Search Results (2,318)

A three-dimensional thermo-elasto-hydrodynamic (TEHD) lubrication model is presented for the high-pressure deep-grooved mechanical seal employed. The thermo-elasto deformation behaviors of the seal rings are investigated using the finite element method (FEM). The parametric studies are conducted to explore the deformation characteristics of the seal face and sealing performance under different operating conditions. The results reveal that the deep-grooved face seal induces circumferential waviness deformation of the seal face, generating the hydrodynamic wedge effect dominated by the axial mechanical deformation along the circumferential direction. However, a significant hydrostatic effect produced by the deformation of the seal face along the radial direction is dominant in the load-carrying capacity of the fluid film. The thermo-mechanical coupling deformation of the seal face decreases with increasing fluid pressure and increases as the spring force and rotational speed increase. The leakage rate increases with higher fluid pressure, while it decreases with increased spring force and rotational speed. The axial stiffness of the fluid film increases with greater spring force and rotational speed but decreases with increasing fluid pressure. These findings can serve as theoretical guidance for developing high-pressure deep-grooved mechanical seals with enhanced reliability and stability. Full article

With the widespread application of unmanned aerial vehicles (UAVs) across various domains, the reliability and lifespan prediction of their core power units—the engines—has become a critical research focus. This study addresses the degradation characteristics of UAV engines under complex operating conditions, including high temperature, high pressure, high rotational speed, and severe vibration, and proposes a remaining useful life (RUL) prediction model based on multi-sensor data fusion. First, a multi-sensor data acquisition platform for UAV engines was established, enabling synchronized collection of multi-dimensional parameters across the entire life cycle, including thrust, torque, temperature, vibration, current, and voltage. Subsequently, a multi-sensor fusion-based RUL prediction model for UAV engines was developed, employing an attention-guided multi-scale residual convolution module to extract local multi-scale degradation features, and integrating a residual-attention Transformer to enhance the modeling of long-sequence dependencies. Experimental results demonstrate that the proposed method outperforms conventional CNN, RNN, and fusion models in terms of RMSE, R², and Score metrics, significantly improving the accuracy and training stability of UAV engine lifespan prediction. This study provides both data support and methodological innovation for predictive maintenance of UAV engines, contributing to enhanced flight safety and mission assurance. Full article

Finite element model updating (FEMU) provides a physics-based approach for reducing discrepancies between numerical models and measured responses by estimating uncertain physical parameters. Its application to rotating machinery is challenging because rotor dynamics are strongly affected by rotational speed, bearing and support properties, nonlinear interactions, operating conditions, measurement limitations, and parameter correlation. This review examines FEMU methods and applications for rotating machinery, distinguishing direct FEMU studies from nonlinear, uncertainty, surrogate, and AI-based studies that primarily provide enabling techniques. Direct matrix correction, sensitivity-based, optimization-based, surrogate-assisted, Bayesian, AI-driven, and hybrid approaches are compared in terms of physical interpretability, identifiability, computational demand, uncertainty treatment, and validation. The reviewed literature indicates that FEMU is most mature for rotor–bearing calibration, bearing and support parameter identification, and operational-response-based updating, whereas experimentally validated inverse estimation of nonlinear and compound-fault parameters remains limited. Based on these findings, a lifecycle-oriented FEMU framework and research roadmap are proposed, emphasizing multi-condition identifiability, uncertainty-aware updating, computational efficiency, independent validation, and governed synchronization. Surrogate and AI-assisted estimation should remain connected to validated high-fidelity physical models and defined operating domains for credible condition assessment and digital-twin applications. Full article

Under-race lubrication is an effective oil supply method for high-speed angular contact ball bearings, but the relationship between internal oil–air two-phase flow distribution and end oil return behavior remains insufficiently understood. In this study, a Volume of Fluid (VOF)-based oil–air two-phase flow model was developed for an under-race lubricated angular contact ball bearing and validated experimentally. The effects of oil flow rate, rotational speed, inlet-hole axial position, diameter, and number were investigated. The maximum relative error between the numerical and experimental oil return ratios was 3.17%. At 3000 rpm, increasing the oil flow rate from 65 to 140 L/h increased the average oil volume fraction on the rolling element surfaces from approximately 0.037 to 0.089. In contrast, increasing rotational speed reduced oil retention on bearing component surfaces and the oil return ratio at the large-clearance end. At 140 L/h, the oil return ratio decreased from approximately 97% at 3000 rpm to 86.5% at 6000 rpm. Shifting the inlet holes toward the small-clearance end enhanced cage wetting but reduced oil retention on the rolling elements and large-clearance-end oil return. Within the investigated range, a mid-plane inlet position, smaller inlet-hole diameter, and larger number of inlet holes were more favorable for oil delivery to the rolling elements while maintaining a relatively high oil return ratio. Full article

The initiation of detonation is a critical yet challenging task for pulse and rotating detonation engines. Conventional approaches often rely on nanosecond repetitively pulsed discharges to generate nonequilibrium plasma for ignition assistance, but the complexity and high cost of the required power supplies limit practical applications. In this work, we experimentally investigate a simplified method using ordinary electrode breakdown discharge to produce an arc plasma that promotes jet-induced detonation initiation. Two ignition strategies are compared under the same total energy: dual-spark-plug ignition (energy concentrated at the jet tube head) and single-spark-plug coupled with electrode discharge (energy split between the jet tube head and an electrode pair placed near the detonation chamber inlet). High-speed schlieren measurements are performed to capture the dynamic flame evolution and shock wave structures. The results show that the electrode-discharge approach dramatically increases the detonation success rate from 13.33% to 66.67% over 30 repeated runs. The electrode discharge is found to occur after the emerging flame has already covered the electrodes. Therefore, the promoting mechanism is attributed not to the high temperature or free radicals generated in the already-burned products, but rather to the discharge-induced shock wave. This shock wave interacts with the corner expansion waves generated by the sudden area expansion, thereby delaying the unsteady decay of the leading shock and promoting re-initiation. This study provides the first experimental evidence that ordinary electrode breakdown discharge promotes jet-induced detonation via a shock-wave reinforcement mechanism. The findings enable a low-cost, compact plasma-assisted initiation strategy for practical detonation engines. Full article

To address the inefficiencies of two-stage sweet potato harvesting in southern China, an integrated machine for synchronous haulm shredding and tuber excavation was developed. The equipment features a front-mounted, reverse-rotating crushing knife roller and a rear-mounted, adjustable grate-type digging shovel. The performance of the prototype was systematically evaluated through two-stage field trials in clay loam soil. First, an orthogonal test was employed to assess the haulm shredding quality. The results indicated that the knife roller speed significantly increased the qualified rate of crushed stems and leaves, whereas the forward speed exerted a negative effect. Additionally, the blade-to-ridge clearance primarily dictated the ridge-top stubble length. Second, a quadratic orthogonal rotational composite design was utilized to optimize the integrated harvesting parameters. The analysis demonstrated that shovel inclination significantly enhanced the tuber exposure rate, while both clearance and inclination exhibited quadratic nonlinear effects on the tuber damage rate. Multi-objective optimization established the optimal operational parameters as a blade-to-ridge clearance of 66.6 mm and a shovel inclination of 34.0°. Field validations under these settings achieved a tuber exposure rate of 83.7% and a damage rate of 4.3%, confirming the high reliability of the predictive models. The integrated equipment effectively shortens the harvesting cycle and demonstrates robust adaptability to clayey moist soils, thereby advancing the mechanization of sweet potato production. Full article

Amid the ongoing decarbonization of the international shipping industry, methanol has emerged as a promising alternative fuel for marine auxiliary boilers owing to its environmental advantages and engineering feasibility. However, its low viscosity and surface tension make the atomization process highly sensitive to operating conditions, posing challenges to stable and efficient burner operation. Existing studies have predominantly focused on engine applications, whereas systematic investigations into the atomization characteristics and operating-parameter matching of primary-air swirl-cup nozzles for marine auxiliary boilers remain limited. To address this gap, the present study combines experimental measurements and numerical simulations to investigate the effects of fuel flow rate, atomizing-cup rotational speed, and primary-air damper opening on spray characteristics. Spray imaging was employed to characterize the spray cone angle and macroscopic morphology, while PIV and PDA were used to measure the outer-flow-field velocity and droplet-size characteristics, respectively. Numerical simulations of liquid-film formation and breakup were performed using a coupled VOF-DPM framework. The predicted spray angle and outer-flow-field velocity showed good agreement with the experimental measurements, with overall deviations within 3–12%. Increasing the atomizing-cup speed generally promoted droplet refinement, while adjustment of the primary-air supply further influenced the droplet-size distribution. Under high-speed operating conditions, the atomized droplet size was generally maintained below 100 μm, and the SMD in the investigated near-field region was approximately 60–80 μm. Based on the multi-load experimental results, primary-air parameter-matching relationships were established for fuel flow rates ranging from 100 to 500 kg/h, providing guidance for maintaining stable atomization performance over a wide operating-load range. This study provides a quantitative basis for the operating-parameter design and stable operation of primary-air swirl-cup nozzles in marine methanol-fired auxiliary boilers and offers useful guidance for their engineering application. Full article

Continuous-flow technology offers advantages in fine chemical and pharmaceutical processes; however, high-solid-holdup (solid mass fraction) liquid–solid systems are prone to clogging and mass transfer deterioration. Although multiphase flow reactors are widely applied, their performance remains insufficiently characterized. In this study, computational fluid dynamics (CFD) coupled with the Mixture model and kinetic theory of granular flow (KTGF) is combined with residence time distribution (RTD) experiments to establish and validate a numerical model. The effects of feed flow rate, rotational speed, and solid holdup on mixing and solid-phase RTD are systematically investigated. Simulation results reveal that the reactor exhibits satisfactory radial and axial mixing performance, alongside non-ideal flow characteristics including recirculation, wall enrichment, and weak back-mixing. Increasing feed flow rate enhances axial mixing and suppresses back-mixing. In the solid holdup range of 10–30%, rotational speed significantly influences axial mixing uniformity ζ and dimensionless variance σ_θ²; in the 30–50% range, ζ continuously increases while σ_θ² first decreases and then increases. Based on CFD data within this range, an empirical correlation for the Péclet number Pe was established (with good fitting for Pe < 35); it serves only as an interpolation tool and does not possess predictive or general design capability. These findings provide a reference for applying multiphase flow reactors in high-solid-holdup liquid–solid mixing systems. Full article

Seismic pier-top pounding in high-speed railway bridges transfers short-duration girder-restraint contact forces into bridge piers, coupling local contact damage with global vibration and possible base yielding. This critical review evaluates how evidence and modelling strategies can be transferred from local contact mechanics to pier response and, ultimately, to whole-bridge seismic demand. The literature is synthesized across experimental and refined numerical characterization, reduced-order contact–structure modelling, response-equivalent-pulse construction, and nonlinear whole-bridge analysis. A qualitative evidence-confidence grading is introduced to distinguish the strength and transferability of the available evidence based on study independence, evidence type, and configuration similarity. The primary scope is high-speed railway bridges, while the underlying contact–structure modelling principles are transferable to conventional railway and highway bridges with comparable pier-top restraints, subject to bridge-specific calibration. Conventional spring-dashpot models are computationally efficient but sensitive to contact stiffness, damping, restitution, and damage assumptions, whereas refined finite-element models resolve local response at substantially greater computational cost. Static, impulse-equivalent, and prescribed pulse representations can reduce analysis effort, but agreement in force or impulse alone does not ensure equivalence in pier displacement, base moment, plastic rotation, or residual demand. Demand-oriented pulses can reproduce selected component-level responses within a calibrated applicability domain, while response-triggered loading remains a conditional system-level reduction requiring reliable event logic, state updating, and independent benchmark validation. Future research should prioritize realistic restraint tests, identifiable parameter ranges, multi-demand validation, uncertainty quantification and damage-updatable repeated-impact models. These advances can provide a mechanics-based basis for performance-oriented restraint assessment, while practical design application requires consistency with code-based seismic restraint provisions and post-earthquake track-system serviceability criteria. Full article

The increasing performance requirements of electric vehicle powertrains demand lightweight, efficient, and low-noise transmission systems. High-speed electric drive unit concepts offer significant potential for reducing motor size and mass by shifting torque generation to higher rotational speeds. However, this approach places increased demands on gearbox power density, efficiency, and noise, vibration, and harshness (NVH) performance. This work investigates the NVH behaviour of a compact, high-speed automotive gearbox with a focus on planetary gear stages. Although planetary stages offer high compactness, their complex kinematics can lead to pronounced NVH challenges. In particular, sequentially phased gear meshing results in characteristic sideband components whose orders can be predicted analytically, while their amplitudes remain difficult to estimate reliably during the design phase, necessitating experimental validation. Several NVH-oriented design measures, including high-contact-ratio gearing and low-NVH microgeometry, are applied to a two-stage gearbox comprising a planetary and a cylindrical gear stage. Peak-to-peak transmission error is used as a primary NVH design metric. The planetary stage is analysed in detail to assess the influence of sequential phasing on sideband components in the dynamic response and resulting vibration behaviour. The NVH-oriented gearbox is tested on a bench, with housing accelerations used to analyse planetary sidebands, providing insights into the NVH potential of compact, high-speed gearboxes and the role of sequential phasing in the vibration response. Full article

Friction stir welding (FSW) is a solid-state joining process widely used for aluminum alloys due to its low heat input, reduced distortion, and ability to produce high-quality joints. However, excessive tool forces generated during the welding process can increase machine loading, accelerate tool wear, and negatively affect the process efficiency. Therefore, understanding the relationship between welding parameters, tool forces, and the joint performance is essential for achieving high-quality welds while avoiding unnecessary mechanical loads. In this study, 4 mm thick AA5754 aluminum alloy plates were joined using the FSW process, and the feasibility of using tool force measurements for process optimization was investigated. A comprehensive experimental matrix consisting of nine different rotational speeds and ten different tool travel speeds was established based on preliminary studies and previous literature. During each welding operation, forces acting on the tool in the F_x, F_y, and F_z directions were continuously recorded. The welded joints were evaluated through tensile testing (Zwick Z300 universal testing machine, ZwickRoell, Ulm, Germany), hardness measurements, and microstructural characterization using scanning electron microscopy (SEM) (ZEISS Merlin scanning electron microscope, Carl Zeiss Microscopy GmbH, Oberkochen, Jena, and Göttingen, Germany). A Pearson correlation analysis and a two-way analysis of variance (ANOVA) were performed at a 95% confidence level to quantify the relationships and statistical significance of the process parameters. The results showed that F_z was the dominant force component during welding. The rotational speed had a statistically significant effect on the tensile strength, yield strength and hardness (p < 0.05), accounting for 99.39% of the total variation in hardness. For the mean tool force, both the rotational speed and the tool travel speed were statistically significant (p < 0.0001), contributing 38.48% and 47.16% of the total variation, respectively. The rotational speed also accounted for 81.55% of the variation in the maximum axial force. The Pearson correlation analysis showed a strong negative correlation between the rotational speed and hardness (r = −0.73), whereas the tool travel speed showed positive correlations with F_x (r = 0.61), F_z (r = 0.62), and the mean tool force (r = 0.68). Despite the increased tool loading associated with higher travel speeds, no corresponding improvement in the mechanical performance was observed. The results demonstrated that appropriately selected welding conditions produced joints with a yield strength and hardness exceeding 90% of the corresponding base material properties while maintaining relatively lower tool forces. SEM observations confirmed grain refinement in the stir zone. Overall, the combined correlation and ANOVA results demonstrate that real-time tool force monitoring can provide a quantitative basis for selecting FSW parameters that achieve an adequate mechanical performance while minimizing unnecessary machine and tool loading. Full article

Advanced manufacturing and cutting machinery often operate under variable material properties and uncertain load conditions, making real-time process optimization difficult when high-fidelity simulations and physical experiments are costly. To address this problem, this study proposes a physics-guided surrogate-assisted reinforcement learning framework for multi-objective speed regulation of coal–rock cutting machinery. The haulage speed and drum rotational speed are jointly optimized to balance production rate, cutting specific energy consumption, current load, vibration impact, and speed-regulation stability. First, an EDEM–RecurDyn–Simulink co-simulation model was established to obtain cutting current and vibration response data under different coal–rock structures and speed combinations. Similar-material cutting experiments were conducted to validate the vibration response, with root mean square (RMS) relative errors of 3.38%, 4.21%, 5.75%, and 5.03% under full-coal, single-gangue-layer, double-gangue-layer, and full-rock conditions, respectively. Based on these data, an improved physics-informed neural network (PINN) surrogate model was developed by embedding an equivalent coal–rock difficulty factor, a speed-matching factor, a semi-empirical current prior, and a vibration residual calibration mechanism. The surrogate model achieved R² values of 0.9623 and 0.9147 for cutting current and vibration kurtosis, respectively. It was then integrated into a Soft Actor–Critic (SAC) control environment to learn continuous dual-variable speed-regulation policies. Across five independent SAC training seeds, the improved SAC achieved an average theoretical productivity of 207.8033 ± 6.5641 t·h⁻¹ and a cutting specific energy consumption of 0.3387 ± 0.0114 kW·h·t⁻¹. Compared with the fixed-speed, empirical speed-regulation, and conventional SAC strategies, the proposed method increased the average theoretical productivity by 2.65%, 5.01%, and 1.77%, respectively, while reducing the corresponding specific cutting energy consumption by 1.37%, 4.05%, and 2.22%. These results demonstrate that the proposed framework provides an efficient intelligent optimization method for condition-aware speed regulation in complex industrial cutting processes. Full article

The electrostatic rotary bell (ESRB) sprayer is widely used in the coating industry due to its ability to achieve uniform film thickness and reasonable paint transfer efficiency. However the efficiency of paint transfer and spraying coverage in ESRB systems remain highly sensitive to process parameters. Therefore, optimizing these parameters is essential to reducing paint consumption, energy use, and environmental impact. In this study, a simulation model of the ESRB spraying process was established using ANSYS/Fluent. The spraying flow field, paint deposition profile, and film thickness distribution were validated through the experiment. Based on a single-factor test and the Box–Behnken response surface method, a multi-parameter optimization framework was designed to investigate the effects of six spraying process parameters, including inner and outer shaping air flow rate, bell rotational speed, applied voltage, target distance, and paint flow rate, on coating pattern width and paint transfer efficiency. Based on the Z-score standardization, a mathematical model of the comprehensive score with six factors was established to evaluate spraying efficiency and paint transfer efficiency and predict optimal spraying process parameters. The results indicate that voltage and spray distance are significant factors affecting the comprehensive score, with the order of influence being voltage > spray distance. The optimal parameters were as follows: bell rotational speed X1, 40 kr/min; inner shaping air flow rate X2, 196 sl/min; outer shaping air flow rate X3, 298 sl/min; paint flow rate X4, 249 cc/min; applied voltage X5, 52 kV; and target distance X6, 154 mm. Validation tests showed deviation between the predicted comprehensive score and the actual value from simulation and experiment were 2.03% and 1.36%, respectively. These results demonstrate that the proposed optimization model has high reliability and can be used to optimize spraying process parameters. Full article

To address the issues of subcarrier orthogonality loss and inter-carrier interference (ICI) caused by carrier frequency offset (CFO), this paper proposes and experimentally validates a frequency offset estimation (FOE)-assisted dual-domain Transformer equalizer within an advanced, high-capacity optical-heterodyne radio-over-fiber (RoF)–wireless orthogonal frequency division multiplexing (OFDM) transmission system. To rigorously test the algorithm’s robustness under extreme physical conditions, the experimental platform integrates offline 16-GBaud signal generation, optical I/Q modulation, dual-optical-tone transport over a single-mode-fiber RoF feeder, remote photonic heterodyne frequency conversion based on a uni-traveling-carrier photodiode (UTC-PD), 4.6 km free-space wireless transmission, and 160-GSa/s ultra-high-speed real-time sampling. In this system, the receiver front-end employs an FOE module to pre-compensate for the dominant global CFO-induced phase rotation; subsequently, a low-complexity, compact local-window Transformer is utilized to perform adaptive residual compensation for local data-dependent impairments—such as residual waveform distortion and residual ICI—in both the time and frequency domains (before and after the Fast Fourier Transform, or FFT). This synergistic architecture, combining a physical model-driven approach with a self-attention mechanism, effectively mitigates the adverse impact of global frequency offset on neural network convergence. Experimental results demonstrate that, under conditions of strictly aligned multiply accumulate (MAC) operation complexity, the dual-domain architecture achieves significantly superior performance—in terms of bit error rate (BER), error vector magnitude (EVM), and constellation quality—compared to traditional linear DSP methods and baseline networks such as DNNs, CNNs, and LSTMs. Operating in 16 GBaud QPSK mode with an input optical power of 0 dBm, the system achieves a BER of $1.89\times {10}^{-4}$, representing performance improvements of approximately 5.98-fold and 1.92-fold over the standalone Transformer and FOE-assisted DNN schemes, respectively. Full article

The start-up process of a siphon vertical axial-flow pump is accompanied by rapid internal-flow reconstruction, transient hydraulic loading and unsteady rotor response, which directly affect the operational stability of the pump system. In this study, the unsteady internal flow evolution and rotordynamic characteristics of a siphon vertical axial-flow pump during start-up were investigated using a transient numerical method with dynamic rotational-speed updating. The instantaneous impeller speed was solved based on a torque-balance equation considering motor driving torque, hydraulic resistance torque and rotor inertia, and the angular-velocity boundary condition of the rotating domain was updated at each time step through a custom UDF routine. The numerical model was validated against model-test data, and good agreement was obtained for both pump head and efficiency. Based on the validated model, the flow-angle distribution, vortex stretching term, blade-surface pressure, rotor mechanical response, radial-force time–frequency characteristics and blade-loading variation were analyzed. The results show that the internal flow in the main pump section evolves from a strongly unsteady swirling state to an axially dominated quasi-steady state. In the early stage, obvious pre-swirl, local backflow and strong vortex stretching occur near the impeller inlet, blade-tip clearance and impeller–guide-vane interaction region. With increasing rotational speed and flow rate, the disordered vortical structures are gradually suppressed, and the internal flow becomes more organized. The rotor response exhibits clear stage-dependent characteristics, and the radial force is more sensitive to local flow instability than the axial force and torque. Continuous wavelet transform and variational mode decomposition further indicate that the radial-force signal is dominated by low-frequency transient excitation in the early stage, while medium- and high-frequency modulation components appear in the later stage. This study reveals the coupling mechanism between transient internal-flow evolution and rotor dynamic response during pump start-up, providing guidance for improving the start-up stability of siphon vertical axial-flow pump systems. Full article