Performance Of Blade Research Articles

Effect of rock properties on wear and cutting performance of multi blade circular saw with iron based multi-layer diamond segments

This study is an attempt for comprehensive, combining experimental data with advanced analytical techniques and machine learning for a thorough understanding of the factors influencing the wear and cutting performance of multi-blade diamond disc cutters on granite blocks. A series of sawing experiments were performed to evaluate the wear and cutting performance of multi blade diamond disc cutters with varying diameters in the processing of large-sized granite blocks. The multi-layer diamond segments comprising the Iron (Fe) based metal matrix were brazed on the sawing blades. The segment’s wear was studied through micrographs and data obtained from the Field Emission Scanning Electron Microscopy (FESEM) and Energy Dispersive X-ray (EDS). Granite rock samples of nine varieties were tested in the laboratory to determine the quantitative rock parameters. The contribution of individual rock parameters and their combined effects on wear and cutting performance of multi blade saw were correlated using statistical machine learning methods. Moreover, predictive models were developed to estimate the wear and cutting rate based on the most significant rock properties. The point load strength index, uniaxial compressive strength, and deformability, Cerchar abrasivity index, and Cerchar hardness index were found to be the significant variables affecting the sawing performance.

Performance and Damage Study of Composite Rotor Blades under Impact.

A military helicopter is easily attacked by bullets in a battlefield environment. The composite blade is the main lifting surface and control surface of the helicopter. Its ballistic performance directly determines the vulnerability and survivability of the helicopter in the battlefield environment. To study the ballistic performance of the composite helicopter blade, the damage characteristics of the impacted composite rotor blade are obtained by experiments. A numerical simulation model is established by applying Abaqus software to predict the blade ballistic damage. The three-dimensional progressive damage failure model is used to analyze the ballistic damage under the experimental conditions. The effectiveness and accuracy of the numerical simulation model are verified through a comparison with the experimental results. The ballistic damage of composite blades under three experimental conditions was investigated. The results show that the ballistic damage type of composite blade mainly includes delamination, fiber breakage, and foam collapse. The damage to the composite material at the position of bullet incidence is mainly local shear fracture, while the damage to the composite material at the exit position is mainly fiber tensile fracture. The ballistic damage size of the composite blade is closely related to the ballistic position, incident angle, and structure characteristics along the ballistic path. The larger the incident angle, the smaller the ballistic damage size of the blade. The greater the structural stiffness of the structure near the exit, the greater the damage size of the exit. The numerical simulation model presented in this paper can provide a reference for research on the ballistic performance of composite helicopter blades.

DLFSI: A deep learning static fluid-structure interaction model for hydrodynamic-structural optimization of composite tidal turbine blade

Horizontal axis tidal turbines (HATT) conversion of ocean tidal waves into electricity represents a promising source of clean and sustainable energy. However, the widespread adoption of these turbines has been hindered by persistent challenges, primarily stemming from the high costs associated with their construction and maintenance; and efficient conversion of tidal energy. Addressing these challenges is paramount for propelling tidal turbine technology and ensuring its economic viability. This study focuses on the efficient conversion of tidal energy into electricity by optimization of composite material turbine blades which is a complex problem that spans multiple physical domains, including hydrodynamics (the study of water flow) and structural mechanics (the study of material behavior under loads). To tackle these multifaceted challenges, we introduce an innovative DLFSI (Deep learning fluid-structure interaction) model which represents a groundbreaking approach to predict and optimize the hydrodynamic and structural performance of tidal turbine blades. DLFSI leverages the power of convolutional neural networks (CNN) to recognize intricate geometric features of turbine blades rapidly and accurately. By seamlessly integrating the blade element momentum (BEM) theory and finite element method (FEM), the DLFSI model facilitates comprehensive predictions of how composite blades will perform in real-world conditions. With this approach, we have achieved substantial improvements in critical performance metrics such as the power coefficient (a measure of energy conversion efficiency) and the maximum equivalent stress (a key indicator of structural integrity). The innovative DLFSI model presented in this study holds the potential for practical application within the realm of tidal turbine design and is poised to catalyze the sustainable progression of renewable energy technologies.

Simulation Analysis and Experimental Study on Airfoil Optimization of Low-Velocity Turbine

By combining computational fluid dynamics (CFD) and surrogate model method (SMM), the relationship between turbine performance and airfoil shape and flow characteristics at low flow rate is revealed. In this paper, the flow velocity tidal energy airfoil model is designed based on the Kriging model, and the original airfoil with a relative thickness of 12% and a relative curvature of 2.5% is obtained. The parameter optimization is carried out by setting the 4th CST equations through the surrogate model; the maximum lift-drag ratio is the optimization goal, the optimization design variable is 10, the maximum number of iterations is 100, and the maximum number of sub-optimization iterations is 200. The results show that the hydrodynamic performance of the airfoil with thinner thickness and more curvature is better, the maximum thickness part is shifted forward by 4.58%, and the lift-drag ratio is improved by 4.03%. The flow field and the efficiency are more stable, which provides an engineering reference for the optimal design of hydraulic turbine airfoils under low flow velocity. It supplements the research on the performance of turbine blades in low velocity.

Vibration bending fatigue analysis of Ti‐6Al‐4V airfoil blades repaired using additive manufacturing

AbstractThe repair of airfoil blades is an enabling technology to extend the operational life of gas turbine engines. Directed energy deposition (DED) additive manufacturing (AM) provides the ability to add material by melting blown powder using a directed energy source. Seventeen Ti‐6Al‐4V airfoil blades were repaired using DED AM and analyzed to determine what effect the repair will have on the blade performance in high cycle vibration fatigue testing. Volumetric computed tomography (CT) was used to quantify the pores from the AM process. The blades were then subjected to vibrational bending fatigue, used to simulate turbine engine loading conditions, until failure. Only three blades failed in the repaired sections. The identified pore sizes and fatigue stress distribution in the blade were used to suggest that understanding the impact of internal and near surface level pores arising from the AM repair is critical towards the implementation of AM repair in aerospace components under fatigue loading.

Data Analysis of Biomechanical Dynamic Modeling of a Prosthetic Running Blade

This study presents a comprehensive data analysis of the biomechanical performance of prosthetic running blades, utilizing vast data obtained from finite element simulations to elucidate the dynamics of force and energy under operational conditions. The primary focus is on understanding the behavior of these prosthetics at a speed of ‘1 m/s’ and exploring the stability and fluctuations of various force and energy components. Key findings reveal that the kinetic energy of the blade and the total system energy exhibit minimal fluctuations, indicating a stable system behavior under the tested conditions. The normal contact force F c shows a significant dynamic response, while the normal velocity V y maintains a consistent downward trajectory, and the tangential force F x remains essentially constant. Notably, a strong positive correlation between the force components F c and F x is observed, suggesting a synchronous relationship in their magnitudes. Additionally, a moderate negative correlation between the normal velocity V y and the kinetic energies of the blade and system is identified, highlighting intricate interdependencies. This research contributes significantly to the understanding of prosthetic running blades, offering insights crucial for their design and optimization. The correlations and patterns identified underscore the need for further investigation into the causal relationships and practical implications of these dynamics in prosthetic technology.

Sawing Performance of Saw Blade with Viscoelastic Coating Fabricated on Micro-textured Substrate Surface

Sawing Performance of Saw Blade with Viscoelastic Coating Fabricated on Micro-textured Substrate Surface

Numerical modelling and simulation analysis of wind blades: a critical review

Abstract Wind energy has emerged as a promising renewable energy source and wind turbine technology has developed rapidly in recent years. Improved wind turbine performance depends heavily on the design and optimization of wind blades. This work offers a critical evaluation of the state of the art in the field of numerical modelling and simulation analysis, which have become crucial for the design and optimization of wind blades. The evaluation of the literature includes considerable research on the application of numerical methods for the structural and aerodynamic performance of wind blades under various operating situations, as well as for analysis and optimization of wind blades. The article illustrates how numerical techniques can be used to analyse wind blade performance and maximize design efficiency. The study of blade performance under various wind conditions has also been made possible through the use of simulation analysis, thus enhancing the efficiency and dependability of wind turbines. Improvements in wind turbine efficiency and dependability, and ultimately the move towards a more sustainable energy future, will be greatly helpful for the development of numerical modelling and simulation techniques.

Enhancing Epoxy Composite Performance with Carbon Nanofillers: A Solution for Moisture Resistance and Extended Durability in Wind Turbine Blade Structures.

The increasing prominence of glass-fibre-reinforced plastics (GFRPs) in the wind energy industry, due to their exceptional combination of strength, low weight, and resistance to corrosion, makes them an ideal candidate for enhancing the performance and durability of wind turbine blades. The unique properties of GFRPs not only contribute to reduced energy costs through improved aerodynamic efficiency but also extend the operational lifespan of wind turbines. By modifying the epoxy resin with carbon nanofillers, an even higher degree of performance can be achieved. In this work, graphene nanoplatelet (GNP)-enhanced GFRPs are produced through industrial methods (filament winding) and coupons are extracted and tested for their mechanical performance after harsh environmental aging in high temperature and moisture. GNPs enhance the in-plane shear strength of GFRP by 200%, while reducing their water uptake by as much as 40%.

Influence of sintering temperature on dicing performances of metal-bonded diamond blades on sapphire

A novel Ti–Al-Diamond metal matrix composite (MMC) material has been recently developed for fabricating diamond blade that is an indispensable tool for the mechanical dicing of optoelectronic devices. This work aims to achieve a deep understanding of the influence of sintering temperature on the microstructure, the mechanical and frictional properties, and the grinding and dicing performances on hard-and-brittle materials. Firstly, the microstructures and the mechanical and frictional properties of Ti–15Al-25 vol% Diamond metal matrix composites (MMCs) sintered at 750, 850, and 950 °C were investigated. The upraising of sintering temperature results in the enhancement of the diffusion between constitute elements, which consequently increases the hardness and bending strength, but reduces the porosity of sintered MMCs. Then, Ti–15Al-25 vol% Diamond blades were sintered at 750, 850, and 950 °C for dicing of sapphire. The increase in sintering temperature was found to be responsible for the compromise of the self-sharpness capability of diamond blades, resulting in an inferior dicing quality in terms of the chipping size, the kerf width, and the surface roughness, but an improved dicing ratio. Results obtained in this work indicate that sufficient porosity and self-sharpening capability play the most determinant role in satisfying the dicing quality of sapphire.

Simulation of particle deposition on high temperature turbine film cooling blade surface with dynamic mesh morphing

Particles carried by gas and impurities in the operation environment can deposit on turbine blades. The deposition of particles on high temperature turbine blade can seriously damage aerodynamic efficiency and cooling characteristic. Numerical simulations are utilized to investigate particle deposition and the influence of deposition on cooling performance of high temperature turbine blade. The Euler Lagrangian method is chosen to track particles. Firstly, a deposition model is developed to estimate particle deposition by User Defined Function (UDF) of Fluent. On the basis of it, dynamic mesh morphing is used to simulate the blade surface changes caused by deposition. It is mainly explored the differences in the number, thickness, and distribution of particle deposition with different particle sizes and blowing ratios. The effect of particle deposition on film cooling effectiveness is also taken into account. The result shows that particle deposition is more likely to occur at the leading edge of the blade and near the trailing edge of pressure side. Deposition on the pressure side near the leading edge can make a positive effect on cooling effectiveness. For different particle diameters, the deposition number of 10 μm particles is highest, the maximum deposit thickness of 20 μm even exceeds 2 mm. For different blowing ratios, the influence of particle deposition is mainly reflected in the middle of the pressure side. The cooling effectiveness loss can reach 30%.

The Influence of Microstructure Characteristics on Thickness Measurement of TBCs Using Terahertz Time-Domain Spectroscopy

Thermal barrier coatings (TBCs) exhibit excellent thermal insulation capabilities, proving crucial in enhancing the performance of turbine blades. Accurate measurement of TBC thickness is pivotal for the quality control and health monitoring of turbine blades. However, the absence of suitable non-destructive testing (NDT) methods poses a challenge in ensuring precise quality control and health assessment of TBCs. This study investigates the efficacy of terahertz time-domain spectroscopy (THz-TDS) in measuring TBCs thickness, specifically focusing on the microstructure characteristics of the top coat (TC), including grain morphology, internal porosity, surface roughness, and agglomerates. The findings emphasize the significance of grain morphology in determining thickness measurement due to the varied terahertz wave propagation modes. Moreover, the study involved polishing EB-PVD and APS samples to mitigate surface roughness. This process revealed a discernible linear correlation between reduced surface roughness and decreased measurement errors. The slopes of the error reduction curves ranged from 0.59 to 1.7 for EB-PVD and 2.17 to 5.79 for APS samples. Furthermore, the research observed THz light scattering within internal pores, resulting in diminished outgoing energies and subsequent increments in measurement errors.

Numerical study on cooling performance and thermal stress characteristic of an f-class gas turbine stator blade

In this study, a coupled numerical computation approach integrating aerothermal and thermomechanical effects was employed to investigate the cooling efficiency and thermal stress characteristics of gas turbine stator blades. A comprehensive analysis was conducted considering varying turbulence intensities in the coolant flow (spanning from 0.05 to 0.15) and different coolant media configurations, including pure air, dual-medium mixture of air and steam, and pure steam. The distributional traits of cooling efficiency and thermal stress on the stator blade surface under these conditions were meticulously examined. Furthermore, quantitative assessments were performed to determine the extentto which coolant turbulence intensity and coolant type affect the average cooling efficiency and maximum equivalent thermal stress of turbine stator blades, thereby revealing the influence laws. The results reveal that the minimum cooling efficiency on the stator blade surface predominantly occurs at the position of channel 4 on the pressure surface, while the highest cooling efficiency is generally found near the leading edge of the suction surface. Regions of elevated thermal stress were consistently concentrated around the stator blade tip and root areas. When the coolant turbulence intensity increased from 0.05 to 0.15, the average cooling efficiency on the stator blade surface improved by 2.06%, accompanied by a reduction of 1.12% in the maximum thermal stress. In comparison to pure air cooling, dual-medium (air and steam) cooling and pure steam cooling lead to respective enhancements in the average cooling efficiency of approximately 3.3% and 13.2%, with corresponding decreases in the maximum thermal stress of 2.18% and 10.2%.

Experimental assessment of a morphing trailing edge device for wind turbine blade performance improvement

Nowadays, wind energy plays a central role in the renewable energy production, and the optimization of wind turbine performance is the focus of current research studies. In this context, morphing trailing edge system could be a promising solution to enhance wind turbine blades' aerodynamic performance. In this paper, an innovative morphing trailing edge system was designed, developed, and tested to improve the performance of a wind turbine blade airfoil. The trailing edge deformation is electrically operated through piezoelectric actuators and a compliant surface. Wind tunnel tests were performed for the sake of system validation at Reynolds number equal to 1.75×105 and 3.5×105 and an angle of attack ranging from −8° to 8°. The results put in evidence the effectiveness of the proposed morphing trailing edge system to enhance the aerodynamic performance. The trailing edge deformation allows to increase or decrease the lift coefficient. The mean percentage difference of lift coefficient was found equal to −83.6% and 68.4% for an upward and downward deflection, respectively. Meanwhile, the drag coefficient does not have a significant variation. Consequently, the aerodynamic efficiency will be increased or decreased keeping the angle of attack unchanged. The mean percentage difference of efficiency was found equal to −83.2% and 77.5% for an upward and downward deflection, respectively. In this way, it would be possible to optimize wind turbine blades' efficiency and production under different operating conditions.

Overview of a Gas Turbine Blades Power Plant

Power plants that employ turbine blades to generate electricity usually need them to have certain qualities, like high strength, fatigue and corrosion resistance, and temperature tolerance. Super alloys and ceramic composites are common materials used in their construction. Defects or imperfections that might impair the performance and lifetime of turbine blades are a typical issue in their production. Casting flaws, material inclusions, and inadequate cooling during manufacturing are a few examples of these faults. Power plants use strict inspection procedures and quality control measures to reduce these problems and guarantee the dependability of their turbine blades. Improvements in material composition and design are usually required when changing the materials used in turbine blades to boost their effectiveness and performance. Depending on the particular use and intended result, turbine blades can undergo a variety of alterations. Advanced alloy material modifications, coatings, ceramic matrix composites (CMCs), airfoil design optimization, cooling technologies, and tip modifications are a few examples of typical modifications. It's important to note that the specific modifications applied to turbine blades can vary widely depending on the type of turbine (gas, steam, wind, etc.), the operating conditions, and the goals of the modification.

Performance Evaluation of Damaged Blades Using Numerical Simulation and Machine Learning

The formulation of maintenance strategies for gas turbines requires an accurate and rapid assessment of damaged blade performance. Variety and uncertainty in the three-dimensional geometric deformation of gas turbine vanes and blades increase the difficulty of degradation analysis. In this paper, the effects on the aerodynamic performance of partial damage to turbine nozzle guide vanes are investigated experimentally and numerically. A methodology for constructing a deformation–degradation model for high-pressure gas turbine vanes/blades is proposed based on machine learning. A database consisting of 670 numerical simulation results with various deformation patterns is constructed for the vane cascade. A mapping is constructed between the matrices defining geometric deformations and the total pressure loss coefficient of the cascades based on a convolutional neural network model. The accuracy of this deformation–degradation model is verified against experimental results. We find that deformation on the suction side of the blade has the most significant influence on aerodynamic performance. The deformation–degradation model constructed for a specific cascade provides a rapid evaluation of aerodynamic performance based on rough geometrical measurements without additional experiments or numerical simulations, providing a potential tool in the precise repair of gas turbines.

Aerostructural Design Optimization of Wind Turbine Blades

This study presents an aerostructural optimization process for wind turbine blades aimed at enhancing the turbine’s performance. The optimization framework integrates DAFoam as the computational fluid dynamics (CFD) solver, TACS as the finite element method (FEM) solver, Mphys for fluid–structure coupling, and SNOPT as the optimizer within the OpenMDAO framework. The objective is to simultaneously increase the torque generated by the wind turbine while decreasing the mass of the blade, thereby improving its efficiency. The design variables in this optimization process are the blade shape and panel thickness. The aerodynamic objective function is torque, a key performance indicator for wind turbine efficiency. The structural objective function is the blade mass, as reducing mass is essential to minimize material and manufacturing costs. The optimization process utilizes the integrated capabilities of DAFoam, TACS, Mphys, and SNOPT to iteratively evaluate and modify the blade shape and panel thickness. The OpenMDAO framework facilitates seamless communication between the solvers and the optimizer, ensuring a well-coordinated, efficient optimization process. The results of the optimization show a 6.78% increase in torque, which indicates a significant improvement in the wind turbine’s energy production capacity. Additionally, a 4.22% decrease in blade mass demonstrates a successful reduction in material usage without compromising structural integrity. These findings highlight the potential of the proposed aerostructural optimization process to enhance the performance and cost-effectiveness of wind turbine blades, contributing to the advancement of sustainable energy solutions. This work represents the first attempt to implement DAFoam for wind turbine aerostructural design optimization.

Fatigue-Life Estimation of Vertical-Axis Wind Turbine Composite Blades Using Modal Analysis

Abstract Vertical-axis wind turbines (VAWTs) have gained significant impact due to their belief in sustainable wind energy solutions. The primary challenge with VAWTs is complicated structural dynamics and incorporating the optimal composite blade configuration. This article presents an integrated study of the dynamic performance and fatigue-life characteristics of modern VAWT composite blades. Considering the VAWT’s design parameters, the impact of variables such as stress level, loading conditions, fiber type, laminate stacking sequences, and lamina ply angles on the dynamic behavior and fatigue life of VAWTs is investigated. Stress-life curves are generated for glass/carbon-polyester VAWT composite blade configurations. Multi-response optimization using the Taguchi technique combined with the response surface methodology is employed to model, propose, and elect the optimal VAWT composite blade configurations. Finite element analyses (FEAs) are conducted within the solidworks simulation software to simulate and predict the dynamic performance and fatigue-life characteristics of VAWT composite blades. The results show that the composite blades significantly enhance the dynamic and fatigue-life characteristics of VAWTs. Furthermore, a small damage percentage of 2.5% characterized by the FEA for the optimal VAWT composite blade configuration validated the sustainability of the VAWT composite blades in dynamic loading conditions.

Control of shock–boundary layer interaction in a transonic compressor cascade via heat transfer at a low Reynolds number

The shock–boundary layer interaction mechanism of a transonic compressor profile at different Reynolds numbers (Re) was investigated by a three-dimensional Reynolds averaged Navier–Stokes simulation. The reason behind the deterioration of the transonic blade performance at low Re was revealed. Based on this, the mechanism of wall heat transfer regulating the interaction between the shock and the boundary layer on the blade surface was investigated to clarify the impact of wall heat transfer on transonic blade performance. The results show that as the Re decreases, the blade performance deteriorates, and a critical Re exists. When the Re exceeds this critical value, the separation structure on the suction side becomes the dominant factor contributing to losses. At this point, wall heat transfer reduces the gas kinematic viscosity near the wall, weakening the stabilizing effect of turbulence dissipation on the separated shear layer. This accelerates the transition process, consequently reducing the size of the separation bubble and decreasing blade losses. Below the critical Re, the passage normal shock approaches the exit of the blade passage and increases in strength, causing severe separation on the pressure side and resulting in a sharp decline in blade performance. At this stage, wall heat transfer can restore the blade’s boosting capability and weaken the passage normal shock. Although this may deteriorate the performance on the suction side to some extent, the degree of separation on the pressure side is significantly reduced, causing the wake region to narrow and improving blade performance. Comparatively, the control effect is more significant at a low Re (Re = 1.5 × 105), with losses reduced by 40.6 % compared to adiabatic wall conditions.

Durability and Damage Tolerance Analysis Approaches for Wind Turbine Blade Trailing Edge Life Prediction: A Technical Review

The size of wind turbine blades is increasing rapidly, and they are being installed in remote offshore locations. Consequently, it is essential to focus on improving the design and maintenance procedures in the blade industry to meet the growing demand. Of particular concern is the long-term operational performance of the wind turbine blade trailing edge. In this paper, we discuss the application of durability and damage tolerance analysis (DADTA) approaches to trailing edge service life prediction. DADTA is mandated in the aerospace sector to support airworthiness certification and to provide an updated life prediction of the structure based on the different stages of their service life. The DADTA framework has two main parts: durability and damage tolerance analysis. The durability part uses a structural fatigue approach based on a damage accumulation method during the initial design phase to predict the lifespan of a structure without defects. On the other hand, the damage tolerance analysis part uses a fracture mechanics approach and a damage growth method to update the lifespan prediction of a structure during the operation stages. This is achieved by utilizing sensors and inspection data as inputs while the structure is in service. Both these methods are comprehensive and have merits; however, their broad adoption in the wind turbine blade industry is still lacking. The current paper provides an extensive review of these methods and shows how these can be applied to the wind turbine blade industry, specifically for predicting the structural design life of the trailing edge of composite wind turbine blades. The review includes (a) defining wind turbine trailing edge failure modes, (b) trailing edge design procedures, and (c) a detailed discussion of the application of durability and damage tolerance analysis for trailing edge life prediction. Overall, this review paper would be of special interest to blade designers and would guide researchers and engineers interested in life prediction methodologies based on DADTA approaches for wind turbine blades.