Search Results (748)

A three-dimensional numerical investigation is conducted to clarify the internal pressure and velocity distributions in a hydraulic turbine under multiple operating conditions. The study aims to identify the main high-gradient regions and the influence of operating parameters on the internal flow field. The incompressible single-phase Navier–Stokes equations are solved using the SST k-ω turbulence model. Eleven operating conditions with different guide vane openings, net heads, output powers, and discharges are simulated using a full-passage turbine model with mass flow inlet and static pressure outlet boundary conditions. The numerical results are validated against experimental performance data. The results show that the pressure and velocity fields exhibit generally symmetric distributions in the circumferential and axial directions, whereas strong local gradients appear in the rotor–stator interaction region. Local high-pressure and high-velocity zones are mainly observed near the blade leading edges, while low-pressure and low-velocity regions develop near the trailing edges, runner cone, and draft tube. Increasing the net head raises the overall pressure and velocity levels and enhances the low-pressure and low-velocity regions in the draft tube. Under a fixed head, increasing the guide vane opening mainly affects the flow distribution around the stay and guide vanes and modifies the flow structure in the runner cone and draft tube. These findings provide a systematic numerical characterization of the pressure and velocity distributions in the turbine and help identify critical regions for further hydraulic performance analysis and flow field optimization. Full article

This study presents a comprehensive numerical investigation of a modified backward bent duct buoy (BBDB) floating oscillating water column (FOWC) system, with emphasis on coupled hydrodynamic response and power take-off (PTO) representation. A fully integrated computational framework is developed using SIEMENS STAR-CCM+, ANSYS AQUA and ANSYS CFX, and three-dimensional CFD, incorporating free-surface wave modeling (VOF), six-degree-of-freedom (6-DOF) body motion, and mooring system interaction under realistic offshore wave conditions (H_s = 3.0 m, T = 9.0 s). A key contribution of this work is the development of an orifice-based PTO surrogate calibrated to replicate turbine-equivalent pressure-drop behavior. Comparative analysis demonstrates that the selected 0.30D orifice reproduces turbine response with deviations below 10% in pressure and flow characteristics, while maintaining superior numerical stability. Hydrodynamic analysis confirms that the modified BBDB-FOWC exhibits stable and bounded motion, with dominant heave-driven response and controlled pitch behavior. The influence of viscous damping is quantified through free-decay analysis and incorporated into the coupled simulations. Results show that damping enhances pressure development by ~25% and flow throughput by ~20%, leading to a significant increase in energy extraction potential. Dimensionless analysis further reveals that the system operates in a turbulent, inertia-dominated regime, governed by nonlinear oscillatory flow dynamics. The combined results demonstrate that the proposed methodology enables accurate, stable, and computationally efficient modeling of floating OWC systems with realistic PTO behavior. The findings provide a scalable framework for future optimization and support the development of high-performance offshore wave energy converters. Full article

Blade tip leakage flow in gas turbines is associated with aerodynamic loss and local heat transfer variation in the tip region. In this study, the flow structure, total pressure loss coefficient, heat transfer coefficient (HTC), and film cooling effectiveness (FCE) were numerically investigated for a plane tip (PLN) and five squealer tip geometries: a conventional squealer tip (SQR), cutback squealer tip (CBS), multi-cavity squealer tip (MCS), triangular-grooved suction-side squealer tip (GSS), and multi-cavity triangular-grooved suction-side squealer tip (MGS). All configurations were compared under the same cascade geometry, tip-clearance condition, and inlet/outlet boundary conditions to examine the geometry-dependent relationship among aerodynamic loss, heat transfer, and film cooling performance. Film cooling was evaluated at blowing ratios of M = 1 and 2 using a camber-line hole arrangement, and the effect of hole rearrangement was further examined at the same blowing ratio and with the same number of cooling holes. The results indicate that the aerodynamic and thermal characteristics of the tip region vary with the leakage-flow path, cavity recirculation, and reattachment behavior formed by each tip geometry. Under the present conditions, SQR showed the lowest downstream total pressure loss coefficient, with a 7.27% reduction relative to PLN, whereas MGS showed the lowest geometry-normalized heat transfer rate among the tested geometries. Increasing the blowing ratio tended to increase FCE, although local cooling performance was affected by high-pressure or reattachment-dominated regions where coolant ejection, surface attachment, or lateral spreading was limited. Compared with the camber-line arrangement, the rearranged hole configuration increased local FCE by up to 29.6% for CBS and 23.3% for MGS at the same blowing ratio. These results may be used as comparative data for evaluating squealer tip geometries and cooling-hole placement during preliminary blade tip cooling design. Full article

Monitoring the operating status of steam turbines is critical for efficient and safe power generation. This study proposes a digital twin design and modeling method for steam turbines, integrating reverse modeling techniques with genetic algorithm optimization. Firstly, the geometric design model is reconstructed from 3D-scanned point cloud data using point cloud fusion and surface reconstruction technologies, covering 13 stages of high-pressure rotor blades, 9 stages of intermediate-pressure stator blades, and the cylinder. Secondly, a physics-based model suitable for computational fluid dynamics simulations is generated using optimized mesh design parameters. To address unmeasurable parameters, a genetic algorithm is applied for data-driven design optimization, enhancing the dynamic simulation accuracy to 95%. Finally, leveraging a reduced-order model, real-time mapping of key physical fields is achieved. The effectiveness of the design methodology is validated under typical deep peak-shaving operating conditions. Full article

The accurate reconstruction and real-time prediction of transient three-dimensional flow fields in hydraulic turbines are critical for ensuring operational stability under renewable energy-driven variable-load conditions, yet conventional computational fluid dynamics (CFD) approaches remain too computationally expensive for digital twin applications. This paper proposes a hybrid framework that integrates Proper Orthogonal Decomposition (POD) with Long Short-Term Memory (LSTM) networks to reconstruct and predict the unsteady flow field within the draft tube of a Francis turbine using only four sparse wall-mounted pressure sensors. The methodology begins with high-fidelity Large Eddy Simulation (LES) to establish a comprehensive flow field database under Part Load (PL), Best Efficiency Point (BEP), and High Load (HL) conditions. POD is subsequently applied to extract dominant coherent structures and their temporal coefficients, achieving a low-dimensional representation of the high-dimensional flow field. A comparative analysis between standard POD and weighted POD reveals that under the PL condition characterized by a strong double-helical vortex rope, the weighting effect is significant—standard POD captures 90% of the total energy with the first 2 modes, while weighted POD requires up to 8 modes to reach the same threshold. Under the BEP and HL conditions, the energy distributions of the two methods are nearly identical, yet weighted POD still yields cleaner spatial modes with sharper vortex boundaries and fewer spurious wall-region vortices. An LSTM network is then trained to establish a mapping between time-series signals from the four sensors and the POD temporal coefficients. The results demonstrate that LSTM prediction performance is governed by the spatial correlation between each mode and the sensor locations rather than by temporal regularity. Modes that project strongly onto the sensor locations—PL Modes 1–2 (R² = 0.85 and 0.513), BEP Mode 1 (R² = 0.96), and HL Mode 1 (R² = 0.92)—are reliably predictable, while PL Mode 3 and HL Mode 2, despite their regular temporal oscillations, yield strongly negative R² values (−3.366 and −186.6) because their spatial structures are concentrated away from the wall. With a condition-adaptive strategy predicting only sensor-correlated, energetic modes, the reconstructed pressure fields achieve mean L2 relative errors of 17.01% (PL), 7.17% (BEP), and 12.91% (HL). Because the mean flow dominates total pressure energy (86.66–98.07%), the effective absolute error is substantially lower. The proposed POD-LSTM framework successfully bridges the gap between high-fidelity CFD and real-time monitoring, enabling full-field flow state estimation from sparse sensor measurements without the computational expense of online simulations. This capability is particularly valuable for digital twin applications in hydraulic turbines operating under rapidly varying renewable energy conditions. Full article

This work investigates the performance degradation of dual vertical axis wind turbines at low tip speed ratios using numerical simulation using two-dimensional computational fluid dynamics (CFD). In order to address this problem, it suggests a unique deflector configuration and arrangement. The results show a 21.33% improvement in self-starting potential at low TSRs when dual-configuration deflectors are deployed close to the twin rotors. Additionally, the average torque coefficient increases by 24.31% and the peak power coefficient increases by 53.12%, indicating a significant improvement in performance at high tip speed ratios. While curved deflectors on both sides provide converging channels that increase flow volume and dynamic pressure in the downwind zone, the central deflector decreases reverse airflow in the midsection. The proposed deflector arrangement also exhibits great potential for the compact layout of wind farm arrays; the accelerated wake recovery characteristic is beneficial to improving the overall efficiency of wind farms. With important ramifications for the advancement of renewable energy technology, this work provides fresh insights into dual vertical axis wind turbine optimization. Full article

Plasma-sprayed yttria-stabilized zirconia (YSZ) coatings are critical to enhancing the performance of thermal barrier coatings in gas turbines and aero-engines; however, their service life is significantly constrained by microstructural evolution and multi-mechanism coupling effects. Focusing on plasma spraying process routes (atmospheric plasma spraying, APS; suspension plasma spraying/solution precursor plasma spraying, SPS/SPPS; low-pressure plasma spraying, LPPS) and key process parameters as primary input variables, this review systematically analyzes their regulatory roles in microstructural characteristics such as porosity and crack density. Available studies indicate that distinct process routes give rise to pronounced structural differences: the porosity of APS coatings is 10%–20%, that of SPS/SPPS coatings is 15%–30%, and that of LPPS coatings is 1%–8%. After thermal exposure above 1100 °C, the porosity decreases to 6%–12%, 8%–18%, and 0.5%–3%, respectively, while the thermal conductivity increases to a maximum of approximately 2.5 W·m⁻¹·K⁻¹ and the Young’s modulus rises to 60–220 GPa. Further analysis reveals that mechanisms such as sintering densification, phase destabilization, thermally grown oxide (TGO) interfacial stress accumulation, and calcium–magnesium–alumino-silicate (CMAS) infiltration exert coupled amplification effects through microstructural evolution, thereby accelerating coating failure. On this basis, emerging regulation strategies are evaluated: the CMAS penetration depth of high-entropy oxides at 1300 °C for 5 h is only about 1/7 that of conventional YSZ, the thermal cycling life of self-healing coatings is enhanced by up to 4.2 times, and the crack density is reduced by approximately 35%. Finally, it is proposed that a quantitative prediction model integrating “structural parameters–evolution kinetics–service life” should be established, and that anti-sintering design, gradient structures, and functionalized systems be combined to enable the transition of YSZ coatings from empirical optimization to predictable design. Full article

Tube boilers are extensively employed in oil and gas refineries, as well as in petroleum, energy, and power generation industries, where they serve critical functions in local steam-generation units and combined-cycle gas turbine (CCGT) plants. However, these boilers are prone to defects arising from waterside corrosion (e.g., thinning of U-bend tubes), fireside corrosion, and material degradation caused by stress or creeping. Among these issues, wall thinning of tube bends is particularly severe, as it results in localized metal loss, reduced structural integrity, and an elevated risk of tube rupture or failure under high-temperature and high-pressure operating conditions. Such failures can significantly compromise boiler safety and efficiency, potentially leading to forced outages, costly unplanned repairs, or catastrophic damage if not detected in time. The current condition-monitoring policy for U-bends relies on scheduled preventive maintenance and unscheduled corrective interventions. In practice, this involves randomly checking approximately 10–20% of the tubes through spot scanning, partial scanning, or full scanning, with repairs typically carried out only after an undetected failure occurs. Such maintenance strategies generally require plant shutdowns, making the process time-consuming, labor-intensive, and ultimately not cost-effective. This paper reviews existing solutions, technologies, and research addressing the problem, and introduces femtosecond laser micromachined fiber optic sensors as a transformative approach for real-time monitoring of wall thickness reduction in U-bend boiler tubes, thereby opening pathways for further research. Full article

Organic Rankine Cycles (ORCs) are widely recognized as an effective solution for waste heat recovery (WHR). However, the design and optimization of these systems must address the tradeoff between computational efficiency and the need to capture complex component behavior. This requires moving beyond purely energetic 0D modeling approaches to account for constructional, spatial, and operational constraints. This work presents a novel modeling framework with a specific focus on the expansion device. Radial inflow turbine stages are selected for their capability to achieve high pressure ratios while maintaining compactness and high efficiency. Heat exchangers follow a generic one-dimensional counterflow configuration, with a shell-and-tube geometry adopted for sizing purposes. The turbine stages are modeled by resolving several internal sections in order to capture local thermofluid dynamic conditions. The framework predicts turbine efficiency and incorporates a newly developed formulation for shock-induced losses, improving performance prediction under trans-sonic flow conditions. After validation against experimental data, the model is applied to a WHR system integrated with an internal combustion engine fueled by biofuels. The results highlight the existence of optimal operating conditions arising from competing physical mechanisms. The analysis also shows the transition from single-stage to two-stage turbine configurations at high pressure ratios and emphasizes the role of real gas effects in determining stage performance and optimal expansion distribution. The results of simulations carried out for three different working fluids (ethanol, toluene, and R1234ze(E)) highlight that the available mechanical power ranges from 10 to 22 kW for single-stage turbine configurations and from 24 to 36 kW for two-stage configurations, with total system volumes varying between approximately 600 and 9000 L. Among the working fluids considered here, ethanol provides the best overall performance for the present case study. Overall, the proposed approach provides a reliable and computationally efficient tool for the preliminary design and optimization of ORC-based WHR systems. Full article

Accurately predicting the temperature field of turbine blades is of great significance for evaluating the thermal reliability and service life of high-temperature components in aero-engines. However, due to the high computational cost of numerical simulations and the limitations imposed by complex geometric structures and harsh operating environments, experimental measurements can usually only obtain sparse sensor data, making the acquisition of complete temperature distributions still challenging. Therefore, reconstructing the complete temperature field under sparse measurement conditions has become a key research issue in turbine thermal analysis. To address this problem, this paper proposes an attention-enhanced CNN–LSTM framework for reconstructing transient turbine blade temperature fields from sparse data. The model combines the spatial feature extraction capability of Convolutional Neural Networks (CNNs) with the time-series modeling capability of Long Short-Term Memory networks (LSTM). An SE channel attention module is introduced in the CNN feature extraction stage to achieve adaptive recalibration of channel features, and a temporal attention mechanism is incorporated after the LSTM layer to highlight key transient thermal features. A multi-condition temperature field dataset was constructed by conducting Computational Fluid Dynamics (CFD) simulations on low-pressure turbine guide vanes, and the model was experimentally validated through thermal shock tests. The results show that the proposed model can accurately reconstruct the spatial distribution and transient evolution of the turbine blade temperature field under sparse measurement conditions. Under different operating conditions, the predicted temperature fields are highly consistent with the CFD results, with the maximum Reconstruction error remaining below 19 °C. Error distribution analysis indicates that the model has stable Reconstruction performance and good generalization ability. Full article

Rain erosion is a critical issue for the development of wind power generation because it limits the lifetime of wind turbine blades. To clarify the erosion initiation mechanism in wind turbine blades of metallic material, pit formation and erosion initiation on a smooth wet wall of aluminum materials A3003 and annealed A5052 were investigated; water droplets were impinged on the wall using a pulsed-jet tester; and combined theoretical and numerical studies were performed by considering the influence of the water film on the wall. Although the theoretical and numerical impact pressures were much lower than the offset yield strength of the materials, random pit formation and erosion initiation were observed on the target material. To clarify the reason for this, the occurrence of cavitation erosion was investigated based on the numerical pressure distribution of a droplet impacting a wet wall. The numerical results showed that the pressures in the droplet center and water film became lower than the saturated vapor pressure, suggesting the occurrence of cavitation erosion. Furthermore, a similar pit formation and erosion initiation were observed on the wall material in the acoustic cavitation test under the cavitation erosion condition. These results indicate that the pit formation could have been caused by the high impact pressure caused by the micro-jet mechanism that occurs when a droplet impacts the wet wall. This could potentially explain the mechanism of the more severe erosion in the actual wind turbine blade than was expected. Full article

The design of millimeter-scale micro-turbine blades is challenging due to conflicting requirements: achieving aerodynamic performance while remaining compatible with microfabrication, and exploring high-dimensional morphological design spaces without prohibitive computational cost. To address these challenges, this study proposes an intelligent framework for the design and optimization of the three-dimensional blade profile of a 3 mm diameter micro-turbine. The blade morphology is parameterized using 22 variables, ensuring geometric feasibility for micro-EDM (Electrical Discharge Machining) fabrication. A physics-informed neural network (PINN) surrogate model, efficiently trained through a two-stage active learning strategy combining KD-tree exploration and residual-based sampling, provides accurate predictions of flow fields. Multi-objective optimization using Non-dominated Sorting Genetic Algorithm II (NSGA-II) is then performed to maximize torque and thrust. Experimental results show that the optimized blade achieves a 38.6% increase in rotational speed while retaining 75.1% of thrust at 0.2 MPa inlet pressure, validating the framework’s effectiveness. This methodology offers a systematic solution for designing microfluidic devices characterized by high-dimensional parameters and high-fidelity simulation requirements. Full article

Urban water distribution systems often dissipate excess hydraulic energy through pressure-reducing valves to maintain safe operating conditions, particularly in cities with complex topography. This study investigates the potential for sustainable energy recovery using microturbines in a large-scale urban water distribution system, with a focus on the city of Busan, South Korea. A digital twin of the Busan water transmission and distribution network was developed to analyze system-wide hydraulic characteristics, including elevation, hydraulic head, pressure, and flow. Candidate locations for microturbine installation were identified based on existing pressure regulation points and quantified using hydraulic simulation results. The recoverable power and energy potential were estimated by considering flow rate, available head difference, and turbine efficiency, and the model results were validated using operational data and field investigations at selected sites. The results show that significant recoverable energy is concentrated at pressure-reducing valve locations where excess pressure coincides with high flow rates and substantial pressure differentials under representative operating conditions. The maximum recoverable energy at a single site was estimated to be approximately 16.9 MWh/month, indicating that distributed microturbine installations can provide meaningful supplementary energy recovery. The findings demonstrate that digital twin–based analysis offers a systematic and practical approach for identifying energy recovery opportunities in urban water distribution systems and can support more energy-efficient and sustainable water utility operations. Full article

The development of renewable energy and the increasing demand for electricity underscore the importance of pumped storage for grid stability. Under low-flow pump operating conditions, pump-turbines frequently exhibit hump characteristics, causing severe hydraulic instability and strong pressure pulsations. This study investigates the formation of a hump using full-channel numerical simulations based on the Scale-Adaptive Simulation turbulence model. The numerical flow–head characteristics were validated against the available experimental H–Q data, while the pressure pulsation results were used for qualitative mechanism analysis. The results reveal three major mechanisms: pre-swirl and spiral backflow in the draft tube, non-uniform runner inflow, and vortex flow-induced separation in the wicket gates. An analysis of entropy production reveals that vortex dissipation is responsible for as much as 71% of hydraulic losses in the hump region. In order to mitigate these effects, four stabilizing fins were installed inside the draft tube. The simulations indicate that the fins possess the capability to inhibit swirl and backflow, confine the vortices within the fin–runner interface, improve inflow uniformity and reduce overall hydraulic losses. As a result, the structural modification significantly attenuates the pressure pulsation amplitudes at key monitoring points and visibly shortens the recovery periods. The region of the hump and positive slope of the performance curve are considerably reduced while the head near the region of the hump is increased. Although the intrinsic hump characteristic is still present, the fin-based flow-control strategy can effectively improve the performance and stability of the pump-turbine, which can guide the design and optimization of high-efficiency pumped-storage plants. Full article

Gas turbine engines operate in extremely harsh environments, subjecting turbines to high aerodynamic and thermal loads. In this context, non-axisymmetric endwalls have emerged as an effective strategy for reducing aerodynamic losses and mitigating heat transfer on the endwall surfaces, leading to their widespread adoption in turbine designs. This study presents an optimization of the endwall shape for a turbine guide vane from a real engine, employing the multi-island genetic algorithm. The optimization objectives are the endwall surface heat transfer coefficient and the total pressure loss coefficient at the blade outlet. The findings indicate that the modified endwall disrupts the horseshoe vortex structure at the blade leading edge, adversely influencing the formation and development of passage vortices within the cascade. Notably, this modification results in a significant reduction in aerodynamic losses and a decrease in the heat transfer coefficient on the endwall surface. Specifically, the total pressure loss coefficient at the outlet is reduced by 1.96%, while the endwall surface heat transfer coefficient decreases by 3.05%. These results underscore the considerable effectiveness of the optimized endwall design in enhancing turbine performance. Full article