Design of cooling systems for rotor platforms is critical due to the complex flow field and heat transfer phenomena related to the secondary flow structures originating at the blade leading edge. Horseshoe vortex and passage vortex are the fluid-dynamic features that largely influence the aerodynamic behaviour and the thermal protection level of the platform. The driving parameter is the coolant to mainstream momentum flux ratio, but several issues have to be considered in the design process of cooling technologies. As well acknowledged, an in-depth understanding of losses and heat transfer phenomena are deemed necessary to design effective cooling systems. In the present review, measurements and predictions on the behaviour of the HPT rotor cooled platform, obtained during the last two decades by several research groups, are gathered, described and analysed in terms of aerodynamic losses and heat transfer performance, and are compared with one another with respect to the effectiveness level that is ensured.
{"title":"The Aero-Thermal Performance of Purge Flow and Discrete Holes Film Cooling of Rotor Blade Platform in Modern High Pressure Gas Turbines: A Review","authors":"G. Barigozzi, H. Abdeh, S. Rouina, N. Franchina","doi":"10.3390/ijtpp7030022","DOIUrl":"https://doi.org/10.3390/ijtpp7030022","url":null,"abstract":"Design of cooling systems for rotor platforms is critical due to the complex flow field and heat transfer phenomena related to the secondary flow structures originating at the blade leading edge. Horseshoe vortex and passage vortex are the fluid-dynamic features that largely influence the aerodynamic behaviour and the thermal protection level of the platform. The driving parameter is the coolant to mainstream momentum flux ratio, but several issues have to be considered in the design process of cooling technologies. As well acknowledged, an in-depth understanding of losses and heat transfer phenomena are deemed necessary to design effective cooling systems. In the present review, measurements and predictions on the behaviour of the HPT rotor cooled platform, obtained during the last two decades by several research groups, are gathered, described and analysed in terms of aerodynamic losses and heat transfer performance, and are compared with one another with respect to the effectiveness level that is ensured.","PeriodicalId":36626,"journal":{"name":"International Journal of Turbomachinery, Propulsion and Power","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44622081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Optimization methods have been widely applied to the aerodynamic design of gas turbine blades. While applying optimization to high-fidelity computational fluid dynamics (CFD) simulations has proven capable of improving engineering design performance, a challenge has been overcoming the prolonged run-time due to the computationally expensive CFD runs. Reduced-order models and, more recently, machine learning methods have been increasingly used in gas turbine studies to predict performance metrics and operational characteristics, model turbulence, and optimize designs. The application of machine learning methods allows for utilizing existing knowledge and datasets from different sources, such as previous experiments, CFD, low-fidelity simulations, 1D or system-level studies. The present study investigates inserting a machine learning model that utilizes such data into a high-fidelity CFD driven optimization process, and hence effectively reduces the number of required evaluations of the CFD model. Artificial Neural Network (ANN) models were trained on data from over three thousand two-dimensional (2D) CFD analyses of turbine blade cross-sections. The trained ANN models were then used as surrogates in a nested optimization process alongside a full three-dimensional Navier–Stokes CFD simulation. The much lower evaluation cost of the ANN model allows for tens of thousands of design evaluations to guide the search of the best blade profiles to be used in the more expensive, high-fidelity CFD runs, improving the progress of the optimization while reducing the required computation time. It is estimated that the current workflow achieves a five-fold reduction in computational time in comparison to an optimization process that is based on three-dimensional (3D) CFD simulations alone. The methodology is demonstrated on the NASA/General Electric Energy Efficient Engine (E3) high pressure turbine blade and found Pareto front designs with improved blade efficiency and power over the baseline. Quantitative analysis of the optimization data reveals that some design parameters in the present study are more influential than others, such as the lean angle and tip scaling factor. Examining the optimized designs also provides insight into the physics, showing that the optimized designs have a lower amount of pressure drop near the trailing edge, but have an earlier onset of pressure drop on the suction side surface when compared to the baseline design, contributing to the observed improvements in efficiency and power.
{"title":"Optimization of Turbine Blade Aerodynamic Designs Using CFD and Neural Network Models","authors":"Chao Zhang, Matthew Janeway","doi":"10.3390/ijtpp7030020","DOIUrl":"https://doi.org/10.3390/ijtpp7030020","url":null,"abstract":"Optimization methods have been widely applied to the aerodynamic design of gas turbine blades. While applying optimization to high-fidelity computational fluid dynamics (CFD) simulations has proven capable of improving engineering design performance, a challenge has been overcoming the prolonged run-time due to the computationally expensive CFD runs. Reduced-order models and, more recently, machine learning methods have been increasingly used in gas turbine studies to predict performance metrics and operational characteristics, model turbulence, and optimize designs. The application of machine learning methods allows for utilizing existing knowledge and datasets from different sources, such as previous experiments, CFD, low-fidelity simulations, 1D or system-level studies. The present study investigates inserting a machine learning model that utilizes such data into a high-fidelity CFD driven optimization process, and hence effectively reduces the number of required evaluations of the CFD model. Artificial Neural Network (ANN) models were trained on data from over three thousand two-dimensional (2D) CFD analyses of turbine blade cross-sections. The trained ANN models were then used as surrogates in a nested optimization process alongside a full three-dimensional Navier–Stokes CFD simulation. The much lower evaluation cost of the ANN model allows for tens of thousands of design evaluations to guide the search of the best blade profiles to be used in the more expensive, high-fidelity CFD runs, improving the progress of the optimization while reducing the required computation time. It is estimated that the current workflow achieves a five-fold reduction in computational time in comparison to an optimization process that is based on three-dimensional (3D) CFD simulations alone. The methodology is demonstrated on the NASA/General Electric Energy Efficient Engine (E3) high pressure turbine blade and found Pareto front designs with improved blade efficiency and power over the baseline. Quantitative analysis of the optimization data reveals that some design parameters in the present study are more influential than others, such as the lean angle and tip scaling factor. Examining the optimized designs also provides insight into the physics, showing that the optimized designs have a lower amount of pressure drop near the trailing edge, but have an earlier onset of pressure drop on the suction side surface when compared to the baseline design, contributing to the observed improvements in efficiency and power.","PeriodicalId":36626,"journal":{"name":"International Journal of Turbomachinery, Propulsion and Power","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41737418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Duquesne, Joffrey Chanéac, Gabriel Mondin, J. Dombard
Boundary-layer flow separation is a common flow feature in many engineering applications. The consequences of flow separation in turbomachinery can be disastrous in terms of performance, stability and noise. In this context, flow separation is particularly difficult to understand because of its three-dimensional and confined aspects. Analyzing the skin friction lines is one key point to understanding and controlling this phenomenon. In the case of separation, the flow at the wall agglutinates around a manifold while the fluid from the boundary layer is ejected toward the flow away from the wall. The analysis of a three-dimensional separation zone based on topology is well addressed for a simple geometry. This paper aims at providing simple rules and methods, with a clear vocabulary based on mathematical background, to conduct a similar analysis with complex turbomachinery geometry (to understand a surface with a high genus). Such an analysis relies on physical principles that help in understanding the mechanisms of flow separation on complex geometries. This paper includes numerous typical turbomachinery surfaces: the stator row, vaneless diffuser, vaned diffuser, axial rotor and shrouded and unshrouded centrifugal impeller. Thanks to surface homeomorphisms, the generic examples presented can easily be converted into realistic shapes. Furthermore, classical turbomachinery problems are also addressed, such as periodicity or rotor clearance. In the last section, the proposed methodology is conducted on a radial diffuser of an industrial compressor. The flow at the wall is extracted from LES computations. This study presents the different closed separation zones in a high-efficiency operating condition.
{"title":"Topology Rule-Based Methodology for Flow Separation Analysis in Turbomachinery","authors":"P. Duquesne, Joffrey Chanéac, Gabriel Mondin, J. Dombard","doi":"10.3390/ijtpp7030021","DOIUrl":"https://doi.org/10.3390/ijtpp7030021","url":null,"abstract":"Boundary-layer flow separation is a common flow feature in many engineering applications. The consequences of flow separation in turbomachinery can be disastrous in terms of performance, stability and noise. In this context, flow separation is particularly difficult to understand because of its three-dimensional and confined aspects. Analyzing the skin friction lines is one key point to understanding and controlling this phenomenon. In the case of separation, the flow at the wall agglutinates around a manifold while the fluid from the boundary layer is ejected toward the flow away from the wall. The analysis of a three-dimensional separation zone based on topology is well addressed for a simple geometry. This paper aims at providing simple rules and methods, with a clear vocabulary based on mathematical background, to conduct a similar analysis with complex turbomachinery geometry (to understand a surface with a high genus). Such an analysis relies on physical principles that help in understanding the mechanisms of flow separation on complex geometries. This paper includes numerous typical turbomachinery surfaces: the stator row, vaneless diffuser, vaned diffuser, axial rotor and shrouded and unshrouded centrifugal impeller. Thanks to surface homeomorphisms, the generic examples presented can easily be converted into realistic shapes. Furthermore, classical turbomachinery problems are also addressed, such as periodicity or rotor clearance. In the last section, the proposed methodology is conducted on a radial diffuser of an industrial compressor. The flow at the wall is extracted from LES computations. This study presents the different closed separation zones in a high-efficiency operating condition.","PeriodicalId":36626,"journal":{"name":"International Journal of Turbomachinery, Propulsion and Power","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43375496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Conventional signal processing methods such as Principle Component Analysis (PCA) focus on the decomposition of signals in the 2D time–frequency domain. Parallel factor analysis (PARAFAC) is a novel method used to decompose multi-dimensional arrays, which focuses on analyzing the relevant feature information by deleting the duplicated information among the multiple measurement points. In the paper, a novel hybrid intelligent algorithm for the fault diagnosis of a mechanical system was proposed to analyze the multiple vibration signals of the centrifugal pump system and multi-dimensional complex signals created by pressure and flow information. The continuous wavelet transform was applied to analyze the high-dimensional multi-channel signals to construct the 3D tensor, which makes use of the advantages of the parallel factor decomposition to extract feature information of the complex system. The method was validated by diagnosing the nonstationary failure modes under the faulty conditions with impeller blade damage, impeller perforation damage and impeller edge damage. The correspondence between different fault characteristics of a centrifugal pump in a time and frequency information matrix was established. The characteristic frequency ranges of the fault modes are effectively presented. The optimization method for a PARAFAC-BP neural network is proposed using a genetic algorithm (GA) to significantly improve the accuracy of the centrifugal pump fault diagnosis.
{"title":"Multi-Channel High-Dimensional Data Analysis with PARAFAC-GA-BP for Nonstationary Mechanical Fault Diagnosis","authors":"Hanxin Chen, Shaoyi Li, Menglong Li","doi":"10.3390/ijtpp7030019","DOIUrl":"https://doi.org/10.3390/ijtpp7030019","url":null,"abstract":"Conventional signal processing methods such as Principle Component Analysis (PCA) focus on the decomposition of signals in the 2D time–frequency domain. Parallel factor analysis (PARAFAC) is a novel method used to decompose multi-dimensional arrays, which focuses on analyzing the relevant feature information by deleting the duplicated information among the multiple measurement points. In the paper, a novel hybrid intelligent algorithm for the fault diagnosis of a mechanical system was proposed to analyze the multiple vibration signals of the centrifugal pump system and multi-dimensional complex signals created by pressure and flow information. The continuous wavelet transform was applied to analyze the high-dimensional multi-channel signals to construct the 3D tensor, which makes use of the advantages of the parallel factor decomposition to extract feature information of the complex system. The method was validated by diagnosing the nonstationary failure modes under the faulty conditions with impeller blade damage, impeller perforation damage and impeller edge damage. The correspondence between different fault characteristics of a centrifugal pump in a time and frequency information matrix was established. The characteristic frequency ranges of the fault modes are effectively presented. The optimization method for a PARAFAC-BP neural network is proposed using a genetic algorithm (GA) to significantly improve the accuracy of the centrifugal pump fault diagnosis.","PeriodicalId":36626,"journal":{"name":"International Journal of Turbomachinery, Propulsion and Power","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46984516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the sCO2-HeRo project, the Chair of Turbomachinery at the University of Duisburg-Essen developed, built and tested a turbomachine with an integral design in which the compressor, generator and turbine are housed in a single hermetic casing. However, ball bearings limited operation because their lubricants were incompatible with supercritical CO2 (sCO2) and they had to operate in gaseous CO2 instead. To overcome this problem, the turbomachine was redesigned built and tested in the sCO2-4-NPP project. Instead of ball bearings, magnetic bearings are now used to operate the turbomachine with the entire rotor in sCO2. This paper presents the revised design, focusing on the usage of magnetic bearings. It also investigates whether the sCO2 limits the operating range. Test runs show that increasing the density and rotational speed results in greater deflection of the rotor and greater forces on the bearings. Measurements are also analyzed with respect to influence of the density increase on the destabilizing forces in the rotor–stator cavities. The conclusion is that for the operation of the turbomachine, the control parameters of the magnetic bearings must be adjusted not only to the rotor speed, but also to the fluid density. This enabled successful operation of the turbomachine, which reached a speed of about 40,000 rpm during initial tests in CO2.
{"title":"Turbomachine Operation with Magnetic Bearings in Supercritical Carbon Dioxide Environment","authors":"A. Hacks, D. Brillert","doi":"10.3390/ijtpp7020018","DOIUrl":"https://doi.org/10.3390/ijtpp7020018","url":null,"abstract":"In the sCO2-HeRo project, the Chair of Turbomachinery at the University of Duisburg-Essen developed, built and tested a turbomachine with an integral design in which the compressor, generator and turbine are housed in a single hermetic casing. However, ball bearings limited operation because their lubricants were incompatible with supercritical CO2 (sCO2) and they had to operate in gaseous CO2 instead. To overcome this problem, the turbomachine was redesigned built and tested in the sCO2-4-NPP project. Instead of ball bearings, magnetic bearings are now used to operate the turbomachine with the entire rotor in sCO2. This paper presents the revised design, focusing on the usage of magnetic bearings. It also investigates whether the sCO2 limits the operating range. Test runs show that increasing the density and rotational speed results in greater deflection of the rotor and greater forces on the bearings. Measurements are also analyzed with respect to influence of the density increase on the destabilizing forces in the rotor–stator cavities. The conclusion is that for the operation of the turbomachine, the control parameters of the magnetic bearings must be adjusted not only to the rotor speed, but also to the fluid density. This enabled successful operation of the turbomachine, which reached a speed of about 40,000 rpm during initial tests in CO2.","PeriodicalId":36626,"journal":{"name":"International Journal of Turbomachinery, Propulsion and Power","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42160026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Valdo Pagès, P. Duquesne, S. Aubert, L. Blanc, P. Ferrand, X. Ottavy, C. Brandstetter
The application of composite fans enables disruptive design possibilities but increases sensitivity to multi-physical resonance between aerodynamic, structure dynamic and acoustic phenomena. As a result, aeroelastic problems increasingly set the stability limit. Test cases of representative geometries without industrial restrictions are a key element of an open scientific culture but are currently non-existent in the turbomachinery community. In order to provide a multi-physical validation benchmark representative of near-future UHBR fan concepts, the open-test-case fan stage ECL5 was developed at Ecole Centrale de Lyon. The design intention was to develop a geometry with high efficiency and a wide stability range that can be realized using carbon fibre composites. This publication aims to introduce the final test case, which is currently fabricated and will be experimentally tested. The fan blades are composed of a laminate made of unidirectional carbon fibres and epoxy composite plies. Their structural properties and the ply orientations are presented. To characterize the test case, details are given on the aerodynamic design of the whole stage, structure dynamics of the fan and aeroelastic stability of the fan. These are obtained with a state-of-art industrial design process: static and modal FEM, RANS and LRANS simulations. Aerodynamic analysis focuses on performance and shows critical flow structures such as tip leakage flow, radial flow migration and flow separations. Mechanical modes of the fan are described and discussed in the context of aeroelastic interactions. Their frequency distribution is validated in terms of resonance risk with respect to synchronous vibration. The aeroelastic stability of the fan is evaluated at representative operating points with a systematic approach. Potential instabilities are observed far from the operating line and do not compromise experimental campaigns.
{"title":"UHBR Open-Test-Case Fan ECL5/CATANA","authors":"Valdo Pagès, P. Duquesne, S. Aubert, L. Blanc, P. Ferrand, X. Ottavy, C. Brandstetter","doi":"10.3390/ijtpp7020017","DOIUrl":"https://doi.org/10.3390/ijtpp7020017","url":null,"abstract":"The application of composite fans enables disruptive design possibilities but increases sensitivity to multi-physical resonance between aerodynamic, structure dynamic and acoustic phenomena. As a result, aeroelastic problems increasingly set the stability limit. Test cases of representative geometries without industrial restrictions are a key element of an open scientific culture but are currently non-existent in the turbomachinery community. In order to provide a multi-physical validation benchmark representative of near-future UHBR fan concepts, the open-test-case fan stage ECL5 was developed at Ecole Centrale de Lyon. The design intention was to develop a geometry with high efficiency and a wide stability range that can be realized using carbon fibre composites. This publication aims to introduce the final test case, which is currently fabricated and will be experimentally tested. The fan blades are composed of a laminate made of unidirectional carbon fibres and epoxy composite plies. Their structural properties and the ply orientations are presented. To characterize the test case, details are given on the aerodynamic design of the whole stage, structure dynamics of the fan and aeroelastic stability of the fan. These are obtained with a state-of-art industrial design process: static and modal FEM, RANS and LRANS simulations. Aerodynamic analysis focuses on performance and shows critical flow structures such as tip leakage flow, radial flow migration and flow separations. Mechanical modes of the fan are described and discussed in the context of aeroelastic interactions. Their frequency distribution is validated in terms of resonance risk with respect to synchronous vibration. The aeroelastic stability of the fan is evaluated at representative operating points with a systematic approach. Potential instabilities are observed far from the operating line and do not compromise experimental campaigns.","PeriodicalId":36626,"journal":{"name":"International Journal of Turbomachinery, Propulsion and Power","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43267204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
James Hammond, Nick Pepper, F. Montomoli, V. Michelassi
Computational Fluid Dynamics is one of the most relied upon tools in the design and analysis of components in turbomachines. From the propulsion fan at the inlet, through the compressor and combustion sections, to the turbines at the outlet, CFD is used to perform fluid flow and heat transfer analyses to help designers extract the highest performance out of each component. In some cases, such as the design point performance of the axial compressor, current methods are capable of delivering good predictive accuracy. However, many areas require improved methods to give reliable predictions in order for the relevant design spaces to be further explored with confidence. This paper illustrates recent developments in CFD for turbomachinery which make use of machine learning techniques to augment prediction accuracy, speed up prediction times, analyse and manage uncertainty and reconcile simulations with available data. Such techniques facilitate faster and more robust searches of the design space, with or without the help of optimization methods, and enable innovative designs which keep pace with the demand for improved efficiency and sustainability as well as parts and asset operation cost reduction.
{"title":"Machine Learning Methods in CFD for Turbomachinery: A Review","authors":"James Hammond, Nick Pepper, F. Montomoli, V. Michelassi","doi":"10.3390/ijtpp7020016","DOIUrl":"https://doi.org/10.3390/ijtpp7020016","url":null,"abstract":"Computational Fluid Dynamics is one of the most relied upon tools in the design and analysis of components in turbomachines. From the propulsion fan at the inlet, through the compressor and combustion sections, to the turbines at the outlet, CFD is used to perform fluid flow and heat transfer analyses to help designers extract the highest performance out of each component. In some cases, such as the design point performance of the axial compressor, current methods are capable of delivering good predictive accuracy. However, many areas require improved methods to give reliable predictions in order for the relevant design spaces to be further explored with confidence. This paper illustrates recent developments in CFD for turbomachinery which make use of machine learning techniques to augment prediction accuracy, speed up prediction times, analyse and manage uncertainty and reconcile simulations with available data. Such techniques facilitate faster and more robust searches of the design space, with or without the help of optimization methods, and enable innovative designs which keep pace with the demand for improved efficiency and sustainability as well as parts and asset operation cost reduction.","PeriodicalId":36626,"journal":{"name":"International Journal of Turbomachinery, Propulsion and Power","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47730350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With an increase in fluid densities in centrifugal compressors, fluid-structure interaction and coupled acoustoelastic modes receive growing attention to avoid machine failure. Besides the vibrational behavior of the impeller, acoustic modes building up in the side cavities need to be understood to ensure safe and reliable operation. In a coupled system, these structure and acoustic dominant modes influence each other. Therefore, a comprehensive overview of frequency shift effects in rotor-cavity systems is established based on findings in the literature. Additionally, experimental results on coupled mode pairs in a rotor-cavity test rig with a rotating disk under varying operating conditions are presented. Measurement results for structure dominant modes agree well with theoretical predictions. The development of a forward and a backward traveling wave is demonstrated for each mode in case of disk rotation. Conducted experiments reveal the occurrence of weakly and strongly coupled mode pairs as frequency shifts are observed that cannot solely be explained by “uncoupled mode effects”, such as the added mass, speed of sound, and stiffening effect, but indicate an additional coupling effect. However, the hypothesis of a bigger frequency shift for stronger coupled modes cannot be corroborated consistently. Only for the strongly coupled four nodal diameter mode pair in the “wide cavity” setup, a coupling effect is clearly visible in the form of mode veering.
{"title":"Acoustoelastic Modes in Rotor-Cavity Systems: An Overview on Frequency Shift Effects Supported with Measurements","authors":"Tina Unglaube, D. Brillert","doi":"10.3390/ijtpp7020015","DOIUrl":"https://doi.org/10.3390/ijtpp7020015","url":null,"abstract":"With an increase in fluid densities in centrifugal compressors, fluid-structure interaction and coupled acoustoelastic modes receive growing attention to avoid machine failure. Besides the vibrational behavior of the impeller, acoustic modes building up in the side cavities need to be understood to ensure safe and reliable operation. In a coupled system, these structure and acoustic dominant modes influence each other. Therefore, a comprehensive overview of frequency shift effects in rotor-cavity systems is established based on findings in the literature. Additionally, experimental results on coupled mode pairs in a rotor-cavity test rig with a rotating disk under varying operating conditions are presented. Measurement results for structure dominant modes agree well with theoretical predictions. The development of a forward and a backward traveling wave is demonstrated for each mode in case of disk rotation. Conducted experiments reveal the occurrence of weakly and strongly coupled mode pairs as frequency shifts are observed that cannot solely be explained by “uncoupled mode effects”, such as the added mass, speed of sound, and stiffening effect, but indicate an additional coupling effect. However, the hypothesis of a bigger frequency shift for stronger coupled modes cannot be corroborated consistently. Only for the strongly coupled four nodal diameter mode pair in the “wide cavity” setup, a coupling effect is clearly visible in the form of mode veering.","PeriodicalId":36626,"journal":{"name":"International Journal of Turbomachinery, Propulsion and Power","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41687778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Empirical correlations are still fundamental in the modern design paradigm of axial turbines. Among these, the prominent Ainley and Mathieson correlation (Ainley D. and Mathieson G., 1951, “A Method of Performance Estimation for Axial-Flow Turbines,” ARC Reports and Memoranda No. 2974) and its derivatives, plays a crucial role. In this paper, the underlying assumptions of the aforementioned models are discussed by means of a descriptive review, whilst an attempt is made to enhance their reliability and, potentially, accuracy in performance estimations. Closer investigation reveals an intriguing misuse of the lift coefficient in the secondary loss. In light of this, an enhanced model that, notably, builds upon the Zweifel criterion and the vortex penetration depth concept is developed and discussed. The obtained accuracy is subsequently assessed through CFD computations, employing a database comprising 109 cascades. The results indicate a 50% probability of achieving the ±15% error interval, which is twice as good as the most recent Aungier model (Aungier R., 2006, “Turbine Aerodynamics: Axial-Flow and Radial-Inflow Turbine Design and Analysis”, ASME Press, New York). Furthermore, the reliability of the proposed model is demonstrated by a reconstruction of the Smith chart, on the one hand, and a performance analysis, on the other. The reconstruction exhibits contours that conform to the original. The results of the performance study are compared with the CFD solutions of eight cascades working in off design conditions and confirm the need of the additionally included turbine design parameters, such as the axial velocity and the meanline radius ratios.
{"title":"A Reliable Update of the Ainley and Mathieson Profile and Secondary Correlations","authors":"Yumin Liu, P. Hendrick, Z. Zou, F. Buysschaert","doi":"10.3390/ijtpp7020014","DOIUrl":"https://doi.org/10.3390/ijtpp7020014","url":null,"abstract":"Empirical correlations are still fundamental in the modern design paradigm of axial turbines. Among these, the prominent Ainley and Mathieson correlation (Ainley D. and Mathieson G., 1951, “A Method of Performance Estimation for Axial-Flow Turbines,” ARC Reports and Memoranda No. 2974) and its derivatives, plays a crucial role. In this paper, the underlying assumptions of the aforementioned models are discussed by means of a descriptive review, whilst an attempt is made to enhance their reliability and, potentially, accuracy in performance estimations. Closer investigation reveals an intriguing misuse of the lift coefficient in the secondary loss. In light of this, an enhanced model that, notably, builds upon the Zweifel criterion and the vortex penetration depth concept is developed and discussed. The obtained accuracy is subsequently assessed through CFD computations, employing a database comprising 109 cascades. The results indicate a 50% probability of achieving the ±15% error interval, which is twice as good as the most recent Aungier model (Aungier R., 2006, “Turbine Aerodynamics: Axial-Flow and Radial-Inflow Turbine Design and Analysis”, ASME Press, New York). Furthermore, the reliability of the proposed model is demonstrated by a reconstruction of the Smith chart, on the one hand, and a performance analysis, on the other. The reconstruction exhibits contours that conform to the original. The results of the performance study are compared with the CFD solutions of eight cascades working in off design conditions and confirm the need of the additionally included turbine design parameters, such as the axial velocity and the meanline radius ratios.","PeriodicalId":36626,"journal":{"name":"International Journal of Turbomachinery, Propulsion and Power","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46345257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The increased demands of compact modern aero engine architectures have highlighted the problem of outlet guide vane (OGV) buffeting in off-design conditions. This structural response to aerodynamic excitations is characterised by increased vibration, risking structural fatigue. Investigations focused on understanding, mitigation and avoidance are therefore of high priority. OGV buffet is a type of transonic buffet caused by unsteady shock movement, but the exact parameters driving it are not fully understood. To try and understand them, this paper examines the buffet of a quasi-2D OGV geometry. Parametric studies of the incidence angle and inlet Mach number were performed. Forcing frequencies for both studies were found to be close to the experimentally detected frequency of vibration in the first bow mode, which demonstrates that buffet is driven by quasi-2D flow features. Increasing the inlet Mach number increased the dominant forcing frequency, whereas increasing the incidence yielded little change. Profiles of unsteady pressure amplitudes were shown to smoothly increase in magnitude with an increasing incidence and inlet Mach number.
{"title":"Two-Dimensional Investigation of the Fundamentals of OGV Buffeting","authors":"Jonah Harris, B. Lad, Sina Stapelfeldt","doi":"10.3390/ijtpp7020013","DOIUrl":"https://doi.org/10.3390/ijtpp7020013","url":null,"abstract":"The increased demands of compact modern aero engine architectures have highlighted the problem of outlet guide vane (OGV) buffeting in off-design conditions. This structural response to aerodynamic excitations is characterised by increased vibration, risking structural fatigue. Investigations focused on understanding, mitigation and avoidance are therefore of high priority. OGV buffet is a type of transonic buffet caused by unsteady shock movement, but the exact parameters driving it are not fully understood. To try and understand them, this paper examines the buffet of a quasi-2D OGV geometry. Parametric studies of the incidence angle and inlet Mach number were performed. Forcing frequencies for both studies were found to be close to the experimentally detected frequency of vibration in the first bow mode, which demonstrates that buffet is driven by quasi-2D flow features. Increasing the inlet Mach number increased the dominant forcing frequency, whereas increasing the incidence yielded little change. Profiles of unsteady pressure amplitudes were shown to smoothly increase in magnitude with an increasing incidence and inlet Mach number.","PeriodicalId":36626,"journal":{"name":"International Journal of Turbomachinery, Propulsion and Power","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46478538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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