Predictive maintenance is considered a proactive approach that capitalizes on advanced sensing technologies and data analytics to anticipate potential equipment malfunctions, enabling cost savings ...and improved operational efficiency. For journal bearings, predictive maintenance assumes critical significance due to the inherent complexity and vital role of these components in mechanical systems. The primary objective of this study is to develop a data-driven methodology for indirectly determining the wear condition by leveraging experimentally collected vibration data. To accomplish this goal, a novel experimental procedure was devised to expedite wear formation on journal bearings. Seventeen bearings were tested and the collected sensor data were employed to evaluate the predictive capabilities of various sensors and mounting configurations. The effects of different downsampling methods and sampling rates on the sensor data were also explored within the framework of feature engineering. The downsampled sensor data were further processed using convolutional autoencoders (CAEs) to extract a latent state vector, which was found to exhibit a strong correlation with the wear state of the bearing. Remarkably, the CAE, trained on unlabeled measurements, demonstrated an impressive performance in wear estimation, achieving an average Pearson coefficient of 91% in four different experimental configurations. In essence, the proposed methodology facilitated an accurate estimation of the wear of the journal bearings, even when working with a limited amount of labeled data.
This paper discusses the question of heat flux distribution between bristle package and rotor during a rubbing event. A three-dimensional Computational Fluid Dynamics (3D CFD) model of the brush seal ...test rig installed at the Institute of Thermal Turbomachinery (ITS) was created. The bristle package is modelled as a porous medium with local non-thermal equilibrium. The model is used to numerically recalculate experimentally conducted rub tests on the ITS test rig. The experimentally determined total frictional power loss serves as an input parameter to the numerical calculation. By means of statistical evaluation methods, the ma in influences on the heat flux distribution and the maximum temperature in the frictional contact are determined. The heat conductivity of the rotor material, the heat transfer coefficients at the bristles and the rubbing surface were identified as the dominant factors.
Summary
The emission requirements for jet engines are becoming more stringent and the combustion process determines pollutant emissions. Therefore, we model the distribution of fuel drops generated ...by a fuel injector in a jet engine, which can be assumed to be a five‐dimensional problem in terms of drop size, x‐position, y‐position, x‐velocity and y‐velocity. The data are generated by numerical simulations of the fuel atomization process for several jet engine operating conditions. In combustion simulations, the variables are usually assumed to be independent at the start of the simulation, which is clearly not so as our data show. The dependence between some of the variables is non‐monotone and asymmetric, which makes the modelling task difficult. Our aim is to provide a realistic parametric model for the dependence structure. For this, we employ vine copulas which provide a flexible way to construct a multivariate distribution function. However, we need to use non‐standard bivariate copulas as building blocks. Using this copula representation enables us to create realistic samples of fuel spray droplets which improve the prediction of the combustion process and the pollutant emissions. Moreover, this approach is significantly faster than solving the set of differential equations describing fuel disintegration.
Sand ingestion is highly detrimental for gas turbines because it leads to erosion and corrosion of engine components, accelerating material fatigue and contributing to global engine failure. In this ...paper the high velocity impact of a molten sand particle onto a solid wall is investigated by means of the Smoothed Particles Hydrodynamics method where the three phases are taken into account. Nominal conditions are a 25 μm particle composed of molten sand (dynamic viscosity μl=11 Pa·s) impacting the wall at a velocity of 250 m/s. The influence of different parameters are explored such as the mechanical properties of the molten sand particle (density, viscosity, surface tension), the impact conditions (velocity magnitude, particle size and angle of impact) as well as the particle shape (sphere or cube with different geometrical features impacting the wall). It is found that the particles do not form a lamella during the impact but mostly conserve its initial shape. It is also confirmed that sharp features such as edges lead to a larger normal pressure at the impact location. Correlations to quantify (i) the spread factor, (ii) the maximum and mean impact force and impact pressure and (iii) the slip distance are derived for the first time based on the investigated parameters. The importance of these correlations is that they provide information needed to implement low-order models for studying impact and deposition of molten sand in engineering simulations.
•Discussed those effects and presents literature regarding the known effects and data.•Presents a new procedure to easily determine the emissivity.•Presents a new calibration approach to consider ...effects of angle of view (introduced by e.g. curved surfaces).•Validates the new approach with an experiment.•Presents an error estimation.
Infrared Thermography is a capable tool for resolving surface temperatures with high resolution and accuracy, even on complex surfaces. With current calibration techniques, the surface emissivity needs to be constant and close to unity to ensure a low calibration error. This is commonly achieved with special surface coatings. These coatings however, show a reduction of emissivity with increasing angle of view. Performing a state of the art in situ calibration with temperature calibration points (e.g. thermocouples) thus can lead to a measurement error on curved surfaces when assuming constant emissivity. In this paper, an adapted calibration procedure is presented considering the effects of surface topology. The process is closely linked to the basic in situ calibration with only few additional steps needed. If the angle of view θ(e. g. the camera position) is known in the experiment, this new procedure allows a correction of the induced effects and thus a reduction of measurement uncertainty. This can be achieved by only using a single additional in situ calibration pair. Data from a validation experiment is presented for two different camera systems (MWIR, LWIR), showing that the error can be reduced from ΔTS,rel>5% to ΔTS,rel<1.5% at θ≈65°, allowing the acquisition of temperature data on complex surfaces. With exact emissivity functions and camera positions, temperature acquisition can even be performed up to angles of view of θ≈80° with tolerable error.
A new experimental study is presented for a combustor with a double-wall cooling design. The inner wall at the hot gas side features effusion cooling with 7-7-7 laidback fan-shaped holes, and the ...outer wall at the cold side features an impingement hole pattern with circular holes. Data have been acquired to assess the thermal and aerodynamic behavior of the setup using a new, scaled up, engine-similar test rig. Similarity includes Reynolds, Nusselt, and Biot numbers for hot gas and coolant flow. Different geometrical setups are studied by varying the cavity height between the two walls and the relative alignment of the two hole patterns at several different blowing ratios. This article focuses on the thermal performance of the setup. The temperature data are acquired using two infrared systems on either side of the effusion wall specimen. In addition to cooling effectiveness evaluations, finite element simulations are performed, yielding the locally resolved wall heat fluxes. Results are presented for three cavity heights and two longitudinal specimen alignments. The results show that the hot gas side total cooling effectiveness can achieve values as high as 90% and is mainly influenced by the effusion coverage. Impingement cooling has a small influence on overall effectiveness, and the area of influence is mainly located upstream where effusion cooling is not built up completely. The analyzed geometric variations show a major influence on cavity flow and impingement heat transfer. Small cavities lead to constrained flow and high local Nusselt numbers, while larger cavities show more equalized Nusselt number distributions. A present misalignment shows especially high influence at small cavity heights. The largest cavity height, in general, showed a decrease in heat transfer due to reduced jet momentum.
The formation of pollutant emissions in jet engines is closely related to the fuel distribution inside the combustor. Hence, the characteristics of the spray formed during primary breakup are of ...major importance for an accurate prediction of the pollutant emissions. Currently, an Euler–Lagrangian approach for droplet transport in combination with combustion and pollutant formation models is used to predict the pollutant emissions. The missing element for predicting these emissions more accurately is well defined starting conditions for the liquid fuel droplets as they emerge from the fuel nozzle. Recently, it was demonstrated that the primary breakup can be predicted from first principles by the Lagrangian, mesh-free, Smoothed Particle Hydrodynamics (SPH) method. In the present work, 2D Direct Numerical Simulations (DNS) of a planar prefilming airblast atomizer using the SPH method are presented, which capture most of the breakup phenomena known from experiments. Strong links between the ligament breakup and the resulting spray in terms of droplet size, trajectory and velocity are demonstrated. The SPH predictions at elevated pressure conditions resemble quite well the effects observed in experiments. Significant interdependencies between droplet diameter, position and velocity are observed. This encourages to employ such multidimensional interdependence relations as a base for the development of primary atomization models.
With the increasing demand for efficient and accurate numerical simulations of spray combustion in jet engines, the necessity for robust models to enhance the capabilities of spray models has become ...imperative. Existing approaches often rely on ad hoc determinations or simplifications, resulting in information loss and potentially inaccurate predictions for critical spray characteristics, such as droplet diameters, velocities, and positions, especially under extreme operating conditions or temporal fluctuations. In this study, we introduce a novel approach to modeling multivariate spray characteristics using Gaussian mixture models (GMM). By applying this approach to spray data obtained from numerical simulations of the primary atomization in air-blast atomizers, we demonstrate that GMMs effectively capture the spray characteristics across a wide range of operating conditions. Importantly, our investigation reveals that GMMs can handle complex non-linear dependencies by increasing the number of components, thereby enabling the modeling of more complex spray statistics. This adaptability makes GMMs a versatile tool for accurately representing spray characteristics even under extreme operating conditions. The presented approach holds promise for enhancing the accuracy of spray combustion modeling, offering an improved injection model that accurately captures the underlying droplet distribution. Additionally, GMMs can serve as a foundation for constructing meta models, striking a balance between the efficiency of low-order approaches and the accuracy of high-fidelity simulations.
A new experimental study is presented for a combustor with a double-wall cooling design. The inner wall at the hot gas side features effusion cooling with 7-7-7 laidback fan-shaped holes, and the ...outer wall at the cold side features an impingement hole pattern with circular holes. Data are acquired to asses the thermal and aerodynamic behavior of the setup, using a new, scaled up, engine similar test rig. Similarity includes Reynolds, Nusselt and Biot numbers for hot gas and coolant flow. Different geometrical setups are studied by varying the cavity height between the two walls and the relative alignment of the two hole patterns at two different impingement Reynolds numbers. This article focuses on the aerodynamic performance of the setup. Instationary flow data are acquired, using a high speed stereo PIV setup. For each geometrical configuration, approximately 20 planes are recorded with a data rate of 1000 Hz by traversing the flow region of interest in the cavity between the two specimen. This fine resolution allows the reconstruction of 3D flow fields for the mean data values and an extensive analysis of transient phenomena at each plane. Time averaged data and jet-center plane transient data are presented in detail. The results show a complex flow field with a hexagonal vortex pattern in the cavity, which is mainly influenced by the cavity height and the relative alignment of the two walls. The jet Reynolds number shows small influence when analyzing normalized data. Small cavity heights show a less developed flow field with less stable vortex systems. The alignment shows a similar influence on vortex system stability, with the aligned case performing better. Additionally, statistical analysis of the jet flow and frequency domain analysis of the jet and the effusion flow are presented, showing the damping capability of the cavity, especially at increased cavity heights, and a residual low frequency pulsation of the effusion cooling inflow.
In this study, the probabilistic, data driven nature of the generative adversarial neural networks (GANs) was utilized to conduct virtual spray simulations for conditions relevant to aero engine ...combustors. The model consists of two sub-modules: (i) an autoencoder converting the variable length droplet trajectories into fixed length, lower dimensional representations and (ii) a Wasserstein GAN that learns to mimic the latent representations of the evaporating droplets along their lifetime. The GAN module was also conditioned with the injection location and the diameters of the droplets to increase the generalizability of the whole framework. The training data was provided from highly resolved 3D, transient Eulerian–Lagrangian, large eddy simulations conducted with OpenFOAM. Neural network models were created and trained within the open source machine learning framework of PyTorch. Predictive capabilities of the proposed method was discussed with respect to spray statistics and evaporation dynamics. Results show that conditioned GAN models offer a great potential as low order model approximations with high computational efficiency. Nonetheless, the capabilities of the autoencoder module to preserve local dependencies should be improved to realize this potential. For the current case study, the custom model architecture was capable of conducting the simulation in the order of seconds after a day of training, which had taken one week on HPC with the conventional CFD approach for the same number of droplets (200,000 trajectories).
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•GANs were combined with autoencoders (AE) to conduct virtual spray simulations.•AE converts variable length droplet trajectories into fixed length representations.•Conditioned GANs mimic the latent representations of the evaporating droplets.•Training data was provided from highly resolved Eulerian-Lagrangian LES simulations.•Predictive accuracy highly depends on encoding methodology.
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