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Article

Microstructure Image-Based Finite Element Methodology to Design Abradable Coatings for Aero Engines

1
Department of Mechanical Engineering, SRM University AP, Mangalagiri 522240, India
2
Symbiosis Institute of Technology, Symbiosis International University (Deemed), Pune 412115, India
*
Author to whom correspondence should be addressed.
Aerospace 2023, 10(10), 873; https://doi.org/10.3390/aerospace10100873
Submission received: 19 August 2023 / Revised: 26 September 2023 / Accepted: 6 October 2023 / Published: 8 October 2023

Abstract

:
Upgrading abradable or wearable coatings in the high-temperature zone of aero engines is advised to increase the efficiency and high-density power in gas turbine engines for military or commercial fixed-wing and rotary-wing aircraft. The development of these coated materials is also motivated by minimization of the number of failures in the blade, as well as increasing their resistance to wear and erosion. It is suggested that abradable coatings or seals be used to accomplish this goal. The space between the rotor and the shroud is minimized thanks to an abradable seal at the blade’s tip. Coatings that can withstand abrasion are often multiphase materials sprayed through thermal spray methods, and which consist of a metal matAzmeerix, oxide particles, and void space. The maintenance of an ideal blend of qualities, such as erosion resistance and hardness, during production determines a seal’s effectiveness. The objective of this research is to develop microstructure-based modelling methodology which will mimic the coating wear process and subsequently help in designing the abradable coating composition. Microstructure modelling, meshing, and wear analysis using many tools such as Fusion360, Hyper Mesh, and LS-Dyna, have been employed to develop an abradable coating model and perform wear analysis using a simulated rub rig test. The relation between percentage composition and morphology variations of metal, oxide, and voids to the output parameters such as hardness, abradability, and other mechanical properties is explored using simulated finite analysis models of real micrographic images of abradable coatings.

1. Introduction

There are a number of vulnerable parts in aero turbine engines, combustion chambers, and compressors; all these parts are coated to prevent abrasion and high-temperature protection. Coatings are used for both surface protection and sealing (clearance control) in compressors and turbines. Aero engines often use coatings for clearance control or to guarantee that the working fluids (air in the compressor and fuel combustion products/air in the turbine) flow smoothly and efficiently across the blade surfaces, from tip to casing liner. To do this, an abradable protection system is typically but not always applied to the blade tip and the case lining, respectively. It is possible to improve engine efficiency by reducing the tip clearance between the rotor and stator components by using sacrificial abradable coatings for stationary and aerodynamic gas turbines. Coating elements that resist abrasion surface coatings like combustion flames, arc wires, high-velocity combustion, and plasma spraying may be used to make coating systems for use in the gas turbine and aerospace industries. Industrial turbine operating efficiency can be greatly increased by physically reducing the distance between rotating and stationary elements. Several turbine and aviation engine manufacturers are currently offering a few compressor and hot section enhancements. These upgrades essentially consist of improved abradable sealing features and updated clearance control procedures to decrease hot gas bypass (i.e., leakage around the turbine) [1,2]. A multiphase substance called an abradable coating is created utilizing thermal spray processes, where the material melts at a high temperature and then sprays on a substrate. Abradable seals are often used in the aerospace sector [3,4,5,6]. CoNiCrAlY-BN-Polyester composite coatings, AlSi-hBN, NiCrAl-Bentonite, and NiCrAl-Bentonite-hBN are just a few of the more common materials used to make these seals. Using a TBC made of many layers of metal and ceramic increases engine efficiency by protecting the turbine and combustor from the hot gas stream [7].
Abradable seal coating systems must have excellent abradability, great resistance to gas and particle erosion, thermal stability, and self-lubrication. To increase the use of coatings, a balance between spalling resistance, surface finish, erosion, and abradability is required. High-temperature damage, high-temperature exposure, creep failures, fatigue failures, corrosion failures, and failures are all eliminated [1,8,9] as well, making gas turbine blades far more reliable.
Abradable coatings are tested using a test rig, which rotates a wheel on an abradable surface to calculate the total incursion depth, blade wear, and shroud wear volume. The ratio of volume loss due to shroud wear to blade wear is known as abradability. Force and wear on the blade tip are measured in a series of rub tests conducted at a variety of infeed and exit speeds. The abradable coating loss and blade tip loss of various coatings are compared. Blades and knife/fin seal materials typically made of steel, titanium alloy, or nickel alloy may be swapped out for a variety of softer materials [2,10,11].
The behavior of coatings depends on the SEM (using a 120 kilowatt (kW) BSE-mode power supply at 20 kilovolts in order to take the picture) microstructures of the coatings. Detailed FE models were run in simulation softwares [5,12,13] to ascertain the residual stress distribution and fracture mode of thermal barrier coating, fretting wear in composite cermet coating, effective material properties, thermo-mechanical behavior, and performance of coating at the microscopic level. Using finite element modeling based on microstructure, Bolelli [14] has shown that the thermo-mechanical behavior of thermal spray coatings may be understood and predicted. Nayebpashaee N authored an article [15] in which a micromechanically based finite element method (FEM) for predicting residual stress and the mode of failure of a thermal barrier coating (TBC) made of a metallic bond coat (BC) and a ceramic topcoat (TC) with and without thermally generated oxide (TGO) is described. To determine the true material characteristics of a thermally sprayed tungsten carbide–cobalt coating, B. Klusemann [16] developed a comprehensive FE model of the microstructure using SEM images and then experimentally examined the residual stresses in the coating. The widespread use of abradable coatings was investigated by T.A. Taylor [17]. A matrix of rub tests was performed with varying blade tip speeds and infeed rates to measure the effects on rub force and blade tip wear. The rubbed tip material were both examined in the SEM after being polished to reveal the wear mechanism at work. In a study by Lord Murugan [18], to better understand the microstructure-level interactions between microscopic particles and conventional turbine blade ceramic coatings, FE-based microstructure modeling and analysis were utilized to investigate the particle–surface interactions and restitution characteristics. Sharma [19] came up with a microstructure-sensitive finite element model for the fretting wear of HVOF Cr3C2-NiCr coatings. Voronoi tessellations revealed the coating’s microstructure, which consisted of a Cr3C2 phase dispersed randomly. Three novel numerical finite element models were developed by Holmberg K. [20]. The microstructural properties of widely used thick thermal spray and laser-clad metal matrix coatings were included in three different models: a flawless synthetic material model with no flaws, a sophisticated synthetic material model with flaws, and a real model based on photos. In order to fix dynamic boundary-value problems in the plane-stress formulation, Aleksandr Zemlianov [21] suggested using the ABAQUS/Explicit program. For dynamic boundary-value problems in the plane-stress formulation, R. Balokhonov [22] suggested using the ABAQUS/Explicit program. Mr. Zhong-Chao Hu [23] conducted research to better understand what causes TBCs to fail in high-temperature service circumstances. Li Chang-Jiu [24] studied flame spraying to create porous Al2O3 coatings in a semi-molten state.. In [25], Yann Duramou’s study investigated the connection between the microstructure and mechanical properties of AlSi-polyester abradable coatings that were sprayed with atmospheric plasma using finite element models. In Bérenger Berthoul [26,27], a new framework was created for simulating coating wear in turbomachinery. Coating abrasion phenomenology research served as the foundation for the model.. Pathak, P. [28] proposed the development of a thermal shock resistance structure to improve the temperature capacity and reliability of abrasion-resistant seal structures. The coating’s fracture toughness was measured using microhardness testing, and its thermomechanical performance was evaluated using object-oriented finite element analysis. In [29], Yumeng Ni examined how the CuAl-NiC abradable seal coating system corrodes in a chloride solution.
Irissou [30] developed APS CoNiCrAlY-BN-polyester abradable coatings with varying surface Rockwell hardness and porosity. The coatings’ resistance to erosion wear, adhesive strength, and performance under rub wear were tested. The study of D. Aussavy [31,32] identified the thermomechanical properties of coatings that are susceptible to abrasion. Prakash Jadhav’s [33] research concerns the use of microstructure-based image models of coatings to study abradability using simulations. In [34], the review updated the standard metal/alloy friction and wear theories to provide a semi-quantitative account of the specific mechanisms by which coatings achieve their superior anti-friction and anti-wear performance. In [35], the authors explain the performance of modified surfaces, which were developed by using various surface engineering techniques to combat slurry erosion failure in hydrodynamic turbines and effects of different operating parameters, such as the angle of impingement, erodent size and shape, and slurry concentration, on the performance of coating materials.
In this research, an experimental paper is referred to in which an abradable powder called CoNiCrAlY-BN was deployed using plasma spray. The paper generated different coating variations with their microstructural images, measured hardness, measured erosion rates, etc. [30]. As the focus of this work is to develop a simulation methodology to understand and predict the abradability of coatings using microstructure-based image models, the experimental data from the paper [30] were used to validate the proposed methodology. As abradable coatings are very important for turbine blades and casing to seal the gap and protect surfaces under rub events, the proper design of the coating is very important. By using simulation methodology, instead of conducting experiments to predict the properties of coatings, a great deal of repetitive experimental work can be saved. The novelty of this research is that it presents a novel simulation methodology to predict the behavior of coating using only a few microstructure images, which if proved successful, can assist a great deal in improving the design of abradable coatings for better performance.

2. Methodology

2.1. Key Performance Design Considerations for Sealing Turbomachinery Using Systems with Abradable Seal Coatings

The compatibility of the blade should be tested with fins or labyrinth seals under various incursion circumstances. In terms of coatings’ cohesiveness, resistance to oxidation at high temperatures from gases and liquids that are aqueous, or to chemicals that are corrosion-resistant, is important. Coatings are resistant to attacks from corrosive substances at high temperatures, such as sulfides, chlorides, and silicates (CMAS), to sintering at high temperatures, and to thermal shock or cycle-induced degradation of solid particles. The primary purposes of abradable coatings are their compatibility with labyrinth seals, shrouded versions of turbine, compressor, or fan blades, or their unshrouded counterparts. This is because abrasive wear and/or friction-induced overheating of the dynamic component may be mitigated if the coating of the abradable counterpart is softer than the material of the dynamic rubbing component. Blades, knives, and fin seals are often made of steel, titanium alloy, or nickel alloy, which are among the softer materials used in turbomachinery. The High-Pressure Compressor (HPC) and High-Pressure Turbine stages shown in Figure 1a operate at extremely high temperatures, requiring the use of materials such as NiCrAl-Bentonite and CoNiCrAlY-BN-Polyester coated on the inside circumference of casing over which turbine blades are continuously rotated to maintain clearance between the blade and casing. This is to upgrade the High-Pressure (HP) Turbine’s current clearing seal, which consists of thermal barriers [31].

2.2. Rub Rig Event-Modelling Methodology

The rub experiments were generally performed using the abradable test gear shown in Figure 1b. By rubbing a miniature turbine blade (or knife edge) against the coupon of an abradable (or honeycomb) seal, this device simulates the wear that gas turbines experience while in use. In this test, the wheel spins at high speeds, removing the coating and also wearing down the wheel itself. After an experiment is complete, information is collected on coating wear on coupons and blade tip wear. Coating performance can be measured in terms of its abradability, which is a comparison of the coating’s wear to that of the blade. Here, we attempted this by using a simulation to replicate the dynamic processes at work on the coating microstructure of the blade. Abradability is defined as the ratio of coating wear to wheel wear after measuring wear on the wheel surface and coating surface. For a good abradable seal, the preferred abradability ratio is in the range of 10 to 20. Utilizing 3D FEA models of this set-up with a microstructure-based foundation is the main component of the modeling process here. The coating was initially prepared by APS (air plasma spraying) on coupons, and then its microstructure was examined using micrography. A proprietary technique was used to prepare the FEA model and mesh based on the microstructure image. For the creation of the model and refined mesh, Autodesk Fusion 360 2021 and Hyper Mesh 2021 software were employed. The related generated mesh file was imported into the LS-DYNA 13.1 [36] program for additional processing to produce a 3D model of the coating and simulation of micrograph model to achieve dynamic wear. This model’s primary goal is to replicate the coating’s behavior on a rub rig, as seen in the rub rig test setup. Some modifications were made in the simulation for the sake of modelling convenience. The blade, rather than rotating like a wheel, moves forward and backward repeatedly to imitate its motion. On the coating microstructure, the blade was rotated at a rate proportional to the tangential speed of the rotating wheel. After the simulation was complete, the abradability was evaluated by examining the blade and microstructure volume loss.

2.3. APS Microstructures 1 and 2

The abradable coating microstructures used in this research are taken from [33]. Bond coat was made using gas-atomized CoNiCrAlY powder (Amdry 9951, Sulzer Metco, Westbury, NY, USA). Spraying on a powdered composite of CoNiCrAlY, BN, and polyester (Co25Ni16Cr6Al0.3Y-4BN-15 Polyester) (SM 2043, Sulzer Metco, Westbury, NY, USA) created wear-resistant coatings. Using two different torches (model numbers F4MB and 9MB, both manufactured by Sulzer Metco, Westbury, NY, USA), we sprayed the bond coat and abrasive powders using air plasma spray (APS).
Before depositing the bond coat, the mild steel 1020 substrates were grit-blasted with a 24-grit alumina grit. The as-sprayed samples were put through a thermal treatment cycle to burn away the polyester from the coating, resulting in the necessary porosity for the abradable seals. The last round of testing was an air heat treatment at 500 degrees Celsius for 3.5 h. APS engineers have developed CoNiCrAlY-BN-polyester abrasive coatings with a wide range of porosities and surface Rockwell hardness. The coatings’ performance and behavior were examined using adhesion, erosion wear, and rub wear tests. The findings demonstrate that the hardness of abradable coatings may be improved by reducing their porosity percentage. Figure 2a,b from [30] show SEM cross-sectional images of coatings with a magnification of 100 µm of (a) 56% porosity 48 HR15Y and (b) 46% porosity 71 HR15Y.

2.4. APS Microstructure 3 and 4

Both of these microstructures were coated with CoNiCrAlYBN-polyester using an atmospheric plasma spray method. The hardness of the abradable coatings is increased while the porosity is decreased, marking a single key difference between these microstructures and prior APS microstructures. Figure 3a,b is a cross-sectional SEM image [34] depicting two coatings of magnification 100 µm, one with a porosity of 50% and a Rockwell hardness of 55 HR15Y, and the other with a porosity of 35% and a Rockwell hardness of 75 HR15Y.

2.5. Geometric Modelling of Microstructure

In this study, CoNiCrAlYBN-polyester was used in the four images to model and simulate the abrasion resistance of thermal barrier coatings. Autodesk Fusion 360 2021 was the software used for microstructure modeling. The DFX file format was created separately for each of the three phases of metal, oxide, and porosity using the Image J program and is rigorously followed in the production of modeling. The DFX file was used to construct and put together all four three-phase models. Once the microstructures were put together, the same procedure was followed for the remaining percentage variations in porosity and hardness. For creating refined meshes with consistent element sizes and densities, Hyper Mesh 2021 software was employed. The mesh style was utilized to make fine mesh, and the matching mesh file was imported into the LS-DYNA program for further processing to produce a 3D model of the coating and a simulation of the micrograph model.

2.6. 3D Modality of Microstructure

Figure 4a,d illustrate the porosity of the microstructure, which was modelled in 3D using Fusion 360 software at 56%, 46%, 50%, and 35%; phases of metal and oxide porosity are represented by unique colors. The sizes and shapes of the ingredients of the four microstructures differ, but the overall dimensions of the micrograph are the same, 0.6 mm by 0.412 mm.

2.7. 3D Microstructure Mesh

Meshes for all four microstructures (56%, 46%, 50%, and 35%) are displayed in Figure 5a,d. Only the 2D surface is shown, and the metal and oxide phases are depicted using distinct colors. In this scenario, a mesh is generated with a first-area-phase (porosity) element size of 5. For structures with 56% porosity and 48 HR15Y, 46% porosity and 71 HR15Y, 50% porosity and 55 HR15Y, and 35% porosity and 75 HR15Y, the average number of elements in the coating was 800,000 and those in the blade model was 100,000. The element formulation used was constant stress hex 8 node solid element. The same element formulation was used for all the ingredients, i.e., metal, oxide and porosity.

2.8. FEM Model of Microstructure in LS-DYNA 13.1 Software

The 3D model is about 0.6 mm by 0.412 mm in size in planar direction and is a few elements thick in the thickness direction. The coating’s many components, such as metal, oxide, and porosity, are denoted by various color elements. To ensure continuity in the model, porosity is represented here as discrete parts. Figure 5 depicts the creation of a 3D blade model of 0.5 mm × 0.02 mm that is a few elements thick and has a bottom shape that is semicircular. The simulation setup is finalized when the blade and coating models have been imported into the LS-Dyna 13.1 software. As the wheel is put onto a coupon at a set feed rate, the experimental rub rig simulates the dynamic difficulty of blade tips attached to a high-speed spinning wheel. A coupon receives its coating and is then adhered to the mount. When the blade tip hits the ground, the coating is scraped. After an experiment has ended, data on the coating wear on coupons and the tip wear on blades are obtained. Abradability is a metric for evaluating coating performance that compares coating wear to blade wear. Here, the simulation attempts to mimic similar dynamic events. The finest option for dynamic wear simulation 13.1 software is undoubtedly LS-Dyna, but for the sake of modeling convenience, there were some adjustments performed in the simulation. The blade moved forward and backward repeatedly to mimic the motion of the revolving wheel rather than a blade rotating in place of it. The blade was simulated to move at the same rate as the tangential speed of the revolving wheel (about 450 m/s). In order to prevent dynamic wave reflections from the bottom, the correct boundary conditions for the coating model include considering the bottom surface as non-reflective. Constraining the left and bottom side along its edge helps to contain the coating. In plain strain, for example, longer vertical surfaces are restricted to a perpendicular or out-of-plane orientation. The blade was also given suitable boundary conditions, such as forward and backward displacements, in addition to the velocity. Limitations on normal strain also apply to blade-length surfaces. The piecewise linear plasticity (Ti64) material model was used to represent the blade, whereas the kinematic plasticity (AP) material model was used to simulate the alloy coating in LS-Dyna. The coating model provides individual values for metal, oxide, and porosity moduli; density; Poisson’s ratio; yield strength; and tangent moduli. The modulus employed for the porosity components was relatively small. All the coating’s components were presumptively subject to strain-based failure, and estimates of the strains at which metal, oxide, and porosity would fail were given. Using trial simulations, we estimated the optimal value of the porosity failure strain, which turned out to be between 1% and 2%. A piecewise linear plasticity model (with temperature taken into consideration at 371.1 degrees Celsius) was used in conjunction with stress–strain data for the blade material. The modulus and the Poisson’s ratio were other inputs for the blade. The MAT ADD EROSION command was used in the material model to specify the stress limits at which the blades would fail under load. In order to avoid making hourglass errors, the hourglass command was utilized and implemented across the board. Figure 6a,b show an example of the boundary’s MOTION command sent to the blade as two pieces of data (vertical y-axis motion and horizontal x-axis motion), each of which is represented as velocity as distance vs. time split into 60 intervals. For the times specified, the blade’s horizontal and vertical positions were correct.
The instruction that specifies contact between the blade and the coating materials is contact eroding surface to surface. When elements approach the failure limitations specified in the material models, this contact allows the elements to fail. In the same way that particles are worn away over time, failed elements were removed from the simulation. The simulation determines the overall coating material and blade element volume loss percentage. The volume of coating (metal and oxide) removed was compared to the volume of the blade to obtain the abradability parameter. According to the results of the tests, the best shrouds and coatings have an abradability of 20 or more, which implies that they can remove a volume of coating at least 20 times as much volume as the blade. All simulations were conducted with identical boundary conditions, total model size, blade velocity, etc., so that meaningful comparisons may be made.

2.9. Material Properties for Coating and Blade and Input Parameters for Blade

The critical investigation here was to determine how changes in the material qualities of all the coating or blade components affect the abradability. The best settings can be found to produce improved abradability by comprehending the impact of each individual parameter. As previously mentioned, a representative microstructure-based FEA mesh model is employed for all the situations below. To begin with, Table 1 displays the attributes of the blade and shroud materials; it should be noted that all material inputs are constant. Metal, oxide, and porosity coating models each have their own set of reported modulus, density, Poisson’s ratio, yield strength, and tangent modulus data. A very small value of the modulus is applied to the porosity components. For all the coating’s components, strain-based failure is assumed, and estimates of the failure strain limits for metal, oxide, and porosity are given as 2.5%, 1%, and 2%, respectively. Material characteristics, including density, modulus, and Poisson’s ratio, are given for blade titanium 64.
Additionally, Table 2 shows material inputs for blades; Figure 7 shows the material behavior plot for titanium 64, the material used for the blades, which is considered an input (at 700 °F to account for the temperature effect); and 0.9 GPa is assumed for blade erosion in the event of stress-based failure.

3. Results

3.1. All Coating Cases—Prior to Erosion Models

According to the boundary conditions established along the x and y directions, Figure 8a,d show that the 3D model is only a few elements thick in the thickness direction and is of the size 0.6 mm by 0.412 mm in the planar direction. Metal, oxide, and porosity are all characteristics of the coating that are represented by different colors. To avoid the collapse of the model, porosity is shown here as modular components. Building a 3D blade model with a semicircular blade base and some thickness is depicted in Figure 5. This method treats porosity as distinct entities, with the blade resting still on the coated material at first before moving back and forth during post processing to ensure uniformity. Porosity, oxides, and metals are similarly automatically eliminated as material elements when their respective failure strain levels are achieved. This occurs whenever the blade accomplishes its task based on the qualities listed in Table 1 and Table 2. It should be noted that a very small quantity of blade material is also removed during this entire process as the blade swings back and forth at a specific frequency to remove the coated material.

3.2. Abradable Seal with 56% Porosity and 48 HR15Y after Erosion Results

The velocity in Figure 6 determines how the blade moves. Figure 9a show that the blade stops moving after a predetermined amount of time, and the colors represent different pore sizes and shapes in four microstructures that correspond to different metallurgical stages; however, the coated substance loses some of its material, specifically metal and oxide, during this process. Although blade loss is clearly evident, it is important to note that metal and oxide loss and blade loss are also present throughout this process. Eventually, a little gap arises between the blade and the coated material.
Once the simulation was finished, the D3 plot and the time history graph were used to calculate the volume of material loss for metal, oxide, and blade using the volume fail command. According to Figure 9b, which also demonstrates how the rate of metal erosion rises as the blade gets deeper, the volume loss of metal is greater and the volume loss of oxide is marginally less than the metal. It is clear that the blade loss is lower than that of metal and oxide, though. As the blade penetrates deeper into the coated substance, so does the volume loss shown by the blade in the graph. The volume loss of the blade and the volume loss of metal and oxide with 56% porosity and 48 HR15 Rockwell hardness were observed for the full time period. However, volume loss in an abrasion-resistant seal caused the loss of metal and oxide. In comparison to the abradable seal, which was anticipated to lose the most metal and oxide at a given porosity and hardness, the volume loss of the blade over the full interval of time was predicted to be less.

3.3. Abradable Seal with 46% Porosity and 71 HR15Y after Erosion Results

As seen in Figure 10a,b, which also demonstrates how the metal erosion rate rises as blade depth increases, it is clear that the blade loss is lower than that of metal and oxide. As the blade penetrates deeper into the coated substance, so does the volume loss shown by the blade in the graph. The volume loss of the blade and the volume loss of metal and oxide with 46% porosity and 71HR15 Rockwell hardness were both seen during the full time period, in contrast to the previous figure where the volume loss of an abrasion-resistant seal results in the loss of metal and oxide. Compared to the abradable seal, which is anticipated to lose less metal and oxide, the volume loss of the blade over the entire interval of time is predicted to be larger. It is critical to emphasize that blade wear is a crucial factor in determining how well an abrasion-resistant seal performs. There may be serious repercussions if the blades experience high wear rates. For instance, an uneven force may suddenly increase, causing the seals to sustain unanticipated secondary damage.

3.4. Coatings with the Same Chemical Composition but Different Microstructures (i.e., Porosity and Hardness) May Be Worn Away by Abrasion

The blade moves vertically downward from left to right and from right to left, based on the boundary condition that has been given, removing metal piece by piece with each action and losing material as well. Throughout the entire process, the blade revolves 60 times, eliminating the material. Figure 10 above, however, can be used to calculate individual metal volume loss, oxide volume loss, and blade volume loss using data from the last 60 passes from the beginning. The formula below is then used to calculate abradability.
A b r a d a b i l i t y = v o l u m e   f r a c t i o n   o f   c o a t i n g   ( m e t a l   +   o x i d e )   r e m o v e d ( o r )   s h r o u d   w e a r v o l u m e   f r a c t i o n   o f   b l a d e   r e m o v e d .
The abradability increases steadily from the first pass to the last pass, as shown in Figure 11a, but it is higher for the microstructure with 56% porosity and 48 HR15Y due to its higher porosity levels and lower hardness value. Figure 11b shows that, because of the low porosity levels and high hardness value of the microstructure, the abradability of 46% porosity and 71 HR15Y for the final 60th pass is less than the abradability values in Figure 11a. Increasing and decreasing values of abradability for the 60th pass for both APS1 and APS2 coating results are shown in Table 3.

3.5. Abradable Seal with 50% Porosity and 55 HR15Y after Erosion Results

Figure 12a,b also shows that when the blade goes deeper and more metal is lost, the rate of metal erosion increases. There is no doubt that blade loss is smaller than metal loss. The volume loss displayed by the blade in the graph increases as the blade incises farther into the covered substance. For the entire time period, the volume loss of the blade and the volume loss of metal with 50% porosity and 55 HR15 Rockwell hardness were both noted. Abrasion-resistant seals, however, experienced volume loss, which resulted in the loss of metal, and the volume loss of the blade over the entire period of time was estimated to be less than that of the abradable seal, which was expected to lose the most metal at a given porosity and hardness.

3.6. Abradable Seal with 35% Porosity and 77 HR15Y after Erosion

Figure 13a,b shows how metal degradation rates climb as blade depth rises. However, it is obvious that blade loss is less than that of metal. The volume loss indicated by the blade in the graph increases as it reaches deeper into the covered substance. In contrast to the preceding figure, where metal is lost as a result of the volume loss of an abrasion-resistant seal, both the volume loss of the blade and the volume loss of metal with 35% porosity and 77 HR15 Rockwell hardness was seen during the entire time period. At the specified hardness and porosity ranges, the blade volume loss throughout the full-time interval was predicted to be lesser than that of the abradable seal, which was expected to lose more metal.

3.7. Coatings with the Same Chemical Composition Might Wear Differently If They Have Various Microstructures, Which in Turn Lead to Varying Porosity and Hardness

According to Figure 14a, the abradability rises continuously from the first to the last pass, although it is higher for the microstructure with 56% porosity and 48 HR15Y due to its higher porosity levels and lower hardness value.
As shown in Figure 14b, the abradability of 35% porosity and 77 HR15Y for the final 60th pass is less than the abradability values in Figure 14a due to the low porosity levels and high hardness value of the microstructure. Increasing and decreasing values of abradability for the 60th pass for both APS3 and APS4 coatings result in Table 4.
Table 3 and Table 4 show that shroud wear increases when the hardening value decreases and the percentage of porosity rises, showing that abradable seal wear increases and blade wear decreases while abradability increases. Similar to this, abradability diminishes as porosity levels reduce, and as hardness values climb, abradable seal wear decreases and blade wear rises. This is the most recent trending method to determine the abradability of coated materials, and it means that abradability is directly proportional to porosity percentage and indirectly proportional to hardness value.
Some of the experimental data in Table 5 were taken from reference [33], including bond strength, erosion rate, porosity, and hardness. In this work, an FEA model of the rub-rig testing environment was created, and an attribute dubbed “abradability” was found using LS-Dyna simulation. However, the data below show abradability, which changes depending on how numerous instances with varied attributes are compared.

3.8. Abradability Comparison Results

3.8.1. Analyses of Coatings’ Abrasion and Erosion Rates

In relation to the coating’s erosion rate, the abradability is depicted in Figure 15a. Within the hardness and porosity ranges of the coatings under study, the abradability was linearly correlated with the rate of coating erosion, increasing from 6.5 to 11.34. The fan and compressor parts of aircraft engines erode as a result of fine particles entering the air and passing through the jet engine’s flow path, most frequently during landings and takeoffs. Because of its low abradability, coating is a good option for aircraft engine applications where it is necessary to prevent erosion and wear of the abradable seal.
The relationship between coating porosity percentage and abradability is depicted in Figure 15b. The abradability increased from 6.5 to 11.4 with respect to the porosity percentage, going from 35% to 56%, showing a direct proportionality between the two. Composite materials known as “abradable seal” are made of a metal phase, a ceramic containing one or both self-lubricating non-metal phases, and a polymer to create porosity. The coated sample went through a thermal treatment cycle to burn off the polyester from the coating and obtain the right amount of porosity for the abradable seal.

3.8.2. Compatibility of Coatings in Terms of Abradability, Bond Strength, and Rockwell Hardness

Figure 15c shows the results of the relationship between bond strength value and abradability. For each microstructure, the failure mode was cohesive. When binding strength was low, the coating’s abradability value was relatively high, and when bond strength was high, the abradability number was low. A linear relationship between bond strength and the abradability number was inverted.
Abradability changes with the number of coatings and the hardness, as seen in Figure 15d. The abradability number is inversely correlated with the hardness; it rises from low to high as the hardness value falls from 77 HR15Y to 48 HR15Y. The damage to seals and blades becomes worse the tougher the material is. A rise in the hardness of the abradable seal resulted in significant damage to the blade.

3.8.3. Abradability and Wear Depth of Coating Comparison Results

Figure 15e,f illustrate the evolution of abradable seal wear depth and blade versus abradability number. Blade wear has an inverse functional relationship to abradability; it decreases as the number increases, but seal wear has a direct proportionate relationship to abradability. The greater the abrasion resistance, the more the seal will wear down. Blade wear being the most crucial factor in determining how well an abradable seal performs, it is important to mention it. There could be serious repercussions if the blades experience high wear rates. For instance, an unbalanced force could quickly increase, causing unforeseen secondary damage to the seals.

4. Conclusions

A microstructure-based modelling methodology was developed here which mimics the coating wear process and subsequently assists in designing the abradable coating composition. Microstructure modelling, meshing, and wear analysis, using many tools such as Fusion360, Hyper Mesh, and LS-Dyna, have been employed to develop an abradable coating model and perform wear analysis using simulated rub rig test. The relation between percentage composition and morphology variation of metal, oxide, and voids to the output parameters such as hardness, abradability, and other mechanical properties is explored using simulated finite analysis models of real micrographic images of abradable coatings.
Microstructure images of various CONicral-BN polyester coatings as abradable coatings were used. Using these images, 3D coating finite element models were created, meshed, and further improved by adding the blade using various tools. A simulated rub rig test was then performed on the coating models using LS-Dyna.
It is concluded here that abradability and erosion rate increase as the porosity level increases. As the bond strength and hardness level increase, abradability level drops. Abradability number increases when the level of coating wear increases or blade wear decreases.
High-resolution SEM images will be used in future research to develop the ability to predict abradability, and the simulation approach developed will be used to predict the characteristics and performance of any unknown coating composition merely by looking and using the coating’s microstructure image.

Author Contributions

Software, A.K.A. and C.L.; Formal analysis, A.K.A.; Investigation, A.K.A.; Data curation, C.L.; Writing—original draft, P.J.; Writing—review & editing, P.J.; Supervision, C.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data will be available upon request.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. (a) Placement of abrasive coatings inside a Turbojet engine. (b) A view of the whole abradable test apparatus.
Figure 1. (a) Placement of abrasive coatings inside a Turbojet engine. (b) A view of the whole abradable test apparatus.
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Figure 2. (a) 56% porosity and 48 HR15Y; (b) 46% porosity and 71 HR15Y.
Figure 2. (a) 56% porosity and 48 HR15Y; (b) 46% porosity and 71 HR15Y.
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Figure 3. (a) 50% porosity and 55 HR15Y; (b) 35% porosity and 75 HR15Y.
Figure 3. (a) 50% porosity and 55 HR15Y; (b) 35% porosity and 75 HR15Y.
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Figure 4. Three-dimensional (3D) modality of microstructure: (a) 56% porosity and 48 HR15Y; (b) 50% porosity and 55 HR15Y; (c) 46% porosity and 71 HR15Y; (d) 35% porosity and 75 HR15Y.
Figure 4. Three-dimensional (3D) modality of microstructure: (a) 56% porosity and 48 HR15Y; (b) 50% porosity and 55 HR15Y; (c) 46% porosity and 71 HR15Y; (d) 35% porosity and 75 HR15Y.
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Figure 5. Three-dimensional (3D) microstructure mesh (a) 56% porosity and 48 HR15Y; (b) 50% porosity and 55 HR15Y; (c) 46% porosity and 71 HR15Y; (d) 35% porosity and 75 HR15Y.
Figure 5. Three-dimensional (3D) microstructure mesh (a) 56% porosity and 48 HR15Y; (b) 50% porosity and 55 HR15Y; (c) 46% porosity and 71 HR15Y; (d) 35% porosity and 75 HR15Y.
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Figure 6. Blade motion: (a) vertical and (b) horizontal motion.
Figure 6. Blade motion: (a) vertical and (b) horizontal motion.
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Figure 7. Material behavior plot for blade.
Figure 7. Material behavior plot for blade.
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Figure 8. (a) 56% porosity and 48 HR15Y before erosion and (b) 46% porosity and 71 HR15Y before erosion. (c) 50% porosity and 55 HR15Y before erosion and (d) 35% porosity and 77 HR15Y before erosion.
Figure 8. (a) 56% porosity and 48 HR15Y before erosion and (b) 46% porosity and 71 HR15Y before erosion. (c) 50% porosity and 55 HR15Y before erosion and (d) 35% porosity and 77 HR15Y before erosion.
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Figure 9. (a) 56% porosity and 48 HR15Y after erosion; (b) volume loss of the abradable seal and volume loss of the blade with respect to time.
Figure 9. (a) 56% porosity and 48 HR15Y after erosion; (b) volume loss of the abradable seal and volume loss of the blade with respect to time.
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Figure 10. (a) 46% porosity and 71 HR15Y after erosion. (b) Volume loss of the abradable seal and volume loss of the blade with respect to time.
Figure 10. (a) 46% porosity and 71 HR15Y after erosion. (b) Volume loss of the abradable seal and volume loss of the blade with respect to time.
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Figure 11. (a) Abradability of an abradable seal with 56% porosity and 48 HR15Y with respect to 60 passes of the blade; (b) abradability of an abradable seal with 46% porosity and 71 HR15Y with respect to 60 passes of the blade.
Figure 11. (a) Abradability of an abradable seal with 56% porosity and 48 HR15Y with respect to 60 passes of the blade; (b) abradability of an abradable seal with 46% porosity and 71 HR15Y with respect to 60 passes of the blade.
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Figure 12. (a) After erosion, 50% porosity, and 55 HR15Y. (b) Volume loss of the abradable seal and volume loss of the blade with respect to time.
Figure 12. (a) After erosion, 50% porosity, and 55 HR15Y. (b) Volume loss of the abradable seal and volume loss of the blade with respect to time.
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Figure 13. (a) shows 35% porosity and 77 HR15Y after erosion; (b) volume loss of the abradable seal and volume loss of the blade with respect to time.
Figure 13. (a) shows 35% porosity and 77 HR15Y after erosion; (b) volume loss of the abradable seal and volume loss of the blade with respect to time.
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Figure 14. (a) Abradability of an abradable seal with 50% porosity and 55 HR15Y with respect to 60 passes of the blade. (b) Abradability of an abradable seal with 35% porosity and 77 HR15Y with respect to 60 passes of the blade.
Figure 14. (a) Abradability of an abradable seal with 50% porosity and 55 HR15Y with respect to 60 passes of the blade. (b) Abradability of an abradable seal with 35% porosity and 77 HR15Y with respect to 60 passes of the blade.
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Figure 15. (a) Abradability variation with erosion rate. (b) Abradability variation with porosity percentage. (c) Abradability variation with bond strength. (d) Abradability variation with Rockwell hardness. (e) Wear of blade variation with abradability. (f) Wear of seal variation with abradability.
Figure 15. (a) Abradability variation with erosion rate. (b) Abradability variation with porosity percentage. (c) Abradability variation with bond strength. (d) Abradability variation with Rockwell hardness. (e) Wear of blade variation with abradability. (f) Wear of seal variation with abradability.
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Table 1. Material properties for metal, porosity, oxide, and blade [31].
Table 1. Material properties for metal, porosity, oxide, and blade [31].
S. No.MaterialDensity (kg/mm3)Young’s Modulus (Gpa)Poisson’s RatioYield Strength (Gpa)Tangent Modulus (Gpa)Failure Strain
1Metal3 × 10−61500.30.71400.025
2Porosity1 × 10−610.330.0250.10.02
3Oxide3.8 × 10−61900.340.3751800.01
4Titanium643.2 × 10−61590.342---
Table 2. Material inputs for blade [10].
Table 2. Material inputs for blade [10].
S. NoStress (Gpa) Strain
100
20.170.02
30.20.05
40.210.1
50.220.25
60.180.5
70.1251
Table 3. Abradability for APS1 and APS2 coatings.
Table 3. Abradability for APS1 and APS2 coatings.
ModelMetal Wear (µm3)Oxide Wear
(µm3)
Shroud Wear (Metal + Oxide) (µm3)Blade Wear (µm3)Abradability for 60th Pass
56% porosity and 48 HR15Y1.55 × 10−11.41 × 10−12.96 × 10−12.61 × 10−211.34
46% porosity and 71 HR15Y1.48 × 10−12.59 × 10−21.74 × 10−12.65 × 10−26.56
Table 4. Abradability for APS3 and APS4 coatings.
Table 4. Abradability for APS3 and APS4 coatings.
ModelMetal Wear (µm3)Oxide Wear (µm3)Shroud Wear (Metal + Oxide) (µm3)Blade Wear (µm3)Abradability for 60th Pass
50% porosity and 55 HR15Y1.78 × 10−101.78 × 10−12.3 × 10−27.74
35% porosity and 77 HR15Y1.6 × 10−101.6 × 10−12.46 × 10−26.5
Table 5. Comparing the abradability with reference to different types of properties.
Table 5. Comparing the abradability with reference to different types of properties.
S. NoPropertyCase1Case2Case3Case4
1Bond strength (Mpa)4.8512.515
2Erosion rate (µm/sec)5.95.12.21.8
3Wear of blade (µm)010100800
4Wear of abradable seal (µm)11001050900790
5Porosity (%)56504635
6Rockwell hardness (HR15Y)48557177
9Abradability11.347.366.566.5
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Azmeera, A.K.; Jadhav, P.; Lande, C. Microstructure Image-Based Finite Element Methodology to Design Abradable Coatings for Aero Engines. Aerospace 2023, 10, 873. https://doi.org/10.3390/aerospace10100873

AMA Style

Azmeera AK, Jadhav P, Lande C. Microstructure Image-Based Finite Element Methodology to Design Abradable Coatings for Aero Engines. Aerospace. 2023; 10(10):873. https://doi.org/10.3390/aerospace10100873

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Azmeera, Anitha Kumari, Prakash Jadhav, and Chhaya Lande. 2023. "Microstructure Image-Based Finite Element Methodology to Design Abradable Coatings for Aero Engines" Aerospace 10, no. 10: 873. https://doi.org/10.3390/aerospace10100873

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