Search Results (365)

The development of compact high-speed low-pressure turbines with high efficiencies requires the characterization of the secondary flow structures and the interaction of cavity purge and leakage flows with the mainstream. During the SPLEEN project funded by the European Union’s Horizon 2020, the von Karman Institute and Safran Aircraft Engines performed detailed measurements of low-pressure turbines in engine-realistic conditions (i.e., low Reynolds and high exit Mach numbers considering background turbulence, wakes, row interactions, and leakages). The SPLEEN project is thus a fundamental contribution to the progress of high-speed low-pressure turbines by delivering unique experimental databases, essential to characterize the time-resolved 3D turbine flow, and new critical knowledge to mature the design of 3D technological effects. Being able to simulate the flow and associated losses in such a configuration is both challenging and of paramount importance to help the understanding of the flow physics complementing experimental measurements. This paper focuses on the high-fidelity numerical simulation of one of the SPLEEN configuration consisting of a linear blade cascade. The objective is to provide a validated numerical setup in terms of computational domain, boundary conditions, mesh resolution and numerical scheme to reproduce the experimental results. By mean of wall-resolved large-eddy simulations, the design point characterized by an exit Mach number of 0.9 and an exit Reynolds number of 70,000 with a turbulence level of 2.4% is investigated for the baseline configuration without purge and without wake generator. The results show that the considered computational domain and the associated inlet total pressure profile play a critical role on the development of secondary flows. The isentropic Mach number distribution around the blade is shown to be robust to the mesh and numerical scheme. The development of the wake and secondary flow fields are drastically influenced by the mesh resolution and numerical scheme, impacting the resulting losses. Full article

Secondary flow phenomena have a significant influence on the generation of losses and the propagation of coolant on the turbine end walls. The majority of film cooling studies are carried out on linear rather than annular cascades due to the structural simplicity and ease of measurement integration of the former. This approach neglects the effects of the radial pressure gradient that is naturally imposed on the vortex flow in annular cascades. The first part of this paper numerically investigates the effect of the radial pressure gradient on the secondary flow under periodic flow conditions by comparing a linear and an annular case. It is shown that the radial pressure gradient has a significant influence on the propagation of the secondary flow induced vortices in the wake of the nozzle guide vanes (NGV). In the second part of the paper, a novel approach of a five-passage annular sector cascade is presented, which avoids the hub boundary layer separation, as is typical for this type of test rig. To increase the periodicity, a benchmark approach is introduced that includes multiple pointwise and integral flow quantities at different axial positions. Based on the optimized best-case design, general design guidelines are derived that allow a straightforward design process for annular sector cascades. Full article

The growing global demand for electricity, driven by the development of electromobility, data centers, and smart technologies, necessitates innovative approaches to energy generation. Wind power, as a clean and renewable energy source, plays a pivotal role in the global transition towards low-carbon power systems. This paper presents a comprehensive review of generator technologies used in wind turbine applications, ranging from conventional synchronous and asynchronous machines to advanced concepts such as low-speed direct-drive (DD) generators, axial-flux topologies, and superconducting generators utilizing low-temperature superconductors (LTS) and high-temperature superconductors (HTS). The advantages and limitations of each design are discussed in the context of efficiency, weight, reliability, scalability, and suitability for offshore deployment. Special attention is given to HTS-based generator systems, which offer superior power density and reduced losses, along with challenges related to cryogenic cooling and materials engineering. Furthermore, the paper analyzes selected modern generator designs to provide references for enhancing the performance of grid-synchronized hybrid microgrids integrating solar PV, wind, battery energy storage, and HTS-enhanced generators. This review serves as a valuable resource for researchers and engineers developing next-generation wind energy technologies with improved efficiency and integration potential. Full article

This article uses the sailfish outline as an airfoil profile to create a dual vertical-axis water turbine model for capturing wave and tidal current energy. A parametric water turbine model is built with the shape function perturbation and characteristic parameter description methods. Optimized by the multi-island genetic algorithm on the Isight platform, a CNC sample of the optimized model is made. Its torque and pressure are measured in a wind tunnel and compared with CFD numerical analysis results. The results show small differences between the numerical and experimental results. Both indicate that the relevant performance parameters of the turbine improved after optimization. During constant flow velocity measurement, the optimized axial-flow turbine has a pressure increase of 55% and a torque increase of 40%, while for the centrifugal turbine, the pressure increases by 60% and the torque by 12.5%. During constant rotational speed measurement, the axial-flow turbine’s pressure increases by 16.7%, with an unobvious torque increase. The Q-criterion diagram shows more vortices after optimization. This proves the method can quickly and effectively optimize the dual vertical-axis water turbine. Full article

Critical components in support structures for wind turbines, flange joints, are fundamental to ensure the structural integrity of mechanical assemblies under varying operational conditions. This paper investigates the structural performance of L-type flange joints, focusing on the influence of bolt grades and bolt pretension through a finite element analysis (FEA) study of its key performance indicators, including stress distribution, deformation, and force–displacement behaviors. This paper studies two high-strength bolt grades, Grade 10.9 and Grade 12.9, and two main steps—first, bolt pretension and, second, external loading (tower shell tensile load)—to investigate the influence on joint reliability and safety margins. The novelty of this study lies in its specific focus on static axial loading conditions, unlike the existing literature that emphasizes fatigue or dynamic loads. Results show that the specimen carrying a higher bolt grade (12.9) has 18% more ultimate load carrying capacity than the specimen with a lower bolt grade (10.9). Increased pretension increases the stability of the joint and reduces the micro-movements between A and B (on model specimen), but could result in material fatigue if over-pretensioned. Comparative analysis of the different bolt grades has provided practical guidance on material selection and bolt pretension in L-type flange joints for wind turbine support structures. The findings of this work offer insights into the proper design of robust flange connections for high-demand applications by highlighting a balance among material properties, bolt pretension, and operational conditions, while also proposing optimized pretension and material recommendations validated against classical analytical models. Full article

The hydraulic turbine serves as the cornerstone of hydropower generation systems, with the sealing system’s performance critically influencing energy conversion efficiency and operational cost-effectiveness. The sealing ring is a pivotal component, which mitigates leakage and energy loss by regulating flow within the narrow gap between itself and the frame. This study investigates the intricate flow dynamics within the gap between the sealing ring and the upper frame of a super-large-scale Francis turbine, with a specific focus on the rotating wall’s impact on the flow field. Employing theoretical modeling and three-dimensional transient computational fluid dynamics (CFD) simulations grounded in real turbine design parameters, the research reveals that the rotating wall significantly alters shear flow and vortex formation within the gap. Tangential velocity exhibits a nonlinear profile, accompanied by heightened turbulence intensity near the wall. The short flow channel height markedly shapes flow evolution, driving the axial velocity profile away from a conventional parabolic pattern. Further analysis of rotation-induced vortices and flow instabilities, supported by turbulence kinetic energy monitoring and spectral analysis, reveals the periodic nature of vortex shedding and pressure fluctuations. These findings elucidate the internal flow mechanisms of the sealing ring, offering a theoretical framework for analyzing flow in microscale gaps. Moreover, the resulting flow field data establishes a robust foundation for future studies on upper crown gap flow stability and sealing ring dynamics. Full article

This study investigates an aerodynamic optimization framework inspired by marine biological morphology, utilizing the sailfish profile as a basis for airfoil configuration. Through Latin hypercube experimental design combined with optimization algorithms, four key geometric variables governing the airfoil’s hydrodynamic characteristics were systematically analyzed. Parametric studies revealed that pivotal factors including installation angle significantly influenced the fluid dynamic performance metrics of lift generation and pressure drag. Response surface methodology was employed to establish predictive models for these critical performance indicators, effectively reducing computational resource consumption and experimental validation costs. The refined bio-inspired configuration demonstrated multi-objective performance improvements compared to the baseline configuration, validating the computational framework’s effectiveness for hydrodynamic profile optimization studies. Furthermore, a coaxial dual-rotor vertical axis turbine configuration was developed, integrating centrifugal and axial-flow energy conversion mechanisms through a shared drivetrain system. The centrifugal rotor component harnessed tidal current kinetic energy while the axial-flow rotor module captured wave-induced potential energy. Transient numerical simulations employing dynamic mesh techniques and user-defined functions within the Fluent environment were conducted to analyze rotor interactions. Results indicated the centrifugal subsystem demonstrated peak hydrodynamic efficiency at a 25° installation angle, whereas the axial-flow module achieves optimal performance at 35° blade orientation. Parametric optimization revealed maximum energy extraction efficiency for the centrifugal rotor occurs at λ = 1.25 tip-speed ratio under Re = 1.3 × 10⁵ flow conditions, while the axial-flow counterpart attained optimal performance at λ = 1.5 with Re = 5.5 × 10⁴. This synergistic configuration demonstrated complementary operational characteristics under marine energy conversion scenarios. Full article

This study investigates the stability of high-rise wind turbine tower foundations in collapsible loess regions through finite element analysis. The mechanisms by which wind load, extreme rainfall load, and seismic load interact during the dynamic response of a pile foundation under single-action and intercoupling conditions are analyzed. A comprehensive multi-parameter analytical model is developed to evaluate pile foundation stability, incorporating key indicators including pile skin friction, average axial stress of pile groups, horizontal displacement at pile tops, and pile inclination. The results show that, among single-load conditions, seismic loading has the most pronounced impact on foundation stability. The peak horizontal displacement at the pile top induced by seismic loads reaches 10.07 mm, substantially exceeding the effects of wind and rainfall loads, posing a direct threat to wind turbine tower safety. Under coupled loading conditions, notable nonlinear interaction effects emerge. Wind–earthquake coupled loading amplifies horizontal displacement by 1.85 times compared to single seismic loading. Rainfall–earthquake coupled loading reduces the peak of positive skin friction by 20.17%. Notably, all seismic-involved loading combinations significantly compromise the pile foundation safety margin. The seismic load is the dominant influencing factor in various loading conditions, and its coupling with other loads induces nonlinear superposition effects. These findings provide critical insights for wind turbine foundation design in collapsible loess areas and strongly support the need for enhanced seismic considerations in engineering practice. Full article

Accurate loss prediction since the preliminary design steps is crucial to improve the development process and the aerodynamic performance of turbines. Initial design phases typically employ reduced-order models in which the different loss-generating mechanisms are assessed through correlations. These correlations are often based on the hypothesis of loss linearity, which assumes that losses from different sources can be summed to obtain the total losses. However, this assumption could constitute an oversimplification, as losses occur concurrently and can interact with each other, potentially impacting overall performance, all the more in low aspect ratio turbomachinery. The aim of this paper is to investigate the role of interactions between different phenomena in the generation of loss. 3D RANS simulations are run on two simplified representations of a turbine blade channel, a curved duct and a linear cascade, and on a real turbine vane. Several inlet and wall boundary conditions are employed to examine loss-generating phenomena both separately and simultaneously. This approach enables the analysis of where and how interactions occur and quantifies their influence on the overall losses. Losses caused by boundary layer–vortex interactions are found to be highly sensitive to the relative positions of these two phenomena. It was observed that the loss linearity assumption may be acceptable in certain cases, but it is generally inadequate for off-design conditions and twisted annular configurations. Full article

In the Amazon, nearly one million people remain without reliable access to electricity. Moreover, the rural electricity grid is a mostly single-phase, ground-return type, with poor energy quality and high expenses. This study examines very low-head micro-hydropower (MHP) sites in the Amazon, emphasizing the integration of multiple axial-flow turbines. It includes an analysis of flow duration curves and key curves, both upstream and downstream, to design an MHP plant with multiple units targeting maximized energy yield. The presence of multiple turbines is crucial due to the substantial annual flow variation in the Amazon rivers. One contribution of this work is its scalable framework for ultra-low-head and high flow variability in small rivers, which is applicable in similar hydrological configurations, such as those typical of the Amazon. The design applies the minimum pressure coefficient criterion to increase turbine efficiency. Computational Fluid Dynamics (CFD) simulations forecast turbine efficiency and flow behavior. The CFD model is validated using experimental data available in the literature on a similar turbine, which is similarly used in this study for cost reasons, with discrepancies under 5%, demonstrating robust predictions of turbine efficiency and head behavior as a function of flow. This study also explores the implications of including inlet guide vanes (IGVs). We use a case study of a small bridge in Vila do Janari, situated in the southeastern part of Pará state, where heads range from 1.4 to 2.4 m and turbine flow rates span from 0.23 to 0.92 m³/s. The optimal configuration shows the potential to generate 63 MWh/year. Full article

To mitigate the issue of high-pitch natural frequency in V-shaped floating offshore wind turbines (FOWTs), a novel semi-submersible floater design, termed NewSemi, is proposed in this study. The structural performance of the NewSemi floater is compared with that of two existing 5 MW FOWTs, namely, the V-shaped and Braceless. Frequency domain analysis demonstrates that the NewSemi floater exhibits the most favorable response amplitude operator (RAO) in the pitch direction, along with superior damping characteristics. The result reveals a 16.44% reduction in pitch natural frequency compared to the V-shaped floater. Time-domain analysis under extreme conditions reveals 14.6% and 65.2% reductions in mean surge and pitch motions compared to Braceless FOWT, demonstrating enhanced stability. In addition, compared with the V-shaped FOWT, it exhibits smaller standards and deviations in surge and pitch motion, with reductions of 11.3% and 31.9%, respectively. To accommodate the trend toward larger FOWTs, an optimization procedure for scaling up floater designs is developed in this study. Using a differential evolution algorithm, the optimization process adjusts column diameter and spacing while considering motion response and steel usage constraints. The NewSemi floater is successfully scaled from 5 MW to 10 MW, and the effects of this scaling on motion and structural dynamics are examined. Numerical analysis indicates that as turbine size increases, the motion response under extreme sea conditions decreases, while structural dynamic responses, including blade root torque, rotor thrust, tower-base-bending moment and axial force, significantly increase. The maximum values of blade root torque and tower-base-bending moment increase by 10.4 times and 3.95 times in different load cases, respectively, while the mooring forces remain stable. This study offers practical engineering guidance for the design and optimization of next-generation floating wind turbines, enhancing their performance and scalability in offshore wind energy applications. Full article

This review examines various methods for the design and optimization of horizontal-axis hydrokinetic turbines. A detailed analysis is presented of the results from numerical and experimental studies on small axial hydrokinetic turbines optimized through different methodologies. The influence of individual components of the flow passage on the turbine’s efficiency is emphasized. The energy performance of the studied turbines is compared with that of modern commercial hydrokinetic turbines. It is demonstrated that Computational Fluid Dynamics (CFD) can be used to optimize the geometry of the flow passage, achieving a higher power coefficient compared to commercial hydrokinetic turbines. All of this contributes to the future development of more efficient axial hydrokinetic turbines suitable for operation at lower flow velocities. Full article

To meet the increasingly stringent performance indicators of gas turbines, the turbine inlet temperature has increased, and variable geometry turbine technology is widely applied. Therefore, this study developed a quasi-two-dimensional (quasi-2D) method for variable geometry turbine performance considering cooling air mixing based on the elementary blade method and the cooling airflow mixing model. To address the high-dimensional, multi-variable data fitting problem of variable geometry turbines considering the effects of cooling air, this study adopted a BP neural network to further establish a surrogate model for variable geometry turbine performance. A sensitivity analysis of a single-stage turbine was conducted. The variable geometry cooling performance of a single-stage turbine and an E³ five-stage low-pressure air turbine were calculated, and the corresponding surrogate models were established. The relative errors between the calculated mass flow rate and efficiency of the single-stage turbine and the experimental values were no more than 0.70% and 4.44%, respectively; for the five-stage air turbine, the maximum relative errors in mass flow rate and efficiency were no more than 1.67% and 1.385%, respectively. When the throat area of the single-stage turbine nozzle changed by ±30%, the maximum relative errors between the calculated mass flow rate and efficiency and their experimental values were 3.602% and 4.228%, respectively; thus, the determination coefficients of the constructed BP neural network model for the training samples were all greater than 0.999, indicating that the surrogate model has high prediction accuracy and strong generalization ability and can quickly predict variable geometry turbine cooling performance. Full article

A tapered roller bearing (TRB) is a specialized type of bearing with a high load-to-volume ratio, designed to support both radial and axial loads. Lubrication plays a crucial role in TRB operation by reducing friction and dissipating heat generated during rotation. However, it can also negatively impact TRB performance due to the viscous and inertial effects of the lubricant. Extensive research has been conducted to examine the role of lubrication in TRB performance. Lubrication primarily influences the frictional characteristics, thermal behavior, hydraulic losses, dynamic stability, and contact mechanics of TRBs. This paper aims to collect and classify the scientific literature on TRB lubrication based on these key aspects. Specifically, it explores the scope of research on the use of Newtonian and non-Newtonian lubricants in TRBs. Furthermore, this study analyzes research based on TRB size and type, considering both oil and grease as lubricants. The findings indicate that both numerical and experimental studies have been conducted to investigate Newtonian and non-Newtonian lubricants across various TRB sizes and types. However, the results highlight that limited research has focused on non-Newtonian lubricants in TRBs with an Outer Diameter (OD) exceeding 300 mm, i.e., those typically used in wind turbines, industrial gearboxes, and railways. Full article

Wind energy is a vital pillar of modern sustainable power generation, yet wind turbine generators remain vulnerable to incipient inter-turn short-circuit (ITSC) faults in their stator windings. These faults can cause fluctuations in the output voltage, frequency, and power of wind turbines, eventually leading to overheating, equipment damage, and rising maintenance costs if not detected early. Although significant progress has been made in condition monitoring, the current methods still fall short of the robustness required for early fault diagnosis in complex operational settings. To address this gap, this study presents a novel deep learning framework that involves traditional baseline machine-learning algorithms and advanced deep network architectures to diagnose seven distinct ITSC fault types using signals from current, vibration, and axial magnetic flux sensors. Our approach is rigorously evaluated using metrics such as confusion matrices, accuracy, recall, average precision (AP), mean average precision (mAP), hypothesis testing, and feature visualization. The experimental results demonstrate that deep learning models outperform machine learning algorithms in terms of precision and stability, achieving an mAP of 99.25% in fault identification, with three-phase current signals emerging as the most reliable indicator of generator faults compared to vibration and electromagnetic data. It is recommended to combine three-phase current sensors with deep learning frameworks for the precise identification of various types of incipient ITSC faults. This study offers a robust and efficient pipeline for condition monitoring and ITSC fault diagnosis, enabling the intelligent operation of wind turbines and maintenance of their operating states. Ultimately, it contributes to providing a practical way forward in enhancing turbine reliability and lifespan. Full article