energy evolution, and fragmentation characteristics of damaged rock masses and risk mitigation when dynamic catastrophes manifest.

To prevent structural catastrophic responses induced by the collapse of the roof in goafs,based on field investigations and considering the impact disturbance behavior of roof collapses in goafs on the floor,a structural response model for the impact of goaf collapses on the floor and a dynamic response governing equation are established.The characteristics and attenuation laws of the structural response of the floor in goaf groups are studied,and the effects of factors such as joint density and thickness-to-span ratio on the displacement and stress response of the floor are analyzed,revealing the characteristics of its structural response.The results show that with the increase of the distance,the displacement and stress of the floor attenuation gradually and the attenuation rate decreases under the impact load.The response of floor is affected by the collapse position,distance and surrounding rock.As the collapsed goaf is closer to the center,the displacement and stress attenuation rates of the floor are smaller,and the impact and damage to the surrounding goafs are more extensive.With an increase in joint density,the stiffness,vibration frequency,and energy dissipation rate of the floor decrease,while the peak values of displacement and tensile stress show an increasing trend,leading to a reduction in impact deformation resistance and stability.As the thickness-to-span ratio increases,the peak values of displacement and tensile stress of the floor decrease exponentially.A significant inflection point appears when the thickness-to-span ratio is 0.6,with the attenuation rate differing by more than 10 times.Increasing the thickness-to-span ratio of the floor can shorten the response time,reduce displacement and tensile stress,and improve the stability of the floor.The reliability of the theoretical method is verified by numerical methods.The research results can provide some theoretical support for the safe production and disaster prevention and control in open stope mining method.

The advancement of intelligent mining in open-pit operations has imposed higher demands on geological transparency, aiming to provide a robust foundation for intelligent drilling and charging. In this study, a linear array of 120 nodal seismometers was deployed along the surfaces of the C8 and C9 platforms at Fenghuang Mountain to investigate cavities within the rock mass and prevent improper intelligent charging. The seismometers were 1 m apart along measurement lines, with a 2-m spacing between lines, and the monitoring time for each line was set at 2 h. This deployment was paired with spatial autocorrelation and station autocorrelation to analyze ambient noise seismic data and image the velocity and structure within the rock mass. The results demonstrate that the locations and sizes of cavities or loose structures can be accurately identified at the prepared excavation site. Compared with traditional geological exploration methods for open-pit mines, the approach in this study offers higher accuracy, greater efficiency, reduced labor intensity, and insensitivity to water conditions. Ambient noise seismic imaging for detecting adverse geological conditions in open-pit mines provides critical insights and references for intelligent mining advancements.

This study investigates the dynamic crack propagation mechanism in damaged rocks under blasting excavation in complex geological conditions. A novel rock fracture analysis method based on pre-compression-induced random damage is proposed, overcoming the limitations of traditional prefabricated crack models. Innovatively, multi-level cyclic static pre-compression is applied to simulate the random damage distribution in engineering-scale rocks, combined with high-resolution computed tomography (CT) imaging to achieve non-destructive 3D visualization of internal crack morphologies under explosive loading. A theoretical model for predicting blast-induced crack propagation radius in damaged sandstone is established and validated through integrated laboratory blast experiments, CT scanning, and PFC-2D numerical simulations, demonstrating a prediction error margin below 5%. Key findings reveal a significant positive correlation between sandstone damage levels and the expansion range of blast-induced cracks as well as crater dimensions. The pre-existing crack network in damaged rocks effectively guides gas wedging effects, unveiling a “weakening-synergistic fracturing” dual mechanism. These results provide theoretical foundations and technical support for optimizing blasting parameters and mitigating dynamic disasters in tunnel engineering under complex geological settings.

Multi-modal personality recognition integrates text, audio, and video information to accurately identify personality traits, offering significant value in fields like human-computer interaction. However, existing methods face feature extraction, noise removal, and modal alignment challenges. These issues impact recognition accuracy and model robustness. To address these issues, we propose an Emotion-Assisted multi-modal Personality Recognition using adversarial Contrastive learning (EAPRC). EAPRC leverages text, audio, and image data, incorporating emotional information to enhance recognition accuracy and robustness through adversarial training. The model reduces inter-modal noise using adversarial sample generation and employs joint class propagation contrastive learning to extract discriminative feature representations. For emotion-based assistance, EAPRC uses emotion feature-guided fusion and emotion score decision fusion to exploit the correlation between emotions and personality traits fully. It further improves the accuracy and stability of multi-modal personality recognition. Experimental results on the ChaLearn First Impressions and ELEA datasets demonstrate that EAPRC performs effectively, validating its capability in multi-modal personality recognition tasks.

In sharp contrast to prefabricated cracks, the damage to rock masses resulting from external disturbances such as excavation disturbances and tectonic movement varies substantially as to the incidence, density, and magnitude of defects. The growth ratio of the energy dissipation density proportion D(Rω (α)) of the damaged rock under impact loading is closely related to the static damage factor D(α) and is theoretically explored based on the Weibull distribution in this paper. Sandstones with varied damage levels after distinct static precompression, as described by CT imaging, are used to evaluate the impact load of different driving pressures. In addition, a high-speed camera and geometric fractal are used to exhibit the ejection and fragmentation characteristics of the pulverized sandstones after impact loading. The experimental outcomes confirm the theoretical study where the function of D(Rω (α)) involving D(α) obeys the Weibull distribution, and the D(Rω (α)) slowly rises with the expansion of the damage factor. With the increase of either the damage level or driving pressure of the sandstone, the number of pulverized rocks, the fragmentation degree, and the D(Rω (α)) all increase. These results further advance rock dynamic theory and corroborate the energy evolution, ejection, and fragmentation characteristics of damaged sandstone under impact loading. These results can also serve as references for rock dynamic risk mitigation under dynamic catastrophes..

This study presents a metaheuristic-hybridized model based on sparrow search algorithm (SSA) and multi-output least-squares support vector regression machines (SSA-MLS-SVR) to predict the continuous shear displacements of rock fractures, which is closely related to the geo-structure stability and safety. Based on the database including 258 continuous shear samples of rock fractures, two subdatasets recording continuous shear displacements in three (216 samples) and four steps (141 samples) are used to develop the proposed model respectively. In the model improvement phase, three kinds of nonlinear transformations are utilized to eliminate the low sensitivity of SSA-MLS-SVR model caused by value scale and data distribution. The experimental results show that the nonlinear transformations can significantly improve the prediction accuracy of SSA-MLS-SVR. Additionally, some characteristics of the continuous shear process of rock fractures are also discovered via extended experiments. First, the prediction accuracy of the first-step shear displacement can be greatly improved using the peak shear displacement as an input. And it is inferred that the beginning of the post-peak shear process (the first-step shear) may be closely related to the peak shear of rock fractures. Second, the post-peak shear process is a continuous random process, in which the displacement of each shear step is only highly correlated with the most recent shear displacements in the time dimension.

Interconnected cracks are prefabricated on plexiglass plates (polymethyl methacrylate, PMMA) to study the effect of crack length on the initiation and propagation of interconnected cracks under impact loads. A new dynamic caustics test system was constructed to analyze the specimen's initiation process; the fractal method was used to quantify crack propagation; and the numerical simulation was used to monitor the specimen's full-field stress change. The results show that, with the direction of the impact loads as the axis of symmetry, interconnected cracks with different lengths and symmetrical angles, only the longer cracks initiate under the action of impact loads. With the increase in the length of one side of the interconnected crack, the crack initiation time is delayed, the trajectory of crack propagation becomes more irregular, and the peak propagation velocity of the crack increases first and then decreases. After the analysis, it was concluded that there is a certain competitive relationship in the crack tip propagation law between interconnected cracks with different lengths. In the energy storage stage, the tip of the longer crack is more likely to accumulate energy than that of the shorter crack, and it also has a suppressive effect on the energy storage of the latter. In the initiation and propagation stages, the energy at the tip of the uninitiated shorter crack will transfer to the tip of the longer crack, promoting its propagation. The research provides a basis for analyzing the initiation and propagation laws of interconnected cracks in practical engineering applications.

Borehole breakouts significantly influence drilling operations’ efficiency and economics. Accurate evaluation of breakout size (angle and depth) can enhance drilling strategies and hold potential for in situ stress magnitude inversion. In this study, borehole breakout size is approached as a complex nonlinear problem with multiple inputs and outputs. Three hybrid multi-output models, integrating commonly used machine learning algorithms (artificial neural networks ANN, random forests RF, and Boost) with the Walrus optimization algorithm (WAOA) optimization techniques, are developed. Input features are determined through literature research (friction angle, cohesion, rock modulus, Poisson’s ratio, mud pressure, borehole radius, in situ stress), and 501 related datasets are collected to construct the borehole breakout size dataset. Model performance is assessed using the Pearson Correlation Coefficient (R2), Mean Absolute Error (MAE), Variance Accounted For (VAF), and Root Mean Squared Error (RMSE). Results indicate that WAOA-ANN exhibits excellent and stable prediction performance, particularly on the test set, outperforming the single-output ANN model. Additionally, SHAP sensitivity analysis conducted on the WAOA-ANN model reveals that maximum horizontal principal stress (σH) is the most influential parameter in predicting both the angle and depth of borehole breakout. Combining the results of the studies and analyses conducted, WAOA-ANN is considered to be an effective hybrid multi-output model in the prediction of borehole breakout size.

The combination of the dynamic action of explosion stress wave and the static action of explosion gas expansion is what primarily drives rock-breaking blasting, and their different intensities lead to different blasting effects. Therefore, experiments were conducted to explore the damage behaviour of the surrounding medium caused by different blast-induced dynamic and static loadings using digital laser Schlieren and digital laser dynamic caustic systems. The results were as follows: In the air medium, when the explosives detonated, TATP (triacetone triperoxide) had the strongest quasi-static effect, and the highest velocity explosion shock wave and products compared with those of NHN (nickel hydrazine nitrate) and DDNP (diazodinitrophenol). Part of the TATP explosion product was ahead of the shock wave front, whereas for NHN and DDNP, their explosion products were behind the propagation of the shock wave front. The highest pressure peak of TATP was the result of the combined action of the shock wave and explosion product impacting the sensor. In the solid medium, NHN, the explosive with the strongest dynamic load, had the strongest stress wave and highest stress intensity factor peak of the main crack. The velocity reached the peak value at the early stage of propagation, and the dynamic action had a dominant effect on the cracking of the crack; the stronger the dynamic action, the higher the crack initiation energy. The stress intensity factor and propagation rate of the main crack of TATP with the strongest quasi-static effect decreased slower than those of the other explosives; therefore, the main crack propagation time and length were the longest. After cracking, the quasi-static effect dominated the process of crack propagation, where the stronger the quasi-static effect, the longer duration of the driving force of crack propagation. The research results provide a basis for customising explosives for different functions in practical engineering and realising the fine and efficient utilisation of explosion energy.

Geotechnical engineering in cold regions frequently involves dealing with frozen fractured rock masses, particularly in the activities of strip mining and tunnel support design, where tensile failure predominates as the main failure mode in stress-driven failures. Seasonal freezing can adversely affect the performance of rock masses. To investigate the tensile characteristics of frozen rock masses, marble specimens with double parallel ice-filled flaws were artificially frozen and subjected to Brazilian splitting experiments at a loading rate of 0.001 mm/s. The influence of the angle of the double coplanar flaws and the rock bridge angle of ice-filled flaws on the tensile behaviours were numerically studied by RFPA3D (3D Rock Failure Process Analysis), a finite element method specifically developed for simulating rock failure. Results showed that as the angle of the double parallel ice-filled flaws increases, tensile strength initially decreases and then increases. Furthermore, in specimens with the double coplanar ice-filled flaws, an increase in the angles of the flaws and rock bridge leads to a gradual decrease in tensile strength. The spatial distribution of ice-filled flaws is a crucial factor that influences the failure mode after split cracking occurs. The ice filling and bonding mechanism controls the tensile strength and cracking behaviour of frozen rock masses. The findings of this study provide valuable insights and serve as a theoretical foundation for designing blasting parameters and disaster prevention in strip mines located in cold regions.

The flow characteristics of blasthole stemming slurry (BSS), predominantly comprising yellow mud (YM), tail mud (TM), or drilling cuttings (DC), were systematically investigated. Various influencing factors, including slurry mass concentration, the addition of TM or DC, and the mass ratio of TM to YM (TM/YM) and DC to YM (DC/YM), were meticulously examined. Experiments were conducted to assess the fluidity, rheological properties, and bleeding rate of BSS samples, which were prepared by manipulating slurry mass concentration and the proportions of TM or DC. The results indicate that the rheological properties of BSS are suitably described by the Herschel-Bulkley model. A critical mass concentration was identified, beyond which the flowability of BSS rapidly deteriorates. Replacing YM with an equivalent amount of TM at a mass concentration of 59% increased the yield stress by 167.30%, while reducing the bleeding rate to 0 within the 53%–59% mass concentration range. Conversely, replacing YM with DC at a mass concentration of 62% reduced the yield stress by 63.96%, while increasing the 60-minute bleeding rate from 0% to 1.44%. Increasing the TM/YM ratio resulted in reduced fluidity, elevated yield stress, and a variable degree of shear thickening. The degree of shear thickening was highest when the TM/YM ratio was 1, with significant impacts on differential viscosity at higher shear rates. On the other hand, increasing the DC/YM ratio enhanced fluidity, decreased yield stress, and influenced the degree of shear thickening and differential viscosity, with the highest shear thickening and lowest differential viscosity observed at a DC/YM ratio of 3. The bleeding rate of BSS consistently rose with the increase in the DC/YM ratio.

The propagation mechanism of explosion stress waves in frozen rock mass is the main factor affecting the blasting efficiency and safety construction of strip mines in alpine cold regions. In order to study explosion stress wave propagation and crack extension in the blasting process of frozen rock mass with ice-filled cracks, RFPA2D is adopted to simulate the influence of the geometric parameters of ice-filled cracks (ice-filled crack thickness d, normal distance R from blasting hole to the ice-filled crack, and ice-filled crack angle α), loading intensity and loading rate on the explosion stress wave propagation effect and the damage range. The results show: The attenuation trend of explosion stress waves decreases gradually with an increase of thickness (e.g., In the case of R is 0.2 m, when d is 0.02 m, 0.04 m, and 0.08 m, the calculated attenuation factor of the minimum principal stress peak value is 7.128%, 18.056%, and 30.035%, respectively), and it decreases slightly with an increase of normal distance and ice-filled crack angle. The damage elements range of the ice-filled crack decreases when the ice-filled crack thickness and normal distance increases. The loading intensity and the loading rate have a significant influence on blasting hole fracture patterns. The ice-filled crack has a guiding effect on the growth of blasting cracks at the blasting hole. Nevertheless, the existence of ice-filled cracks inhibits the propagation of explosion stress waves in frozen rock mass.

In the realm of open-pit mining, the characterization of blast pile fragmentation poses significant challenges. This study pioneers a novel approach, harnessing the capabilities of 3D laser scanning technology to acquire comprehensive spatial data of blast piles. Essential to this research is the deployment of sophisticated data processing techniques, including the Random Sample Consensus (RANSAC) for plane fitting and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) for clustering algorithms, to meticulously delineate the contours of rock blocks within blast piles. The innovative methodology facilitates swift determination of rock block volumes and their maximum particle dimensions through the calculation of 3D convex hulls and Oriented Bounding Boxes (OBB). Additionally, the application of Delaunay triangulation to the blast pile's 3D point cloud data culminates in the creation of a detailed mesh model, from which the blast pile's volume is accurately derived using projection methods. Rigorous indoor testing has yielded a relative error margin of approximately 4.61% for block volumes and 4.75% for particle diameters under stacked conditions. In practical field applications, the method exhibits commendable accuracy, with an average rock block identification accuracy of 80.4%, increasing proportionally with the size of the rock blocks. The calculated volume of the blast pile closely mirrors actual excavation volumes, manifesting a relative error of 4.85%. Computational errors for key metrics such as the blast pile's height, forward throw distance, and lateral extent were found to be 2.92%, 3.91%, and 4.29%, respectively. The findings of this study are instrumental in assessing blasting effectiveness and in refining blasting parameters, marking a significant advancement in the field of open-pit mining.

为了解决湖南某矿顶板破碎条件下缓倾斜薄矿体难采问题,提出通过优化地下采场爆破参数来控制采场爆破,以减弱爆破活动对破碎顶板的影响,提高顶板自稳时间.首先对影响该矿采场爆破效果的主要因素诸如炮孔深度、炮孔倾角、掏槽孔孔间距和炮孔直径等进行分析,确定自变量;其次确定抛掷距离、大块率、炮孔利用率和炸药单耗等能反映采场爆破效果优劣的指标为因变量,并基于自变量和因变量建立数学模型;最后利用非支配排序遗传算法Ⅱ(Non-dominated Sorting Genetic Algorithms Ⅱ,简称 NSGA-Ⅱ)对爆破参数进行优化.试验结果显示,随着迭代次数的不断增加,爆破参数水平逐渐稳定并趋于一个最优值,最终找到一组最佳爆破参数组合.利用算法对爆破参数寻优能有效降低人工干预,改善爆破效果,对井下爆破有重要的指导意义.