Search Results (528)

Aiming at the difficult problem of floor heave control in deep coal mine roadways, this paper took the 1224 transportation roadway of Shuguang Coal Mine in Shanxi as the engineering background and carried out the first underground industrial test of floor-slotting pressure relief technology by using special slotting equipment. The aim is to reveal the energy transfer law of the floor rock mass during slotting pressure relief and clarify its inherent connection with stress redistribution and floor heave deformation control. The research adopts a combination of theoretical analysis, numerical simulation, and field tests to systematically explore the energy accumulation characteristics of the floor and the induced mechanism of floor heave. Results show that the maximum energy accumulated in the floor after roadway excavation reaches 6.0 × 10⁵ J, which is the fundamental cause of floor heave. After optimizing the slotting parameters (depth 2.5 m, width 0.2 m), numerical simulation indicates that the surrounding rock stress concentration zone migrates to the deep part, the energy peak shifts down by 2.5 m, the floor plastic zone expands, and the range of the high-energy zone shrinks. Field test results show that the floor heave amount decreases from 30 cm to 20 cm, with a reduction rate of 33%. This study reveals the synergistic mechanism of “energy transfer–stress regulation–deformation control”, verifies the effectiveness and feasibility of the slotting pressure relief technology in the floor heave control of deep, high-stress roadways, and provides a guarantee for the safe and efficient advancement of the working face. Full article

Utilizing excavated waste soil to level gullies offers significant advantages in terms of engineering economy and construction efficiency. However, the stability and deformation risks of high-fill embankments in mountainous gullies under rainfall conditions have attracted significant attention, particularly when such structures are located adjacent to residential areas. This study compares two design schemes for highway high-fill embankments, Scheme 1: high-fill slope supported by stabilizing piles and prestressed anchors, and Scheme 2: ordinary waste soil as the core, foamed lightweight soil (EPS) as the edge band, and reinforcement by a micro-pile retaining wall system. Finite element analysis was used to evaluate the Factor of Safety (FOS), displacements of retaining structures, and characteristic slope points under three conditions (no rainfall, heavy rainfall, and heavy rainfall with soil strength deterioration). The results show that Scheme 2 reduces total costs by 3.5%, shortens the construction period by 14%, and cuts maintenance costs by 65%, with a minimum FOS of 1.56 under extreme rainfall. Further parametric analysis of Scheme 2 optimized key design parameters, and field monitoring data over 6 months verified the reliability of the numerical simulation. This study provides a transferable design-verification pathway for combining lightweight and conventional fills in high embankments, offering technical support for similar projects in complex mountainous areas. Full article

In intelligent excavator applications, traditional excavator posture recognition methods face two major challenges: limited recognition accuracy and insufficient computing resources on edge devices. To address these issues, this study proposes an excavator posture recognition method based on an improved Real-Time Detection Transformer (RT-DETR). First, a new backbone network is designed based on the Reparameterized Vision Transformer to improve feature utilization efficiency while reducing computational demands. Next, the overall architecture is optimized by introducing lightweight Dynamic Upsamplers, which reduce information loss during upsampling and enhance multi-scale feature fusion. In addition, a Cross-Attention Fusion Module is adopted to strengthen local feature extraction while retaining the global modeling capability of the Transformer, thereby improving the discrimination between foreground and background. Finally, a Multi-Scale Fusion Network is introduced to further enhance the multi-scale feature representation ability of RT-DETR. Experimental results show that the proposed method achieves a mean average precision (mAP) of 94.29% for small object detection, which is 7.96% higher than that of the baseline RT-DETR, while reducing the number of model parameters by 34.95%. Compared with YOLO-series models, the proposed method improves mAP by 8.62% to 12.75%. These results indicate that the proposed method outperforms existing methods in both detection accuracy and computational efficiency and provides an efficient and feasible solution for real-time excavator posture recognition. Full article

To improve the blasting performance of tunnel wedge cutting while mitigating vibration effects, this study proposes a precise delayed blasting method and evaluates its effectiveness through a three-dimensional numerical simulation, similarity model test, and field application. The proposed method divides the cut holes into initial and secondary groups and uses electronic detonators to control the delay time. The numerical results show that delayed blasting reduces the peak stress in the surrounding rock, accelerates stress-wave attenuation, improves cavity integrity, and lowers the peak particle velocity (PPV), while maintaining sufficient rock breaking capacity. Model tests conducted under different delay times indicate that the delayed scheme increases the pull efficiency, decreases the ratio of large fragments, and reduces the PPV, with an optimal delay time range of 4~8 ms for moderately weathered limestone. Field tests in the Da Balai Tunnel further verify the effectiveness of the proposed method. Compared with conventional blasting, delayed blasting increases the pull efficiency from 77.8% to 97.3%, reduces the large fragment ratio from 30.6% to 11.4%, decreases the PPV by 52.5%, and increases the dominant vibration frequency by 48.7%. These results demonstrate that the proposed method can simultaneously enhance the rock-breaking quality and vibration control, providing practical guidance for tunnel blasting excavation under complex geological conditions. Full article

The navigation conditions of inland river crossing waterways are directly related to the efficiency and safety of the entire water transport network. In this paper, a two-dimensional hydrodynamic model is established by using Delft3D to simulate the crossflow distribution characteristics before and after the excavation project under the condition of 98% guaranteed flow rate (1690 m³/s). On this basis, the optimized channel width calculation formula is introduced to quantify the drift of ships of different tonnage classes (1000 t and 2000 t) under the action of crossflow. The results show that the maximum lateral flow velocities of north branch, middle Branch and south branch after excavation are 0.57 m/s, 0.42 m/s and 0.50 m/s. Based on the calculation results of the required channel width and the actual situation of the section, the organizational scheme of adopting one-way navigation under the condition of high flow during the flood season is proposed, and the speed of downbound ships (1000 and 2000 t) should not be less than 9 km/h to ensure the safety of one-way navigation. In the upbound ship, the 1000-t class needs to be not less than 6 km/h, and the 2000-t class needs to be not less than 7 km/h. The study establishes an engineering-oriented quantitative link from hydrodynamic cross-current analysis to navigation-width assessment and further to traffic organization under flood-season conditions, providing practical support for navigation safety management in complex inland river confluence reaches. Full article

Future lunar mining missions are expected to involve deeper geological conditions. Understanding the mechanical behaviors of the lunar subsurface regolith is essential to operational safety. Recent findings from the Chang’e-4 and Chang’e-5 missions revealed a marked increase in particle size and relative density of lunar regolith with depth. In addition, the geostatic stress naturally increases with depth. These three variables pose significant challenges for accurately predicting the shear strength. Existing predictive models, such as the Alshibli model, fail to account for the distinct conditions of lunar subsurface regolith. To address this, consolidated drained triaxial tests were conducted on the CUMT-1 lunar regolith simulants. The influences of confining pressure, relative density, and particle size distribution on shear strength were systematically analyzed. A novel indicator, named inter-particle void ratio, was introduced to capture the combined effects of relative density and particle size distribution. Based on this indicator, a new empirical model was proposed for predicting peak shear strength under varying subsurface conditions. The results suggest that deeper lunar regolith may have significantly lower shear strength than previously estimated, primarily due to the combined effect of increased inter-particle void ratio and geostatic stress. This finding has important implications for the assessment of excavation efficiency, underground construction stability, and the overall safety of lunar subsurface infrastructure. Full article

Rock bursts frequently occur in the fault group area in China, seriously restricting the safe and efficient production of coal mines. Based on field investigation, physical experiments, and numerical simulation, this study investigates the rupture types and spatial evolution of microseismic events during the excavation of working face through fault group areas in the TB Coal Mine, where the hard roof asymmetric is cut by faults. It reveals the cooperative instability mechanism of faults and hard roof, as well as the mechanisms of rock burst. Targeted rock burst prevention measures are proposed, including “roof blasting to cut off dynamic and static load transfer” and “coal blasting to reduce abutment stress”. The results demonstrate the following: (1) during mining in fault group areas, the synchronous activation of faults induces shear-type and high-energy microseismic events and the subsequent movement of hard roof, which has been cut by faults, forms asymmetric parallelograms and symmetric inverted trapezoids, and induces tensile-type and high-energy microseismic events. The synchronous activation of faults and the breaking of the hard roof are identified as the primary reason for high-energy microseismic events. (2) As the fault dip angle approaches 90º, the compressive strength of the fault-segmented hard roof strata decreases. Under synchronous activation of faults, roof failure concentrates in the central, right, and left sections for fault combinations with dip angles of 70° + 70°, 90° + 70°, and 110° + 70°, respectively. (3) Numerical simulations reveal two rock burst mechanisms in faults—hard roof systems: a forward “high dynamic stress and high static stress” type and a rear “low dynamic stress and high static stress “ type, which is consistent with in situ monitoring data. (4) For the three stages in which the 502 working face approaches, passes through, and mines away from the fault group area, a stress relief scheme combining roof blasting and coal blasting is proposed. Compared with the 501 working face, during the mining of the 502 working face, the total microseismic frequency and energy decreased by 71.9% and 87.9%, respectively, and the effectiveness of these measures is verified. Full article

Operating data from tunnel boring machines (TBMs) capture the state of both the machine and the ground, and accurate forecasting of their evolving operating variables is essential for assessing rock-mass stability and improving construction efficiency. However, it is difficult for the current methods to predict multivariate TBM driving parameters accurately. Therefore, a novel multivariable time series prediction method was proposed based on Convolution–GRU–Attention (CGA) neural networks. Initially, data preprocessing such as effective data extraction, segmentation, status judgment, and correlation analysis is applied to raw TBM excavation data to construct a parameter database encompassing 5987 TBM excavation cycles. Subsequently, the forecasting model is trained, incorporating techniques such as cross-validation, to ensure accurate predictions of excavation parameter trends. With the average coefficient of determination ($R^2$) for total cutterhead thrust prediction reaching 0.883, and for cutterhead torque prediction achieving 0.923, the evaluation performance of the CGA model with a filter is better than GRU and BPNN. The results demonstrate that the proposed CGA model provides reliable predictions of key TBM operational parameters and offers useful insights into the evolution of TBM excavation behavior. Full article

Current methods for predicting deep excavation deformation suffer from insufficient accuracy and limited generalization capability. Moreover, the applicability of these methods to different types of monitoring data also requires in-depth analysis. To address this, a machine learning-based prediction model, i.e., the VMD-GWO-CNN model, integrating Variational Mode Decomposition (VMD), the Grey Wolf Optimizer (GWO), and the Convolutional Neural Network (CNN), is proposed to predict various types of monitoring data. The GWO algorithm optimizes both the key parameters of VMD and the hyperparameters of the CNN. The optimized CNN model predicts each subsequence decomposed by VMD, and the final prediction is obtained by superimposing these results. Furthermore, the prediction performance of the proposed model is evaluated against the LSTM, CNN, and GWO-CNN models using four metrics (RMSE, MAE, MAPE, R²). The results indicate that all four algorithms possess effective predictive capability for the monitoring data, in which the VMD-GWO-CNN model demonstrates the best performance across all metrics. Specifically, its RMSE for surface settlement prediction is reduced by 59.2%, 34.1%, and 33.0% compared to the LSTM, CNN, and GWO-CNN models, respectively. Moreover, the VMD-GWO-CNN model exhibits strong predictive performance for deformation in slope engineering and subgrade engineering, demonstrating its good applicability across different geotechnical engineering. The findings provide a scientific basis for safe excavation construction and contribute to efficient and rapid execution of foundation pit projects. Full article

Historic cities face a dual challenge of managing waterlogging risks while adhering to strict preservation constraints. Traditional drainage upgrades often require extensive excavation, threatening cultural heritage. This study establishes a quantitative assessment framework for the historic urban district of City B using a 1D-2D-coupled hydrodynamic model (InfoWorks ICM). The model was calibrated using continuous monitoring data, achieving a Nash–Sutcliffe Efficiency (NSE) of 0.91. Its spatial accuracy was subsequently validated against historical waterlogging records, showing a strong consistency between simulated flood-prone areas and observed flood locations. We simulated waterlogging distribution under rainfall events with return periods of 0.5 to 5 years. Results reveal two key deficiencies in the current drainage system under a 0.5-year return period storm event. Firstly, 75.3% of the pipe segments are hydraulically overloaded, failing to meet the design standard. Secondly, this widespread network overload contributes to surface waterlogging, with 9.58 ha (1.80% of the total area) being waterlogged. We evaluated three strategies: Low Impact Development (LID), underground storage tanks, and intercepting sewers. A hybrid grey-green infrastructure (HGGI) system was proposed, integrating source reduction and terminal storage. The HGGI system reduced waterlogged areas by 83.58% (0.5-year event) and 64.87% (5-year event), outperforming single measures. Crucially, this hybrid system achieves minimal intervention in historic street patterns through trenchless construction for intercepting sewers, decentralized LID layout and underground storage tanks, avoiding large-scale road excavation while enhancing flood resilience. This study demonstrates that hybrid strategies can effectively balance flood resilience with environmental and cultural preservation in high-density historic districts. Full article

In the construction industry, struck-by accidents involving heavy equipment such as crawler excavators are a leading cause of worker fatalities and injuries. Existing vision-based hazard detection methods are limited by approximate evaluations, reliance on specific references, and neglect of spatial relationships between equipment and workers, making them inadequate for complex dynamic construction environments. This study aims to address these limitations by proposing a precise and adaptable struck-by hazard detection method. The method integrates four core modules: object tracking via the YOLOv5-DeepSORT model to detect workers, excavators, and their key components; activity recognition to identify the operational states of excavators, working or static, and workers, driver or field worker; proximity estimation based on stereo vision using the BGNet model and camera calibration to calculate 3D spatial distances; and safety identification to assess worker safety status in real time. Validated through three virtual construction scenarios, flat ground, rugged terrain, slope, the method achieved high safety status identification accuracies of 92.71%, 90.04%, and 94.25% respectively. The results demonstrate its robustness in adapting to diverse construction environments and accurately capturing equipment–worker spatial interactions. This research expands the application scope of hazard monitoring in complex settings, enhances safety identification efficiency, and provides a reliable technical solution for improving construction site safety management. Full article

To address persistent problems such as clogging, high digging resistance, incomplete soil removal, and severe pod loss during the operation of shovel-chain peanut harvesters, a hybrid excavation approach was developed based on an in-depth analysis of the mechanical interaction between the peanut plant–soil complex (hereafter referred to as the “complex”) and the harvesting mechanism. The proposed approach integrates vertical and horizontal excavation directions to enhance soil fragmentation and reduce operational resistance. A progressive soil disintegration process was introduced, in which the complex undergoes lateral and longitudinal compression-bending deformation during movement. A driven soil–plant separation scheme was implemented through coordinated operation of upper conveying and lower combing–lifting mechanisms, promoting efficient and continuous material flow. A resistance-reducing digging device consisting of opposing round plow blades and horizontally sliding digging shovels was designed to minimize excavation resistance and soil adhesion. Meanwhile, an anti-clogging separation mechanism, integrating squeezing and feeding rollers and harrow-chain, was developed to improve soil removal and pod separation. Key structural and operational parameters—such as the chain-to-machine speed ratio, tooth-to-chain rotation speed ratio, harrow-tooth spacing ratio, and pushing-tooth transmission ratio—were optimized through theoretical analysis and prototyping. The final design also refined the number of pushing-tooth rows, squeezing and feeding roller geometry, conveying-tooth radius, and the configuration and distribution of rake and stick-tooth shafts. Field experiments were conducted using the developed prototype under sandy loam conditions (11–15% moisture content) with Yu Hua 22 peanut plants (35–40 cm height, 70 cm ridge spacing, 30 cm narrow-row spacing) at a working speed of 1.5–1.6 km·h⁻¹. Results demonstrated that the prototype achieved average ground pod loss, buried pod, and soil carryover rates of 1.13%, 0.95%, and 7.87%, respectively. The entire operation proceeded smoothly without clogging, and continuous conveying of peanut plants was maintained. These findings confirm that the proposed combined excavation and separation system meets and in some respects exceeds the performance requirements for efficient peanut harvesting under typical field conditions. Full article

Reliable preliminary assessment of stress redistribution and rock mass stability is a critical step in tunnel design, providing guidance before detailed numerical modeling and support design are undertaken. This study presents RockStressCalc, a Python-based computational framework that integrates classical elastic stress–displacement analysis with empirical rock mass strength evaluation for circular tunnels within a transparent analytical workflow. The tool combines Kirsch’s closed-form solution for stress redistribution around a circular opening under anisotropic in situ stress conditions with the generalized Hoek–Brown criterion to enable spatially resolved evaluation of elastic strength reserve. The framework assumes a homogeneous, isotropic, linear–elastic rock mass under plane strain conditions and introduces a Stability Factor as a stress-based indicator of proximity to initial yield. The analytical implementation is verified against finite-element simulations performed in Plaxis2D under equivalent elastic assumptions. The maximum stress difference at the excavation boundary remained below 10%, while displacement deviations were below approximately 4%. In addition, comparison between the analytical far-field Stability Factor and the numerical strength reduction multiplier demonstrated close agreement, confirming consistency between the analytical and finite-element formulations under uniform stress conditions. The results show that RockStressCalc provides a computationally efficient analytical baseline suitable for rapid parametric evaluation, sensitivity studies, educational use, and independent verification of numerical models in early-stage tunnel design. By emphasizing explicit coupling of stress redistribution and strength evaluation within a reproducible framework, rather than introducing new constitutive models, the proposed approach offers practical engineering value as a screening and benchmarking tool and provides a foundation for future probabilistic or extended tunnel stability analyses. Full article

Soft–hard composite strata are widely distributed in the surrounding rock of deep tunnels, which severely reduces TBM excavation efficiency. To elucidate the rock-breaking mechanism of TBM disc cutters in composite strata and to address unresolved issues related to cutter force evolution, a self-developed rotary cutting test platform was employed, and three types of large-scale samples (red sandstone, granite, and red sandstone–granite composites) were prepared, on which systematic rotary rock-cutting experiments were conducted under varying confining pressures, rotational speeds, and penetration depths. The results indicate that rock failure in composite strata exhibits pronounced heterogeneity, with significant stress concentration occurring at soft–hard rock interfaces, leading to abrupt increases in normal force and torque. Penetration depth is the most sensitive factor influencing cutting force and specific energy, followed by confining pressure and rotational speed. The minimum specific energy and maximum rock-breaking efficiency are achieved at a penetration depth of 2.5 mm, a confining pressure of 7 MPa, and a rotational speed of 2.5–3 r/min. Furthermore, a dynamic model describing the evolution of disc cutter normal force and torque at soft–hard rock interfaces was derived based on the CSM theoretical framework, and its validity was verified using the experimental results. Integrating experimental observations with theoretical analysis reveals that rock fragmentation in composite strata is dominated by radial tensile cracking in hard rock and shear-dominated crushing in soft rock, while strong stress perturbations and coupled failure occur at the composite interface. This study clarifies the force evolution and fracture mechanisms of disc cutters operating in composite strata and establishes a reliable dynamic prediction model for cutter loads, providing theoretical support and engineering guidance for TBM parameter optimization and cutterhead design. Full article

Accurate determination of in situ stress is fundamental for the safe and efficient design of underground construction projects such as tunnels, caverns, and deep mining excavations. Conventional techniques—particularly overcoring and hydraulic fracturing—have been widely adopted for decades, but their practical use is often constrained by high operational cost, rigorous field requirements, and logistical limitations at depth. As engineering projects advance into deeper and more complex geological environments, these constraints have prompted growing interest in laboratory-based, core-derived stress measurement approaches. Such methods utilize the stress-relief deformation that occurs when drill cores are extracted, enabling stress estimation without extensive downhole instrumentation. This paper presents a critical review of core-based stress measurement techniques based on a structured survey of peer-reviewed literature retrieved from major scientific databases (Web of Science, Scopus, and Google Scholar), covering studies published from the 1960s to 2025. The review examines Anelastic Strain Recovery (ASR), Differential Strain Curve Analysis (DSCA), Deformation Rate Analysis (DRA), acoustic-emission-based Kaiser effect approaches, and the emerging Diametrical Core Deformation Technique (DCDT). Recent studies show that DCDT, which measures instantaneous elastic diametrical deformation of cores, provides a more direct and physically transparent link to differential in situ stress, with reduced sensitivity to time-dependent effects. The DCDT, based on precise measurement of instantaneous elastic deformation upon coring, offers high-resolution stress estimation with minimal disruption to field operations. Its compatibility with optical scanning, laser micrometers, and CT imaging highlights its potential as a practical alternative to conventional techniques. A comparative synthesis of assumptions, accuracy, and applicability is provided, and key limitations and future research needs of core-based stress measurement methods are identified. The findings of this review provide practical guidance for selecting stress measurement techniques and support the application of core-based methods, particularly DCDT, in deep underground engineering, where cost-effective and reliable stress characterization is required. Full article