In this work we examine the flow deviation and its relationship to critical choking, i.e., choking of the meridional component of velocity, in transonic turbine cascades operating with non-ideal compressible flows. To this purpose, a generalized expression of the corrected flow per unit area as a function of both the thermodynamic state and the molecular complexity of the working fluid, the Mach number, and the amount of swirl is derived. The trends of the corrected flow with respect to these quantities are used to infer physical insights on the flow deviation and on the operability of transonic turbine cascades in off-design conditions. Moreover, reduced-order models for the estimation of the flow deviation and the preliminary assessment of the losses have been developed and validated against the results of CFD simulations performed on a representative transonic turbine stator. Results suggest that flows of dense organic vapors exhibit larger deviations than those pertaining to compounds made of simple molecules, e.g., air. Furthermore, transonic turbines expanding dense vapors reach critical choking conditions at lower Mach numbers than the ones operating with simple molecules, and are affected by larger dissipation due to viscous mixing.
{"title":"Flow deviation and critical choking in transonic turbine cascades operating with non-ideal compressible flows","authors":"Francesco Tosto, A. Giuffrè, P. Colonna, M. Pini","doi":"10.33737/jgpps/151659","DOIUrl":"https://doi.org/10.33737/jgpps/151659","url":null,"abstract":"In this work we examine the flow deviation and its relationship to critical choking, i.e., choking of the meridional component of velocity, in transonic turbine cascades operating with non-ideal compressible flows. To this purpose, a generalized expression of the corrected flow per unit area as a function of both the thermodynamic state and the molecular complexity of the working fluid, the Mach number, and the amount of swirl is derived. The trends of the corrected flow with respect to these quantities are used to infer physical insights on the flow deviation and on the operability of transonic turbine cascades in off-design conditions. Moreover, reduced-order models for the estimation of the flow deviation and the preliminary assessment of the losses have been developed and validated against the results of CFD simulations performed on a representative transonic turbine stator. Results suggest that flows of dense organic vapors exhibit larger deviations than those pertaining to compounds made of simple molecules, e.g., air. Furthermore, transonic turbines expanding dense vapors reach critical choking conditions at lower Mach numbers than the ones operating with simple molecules, and are affected by larger dissipation due to viscous mixing.","PeriodicalId":53002,"journal":{"name":"Journal of the Global Power and Propulsion Society","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42906361","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}
Jiajun Cao, Qingbiao Li, Liping Xu, Rui Yang, Yuejin Dai
Current surrogate model methods that are widely used in optimization and design processes rely on manual parameterization to describe the geometry of objects. The loss of geometric information in this process limits the prediction accuracy of surrogate model. To tackle this problem, the new method directly picks important geometric features from surface meshes of fluid domain using Graph Neural Networks (GNNs) and predicts contours of fluid variables based on extracted information with Convolutional Neural Networks (CNNs). The prediction error of CNNs propagates backwards to train GNNs to select sensitive features from surface meshes. This framework reduces uncertainties introduced by manual parameterization and the loss of geometric information because the input of this new method is from the meshes used in the numerical simulations. With CNN and larger amount of extracted geometric information, this method can also predict higher dimensions distributions of flow variables rather than only several performance metrics. The nature of non-parametric representation of geometry also allows users to access designs defined by other parameterization methods to create a larger database. Additionally, thanks to the generic nature of the new method, it can be used for any other design or optimization processes governed by partial differential equations involving complicated geometries. To demonstrate this new method, a non-parametric surrogate model is built for a low-pressure steam turbine exhaust system (LPES). The new surrogate model uses 10 surfaces meshes of the LPES as input and it is used to predicts the energy flux contours at the exit of the last stage of the turbine. Altogether 582 designs have been generated, which contains two types of geometries defined by different methods. Among them, 550 cases are used for training, and 32 cases for testing. The power output of the last two stages of the turbine predicted by the surrogate model has average 0.86% difference compared with those of numerical simulations over a wide range of power ratings. The structural similarity index measure (SSIM) is used to measure the differences between the simulated and predicted contours at the exit of the last rotor, where the average SSIM of 640 contours is 0.9594 (1.0 being identical).
{"title":"Non-parametric surrogate model method based on machine learning with application on low-pressure steam turbine exhaust system","authors":"Jiajun Cao, Qingbiao Li, Liping Xu, Rui Yang, Yuejin Dai","doi":"10.33737/jgpps/151661","DOIUrl":"https://doi.org/10.33737/jgpps/151661","url":null,"abstract":"Current surrogate model methods that are widely used in optimization and design processes rely on manual parameterization to describe the geometry of objects. The loss of geometric information in this process limits the prediction accuracy of surrogate model. To tackle this problem, the new method directly picks important geometric features from surface meshes of fluid domain using Graph Neural Networks (GNNs) and predicts contours of fluid variables based on extracted information with Convolutional Neural Networks (CNNs). The prediction error of CNNs propagates backwards to train GNNs to select sensitive features from surface meshes. This framework reduces uncertainties introduced by manual parameterization and the loss of geometric information because the input of this new method is from the meshes used in the numerical simulations. With CNN and larger amount of extracted geometric information, this method can also predict higher dimensions distributions of flow variables rather than only several performance metrics. The nature of non-parametric representation of geometry also allows users to access designs defined by other parameterization methods to create a larger database. Additionally, thanks to the generic nature of the new method, it can be used for any other design or optimization processes governed by partial differential equations involving complicated geometries. To demonstrate this new method, a non-parametric surrogate model is built for a low-pressure steam turbine exhaust system (LPES). The new surrogate model uses 10 surfaces meshes of the LPES as input and it is used to predicts the energy flux contours at the exit of the last stage of the turbine. Altogether 582 designs have been generated, which contains two types of geometries defined by different methods. Among them, 550 cases are used for training, and 32 cases for testing. The power output of the last two stages of the turbine predicted by the surrogate model has average 0.86% difference compared with those of numerical simulations over a wide range of power ratings. The structural similarity index measure (SSIM) is used to measure the differences between the simulated and predicted contours at the exit of the last rotor, where the average SSIM of 640 contours is 0.9594 (1.0 being identical).","PeriodicalId":53002,"journal":{"name":"Journal of the Global Power and Propulsion Society","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48020678","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 drastic property changes of supercritical CO2 (SCO2) make the performance of SCO2 compressors different from that of conventional compressors. This study deals with the real-gas effect on the SCO2 compressor performance by theoretical analysis and numerical validation. A set of similitude parameters are firstly deduced by dimensional analysis. Then keeping these parameters unchanged, the performance variation of a SCO2 compressor is analyzed when the inlet flow condition changes in a certain temperature and pressure range. Results show that the proposed similitude method could accurately reflect the variation trend of SCO2 compressor performance under different inflow conditions. The real-gas effect enables the compressor to obtain higher pressure ratio with lower temperature rise. It is recommended that the inlet temperature of SCO2 compressor should be as close as possible to the critical temperature and the pressure should be about 150 kPa higher than the corresponding pseudo-critical pressure at the same temperature.
{"title":"A study of real-gas effect on SCO2 compressor performance using similitude method","authors":"Pengcheng Xu, Z. Zou","doi":"10.33737/jgpps/152462","DOIUrl":"https://doi.org/10.33737/jgpps/152462","url":null,"abstract":"The drastic property changes of supercritical CO2 (SCO2) make the performance of SCO2 compressors different from that of conventional compressors. This study deals with the real-gas effect on the SCO2 compressor performance by theoretical analysis and numerical validation. A set of similitude parameters are firstly deduced by dimensional analysis. Then keeping these parameters unchanged, the performance variation of a SCO2 compressor is analyzed when the inlet flow condition changes in a certain temperature and pressure range. Results show that the proposed similitude method could accurately reflect the variation trend of SCO2 compressor performance under different inflow conditions. The real-gas effect enables the compressor to obtain higher pressure ratio with lower temperature rise. It is recommended that the inlet temperature of SCO2 compressor should be as close as possible to the critical temperature and the pressure should be about 150 kPa higher than the corresponding pseudo-critical pressure at the same temperature.","PeriodicalId":53002,"journal":{"name":"Journal of the Global Power and Propulsion Society","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47851531","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}
A. Gaitanis, Antoine Laterre, F. Contino, W. De Paepe
In an energy mix driven by renewables, there is a need for small-scale highly efficient and flexible cogeneration units, such as Micro Gas Turbines (mGTs). These mGTs should perform transient operations and work at part-load to meet the power grid requirements. Therefore, full transient characterisation is necessary. One of the most crucial factors is accurately incorporating each component's dynamic behavior. Compressor and Turbine performance maps, although essential, are usually obtained in costly test rigs or CFD simulations. Also, the accurate modelling of the heat exchanger affects the efficiency of the whole cycle. The aim of this work is the development of real time transient mGT model, where we focus in the first step on accurate component modelling. Hence, an effective performance map representation method for mGT's compressor and turbine was developed. Moreover, a Recuperator 1-D numerical model is developed. Those modelling techniques were tested in a MATLAB/SIMULINK model in transient conditions. The fundamental target of this study is to enhance the fidelity of dynamic simulations for small-scale gas turbines. Key parameters like shaft speed and combustor inlet temperature, show deviation from experiments less than 1% which solidifies our aim to establish a general and efficient performance prediction.
{"title":"Towards real time transient mGT performance assessment: effective prediction using accurate component modelling techniques","authors":"A. Gaitanis, Antoine Laterre, F. Contino, W. De Paepe","doi":"10.33737/jgpps/150359","DOIUrl":"https://doi.org/10.33737/jgpps/150359","url":null,"abstract":"In an energy mix driven by renewables, there is a need for small-scale highly efficient and flexible cogeneration units, such as Micro Gas Turbines (mGTs). These mGTs should perform transient operations and work at part-load to meet the power grid requirements. Therefore, full transient characterisation is necessary. One of the most crucial factors is accurately incorporating each component's dynamic behavior. Compressor and Turbine performance maps, although essential, are usually obtained in costly test rigs or CFD simulations. Also, the accurate modelling of the heat exchanger affects the efficiency of the whole cycle. The aim of this work is the development of real time transient mGT model, where we focus in the first step on accurate component modelling. Hence, an effective performance map representation method for mGT's compressor and turbine was developed. Moreover, a Recuperator 1-D numerical model is developed. Those modelling techniques were tested in a MATLAB/SIMULINK model in transient conditions. The fundamental target of this study is to enhance the fidelity of dynamic simulations for small-scale gas turbines. Key parameters like shaft speed and combustor inlet temperature, show deviation from experiments less than 1% which solidifies our aim to establish a general and efficient performance prediction.","PeriodicalId":53002,"journal":{"name":"Journal of the Global Power and Propulsion Society","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42493671","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}
Atmospheric particulate pollutants are prone to deposit in aero-engine turbines due to high-temperature and high-velocity gas flows. The resulting deposition changes the blade profile, leading to a degradation of aerodynamic performance, increase in surface roughness, and blockage of film cooling holes and internal cooling channels, which further reduces cooling performance of the blade. Therefore, the blades are easily ablated, especially for the rotating parts as they have high rotating speed. In present study, unsteady simulations on the effects of particle deposition were carried out by demonstrating the migration trajectories and deposition distributions of particles in turbine rotor passages of an aero-engine that operates at real engine conditions. The effects of rotating speed, blade tip clearance and its cavity depth on the deposition and migration of contaminant particulates were examined. Results reveal that the deposition on the blade surfaces varies with the rotating speeds and the rotor tip clearances. The deposits are mainly concentrated on the pressure side of the blade where multiple rebounds of the particles are observed under a cruise operating condition. At a larger tip clearance, more particles flow into the tip clearance due to stronger leakage flow, and the squealer tip increases the capture efficiency of the particles on the blade tip.
{"title":"Unsteady simulations of deposition in a rotor passage of the first-stage turbine for an aero-engine","authors":"Zihan Hao, Xing Yang, Xiangyu Wang, Z. Feng","doi":"10.33737/jgpps/150549","DOIUrl":"https://doi.org/10.33737/jgpps/150549","url":null,"abstract":"Atmospheric particulate pollutants are prone to deposit in aero-engine turbines due to high-temperature and high-velocity gas flows. The resulting deposition changes the blade profile, leading to a degradation of aerodynamic performance, increase in surface roughness, and blockage of film cooling holes and internal cooling channels, which further reduces cooling performance of the blade. Therefore, the blades are easily ablated, especially for the rotating parts as they have high rotating speed. In present study, unsteady simulations on the effects of particle deposition were carried out by demonstrating the migration trajectories and deposition distributions of particles in turbine rotor passages of an aero-engine that operates at real engine conditions. The effects of rotating speed, blade tip clearance and its cavity depth on the deposition and migration of contaminant particulates were examined. Results reveal that the deposition on the blade surfaces varies with the rotating speeds and the rotor tip clearances. The deposits are mainly concentrated on the pressure side of the blade where multiple rebounds of the particles are observed under a cruise operating condition. At a larger tip clearance, more particles flow into the tip clearance due to stronger leakage flow, and the squealer tip increases the capture efficiency of the particles on the blade tip.","PeriodicalId":53002,"journal":{"name":"Journal of the Global Power and Propulsion Society","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47335694","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}
Oguzhan Murat, B. Rosic, Koichi Tanimoto, Ryo Egami
Since the renewable sources, which have gained great attention due to the low-carbon policies, are inherently intermittent, the conventional power generation systems will be in use to meet the power demand. These systems, however, must be capable of operating along with renewables, which will lead to a need for more operational flexibility with frequent system ramps. Therefore, understanding and control of thermal stresses and clearances are essential for improving flexibility of conventional power plants. Computational fluid dynamics tools are of great importance in predicting the turbomachinery flows design since the direct measurements of detailed and spatial flow and temperature distribution are often not trivial in the real engines. During shut-down regimes of steam turbines, natural convection takes place along with relatively weak forced convection which is not strong enough to prevent a rising thermal plume leading to a non-uniform cooling in the turbine cavities. Although natural and forced convection have been studied separately in the literature, mixed type of flows in turbine cavities have not been investigated extensively. This paper provides unique experimental data set for validation and development of the predictive tools, which is generated from the detailed flow field measurements in a test facility designed for mixed type of flows in the turbine casing cavities with engine representative conditions. Additionally, large eddy simulations have been performed and validated against the generated experimental data, to gain deeper insight into the flow field. Thus, this paper offers a great insight in these complex flow interactions and unique experimental data for enabling the flexible operations and the development of advanced turbulence modelling.
{"title":"Experimental and numerical investigations of mixed\u0000convection in turbine cavities for more flexible operations","authors":"Oguzhan Murat, B. Rosic, Koichi Tanimoto, Ryo Egami","doi":"10.33737/jgpps/150751","DOIUrl":"https://doi.org/10.33737/jgpps/150751","url":null,"abstract":"Since the renewable sources, which have gained great attention due to the low-carbon policies, are inherently intermittent, the conventional power generation systems will be in use to meet the power demand. These systems, however, must be capable of operating along with renewables, which will lead to a need for more operational flexibility with frequent system ramps. Therefore, understanding and control of thermal stresses and clearances are essential for improving flexibility of conventional power plants. Computational fluid dynamics tools are of great importance in predicting the turbomachinery flows design since the direct measurements of detailed and spatial flow and temperature distribution are often not trivial in the real engines. During shut-down regimes of steam turbines, natural convection takes place along with relatively weak forced convection which is not strong enough to prevent a rising thermal plume leading to a non-uniform cooling in the turbine cavities. Although natural and forced convection have been studied separately in the literature, mixed type of flows in turbine cavities have not been investigated extensively.\u0000\u0000This paper provides unique experimental data set for validation and development of the predictive tools, which is generated from the detailed flow field measurements in a test facility designed for mixed type of flows in the turbine casing cavities with engine representative conditions. Additionally, large eddy simulations have been performed and validated against the generated experimental data, to gain deeper insight into the flow field. Thus, this paper offers a great insight in these complex flow interactions and unique experimental data for enabling the flexible operations and the development of advanced turbulence modelling.","PeriodicalId":53002,"journal":{"name":"Journal of the Global Power and Propulsion Society","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41457931","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}
Corner separation is known to limit the operability of aeronautical compressors. Dedicated control devices such as guide fins are envisioned to reduce its negative effects. This paper presents a methodology based on RANS (Reynolds-Averaged Navier-Stokes) computations enabling to select guide fins efficient for that purpose. This methodology is applied to a reference case of linear compressor cascade operating at low Mach number (∼0.11). A set of 17 parameters is used to define two design spaces of interest, from which guide fins are generated. From then, an automated process generates and merges an unstructured mesh built around each guide fin with a fixed, structured mesh of reference representing a single channel of the cascade. Finally, RANS results on the resulting hybrid mesh are obtained using the Computational Fluid Dynamics solver elsA. This set up has proven successful in evaluating automatically hundreds of guide fins of various shapes. Several geometries illustrate the diversity of the design space. A selection of guide fins is then evaluated experimentally. Evolutions of the losses downstream of the cascade are compared to their respective RANS predictions, and to the reference case without guide fin. These experimental results validate the implemented methodology and show encouraging results in terms of loss redistribution brought by the control device.
{"title":"Experimental validation of a corner stall control methodology using parametrised guide fins","authors":"Gabriel Mondin, W. Riéra, P. Duquesne, X. Ottavy","doi":"10.33737/jgpps/152238","DOIUrl":"https://doi.org/10.33737/jgpps/152238","url":null,"abstract":"Corner separation is known to limit the operability of aeronautical compressors. Dedicated control devices such as guide fins are envisioned to reduce its negative effects. This paper presents a methodology based on RANS (Reynolds-Averaged Navier-Stokes) computations enabling to select guide fins efficient for that purpose. This methodology is applied to a reference case of linear compressor cascade operating at low Mach number (∼0.11). A set of 17 parameters is used to define two design spaces of interest, from which guide fins are generated. From then, an automated process generates and merges an unstructured mesh built around each guide fin with a fixed, structured mesh of reference representing a single channel of the cascade. Finally, RANS results on the resulting hybrid mesh are obtained using the Computational Fluid Dynamics solver elsA. This set up has proven successful in evaluating automatically hundreds of guide fins of various shapes. Several geometries illustrate the diversity of the design space. A selection of guide fins is then evaluated experimentally. Evolutions of the losses downstream of the cascade are compared to their respective RANS predictions, and to the reference case without guide fin. These experimental results validate the implemented methodology and show encouraging results in terms of loss redistribution brought by the control device.","PeriodicalId":53002,"journal":{"name":"Journal of the Global Power and Propulsion Society","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42474094","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}
Ao Zhang, Yang Liu, Jinguang Yang, Zhi Li, Chuan-Gui Zhang, Yiwen Li
Big data and machine learning are developing rapidly, and their applications in the aerodynamic design of centrifugal impellers and other turbomachinery have attracted wide attention. In this paper, centrifugal impellers with large flow coefficient (0.18–0.22) are taken as research objects. Firstly, through one-dimensional design and optimization, main one-dimensional geometric parameters of those centrifugal impellers are obtained. Subsequently, hundreds of samples of centrifugal impellers are obtained by using an in-house parameterization program and Latin hypercube sampling method. The NUMECA software is used for CFD calculations to build a sample library of centrifugal impellers. Then, applying the artificial neural network (ANN) to deal with the data in the sample library, a nonlinear model between the flow coefficients, the geometric parameters of these centrifugal impellers and the aerodynamic performance is constructed, which can replace CFD calculations. Lastly with the help of the multi-objective genetic algorithm, a global optimization is carried out to fulfull a rapid design optimization for centrifugal impellers with flow coefficients in the range of 0.18–0.22. Three examples provided in the paper show that the design and optimization method described above is faster and more reliable compared with the traditional design method. This method provides a new way for the rapid design of centrifugal impellers.
{"title":"Machine learning based design optimization of centrifugal impellers","authors":"Ao Zhang, Yang Liu, Jinguang Yang, Zhi Li, Chuan-Gui Zhang, Yiwen Li","doi":"10.33737/jgpps/150663","DOIUrl":"https://doi.org/10.33737/jgpps/150663","url":null,"abstract":"Big data and machine learning are developing rapidly, and their applications in the aerodynamic design of centrifugal impellers and other turbomachinery have attracted wide attention. In this paper, centrifugal impellers with large flow coefficient (0.18–0.22) are taken as research objects. Firstly, through one-dimensional design and optimization, main one-dimensional geometric parameters of those centrifugal impellers are obtained. Subsequently, hundreds of samples of centrifugal impellers are obtained by using an in-house parameterization program and Latin hypercube sampling method. The NUMECA software is used for CFD calculations to build a sample library of centrifugal impellers. Then, applying the artificial neural network (ANN) to deal with the data in the sample library, a nonlinear model between the flow coefficients, the geometric parameters of these centrifugal impellers and the aerodynamic performance is constructed, which can replace CFD calculations. Lastly with the help of the multi-objective genetic algorithm, a global optimization is carried out to fulfull a rapid design optimization for centrifugal impellers with flow coefficients in the range of 0.18–0.22. Three examples provided in the paper show that the design and optimization method described above is faster and more reliable compared with the traditional design method. This method provides a new way for the rapid design of centrifugal impellers.","PeriodicalId":53002,"journal":{"name":"Journal of the Global Power and Propulsion Society","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47531337","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 blade tip clearance is a crucial factor in the compressor performance and the aeroacoustics. There are usually main blades and splitter blades, two different types of blades in centrifugal compressors. Keeping almost the same work input, three different tip clearance configurations were designed in which the tip clearance gaps of main blades and splitter blades were uneven. Then experimental investigations were carried out to study the influence of uneven tip clearances on the aeroacoustic characteristics of centrifugal compressors. The results showed that larger main blade tip clearances or larger splitter blade tip clearances would induce rotating instabilities (RI) near flow instability boundary at low rotating speeds. However, the broadband noises below the blade passing frequency (BPF) in the case with uneven blade tip clearances were suppressed significantly which might be due to the incongruous interaction between the tip clearance leakage flows of main blades and splitter blades. In addition, the blade nonsynchronous vibrations (NSV) were observed in the analysis of the frequency spectrum of far-field noise in the case which had smaller main blade tip clearances and larger splitter blade tip clearances. Based on the jet core feedback theory, a physical explanation was given for NSV occurred in this case.
{"title":"Influence of uneven blade tip clearances on aeroacoustic characteristics of centrifugal compressors","authors":"Meijie Zhang, M. Qi, Hong Zhang","doi":"10.33737/jgpps/152718","DOIUrl":"https://doi.org/10.33737/jgpps/152718","url":null,"abstract":"The blade tip clearance is a crucial factor in the compressor performance and the aeroacoustics. There are usually main blades and splitter blades, two different types of blades in centrifugal compressors. Keeping almost the same work input, three different tip clearance configurations were designed in which the tip clearance gaps of main blades and splitter blades were uneven. Then experimental investigations were carried out to study the influence of uneven tip clearances on the aeroacoustic characteristics of centrifugal compressors. The results showed that larger main blade tip clearances or larger splitter blade tip clearances would induce rotating instabilities (RI) near flow instability boundary at low rotating speeds. However, the broadband noises below the blade passing frequency (BPF) in the case with uneven blade tip clearances were suppressed significantly which might be due to the incongruous interaction between the tip clearance leakage flows of main blades and splitter blades. In addition, the blade nonsynchronous vibrations (NSV) were observed in the analysis of the frequency spectrum of far-field noise in the case which had smaller main blade tip clearances and larger splitter blade tip clearances. Based on the jet core feedback theory, a physical explanation was given for NSV occurred in this case.","PeriodicalId":53002,"journal":{"name":"Journal of the Global Power and Propulsion Society","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43291112","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}
Compared with steady state data, engine transient state data cover a wider working scope of components, more complex operating conditions, and therefore can provide more abundant information regarding engine health status. To make the fullest use of engine transient data, this paper presents the methods on how to choose the proper measurements and health parameters when constructing an aeroengine gas path analysis system. The measurement selection based on sensitivity analysis is conducted, compared to which an effortless measurement selection method termed Minimum Identifiability Loss (MIL) is proposed. Aiming to reduce the estimation uncertainty, the analysis of maximal linearly independent group is presented to select optimal health parameters under the condition of limited measurements. Finally, the component health status identifiability analysis base on transient data also gives a good explanation to gas path analysis “smearing effect”.
{"title":"Parameter selection for aeroengine transient state gas path analysis","authors":"Kun Yang, Qiuye Tu, Yunhao Zeng, Jing Xuan","doi":"10.33737/jgpps/150548","DOIUrl":"https://doi.org/10.33737/jgpps/150548","url":null,"abstract":"Compared with steady state data, engine transient state data cover a wider working scope of components, more complex operating conditions, and therefore can provide more abundant information regarding engine health status. To make the fullest use of engine transient data, this paper presents the methods on how to choose the proper measurements and health parameters when constructing an aeroengine gas path analysis system.\u0000\u0000The measurement selection based on sensitivity analysis is conducted, compared to which an effortless measurement selection method termed Minimum Identifiability Loss (MIL) is proposed. Aiming to reduce the estimation uncertainty, the analysis of maximal linearly independent group is presented to select optimal health parameters under the condition of limited measurements. Finally, the component health status identifiability analysis base on transient data also gives a good explanation to gas path analysis “smearing effect”.","PeriodicalId":53002,"journal":{"name":"Journal of the Global Power and Propulsion Society","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47520468","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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