Turbine Blades Research Articles

Study on robot trajectory planning and coating thickness prediction for plasma spraying on complex surface

Plasma spraying techniques are commonly employed for the deposition of thermal barrier coatings (TBCs) due to their efficiency and cost-effectiveness. However, ensuring uniform coating thickness and quality on complex free-form surfaces poses significant challenges. This paper investigates the influence of spraying trajectory and related parameters (spraying distance, angle, velocity) on coating thickness distribution, addressing the need for simplified analysis among numerous variables affecting coating quality. Different from the predominantly existing research focusing on flat or rotationally symmetric substrates, this study delves into the planning of spray trajectories for free-form surfaces, which is crucial for industries dealing with complex components, such as turbine blades. Innovative optimization approaches are employed to refine spray trajectories and improve coating consistency. Through theoretical modeling, simulation and experimental validation, the impact of spray parameters on coating thickness was demonstrated. Both the mean and disperssion coefficient errors of the coating thickness, obtained by the theoretical prediction model and the spray experiments, are lower than 10 %. The normal spray trajectory makes the coatings more evenly distributed, and the coating uniformity is at least 50 % higher than that of the codirectional spraying. This research contributes to the optimization of plasma spraying processes, particularly on irregular surfaces, thereby facilitating the development of high-performance TBCs for industrial applications.

DCW-YOLO: An Improved Method for Surface Damage Detection of Wind Turbine Blades

Wind turbine blades (WTBs) are prone to damage from their working environment, including surface peeling and cracks. Early and effective detection of surface defects on WTBs can avoid complex and costly repairs and serious safety hazards. Traditional object detection methods have disadvantages of insufficient detection capabilities, extended model inference times, low recognition accuracy for small objects, and elongated strip defects within WTB datasets. In light of these challenges, a novel model named DCW-YOLO for surface damage detection of WTBs is proposed in this research, which leverages image data collected by unmanned aerial vehicles (UAVs) and the YOLOv8 algorithm for image analysis. Firstly, Dynamic Separable Convolution (DSConv) is introduced into the C2f module of YOLOv8, allowing the model to more effectively focus on the geometric structural details associated with damage on WTBs. Secondly, the upsampling method is replaced with the content-aware reassembly of features (CARAFE), which significantly minimizes the degradation of image characteristics throughout the upsampling process and boosts the network’s ability to extract features. Finally, the loss function is substituted with the WIoU (Wise-IoU) strategy. This strategy allows for a more accurate regression of the target bounding boxes and helps to improve the reliability in the localization of WTBs damages, especially for low-quality examples. This model demonstrates a notable superiority in surface damage detection of WTBs compared to the original YOLOv8n and has achieved a substantial improvement in the mAP@0.5 metric, rising from 91.4% to 93.8%. Furthermore, in the more rigorous mAP@0.5–0.95 metric, it has also seen an increase from 68.9% to 71.2%.

Bayesian Inference for the Calibration of Progressive Damage Model of Dovetail Specimens from Laminated Composite Fan Blade

Abstract Composite fan blades are the preferred alternative for the fan stage of most advanced high bypass ratio turbofan engines. The ability of the dovetail to safely bear this load is one of the key points of the multi-level “test pyramid” approach of compliance demonstration for special airworthiness regulation. Debonding between adjacent layers is the main damage mode of laminated composite fan blades. However, there is difficulty in measuring the as manufactured interlaminar mechanical properties used in finite element models. In this study, tensile loading was applied to simulate the interacting centrifugal force and capture mixed mode damage evolution. Structural responses and material damages were calibrated with measured tensile loads through Bayesian inversion. Posterior probability distributions of maximum interface tractions and contact stresses were solved using Markov chain Monte Carlo sampler. Results indicated the two bilinear cohesive material models had a capacity of predicting empirical means of longitudinal reaction forces as that in test considering additional discrepancy term (0.035 kN and 0.96 kN respectively), while they made an significant impact on the prediction of tensile load history especially when two delamination cracks initiated and propagated. Interface elements provided a higher matching quality in predicting loading history and capturing damage mechanism in association with in-plane progressive damage analysis. This calibrated parameter set could be functioned as benchmark in numerically determining the ultimate tensile load of dovetail elements and reducing the necessary number of physical tests at elemental length level.

Utilization of High-Temperature miniaturized testing to Assist in life management for gas turbine Blades: An Overview

Safely operating gas turbine blades in aero-engines or industrial gas turbines under severe thermo-mechanical conditions always poses a continuous challenge. There is an urgent need for more reliable life prediction tools, necessitating earlier and more rigorous assessments of in-service damage. This paper introduces a systematic examination of high-temperature miniature specimen testing method within a practical life management framework. To improve current practices in assessing the condition of service-aged gas turbine blades, a proactive utilization of miniature specimen testing is recommended for early in-service assessment within the component lifecycle and integrated into a comprehensive life assessment/management framework. The paper outlines a structured approach to life management, combining miniature specimen sampling and creep and fatigue testing methods. This forms the basis for a novel, holistic life assessment methodology, which is proposed in this paper, incorporating the innovative use of high-temperature miniature specimen testing.

Acoustic emission data analytics on delamination growth in a wind turbine blade under full-scale cyclic testing

This study investigates Acoustic Emission (AE) measurement data collected in an experiment where fatigue loading tests were carried out on a 14.3-meter full-scale composite wind turbine blade in a test facility. Artificial defects were embedded in the blade and these defects initiate damage growth in four different areas of the blade. Statistical algorithms and techniques were applied to the acoustic emission data to understand the growth of the damages and to identify possible fracture mechanisms. In composite materials, the different types of failure, such as micro-cracking, delamination, matrix cracking, etc. will release AE waveforms with a continuum of frequencies in different ranges. These frequency ranges will be used in the interpretation of the AE data. The AE parameters, i.e., energy and frequency, are used to show a steady damage growth and structural failure of the blade. These parameters, combined with AE amplitude probability distributions, can be used to monitor the structural health of wind turbine blades. This study provides new insights into the acoustic emission characteristics of a composite structure rather than material coupons.

Optimization and mechanistic analysis of the configurational parameters of a serrated trench for improving film cooling performance

Combinations of trench and holes in film cooling design for turbine blades have been suggested recently. In this work, structural optimization is performed for one of our previously proposed serrated trenches. Geometric parameters including serrated angle, width, and height of the trench, which are the key factors affecting the flow and cooling characteristics, are optimized. The relative area-averaged cooling effectiveness, the relative pressure drop coefficient, and the performance evaluation criterion (PEC) are the optimizing objectives. The multi-objective genetic algorithm is employed as the search strategy to achieve PEC maximization at blowing ratios in the range of 0.5–2.0. The individual variations of each parameter are studied by controlling the variables using the response surface method. It shows that the trench height is the most influential factor on flow and heat transfer; while the trench serrated angle mainly affects the heat transfer; and the trench width has a weak effect on both, depending on the blowing ratio. To achieve maximum PEC, the trench height needs to enlarge with the increase in blowing ratio, while contrary to this, the trench width needs to increase under low blowing ratios and decrease under high blowing ratios, and the optimum trench serrated angle is within the range of 80°–85° at all blowing ratios. The optimum geometry reduces the pressure loss while improves the cooling effectiveness by 8.43 %–17.97 % compared to the baseline trench. This work is instructive for the design and application of practical structures for blade cooling.

Improving the Quality of Heat Treatment Using Microwave Heating of Products with a Complex Profile of Hardened Surfaces

The current article provides the results of the study on the improving the procedure of induction heating of products with a curvilinear surface profile by hardening of steam turbine blades surface with a complex helical shape and requiring protection against erosive wear [9, 10] using a universal microwave heating device. A principally new device that uses the effect of the magnetic field's force action has been developed and constructed. That makes possible to provide a high-quality strengthening of product surfaces regardless of their geometric configuration and size. The advantages of thermal treatment technology on such device are substantiated based on the results of metallographic, X-ray structural, and hardness analysis.

Enhancing wind turbine load response tool through geometric non-linearities correction: Case study on DEFlex and design load comparison

This paper introduces a rapid correction technique applied in DEFlex, Ørsted’s in-house aero-servo-hydro-elastic solver for offshore wind turbines. The technique addresses geometric non-linearities from large wind turbine blade deflections, focusing specifically on correcting the angle of attack for torsional deflections. To assess the implementation, comparisons were made with the literature and HAWC2, using the IEA 15-MW wind turbine blade subjected to static and simplified dynamic loading. Additionally, simulations of normal operation scenarios, both with and without turbulence, were performed on a real wind turbine exceeding 10 MW rated power. The results were compared with Siemens Gamesa Renewable Energys tool BHawC, which utilizes a co-rotational formulation for capturing large blade deflections. The findings reveal that coupling DEFlex with the correction method accurately captures the angle of attack dynamics and significantly improves the agreement of fatigue loads.

Thermal performance of teardrop pin fins and zig zag ribs in a wedge channel

Abstract Aviation, marine propulsion, and power generation employ gas turbine engines extensively. The combustion process’s high temperatures make gas turbine engine development difficult. For safe turbine blade operation, internal cooling is essential. Ribs, pin-fins, and impinging jets are just examples of the several different types of structures that are typically included in internal cooling systems. The present study investigates the effect of rib placed in between the pin fins in a wedge channel. Nine rib configurations along with base line model without ribs are employed in this study. The SST k-omega turbulence model was employed to simulate the flow field and heat transfer of each case using the commercial software ANSYS Fluent. The investigation demonstrated that the heat transfer distribution and flow field in pin-fin arrays were substantially influenced by the ribs-induced secondary flows, particularly in the spanwise direction, which resulted in a significant heat transfer variation. In comparison to other configurations, the 4H4L rib configuration exhibits the highest thermal performance factor, surpassing the baseline by approximately 16.6 %.

Large eddy simulation of in-hole blockage effects on cooling performance of fan-shaped holes

Film-cooling and thermal barrier coating approaches are commonly used in gas turbines to protect the turbine parts from the high-temperature flow of gases. However, one drawback of this method is that the coatings can partially obstruct the cooling hole exit on the turbine blade surfaces, resulting in reduced cooling performance. Therefore, this study aimed to investigate the effects of in-hole blockage thickness on cooling effectiveness and flow characteristics of fan-shaped holes using large eddy simulations (LES). A laidback fan-shaped hole located on a flat plate was the reference cooling hole. Numerical simulations were conducted for two different blocked cooling hole configurations with various blockage thicknesses (t/D = 0.5 and 0.9) at three different blowing ratios (0.5, 1.0, and 2.0). The cooling effectiveness computed by the LES method was validated for both unblocked and blocked cooling holes, and the results were compared to the experiments at various blowing ratios. It was revealed that an increase in blockage thickness had a significant impact on the area-averaged cooling effectiveness, particularly at high blowing ratios. The overall area-averaged cooling effectiveness for the t/D = 0.9 case was approximately 75 % lower than that of the unblocked cooling hole. Moreover, assessment of the instantaneous velocity field inside the hole over time revealed that larger blockage thicknesses resulted in greater velocity fluctuations and a more unsteady flow.

Finite element analysis of thermal barrier properties under relevance vector machine in coated pistons and blades

Internal Combustion (IC) engines require Thermal Barrier Coatings (TBCs) to preserve their effectiveness and performance. By coating engine parts with TBCs, thermal fatigue and environmental heat loss may be minimised. To reduce heat loss in IC engines during the combustion stage, piston thermal barrier coating is extremely beneficial. Additionally, it is well known that power plants with higher energy efficiency tend to operate their gas turbines at higher operating temperatures. To produce TBCs for the thermal design of gas turbines and diesel engines with higher performance, an in-depth study on the thermophysical properties of TBCs is required. This article presents an experimental investigation into the combined effect of gas turbine blades and diesel engine pistons coated with a heat barrier, utilising two distinct Thermal Barrier Coatings. Initially, numerical calculations are used to assess the wall heat transfer model’s ability to control temperature and density. The piston and blade top surfaces received plasma-sprayed, Yttria-Stabilised Zirconia (YSZ) with different material combinations on the piston and blades are evaluated. The Finite Element Method is developed for the coating of the ideal thickness to analyse the failure mechanism of the TBC sample. To evaluate the fatigue residual lifespan of TBC pistons, as well as blades in high-power engines, the authors also created a relevant vector Machine-based lifetime prediction model. The CO, HC and NOx emissions, as well as the fuel depletion and braking thermal efficiency, are used to calculate the performance analysis of the coated piston and blades. The results demonstrated improved thermal process endurance and decreased thermal conductivity by 28% when compared to YSZ using the RVM method respectively.

Drone-based inspection of wind turbine blades: a comparative study of deep learning models

Maintaining wind turbine blades is a challenging task, often marked by high costs, safety risks, time inefficiency, and the possibility of incorrect diagnosis. A promising approach to support preventive maintenance involves the use of drones and deep learning for inspection and early fault detection. This paper offers a comparative study of five advanced deep learning models: Residual Networks (ResNet), Inception Networks (InceptionV3), YOLO (You Only Look Once), EfficientNet, and Vision Transformers (ViTs) applied to the DTU Drone Inspection Images of Wind Turbine dataset. The objective is to determine the most effective model for detecting defects in wind turbine blades, which is critical for ensuring the efficiency and safety of wind energy systems. The models were assessed using key performance metrics, such as accuracy, precision, recall, F1-score, and inference time. EfficientNet emerged as the top performer with the highest accuracy and balanced efficiency, while YOLO demonstrated the fastest inference time, making it ideal for real-time applications. ResNet and InceptionV3 also performed well, particularly in detecting subtle defects, whereas ViTs showed strong capabilities in capturing complex global features despite longer processing times. The findings provide valuable insights for selecting appropriate deep learning models in drone-based wind turbine inspections, contributing to more effective and reliable maintenance practices.

Failure assessment of braided ceramic matrix composite dovetail turbine blade under thermo-mechanical load

Failure assessment of braided ceramic matrix composite dovetail turbine blade under thermo-mechanical load

Investigation of temperature assisted corrosion failure of an aircraft turbine blade

In this study, the root cause of a recurring corrosion problem at the tip of an internally cooled high-pressure turbine blade (HPT) of a turbofan engine was investigated. A two-pronged strategy was utilized involving (i) experimental techniques to identify the blade material and corrosion products, and (ii) computational methods to analyze the fluid flow over the blade. In the experimental thrust, an array of techniques was employed to determine the chemical composition, microstructure, corrosion products and microhardness values while the airflow, pressure distribution and thermal profile over the blade were found through computational paradigms. The blade was a Ni-based superalloy containing typical gamma (γ) and gamma prime (γ′) phases, with an average microhardness value of 389 HV at room temperature. SEM analysis of the corroded area revealed oxides of iron, calcium, magnesium, aluminium, and silicon (FCMAS) most of which were not part of the base alloy. To determine the temperature profile and pressure distribution on the blade, a conjugate heat transfer analysis using Ansys CFX was conducted. A combination of experimental data from the engine ground running test station and analytical equations was used to find the required boundary conditions for the computational analysis. Pressure distribution over the entire blade was found which showed higher flow velocities and cross flows at the blade tip which potentially cause erosion at that region in the presence of impurities in the incoming air. Temperature distribution over the entire blade was also obtained, and it was found that the highest temperatures for the internally cooled blade occurred at the tip region which were in the range of ∼1060 °C–1250 °C (average ∼1114 °C). The temperature on the tip was high enough to cause the melting of the impurities that ingress the coating and cause its degradation during thermal cycling. This exposes the base alloy to FCMAS and causes corrosion. These high temperatures (1060–1250 °C) also induced phase transformation and increased the brittleness (∼22 % increase in hardness) which aggravated the presence of corrosion and resulted in crack formation and blade rejection.

Fatigue Characteristics Analysis of Carbon Fiber Laminates with Multiple Initial Cracks

In the entire wind turbine system, the blade acts as the central load-bearing element, with its stability and reliability being essential for the safe and effective operation of the wind power unit. Carbon fiber, known for its high strength-to-weight ratio, high modulus, and lightweight characteristics, is extensively utilized in blade manufacturing due to its superior attributes. Despite these advantages, carbon fiber composites are frequently subjected to cyclic loading, which often results in fatigue issues. The presence of internal manufacturing defects further intensifies these fatigue challenges. Considering this, the current study focuses on carbon fiber composites with multiple pre-existing cracks, conducting both static and fatigue experiments by varying the crack length, the angle between cracks, and the distance among them to understand their influence on the fatigue life under various conditions. Furthermore, this study leverages the advantages of Paris theory combined with the Extended Finite Element Method (XFEM) to simulate cracks of arbitrary shapes, introducing a fatigue simulation method for carbon fiber composite laminates with multiple cracks to analyze their fatigue characteristics. Concurrently, the Particle Swarm Optimization (PSO) algorithm is employed to determine the optimal weight configuration, and the Backpropagation neural network (BP) is used to train and adjust the weights and thresholds to minimize network errors. Building on this foundation, a surrogate model for predicting the fatigue life of carbon fiber composite laminates with multiple cracks under conditions of physical parameter uncertainty has been constructed, achieving modeling and assessment of fatigue reliability. This research offers theoretical insights and methodological guidance for the utilization of carbon fiber-reinforced composites in wind turbine blade applications.

Fatigue damage mechanics approach to predict the end of incubation and breakthrough of leading edge protection coatings for wind turbine blades

The state of the surface of the leading edge of wind turbine blades is important for optimal aerodynamic performance. Rain erosion leads to damage and roughness on the leading edge. In this study, we present an approach to predict the level of roughness of the leading edge based on fatigue damage accumulation due to impacts of rain droplets. Impact simulations of droplets on the protective coating layer are coupled with rain erosion test data and fatigue S-N curves. Fatigue damage values are then related to surface roughness levels. An approach to extract S-N curve parameters from a rain erosion test and then make predictions for other coatings based only on the output of impact simulations is presented and tested against test data. Both the end of incubation and coating breakthrough times are predicted with this approach. Stress, strain and energy density values were used as fatigue damage indicators and the respective predictions were compared to each other. It was found that the maximum principal strain gave the best predictions and matched the experimental trends.

Comparison of Ingestion of Different Size Hard and Soft Bodies Into a Representative Fan Assembly Model

Abstract Foreign matter ingestion into a jet engine is a significant hazard to the safety of aircraft. While soft body ingestions (i.e., bird or ice ingestions) have been extensively researched, the threat posed by uncrewed aircraft systems (UASs) is a more recent concern due to their recent rise in popularity and has not been thoroughly studied. To better understand the damage caused by UAS ingestions, it is crucial to examine the resulting ingestion damage in comparison to birds of similar mass. This analysis is an essential initial step in determining how previous knowledge regarding soft body ingestions can relate to this new threat. To properly analyze these ingestions, development of a model that accurately represents a fan assembly is essential. This model should include a fan, as well as representative boundary conditions for the ingestion, such as blade retention systems, nose cone, casing, and shaft. Items that are analyzed during the ingestion include the overall damage to the fan blades, average and peak forces imparted on the retention systems, impact loads with the casing, and transient loads due to impact on the shaft. The foreign object models used were experimentally validated at their nominal sizes to increase confidence in the results. Comparison of the effects of ingestion of UAS and birds of difference mass into the representative fan model are presented and discussed to gain a better understanding of the differences between soft and hard body ingestion.

Impact of internal lattice structures on the weight and natural frequencies of a low pressure turbine blade

Vibration characteristics play a crucial role in the overall performance of Low-pressure (LP) turbine blades and different techniques are developed to enhance vibrational response by increasing natural frequencies. The present analysis aims to develop a new technique based on the investigation of improvement in natural frequencies and mass reduction of a topology-optimized blade design through location-based integration of lattice structures inside the blades. FE models are developed for three different lattice locations based on mode shape behavior obtained through modal analysis of two different nickel-based alloys at stressed and unstressed conditions. The results show that the internal BCC lattice at specific locations showed better vibrational characteristics compared to other incorporated lattice structures, and validates the location-based integration scheme for enhancement of natural frequencies and reduced mass in applied conditions. By this method, 5.7% mass reduction was achieved from an already 35% mass-reduced blade along with enhancement in the first and second natural frequencies by 8.2% and 5.9% respectively when unstressed. At stressed condition, the natural frequencies increased by ≈7.7% and ≈6.6%.

Fatigue fracture mechanism and life assessment for irregular film cooling hole structures in Ni-based single crystal turbine blades

Film cooling holes are the main cooling structures in nickel-based single-crystal cooling turbine blades. To evaluate the low-cycle fatigue life of irregular gas film holes, nine types of Ni-based single-crystal flat-plate test pieces with irregular film cooling holes of different shapes were designed in this study. Fatigue tests were performed at high temperature (850 ℃) and the multiscale fracture mechanisms of the samples analyzed in detail. The stress–strain field around the irregular film cooling holes was analyzed based on crystal plasticity theory using the finite element method. Three life prediction models based on the Coffin–Manson–Basquin formula, maximum principal strain, and crystal plasticity theory were proposed to predict the fatigue life of irregular film-cooled pore structures. The predicted results are all within the double-error band.

Experimental study and life prediction for aero-engine turbine blade considering creep-fatigue interaction effect

As an important failure form of the turbine blade, creep-fatigue interaction damage affects the safe operation and maintenance strategy of aero-engine, and has been the focus of scientific research and the academic community. Firstly, based on the Kachanov-Rabotnov-Lemaitre continuum damage mechanics theory and the nonlinear symmetry of creep damage and fatigue damage, a creep-fatigue life prediction model is constructed considering the interaction effect in this paper. Then, based on the thermal-fluid–solid multi-physical field coupling numerical simulation of the turbine blade, the equivalent method of creep-fatigue load spectrum was explored according to the equal damage criterion and linear damage rule, and the creep-fatigue interaction test of smooth samples of the blade material was conducted to analyze the creep-fatigue fracture morphology. Finally, the stress term in the creep-fatigue life prediction model of blade material is modified by the correction factor α, and the modified creep-fatigue life prediction model of the turbine blade is constructed considering the interaction effect. The results show that the modified creep-fatigue life prediction model considering the interaction effect has a high life prediction ability with an error of 3.9%. The above research has important scientific research value for the life extension design of turbine blades and the improvement of aero-engine maintenance strategy.