Search Results (2,987)

To address the difficulty of directionally cutting thick, hard key strata in gob-side entry retaining using conventional blasting or hydraulic fracturing, this paper proposes a high-pressure water-jet slotting-induced pre-cracked weakening belt (PCWB) roof-cutting technology. Several finite-length PCWBs are arranged within the key stratum and designed to coalesce into a plane, inducing through-going roof failure along a pre-determined path. A fixed–fixed key strata beam model combined with linear elastic fracture mechanics shows that the double-belt configuration forces the bending moment and shear force to concentrate in a thin rock bridge, where bending and shear stresses are amplified by about 1.5–2.8 times and 1.2–1.7 times, respectively, for 2–4 m thick key strata, providing a mechanical basis for preferential tensile–shear failure. Two-dimensional RFPA2D simulations reveal “width-dominated, length-assisted” control of cutting performance and identify an optimal weakening belt geometry of about 400 mm in width and 200 mm in length. Three-dimensional numerical modeling of parallel slot pairs indicates that intra-pair spacing of about 40 mm produces a continuous, directional weakening belt, whereas smaller or larger spacing causes, respectively, destructive interference or loss of connectivity. High-pressure water-jet tests (320 MPa, 0.33 mm nozzle, 1.30 mm/s traverse speed) on limestone blocks confirm that single slots can penetrate the full thickness and that cracks from adjacent slots coalesce through the rock bridge, forming a wide, straight fracture band. Field application in the Dongjiang Mine (3.5 m limestone key stratum, ~400 m depth) shows that the first weighting is advanced from the 7th to the 3rd day, peak support resistance is reduced from 8.8 to 7.4 MPa, and periodic weighting becomes more frequent and smoother. The PCWB technology is therefore suitable for panels with 2–4 m thick hard key strata at similar depths, offering precise key stratum severance, active stress relief, and safe, controllable construction. Full article

Weak alternating electric fields are widely used in neuromodulation techniques such as transcranial alternating current stimulation (tACS), yet the precise biophysical mechanisms underlying neuronal responses remain incompletely understood. Current computational models often neglect the electrical properties of the extracellular microenvironment, limiting their predictive accuracy. Motivated by experimentally observed frequency-dependent modulation of neuronal activity, we developed a two-compartment model of hippocampal CA3 pyramidal neurons in which extracellular resistance is explicitly parameterized and systematically examined as a key factor influencing neuronal response properties under external electric fields. Within a dual-compartment Hodgkin–Huxley framework, the neuron is divided into a “soma–basal dendrite unit” and an “apical dendrite unit,” accounting for voltage polarization induced by external fields. Using phase-locking ratio curves and three-dimensional parameter response surface, we systematically characterized neuronal sensitivity to field parameters and examined how potassium equilibrium potential ($V_K$) and extracellular resistance ($R_{\mathrm{out}}$) modulate these responses. Our results demonstrate that increasing $R_{\mathrm{out}}$ enhances neuronal responsiveness to external fields, while $V_K$ variations primarily regulate intrinsic excitability. These findings provide mechanistic insights into the frequency-dependent modulation of neuronal responses under weak electric fields, consistent with phenomena observed in biological neural systems, and provide a mechanistic and theoretical framework for understanding the joint effects of electric field amplitude and frequency on neuronal sensitivity to weak electric fields, which may help inform future neuromodulation strategies. Full article

Resilient wheels are widely employed in metro vehicles to mitigate vibration and noise, in which rubber damping components play a critical role in load transmission and fatigue resistance. However, stress concentration and cyclic loading can significantly compromise their durability and service life. In this study, the structural optimization and fatigue life of rubber damping components in resilient wheels are systematically investigated based on finite element analysis and in-service metro operational data. A three-dimensional finite element model incorporating hyperelastic material behavior is developed to evaluate stress distributions under three representative conditions: press-fit assembly, straight-line operation, and curved-track operation. Based on the resulting stress fields, critical high-stress regions within the rubber component are identified and selected as targets for structural optimization. The Design of Experiments (DOE) methodology, integrated with the Isight 2022 optimization platform, is employed to determine the optimal geometric parameters that minimize the von Mises equivalent stress. Furthermore, a fatigue life prediction framework is established using actual metro service mileage data. Fatigue performance is assessed using Fe-safe 2022 software in conjunction with rubber fatigue crack propagation theory, and the results before and after optimization are systematically compared. This study demonstrates that stress concentrations in resilient wheel rubber damping components predominantly occur at fillet transition regions, governed by load transfer characteristics under press-fitting and service conditions. Through DOE-based structural optimization, the critical geometric parameters are effectively refined, leading to a significant reduction in stress levels in key regions. As a result, the proposed approach markedly improves fatigue performance, extending the minimum fatigue life from 1300 days to 24,322 days, thereby substantially enhancing the durability and reliability of the resilient wheel system. Full article

To improve the aerodynamic design efficiency of nacelle intake systems for wing-mounted civil aero-engines under multiple operating conditions, an integrated multi-objective optimization method was developed to address the limited optimization efficiency and robustness encountered in conventional approaches. The proposed method employed parametric techniques to construct three-dimensional non-axisymmetric nacelle geometries and integrated flow-field simulations with performance evaluation modules, forming a hybrid optimization framework based on a Kriging surrogate model coupled with the NSGA-II genetic algorithm. Two-dimensional numerical analyses were employed to rapidly evaluate inlet profiles and constrain the three-dimensional design space. Following the reduction in the design space, the three-dimensional optimization simultaneously accounted for multiple performance objectives, including nacelle drag and block fuel consumption during cruise conditions, as well as inlet distortion and flow separation under off-design conditions. A set of Pareto-optimal solutions was obtained through surrogate-based prediction and validated using high-fidelity CFD simulations. The results indicate that the optimized nacelle configuration achieves a 0.933% reduction in drag coefficient and a 0.628% decrease in block fuel consumption under cruise conditions. Under crosswind conditions, the inlet total pressure recovery coefficient is increased by 2.76%, accompanied by a pronounced reduction in flow separation, while under maximum-lift coefficient conditions, the total pressure recovery remains above 99%. These results demonstrate that the proposed optimization approach enables coordinated aerodynamic performance improvements across multiple operating conditions while simultaneously enhancing overall aircraft fuel efficiency, providing an effective strategy for advanced nacelle aerodynamic shape design. Full article

To address the problems of uneven stubble height and high missed-cutting rate caused by the insufficient profiling capability of traditional forage harvesters in complex hilly terrain, this paper designs a three-degrees-of-freedom (DOF) profiling header primarily for typical hilly terrain with gentle slopes of 8–15°. Through pitch, roll, and height adjustments, it stably maintains stubble height at 150 mm. Subsequently, geometric analysis and structural optimization achieved kinematic decoupling among all degrees of freedom, thereby overcoming the inherent limitations of the two-DOF header, such as poor adaptability to longitudinal slope and strong adjustment coupling. Three-dimensional modeling was completed in SolidWorks, multibody dynamics simulation was performed in ADAMS, and a profiling control system incorporating a hydraulic system, multi-source sensor fusion, and a fuzzy PID controller was built. The dynamics simulation results show that under the working conditions of 15° longitudinal and 10° transverse slopes, the stubble height error of the header is controlled within 10%, the attitude angle adjustment error is less than 0.5°, and the dynamic response is excellent. Prototype field tests showed that, compared with the two-DOF header, the three-DOF profiling header improved the stubble height stability by about 35%, reduced the missed-cutting rate by about 5%, and increased the operating efficiency by about 15%. No cutting blade contact with the soil occurred, verifying the rationality of the mechanism design and its adaptability to terrain. This study provides an effective technical solution for improving the mechanization level of forage harvesting in hilly and mountainous areas. Full article

In the field of engineering, the advancement of automated scoring systems for laboratory reports has been significantly hampered by three persistent challenges: scarcity of high-quality annotated data, high domain-specific complexity, and insufficient model interpretability. To address these limitations, this study proposes an AdaBoost regression model based on multi-level feature engineering and threshold control, denoted as MFTC-ABR. This method constructs a multi-dimensional feature set using a lightweight neural network, which evaluates laboratory reports across four core dimensions: comprehension of experimental principles, completion of experimental procedures, depth of result analysis, and plagiarism detection. At the scoring algorithm level, a dynamic threshold adjustment mechanism is integrated into the AdaBoostReg ensemble learning framework. By redesigning the sample weight update rule, the prediction errors of samples are divided into three intervals: the acceptable region, the stable learning range, and the focus range. Accordingly, a differentiated weight update strategy is implemented, and a history-aware mechanism is introduced to further regulate the attention allocated to individual samples. Finally, experimental results on the power electronics laboratory report dataset show that MFTC-ABR model achieves a mean absolute error (MAE) of 3.09 and a scoring consistency rate of 82% within a five-point error tolerance. These findings validate the effectiveness and practicability of the proposed method for automatic assessment in specialized domains with limited data availability. Full article

During the installation of prefabricated vertical drains (PVDs) in soft soil foundations, the smear effect induced by mandrel shoe penetration can severely damage the soil structure and reduce permeability, thereby becoming a key factor restricting foundation consolidation efficiency. Previous studies have generally neglected the smear disturbance caused by the geometry of the mandrel shoe. Although existing studies have conducted numerical and theoretical analyses on the smear effect induced by PVD installation, most of them are still based on equivalent circular simplifications and are therefore unable to characterize the anisotropic disturbance induced by a triangular mandrel shoe. To address this limitation, a three-dimensional CEL penetration model considering the real triangular geometry was established, and the traditional cavity expansion theory was directionally modified. The effects of penetration rate, geometric angular structure, and soil type of the triangular mandrel shoe on the smear zone were systematically investigated. The results show that, with increasing penetration rate, the near-field peak stress and far-field displacement increase simultaneously; from slow penetration to fast penetration, the near-field peak stress increases by approximately 42%. By quantitatively defining the critical threshold corresponding to a sharp 50% attenuation in radial displacement as the boundary of the strong smear zone, it was found that increasing the size of the mandrel shoe significantly amplifies the geometric corner effect, and the near-field disturbance range increases by about 21% compared with that of the small-sized case. The larger the size, the more pronounced the anisotropic disturbance characteristics become: the stress concentration effect and displacement splitting in the vertex direction are further enhanced, causing the disturbance range in that direction to far exceed that in the side direction. Soil properties are the key medium parameters controlling the smear zone. Owing to its relatively high stiffness index and skeleton strength, Clayey Silt shows the largest displacement range, whereas Common Clay exhibits the smallest smear zone because of its stronger structural constraint. The modified theoretical model agrees well with the CEL numerical simulation results, verifying its effectiveness under conditions that consider the geometric characteristics of the mandrel shoe. This study provides a theoretical basis and numerical support for the structural design of mandrel shoes in soft-ground PVD construction. Full article

Excavation adjacent to operating urban rail transit faces formidable deformation control challenges. To address this, a parametric collaborative optimization framework integrating micro steel pipe pile isolation and temporary intermediate partition wall reinforcement is proposed. Taking a foundation pit project at Shangdi Station of Beijing Metro Line 13 as a case study, a three-dimensional finite element model was established using the Hardening Soil constitutive model and calibrated with field monitoring data. Optimization analysis reveals that micro-pile spacing is the dominant factor controlling local rail settlement, while intermediate partition wall thickness primarily dictates global surface settlement. By balancing stringent safety limits with construction economy through a multi-objective evaluation, the preferred support configuration was calculated to be 273 mm diameter micro-piles at 500 mm spacing, combined with a 300 mm-thick partition wall. This collaborative configuration successfully truncates lateral soil displacement, reducing maximum rail settlement by over 55% and surface settlement by 53.6% compared to the baseline. Field monitoring results show high consistency with the numerical predictions (RMSE = 0.1438 mm), confirming the reliability of the proposed parametric collaborative optimization framework. Ultimately, this framework provides a validated, quantitative design methodology and a practical reference for support design in constrained excavations adjacent to existing sensitive infrastructure. Full article

The alerting of a microburst at the Hong Kong International Airport (HKIA) is currently detection-based. The technical feasibility of forecasting microbursts in an operational environment was examined in this study through four examples: three cases of a band of intense convection and another case of a severe squall line. A Weather Research and Forecasting (WRF) model with a spatial resolution of 40 m was used in the simulation. Data from several weather radars were integrated into the WRF model using a three-dimensional variational method. A forecast time of 8 h was adopted, and the forecast reflectivity and velocity fields were input into an operationally used microburst detection algorithm to forecast the intensity, sign, and location of the microbursts, which were then compared with the actual observations from a terminal Doppler weather radar at the HKIA. The microbursts were simulated with mixed success. In general, the vertical velocity within the convection band was accurately simulated. However, there may be difficulties in forecasting the magnitude of downbursts, and thus, the intensity of the forecast microbursts in comparison with the actual observations. This study is preliminary, and more cases with available flight data will be studied in the future. Full article

Axial Flux Permanent Magnet Synchronous Motors (AFPMSMs) are gaining increasing attention for their application in electric vehicle (EV) drive systems. Their high torque density and compact axial geometry make them attractive for high-performance EV drive systems. However, cogging torque remains a major challenge, degrading low-speed drivability, noise performance, and control stability. This article proposes a magnet skew on rotor modulation structure using a genetic algorithm (GA) to reduce cogging torque in AFPMSMs utilizing a 12/15 non-integer pole/slot arrangement. The objective of optimization is to simultaneously reduce cogging torque under identical electromagnetic constraints. A complete three-dimensional finite element model (3D-FEM) incorporating nonlinear magnetic material properties has been developed to evaluate the electromagnetic field distribution and torque components. The results indicate that a 12/15 non-integer pole/slot arrangement improves harmonic distribution and extends the operating range with lower cogging torque compared to integer pole/slot designs. Combined with GA-optimized skew angles, this reduces peak-to-peak cogging torque to less than 50%. This design is ideally suited for the traction requirements of electric vehicles, including premium electric vehicles where smooth operation at low speeds is critical. Full article

In water injection development of tight oil reservoirs (TORs), the complex fracture network formed by hydraulic fracturing and water injection induction is the key factor determining the development effectiveness. Accurate inversion of water injection-induced fracture parameters holds significant importance for enhancing reservoir development outcomes. This paper innovatively proposes a parameter inversion framework that integrates the Embedded Discrete Fracture Model (EDFM) with intelligent optimization algorithms. EDFM efficiently characterizes complex unstructured fracture systems while maintaining mass conservation between the matrix and fractures; intelligent optimization algorithms automatically invert parameters such as fracture half-length, orientation, and conductivity. First, a three-dimensional geological model of the TOR is constructed, utilizing EDFM to handle the impact of fractures on the seepage field. Based on considerations of fracture geometry, conductivity, and stress sensitivity, a coupled fluid dynamics model for fractures and matrix is developed. Subsequently, an objective function is built based on water injection production dynamic data, and the Projection-Iterative-Methods-based Optimizer (PIMO) algorithm is employed to achieve efficient inversion of fracture parameters. Taking a TOR in the Ordos Basin as an example for verification, through synthetic model validation, this method significantly improves the accuracy and efficiency of history matching, with inversion results reliably guiding numerical simulation predictions. The results demonstrate that this method can effectively enhance the precision of fracture parameter identification, offering clear advantages in inversion speed and accuracy over traditional trial-and-error approaches. This study provides new insights for modeling induced fractures in TORs and optimizing water injection development strategies. Full article

Lateral wear inevitably develops on the wheel treads of high-speed trains after a period of operation. Extensive research has been dedicated to circumferential wear (e.g., wheel polygonization), whereas studies on lateral tread wear and its impact on wheel-rail noise remain limited. This study investigates this issue through a combined approach of field measurements and numerical simulation. First, lateral wear profiles are measured on in-service high-speed train wheels, and their patterns are systematically analyzed. Subsequently, a three-dimensional transient wheel-rail rolling contact model is developed using the explicit finite element method. This model is employed to analyze the effects of the lateral hollow wear depth on the contact patch position and wheel-rail forces at 400 km/h. Finally, these calculated forces are imported into a coupled wheel-rail vibration and acoustic radiation model to predict noise characteristics at different wear depths. This study clarifies the coupling of lateral tread hollow wear with wheel-rail contact characteristics at 400 km/h and quantifies its mechanical influence on high-frequency wheel-rail noise via contact patch evolution and structural receptance variation. The results demonstrate that lateral wear manifests as hollow wear, with a maximum depth of approximately 1 mm within a reprofiling cycle. It has been found that as the hollow wear depth increases, the contact patch center shifts toward the wheel flange, and its major axis elongates. Consequently, wheel-rail noise increases significantly with greater wear depth. Specifically, a wear depth increase of 0.78 mm leads to increments of 2.3 dB in wheel noise, 0.9 dB in rail noise, and 1.0 dB in total wheel-rail noise. These findings underscore that tread hollow wear is a significant contributor to high-speed wheel-rail noise, highlighting the need for its consideration in maintenance and noise control strategies. Full article

For a protein to perform its biological functions, it must adopt a specific three-dimensional conformation. In addition, many proteins require the assistance of other protein complexes known as chaperonins to fold —i.e., to acquire such a specific conformation—, although the exact mechanisms whereby the chaperonins act and assist the folding process have not been completely determined. In this work, we characterize the physical environment at the interior of the chaperonin HSP60/HSP10 via Molecular Dynamics Simulations. We found that, inside the cavity of the chaperonin (within a region covering much of the cavity’s volume), the long-range electrostatic potential presents a structured pattern that, except for small fluctuations, does not change in time. The electrostatic potential generates an electric field that can be modeled, as a first approximation, as constant and unidirectional $(\mathit{E}/\left(\mathrm{V}·{\AA }^{-1}\right)\approx -0.0054\widehat{𝚤}+0.010\widehat{\mathit{𝚥}}-0.162\widehat{k}$, here the chaperonin’s main axis is aligned along $\widehat{k})$, which can produce large deformations in the structure of a heated protein (Rhodanese); the long-range approximated $\mathit{E}\left(\mathit{r}\right)$ can in fact unfold the Rhodanese, when applied as an external field. Finally, we discuss the possible implications of such an electric field for the protein folding problem, within the context of proteins whose folding is assisted by chaperones. The existence and effects of the electric field are consistent with several theories and experimental observations related to the protein folding problem, in particular with the foldon view. Full article

To explore the influence mechanism of welding process parameters on the residual stress and temperature field of complex welded components, this paper takes H-shaped steel, which is widely used in engineering, as the research object. Based on the thermal-force coupling finite element method, a three-dimensional numerical model of its welding process is established using the ANSYS Workbench platform. Based on the heat conduction equation and structural constraint theory, in accordance with the classification criteria for thin plates and medium-thick plates in the standards of the International Institute of Welding, and in combination with the typical structural size characteristics, six sets of comparative working conditions were designed. The influence of two key parameters, namely, the welding heat source parameters and welding speed, on the welding residual stress and temperature field was analyzed in detail. The research results show that increasing the welding heat input will raise peak welding temperature and expand the range of the high-temperature zone, resulting in a significant increase in residual tensile stress in the weld zone after cooling. Increasing the welding speed can effectively reduce heat accumulation and decrease the temperature gradient, thereby lowering the peak residual stress by approximately 10% to 15%. Research reveals that, under the premise of ensuring thorough penetration, adopting a process combination of “lower heat input and higher welding speed” can effectively suppress the generation of welding residual stress in H-beams. The research results can provide a theoretical basis for the optimization of welding processes in actual production. Full article

Ocean temperature and salinity structures are crucial in understanding ocean circulation and heat–salt transport processes. However, the high cost and limited spatiotemporal coverage of in situ observations make it difficult to reconstruct high-resolution three-dimensional temperature–salinity (T-S) fields. To address these limitations and the strong spatiotemporal heterogeneity of T-S structures in the South China Sea (SCS), the Smart Synthetic Ocean Profile (SSOP) model is proposed, which is a two-stage machine learning-based inversion framework for reconstructing subsurface T-S profiles from satellite surface data. The framework integrates localized training, adaptive model selection, and an error correction strategy. Using climate-state grids with a consistent spatiotemporal resolution as a baseline, multiple candidate regression models are independently trained for each grid point–depth layer–month combination, and the optimal model is selected through performance validation to generate initial T-S profiles. An error correction module is then introduced to refine temperature profile deviations, improving profile consistency and overall accuracy. Experiments using three independent observational periods from the SCS show that SSOP reliably reconstructs vertical T-S structures, particularly in the upper ocean and thermocline. Comparisons with in situ observations indicate that SSOP achieves improved accuracy relative to the Modular Ocean Data Assimilation System and climatology. Full article