bluuebunny/crossref_metadata_2025 huggingface dataset:
A Lesson on Operationalizing Machine Learning for Predictive Maintenance of Gas Turbines
Authors: Pileggi Paolo , Lazovik Elena , Snijders Ron , Axelsson Lars-Uno , Drost Sietse , Martinelli Giulio , de Grauw Max , Graff Joris
Published: September 2021

OEMs, service providers and end-users are moving from preventative to predictive maintenance to minimize the risk of unwanted power plant shut-downs and to maximize profitability. Digital Twin and Machine Learning (ML) are important techniques in this transformation as it complements and improves the traditional expert-based knowledge systems. There is a continued trend to use data-driven, so-called black-box, ML techniques as an improvement over traditional statistical approaches. However, these ML approaches suffer from low interpretability or explainability, making it hard to trust how or why a certain anomaly in the system is detected, limiting the trust in the prediction and making it much less likely to identify the real original cause of the problem. In this paper, we present our lesson learnt from operationalizing ML in a real-world use case that studied data from the 1.85 MWe OPRA OP16 all radial single-shaft gas turbine. We comment on the unforeseen obstacles we uncovered during our ML anomaly detection application and juxtapose them with the high potential value that our novel ML applications and explanation method can provide. ML may be enticing for the predictive maintenance of gas turbines but our lesson makes it clear that operationalizing ML goes beyond merely algorithm specifics. In line with the nature of the Digital Twin, it requires careful consideration of the specialized IT system supporting the algorithm, and the specific process it supports and in which it is deployed.
Hot-Wire Measurements in Non-Calibrated Conditions
Authors: Wang Yuexin , Guo Tao , Zhu Huiren
Published: September 2021

The hot-wire anemometer is a widely used instrumentation to determine flow velocity and to investigate flow quality. The main objective of this paper is to expand the application range of the hot wire by improving the measurement accuracy under non-calibrated temperature and pressure. According to the four kinds of heat transfer derivations, a new calibration method was carried out. Considering natural convection, heat radiation and heat conduction, and forced convection heat transfer, it can be found that the forced convection heat transfer plays a dominant role, and the main factor causing the change is the temperature. Forced convection heat transfer also changes with pressure, which affects heat transfer by affecting kinematic viscosity. Based on this, a new calibration method and formula of velocity were put forward, which can be used over a range of temperature and pressure, considering the changes of physical property of the calibration scheme were verified by numerical simulation. The numerical calculated results were compared, the average error was 0.69%, the maximum error was 2.9%. The results show that the calibration method has high accuracy in a certain range. This paper provides a new solution for the calibration of hot-wire anemometer, and expands the adaptability of hot-wire anemometer in the measurement of severe external conditions.
Cascade With Sinusoidal Leading Edges: Identification And Quantification of Deflection With Unsupervised Machine Learning
Authors: Corsini Alessandro , Delibra Giovanni , Tieghi Lorenzo , Tucci Francesco Aldo
Published: September 2021

One of the key issues in turbomachinery design is the identification of loss mechanisms and their quantification, both during preliminary design and in all subsequent optimization loops.

Over the years, many correlations have been proposed, accounting for different dissipative mechanisms that occur in blade-to-blade passages, such as the development of boundary layers, turbulent wake mixing, shockwaves, and secondary flows or off-design incidence.

In recent years, the fan industry started the production of more complex rotor geometries, characterized by sinusoidal leading and trailing edges, mostly to extend stall margin and to reduce noise emissions.

Literature still lacks a quantification of the losses introduced by the secondary motions released by serrated leading-edges. In this paper we investigate a design of experiments that entails 76 cases of a 3D flow cascade with NACA 4digit profiles with sinusoidal leading edges to measure losses according to the Lieblein’s approach.

The flow field simulated with RANS strategy was investigated using an unsupervised machine learning strategy to classify and isolate the turbulent wake downstream of the cascade with a combination of Principal Component Analysis and Gaussian Mixture clustering. Then a gradient boosting regressor was used to derive the correlation between input parameters and cascade deflection.
Mistuning and Damping of a Radial Turbine Wheel. Part 1: Fundamental Analyses and Design of Intentional Mistuning Pattern
Authors: Nakos Alex , Beirow Bernd , Zobel Arthur
Published: September 2021

The radial turbine impeller of an exhaust turbocharger is analyzed in view of both free vibration and forced response. Due to random blade mistuning resulting from unavoidable inaccuracies in manufacture or material inhomogeneities, localized modes of vibration may arise, which involve the risk of severely magnified blade displacements and inadmissibly high stress levels compared to the tuned counterpart. Contrary, the use of intentional mistuning (IM) has proved to be an efficient measure to mitigate the forced response.

Independently, the presence of aerodynamic damping is significant with respect to limit the forced response since structural damping ratios of integrally bladed rotors typically take extremely low values. Hence, a detailed knowledge of respective damping ratios would be desirable while developing a robust rotor design. For this, far-reaching experimental investigations are carried out to determine the damping of a comparative wheel within a wide pressure range by simulating operation conditions in a pressure tank.

Reduced order models are built up for designing suitable intentional mistuning patterns by using the subset of nominal system modes (SNM) approach introduced by Yang and Griffin [1], which conveniently allows for accounting both differing mistuning patterns and the impact of aeroelastic interaction by means of aerodynamic influence coefficients (AIC). Further, finite element analyses are carried out in order to identify appropriate measures how to implement intentional mistuning patterns, which are featuring only two different blade designs. In detail, the impact of specific geometric modifications on blade natural frequencies is investigated. The first part of this three-part paper is focused on designing the IM pattern. The second and third part following later on will address the topics (i) experimental validation after implementation of the IM pattern at rest and under rotation, and (ii) the development of an approach for fast estimating damping ratios in the design phase.
A Novel Gas Path Fault Diagnostic Model for Gas Turbine Based on Explainable Convolutional Neural Network With LIME Method
Authors: Yao Chen , Yueyun Xi , Jinwei Chen , Huisheng Zhang
Published: September 2021

Gas turbine is widely used in aviation and energy industries. Gas path fault diagnosis is an important task for gas turbine operation and maintenance. With the development of information technology, especially deep learning methods, data-driven approaches for gas path diagnosis are developing rapidly in recent years. However, the mechanism of most data-driven models are difficult to explain, resulting in lacking of the credibility of the data-driven methods. In this paper, a novel explainable data-driven model for gas path fault diagnosis based on Convolutional Neural Network (CNN) using Local Interpretable Model-agnostic Explanations (LIME) method is proposed. The input matrix of CNN model is established by considering the mechanism information of gas turbine fault modes and their effects. The relationship between the measurement parameters and fault modes are considered to arrange the relative position in the input matrix. The key parameters which contributes to fault recognition can be achieved by LIME method, and the mechanism information is used to verify the fault diagnostic proceeding and improve the measurement sensor matrix arrangement. A double shaft gas turbine model is used to generate healthy and fault data including 12 typical faults to test the model. The accuracy and interpretability between the CNN diagnosis model built with prior mechanism knowledge and built by parameter correlation matrix are compared, whose accuracy are 96.34% and 89.46% respectively. The result indicates that CNN diagnosis model built with prior mechanism knowledge shows better accuracy and interpretability. This method can express the relevance of the failure mode and its high-correlation measurement parameters in the model, which can greatly improve the interpretability and application value.
High Speed OH PLIF Measurements of Combustor Effusion Films in a High Pressure, Liquid Fueled Combustor
Authors: Chandh Aravind , Patel Shivam , Bibik Oleksandr , Adhikari Subodh , Wu David , Rezvani Reza , Davis Dustin , Lieuwen Tim , Emerson Benjamin
Published: September 2021

This paper presents measurements of 10 kHz OH planar laser induced fluorescence (PLIF) with an objective to study the interaction of effusion cooling with the flame and hot combustion products in the liquid fueled combustor. The combustor rig is a single sector representation a rich-burn/quick-quench/lean-burn (RQL) configuration. It consists of a swirl nozzle, dilution, and effusion jets. The rig is operated under realistic aircraft conditions, including elevated combustor inlet temperature, and elevated pressure. The PLIF laser sheet was arranged perpendicular and parallel to the liner at distinct liner locations. Parametric variations of important parameters, namely equivalence ratio, and effusion cooling air blowing ratio are conducted to investigate their effect on flame-effusion jet interactions. The PLIF images were analyzed using several data reduction techniques to de-noise the images and identify patterns in the effusion jet-flame interactions. Results show that the effusion jets are highly unsteady, interacting strongly with the turbulent flame from the swirl nozzle and the dilution jets. This work is an extension of recent effusion film mixing studies that were performed with acetone PLIF under non-reacting conditions.
Operational Scenarios of a Gas Turbine Using Exhaust Gas Recirculation for Carbon Capture
Authors: Burnes Dan , Saxena Priyank
Published: September 2021

Finding viable economic solutions to significantly reduce or eliminate greenhouse gas emissions from energy and transportation products in the near future is paramount for the long-term survival of fossil fuel burning systems. One of which, the industrial gas turbine, has proven for decades to be a versatile energy system providing high efficiencies in combined heat and power applications melding well within existing infrastructure. Applying appropriate technology, the industrial gas turbine could be augmented to both sequester carbon and improve efficiency leveraging the full heating value of the fuel. The paper considers a more detailed operational assessment of a gas turbine using exhaust gas recirculation (EGR) to enable cost effective post combustion carbon sequestration and utilization. In this study, the effect of using EGR will be assessed at part load and throughout the operational envelope quantifying component and overall performance, detailed combustion characteristics, and maximizing the utilization of exhaust heat and sequestered carbon in various applications. This study will also attempt to quantify true carbon footprint of gas turbine installations and endeavor to understand the relative change of replacing the gas turbine with an all-electric alternative. Fundamentally, we are looking to see if there is a future to sustain and adapt this significant natural gas (NG) energy infrastructure to a net-zero carbon emissive future by 2050.
A Detailed Loss Analysis Methodology for Centrifugal Compressors
Authors: Zhang Luying , Kritioti Loukia , Wang Peng , Zhang Jiangnan , Zangeneh Mehrdad
Published: September 2021

A deep understanding of loss mechanisms inside a turbomachine is crucial for the design and analysis work. By quantifying the various losses generated from different flow mechanisms, a targeted optimization can be carried out on the blading design. In this paper an evaluation method for computational fluid dynamics simulations has been developed to quantify the loss generation based on entropy production in the flow field. A breakdown of losses caused by different mechanisms (such as skin friction, secondary flow, tip clearance vortex and shock waves) is achieved by separating the flow field into different zones. Each zone is defined by the flow physics rather than by geometrical locations or empirical correlations, which makes the method a more general approach and applicable to different machine types.

The method has been applied to both subsonic and transonic centrifugal compressors, where internal flow is complex due to the Coriolis acceleration and the curvature effect. An evaluation of loss decomposition is obtained at various operational conditions. The impact of design modification is also assessed by applying the same analysis to an optimized design.
Preliminary Study of Heat Pipe Turbine Vane Cooling in the NASA N+3 Reference Engine
Authors: McNichols Ezra O. , Jones Scott M. , Mirhashemi Arman , Juangphanich Paht , Shyam Vikram
Published: September 2021

This paper investigates the effects of implementing Heat Pipe Turbine Vane (HPTV) cooling in the NASA N+3 engine. The HPTV can be thought of as a heat pipe in the shape of a turbine vane, functioning as both an aerodynamic body and heat exchanger. The heat-absorbing section of the HPTV remains fixed in the vanes of the high-pressure turbine (HPT), while the heat-rejecting section can be placed in any stage of the low pressure turbine (LPT) as well as the bypass stream. The optimal location of the condensing (heat-rejecting) section is shown to be in the bypass stream for both HPT stages. The thrust-specific fuel consumption (TSFC) increased by 0.2%, which is mainly attributed to the elimination of air cooling in the second stage HPT vanes combined with the transfer of energy from the main gas path to elsewhere in the cycle. Air cooling is also eliminated in the first stage HPT vanes, but this cooling air is nonchargeable. A preliminary design is proposed and shown to demonstrate the desired performance and operates below the heat flux limitations of the heat pipe.
LES Based CFD Investigation of the Ignition Process in Lean Spray Burner
Authors: Andreini A. , Amerighi M. , Palanti L. , Facchini B.
Published: September 2021

During the last decades several new technologies were investigated in order to reduce the pollutant emissions and increase the overall engine efficiency. Unluckily, some of them including the lean direct injection spray combustion hinder the ignition performances of the combustor. Moreover, several expensive tests under very challenging operating conditions must be carried out to obtain the required certifications and assess the combustor behaviour with respect to the ignition process. Therefore, a deeper knowledge of the phenomena involved in the flame onset is mandatory to shorten the design process and achieve the required performances from the very beginning. In the last years, CFD simulations established as valid alternative to the experiments to investigate the complex phenomena involved in the ignition process. In fact, several examples are available in scientific literature about the use of simulations to predict the development of the flame starting from an initial kernel. In particular, LES proved to be a reliable tool to uncover new mechanisms of ignition and flame stabilization in gas turbines. In this work, two reactive LES of the ignition process were attempted using ANSYS Fluent 2019R1, with the aim of testing the Thickened Flame Model already implemented in the solver. In fact, compared to the previous versions, a new formulation for the efficiency function based on the pioneering work of Colin was made available. Such promising tool was validated against some detailed experimental results of a lean swirled flame, known as KIAI-CORIA spray flame. At first, a non-reactive and reactive LES were carried out to validate the cold field and the stabilized flame structure respectively. Finally, two ignition simulations were performed, from initial spark deposition up to flame stabilization or kernel quenching. All the obtained results have been extensively compared against the available experimental data showing that the employed simulation setup is fairly capable of describing the phenomena involved in the rig ignition.
A Numerical Sensitivity Study of Modeling Parameters in the Combustion of a Swirler
Authors: Al-Rifai Saja H. , Lin Cheng-Xian , Bohan Brian T. , Polanka Marc D.
Published: September 2021

In this study, a sensitivity analysis based on Reynolds Averaged Navier-Stokes (RANS) equations has been conducted to model the reacting turbulent flow in a swirler used in a (Disk-Oriented) gas-turbine using propane-air mixture. Several popular turbulence models and combustion models have been compared at different equivalence ratios. The effects of simulation parameters such as turbulence intensity, TKE Prandtl number, Schmidt number, and gravity direction have been studied. The contour plots of the species mass fraction (H2, OH) and temperature distributions from the CFD results are compared against the experimental visual results. The results showed that the realizable k-ε model and the steady diffusion flamelet model (SDF) are more suitable to model the turbulence combustion in the swirl domain. The computations further showed that the TKE Prandtl number and gravity are sensitive parameters to model the combustion from the swirler, while the Schmidt number and turbulence intensity showed less sensitivity.
Flamelet Versus Detailed Chemistry LES for a Liquid Fueled Gas-Turbine Combustor: A Comparison of Accuracy and Computational Cost
Authors: Karalus Megan , Thakre Piyush , Goldin Graham , Brandt Dustin
Published: September 2021

A Honeywell liquid-fueled gas turbine test combustor, at idle conditions is numerically investigated in Simcenter STAR-CCM+ version 2020.3. This work presents Large Eddy Simulation (LES) results using both the Flamelet Generated Manifold (FGM) and detailed chemistry combustion models. Both take advantage of a hybrid chemical mechanism (HyChem) which has previously demonstrated very good accuracy for real fuels such as Jet-A with only 47 species. The objective of this work is to investigate the ability of FGM and detailed chemistry modeling to capture pollutant formation in an aero-engine combustor. Comparisons for NOx, CO, Unburned Hydrocarbons, and Soot are made, along with the radial temperature profile.

To fully capture potential emissions, a soot moment model, and Zeldovich NOx model are employed along with radiation. A comparison of results with and without chemistry acceleration techniques for detailed chemistry is included. Then, computational costs are assessed by comparing the performance and scalability of the simulations with each of the combustion models. It is found that the detailed chemistry case with clustering can reproduce nearly identical results to detailed chemistry without any acceleration if CO is added as a clustering variable. With the Lagrangian model settings chosen for this study, the detailed chemistry results compared more favorably with the experimental data than FGM, however there is uncertainty in the secondary breakup parameters. Sensitivity of the results to a key parameter in the spray breakup model are provided for both FGM and Complex Chemistry (CC). By varying this breakup rate, the FGM case can predict CO, NOx, and Unburned Hydrocarbons equally well. The smoke number, however, is predicted most accurately by CC. The cost for running detailed chemistry with clustering is found to be about 4 times that of FGM for this combustor and chemical mechanism.
Power and Compression Analysis of Power-To-Gas Implementations in Natural Gas Pipelines With Up to 100% Hydrogen Concentration
Authors: Allison Timothy C. , Klaerner John , Cich Stefan , Kurz Rainer , McBain Marybeth
Published: September 2021

The introduction of hydrogen or synthetic natural gas produced from renewable electricity into gas pipelines is being considered to enable decarbonization and energy storage. Prior published studies show that hydrogen concentrations over 20–30% are likely to require significant infrastructure modifications and that significant concentrations of hydrogen will decrease energy transport capacity and/or reduce transport efficiency due to higher compression work. A comparative analysis of four power-to-gas implementations utilizing alkaline electrolysis, steam methane reforming, and catalytic methanation at hydrogen concentrations from 0–100% is performed in order to quantify production and transport power requirements utilizing pipeline or electrical transport. The pipeline transport analysis evaluates the pipeline transport capacity, efficiency, and emissions at various hydrogen concentrations and their sensitivity to pipeline diameter and compressor station spacing. The results show that production costs for hydrogen and synthetic natural gas dominate the overall energy requirement, requiring more power to create product than will be delivered for end use. Pipeline transport power requirements also increase by a maximum factor of 6–8 depending on surface roughness at high hydrogen percentages, but pipeline transport losses are less than electrical transmission losses in all cases. The increased pipeline compression power increases CO2 emissions along the pipeline up to a peak value of 240% relative to pure methane at a mole fraction of 65% hydrogen, above which CO2 emissions reduce. An analysis of pipeline compression conditions shows that flow requirements for all cases exceed the capabilities of reciprocating compressors but are mostly within the capabilities of centrifugal compressors, although multiple bodies may be required at hydrogen concentrations exceeding approximately 40–85%.
Optimization of an Additively Manufactured U-Bend Channel Using A Surrogate-Based Bayesian Method
Authors: Ghosh Shinjan , Mondal Sudeepta , Wardell Ryan , Fernandez Erik , Kapat Jayanta S. , Ray Asok
Published: September 2021

CFD-based design optimization of turbulent flow scenarios is usually computationally expensive due to requirement of high-fidelity simulations. Previous studies prove that one way to reduce computational resource usage is to employ Machine Learning/Surrogate Modeling approaches for intelligent sampling of data points in the design space and is also an active area of research, but lacks enough experimental validation. Such a method has been used to optimize the shape of a U-bend channel for the minimization of pressure drop. U-bends are an integral part of serpentine cooling channels inside gas turbine blades but also contribute to total pressure drop by more than 20%. Reducing this pressure loss can help in more efficient cooling at low pumping power. A ‘U-bend’ or 180-degree bend shape has been used from literature, and a 16-dimensional design space has been created using parametrized spline curves, which creates a variety of shapes inside a given bounding box. A Latin Hypercube Sampling (LHS) was carried out for populating the initial design space with output data from the CFD simulation. After training a surrogate model on this data set, Bayesian updates were used to search for an optimum using an exploration vs exploitation approach. The resulting optimum shape showed that pressure drop was lowered by almost 30%, when compared to the baseline. The aim of this study is to experimentally validate this method using 3D printed models of the baseline and optimum channels respectively. Pressure taps placed across stream-wise locations on these channels helped to create a pressure profile for turbulent flow at a Reynolds number of 17000, for comparison to CFD results.
Adjoint Based Heat Conduction Optimization of Struts Parameters Within Hollow Blade
Authors: Ruan Yougang , Feng Zhenping
Published: September 2021

In gas turbine, the interaction between hot gas mainstream and blade solid region becomes more and more obvious as the turbine inlet temperature increases, thus heat conduction within the blade solid regions should be taken into consideration in optimization design process. In this paper, an adjoint-based optimization method for heat conduction problems in the solid region was built based on ANSYS Fluent and OpenFOAM Solver. The continuous adjoint equation and the corresponding boundary conditions for three typical conduction boundary conditions were derived in detail. To validate the correctness of this method, inverse design problems within the hollow cylinder and hollow blade were calculated, respectively. Inner shape inverse design of the hollow cylinder and the blade thickness inverse design were performed, and the target values were found successfully. Adjoint gradients were compared with finite-difference method or theoretical results. Then a Conjugate Heat Transfer (CHT) calculation was performed using ANSYS Fluent software, and the numerical methods were validated against the experimental results. An optimization of the struts place and thickness within hollow blade for average temperature was performed based on the CHT calculation results. Average temperature within the solid region of the optimized blade decreased 11.1K as compared to the original case.
Probabilistic Approach for Optimizing Uncertainties of Input Variables to Reach a Desired Confidence Level
Authors: Prots Andriy , Voigt Matthias , Mailach Ronald , Magin Philip , Danner Florian
Published: September 2021

The development of jet engines is typically accompanied by measurement campaigns to mitigate technical risks at an early design stage and to validate the specified performance. Often different configurations are compared in order to determine the superior one. But due to uncertainties in boundary conditions, geometry, and sensors, the derived performance values are subject to uncertainty as well. Assuming that the desired difference in performance metrics is small compared to the associated uncertainty, it can consequently be hard to conclude on the superiority of the configurations.

In this paper, a probabilistic approach is used to estimate the uncertainties of the output values of interest. For that, the measurement process is executed virtually taking the low-speed research compressor of Technische Universität Dresden as a test case. In the first step, a sampling for the uncertainties associated with boundary conditions and geometry is created. Then, Computational Fluid Dynamics (CFD) calculations for these samples are executed. Afterwards, virtual measurements are performed, for which the unbiased value of the measurement quantity of interest is extracted from the CFD calculation and then merged with a measurement uncertainty. Finally, these virtual measurements are evaluated in the same way as it is done for real measurements to derive the output values.

Evaluating the samples allows to obtain the associated uncertainties and hence the confidence levels of a measurement campaign which are to be optimized. The system behavior is first approximated with an inner meta model. This surrogate can be used to create an outer meta model describing the relationship between the variance of the input variables and the uncertainties of the output variables. By evaluating the outer meta model it is possible to identify important input variables effecting the uncertainty of the output variables. Finally, the outer meta model is used to find combinations of input variances, which on one hand lead to the desired output uncertainties and on the other hand are optimal with respect to the associated cost.
A Quantitative Approach for the Estimation of the Fouling Rate on the Stationary Parts of a Multistage Test Compressor
Authors: Vulpio Alessandro , Suman Alessio , Casari Nicola , Pinelli Michele
Published: September 2021

Gas turbine particle ingestion may lead to the deposition of contaminants in the compressor section, inducing the performance losses of the whole engine. The economic losses derived from this issue push great interest in the investigation of such a phenomenon from a numerical and experimental standpoint. This paper describes a quantitative approach to predict particle deposition on the vanes of an axial compressor starting from the flow field obtained employing CFD simulations. The results are then compared to the experiments performed on the Allison 250 C18 compressor unit subject to particle ingestion under controlled conditions. The results derived from the experimental and numerical investigations are presented, providing insight into the mass deposited on the vanes and the corresponding zones most affected by the particle deposition issue. The numerical model showed good agreement in the estimation of the predicted values of the deposited mass and the corresponding patterns through the compressor stages. The low-complexity approach proposed here, helps the designer to predict the contamination of the stationary rows starting from a simple set of single-phase numerical results. Furthermore, with the implementation of this approach into the design path, the designer could reduce the impact of fouling, looking at the effects of their solutions under the fouling-reduction light.
Non-Equilibrium Turbulence Modelling for Compressor Corner Separation Flows
Authors: Sun Wei
Published: September 2021

Corner separation is one type of the three-dimensional (3D) separated flows which is commonly observed at the junction of the blade suction surface and endwall of an axial compressor. The commonly used Reynolds-Averaged Navier-Stokes (RANS) turbulence models, namely Spalart-Allmaras (SA) and Menter’s Shear Stress Transport (SST) models, have been found to overpredict the size of corner separation. The physical reason is partly attributed to the underestimation of turbulence mixing between the mainstream flow and the endwall boundary-layer flow. This makes the endwall boundary layer unable to withstand the bulk adverse pressure gradients, and in turn leads to its premature separation from the endwall surface during its migration towards the endwall/blade suction surface corner.

The endwall flow characteristics within the compressor stator cascade are then studied to facilitate understanding the physical mechanisms that drive the formation of 3D flow structures, and the physical reasons that lead to RANS modelling uncertainties. It is found that the insufficient near-wall boundary layer mixing is partly due to the failure of both SA and SST models to reasonably model the non-equilibrium turbulence behaviors inside the endwall boundary layer, which is caused by the boundary layer skewness.

Based on the understanding of the skew-induced turbulence characteristics and its effect on mixing, a detailed effort is presented towards the physical-based modelling of the skew-induced non-equilibrium wall-bounded turbulence. The source terms in the SA and SST models that control mixing are identified and modified, in order to enhance mixing and strengthen the endwall boundary layer. The improved turbulence models are then validated against the compressor corner separation flows under various operating conditions to prove that the location and extent of the corner separation are more realistically predicted.
Electrochemical Defect Analysis (EC-D) of Additive Manufactured Components
Authors: Sous Florian , Herrig Tim , Bergs Thomas , Karges Florian , Feiling Nicole , Zeis Markus
Published: September 2021

Due to more freedom in design and flexibility in production, parts produced by additive manufacturing technologies (AM) offer a huge potential for the manufacture of turbomachinery components. Because of the layer by layer built structure, internal defects like cracks or gaseous pores can occur. These defects considerably reduce the mechanical properties and increase the importance of quality control, especially in the field of turbomachinery. Therefore, in this study, an electrochemical defect analysis (EC-D) of additive manufactured components is introduced, performed and validated in comparison to a nondestructive X-ray testing of the same part. A test rig was developed, which allows an alternation between electrochemical machining and subsequent optical documentation of each removed layer. The documentation of the surface and the macroscopic defects in the AM-parts are captured by an integrated camera system.
A Marine Turbocharger Compressor Multi-Point 3D Design Optimization Tool
Authors: Ntonas Konstantinos , Aretakis Nikolaos , Mathioudakis Konstantinos
Published: September 2021

A marine turbocharger 3D compressor design tool, implemented on an existing marine turbocharger retrofit platform is presented. It produces 3D centrifugal compressor geometry for optimal compressor retrofit. It encompasses two modules, allowing the design process to become fully automatic.

First, a 1D compressor multi-point design optimization process is carried out, aiming to provide a fast and reliable solution based on Turbocharged diesel Engine range of operation. Structural integrity is ensured by using simplified structural analysis. Dimensionless parameters are used as optimization variables, for a given nominal compressor mass flow and power. Then a CFD compressor multi-point design optimization process is carried out, producing optimized 3D compressor geometry. It complies with the Turbocharged diesel Engine range of operation, while structural integrity is ensured by using Finite Element analysis.

A turbocharger compressor design case study is presented. First, a turbocharger 1D compressor design is carried out, aiming to at least reconstituting the original diesel engine performance. This first module provides a reliable compressor initial geometry for the 3D design module. A fully 3D compressor design is then performed, using a CFD-FEA optimization process, in order to provide an improved retrofitting solution.

Comparison between the multi-point and the traditional one-point design method, shows that the multi-point method provides a wider SFC reduction in the range that the Diesel engine normally operates.
Challenges With Measuring Supercritical CO2 Compressor Performance When Approaching the Liquid-Vapor Dome
Authors: Mortzheim Jason , Hofer Doug , Priebe Stephan , McClung Aaron , Moore J. Jeffery , Cich Stefan
Published: September 2021

A team led by General Electric Research (GER) and Southwest Research Institute (SwRI) was tasked to design, build and test an advanced 4MW CO2 compressor that would operate near the liquid-vapor dome for Carbon Dioxide (CO2). The US Department of Energy (DoE) Solar Technologies Office (SETO) funded program was targeted towards a Concentrated Solar Power (CSP) plant where optimum power cycle efficiency can be obtained when operated close to the liquid-vapor dome where CO2 is a supercritical fluid (sCO2) as compression power is reduced in the main compressor. However, the CSP cycle and other related supercritical CO2 cycles (fossil, nuclear, waste heat recovery) have considerable compression challenges both mechanically and aerodynamically when operating with a high density fluid that exceeds 70% the density of water. The subject of this paper is highlighting the challenge in determining compressor performance using industry standard measurements. This application is the highest density industrial-scale centrifugal compressor in the world at 720 kg/m3.

This paper will investigate the uncertainty when measuring compressor efficiency using ASME PTC-10 instrumentation and the effect of the strong CO2 property variation when operating as a supercritical fluid, near the fluid-vapor dome. Prior work in this area by Wahl will be summarized and compared with the current compressor test program uncertainty. It will be shown that Wahl predicted high uncertainty as well although, the current testing program is even closer to the liquid-vapor dome than the test program under Wahl.

The uncertainty analysis has shown that traditional PTC-10 temperature measurements lead to high levels of uncertainty for sCO2 compression near the liquid-vapor dome. The uncertainty is driven by the large changes in thermodynamic properties of sCO2. These property changes are affected by the measured pressure and temperature; however, temperature measurement error is the primary contributor to uncertainty. Because of this, looking at alternate sCO2 property measurements was investigated. Higher quality localized pressure calibration, improving flow measurement accuracy, and measuring density in addition to temperature all significantly improved efficiency uncertainty. The authors confirmed the most significant measurement change is to measure pressure and density through either a densitometer or a Coriolis flow meter which provides a density measurement in conjunction with flow rate accuracy.
Implementation of Vortex Generator and Ramp to Improve Film Cooling Effectiveness on Blade Endwall
Authors: Hussain Sadam , Yan Xin
Published: September 2021

With the arrangements of vortex generators (VG) and ramp, film cooling effects on endwall near leading edge were numerically investigated at two blowing ratios (i.e. M = 0.5 and M = 1). To determine suitable numerical methods, mesh independency analysis and turbulence model selection were carried out based on the existing experimental data and LES results. With the numerical methods, flow fields near the leading edge were visualized to illustrate the influence of VG and ramp on coolant coverage on blade endwall. Film cooling effectiveness distributions on endwall and coolant trajectories near leading edge were compared among five different configurations with VG and ramp. The results show that the attachment of coolant on blade endwall is improved with the implement of VG between shaped-hole and leading edge. With the implementation of ramp on endwall between cooling hole and leading edge, the coolant spreads wider on endwall along pitchwise direction than the baseline case. With the implementation of VG and ramp, film cooling effect on endwall near leading edge is significantly improved as compared with the only ramp and only VG cases. Compared with the baseline case, pitchwise-averaged film cooling effectiveness on blade endwall near leading edge is increased by about 9%, and the film cooling effectiveness distributions on endwall along pitchwise direction become much uniform, for the case with both ramp and VG at M = 1.
Prediction of CO Emission Index for Aviation Gas Turbine Combustor Using Flamelet Generated Manifold Combustion Model
Authors: Patwardhan Saurabh , Nakod Pravin , Orsino Stefano , Yadav Rakesh , Xu Fang , Verma Vishwas
Published: September 2021

Carbon monoxide (CO) has been identified as one of the regulated pollutants and gas turbine manufacturers target to reduce the CO emission from their gas turbine engines. CO forms primarily when carbonous fuels are not burnt completely, or products of combustion are quenched before completing the combustion. Numerical simulations are effective tools that allow a better understanding of the mechanisms of CO formation in gas turbine engines and are useful in evaluating the effect of different parameters like swirl, fuel atomization, mixing etc. on the overall CO emission for different engine conditions like idle, cruise, approach and take off. In this paper, a thorough assessment of flamelet generated manifold (FGM) combustion model is carried out to predict the qualitative variation and magnitude of CO emission index with the different configurations of a Honeywell test combustor operating with liquid fuel under idle condition, which is the more critical engine condition for CO emission. The different designs of the test combustor are configured in such a way that they yield different levels of CO and hence are ideal to test the accuracy of the combustion model. Large eddy simulation (LES) method is used for capturing the turbulence accurately along with the FGM combustion model that is computationally economical compared to the detailed/reduced chemistry modeling using finite rate combustion model. Liquid fuel spray breakup is modeled using stochastic secondary droplet (SSD) model. Four different configurations of the aviation gas turbine combustor are studied in this work referring to earlier work by Xu et al. [1]. It is shown that the FGM model can predict CO trends accurately. The other global parameters like exit temperature, NOx emissions, pattern factor also show reasonable agreement with the test data. The sensitivity of the CO prediction to the liquid fuel droplet breakup model parameters is also studied in this work. Although the trend of CO variation is captured for different values of breakup parameters, the absolute magnitude of CO emission index differs significantly with the change in the values of breakup parameters suggesting that the spray has a larger impact on the quantitative prediction of CO emission. An accurate prediction of CO trends at idle conditions using FGM model extends the applicability of FGM model to predict different engine operating conditions for different performance criteria accurately.
Coupled Time and Passage Spectral Method for an Efficient Resolution of Turbomachinery Far Upstream Wakes
Authors: Wang Dingxi , Zhang Sen , Huang Xiuquan , Huang Huang
Published: September 2021

The paper proposes a novel numerical method called coupled time and passage spectral method for an efficient resolution of far upstream wakes in an unsteady analysis of flow field within generic multiple blade rows. The proposed method is a very simple and natural extension of the time spectral form harmonic balance method. By including inter blade phase angle and passage index in a truncated Fourier series, the proposed method is capable of circumventing the limitations of the harmonic balance method in dealing with zero frequency harmonics and time harmonics with same frequency but different inter blade phase angles. Different from the harmonic balance method, which seeks solution at different time instants of the same passage, the coupled spectral method seeks solutions at different passages and time instants. Same as the harmonic balance method, all these solutions are connected via a spectral operator. Coupled time and passage sampling is performed using the modified Gram Schmidt process to choose the time and passage pairs which give the most orthogonal rows of an inverse Fourier transform matrix. The coupled time and passage spectral method requires minimum change to an existing harmonic balance solver. A numerical case study has been provided in the paper to demonstrate the expected capability against the harmonic balance method.
Rotordynamic Characteristics of the Straight-Through Labyrinth Seal Based On the Applicability Analysis of Leakage Models Using Bulk-Flow Method
Authors: Wang Tianhao , Li Zhigang , Li Jun
Published: September 2021

Labyrinth seals are widely applied in the turbomachinery to control the leakage flow through the clearance between the stationary and rotating components. The fluid excitation induced by the labyrinth seal would deteriorate the stability of turbomachinery shaft. Developing an accurate and rapid prediction approach is crucial for the analysis of the fluid excitation rotordynamics of the labyrinth seal. The objective of this study is to analyze the applicability of leakage models using Bulk-Flow method and investigate the factors affecting the rotordynamic characteristics of the labyrinth seal. An elliptical orbit for rotor whirling was assumed in the one-control-volume Bulk-Flow model considering an isentropic process to predict the frequency-dependent rotordynamic coefficients of the labyrinth seal. The optimal leakage model was determined by comprehensively analyzing the applicability of 72 leakage models. Employing the optimal leakage model in the Bulk-Flow method, the effects of sealing clearance, pressure ratio, preswirl ratio and rotational speed on the rotordynamic characteristics of the labyrinth seal were investigated. The conclusions show that the Bulk-Flow method has an average prediction error of around 10% for the leakage flow rate, cross-coupled stiffness and direct damping when equipped with the optimal leakage model. Increasing preswirl ratio has a significantly destabilizing effect on the rotor stability, while the influence of increasing rotational speed is strongly related to preswirl direction. The effective damping of the labyrinth seal is sensitive to the inlet pressure, but insensitive to the outlet pressure and sealing clearance. The crossover frequency is almost impervious to the inlet pressure, outlet pressure and sealing clearance.
Correlating Time-Resolved Pressure Measurements With Rim Sealing Effectiveness for Real-Time Turbine Health Monitoring
Authors: DeShong Eric T. , Peters Benjamin , Berdanier Reid A. , Thole Karen A. , Paynabar Kamran , Gebraeel Nagi
Published: September 2021

Purge flow is bled from the upstream compressor and supplied to the under-platform region to prevent hot main gas path ingress that damages vulnerable under-platform hardware components. A majority of turbine rim seal research has sought to identify methods of improving sealing technologies and understanding the physical mechanisms that drive ingress. While these studies directly support the design and analysis of advanced rim seal geometries and purge flow systems, the studies are limited in their applicability to real-time monitoring required for condition-based operation and maintenance. As operational hours increase for in-service engines, this lack of rim seal performance feedback results in progressive degradation of sealing effectiveness, thereby leading to reduced hardware life.

To address this need for rim seal performance monitoring, the present study utilizes measurements from a one-stage turbine research facility operating with true-scale engine hardware at engine-relevant conditions. Time-resolved pressure measurements collected from the rim seal region are regressed with sealing effectiveness through the use of common machine learning techniques to provide real-time feedback of sealing effectiveness. Two modelling approaches are presented that use a single sensor to predict sealing effectiveness accurately over a range of two turbine operating conditions. Results show that an initial purely data-driven model can be further improved using domain knowledge of relevant turbine operations, which yields sealing effectiveness predictions within three percent of measured values.