Blade Structure Research Articles

Uniformizing the temperature of turbine blades during the heat treatment process from the perspective of radiation energy distribution

Nickel-based single-crystal turbine blades are critical components of jet engines. Due to element segregation and microstructural defects in as-cast blades, vacuum heat treatment is essential. Controlling the blades’ heat treatment temperature is crucial for improving mechanical performance. However, when treating multiple blades simultaneously, large temperature differences often occur, making it challenging to ensure consistent and uniform temperatures. This paper establishes a numerical algorithm that links blade temperature with radiant energy, optimizing blade arrangement to achieve uniform energy distribution and temperature field homogenization. The improved view factor finite element algorithm is more suitable for blade structures. The Particle Swarm Optimization (PSO) and Coordinate Descent (CD) methods were used to solve the optimization function, aiming to minimize the temperature difference among blades. Finite element simulation was utilized to model the temperature field of the blades during radiative heat transfer from heating elements. The PSO and CD optimization methods were employed to find the local optimal solution that minimizes the view factor variance, reducing it from 2.24 before optimization to about 1. Simultaneously, the optimized maximum average temperature difference of the blades was 71.1 °C, approximately 50 % lower than the 138.8 °C before optimization. By comparing the view factor values with the simulated temperature fields, the strong correlation between the view factor and blade temperature was verified. This paper innovatively proposes a numerical method for optimizing blade arrangement to homogenize the temperature field, effectively enhancing temperature consistency during the heat treatment process.

Study on coupled mode flutter parameters of large wind turbine blades

As the size of wind turbine blades increases, the flexibility of the blades increases. In actual operation, airflow flow can cause aerodynamic elastic instability of the blade structure. Long blades may experience coupled mode flutter due to the bending torsion coupling effect, leading to blade failure. Based on Euler Bernoulli beam theory combined with Theodorsen non directional aerodynamic loads, a blade flutter characteristic equation is established through finite element method. Taking NREL 5 MW wind turbine blades as an example, analyze the influence of parameter changes in different regions of the blades on flutter characteristics. Research has found that paramter changes in the tip region of blade have the greatest impact on flutter characteristics. The vibration frequency shows an overall upward trend with the increase of waving stiffness and torsional stiffness. The flutter velocity of the three regions tends to stabilize as the bending stiffness decreases. The blade flutter speed increases with the increase of torsional stiffness. The radius of gyration is inversely proportional to the flutter frequency and flutter velocity. The impact of centroid offset on blade structure flutter frequency is minimal, but the centroid offset in the tip region has a greater impact on flutter velocity. Increasing the torsional frequency can prevent coupled mode flutter and provide a theoretical basis for blade flutter prevention design.

Structural optimization using a genetic algorithm aiming for the minimum mass of vertical axis wind turbines using composite materials

A wind turbine comprises multiple components constructed from diverse materials. This complexity introduces challenges in designing the blade structure. In this study, we developed a structural optimization framework for Vertical Axis Wind Turbines (VAWT). This framework integrates a parametric Finite Element Analysis (FEA) model, which simulates the structure's global behavior, with a Genetic Algorithm (GA) optimization technique that navigates the design domain to identify optimal parameters. The goal is to minimize the mass of VAWT structures while adhering to a suite of complex constraints. This framework quantifies the mass reduction impact attributable to material selection and structural designs. The optimization cases indicate that blades made from Carbon Fiber Reinforced Plastics (CFRP) materials are 47.1 % lighter than those made from Glass Fiber Reinforced Plastics (GFRP), while the structural parts are 44.8 % lighter. This work also provides further recommendations regarding the scale and design of the structures. With the materials and structural design established, future studies can expand to include more load cases and detailed designs of specific components.

Effect of Induction and Blade Elasticity Modelling on Wind Turbine Rotor Performance Predictions

This study investigates the impact of blade induction modelling on the accuracy of wind turbine rotor aeroelastic predictions. It extends the capabilities of AEOLIAN (AErOeLastic sImulAtioN), a Fluid Structure Interaction (FSI) solver based on Blade Element Momentum Theory (BEMT) coupled with a Lumped Mass approach to represent the blade structure. Herein, AEOLIAN’s analytical wake induction engineering model is replaced with the outcomes of a physically-consistent three-dimensional Free-Vortex Wake (FVW) formulation initially employed in AeroROTOR. This versatile aeroelastic simulation tool is implemented within the framework of MATLAB Simulink/Simscape-Multibody©, a modular environment suitable for industry analysts, researchers, and academic users focusing on wind turbine aero-servo-elastic applications. Furthermore, it serves to lay the groundwork for the development of advanced control laws for multi-megawatt rotors, fostering innovation in the design and optimization of the next-generation wind turbines. The presented analyses focus on predicting the aeroelastic behavior of the bottom-fixed NREL 5MW rotor in uniform axial flow over the operating range, complemented by more detailed investigations at the rated condition undergoing inflow with/without wind misalignment (yaw). The study on key performance parameters is conducted by comparing with the higher-fidelity data from available Computational Fluid Dynamics (CFD) and Computational Structural Dynamics (CSD) coupled with CFD.

Co-Ln (Ln = Ce ∼ Yb) bimetal complexes: Syntheses, structures and their applications as supercapacitor anode materials

In this present, 16 Co-Ln (Ln = Ce ∼ Yb) bimetallic complexes (named as complexes #1-#16 and abbreviated as CoLnPda) were synthesized. Among these complexes, complexes #1-#12 were two-dimensional layered, and complexes #13-#16 were three-dimensional block MOFs. Single crystal x-ray diffractometer (SXRD) and x-ray photoelectron spectrometer (XPS) were applied to confirm the components of the complexes and the oxidation state of the central atom. Optical microscopy, powder x-ray diffractometer (PXRD), Fourier transform infrared spectroscopy (FT-IR), and ultraviolet–visible spectrum (Uv–vis) were used to characterize the complexes. Among these 12 kinds of two-dimensional layered complexes, the obtained pure complexes were evaluated by thermo gravimetric analysis (TG) to illustrate their thermal stability. Next, complex #2 (CoPrPda-n) was selected as an example to illustrate the use of such layered complexes as the precursors to prepare the energy storage materials. Under the atmosphere of nitrogen gas flow, the composite with blade structure (C/Pr2O2CO3/CoO/Co) was formed when the precursor was calcined at 800 °C for 2 h. The sample was used as the electrode material of the supercapacitor and when the current density was 2 A·g−1 in 6 M KOH electrolyte, it showed a specific capacity of 1440 F·g−1. The cycle tests showed that the specific capacitance retained well after 2000 cycles at the current density of 20 A·g−1.

Verification of Euler–Bernoulli beam theory model for wind blade structure analysis

This paper presents a computational tool for analyzing the structural response of wind turbine blades using the advanced Euler–Bernoulli Beam theory. The objective is to achieve efficient computation of blade structural response under aerodynamic loading without sacrificing computational accuracy. This study involves the development of a Python-based computer program as a numerical tool, which utilizes inputs such as blade geometry and aerodynamic loading from Blade Element Momentum theory. The program outputs axially varying moments of inertia, spatial deflections of the blade, and stress distributions within the blade. The numerical tool is verified by comparing the results with both analytical solutions and far more time-consuming commercial finite element solvers. One of the key contribution of this research is the application of the polygon algorithm, which efficiently calculates the moments of inertia of web-stiffened turbine blades along the blade length. It is shown herein that this algorithm significantly reduces computational time while maintaining numerical accuracy as compared to the results obtained from commercially available finite element codes. The study confirms that the advanced Euler–Bernoulli beam theory, when combined with the polygon algorithm, is capable of accurately predicting the structural response of cambered and twisted wind turbine blades during the initial design phase.

Influence of Water Flow Speed on the Torque Behaviour of the Hybrid HKT Having Straight and Helical Bladed Savonius Rotor

Flow streams in rivers, canals, and the tail race of a hydropower plant can be transformed into usable kinetic energy with the help of a hydrokinetic turbine. In this work, the torque characteristics of the hybrid turbine having Savonius helical blade angles of 0˚ and 180˚ have been evaluated using a numerical technique. The characteristics of the turbine are driven for the range of water speed of 0.5 to 2.0 m/s and TSR of 0.3 to 1.5. It is observed from numerical analysis that the flow speed of water significantly affects the mean torque and static torque established by the hybrid turbine. The torque developed by the hybrid turbine enhances as water speed increases. However, the structure of the Savonius blade can alter the torque characteristics of the turbine. The mean torque and static torque growth by the hybrid turbine with a Savonius helical blade angle of 0˚ is more optimum than the hybrid turbine with a Savonius helical blade angle of 180˚. Although, the positive magnitude of torque is achieved at every rotor angle over one revolution by introducing a twist angle to the traditional Savonius blade in the hybrid configuration.

Research on Thermocouple Integration Method of Hollow Thin-Walled Turbine Rotor Blade Surface

The hollow thin-walled structure is increasingly used in advanced aero-engine turbine rotor blades, and the traditional surface temperature measurement method based on groove buried couple is no longer applicable. In this paper, a new thermocouple integration method is proposed. The laser additive manufacturing process is used to generate thermocouple embedding channels on the surface of turbine blades. After the thermocouple is embedded, it is pre-fixed, and the thermocouple protection is realized by supersonic flame spraying technology. The strength of the thermocouple integrated structure of the turbine blade is verified by finite element analysis. Based on CFD analysis, the influence of thermocouple integration on the efficiency, pressure ratio and temperature distribution of the turbine blade is studied. The high-speed rotation test shows that the thermocouple integrated structure has high strength and reliability and meets the measurement requirements. This method can provide technical support for the surface temperature measurement of hollow thin-walled turbine rotor blades.

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.

Investigation on Aerodynamic Performance of a Centrifugal Compressor with Leaned and Bowed 3D Blades

The application of centrifugal compressors is extensive in industries such as aerospace and energy. The blade is the primary factor affecting the aerodynamic performance of compressors. In this paper, the aerodynamic performance of a centrifugal compressor with leaned and bowed 3D blades is investigated. The spanwise section profiles of the blade in the circumferential direction are deflected at different angles, resulting in four compressors with distinct leaned and bowed 3D blades based on the original model. There is a significant change in isentropic efficiency of the modified models under design conditions. Specifically, models 1, 3, and 4 experienced an increase of 0.97%, 1.04%, and 0.79%, respectively, while model 2 experienced a decrease of 0.70%. The profile of the blade tip and 50% spanwise section are shifted towards the suction surface, resulting in a geometric structure where the blade is concave towards the pressure surface. This structure gradually lifts the flow from the blade root to the blade tip downstream to the outlet area of the flow channel, reducing the load on the trailing edge of the blade and making the flow more closely aligned with the blade. At the same time, the larger radial velocity gradient near the blade tip suppresses the backflow on the shroud side, making the flow at the impeller outlet more stable. The outlet velocity of the impeller is more evenly distributed along the spanwise and circumferential directions, which improves the flow at the inlet of the diffuser and enhances the efficiency of the diffuser. Due to the high spanwise height of the leading edge of the blade, this bowed blade structure has little effect on the spanwise curvature upstream of the blade, resulting in negligible influence on the flow of the upstream channel.

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.

Research on vibration fatigue behavior of blade structures based on infrared thermography

In recent years, infrared thermography has been widely used in mechanical testing because of its non-contact, rapidity and high accuracy. In order to explore the advantages of infrared thermography in vibration fatigue monitoring of blade structures, the characterization of the vibration fatigue behavior of blade structures is carried out based on infrared thermography with the validation and assistance of laser vibrometry. Firstly, the numerical simulation and experimental analysis were used to determine the size and location of the maximum stress in blade structures. Afterwards, the linear relationship between the stress and amplitude(σν-A curve) of blade structures was calibrated by laser vibrometry, and thus the S-N curve was fitted. Eventually, the heat dissipation law and crack extension process for vibration fatigue of blade structures was analyzed by infrared thermography, and the fatigue limit of the blade structure was predicted by combining infrared thermography and the Luong bilinear method. It is shown that the heat dissipation law and crack extension process for vibration fatigue of blade structures can be effectively analyzed by infrared thermography. Infrared thermography saves some economic and time costs for fatigue limit prediction, and the method is within 2.6% of the results predicted by the Basquin model. This paper provides a certain reference basis for the research methodology for vibration fatigue behavior of blade structures.

Structural analysis and application research for controlled strand length cutting blade of rotary guillotine cutter

In the tobacco processing stage leading to the production of cigarettes, there are strict technical requirements for the structure and proportion of different lengths of cut tobacco following the cutting process. Moreover, the lightweight design of the high-speed rotary-cutting blades is of significant importance during this stage. To better address issues related to the rational design of the blade structure in rotary-cutting cutters and the effective control of size proportion of cut tobacco, this paper establishes a CLSC blade design method featuring concave-convex edges and inter-edge grooves, and provides specific structural schemes. By introducing the structure of the cutting components of the cutter and the cutting process, and by analyzing the differences in layout features between RSEC and CLSC blade structures, as well as their relevance to tobacco cutting and shaping, this paper establishes the installation constraints and mechanical load model for cutter blades under rated conditions. Finite element methods were used to model and analyze both types of cutter blade structures, yielding static and modal analysis data. Furthermore, production verification was conducted on an SD EVO cutter, and data on the rate of different lengths of cut tobacco were obtained. The results show that the mass of the CLSC concave-convex edge cutter blade was reduced by 4.33%, and the static stiffness efficiency was increased by 2.37 times. Although the first-six natural frequencies of the CSLC blade showed degradation in modal analysis, it still met the equipment vibration usage condition. The production verification results indicated that the use of CLSC concave-convex edge cutter blades reduced the long cut rate by 2.48%, increased the medium cut rate by 2.29%, broken cut rate increased by 0.08%, and increased the short cut rate by 0.12%, with an overall reduction in the whole cut rate by 0.19%, achieving the objectives of reducing the long cut rate, controlling the whole cut rate, and not increasing the broken cut rate. The CLSC blades were able to operate continuously, stably, and safely on the rotary-cutting cutter machine. The research presented in this paper can provide a reference for the analysis and design of cutter blade structures in tobacco cutter machines.

The Influence of Blade Structure Optimization on the Hydraulic Performance of Vane Pump

Vane pump has the problems of low pressure reduction efficiency and easy to be stuck at the bottom of the well. In order to solve this problem, the annular pressure reduction downhole tool of vane pump based on eddy current principle is adopted. On the basis of introducing the principle of eddy current hydraulic pressure reduction technology, this paper studies the influence of blade number, blade outlet angle, blade chord height and blade thickness on tool characteristics. The results show that the tool head increases with the increase of blade number, increases first and then decreases with the increase of blade outlet angle, and decreases first and then stabilizes with the increase of blade wall thickness and chord height. The tool efficiency increases with the increase of blade number, decreases with the increase of blade chord height, and decreases with the increase of blade outlet angle to a certain value, which is less sensitive to blade wall thickness. The research results have important guiding significance for the design and structural optimization of blade annular pressure reducing tools.

Correcting Hardening Artifacts of Aero-Engine Blades with an Iterative Linear Fitting Technique Framework.

Aero engines are the key power source for aerospace vehicles. Cermet turbine blades are the guarantee for the new-generation fighters to improve aero-engine overall performance. X-ray non-destructive reconstruction can obtain the internal structure and morphology of cermet turbine blades. However, the beam hardening effect causes artifacts in objects and affects the reconstruction quality, which is an issue that needs to be solved urgently. This study proposes a hardening-correction framework for industrial computed tomography (ICT) images based on iterative linear fitting. First, an iterative binarization was performed to improve the penetration length accuracy of the forward projection. Then, the proposed linear fitting technology combined with the Hermite function model is derived and analyzed to obtain suitable parameters of blade data. Finally, the fitting curves of the blade data, using the proposed method and the traditional polynomial fitting method, were analyzed and compared and were used to correct the engine turbine blade projection data to reconstruct different groups of tomographic images. Different groups of tomographic images were analyzed using three quantitative image quality evaluation indicators. The results show that the root-mean-square error (RMSE) of the tomographic image obtained by the proposed framework is 0.0133, which is lower than that of the compared method. The peak signal-to-noise ratio (PSNR) is 37.7050 dB and the feature structural similarity (FSIM) is 0.9881, which are both higher than that of the compared method. The proposed method improves the hardening-artifact-correction capability and can obtain higher-quality images, which provides new ideas for the development of imaging and detection of new-generation aero-engine turbine blades.

Design theory for vibration characterisation experiments on real turbine blades with underplatform damper

One of the main causes of turbine rotor blade failures is high-frequency fatigue caused by blade resonance, and the vibration of turbine blades can be effectively suppressed through the reasonable design of dry friction damping structure. In order to understand the vibration characteristics of the blade-disc system and to check whether the damping effect meets the technical specifications, it is necessary to design and carry out dry friction damping blade vibration characteristics experiment. This paper takes a certain type of underplatform damped turbine blade in production as an example, and briefly describes the design idea and design process of such blade vibration characteristic experiments under the premise of the experiment blade structure, material and other physical parameters.

Investigations on affinity law under gas–liquid conditions in multistage radial and mixed-flow multiphase pumps

Affinity laws have been widely used in pump design and simulation under high-temperature and corrosive conditions. By applying such laws, it is possible to shorten development cycles and reduce test costs. However, current applications of affinity laws are still limited to liquid conditions. In this paper, expressions for affinity laws and their applicability are investigated for multistage radial and mixed-flow multiphase pumps under gas–liquid conditions. A high-pressure (30 MPa) gas–liquid experimental platform is constructed, and three-stage and 25-stage radial pumps and a 15-stage mixed-flow pump are investigated, with specific speeds of 107 and 216. With gas compressibility taken into account, the gas–liquid two-phase flow rate, head, and power, and the corresponding dimensionless hydraulic coefficients, are defined for multiphase pumps. The deterioration of gas–liquid pressurization performance is found to be divided into three processes with different dynamic mechanisms, corresponding to three flow patterns. The inlet gas volume fraction of pump is used to judge dynamic similarity. At the same inlet gas volume fractions λ1 = λ2, when the gas–liquid flows in two pumps have the same flow pattern, dynamic similarity will be satisfied. The affinity law that is established shows good applicability to the three-stage radial multiphase pump, with goodness of fit R2 larger than 0.9 for the two-phase Ψm–Φm and Πm–Φm performance curves. Finally, experimental results indicate that the affinity law also has good applicability to multiphase pumps with different stage numbers and blade structures under gas–liquid conditions.

Helicopter main rotor FSI analysis using parametric blade model as an application for multidisciplinary optimization

This work is part of a research program aimed at finding new approaches and design solutions for helicopter main rotor modelling using multidisciplinary optimization. It is the fourth stage of an individual research program that includes preliminary tasks such as parametric modelling of a single blade, CFD modelling of a full main rotor for different flight conditions, and preliminary structural modelling of a blade. The main goal of this work is to present the parametric modelling of the rotor blade body and structure as an application for complex simulation. The paper demonstrates the method of advanced analysis of the entire rotor and provides exemplary results obtained from complicated analyses. The analytical foundation for combined fluid-structure analysis is presented. The parametric design method is shown to be applicable for different blade planform shapes and various section airfoils. The blade CFD fluid domain is also prepared using the parametric method, as well as the blade’s inner structure. The simulation parameters from the previous stages of research, which serve as inputs to the FSI analysis, are outlined. These previously obtained parameters are combined and introduced into an FSI simulation to assess their compatibility and applicability. The configuration procedure of the analysis and the boundary conditions are presented. The obtained numerical results are then compared with analytical assumptions. The simulation products, which serve as inputs for further analysis, are presented with graphical representations. The time and memory consumption of the simulation are outlined. The application of the described work in an optimization loop is proposed. As a result of this research, new options for main rotor optimization are developed. The paper demonstrates some crucial possibilities of FSI analysis in the described simulation cases. The use of combined parametric modeling with fluid-structure interaction analysis for different flight conditions is presented as a new perspective for multidisciplinary design optimization of a helicopter rotor system.

A novel twisted rotor blade suitable for high-speed turbomolecular pumps: Numerical modelling and structural optimisation

To meet the urgent need for a new design concept and solve the inaccuracy of existing performance prediction algorithms for high-speed turbomolecular pumps (TMPs), a new algorithm based on a novel twisted rotor blade is proposed. In this algorithm, the blade angle of the turbine rotor row progressively decreases from the root to the tip of the blade tooth. The feasibility and accuracy of the simulation algorithm were verified through experiments. The dependence of the simulation results on the number of simulated molecules was discussed. Both theoretical analysis and simulations confirmed the necessity of setting a twisted rotor blade in the turbine combined blade row. A comparative analysis on the performance of conventional straight-blade and twisted-blade structures based on the first-four stages of turbine combined blade rows of the F-63/55 TMP was conducted. The results indicated that the maximum pumping speed coefficient and maximum compression ratio of the optimised twisted-blade structure increased by 4.59% and 22.26%, respectively. This novel blade structure overcomes the limitations of the conventional straight-blade structure. Progressively decreasing the rotor blade angle from the root to the tip of the blade tooth is beneficial for improving the performance of TMPs. This study provides a new design concept and performance prediction algorithm for the structural optimisation of high-speed TMPs.

Research on the effect of fretting wear on the vibration characteristics of the tenon joint bladed disk

The tenon joint structure is a typical structure of aero-engine bladed disk. Under external excitation, micro-slip inevitably occurs between the tenon and the tenon groove of the blade, which will cause fretting wear on the contact surface. The resonance frequency and margin of the bladed disk structure will change after fretting wear occurs. In this paper, a finite element subprogram is compiled based on the basic principle of Archard wear, which realizes the generation of surface wear morphology and multi-step iterative update of the double-tooth fir-tree joint model under fretting load. The subroutine is used to quantitatively analyze the wear depth distribution of the tenon joint surface under fretting loads. On this basis, the resonance margin and the vibration response characteristics of the bladed disk are quantitatively studied after fretting wear. The research results show that the natural vibration frequency of the bladed disk structure decreases at different wear times. This caused a decrease in the resonance margin of more than 80% of the measuring points. In addition, the resonance response amplitudes all showed an upward trend with the increase of wear depth.