Performance Of Blade Research Articles

An aerodynamic digital twin of real-world leading edge erosion: Acquisition, Generation and 3D CFD

Wind turbine blades face extremely challenging environmental conditions over their operating life-time, that can easily exceed 2 decades. Airborne particles (insects, sand, rain, hail, ice, sea spray etc.) strike the blade leading edge (LE) first and erode or attach to it, roughening its surface. Leading edge roughness (LER) can critically alter the aerodynamic performance of blades, as its aerodynamic impact is strongly coupled to its height with respect to the local boundary layer thickness, which is thinnest around the LE. The actual, detailed topographic manifestation of LER on in-service blades—needed to accurately assess its aerodynamic impact—is highly probabilistic, as it depends on the interaction of multiple stochastic parameters, like the environmental conditions, material composition and production process. Yet little high-resolution topographic LER data of this kind is currently available. This paper details how such data is collected from blades of different turbine manufacturers and processed consistently to build digital twins of the measured LER, that can be analysed aerodynamically using 3D CFD or wind tunnels. Here a special focus lies on how to reconstruct the LER topography and build the computational mesh such that the correct aerodynamic response is observed. For this purpose multiresolution signal decomposition is used to process the topographies and a special meshing procedure established.

Opensource machine learning metamodels for assessing blade performance impairment due to general leading edge degradation

Blades leading edge erosion can significantly reduce annual energy production of wind turbines. Accurate estimates of the resulting blade performance impairment are paramount to predict the resulting energy losses and enable cost-informed decisions on optimal maintenance and operational strategies, maximizing energy production and reducing maintenance costs. Computational Fluid Dynamics (CFD) is a robust approach for predicting the performance losses due to LEE. However, the impact of the damage on blade aerodynamics varies depending on damage pattern, extent and location. Therefore, direct CFD simulation of a sufficiently general set of damaged blades is computationally not viable in industrial applications, since the energy loss assessment needs to be performed for hundreds of turbines at many times of the wind farm operation. To address this issue, previous studies showed how CFD can be used to train machine learning metamodels of the perfomance of damaged blade sections, enabling the definition of multi-fidelity energy loss prediction systems. This study presents improved metamodels, using validated CFD to generate training datasets that cover a more general and wider range of erosion patterns, from low-amplitude roughness to severe grooves. In order to provide the industry with additional erosion geometry-linked tools for estimating energy yield losses, and foster further research and development in this area, the developed meta-models have been made available online with unrestricted access.

Optimization of Savonius rotor blade performance using Taguchi method: Experimental and 3D-CFD approach

The Savonius hydrokinetic turbine (HKT) is both cost-effective and reliable, providing clean energy with minimum environmental impact. The efficiency of the Savonius rotor can be improved by modifying the blade profile to increase the effective torque. However, past research works reported that modifying the blade profile is quite challenging due to small Cp improvement and design constraint. Therefore, the present study proposes a newly developed blade profile blueprint, akin to parameterizable designs such as the modified Bach and Benesh profiles but offering more shape versatility. This new blueprint is optimized with a systematic design of experiment (DOE) using a 3D computational fluid dynamics (CFD) simulation to maximize the Cp. The best design is determined statistically using the Taguchi method and analysis of variance (ANOVA). The optimized rotor profile enhances Cp by approximately 10.9 % compared to the conventional Savonius rotor at the optimal TSR (best Cp = 0.159) and 16.7 % improvement at a higher TSR value of 0.9 (Cp = 0.158). Moreover, the optimized rotor outperforms the Fibonacci rotor (Fibonacci blade profile) by 27 % in terms of efficiency. A thorough CFD analysis suggests that the optimized blade profile has a greater lift generated at the convex side of the advancing blade due to its streamlined shape, which delays the flow separation further up to the root of the blade. The confirmation test (experiment) is also performed to verify the Cp improvement of the optimized rotor, and the results herein concluded that the present CFD prediction is accurate and consistent with the experimental values.

Study on the Pumping Performance and Structure Parameters Optimization of High-Speed Small Compound Molecular Pump.

A molecular pump is the core component of vacuum systems in portable mass spectrometers and other analytical instruments. The forms of the existing molecular pumps mainly are the combinations of vertical bleed and compression channel, which have the shortcomings of heavy mass and large volume, which seriously restricts the application and development of portable mass spectrometers. Aiming at the problems of low strength and insufficient pumping performance under the miniaturization constraints (mass of 1.8 kg; exhaust diameter of 25 mm) of molecular pumps, a compound pump consisting of a horizontal bleed channel and multi-stage spiral compression channel is proposed. The pumping principle of the compound molecular pump is analyzed to obtain its preliminary structural size parameters. The test particle Monte Carlo method is presented for establishing an aerodynamic model for a high-speed small compound molecular pump, which can be used to investigate the pumping performance of bleed blades and compression channels in a thin air environment. On the basis of the aerodynamic model, the NNIA multi-objective optimization algorithm is presented to optimize the structural parameters of the compound molecular pump. After structural parameter optimization, the maximum flow rate and compression ratio of the compound molecular pump are increased by 13.6% and 41.6%, respectively. The experimental results of the pumping performance show that the predicted data of the aerodynamic model are in good agreement with the experimental data, with an error of 12-27%. Namely, the established aerodynamic model has high accuracy and the optimized structural parameters of the compound molecular pump can provide basic conditions for the large-scale application and promotion of portable mass spectrometers.

GA-BP neural network-based nonlinear regression model for machining errors of compressor blades

Given that blade machining errors can substantially degrade aeroengine performance and reliability, there is a critical imperative to implement stringent control over blade machining errors during the manufacturing process. Nevertheless, the prevailing complexity surrounding the numerous machining error types and their obfuscated interrelationships impedes the comprehensive control of blade profile errors. Consequently, unveiling the nonlinear relationships between the distinct machining errors represents a task of paramount importance. To uncover these nonlinear relationships, this work pioneers the application of factor analysis and Genetic Algorithm-optimized BP neural networks to enable nonlinear regression for diverse blade machining errors. Specifically, this paper first constructs an orthogonal factor analysis model to reduce the dimensionality of complex, high-dimensional blade machining error data and extract underlying correlations. This analysis reveals three distinct error groups, each dominated by a latent common factor. Building on these factor analysis outputs, GA-BP neural networks are then leveraged to perform nonlinear regression for intra-group errors. Guided by the Maximal Information Coefficients (MIC) between different errors, we identify control error types within each group to serve as network inputs, with other errors designated as outputs. To prevent overfitting and accelerate convergence of the neural network, Monte Carlo method is used to augment the limited raw error dataset. The augmented data trains the GA-BP network, establishing multivariate nonlinear models with control errors as independent variables and other errors as dependent variables. The model accuracy is validated by a separate validation set. The comparisons between the predicted and true values in the validation set reveal that the relative errors are around 5 %, indicating that the models achieve an accuracy of approximately 95 %. These results demonstrate the satisfactory performance of the established models. Overall, this work elucidates previously unclear relationships between distinct blade machining errors. These new insights establish the foundation for comprehensive error control and will directly benefit blade design, manufacturing, and performance.

Effect of purity on solidification structure and micro-segregation in a nickel-based single crystal superalloy

The purity of nickel-based single crystal alloys plays an important role in the final service performance of turbine blades as it impacts the solidification structure, elemental segregation, and inclusions of castings. The highest purity of superalloys studied before was of altogether around 10 ppm of contents of N and O produced by the triple purification process (VIM+ESR+VAR). However, the impact mechanism still remains controversial, and meanwhile whether a lower content of N and O still keeps the impacts on castings is not yet clear due to the lack of raw materials. A superhigh purity of second generation of nickel-based single crystal superalloy DD98M with the sum of N and O contents as low as 4 ppm (hitherto the highest purity of the superalloy as published), home-produced by electron beam smelting (EBS), was put on focus in this work. The effect of three levels of purity (N-doped, commercial, and EBS, corresponding to 21, 10, and 4 ppm for the sum of N and O contents, respectively) on the microstructure evolution (including primary dendrite arm spacing (PDAS), eutectic, micropores, and γ′ phase) and the solute segregation behavior at dendritic scale and nano scale (γ/γ′ interfaces) were systematically studied and the influencing mechanisms were elucidated. The results show that the PDAS decreased from 406 μm to 322 μm with the reduction of O and N from 21 ppm to 4 ppm, which was irrelevant to precipitation of the nitride or oxide inclusions. Instead, it was due to the decrease of diffusion coefficient D or the increase of equilibrium coefficient k, or the decrease of the critical nucleation supercooling and the incubation time of dendrites. The micro-segregation, the number and volume fraction of eutectic, and the number and voltage percentage of shrinkage pores and gas pores were all greatly decreased with the increase of purity. These changes were closely related to the reduction of PDAS and the reduction of fluidity of the remained liquid in the interdendrites during solidification. The morphology and the size of the γ′ phase were independent from the purity, while the segregation of alloying elements at the γ/γ′ interface changed remarkably with the variation of the purity.

Review of Vibration Analysis and Structural Optimization Research for Rotating Blades

AbstractBlades are important parts of rotating machinery such as marine gas turbines and wind turbines, which are exposed to harsh environments during mechanical operations, including centrifugal loads, aerodynamic forces, or high temperatures. These demanding working conditions considerably influence the dynamic performance of blades. Therefore, because of the challenges posed by blades in complex working environments, in-depth research and optimization are necessary to ensure that blades can operate safely and efficiently, thus guaranteeing the reliability and performance of mechanical systems. Focusing on the vibration analysis of blades in rotating machinery, this paper conducts a comprehensive literature review on the research advancements in vibration modeling and structural optimization of blades under complex operational conditions. First, the paper outlines the development of several modeling theories for rotating blades, including one-dimensional beam theory, two-dimensional plate–shell theory, and three-dimensional solid theory. Second, the research progress in the vibrational analysis of blades under aerodynamic loads, thermal environments, and crack factors is separately discussed. Finally, the developments in rotating blade structural optimization are presented from material optimization and shape optimization perspectives. The methodology and theory of analyzing and optimizing blade vibration characteristics under multifactorial operating conditions are comprehensively outlined, aiming to assist future researchers in proposing more effective and practical approaches for the vibration analysis and optimization of blades.

Modeling of particle erosion of high-pressure turbine based on dynamic mesh method

In this work, we investigate erosion characteristics of a high-pressure turbine by using Oka erosion model coupled with the dynamic mesh method, which allows for the dynamic change of blade profile. The variation of blade profile, material removal and performance degradation during erosion are quantified for the original blade, and the results are compared with those of an optimized blade previously obtained through multi-objective optimization of aerodynamic and erosion resistance performances. It is found that compared with the original blade, the optimized blade is of higher efficiency and lower erosion, suggesting that the previous multi-objective optimization, albeit ignoring the dynamic change of blade profile, still works for the dynamic erosion process. For either blade, the efficiency decreases slowly at first and drops sharply after a period of erosion, because as the erosion proceeds, the regions occupied by the vortex rapidly expand, leading to the blockage of blade passage. The transient erosion characteristics and particle trajectories indicate that the erosion is initially located near the middle and rear of blade on pressure side and the leading edge on suction side; as the erosion progresses, the erosion mainly occurs near the leading edge on pressure side but almost disappears on suction side.

Research on formation mechanism and output effect of wind turbine ice-covered blades

Considering the physical characteristics of wind turbine wing icing, icing synthesis rate, and icing type, we selected the icing type and surface roughness of ice-coated blades as sensitive parameters. The focus of our research was on the equivalent particle roughness height correction model, and we numerically analyzed the two icing processes (frost ice and clear ice) on wind turbine blade surfaces by combining FENSAP-ICE and FLUENT analysis tools. We predicted the ice type on blade surfaces using a multi-time step method and analyzed how variations in icing shape and ice surface roughness affect the aerodynamic performance of blades during frost ice formation or clear ice formation. Our results indicate that differences in blade surface roughness and heat flux lead to disparities in both ice formation rate and shape between frost ice and clear ice. Clear ice has a greater impact on aerodynamics compared to frost ice, while frost ice is significantly influenced by the roughness of its icy surface. These findings can serve as valuable references for wind power operators and manufacturers seeking solutions to issues related to blade surface icing under extremely cold conditions.

Tip gap effects on film cooling performance of a transonic turbine blade with a distinctive coolant supply arrangement

Considered are the influences of tip gap on film cooling performance variations near to and along the tip or end of a turbine blade with a squealer rim contained within a linear cascade with five airfoils. The film coolant is supplied by two plenums which are positioned at forward and aft locations within the blade. The aft blowing ratio varies between 0.88 and 1.48, the forward blowing ratio is set to be approximately constant in the vicinity of 2.75 to 3.0, and a value of about 1.3 is utilized for the ratio of coolant density relative to the main flow density. Measured results include linearly-averaged and spatially-resolved variations of adiabatic effectiveness, which are presented both for the top portion of the pressure surface and end surface of the blade with the squealer rim. Local effectiveness variations along the top pressure side of the blade show significant effectiveness values downstream of aft pressure side hole outlet locations mostly because film lift-off downstream of these holes is less substantial than observed downstream of the forward holes. Spatially-resolved effectiveness data for the end of the blade with a squealer rim show that the largest values of effectiveness are evident near to and immediately downstream of dusting hole outlet locations. Associated linearly-averaged effectiveness data for the tip of the blade recess region with the 1.2 mm tip gap are as much as about two times higher than values for the 2.0 mm tip gap when compared at each surface location. Local and linearly-averaged surface effectiveness variations for the downstream edge region of the blade squealer tip are most strongly influenced by the film cooling holes which are aft and by the dusting hole which is positioned along the tip of the blade rim near the downstream edge. Here, effectiveness magnitudes are also often higher along the downstream edge rim region with the 1.2 mm tip gap, compared to data associated with the 2.0 mm tip gap.

Sand-Laden Wind Erosion Pair Experimental Analysis of Aerodynamic Performance of the Wind Turbine Blades

In the Inner Mongolia region, sand and dust storms are prevalent throughout the year, with sand erosion having a particularly significant impact on the performance of wind turbine blades. To enhance the performance stability of wind turbines and reduce operation and maintenance costs, this study delves into the specific impact of sand-laden wind erosion on the aerodynamic performance of scaled-down wooden wind turbine blades. The experiment conducts vehicle-mounted tests on scaled models of 1.5 MW wind turbine blades that have been eroded by wind-sand flows from different zones, analyzing the changes in aerodynamic performance of wind turbines caused by the erosion. The results indicate that with an increase in the angle of installation, both the overall power output and the wind energy utilization coefficient of the wind turbines show a declining trend. The power outputs of both the partially eroded group and the fully eroded group are unable to reach the rated power level of 100 W. Compared to the uneroded group, the leading-edge eroded group demonstrated higher power output and wind energy utilization coefficients across most wind speed ranges. This finding verifies the possibility that the drag-reducing effect caused by pits from leading-edge erosion has a positive impact on the aerodynamic performance of the blades. It also provides a new research perspective and strong evidence for the study of erosion effects on wind turbine blades and the optimization of their aerodynamic performance.

MODELLING AND 3D PRINTING OF GAS ENGINE TURBINE BLADE

A turbine blade is the individual component which makes the turbine section of a gas turbine. The blades are used for extracting energy from the high temperature, high pressure gas produced by the combustor. This research focuses on the modeling, Analysis and 3D printing of gas engine turbine blades, aiming to enhance efficiency and performance in power generation. Utilizing advanced modelling softwares such as CATIA software, a detailed digital representation of the turbine blade was created, considering the aerodynamic feature. Further, the model is analysed in ANSYS for Subsequently, additive manufacturing techniques were employed to produce physical prototypes using high-strength, heat-resistant materials. The study evaluates the structural integrity, thermal resistance, and overall performance of the 3D-printed turbine blades, comparing them with traditional manufacturing methods. The findings contribute to the advancement of turbine technology, demonstrating the feasibility and benefits of 3D printing in optimizing gas engine turbine blade design for increased efficiency and reliability.

Tidal turbine blade design optimization based on coupled deep learning and blade element momentum theory

The practical design optimization of blade structures is crucial for enhancing the power capture capability of tidal turbines. However, the significant computational costs required for directly optimizing turbine blades through numerical simulations limit the practical application of blade structure optimization. This paper proposes a framework for tidal turbine blade design optimization based on deep learning (DL) and blade element momentum (BEM). This framework employs control points to parameterize the three-dimensional geometric shape of the blades, uses convolutional neural networks to predict the hydrodynamic performance of each hydrofoil section, and couples BEM to forecast the performance of tidal turbine blades. The multi-objective non-dominated sorting genetic algorithm II is employed to optimize the geometric parameters of turbine blades to maximize the power coefficient and minimize the thrust coefficient, aiming to obtain the optimal trade-off solution. The results indicate that the prediction of the DL-BEM model agrees well with experimental data, significantly improving optimization efficiency. The optimized tidal turbine blades exhibit excellent power coefficients and reduced thrust coefficients, achieving a more balanced structural solution. The proposed optimization framework based on DL accurately and rapidly predicts the performance of tidal turbines, facilitating the design optimization of high-performance tidal turbine blades.

Impact of blade shape on the aerodynamic performance and turbulent jet dynamics produced by a ducted rotor

A ducted rotor system was used to produce turbulent jets with a Reynolds number up to 5.97 × 105 and Mach number of 0.222 based on mean streamwise velocity. Three rotors with a diameter of 11.8 cm were manufactured and tested inside a duct with a 1 mm tip clearance at a speed up to 30 000 revolutions per minute (rpm). All rotor blades contain the same aspect ratio of 2.2, a National Advisory Committee for Aeronautics 2410 airfoil, and ideal pitch distribution. However, three different blade planform shapes were used including a rectangular shape with constant chord, trapezoidal shape with a taper ratio of 0.5, and elliptical shape where the trailing edge of the blade is expressed with an elliptical function. The rotor thrust and electric power were measured, and the thrust coefficient and figure of merit was computed. The flow-field produced by the ducted rotors was measured in the near-field using laser Doppler velocimetry techniques. The inflow velocity approximately 3 mm upstream of the rotor blade leading edge was acquired and its significance on blade aerodynamics and performance is analyzed. Time-averaged contours of cross-stream vorticity reveal intense hub and blade tip vortex structures, which are impacted by the shape of the blade, particularly in the blade tip region. Tip vorticity as well as streamwise turbulence intensity and turbulent kinetic energy in this region were mitigated for the rotors with trapezoidal and elliptical blades. However, the turbulent structure of the jet produced by all three rotor blade shapes showed similarity at a mere 2.8 rotor diameters downstream of the rotor. This finding emphasizes the importance of blade design on the near-field dynamics of ducted rotor flows for aircraft propulsion.

Design and optimisation of a 20 MW offshore wind turbine blade

In the global pursuit of Net Zero emissions by 2050, wind turbines have become a leading solution. These renewable energy generators offer a trifecta of benefits, significantly reducing CO2 emissions, minimizing environmental impact, and delivering cost-competitive clean power. However, the key to maximizing their potential lies in the aerodynamic design of the turbine blades. By improving the blade performance, researchers and engineers can significantly increase wind energy capture, propelling wind turbines to the forefront of the global transition to a sustainable future. Higher power generating wind turbines are needed to reach the Net Zero target. By upscaling the “DTU 10 MW Reference Wind Turbine”, this research has achieved an aerodynamically stable 20 MW offshore wind turbine blade design. Variable rotation speed and variable pitch angle configurations have been considered to achieve an ideal power curve. The aerodynamic performance has been evaluated and quantified for a length optimised blade design, wherein the power and thrust have been increased by 80.84% and 88.67%, respectively, at a rated wind velocity of 12 m/s.

Numerical Investigation of the Effect of Trailing Edge Thickness of Simulated Ceramic Matrix Composite Blades on Loss Profiles

Abstract Ceramic matrix composite (CMC) is an enabling material allowing higher turbine inlet temperatures and possibly resulting in better thermal efficiency of gas turbine engines. This is because CMC layers with environmental barrier coating have significantly higher thermal limits (∼1755 K) compared with the more conventional alloyed metallic blades. CMCs possess a complex fabrication process resulting in different geometrical characteristics than metallic blades (e.g., larger trailing edge thickness, large leading-edge curvature, etc.). It is therefore desirable to assess the aerodynamic performance of the CMC blades using experimental and numerical simulations. To investigate, three different CMC blades with varying trailing edge thicknesses were numerically simulated. Both large-eddy simulation with the dynamic subgrid closure as well a recently implemented Reynolds-averaged Navier–Stokes coupled with an intermittency function-based transition model were utilized. Two sets of experimental test points with different Reynolds numbers at a given high-freestream turbulence range (Tu = ∼10–13%) were considered. The predicted pressure loading profiles, total loss distributions, and integrated loss of the three different CMC blades were computed and comparisons against the experimental data are presented herein. It was found that the mixing loss forms a larger proportion of the overall loss as the trailing edge thickness increases.

Numerical investigation on the use of various blade tips for the helicopter's main rotor blade in forward flight regarding aerodynamic performance and HSI noise considerations

The goal of this research is to investigate aerodynamic performance and high-speed impulsive (HSI) noise of various blade tips for the helicopter's main rotor in forward flight. For this purpose, three-dimensional compressible flow field around the rotor blades is numerically simulated by the solution of the unsteady Reynolds averaged Navier-Stokes (URANS) equations with the "SST k-ω" turbulence model. Solution is quantified by the calculation of torque, drag, and thrust coefficients of CQ, CD, CT, and L/D ratio. HSI noise on the rotor plane is assessed by the calculation of sound pressure level at certain points of the flow field using the Ffowcs Williams-Hawking (FW-H) equation. Blade tips are eleven and include anhedral, dihedral, Eagle and combinations of them, and also Blue Edge and rectangular. The combinations are inspired by the tip configurations of the fixed wings. In this regard effects of the tip geometry parameters including curvature and height of its parts have been considered as well. All of the tips are examined for two flight conditions of Caradonna and Tung two-blade rotor with fixed pitch angle and time-varying pitch angles. Based on the present results, it is found that blade tips of dihedral family do not improve the aerodynamic performance of the helicopter blade. Also, addition of anhedral part to the blade tip improves the L/D ratio. According to the present acoustic analysis, it was seen that after the Blue Edge, the Eagle tip stands in order of priority. For the condition of Caradonna and Tung two-blade rotor with tip Mach number of 0.8 and advance ratio of 0.2, HSI noise of the Eagle-tip blade decreases by 2.39 % compared to that of the two-blade rotor with rectangular tip. However, the aerodynamics performance of the Eagle tip is much better than that of the Blue Edge.

Deep learning enhanced fluid-structure interaction analysis for composite tidal turbine blades

A precise and cost-effective prediction tool for fluid-structure interaction (FSI) analysis is crucial for optimizing the structural design of tidal turbine blades. However, the high computational costs associated with fluid dynamic analysis pose a significant challenge, as the current lack of efficient FSI prediction methods hinders the advancement of cutting-edge tidal turbine designs. To address this issue, this paper proposes a novel consolidated framework that integrates deep learning convolutional neural networks (CNN) with blade element momentum (BEM) theory and finite element method (FEM) to perform deformation analysis of turbine blade structures. The proposed CNN-BEM-FEM integrated framework efficiently identifies the geometric features and predicts the hydrodynamic parameters of turbine blades and thus, achieving accurate assessments of the structural behavior of tidal turbines. The study applies two-step verification procedures to validate the prediction accuracy of the CNN-BEM-FEM framework and the result demonstrates excellent agreement with experimental tests for hydrodynamic performance and blade deformation. When compared with the static one-way FSI calculated by Ansys Workbench software, the computational efficiency of CNN-BEM-FEM framework increases by more than 18 times, with discrepancies in blade deformation and equivalent stress calculations generally less than 5 %. By applying the proposed method to predict the FSI performance of tidal turbine blades with various shear web structures, the practical applicability for composite turbine blade design is successfully demonstrated. The results underscore the potential of the CNN-BEM-FEM framework as an efficient and accurate prediction tool for optimizing the structural design of tidal turbine blades.

Unsteady effects of a winglet on the performance of horizontal-axis tidal turbine

A tip winglet can reduce the induced drag and the load fluctuation of a blade, considerably improving the hydrodynamic performance of a tidal turbine. Up to now, there are fewer studies on the unsteady effects of winglets, which limits the application of this design scheme. In this paper, a tidal turbine model is established based on computational fluid dynamics (CFD) and verified by a flume experiment. Then, unsteady effects on the turbine blade are analyzed considering different winglet lengths and cant angles. According to the study, the blade performance is optimal when the winglet cant angle is 45°, with about 11% efficiency improvement and about 8% increase in axial force; as the winglet length increases, the performance tends to further improve. In addition, this study demonstrates that the reason why a winglet can reduce blade load fluctuations is that the winglet takes the tip vortex generation position away from the blade rotation plane, instead of reducing the tip vortex intensity.

Improving thermal performance of turbine blade with combination of circular and oblong fins in a wedge channel: a numerical investigation

Abstract Because of its narrow and aerodynamic design, cooling the trailing edge of a turbine blade offers an essential problem. For the trailing edge internal cooling of gas turbine blades, wedge-shaped channels are used. Pin-fin arrays play a critical role in enhancing heat transmission at the trailing edge of turbine blades. The flow and heat transfer properties of a number of wedge channels with staggered pin-fins of varied shapes are used to develop a design with a more effective heat transfer effect and reduced flow resistance. The present study compares the combination of circular pin fins and oblong pin fins in a wedge duct with a Reynolds number range of 12,000–85,000 and a constant heat flux (surface) of 3280 W/m2 applied to the bottom wall, top wall, and surfaces of the fins. The results indicate that the pressure loss is less in circular fins at the centre and oblong fins side by side, and it is 23.67 % less than circular and oblong fins in opposite positions. The Heat transfer coefficient for circular and oblong fins in opposite positions is 16.72 % higher than circular fins at centre and oblong fin side by side. The thermal performance factor is almost the same for both cases.