Oct 2026· Journal of Applied Fluid Mechanics· 0 citations· 29 references
Abstract
Accurate prediction of centrifugal-pump performance under viscous operating conditions remains challenging, particularly for low specific-speed pumps operating at low Reynolds numbers. This study develops a Reynolds-number-based correction-factor framework derived from a physically based energy-loss analysis. The method explicitly accounts for major internal loss mechanisms, including hydraulic losses, disk friction, leakage flow, recirculation, mixing and diffusion losses, slip-factor deviation, and blade blockage. The model was calibrated using water-test data from an FM-50 centrifugal pump at 1200 rpm and validated using an independent dataset at 900 rpm. The validation results showed accurate head prediction, with and . Efficiency prediction showed larger deviation, with percentage points, reflecting the sensitivity of efficiency to measurement uncertainty and combined loss mechanisms. After validation, the model was extended to viscous-flow conditions and used to derive compact analytical correction factors for head and efficiency as functions of Reynolds number. The proposed expressions showed strong cross-validation performance within the investigated range, with mean for the head correction factor and for the efficiency correction factor. Comparison with ANSI/HI, KSB, and Gülich methods shows that the proposed formulation follows the expected Reynolds-number-dependent trend while providing a more physically interpretable basis for viscous-performance correction. The proposed method offers a practical alternative to conventional correction charts for low specific-speed centrifugal pumps operating under viscous or low-Reynolds-number conditions.
Traditional compressor deviation angle models, primarily developed for NACA and double-circular-arc airfoils, cannot accurately predict the deviation characteristics of modern aerodynamically optimized blades and generally neglect Reynolds number (Re) and Mach number (Ma) effects, limiting their applicability to low-Re compressor designs. To improve prediction accuracy for high-loading compressors under varying Reynolds and Mach numbers, this study develops a physics-enhanced two-stage symbolic regression (PE-TSR) model based on a data-fusion framework. The first-stage symbolic regression model captures the primary effects of blade geometry and aerodynamic loading on deviation angle, while the second-stage model introduces physics-based correction terms associated with Mach-geometry coupling and viscous flow development. The proposed PE-TSR model achieves an average relative error of 2.17% on the test set, representing a 73.9% improvement over the classical Lieblein empirical model. On an independent experimental dataset outside the training set, the model yields a mean absolute error of 1.68° in deviation angle prediction. Sobol global sensitivity analysis indicates that inlet metal angle, loading distribution, and blade camber angle dominate the primary deviation trend, whereas Mach number, Reynolds number, and maximum reverse-flow velocity mainly act as corrective factors that compensate for systematic biases of the primary model under extreme operating conditions. Furthermore, analysis of the PE-TSR analytical formulation reveals that the influence of flow compressibility on the deviation angle is strongly dependent on the blade geometric loading state.
Ruoyu Chen, Chengwu Yang, Lipan Yao et al.· Journal of turbomachinery· 0 citations
This study aims to investigate how high-temperature-induced changes in fluid properties affect the internal flow, energy dissipation and pressure pulsation in centrifugal pumps. It develops a temperature-density coupled correction model based on the Tammann equation of state to improve prediction accuracy under high-temperature conditions. The research systematically analyzes the resulting shifts in unsteady flow behavior, entropy production distribution and excitation mechanisms. The ultimate goal is to provide a theoretical foundation and engineering reference for enhancing the energy efficiency and vibration control of centrifugal pumps operating with high-temperature media.
This study employs a combined numerical and experimental approach. A temperature-density coupled correction model is developed based on the Tammann equation of state. Numerical simulations are conducted using the SST k-ω turbulence model on a validated mesh. An experimental test bench is built to validate the simulated pump performance. The analysis utilizes entropy production theory to quantify and localize energy losses and monitors pressure pulsations at specific points to investigate flow-induced excitation mechanisms under different operating conditions.
High-temperature, low-density media suppress large-scale flow separation within the impeller, significantly decreasing total entropy production and shifting energy dissipation from a concentrated to a distributed pattern. Flow stability improves as separation vortices are eliminated. The dominant pressure pulsation frequency shifts from a low-frequency axial mode to the blade passage frequency and its harmonics. Correspondingly, the primary excitation mechanism transitions from rotation-induced stall to dynamic-static interference and small-scale vortex shedding.
The study's limitations include the numerical model's omission of tip clearance, wall roughness, mechanical and volumetric losses, contributing to residual prediction errors. Experimental validation is based on a single pump handling a specific medium, limiting generalizability.
The study enables more accurate performance prediction for centrifugal pumps handling high-temperature media, directly aiding in optimized hydraulic design and reducing safety margins. It demonstrates that operating with high-temperature, low-density fluids inherently reduces large-scale flow instabilities and shifts energy loss patterns, guiding the selection of operating conditions for improved system efficiency. The identified shift in dominant pressure pulsation frequency and excitation mechanism provides critical insights for mitigating vibration and fatigue, informing the design of pump casings, support structures and connected piping in thermal systems for enhanced reliability in industries like chemical processing and power generation.
This research supports the global transition toward sustainable energy by enhancing the efficiency of critical thermal systems. Improving centrifugal pump performance reduces industrial energy consumption and associated carbon emissions. Increased operational reliability and safety in chemical plants and power stations contribute to environmental protection and public safety. By providing a pathway to design more robust and efficient industrial equipment, the study aids in reducing lifecycle costs and resource waste, ultimately supporting cleaner industrial processes and more stable energy infrastructure for society.
The study's originality lies in establishing a direct mechanistic link between high-temperature property changes and flow-energy-vibration coupling in centrifugal pumps, a gap in prior ambient-temperature research. It introduces a validated temperature-density coupled correction model based on the Tammann equation, moving beyond constant-property assumptions. Its value is providing a quantitative framework that explains how property shifts suppress large-scale separation, redistribute entropy production and fundamentally alter pressure pulsation dominance from stall to blade-frequency excitation. This enables accurate performance prediction and targeted design for efficiency and reliability in thermal systems.
Pump-turbines often experience performance deterioration under high-load conditions beyond their best efficiency point, while the underlying flow mechanisms remain insufficiently understood. In this study, we investigate the relationship between internal flow structures and energy performance in a pump-turbine operating at a rated head of 202 m over a range of guide vane openings. Energy losses are evaluated using an average kinetic energy-based method and compared with an entropy production approach. A threshold-independent rigid vorticity method is adopted for vortex identification, and a streamline-based coordinate system is introduced for spatial quantification of energy loss and blade loading. The results show that hydraulic losses are mainly concentrated in the draft tube (66–75%) and runner (25–30%) under high-load conditions. A coupled vortex system formed by separation vortices and horseshoe vortices governs localized dissipation in the runner. In the draft tube, a columnar vortex rope generates strong shear layers that dominate energy loss in the cone and elbow regions. At high flow rates, negative incidence induces pressure-side separation, forming negative torque regions that reduce net runner torque and lead to output power deterioration. These findings highlight the dominant role of coupled vortex structures and pressure redistribution in performance degradation under high-load operation.
Lingkai Zhu, Kai Liang, Yunkuan Yu et al.· Applied Sciences· 0 citations
Pumped-storage hydropower requires pump-turbines to operate safely and efficiently under off-design conditions, where stall-induced unsteady flows can redistribute hydraulic losses and reduce operational stability. Unlike previous analyses focused mainly on spatial correlations, this study develops a spatiotemporal framework to clarify how hydraulic loss (HL) and vortex evolution (VE) co-vary under different stall states at the valley point of the pump-mode hump region in a low-specific-speed, ultra-high-head pump-turbine. Detached eddy simulations (DESs) were performed for an original-runner scheme (ORI) and an optimized-runner scheme (OPT), with identical stationary components, boundary conditions, and numerical settings. The comparative cases cover four representative flow states: non-stall, fixed stall, rotating stall, and mixed stall. The local hydraulic-loss rate (LHLR) was decomposed into dissipation (DIS) and transport (TRANS) terms, and Liutex-based vorticity decomposition was used to distinguish shear- and rigid-rotation-related vortex quantities. Pearson correlation analysis was then applied in both space and time. The results show that DIS is consistently associated with shear enstrophy ΩS, whereas the spatiotemporal correlation associated with TRANS and VE parameters exhibits stronger regional and stall-state dependence. These findings provide a quantitative basis for identifying loss-sensitive vortex features and support flow-control and runner-optimization strategies for improving pump-turbine efficiency and stability.
To address the low efficiency and unclear internal loss mechanisms of azimuth waterjet propulsion (AWP) systems operating under shallow and complex flow conditions, this study investigates an AWP unit at 950 rpm with a thrust of 1.63 kN. Steady numerical simulations are conducted under mooring and low-speed conditions, focusing on thrust coefficient, impeller efficiency, pump efficiency, and diffuser flow characteristics, with comparisons to a conventional mixed-flow pump. The results show that the propeller hydraulic efficiency at the design condition is approximately 52%, significantly lower than the 80–93% typical of mixed-flow pumps. The diffuser contributes nearly 80% of the total hydraulic loss, dominated by secondary flow effects. From the perspective of radial equilibrium in the guide vanes, secondary flow development is closely linked to spanwise momentum non-uniformity and deviation from equilibrium. The inclined outflow from the impeller induces strong spanwise imbalance, while the nearly 180° turning in the diffuser suppresses conventional force terms and establishes a pressure-gradient-dominated inertial balance associated with streamline curvature. This mechanism drives transverse migration and entrainment, promoting the formation of counter-rotating vortex pairs and secondary flows. Four major vortex concentration regions are identified, where interactions between secondary flow and recirculation generate complex three-dimensional vortex structures, including induced and spiral separation vortices. These vortices locally block the flow passage, causing pressure fluctuations and energy dissipation. The mid-span region of the guide vanes is identified as the primary location of loss accumulation. These findings provide theoretical and engineering guidance for diffuser optimization in AWP systems. It should be noted that the present study is based solely on numerical simulations, and no experimental validation for the investigated AWP configuration is currently available. Future experimental studies are needed to further verify the predicted hydraulic performance and flow structures.
Electric ducted fans (EDFs) have emerged as promising propulsion systems due to their compact design, high thrust density, and enhanced operational safety. Accurate prediction of aerodynamic thrust is essential for EDF design and performance evaluation; however, existing numerical studies have not yet provided a systematic comparison of the thrust-prediction capability of different k-ω-based turbulence models in micro-EDF applications. In this study, a dedicated thrust-measurement platform was developed for a 120 mm EDF, and experimental thrust data were obtained under three representative hover operating conditions. Based on these measurements, six turbulence models, including SST, SKω, BSL, GEKO, EARSM, and SST-γ(alg.), were evaluated using three-dimensional CFD simulations. The numerical model was assessed through thrust validation, centerline velocity comparison, power-consistency analysis, grid independence verification, and qualitative flow-field interpretation. A two-factor full-factorial analysis was further conducted to quantify the effects of rotational speed and turbulence model on prediction accuracy and computational cost. The results show that the turbulence model has a stronger influence on the normalized thrust-prediction error than the rotational speed factor over the investigated operating range. The SST-γ(alg.) model achieves the highest thrust-prediction accuracy, with an average relative deviation of 0.47%, but requires the highest computational cost. In comparison, the SST model provides a favorable balance between accuracy and efficiency, with an average relative deviation of 1.79% and an average computation time of 184.33 min, approximately 33% lower than that of the SST-γ(alg.) model. The centerline velocity and power-consistency results further support the comparative model assessment. Overall, this study provides an experimentally validated comparative reference for turbulence model selection in simulations of similar 120 mm EDF under hover conditions. Considering both prediction accuracy and computational efficiency, the SST model can serve as a practical turbulence model choice for engineering parameter optimization of similar micro-EDF configurations.k−ω
Shenglun Zhang, Chuanping Tang, Hamza Blala et al.· Aerospace· 0 citations
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.
