Search Results (148)

The runner of a pump turbine features a relatively flat structural configuration. The clearance cavities formed between the upper crown, lower band, and surrounding stationary components play a critical role in its dynamic behavior and operational stability. Consequently, a detailed modal analysis of the runner is essential to ensure safe and stable operation. In this study, an acoustic–structure coupling method is adopted to investigate the wet modal characteristics of the pump-turbine runner, explicitly accounting for the added mass effect induced by the fluid in the external flow passages. By systematically varying the geometric parameters of the upper crown clearance cavity, the influence of seal clearance dimensions on the runner’s modal characteristics is examined. The results demonstrate that the radial clearance and the axial height of the seal cavity are the most influential parameters, reducing natural frequencies by up to 15.85% and 16.93%, respectively. The pitch of the seal teeth shows a secondary yet notable effect, inducing a frequency variation of 13.73%. In contrast, local labyrinth seal parameters, such as the number of teeth and tooth width, have a comparatively limited effect. This study provides practical guidance for vibration risk prediction, anti-resonance design, and operational stability assessment of high-head, large-capacity turbine runners by revealing the quantitative relationship between geometric parameters and modal frequencies. Full article

Background/Objectives: Spherical agglomeration is a particle size enlargement technique with promise to improve micromeritic properties of active pharmaceutical ingredients. In a spherical agglomeration process, an immiscible bridging liquid is added to suspended crystals, inducing agglomeration. Interaction between primary particles and bridging liquid is essential for agglomeration to occur, and mixing is critical as it influences flow profiles and particle suspension. Benchtop-scale stirred tanks are commonly used for spherical agglomeration research. However, there is little consistency in the tank and impeller design, resulting in limited understanding of the influence mixing has on agglomerate properties. Methods: To inform spherical agglomeration reactor design, four industrial standard impeller geometries promoting differing levels of radial and axial flow in the tank were tested in a 1 L stirred tank at impeller speeds ranging from 300 rpm to 600 rpm. The impeller clearance-to-vessel diameter ratio was varied between 0.18 and 0.33 to determine the influence that impeller characteristics have on spherical agglomerates. Corresponding CFD simulations were conducted in ANSYS Fluent to understand vessel flow patterns with different impeller geometries, speeds and clearances. Results: Experimental results suggest impellers with increased power number produce more consistent agglomerates. CFD simulations showed a clear influence of impeller clearance on particle suspension and velocity profile in the tank. Conclusions: Whilst experimental studies and CFD studies have been conducted for spherical agglomeration, this work provides a systematic investigation that compares both CFD and experimental analysis for industrial standard impeller geometries to understand the important, yet underexamined link between impeller characteristics and spherical agglomerate shape and size. Full article

This study aims to establish an origin identification method for Scutellariae radix that integrates multidimensional quality indicators and machine learning algorithms, enabling accurate and rapid traceability of Scutellariae radix medicinal materials from four production areas: Hebei (HB), Shanxi (SX), Shaanxi (SAX), and Chengde (CD). The study collected a total of 43 batches of Scutellariae radix samples from the aforementioned origins. It systematically measured 12 key quality indicators covering flavonoids, physicochemical parameters, chromaticity values, and biological activity. These specifically include four flavonoid components: baicalin, wogonoside, baicalein, and wogonin; three physicochemical parameters: moisture content, ash content, and alcohol-soluble extract; four chromaticity values: L*, a*, b*, and ΔE; and in vitro anti-inflammatory activity (IC₅₀ value for NO clearance). On the basis of these parameters, in this study there were five machine learning models constructed based on the following algorithms and methods: Random Forest (RF), Extreme Learning Machine (ELM), Backpropagation Neural Network (BP), and Radial Basis Function Neural Network (RBF). A comparative analysis was conducted to evaluate the origin identification performance of each model. The results indicate significant differences (p < 0.05) in the contents of baicalin, wogonoside, L*, a*, b*, ΔE, and alcohol-soluble extract among Scutellariae radix from different origins. The comparative analysis of four machine learning models reveals that RF outperforms ELM, BP, and RBF in multiclass classification, achieving a test accuracy of 75% and consistent precision, recall, and F1-score of 79.17%. In contrast, the three neural networks attain only 66.67% test accuracy, with RBF showing high precision but low recall, ELM delivering moderate performance, and BP performing poorly. These results underscore the strength of ensemble methods like RF in small-sample settings, where they mitigate overfitting and enhance generalization, whereas neural networks struggle with limited data. We therefore recommend RF for deployment under current data constraints and suggest future work should focus on data expansion, especially for under-performing classes, along with hyperparameter tuning to further improve classification. Full article

Forced vibrations of turbine blades induced by airflow excitation can severely threaten the service life of radial flow turbines in aircraft environmental control systems (ECSs). However, existing studies on airflow excitation in ECS radial flow turbines using novel tubular nozzles are limited. To address this research gap, the ultra-high-frequency airflow excitation characteristics and resonance behavior in an ECS radial flow turbines were studied using numerical simulations and experiments. The effects of radial clearance between the nozzle and the impeller, as well as the nozzle layout, on airflow excitation were investigated. The results indicate that, with the current tubular nozzle design, no shock waves were generated at the nozzle outlet. The rotor–stator interaction was the primary source of excitation in ECS radial flow turbines employing tubular nozzles, inducing significant first-order airflow excitation and leading to turbine fatigue failure. Increasing the radial clearance between the impeller and the nozzle can effectively reduce airflow excitation; however, this effect was nonlinear. With increasing radial clearance, the reduction in airflow excitation became less effective. Meanwhile, the airflow excitation was significantly influenced by the nozzle layout. The single-row nozzle layout exhibited pronounced first-order airflow excitation characteristics and the high-amplitude regions were distributed throughout the entire impeller flow passage. For the double-row staggered nozzle layout, the first-order airflow excitation was greatly diminished, reaching only 50% of the maximum amplitude observed in the single-row layout and the high-amplitude regions were confined to the impeller leading-edge area. This investigation is beneficial for the design of ECS radial flow turbines with novel tubular nozzles. Full article

Aiming at analyzing the load characteristics and friction torque of triple-row hub bearings for new energy vehicles, this work established a comprehensive theoretical and experimental methodology for predicting the internal load distribution and friction torque. Firstly, considering the preload effect via an initial negative clearance, deformation coordination and force balance equations for the triple-row bearing under axial load were formulated, to analyze the external loads under various driving conditions. Based on contact deformation theory, a quasi-static model was developed to combine radial, axial, and moment loads. The Newton–Raphson iterative algorithm was employed to solve the ball load distribution equations, and the correctness was verified by using the finite element method. Furthermore, accounting for the elastic hysteresis, differential sliding, and spin sliding, the theoretical models for friction torque components were established, to investigate the influence of structural parameters and the total friction torque under different driving conditions. Finally, to confirm the effectiveness and the precision of the model, a finite element simulation and experimental measurements of friction torque were conducted, respectively, which showed good agreement with theoretical calculations. The main innovations include proposing a mechanical modeling method for triple-row hub bearings that accounts for preload effects, and establishing an integrated friction torque analysis model applicable to multiple driving conditions. This work provides theoretical support and a methodological foundation for the design of next-generation hub bearings for new energy vehicles. Full article

External gear pumps are widely used in industrial hydraulic systems, but their volumetric efficiency can deteriorate significantly because of internal leakage, especially under high-pressure operating conditions. Conventional lumped parameter models typically assume fixed clearances and therefore cannot accurately capture the leakage behavior associated with pressure-induced deformation and wear. In this study, a dynamic clearance model for an external gear pump is developed and experimentally validated. Radial and axial clearances are measured in situ using eddy-current gap sensors over a range of operating conditions, and empirical correlation equations are identified as functions of pressure and rotational speed. These correlations are embedded into a tooth-space-volume-based lumped parameter model so that the leakage flow is updated at each time step according to the instantaneous dynamic clearances. The proposed model is validated against experimental measurements of volumetric efficiency obtained from a dedicated test bench. At 800 rev/min, the average prediction error of volumetric efficiency is reduced to 1.98% with the proposed dynamic clearance model, compared with 9.43% for a nominal static-clearance model and 3.35% for a model considering only static wear. These results demonstrate that explicitly accounting for dynamic clearance variations significantly improves the predictive accuracy of volumetric efficiency, and the proposed model can be used as a design tool for optimizing leakage paths and enhancing the energy efficiency of external gear pumps. Full article

Radial piston motors are expected to expand their applications in hydraulic drive systems due to their high torque density and mechanical robustness. However, its volumetric efficiency can be significantly affected by the multi-stroke operating characteristics and leakage occurring in the micro-clearances of the valve plate. In this study, a detailed modeling procedure for a multi-stroke radial piston motor is proposed using the 1D system simulation software Amesim. In particular, the dynamic interaction between the ports and pistons inside the motor is formulated using mathematical function-based expressions, enabling a more precise representation of the driving behavior and torque generation process. Furthermore, to characterize the leakage flow occurring in the micro-clearance between the fluid distributor and cylinder housing, the commercial CFD software Simerics MP+ was employed to analyze the three-dimensional flow characteristics within the leakage gap. Based on these CFD results, a leakage-path function was constructed and implemented in the Amesim model. As a result, the developed model exhibited strong agreement with reference data from an actual motor in terms of overall operating performance, including volumetric and mechanical efficiencies while consistently reproducing the leakage behavior observed in the CFD analysis. The simulation approach presented in this study demonstrates the capability to reliably capture complex fluid–mechanical interactions at the system level, and it can serve as an effective tool for performance prediction and optimal design of hydraulic motors. Full article

This study investigates vibration signals generated during end milling of thin-walled EN AW-7075 aluminum alloy components using a set of 24 tools with distinct cutting edge microgeometries. Five characteristic parameters describing the dynamic response of the process, including both energy-related and statistical indicators, were extracted and analyzed. The results clearly demonstrate the critical influence of tool microgeometry on process dynamics. In particular, the introduction of an additional zero-clearance flank land at the cutting edge proved decisive in suppressing vibrations. For the most favorable geometries, the root mean square (RMS) value of vibration was reduced by more than 50%, while the spectral power density (PSD) decreased by up to 70–75% compared with the least favorable configurations. Simultaneously, both time- and frequency-domain responses exhibited complex and irregular patterns, highlighting the limitations of intuitive interpretation and the need for multi-parameter evaluation. To enable a synthetic comparison of tools, the Vibration Severity Index (VSI), which integrates RMS and kurtosis into a single composite metric, was introduced. VSI-based ranking allowed the clear identification of the most dynamically stable geometry. For the selected tool, additional analysis was conducted to evaluate the influence of cutting parameters, namely feed per tooth and radial depth of cut. The results showed that the most favorable dynamic behavior was achieved at a feed of 0.08 mm/tooth and a radial depth of cut of 1.0 mm, whereas boundary conditions resulted in higher kurtosis and a more impulsive signal structure. Overall, the findings confirm that properly engineered cutting-edge microgeometry, especially the formation of additional zero-clearance flank land significantly enhances the dynamic of thin-wall milling, demonstrating its potential as an effective strategy for vibration suppression and process optimization in precision machining of lightweight structural materials. Full article

This paper addresses the issue of fault diagnosis in high-speed train bogie bearings under complex working conditions and proposes a method for calculating the characteristic frequency of rolling bearings that takes into account the influence of radial clearance. By establishing a five-degree-of-freedom nonlinear dynamic model, this study systematically analyzes the modulation mechanism of radial clearance on the fault characteristic frequency of bearings and verifies the findings through an experimental platform. The results indicate that an increase in clearance not only leads to significant attenuation of the fault characteristic frequency amplitude, but also induces sideband modulation effects, thereby interfering with fault diagnosis accuracy. The experimental data show good agreement with the theoretical calculations, verifying the effectiveness of the proposed method. Specifically, the nonlinear stiffness-based characteristic frequency calculation reduces the prediction error from 6.9–5.7% under traditional theory to 2.3–3.4% across a wide range of rotational speeds. Meanwhile, the clearance-induced amplitude attenuation predicted by the model is also experimentally confirmed, with measured amplitude reductions of 35–42% as clearance increases from 0.2 μm to 0.5 μm. These results not only demonstrate the accuracy and engineering applicability of the method but also provide new theoretical foundations and practical references for health monitoring and early fault diagnosis of high-speed train bearings. Full article

In coastal pumping stations, the intake sump geometry strongly affects flow uniformity, hydraulic loss, and vortex formation. This study establishes an Isight-based automated simulation and optimization framework for an axial-flow pump with a closed-type intake to clarify the influence of bellmouth diameter and clearance height on sump hydraulics. A Radial Basis Function surrogate model combined with the NonLinear Programming by Quadratic Lagrangian (NLPQL) was employed to minimize hydraulic loss and improve flow uniformity. The results show that hydraulic loss first decreases and then increases with bellmouth diameter, whereas velocity uniformity and the mean inflow angle exhibit nonlinear variations with clearance height. The optimal configuration increases efficiency by 3.82% and the velocity uniformity by 1.62% compared with the baseline. Helicity density and the Ω-criterion were used to identify vortex structures, revealing that small clearances intensify bottom and wall-attached vortices, whereas larger clearances promote symmetric inflow. An improved tangential-velocity method based on iso-vorticity contours effectively captured near-wall vortex dynamics. These findings provide theoretical support for achieving low head loss, stable inflow, and controlled vortex behavior in axial-flow pump intake systems. Full article

Planetary gears consisting of simple external gear wheels and an internal ring gear are widely used in industry in various fields. This type of drive is most commonly found in robots, and it is also frequently used in the automotive industry, such as in wheel hub drives, in addition to general engineering. This study investigates the design of simple planetary gears manufactured with involute gearing. In simple internal gear planetary gears, the orbiting motion of the planetary gear is transferred to the output shaft by a radial balancing clutch and converted into rotary motion through the planetary gear’s guiding holes and the output element’s pins. The guiding holes reduce the planetary gear teeth strength, and the rim thickness “h” has a fundamental influence on the resulting tooth root stress. The main objective of this research is to design external gears with relief for simple planetary gears with a rim thickness “h” that does not decrease the load-carrying capacity. The dimensioning of involute gearing is well known, but the tooth root weakening effect of the clearance holes in such planetary gears is not known. Therefore, this paper focuses on analyzing how the size and position of the guiding holes influence tooth root stress, using finite element method (FEM) calculations performed in SolidWorks 2023. This study aimed to determine the rim thickness “h” required for the design of such a gear in order not to weaken the load-carrying capacity of the gear teeth. As a result of the research, the design of the guiding holes and the wheel relief holes can be performed with an accurate knowledge of their influence on tooth stress. The research results also make it possible to design this type of planetary gear using simple analytical calculation algorithms. Our goal was to define a simple design limit that could be used specifically in the preliminary design phase. This allows designers to determine the positions and dimensions of the guiding holes in the preliminary design phase without affecting the tooth stress. Full article

Effective metabolic waste clearance and maintaining ionic homeostasis are essential for the health and normal function of the central nervous system (CNS). To understand its mechanism and the role of fluid flow, we develop a multidomain electro-osmotic model of optic-nerve microcirculation (as a part of the CNS) that couples hydrostatic and osmotic fluid transport with electro-diffusive solute movement across axons, glia, the extracellular space (ECS), and arterial/venous/capillary perivascular spaces (PVS). Cerebrospinal fluid enters the optic nerve via the arterial parivascular space (PVS-A) and passes both the glial and ECS before exiting through the venous parivascular space (PVS-V). Exchanges across astrocytic endfeet are essential and they occur in two distinct and coupled paths: through AQP4 on glial membranes and gaps between glial endfeet, thus establishing a mechanistic substrate for two modes of glymphatic transport, at rest and during stimulus-evoked perturbations. Parameter sweeps show that lowering AQP4-mediated fluid permeability or PVS permeability elevates pressure, suppresses radial exchange (due mainly to hydrostatic pressure difference at the lateral surface and the center of the optic nerve), and slows clearance, effects most pronounced for solutes reliant on PVS–V export. The model reproduces baseline and stimulus-evoked flow and demonstrates that PVS-mediated export is the primary clearance route for both small and moderate solutes. Small molecules (e.g., A$\beta$) clear faster because rapid ECS diffusion broadens their distribution and enhances ECS–PVS exchange, whereas moderate species (e.g., tau monomers/oligomers) have low ECS diffusivity, depend on trans-endfoot transfer, and clear more slowly via PVS–V convection. Our framework can also be used to explain the sleep–wake effect mechanistically: enlarging ECS volume (as occurs in sleep) or permeability increases trans-interface flux and accelerates waste removal. Together, these results provide a unified physical picture of glymphatic transport in the optic nerve, yield testable predictions for how AQP4 function, PVS patency, and sleep modulate size-dependent clearance, and offer guidance for targeting impaired waste removal in neurological disease. Full article

This study systematically analyzes the dynamic behavior of bearing tilt-misalignment coupling faults in rotary joints and establishes a high-fidelity nonlinear dynamic model for a dual-support bearing–rotor system. By integrating Hertzian contact theory, the nonlinear contact forces induced by the tilt of the inner/outer rings and axial misalignment are considered, and expressions for bearing forces incorporating time-varying stiffness and radial clearance are derived. The system’s vibration response is solved using the Newmark-β numerical integration method. This study reveals the influence of tilt angle and misalignment magnitude on contact forces, vibration patterns, and fault characteristic frequencies, demonstrating that the system exhibits multi-frequency harmonic characteristics under misalignment conditions, with vibration amplitudes increasing nonlinearly with the degree of misalignment. Furthermore, dynamic models for single-point faults (inner/outer ring) and composite faults are constructed, and Gaussian filtering technology is employed to simulate defect surface roughness, analyzing the modulation effects of faults on spectral characteristics. Experimental validation confirms that the theoretical model effectively captures actual vibration features, providing a theoretical foundation for health monitoring and intelligent diagnosis of rotary joints. Full article

In squeeze casting, the injection parameters including fit clearance, speed, temperature, and their uncertainties significantly impact the forming quality. Robust optimization can improve the design reliability and reduce the influence of uncertainty while using a suitable metamodel is beneficial for prediction accuracy and efficiency. This paper proposes a robust optimization method based on a hybrid metamodel with Simplified Pareto and Updated Training Set (SPUTS) to improve the prediction accuracy along the Pareto front and in the whole design space. After the first round of robust optimization based on a general metamodel, the training set is updated by simplifying the Pareto solution set. A finite element simulation is performed to construct a high-precision metamodel that combines the kriging and radial basis function (RBF) models to run a new robust optimization. The proposed method was validated by application to the robust optimization of an injection mechanism with a large inner diameter. The results indicated that the SPUTS hybrid metamodel greatly reduced the prediction errors in the test set. The optimized design showed better reliability and robustness and had a greater clearance ratio than the initial design. Full article

As a core component of large marine engines, the compressor delivers robust and efficient power for propulsion. This study focuses on assessing and quantifying the uncertainty in the aerodynamic performance of a transonic rotor under various operating conditions, with the aim of investigating the impact of blade manufacturing variability on performance. Monte Carlo simulation (MCS) and sensitivity analysis were initially employed to identify parameters that significantly influence airfoil performance. Subsequently, a non-intrusive polynomial chaos (NIPC) uncertainty quantification model was developed to compare the effects of tip clearance deviation and surface geometry deviation on rotor performance. The study then analyzes how the geometric deviation at the different spanwise sections affects aerodynamic performance. The results reveal that geometric deviations have a more profound influence on aerodynamic performance than blade tip clearance. The impact of geometric deviations on average pressure ratio and efficiency of the transonic compressor rotor intensifies as the air mass flow rate approaches the near-stall point, while it decreases near the choking point. Interestingly, fluctuations in pressure ratio exhibit the opposite trend. Regarding spatial distribution, deviations in the upper half of the blade span (near the tip) exert a more dramatic influence on mass flow rate and pressure ratio fluctuation. A conceivable reason is that the inlet airflow velocity increases along the radial direction of the blade, and manufacturing variations in the same magnitude produce more notable relative geometric deviations in the upper half of the blade span. Centered on the machining tolerance guidelines for transonic compressor rotors, this work recommends stricter profile tolerance requirements for the upper half of the blade span. Full article