Turbine Blades Research Articles

Computational Fluid Dynamics Simulation on Blade Geometry of Novel Axial FlowTurbine for Wave Energy Extraction

Wave energy converters (WECs) utilizing the Oscillating Water Column (OWC) principle have gained prominence for harnessing kinetic energy from ocean waves. This study explores an innovative approach by transforming the pivoting Denniss–Auld turbine blades into a fixed configuration, offering a simplified alternative. The fixed-blade design emulates the maximum pivot points during the OWC’s exhalation and inhalation phases. Traditional Denniss–Auld turbines rely on complex hub systems to enable controllable blade rotation for performance optimization. This research examines the turbine’s efficiency without mechanical actuation. The simulations were conducted using ANSYS™ CFX 2023 R2 to solve the three-dimensional, incompressible, steady-state Reynolds-Averaged Navier–Stokes (RANS) equations, employing the k-ω SST turbulence model to close the system of equations. A grid convergence study was performed, and the numerical results were validated against available experimental and numerical data. An in-depth analysis of the intricate flow field around the turbine blades was also conducted. The modified Denniss–Auld turbine demonstrated a broad operating range, avoiding stalling at high flow coefficients and exhibiting performance characteristics like an impulse turbine. However, the peak efficiency was 12%, significantly lower than that of conventional Denniss–Auld and impulse turbines. Future research should focus on expanding the design space through parametric studies to enhance turbine efficiency and power output.

Simulations With Compressible Multiphase Formulation on Heat Transfer Studies in a Rocket Thrust Chamber With Experimental Validation

Abstract In the combustor for rocket engines, liquid film cooling is a widely adopted technique for restricting the structural components to the acceptable bounds for the successful operation of the propulsion systems. Multiple cooling techniques for thrust chamber walls are favored along with the coolant film in propulsion systems operating at higher chamber pressures by incorporating an ablative cooling mechanism for the nozzle. The adoption of combination will result in challenges in simulation studies due to the presence of multiphase phenomenon in the system. The current article presents the effects of these two cooling methods on a thrust chamber wall studied through compressible multiphase formulations. A majority of the previous studies have used incompressible flow equations to model coolant film behavior and associated heat transfer. The present study utilizes an approach utilizing compressible multiphase flow to simulate the behavior of the compressible hot gas flow and the incompressible coolant liquid film accounting for phase change effects, vapor diffusion into hot gas, radiation effects on coolant surface, liquid entrainment, and blowing effects due to vapor formation at interface. Film-cooling effects on ablative nozzle accounting for pyrolysis phenomenon due to material decomposition governed by Arrhenius expression are also emphasized. The outcome of the numerical model showed good agreement with available test data in literature, and results from the tests done in-house. The model described in the present study was able to support the actual evidence of liquid film cooling being able to preserve the walls of the thrust chamber from severe internal thermal environment and prevent ablation on surface of nozzle.

Thermal and non-thermal fire hazard characteristics of wind turbine blades

Thermal and non-thermal fire hazard characteristics of wind turbine blades

Recovering high-quality glass fibers from end-of-life wind turbine blades through swelling-assisted low-temperature pyrolysis

The recycling of end-of-life wind turbine blades has become a global environmental challenge driven by the rapid growth of wind power. Pyrolysis is a promising method for recovering glass fibers from these discarded blades, but traditional pyrolysis is often operated at high temperatures, which degrades the mechanical properties of recovered fibers. To address this issue, a swelling-assisted pyrolysis method was proposed to recover high-quality glass fibers from end-of-life wind turbine blades at low temperatures. The results confirmed that the decomposition of the resin matrix within the blade was significantly promoted at low temperatures in the swelling-assisted pyrolysis process, achieving a resin decomposition ratio of 76.8 % at 350 °C. This improvement was attributed to enhanced heat transfer and co-pyrolysis with acetic acid. Swelling could physically disrupt the cross-linked structure of the blade, creating a more porous and layered structure, thereby enhancing heat transfer during the pyrolysis process. Simultaneously, the co-pyrolysis with acetic acid could generate hydrogen radicals, which promoted the cracking of macromolecular oligomers into lighter products or gaseous alkanes. Consequently, the formation of pyrolysis char within the solid pyrolysis product was reduced, shortening the oxidation duration to 30 min. In comparison to traditional pyrolysis, the swelling-assisted pyrolysis process effectively suppressed the diffusion of surface defects over the recovered fibers, leading to promising improvements in their flexibility, elasticity, and mechanical properties, with tensile strength notably increased by 27.5 %. These findings provided valuable insights into recovering high-quality glass fibers from end-of-life wind turbine blades.

Analysis of performance improvement methods for offshore wind turbine blades affected by leading edge erosion

Leading edge erosion (LEE) poses greater challenges to the blade design of offshore wind turbines. This paper analyzes the influence of LEE on blade aerodynamic performance and wind turbine load based on high-power offshore wind turbines through the GH-Bladed computing platform. The study found that LEE severely weakens the blade aerodynamic performance, resulting in a lag in the wind turbine reaching its rated power. LEE expands the range of blade surface flow separation, leading to an increase in blade stall risk and a decrease in wind turbine load stability. The promotion of blade aerodynamic performance will cause an increase in blade force, which will strengthen the load level of both the blade and the wind turbine. The optimization of twist angle is an effective method to avoid the loss of power generation of wind turbines under LEE interference, but it is inevitable to cause a decrease in the load stability of wind turbines. Therefore, when the load safety margin of wind turbines is sufficient, adjusting the twist angle is an efficient technique to improve the blade aerodynamic performance and promote the stability of power output, which provides a novel solution for blade design of high-power offshore wind turbines.

Prediction of Steam Turbine Blade Erosion Using Computational Fluid Dynamics Simulation Data and Hierarchical Machine Learning

Abstract The information of the degree of blade erosion is vital for the efficient operation of steam turbines. However, it is nearly impossible to directly measure the degree of blade erosion during operation. Moreover, collecting sufficient data of eroded cases for predictive analysis is challenging. Therefore, this paper proposes a blade erosion prediction method using numerical simulation and machine learning. Pressure data of several blade erosion cases are collected from the numerical turbine simulation. The machine learning approach involves training on collected simulation data to predict the degree of erosion for the first-stage stator (1S) and the first-stage rotor blade (1R) from internal pressure data. The proposed erosion prediction model employs a two-step hierarchical approach. First, the proposed model predicts the 1S erosion degree using the k-nearest neighbor (k-NN) regression. Second, the proposed model estimates the 1R erosion degree with linear regression models. These models are tailored for each of the 1S erosion degrees, utilizing pressure data processed through fast Fourier transform (FFT). The evaluation shows that the proposed method achieves the prediction of the 1S erosion with a mean absolute error (MAE) of 0.000693 mm and the 1R erosion with an MAE of 0.458 mm. The evaluation results indicate that the proposed method can accurately capture the degree of turbine blade erosion from internal pressure data. As a result, the proposed method suggests that the erosion prediction method can be effectively used to determine the optimal timing for maintenance, repair, and overhaul (MRO).

Identification and Localization of Wind Turbine Blade Faults Using Deep Learning

This study addresses the challenges inherent in the maintenance and inspection of wind turbines through the application of deep learning methodologies for fault detection on Wind Turbine Blades (WTBs). Specifically, this research focuses on defect detection on the blades of small-scale WTBs due to the unavailability of commercial wind turbines. This research compared popular object localization architectures, YOLO and Mask R-CNN, to identify the most effective model to detect common WTB defects, including cracks, holes, and erosion. YOLOv9 C emerged as the most effective model, with the highest scores of mAP50 and mAP50-95 of 0.849 and 0.539, respectively. Modifications to Mask R-CNN, specifically integrating a ResNet18-FPN network, reduced computational complexity by 32 layers and achieved a mAP50 of 0.8415. The findings highlight the potential of deep learning and computer vision in improving WTB fault analysis and inspection.

Steady Output Triboelectric-Electromagnetic Hybrid Generator with Variable Drag Turbine Blades for Natural Wind Energy Harvesting.

In recent years, the triboelectric-electromagnetic hybrid generator (TEHG) has been widely studied. However, the problems of unsteady output and high starting wind speed of traditional TEHG in the wind energy environment have not been effectively solved. This work introduces an innovative solution in the form of a steady output triboelectric-electromagnetic hybrid generator (SO-TEHG) with variable drag turbine blades. The SO-TEHG integrates the energy management circuit to output steady electric energy under random wind conditions. In addition, the integration of variable drag turbine blades with the triboelectric nanogenerator (TENG) reduces the wind speed threshold required for SO-TEHG activation. In comparison to the traditional turbine blades, which necessitate a minimum wind speed of 3 m/s, the SO-TEHG's innovative design allows it to commence power generation at a lower 2 m/s wind speed, producing an additional output of 50 V. This enhanced starting capability in mild breezes positions the SO-TEHG as an ideal power source for applications. In practical farmland settings, experimental results conclusively demonstrate the SO-TEHG's ability to successfully activate soil hygrothermographs and hydrogen sensors. As a steady power source driven by gentle winds, the SO-TEHG holds tremendous promise for advancing smart agriculture.

Attention mechanism based on deep learning for defect detection of wind turbine blade via multi-scale features

Abstract An enhanced wind turbine blade surface defect detection algorithm, CGIW-YOLOv8, has been introduced to tackle the problems of uneven distribution of defect samples, confusion between defects and background, and variations in target scales that arise during drone maintenance of wind turbine blades. This algorithm is given based on the YOLOv8 model. Initially, a data augmentation method based on geometric changes and Poisson mixing was used to enrich the dataset and address the problem of uneven sample distribution. Subsequently, the incorporation of the Coordinate Attention (CA) mechanism into the Backbone network improved the feature extraction capability in complex backgrounds. In the Neck, the Reparameterized Generalized Feature Pyramid Network (Rep-GFPN) was introduced as a path fusion strategy and multiple cross-scale connections are fused, which effectively enhances the multi-scale expression ability of the network. Finally, the original CIOU loss function was replaced with Inner-WIoU, which was created by applying the Inner-IoU loss function to the Wise-IoU loss function. It improved detection accuracy while simultaneously speeding up the model's rate of convergence. Experimental results show that the mAP of the method for defect detection reaches 92%, which is 5.5% higher than the baseline network. The detection speed is 120.5 FPS, which meets the needs of real-time detection.

Study on the Properties and Fatigue Characteristics of Glass Fiber Composites Due to Porosity

A study was conducted on the changes in mechanical properties and fatigue failure characteristics due to voids, one of the fabrication defects in composite materials. This study was primarily based on glass fiber fabrics applied to wind turbine blades and their material properties were predicted through micro and meso modeling of composite materials by simulating random defects including voids. As the wind turbine blades become larger, various defects develop. The fundamental changes in the materials’ properties due to voids were predicted through homogenization methods and Representative Volume Element (RVE), and the failure properties were obtained through progressive failure analysis by applying virtual coupons according to ASTM D3090 and ASTM D6641. The progressive failure was identified using the Matzenmiller–Lubliner–Taylor (MLT) failure condition, and the fatigue failure characteristics were assessed through the Tsai–Hill 3D load.

Infusion of Thick-Walled Fiber Metal Laminates with Aligned Holes in the Metal Foils

The rotor blades of wind turbines are becoming increasingly longer, which increases the diameter at the blade connection. Transport problems are the result, as the rotor blades no longer fit under highway bridges, for example. The increase in diameter can be prevented by increasing the bearing strength of the laminate using fiber metal laminates (FMLs). Individual layers of fiber material are replaced by metal foils in FMLs. This work is focused on the infusion of thick-walled FMLs, with infiltration experiments being carried out in-plane and out-of-plane. For the out-of-plane infusion tests, the metal foils are perforated and it is investigated whether the holes should be arranged alternately or aligned in the metal foils. It has been shown that greater laminate thicknesses can be realized with aligned holes. For the determination of voids and dry-spots, the metal foils are treated with a release agent before infusion and after curing the laminate can be demolded ply by ply. The samples made of glass fiber-reinforced plastic (GFRP) and steel/aluminum measure 500 mm by 800 mm by 20 mm.

Exploring the Origin of Exchange Bias in Fe3O4 Films and Its Correlation with Film Thickness and Cooling Field

Exploring the Origin of Exchange Bias in Fe3O4 Films and Its Correlation with Film Thickness and Cooling Field

Film-Cooling Effectiveness on a Turbine Blade Platform With Various Hole Shapes and Layouts

Abstract This paper reports a film-cooling effectiveness experiment on a turbine blade platform that combines two film hole shapes with three layouts. A linear cascade using the pressure-sensitive paint (PSP) technique was employed to measure the adiabatic film effectiveness and discharge coefficients. Three film hole layouts, including two double-row layouts and one dispersed layout, were designed based on the platform configurations. One double-row layout arranges both rows of holes on the pressure side. Another double-row layout arranges one row on the pressure side and one row on the suction side. The dispersed layout was designed with streamwise multirows using the same number of holes. A fan-shaped hole and a diffusion slot hole were tested and compared. The experiments were conducted at a mainstream Reynolds number of 7 × 105, a mainstream turbulence intensity of 3.6%, and a coolant-to-mainstream density ratio of 1.5. The blowing ratio ranged from 0.5 to 2.5. The results demonstrated that regardless of the hole shape, the dispersed layout performed better than the two double-row layouts. However, the effects of the layout on the film effectiveness and discharge coefficients are smaller for the diffusion slot hole. In the three layouts, the film effectiveness of the diffusion slot holes is remarkably greater than that of the fan-shaped holes, and the superiority increases as the blowing ratio increases. In contrast, the superiority of the diffusion slot hole in double-row layouts surpasses that of a dispersed layout.

Considerations for Compressible Film Cooling: A Computational Study of the Effects of Transonic Flows and Varying Mainstream Mach Number

Abstract Recent evidence suggests that film cooling flows with engine-realistic mainstream Mach number have declined performance in comparison to those with conventional low-speed laboratory conditions. Consideration and understanding of these effects are fundamental to improving film cooling research. This computational study investigates the film cooling performance of a 7-7-7 shaped film cooling hole with respect to varying mainstream Mach number, with constant Reynolds number. The cases studied include mainstream Mach numbers from 0.15 to 0.75, with a fixed, engine realistic, hole Reynolds number of Red=10,100. Significant results are then evaluated against varying stagnation temperature ratio and blowing ratio. The results showed that at a blowing ratio of 1.75, the adiabatic effectiveness declines significantly with increasing mainstream Mach number. The decreased performance is due to supersonic flows and shocks in the film cooling hole that disrupt flow in the diffuser section of the hole. These characteristics are observed across all stagnation temperature ratios considered. In addition to these insights, the study discusses the importance of proper thermal scaling and definition of adiabatic effectiveness when operating at high mainstream Mach number. It is demonstrated that the effects of high-speed flow challenge the efficacy of the conventional parameters used to characterize film cooling performance.

Three-dimensional surface temperature measurement using lifetime-based phosphor thermometry

Abstract In this study, we propose a three-dimensional (3D) surface temperature measurement method based on the principle of stereoscopic 3D reconstruction and the dependence of phosphorescence lifetime on temperature. A 385-nm UV(Ultraviolet) light was used as the excitation light, and two high-speed cameras were used as the detectors. The phosphor MFG (Mg4FGeO6: Mn4+) was mixed with the binder HPC and sprayed onto the tested 3D surface. The natural texture generated by the surface roughness of the phosphor coating was used as a feature for cross-correlation calculations. The digital image correlation (DIC) algorithm was used to match these feature positions in the phosphorescent images from the two cameras. The effects of the excitation angle and detecting angle were analyzed. The results indicate that the temperature measurement based on phosphorescent lifetime was not affected by the excitation and detecting angle. The method was validated on a turbine blade as an example of a 3D surface to demonstrate the capability. A comparison of the measurement results with the thermocouples proves that the current method can successfully measure the temperature on 3D surfaces with a maximum difference of 1.63°C. The spatial accuracy of the method was obtained by comparing with the measurement results of a 3D scanner, which shows that the maximum absolute error of the 3D reconstruction was 0.350 mm. The current study proposes a promising 3D surface temperature measurement method, which is expected to be widely used in gas turbine blades, Internal Combustion (IC) engine cylinders, complex curved heat exchangers, and other fields due to its non-contact measurement, low susceptibility to infrared radiation interference, high measurement accuracy, and ability to withstand harsh environments.

Numerical Study on the Impact Pressure of Droplets on Wind Turbine Blades Using a Whirling Arm Rain Erosion Tester

The leading-edge erosion of a wind turbine blade was tested using a whirling arm rain erosion tester, whose rotation rate is considerably higher than that of a full-scale wind turbine owing to the scale effect. In this study, we assessed the impact pressure of droplets on a wet surface of wind turbine blades using numerical simulation of liquid droplet impact by solving the Navier–Stokes equations combined with the volume-of-fluid method. This was conducted in combination with an estimation of liquid film thickness on the rotating blade using an approximate solution of Navier–Stokes equations considering the centrifugal and Coriolis forces. Our study revealed that the impact pressure on the rain erosion tester exceeded that on the wind turbine blade, attributed to the thinner liquid film on the rain erosion tester than on the wind turbine blade caused by the influence of centrifugal and Coriolis forces. This indicates the importance of correcting the influence of liquid-film thickness in estimating the impact velocity of droplets on the wind turbine blade. Furthermore, we demonstrated the correction procedure when estimating the impact velocity of droplets on the wind turbine blade.

The effect of changing the combustion chamber head structure on turbine blades under thermal shock test

When the high-pressure turbine guide blade works in the aero-engine, it is in the complex gas-heat environment of the combustion chamber and the turbine. The temperature distribution and strength of the blade affect the reliability and life of the aero-engine. In order to more accurately analyze the complex flow field aero-thermal parameters between the aero-engine combustion chamber and the turbine, this paper considers the influence of the non-uniform aero-thermal parameters of the combustion chamber outlet on the turbine. Taking the first-stage guide vane of an aero-engine turbine as the research object, the high and low temperature cycle thermal shock test was carried out to obtain the crack location and strength of the turbine guide vane, which provided a certain reference for improving the design of the turbine guide vane. Through the test, it is found that after 750 thermal shock cycles, fatigue cracks appear in four concentrated areas of the blade, which are distributed in the leading edge and trailing edge of the blade respectively. This shows that the temperature at the leading edge and trailing edge of the blade is higher, the heat load is higher, and the risk of damage and ablation is also the highest. Based on the experiment, the cross-component model of the combustion chamber and the blade is established. On this basis, four kinds of swirler structures at the head of the combustion chamber are designed. ANSYS FLUENT software is used to study the unsteady parameters such as the surface temperature of the guide vane under the influence of strong swirling flow. The numerical results show that when the rotation direction of the cyclone is counterclockwise, the temperature of the guide vane wall is more uniform. Compared with the clockwise rotation of the cyclone, the temperature is reduced by about 5 %, and the installation angle of the 50° cyclone blade is better than the installation angle of the 45° blade.

A novel NMF-DiCCA deep learning method and its application in wind turbine blade icing failure identification

Wind turbine blade icing data has the characteristics of multi-source and multi variable. It is difficult to characterize and identify the icing failure with multi-scale features. In this paper, a novel Non-negative Matrix Factorization-Dynamic-inner Canonical Correlation Analysis (NMF-DiCCA )based on GRU and SSAE algorithm is proposed to solve this problem. Firstly, using NMF instead of SVD decomposition method in DiCCA algorithm, the NMF-DiCCA is applied to obtain the dynamic latent variable of time serie. Secondly, the latent structure features S of dynamic latent variable is captured by SSAE. Thirdly, the temporal correlation hidden feature H of dynamic latent variable is extracted by Gated Recurrent Unit (GRU). Finally, the attention weight distribution between latent structure S and temporal correlation hidden feature H is integrated using the attention mechanism, and the fusion feature is reconstructed using the improved SSAE(ISSAE) based on GRU and SSAE.

Exploratory Study on the Application of Graphene Platelet-Reinforced Composite to Wind Turbine Blade

With the growth of the wind energy market and the increase in the size of wind turbines, the demand for advanced composite materials with high strength and low density for wind turbine blades has become imperative. Graphene platelets (GPLs) stand out as highly premising reinforcements due to their exceptional physical properties, resulting in their widespread adoption in the composite industry in recent years. The present study aims to analyze the applicability of a graphene-platelet-reinforced composite (GPLRC) to wind turbine blades in terms of structural performance. A finite element blade model is constructed by referring to the National Renewable Energy Laboratory (NREL) 5 MW wind turbine, and its reliability is verified through a convergence test. The performance of the wind turbine blade is quantitatively examined in terms of the deflection and stress, natural frequencies, and twist angle. The applicability of the GPL-reinforced wind blade is explored through a comparison with wind blades manufactured with glass fiber and carbon nanotubes (CNTs). The comparison indicates that the performance of a wind blade can be remarkably improved by reinforcing with GPLs instead of traditional fillers, and the weight of not only the wind blade itself but also the wind turbine system can be remarkably reduced. The present results can be useful in the development of next-generation high-strength lightweight wind turbine blades.

Development and Measurement of a Very Thick Aerodynamic Profile for Wind Turbine Blades

Development and Measurement of a Very Thick Aerodynamic Profile for Wind Turbine Blades