Search Results (83)

In directional coring drilling, toolface adjustment is performed during drilling interruption by rotating the drill string through the top drive. Because the bottom-hole toolface angle cannot be transmitted to the surface in real time, a dynamic prediction model is required to guide toolface control. Existing flexible drill string models, however, generally neglect the nonlinear wellbore friction caused by stick–slip motion, reducing prediction accuracy. To address this issue, a distributed-parameter torsional dynamic model is established and discretized into a multi-degree-of-freedom system. A friction-state-based prediction–correction iterative algorithm is proposed to resolve the strong coupling between wellbore friction and system dynamics. At each time step, the sticking or slipping state is identified from the predicted motion, and the wellbore friction torque is iteratively updated until the friction state and dynamic equilibrium simultaneously converge, enabling accurate prediction of the drill bit toolface angle. Simulation results show that the proposed model captures the key dynamic characteristics of toolface adjustment. Under typical operating conditions, the drill bit start-up delay is 3.53 s, the peak angular velocity reaches 1.73°/s, and the peak transmitted torque is 2.28 kN·m. After the top drive stops, the drill bit continues rotating because of inertia, resulting in a 2.12° toolface overshoot and an angular lag rate of 21.2%. In addition, the effects of weight on bit, top-drive speed, and equivalent damping on toolface adjustment are quantified, providing guidance for parameter optimization. The proposed method provides a theoretical basis for toolface prediction and control in intelligent directional coring drilling. Full article

The performance of grain storage silos is strongly influenced by discharge flow patterns, hopper geometry, and material properties such as moisture content and impurity levels. However, the combined effects of these factors on flow behavior, discharge rate, and segregation are not yet fully understood. This study experimentally investigated the integrated effects of moisture content, prismatic hopper geometry (hopper angle β), and impurity addition on flow behavior, segregation, and mass flow rate in reduced-scale silos. Experiments were conducted using three prismatic silos with hopper angles of β = 15°, 33°, and 45°, filled with maize at moisture contents of 13.6%, 20.2%, and 26.0% (wet basis), under both clean conditions and with the addition of 10% impurities (fraction passing through a 5 mm sieve). The discharge rate was determined by direct mass–time measurements, flow patterns were inferred from video analysis, and segregation was quantified based on the mass fraction of impurities in samples collected during discharge. The results indicate that moisture content was the most influential factor, reducing the discharge rate by up to 22.8% when increasing from 20.2% to 26.0% w.b. (p < 0.05). Hopper geometry also had a significant effect, with performance differences among configurations becoming more pronounced under high-moisture conditions. The addition of 10% impurities increased the discharge rate under all tested conditions, with gains of up to 29.0% at 26.0% w.b. and β = 15°. Segregation intensified with increasing moisture content, leading to a progressive accumulation of impurities toward the end of discharge. The stick–slip phenomenon was observed under a critical condition (26.0% w.b., β = 15°, with impurities), resulting in a 23.0% reduction in the average discharge rate compared to the equivalent stable condition. These findings demonstrate that granular flow behavior in silos is governed by the interaction between moisture, hopper geometry, and material composition. The results also suggest that operational strategies such as pre-cleaning should be evaluated in conjunction with expected moisture conditions, as pre-cleaning may adversely affect flow performance under high-moisture scenarios. Full article

Stick–slip vibration, reversal, axial impact, and dynamic instability are major challenges in deep drilling operations and are closely associated with nonlinear bit–rock interaction. To investigate these phenomena, this study develops a nonlinear axial–torsional coupled dynamic model of a drill-string system by integrating rock surface morphology evolution with a Stribeck dry friction model. The drill string is discretized into a distributed lumped-parameter model with coupled axial and torsional degrees of freedom. A surface morphology matrix is introduced to simulate the rock-cutting process, while the Stribeck friction model is employed to characterise the nonlinear frictional behaviour at the bit–rock interface. Time-domain simulations, bifurcation analysis, and frequency spectrum analysis are performed to investigate the dynamic responses of the system. The results indicate that rock surface morphology evolution significantly influences the contact conditions and frictional behaviour at the bit–rock interface, and together with dry friction induces transitions among steady-state, multi-periodic, and chaotic motions. Stick–slip vibration is accompanied by axial impact, bit bounce, and a reduction in the dominant torsional vibration frequency. In addition, variations in both driving and frictional parameters can trigger dynamic instability and state transitions. The proposed model provides an effective framework for analysing nonlinear drilling dynamics and offers theoretical guidance for drill-string vibration suppression, drilling parameter optimisation, and efficient drilling in complex formations. Full article

Interfacial yarn pull-out plays a critical role in load transfer and energy dissipation in soft ballistic materials; however, its multistage and friction-dominated nature makes comprehensive experimental characterization time-consuming and experimentally demanding. In this study, a stage-wise physics-guided machine learning (PG-HML) framework is proposed to predict the pull-out behavior of nano hexagonal boron carbide (nh-B₄C)-functionalized para-aramid fabrics using an experimentally constrained dataset. The pull-out response was decomposed into three physically meaningful deformation stages, namely crimp extension, initial interlacement rupture, and stick–slip sliding. Physics-based continuity and admissibility constraints were incorporated into the learning framework to preserve mechanical consistency across stage transitions and improve prediction robustness under limited data conditions. Comparative analyses demonstrated that the proposed PG-HML framework achieved superior predictive capability, particularly in capturing rupture transitions and post-peak stick–slip evolution, with R² values exceeding 0.98 during the crimp extension and rupture stages. Increasing nh-B₄C content enhanced interfacial friction, rupture resistance, and pull-out energy dissipation, while displacement responses gradually approached saturation under force-dominated extraction conditions. Therefore, interfacial pull-out behavior in nh-B₄C/aramid materials can be predicted with high fidelity using limited experimental input, providing a surrogate modeling strategy that enables virtual material screening and significantly reduces the experimental effort required for preliminary design and optimization of advanced soft ballistic materials. Full article

Train brake systems are characterized by strong friction and open-system features during the service process. Low environmental temperatures significantly affect the contact interface and the attrition characteristics of the braking frictional couple, thus intensifying friction-induced vibration and threatening operational safety. To elucidate the impact of environmental temperature on the frictional vibration characteristics of train brake systems, braking deceleration tests under different environmental temperatures were first conducted to obtain the evolution of vibration, noise, and friction coefficient with environmental temperature and brake disc rotational speed. Then, the Stribeck friction parameters under different environmental temperatures were identified using a genetic algorithm. On this basis, a brake system dynamic model was developed, incorporating disc–pad friction, wheel–rail adhesion, and the relative torsion between the brake disc and the wheelset, enabling accurate examination of the vibrational behaviour arising from friction under different environmental temperatures. And the dynamic relationship among environmental temperature, interface friction parameters, and vibration characteristics of the brake system during braking deceleration was elucidated. The findings indicate that as the environmental temperature decreases, the dynamic friction coefficient increases during the relatively high-speed braking phase, intensifying high-frequency unstable vibrations of the braking assembly. During the relatively low-speed braking phase, the friction coefficient exhibits an obvious negative-slope relationship with vehicle speed that means the friction coefficient increases as the speed decreases, and this negative slope effect is enhanced under low-temperature conditions. Consequently, it triggers intense stick–slip motion at the disc–pad interface and even severe vibrations of various components in the brake system, leading to a sudden increase in vibration intensity in the relatively low-speed range. Full article

Boundary lubrication plays a crucial role in determining the service performance and operational lifespan of mechanical components. However, continuum mechanics models and experimental studies are unable to elucidate the dynamic evolution of intermolecular interactions at the interface under boundary lubrication from a microscopic perspective, including phenomena such as asperity contact and lubricant film rupture. In this study, a molecular dynamics simulation approach was employed to construct a boundary lubrication friction model incorporating lubricant molecules, aiming to investigate the influence of applied load and asperity height on the dynamic evolution of atomic interactions at the interface from the perspective of energy variation, under conditions both with and without asperity contact. The results indicate that van der Waals interactions dominate the frictional response, and severe asperity contact leads to a sharp increase in van der Waals energy, which in turn results in a decrease in normal force, thereby increasing the friction coefficient. When the upper and lower surfaces remain separated by the lubricant, an increase in van der Waals energy leads to higher friction force, consequently elevating the friction coefficient. In the absence of contact, the friction coefficient decreases with increasing load; however, once asperity contact occurs, higher loads accelerate lubricant film failure and intensify direct interfacial contact, leading to more pronounced stick–slip oscillations and increased wear. This study provides atomic-scale insights for the design and performance optimization of boundary lubrication interfaces. Full article

Valve stiction remains a persistent nonlinear phenomenon in industrial control loops, often inducing limit-cycle oscillations that degrade control performance, compromise stability, and reduce process efficiency. Reliable detection of stiction is therefore essential for condition-based maintenance and improved operational performance. This study proposes a Hybrid Wavelet–Convolutional Neural Network (HW-CNN) framework for the detection of valve stiction in closed-loop systems. The approach employs the continuous wavelet transform (CWT) to generate time–frequency scalograms that preserve localized energy distributions associated with stick–slip behavior, including transient release events and sustained oscillatory patterns. These representations are subsequently processed using a fine-tuned deep residual neural network to enable automated feature extraction and classification. Unlike conventional signal-based or generic time–frequency learning approaches, the proposed framework is designed to retain control system-specific dynamics within the feature representation, thereby improving the separability of stiction-induced signatures under varying operating conditions. The methodology is evaluated using both simulated control loop data and real industrial datasets obtained from the International Stiction Database (ISDB), ensuring evaluation under controlled and practical conditions. To enhance reliability, performance metrics are reported as averages over repeated experimental runs. The results demonstrate that the proposed HW-CNN framework achieves an accuracy of 96.1% and an F1-score of 96.0% on simulated datasets, and 90.4% accuracy with an F1-score of 90.0% on industrial data. Additional analysis indicates that the model maintains consistent detection capability despite increased variability in real-world conditions. Furthermore, interpretability is supported through Grad-CAM analysis, which shows that the network focuses on physically meaningful regions within the scalograms corresponding to known stiction dynamics. The findings confirm that the integration of wavelet-based feature encoding with deep residual learning provides a robust and interpretable framework for valve stiction detection. Full article

The braking system is a critical safety mechanism for elevators, making precise performance prediction essential for robust design. However, high-speed elevator braking is a complex nonlinear dynamic process featuring real-time stick-slip transitions at the rope–sheave interface. Conventional models often overlook these transient characteristics or assume constant friction, which compromises predictive accuracy. To address these limitations, this study proposes a 16-scenario adaptive dynamic model for elevator braking. By incorporating the Stribeck friction formulation and explicit numerical criteria, the state-space framework autonomously solves multi-condition, time-varying slip dynamics without manual intervention. The proposed model was experimentally validated using a test elevator with a rated capacity of 1000 kg. Empirical results showed high accuracy in predicting macroscopic braking distances (relative errors under 10%) and transient responses, particularly the temporal evolution of velocity and deceleration. Leveraging this validated model, the influence of key parameters—including car load, time-varying friction, and traction capacity—on dynamic braking behavior was further investigated. Ultimately, this 16-scenario framework provides a robust theoretical foundation for predicting transient braking stability and optimizing elevator mechanical design. Full article

To elucidate the damping mechanism of platform dry friction dampers for turbine blades and optimize their design parameters, this study establishes a two-dimensional global–local unified sliding dry friction damping model. This model comprehensively accounts for the blade’s bending-torsion coupling vibration characteristics and the dual-state behavior of the damper, encompassing both stick and slip phases. An iterative solution strategy combining finite element methods with in-house developed programs is employed to simulate the vibration response of turbine blades equipped with dampers under multiple loading conditions. The influence of normal pressure and dimensionless normal pressure on the blade’s vibration characteristics, equivalent stiffness, and equivalent damping is systematically analyzed. To validate the reliability of the simulation results, a dedicated test platform capable of independently simulating centrifugal force effects was constructed, and modal tests as well as vibration response tests were conducted. The results demonstrate that the proposed model accurately describes the nonlinear energy dissipation behavior of dry friction damping, providing a reliable theoretical basis for blade vibration response analysis. Dimensionless normal pressure is identified as a key parameter influencing vibration reduction effectiveness. The resonant amplitude of the blade exhibits a non-monotonic trend, initially decreasing and then increasing with rising dimensionless normal pressure. The optimal dimensionless normal pressure range is found to be 20–30, within which the blade vibration amplitude can be reduced by more than 50%. Experimental verification confirms that the vibration reduction and energy dissipation mechanism of the damping block aligns closely with simulation results, achieving a maximum vibration reduction of 72.6%. Moreover, the optimal dimensionless normal pressure values correspond well with simulation predictions. Based on the optimal dimensionless normal pressure, a forward design method for platform dampers is proposed, which can provide theoretical support and engineering guidance for the optimal design of vibration reduction structures in aero-engine turbine blades. Full article

In Coiled Tubing (CT) acoustic telemetry, the reliability of surface signal reception is severely challenged by the “contact dead zone” of traditional probes and complex nonstationary environmental noise. To address these issues, this paper proposes a hardware-software integrated solution for high-fidelity signal extraction. In terms of hardware, a novel pickup probe based on the micro-lever principle is developed. By utilizing a pivoted lever structure with an optimized arm ratio of 2.6 to 1 and a full pressure-balanced mechanism, the design physically overcomes the contact dead zone inherent in traditional pressure-compensating probes and effectively isolates low frequency common-mode interference through a lateral floating architecture. In terms of software, a joint denoising model combining Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and wavelet thresholding is proposed. A cross-correlation coefficient criterion is introduced to adaptively screen intrinsic mode functions and eliminate residual fluid turbulence noise. Field experiments on a 1500 ft full-scale circulation loop demonstrate that the proposed probe improves the detection sensitivity of the radial breathing mode by approximately 20.6 dB compared to the baseline, while effectively eliminating stick-slip friction noise during dynamic tripping. Furthermore, the joint algorithm increases the Signal to noise Ratio by an additional 16.9 dB under typical pumping conditions of 0.5 bpm, with a normalized cross-correlation exceeding 0.96. These results verify that the proposed method effectively solves the bottleneck of weak signal detection in deep wells, providing robust technical support for CT telemetry operations. Full article

This work investigated the influence of thickness-direction boundary conditions on the flow characteristics of granular material in a quasi-two-dimensional silo using the discrete element method (DEM). Two types of boundary conditions were considered in the thickness direction: wall conditions and periodic boundary conditions. The simulation results indicate that under wall conditions, velocity waves propagate upward, manifested by the formation of bubble-like sub-flow zones in the velocity field, and the particle motion in the upper bed region exhibits a clear stick–slip feature. In contrast, under periodic boundary conditions, particle motion displays a resonant mode. Further statistical analysis reveals that, despite the distinct macroscopic motion mode under the two boundary conditions, the probability distributions of particle vertical fluctuating velocities share similar characteristics: both exhibit fat-tailed and asymmetric features and deviate from Gaussian distribution. Additionally, under wall conditions, the horizontal distributions of particle vertical velocity conform to the kinematic model throughout the bed, whereas under periodic boundary conditions, the horizontal distributions in the upper bed region display plug flow characteristics. In summary, the results of this work demonstrate that thickness-direction boundary conditions play a crucial role in determining the flow characteristics of granular assembly in silos. Full article

This study investigates the transient wheel–rail contact mechanics of welded joints in heavy-haul rails via a validated 3D finite element model, and analyzes the stick-slip behavior, dynamic response and elastoplastic characteristics in the base material zone, heat-affected zone and weld bead zone. Results show a distinct contact state transition from stick-slip in the base material to predominant slip within the welded zones, indicating higher wear susceptibility. Dynamic response analysis reveals the highest and lowest contact-point acceleration amplitudes in the base material and heat-affected zone, respectively, due to material heterogeneity. Plastic deformation consistently initiates at the rail surface, where stress and strain concentrate, establishing it as the primary site for damage nucleation. A systematic parametric study shows that plastic deformation can be effectively mitigated by increasing the yield strength and elastic modulus of the welded joint material, or reducing the wheelset velocity, unsprung mass and wheel–rail friction coefficient. In contrast, adjusting the primary suspension and fastener parameters exerts a negligible influence on plastic deformation control. These findings provide a mechanistic basis for optimizing the performance and maintenance of welded joints in heavy-haul rail operations. This study reveals the coupling law of multiple mechanisms among contact behavior, dynamic response and material failure during the damage initiation process of rail welded joints from the mechanistic perspective, which provides a theoretical basis for the structural optimization, condition assessment and maintenance of rail welded joints in heavy-haul railways. Full article

Rubber materials undergo continuous wear in high-pressure seal applications. To address the risk of adhesive wear and consequent leakage of rubber seals operating under reciprocating sliding in high-pressure hydrogen storage and refueling systems, this study employed high-pressure hydrogen tribology testing. Ball-on-disk reciprocating tests were conducted using a 316L stainless-steel ball against silica-filled nitrile butadiene rubber (NBR), and the friction response and wear-morphology evolution were compared under ambient air, 1 MPa hydrogen (H₂), 50 MPa H₂, 50 MPa nitrogen (N₂), and grease-coated conditions. Under dry sliding, the coefficient of friction (COF) of NBR in air and hydrogen ranged from 1.34 to 1.44, whereas it decreased markedly to 0.942 in 50 MPa N₂. The wear volume under the four dry conditions was concentrated in the range of ~0.292–0.320 mm³. After grease coating, the steady-state COF in air and at 50 MPa H₂ dropped to 0.099 and 0.105, respectively, and the wear features changed from ridge-like wear patterns/tear pits to regular, smooth indentations with slight running marks. The results demonstrate that a lubricating film can effectively separate direct metal–rubber contact and suppress stick–slip, enabling a low-friction, low-wear, and highly stable interface in high-pressure hydrogen, and providing a practical engineering route for reliable operation of rubber seals in hydrogen service. Full article

This paper investigates a friction oscillator model in both its Integer-Order and Fractional-Order formulations. The lack of classical solutions for the governing differential equations with discontinuous right-hand sides is addressed by adopting a Differential Inclusion framework. Using Filippov regularization, the discontinuity is replaced by a set-valued map satisfying appropriate regularity conditions. Selection theory is then applied to construct a Lipschitz-continuous, single-valued function that approximates the set-valued map. This procedure reformulates the discontinuous initial value problem as a continuous, single-valued one, thereby providing a rigorous justification for the proposed approximation method. Numerical simulations are performed to study stick–slip attractors in both the Integer-Order and Fractional-Order cases. The results demonstrate that, in contrast to the Integer-Order system, periodic attractors cannot occur in the Fractional-Order regime. Full article

Severe drill string vibrations, particularly stick–slip, significantly compromise drilling efficiency and tool longevity in deep hard formations. Compound percussive drilling (CPD) has emerged as a promising technique to mitigate these vibrations and enhance the rate of penetration (ROP). However, the complex coupling mechanisms between impact loads and bit dynamics remain insufficiently understood. This study aims to elucidate the axial–torsional vibration characteristics of the drill bit and the underlying vibration reduction mechanisms under CPD conditions. A multi-degree-of-freedom (MDOF) dynamic model was first established, integrating both the dynamics of the CPD tool and the regenerative cutting effects inherent in bit–rock interactions. The governing equations were then solved numerically using the fourth-order Runge–Kutta method, followed by a systematic parametric sensitivity analysis to quantify the influence of impact parameters on vibration mitigation. The results show that while CPD induces detrimental axial–torsional vibrations in soft rock formations, it effectively suppresses stick–slip and enhances ROP in hard rock formations. Notably, coupled axial–torsional impact loading exhibits superior vibration suppression capabilities compared to singular axial or torsional impacts. A critical proportional relationship for parameter optimization was identified; specifically, maximizing vibration mitigation requires scaling the axial impact load proportionally with the torsional impact load. For example, when the axial impact load amplitudes are 5 kN and 10 kN, the corresponding optimal torsional impact load amplitudes are approximately 500 N·m and 1000 N·m, respectively. Furthermore, maintaining the impact frequency within the range of 10–30 Hz yields optimal vibration reduction effects. The benefits of CPD become increasingly pronounced with higher rock strength and longer drill strings. These findings confirm the suitability of CPD technology for deep hard rock environments and provide theoretical guidelines for the optimal selection of impact parameters in engineering applications. Full article