Geometric Effects of Thermal Barrier Coating Damage on Turbine Blade Temperatures

Thermal barrier coatings (TBC) found on turbine blades are a key element in the performance and reliability of modern gas turbines. TBC reduces the heat transfer into turbine blades by introducing an additional surface thermal resistance; consequently allowing for higher gas temperatures. During the service life of the blades, the TBC surface may be damaged due to manufacturing imperfections, handling damage, service spalling, or service impact damage, producing chips in the coating. While an increase in aerofoil temperature is expected, it is unknown to what degree the blade will be affected and what parameters of the chip shape affect this result. During routine inspections, the severity of the chipping will often fall to the discretion of the inspecting engineer. Without a quantitative understanding of the flow and heat transfer around these chips, there is potential for premature removal or possible blade failure if left to operate. The goal of this preliminary study is to identify the major driving parameters that lead to the increase in metal temperature when TBC is damaged, such that more quantitative estimates of blade life and refurbishing needs can be made. A two-dimensional computational Conjugate Heat Transfer model was developed; fully resolving the hot gas path and TBC, bond-coat, and super alloy solids. Representative convective conditions were applied to the cold side to emulate the characteristics of a cooled turbine blade. The hot gas path properties included an inlet temperature of 1600 K with varying Mach numbers of 0.30, 0.59, and 0.80 and Reynolds number of 5.1×105, 7.0×105, and 9.0×105 as referenced from the leading edge of the model. The cold side was given a coolant temperature of 750 K and a heat transfer coefficient of 1500 W/m2*K. The assigned thermal conductivities of the TBC, bond-coat, and metal alloys were 0.7 W/m*K, 7.0 W/m*K, and 11.0 W/m*K, respectively, and layer thicknesses of 0.50 mm, 0.25 mm, and 1.50 mm, respectively. A flat plate model without the presence of the chip was first evaluated to provide a basis of validation by comparison to existing correlations. Comparing heat transfer coefficients, the flat plate model matched within uncertainty to the Chilton-Colburn analogy. In addition, flat plate results captured the boundary layer thickness when compared with Prandtl’s 1/7th power-law. A chip was then introduced into the model, varying the chip width and the edge geometry. The most sensitive driving parameters were identified to be the chip width and Mach number. In cases where the chip width reached 16 times the TBC thickness, temperatures increased by almost 30% when compared to the undamaged equivalents. Additionally, increasing the Mach number of the incoming flow also increased metal temperatures. While the Reynolds number based on the leading edge of the model was deemed negligible, the Reynolds number based on the chip width was found to have a noticeable impact on the blade temperature. In conclusion, this study found that chip edge geometry was a negligible factor, while the Mach number, chip width, and Reynolds number based on the chip width had a significant effect on the total metal temperature.

Experimental Analysis of a Particle Separator Design With Full-Field 3D Measurements

Particle ingestion into turbine engines is a widespread problem that can cause significant degradation in engine service life. One primary damage mechanism is deposition of particulate matter in internal cooling passages. Musgrove et al. proposed a compact particle separator that could be installed between the combustor bypass exit and turbine vane cooling passage inlet. The design had small pressure losses but provided limited particle separation, and its performance has proved difficult to replicate in subsequent experiments. Borup et al. recently developed a Magnetic Resonance Imaging (MRI) based technique for making full-field, 3D measurements of the mean particle concentration distribution in complex flows. A particle separator based on the Musgrove et al. design was fabricated out of plastic using 3D printing. The primary difference from earlier designs was the addition of a drain from the collector, through which 3% of the total flow was extracted. The separator efficiency was measured at two Reynolds numbers, using water as the working fluid and 33-micron titanium microspheres to represent dust particles. Particle Stokes number was shown to play the dominant role in determining efficiency across studies. MRI was used to obtain the 3D particle volume fraction and 3-component velocity fields. The velocity data showed that flow was poorly distributed between the separator louvers, while the collector flow followed the optimal pattern for particle retention. The particle distribution data revealed that strong swirling flow in the collector centrifuged particles towards the outer wall of the collector and into a partitioned region of quiescent flow, where they proceeded to exit the collector via the drain. Future designs could be improved by re-arranging the louvers to produce a more uniform flow distribution, while maintaining the effective collector design.

New Model to Predict Water Droplets Erosion Based on Erosion Test Curves: Application to On-Line Water Washing of a Compressor

Here, a new model for predicting the water droplet erosion (WDE) from online water washing in compressors is developed and its results are discussed in comparisons with a baseline model. The model development started with the analysis of existing WDE models as well as pertinent experimental campaigns aiming at extracting a comprehensive erosion model able to account for the influence of droplet velocity and diameter, impact angle, surface roughness and hardness on the erosion phenomena. The new approach is applied to the study of WDE for droplets of 100 μm diameter in a gas turbine compressor and the predictions are compared with those of the Springer model. Even if the two models (Springer’s and ours) return qualitatively similar results, the erosion prediction is strongly different as in Springer model the erosion rate is four time higher than in the present model. This difference is attributed to the oversimplification of Springer model that does not account for any of the parameters that are relevant for the water erosion such as surface hardness and roughness as well as for a different treatment of the incubation period. Furthermore, to analyze the effect of all the main quantities affecting WDE process, several simulations were performed. Droplets diameter is found to be the key parameter, in determining the erosion rate. Reducing the diameter one can reduce erosion from online water washing. Surface hardness is also very important, while surface roughness can be relevant depending on the time frame one is interested at.

Impact of Dust Feed on Capture Efficiency and Deposition Patterns in a Double-Walled Liner

The introduction of particulates into gas turbine engines poses a serious threat to component durability. Particles drawn from the environment, such as ash or sand, can be introduced into the air system used to cool hot section components and drastically diminish cooling performance. In the current study, a dirt-laden coolant stream impinged on a double-walled cooling configuration, which was comprised of an impingement plate followed by an effusion-cooled plate. Experiments were conducted at both room temperature and at temperatures in excess of 750°C; flow conditions were varied to achieve different pressure ratios across the cooling configuration. Dirt particles were introduced into the coolant using two different methods: in discrete bursts, called slugs; or in a continuous feed ensuring a constant stream of particles. This continuous feed mechanism is at the crux of a new test facility created to introduce flexibility and precision in the control of dirt feed rates, particularly for very small (< 50 mg) amounts of dirt. The difference in capture efficiency and in dirt patterns between the two feed methods showed measurably different dirt accumulation levels on the cold side of the effusion plate at the same test conditions. Results show that the slug feed method caused higher capture efficiency and thicker dirt deposition on the effusion plate compared to the continuous feed.

A Novel Methodology for Detecting Foreign Object Damage on Compressor Blading

Foreign Object Damage (FOD) to compressor airfoils is a common problem in operating aircraft engines that occurs when objects or debris are sucked into the engines. Especially small surface defects or impact damage (100μm – 300μm depth) can be problematic, as it only becomes noticeable during engine maintenance process, but can have a strong influence on the fatigue strength and service life of individual airfoils. Usually the blade and vane inspection during maintenance is carried out by visual examinations. The inspection findings are individually assessed and as a result the airfoils are accepted, repaired or replaced. This manual inspection process has a significant optimization potential by the means of automatization. This paper presents a novel methodology to automatically detect FOD on compressor airfoils. For the investigation and validation, numerous used compressor blades and vanes were digitized on site with a high precision optical 3D scanning system. A first approach is based on a machine learning algorithm. The idea is the surface segmentation of the digitized airfoil into typical affected areas such as the leading edge (LE), trailing edge (TE), pressure side (PS) or suction side (SS), wherein irregularities during the segmentation can be an indication for FOD. For a second approach, the surface curvature of the airfoil is considered. Locally limited regions with high curvature and concave shapes are sought as an indication for FOD. The required parameters position and depth associated to the individual FOD are calculated in both approaches. The results of both approaches are compared to each other and are validated against the results of a commercial software tool, which uses the approach of digital stoning to create surface defect maps. Furthermore, the results are verified by manually examining the airfoil scans. In the case of relatively small FOD, both approaches generate meaningful results. In terms of larger damages and deformations, both approaches have difficulties detecting it. This problem can be compensated by parametrization of the scanned airfoils with a section based approach using NACA like profile parameters. Unusual changes of specific airfoil parameters (e.g. stagger angle and chord length) over the airfoils height can indicate large FOD or deformation.

Physics-Based Part Orientation and Sentencing: A Solution to Manufacturing Variability

Casting deviations introduce geometric variability that impacts the aerodynamic performance of turbomachinery. These effects are studied for a High Pressure Turbine (HPT) rotor blade from a modern aero-engine. 197 blades were measured using three-dimensional structured-light scanning (GOM scanning), and the performance of each blade is quantified using Reynolds-Averaged Navier-Stokes (RANS) simulations. Casting variation is typically managed by applying geometric tolerances to determine the suitability of a component for service. The analysis demonstrates that this approach may not be optimal since it does not necessarily align with performance, in particular the capacity and efficiency. Alternatively, functional acceptance based on the predicted performance of each blade removes the uncertainty associated with geometric tolerancing and gives better performance control. Building on these findings, the paper proposes a method to set the orientation of the fir-tree, which is machined after casting. By customizing the alignment of each blade, performance variability and scrap rates can be significantly reduced. The method uses predictions of performance to reorient the castings to compensate for the manufacturing-induced errors, without changing the design-intent blade geometry and with minimal changes to the manufacturing facility.

Study on Leakage Loss Control Method of Circumferential Bending Clearance

The concept of circumferential bending clearance based on Gauss Bimodal Function is proposed to suppress tip leakage flow (TLF) in a highly-loaded turbine cascade. In this method, a new vortex (BV) can be induced to mix with TLV in the middle of tip region and block the development of tip leakage vortex (TLV). Since the blocking effect divides the TLV into two parts, the tip leakage rate and loss of TLF can be reduced significantly. In order to reveal the mechanisms of blocking effect on leakage flow and its influencing factors, the research numerically investigates the effects of environmental conditions on the TLF development in a turbine cascade. The flow field analysis of the optimal bending clearance is in the first place, and then the effects of clearance heights (δ) and incidence angles (α) on the TLF characteristic and loss are investigated respectively. Results indicate that the blocking effect has a close relationship with the TLF characteristic, which can be divided into the BV migration, TLV-2 location and blocking loss. The nearer distance to the leading edge (LE) and farther distance to the suction side (SS) of BV means a less loss of TLF in bending clearance cases. The further distance away from blade tip and SS of TLV-2 means a larger-scale vortex with more loss. The additional loss in blocking region expands constantly with the increase of clearance height and incidence angle. The bending clearance has limited control effect on TLF with the variation of clearance height, especially the loss increases in Case 2%H. However, it has a strong adaptability with the change of incidence angle, the relative total pressure loss drops up to 16% in Case −5°.

Using Optimization in Industrial Multi-Point Radial Compressor Design: Map Correction

The application of Surrogate-Based Optimization (SBO) to the industrial design process for a radial compressor with two operating points is described. The design specification includes two operating points at mass flow rates differing by a factor of three, and efficiency and pressure ratio targets for each point. The base case, while roughly sized from 1D analysis, fails to achieve the pressure ratio targets. In this paper, the optimization focusses on correcting the two speed-line map of total to static pressure ratio vs. mass flow rate. “Smart parameterization”, combining independent and dependent geometric parameters, and yielding reasonable geometries for most input combinations, coupled with efficient SBO, with separate models for response surface modeling and failure prediction, yields a design achieving the targets in just 57 CFD runs. FINE/Turbo [1] is used as the CFD analysis code and FINE/Design3D [2] and MINAMO [3] as the multi-objective optimizer.

Multi-Fidelity Global-Local Optimization of a Transonic Compressor Rotor

In aerodynamic design, accurate and robust surrogate models are important to accelerate computationally expensive CFD-based optimization. Machine learning techniques can also enable affordable exploration of high-dimensional design spaces with targeted selection of sparse high-fidelity data. In this paper, a multi-fidelity global-local approach is presented and applied to the surrogate-based design optimization of a highly-loaded transonic compressor rotor. The key idea is to train multi-fidelity surrogates with fewer high-fidelity RANS predictions and more rapid and inexpensive lower-fidelity RANS evaluations. The framework also introduces a global-local search algorithm that can spin-off multiple local optimization threads over narrow and targeted design spaces, concurrently to a constantly adapting global optimization thread. The approach is demonstrated with an optimization of the transonic NASA rotor 37, yielding significant increase in performance within a dozen of optimization iterations.

Adjoint-Based Multidisciplinary, Multipoint Optimization of a Radial Turbine Considering Aerodynamic and Structural Performances

This paper presents a multidisciplinary adjoint-based design optimization of a turbocharger radial turbine for automotive applications. The aim is to improve the total-to-static efficiency of the turbine while keeping mechanical stresses below a predefined limit. The search for the optimal design is accomplished using an efficient Sequential Quadratic Programming algorithm considering additional aerodynamic and manufacturing constraints. The aerodynamic performance of the wheel is evaluated by a Reynolds-Averaged Navier-Stokes solver, whereas the maximum stresses in the material are predicted by a Finite Element Analysis tool. The design gradients required by the optimizer are computed with the adjoint approach which provides sensitivity information largely independent of the number of design variables. The results presented in this paper show the clear need to take into account mechanical stresses during optimization, as they are the most restrictive design limitation. However, the gradient-based optimization algorithm is able to effectively keep the stress levels below the critical value while significantly improving the turbine efficiency in a few design cycles.