The Low-speed high-torque water hydraulic axial piston motors (WHAPMs) are essential for zero-pollution subsea equipment. However, the extreme deep-sea environment amplifies the tribological challenges of traditional WHAPMs. Conventional port plates suffer from severe wear and volumetric leakage under high-pressure water conditions. To resolve these fundamental bottlenecks, this study focuses on the core fluid commutation mechanism. A novel pentagonal-wheel actuated valve distribution mechanism is proposed to completely replace the traditional port plate. First, a comprehensive theoretical framework for internal fluid dynamics and kinematic forces was established. The dynamic superiority of this mechanism was then validated through numerical simulations and standard laboratory testing. Prototype tests demonstrate that at 21 MPa and 90 r/min, the motor generates 1200 N·m of torque with a minimal fluctuation rate of 5%. This aligns perfectly with theoretical expectations. Furthermore, the volumetric efficiency consistently exceeds 95%, and the total efficiency remains above 82% across varying conditions. By completely eliminating the problematic sliding friction pairs, this research solves the fundamental leakage and wear issues in water media. It establishes a highly reliable technical foundation for future deep-sea system integration.
Experimental data on wall shear stress are limited, despite their importance for oil and gas production systems. Knowledge of wall shear stress enables optimizing the thickness of the corrosion protection layer and accurately predicting the frictional pressure gradient. A Constant Temperature Anemometer (CTA) is an indirect method for measuring wall shear stress based on the heat transfer between the hot sensor and the fluid. This work explores the performance of a flush-mounted CTA film probe in contact with mineral oil inside a 2” pipe with average inline velocities up to 2.4 m/s in indoor and outdoor testing facilities.First, the instrument performance is evaluated in an indoor facility with tighter controls on air humidity, ambient and fluid temperatures. Among the tested conditions, an overheat ratio of 0.25 provided the highest sensor sensitivity. The resulting calibration curve from the indoor tests exhibits relatively low measurement scatter, with a range of less than 10%. Next, the sensor is used in outdoor tests under two scenarios: uncontrolled and controlled ambient conditions including factors such as temperature, humidity, thermal radiation, and cross-wind. The improvements in the experimental setup minimized the temperature difference between the probe and its ambient environment surrounding the pipe. The mineral oil temperature was kept constant to limit the temperature effects in the measurements. Initially, the wall shear stress measurements showed larger deviations exceeding 20% under uncontrolled outdoor tests. However, the additional changes in the experimental setup helped decrease the measurement scatter down to levels under 10%, which is similar to the sensor performance in the indoor tests. These results demonstrate the importance of engineering controls in experimental conditions and how the wall shear stress measurements can be improved in outdoor facilities using a CTA film probe in mineral oil.
Precise fluidic control in portable Lab-on-a-Chip (LoC) platforms is frequently constrained by reliance on bulky, active pneumatic control systems. To overcome this limitation, a monolithic passive microfluidic valve was developed, computationally modeled, and empirically validated for autonomous flow rate regulation driven purely by fluid-structure interactions (FSI). The device architecture, comprising a compliant poly(dimethylsiloxane) membrane and a rigid control chamber, was optimized via three-dimensional FSI numerical simulations and subsequently fabricated using a standard soft lithography and irreversible plasma bonding protocol. The hydrodynamic performance was characterized under static, dynamic square-wave, and reverse pressurization regimes. Both numerical calculations and empirical evaluations confirmed that the pressure-induced downward deflection of the elastomeric membrane continuously modulates internal hydraulic resistance by geometrically constricting the fluidic pathway. During forward operation, the microvalve successfully buffers pressure fluctuations, autonomously sustaining a stable volumetric flow rate of 53±2.5 μL/min across a 40 to 70 kPa operational envelope with robust transient stability and minimal hysteresis. Conversely, backward flow testing revealed strictly anisotropic behavior, functioning effectively as a directional fluidic diode; reverse pressurization induces outward membrane deflection that entirely deactivates the autoregulatory capability, permitting unhindered flow rates up to 70 μL/min at 100 kPa. By eliminating the need for external control hardware, this self-adaptive, fully passive architecture offers a scalable and energy-efficient solution for maintaining steady fluid delivery in miniaturized point-of-care diagnostics.
The dynamic characteristics of pilot-operated proportional pressure reducing valves are crucial for their performance in precision hydraulic control systems. Although pilot-operated proportional pressure reducing valves are primarily designed for high-flow operating conditions, they are frequently required to operate in low-flow regulation modes in precision hydraulic control systems, where their dynamic step response exhibits significant degradation, manifested as slow response speed, excessive overshoot and poor stability. To address the aforementioned issues encountered by a specific model of pilot-operated proportional pressure reducing valve under low-flow operating conditions, this paper proposes a structural optimization method based on a genetic algorithm. Firstly, multiple sets of optimized orifices are introduced on the main valve sleeve to improve the flow characteristics. Subsequently, key structural parameters influencing the dynamic characteristics are selected as optimization variables, and the ITAE criterion, which comprehensively reflects the system's dynamic performance, is adopted as the fitness function. The genetic algorithm is employed for the global optimization of these key parameters, yielding an optimal set of structural parameters. Simulation results demonstrate that the optimized spool structure significantly enhances the valve's current step response characteristics under low-flow conditions, with substantial reductions in rise time, settling time, and overshoot. Finally, experimental validation confirms the accuracy and effectiveness of the optimization results. The good agreement between experimental and simulation results verifies that the proposed optimization scheme can effectively improve the current step response characteristics of the pilot-operated proportional pressure reducing valve without compromising its static and other dynamic characteristics.
This study investigated the rainfall intensity-dependent error characteristics of tipping-bucket rain gauges (TBRGs) and evaluated their impacts on watershed rainfall estimation using observed rainfall data. Repeated calibration experiments were conducted under five rainfall intensity conditions (10, 20, 30, 50, and 100 mm/h) to quantify relative error and measurement uncertainty. The results showed that the magnitude of the relative error increased with rainfall intensity, changing from near zero (0.01%) at 10 mm/h to 7.66% (i.e., −7.66%) at 100 mm/h, while the expanded uncertainty remained relatively stable (0.215–0.220 mm). A nonlinear rainfall intensity–error correction function was derived from the experimental results, yielding a coefficient of determination (R2) of 0.961.The proposed correction function was applied to five years (2021–2025) of rainfall observations collected in the Soksacheon watershed, Korea. Annual rainfall increases after correction ranged from 0.16% to 0.76%, reflecting the fact that approximately 83–90% of total rainfall occurred under low-intensity conditions (≤20 mm/h). In contrast, analysis of a heavy rainfall event in August 2022 revealed a maximum observed rainfall intensity of 72 mm/h and an increase in corrected rainfall of up to 2.09%. Time-series analysis further showed that observed and corrected cumulative rainfall remained nearly parallel during low-intensity rainfall periods, whereas divergence increased only during high-intensity rainfall conditions exceeding 20 mm/h.The results indicate, within the adopted correction framework, that rainfall intensity-dependent measurement errors have a limited influence on annual rainfall totals but can become more significant during extreme rainfall events. This study provides a quantitative assessment of the interaction between TBRG measurement errors and watershed rainfall characteristics and quantifies the potential effects of applying a laboratory-derived correction relationship to hydrological and flood-related applications.
This study combined numerical simulations with high speed visualization experiments, and MATLAB was used to quantify cavity geometric parameters. The evolution of cavitation structures in the inducer was investigated under different flow rates and NPSHa. Numerical simulations revealed that the backflow vortex (BFV), perpendicular cavitation vortex (PCV), and tip leakage vortex (TLV) influence cavitation evolution: Below the design flow rate, BFV induced inlet flow nonuniformity alters the blade incidence angle and local pressure distribution, promoting TLV development and PCV formation. Above the design flow rate, BFV nearly disappeared, the inlet flow became more uniform, and TLV driven by the pressure difference across the blade dominated the sustained development of cavitation. Visualization experiments showed that the projected cavity area generally increased as NPSHa decreased, with distinct evolution characteristics at different flow rates. At Q ≥ 1.0 Qd, cavitation was dominated by TLV, and the cavitation cloud extended toward the blade trailing edge as NPSHa decreased. At 1.0 Qd, the cavitation region expanded, and the coexistence of TLV and PCV is observed at lower NPSHa. At 0.8 Qd to 0.9 Qd, TLV and PCV coexisted over the investigated range of NPSHa. At 0.5 Qd to 0.7 Qd, BFV extended into the inlet pipe, while the projected cavity area and maximum projected cavity length first increased and then decreased. Below 0.4 Qd, BFV intensified and caused inlet flow passage blockage. The results indicate that inlet recirculation, TLV, and associated low pressure regions are important factors governing cavitation development, providing guidance for NPSHa margin control, inlet flow passage optimization, and cavitation resistant inducer design.
Micromixers are essential for improving mixing performance in microfluidic devices, especially at low Reynolds numbers where fluid motion is largely laminar and mixing relies mainly on diffusion. Using CFD simulations, we performed a detailed comparison between the Conventional Wavy Channel Micromixer (CWC-M) and the Convergent-Divergent Wavy Channel Micromixer (CDWC-M). The main goal was to evaluate how wavy frequency and the changing widths in convergent-divergent zones affect mixing effectiveness across Reynolds numbers from 0.1 to 60. By contrasting the outcomes with the suggested modeling and earlier research, the CFD modeling is also validated. Through the use of concentration plots, mixing index plots, and pressure drop assessment, the study used quantitative analysis and in-depth mixing. The results show that, in comparison to the CWC-M, the CDWC-M provides superior mixing performance. Notably, for the CDWC-M with a wavy frequency of 8π and a channel width of 150 μm, the greatest mixing indices of 0.99 and 0.95 were obtained at Re = 0.1 and 60, respectively. In addition to the comparative assessment, the study pinpoints a critical Re value of ∼5, corresponding to the transition from diffusion-dominated to advection-dominated mixing. It is demonstrated that convergent–divergent geometry triggers periodic cycles of acceleration–deceleration, which results in boundary layer separation and development of counter-rotating vortices, which have a significant impact on the transverse transport. The findings can be generally applied to understand the mixing strength enhancements mechanisms of CDWC-M in laminar microflows beyond the investigated geometry.
High-pressure dense-phase CO2 reciprocating booster pump discharge valves are subjected to periodic high-pressure differentials and repeated poppet opening-closing motions, which may lead to increased local flow resistance, outlet flow-rate fluctuations, and unstable poppet motion, thereby affecting outlet flow-rate measurement stability and system delivery performance. In this study, a transient dynamic-mesh numerical model coupling poppet motion with valve-gap flow is developed, and evaluation indices including the flow-resistance coefficient, peak flow resistance, flow-resistance fluctuation amplitude, and outlet flow-rate fluctuation amplitude are introduced. The flow-rate prediction capability of the model is validated using equivalent full-pump outlet flow-rate experiments, with relative deviations below 5% under three outlet-pressure conditions. Based on the validated model, the flow-field structure, poppet dynamic response, flow resistance, and outlet flow-rate evolution are analyzed under different valve openings and spring stiffnesses. The results show that the throttling effect in the valve gap is pronounced at small valve openings, and the intensified interaction between the local high-speed jet and recirculating flow in the valve chamber is an important cause of increased flow resistance and flow-rate fluctuations. As the valve opening increases, the axial load exerted on the poppet by the valve-gap jet decreases, and the large-scale recirculation structure in the valve chamber is suppressed. Among the three prescribed spring-stiffness cases of 3200, 4350, and 5300 N/m, the 4350 N/m case provides a more favorable overall balance between reducing peak flow resistance and suppressing flow-resistance fluctuations. Compared with the 3200 N/m case, the peak flow-resistance coefficient decreases by approximately 8.8%, and the flow-resistance fluctuation amplitude decreases by approximately 7.9%, whereas the peak outlet flow rate changes only slightly. These findings provide a reference for transient flow-rate characterization, flow-resistance evaluation, and spring-parameter optimization of discharge valves in high-pressure dense-phase CO2 booster pumps.
To simultaneously enhance both the hydraulic efficiency and pressure pulsation characteristics of double-suction centrifugal pumps, this paper proposes a joint impeller–volute multi-objective optimization framework integrating Gaussian Process Regression (GPR) and Multi-Objective Particle Swarm Optimization (MOPSO). Seven key geometric parameters—namely, impeller outlet width, impeller outlet diameter, blade inlet angle, blade outlet angle, blade thickness, Volute throat area ratio, and splitter end position—were systematically identified via Plackett–Burman experimental design. A surrogate model was constructed using GPR, which demonstrated superior predictive accuracy for head, efficiency, and pressure pulsation compared to Artificial Neural Networks (ANN). The MOPSO algorithm was subsequently employed to generate the Pareto front, and the final optimal design was selected using the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) for multi-criteria decision-making. Experimental validation of the baseline CFD model was performed. Based on this validated numerical framework, the optimized pump configuration was generated to deliver a 1.86% increase in head, a 1.49% improvement in efficiency, and a 34.14% reduction in the overall pressure pulsation energy indicator—defined as the root-mean-square average (RMSa) of pressure pulsation coefficients within the 0 – 4 blade passing frequency (BPF) band. Entropy production analysis further revealed that the joint impeller–volute optimization effectively suppresses flow instability at the impeller–volute interface, near the volute tongue, and around the splitter, thereby significantly mitigating energy losses in the volute. Time–frequency analysis corroborated that pressure pulsation energy is predominantly concentrated within the 0 – 4 BPF band. This study establishes a robust and effective methodology for low-vibration, low-noise design of double-suction centrifugal pumps through rational co-optimization of the impeller and volute geometries.
Reversible Pump-Turbines (RPTs) are essential components for energy coordination and grid regulation due to their operational flexibility and large-scale storage capacity. However, conventional Computational Fluid Dynamics (CFD)-based shape design has become increasingly computationally intensive. To address this challenge, this study proposes a novel collaborative shape optimization approach, termed MS-BFM, which integrates a bi-fidelity surrogate model with a joint framework of Morris-based sensitivity analysis and Singular Value Decomposition (SVD)-based feature reduction. First, a hydrodynamic simulation model is established to capture multi-physics responses under diverse operating conditions. Subsequently, a collaborative shape parameterization strategy is implemented, where the Morris–SVD joint method is employed to sequentially screen influential parameters and map them into a reduced latent space. The MS-BFM optimization model is then constructed by leveraging extensive low-fidelity samples supplemented by sparse high-fidelity data. Results indicate that hydraulic performance was enhanced after optimization, with increases of 1.83% in ηrp, 3.53% in ηrt, and 1.47% in ηot. Furthermore, cavitation safety was improved as evidenced by a significant 14.60% rise in pbp under rated pump conditions. The proposed method was evaluated against a Single-fidelity Optimization Model (SOM) and a Cokriging-based Bi-Fidelity Optimization Model (Co-BFM). Results demonstrate that MS-BFM achieves an R2 of 0.9894 (7.72% and 10.88% higher than SOM and Co-BFM, respectively) and reaches the R2 = 0.95 threshold in just 464 iterations. Furthermore, MS-BFM reduces training time by up to 44.52% compared to SOM while maintaining superior predictive accuracy, offering an efficient solution for the complex optimization of hydraulic machinery.
The operational efficiency of industrial bag filters is strongly dictated by their internal flow distribution and hydraulic resistance; however, the coupled effects of key structural parameters on these aerodynamic characteristics remain insufficiently quantified. This study investigates a small-scale industrial bag filter by combining three-dimensional computational fluid dynamics (CFD) with a three-factor, three-level orthogonal experimental design. A novel multi-index evaluation framework was employed to comprehensively characterize the internal flow field. This framework includes the integrated flow non-uniformity index (assessing bag-to-bag flow allocation), relative root mean square velocity (quantifying cross-sectional velocity fluctuations), and pressure drop. The impacts of baffle perforation ratio, inlet size, and bag spacing on flow redistribution and resistance formation were systematically assessed. Furthermore, experimental measurements were conducted to validate the numerical predictions. Results indicate that inlet size is the dominant structural factor governing both flow uniformity and aerodynamic resistance. The optimal configuration—identified as a baffle perforation ratio of 0.25, an inlet size of 500 mm, and a bag spacing of 170 mm—markedly mitigates inlet jet impingement and suppresses large-scale internal recirculation. At a standard filtration velocity of 1.0 m/min, this optimized design reduces the integrated flow non-uniformity index, relative root mean square velocity, and pressure drop by 47.81%, 60.02%, and 29.84%, respectively, compared to the baseline structure. The simulated trends for both pressure drop and relative root mean square velocity exhibit excellent agreement with experimental measurements across various filtration velocities, demonstrating the reliability of the numerical model. Overall, the proposed multi-index approach provides a robust quantitative basis for the initial flow-field assessment and low-resistance structural design of industrial bag filters.
