Mistuned Forced Response Predictions of an Embedded Rotor in a Multistage Compressor

2016 ◽  
Vol 138 (6) ◽  
Author(s):  
Fanny M. Besem ◽  
Robert E. Kielb ◽  
Paul Galpin ◽  
Laith Zori ◽  
Nicole L. Key
Keyword(s):  
Experimental Data ◽  
Steady State ◽  
Aerodynamic Performance ◽  
Forced Response ◽  
Response Analysis ◽  
Data Set ◽  
Multistage Compressor ◽  
The Individual ◽  
Decoupled Method ◽  
Tremendous Impact

This paper covers a comprehensive forced response analysis conducted on a multistage compressor and compared with the largest forced response experimental data set ever obtained in the field. The steady-state aerodynamic performance and stator wake predictions compare well with the experimental data, although losses are underestimated. Coupled and uncoupled unsteady simulations are conducted on the stator–rotor configuration. It is shown that the use of a decoupled method for forced response cannot yield accurate results for cases with strong inter-row interactions. The individual and combined contributions of the upstream and downstream stators are also assessed. The downstream stator is found to have a tremendous impact on the forced response predictions due to the constructive interactions of the two stator rows. Finally, predicted mistuned blade amplitudes are compared to mistuned experimental data. The average amplitudes match the experiments very well, while the maximum response amplitude is underestimated.

Forced Response Sensitivity of a Mistuned Rotor From an Embedded Compressor Stage

2015 ◽  
Author(s):  
Fanny M. Besem ◽  
Robert E. Kielb ◽  
Nicole L. Key
Keyword(s):  
Experimental Data ◽  
Forced Response ◽  
Symmetric System ◽  
Response Analysis ◽  
Cfd Simulations ◽  
Forcing Function ◽  
Wear And Tear ◽  
The Individual ◽  
The Impact ◽  
Interblade Phase Angle

The frequency mistuning that occurs due to manufacturing variations and wear and tear of the blades can have a significant effect on the flutter and forced response behavior of a blade row. Similarly, asymmetries in the aerodynamic or excitation forces can tremendously affect the blade responses. When conducting CFD simulations, all blades are assumed to be tuned (i.e. to have the same natural frequency) and the aerodynamic forces are assumed to be the same on each blade except for a shift in interblade phase angle. The blades are thus predicted to vibrate at the same amplitude. However, when the system is mistuned or when asymmetries are present, some blades can vibrate with a much higher amplitude than the tuned, symmetric system. In this research, we first conduct a deterministic forced response analysis of a mistuned rotor and compare the results to experimental data from a compressor rig. It is shown that tuned CFD results cannot be compared directly with experimental data because of the impact of frequency mistuning on forced response predictions. Moreover, the individual impact of frequency, aerodynamic, and forcing function perturbations on the predictions is assessed, leading to the conclusion that a mistuned system has to be studied probabilistically. Finally, all perturbations are combined and Monte-Carlo simulations are conducted to obtain the range of blade response amplitudes that a designer could expect.

Impact of Turbine Center Frame Wakes on Downstream Rows in Heavy-Duty Low-Pressure Turbine

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Sara Biagiotti ◽  
Juri Bellucci ◽  
Michele Marconcini ◽  
Andrea Arnone ◽  
Gino Baldi ◽  
...  
Keyword(s):  
Experimental Data ◽  
Low Pressure ◽  
Numerical Approach ◽  
Forced Response ◽  
Operating Conditions ◽  
Response Analysis ◽  
Test Case ◽  
Low Pressure Turbine ◽  
Harmonic Content ◽  
The Impact

Abstract In this work, the effects of turbine center frame (TCF) wakes on the aeromechanical behavior of the downstream low-pressure turbine (LPT) blades are numerically investigated and compared with the experimental data. A small industrial gas turbine has been selected as a test case, composed of a TCF followed by the two low-pressure stages and a turbine rear frame (TRF) before the exhaust plenum. Full annulus unsteady computations of the whole low-pressure module have been performed. Two operating conditions, full (100%) and partial (50%) load, have been investigated with the aim of highlighting the impact of TCF wakes convection and diffusion through the downstream rows. Attention was paid to the harmonic content of rotors’ blades. The results show a slower decay of the wakes through the downstream rows in off-design conditions compared with the design point. The analysis of the rotors’ frequency spectrum reveals that moving from design to off-design conditions, the effect of the TCF does not change significantly. The harmonic contribution of all turbine components has been extracted, highlighting the effect of statoric parts on the last LPT blade. The TCF harmonic content remains the most relevant from an aeromechanic point of view as per experimental evidence, and it is considered for an forced response analysis (FRA) on the last LPT blade itself. Finally, aerodynamic and aeromechanic predictions have been compared with the experimental data to validate the numerical approach. Some general design solutions aimed at mitigating the TCF wakes impact are discussed.

Impact of Turbine Center Frame Wakes on Downstream Rows in Heavy Duty Low Pressure Turbine

2019 ◽  
Author(s):  
Sara Biagiotti ◽  
Juri Bellucci ◽  
Michele Marconcini ◽  
Andrea Arnone ◽  
Gino Baldi ◽  
...  
Keyword(s):  
Experimental Data ◽  
Low Pressure ◽  
Forced Response ◽  
Point Of View ◽  
Operating Conditions ◽  
Response Analysis ◽  
Low Pressure Turbine ◽  
Harmonic Content ◽  
Partial Load ◽  
The Impact

Abstract In this work, the effects of Turbine Center Frame (TCF) wakes on the aeromechanical behavior of the downstream Low Pressure Turbine (LPT) blades are numerically investigated and compared with experimental data. A small industrial gas turbine has been selected as a test case, composed of a TCF followed by the two low pressure stages and a Turbine Rear Frame (TRF) before the exhaust plenum. Full annulus unsteady computations of the whole low-pressure module have been performed. Two operating conditions, full (100%) and partial (50%) load, have been investigated with the aim of highlighting the impact of TCF wakes convection and diffusion through the downstream rows. Attention was paid to the harmonic content of rotors’ blades. From an aerodynamic point of view, the results show a slower decay of the wakes through the downstream rows in off-design conditions as compared to the design point. The wakes generated by the struts at partial load persist throughout the domain outlet, while they are chopped and circumferentially transported by the rotors motion. This is due to the strong incidence variation at which the TCF works, which induces the growth of wide regions of separated flow on the rear part of the struts. Nevertheless, the analysis of the rotors’ frequency spectrum reveals that moving from design to off-design conditions, the effect of the TCF does not change significantly, thanks to the filtering action of the first LPT stage movable Nozzle Guide Vane (NGV). From unsteady calculations the harmonic contribution of all turbine components has been extracted, highlighting the effect of statoric parts on the last LPT blade. Anyhow the TCF harmonic content remains the most relevant from an aeromechanic point of view as per experimental evidence, and it is considered for a Forced Response Analysis (FRA) on the last LPT blade itself. Finally, aerodynamic and aeromechanic predictions have been compared with the experimental data to validate the numerical approach. In the last part of this paper some general design solutions, that can help mitigation of the TCF wakes impact, are discussed.

A Case Study of the Unsteady Response of a Hingeless Helicopter Rotor Blade

2019 ◽  
Author(s):  
Pratik Sarker ◽  
Uttam K. Chakravarty
Keyword(s):  
Mathematical Model ◽  
Steady State ◽  
Rotor Blade ◽  
Degrees Of Freedom ◽  
Forced Response ◽  
Helicopter Rotor ◽  
Mode Shapes ◽  
Response Analysis ◽  
Steady State Condition ◽  
Helicopter Rotor Blade

Abstract The helicopter is an essential means of transport for numerous tasks including carrying passengers and equipment, providing air medical services, firefighting, and other military and civil tasks. While in operation, the nature of the unsteady aerodynamic environment surrounding the rotor blades gives rise to a significant amount of vibration to the helicopter. In this study, the unsteady forced response of the Bo 105 hingeless helicopter rotor blade is investigated at the forward flight in terms of the coupled flapping, lead-lag, and torsional deformations. The mathematical model for the steady-state response of the rotor blade is modified to include the unsteady airfoil behavior by using the Theodorsen’s lift deficiency function for three degrees of freedom of motion. The nonlinear mathematical model is solved by the generalized method of lines in terms of the time-varying deflections of the rotor blade. The unsteady airloads are found to create larger deformations compared to that of the steady-state condition for a given advance ratio. The azimuth locations of the peak loadings also vary with different degrees of freedom. The first three natural frequencies and mode shapes of the rotor blade are presented. The model for the forced response analysis is validated by finite element results.

Application of Machine Learning to Interpret Steady State Drainage Relative Permeability Experiments

2021 ◽  
Author(s):  
Eric Sonny Mathew ◽  
Moussa Tembely ◽  
Waleed AlAmeri ◽  
Emad W. Al-Shalabi ◽  
Abdul Ravoof Shaik
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Experimental Data ◽  
Steady State ◽  
Relative Permeability ◽  
Learning Model ◽  
Gradient Boosting ◽  
Data Set ◽  
Machine Learning Model ◽  
Extreme Gradient Boosting

Abstract A meticulous interpretation of steady-state or unsteady-state relative permeability (Kr) experimental data is required to determine a complete set of Kr curves. In this work, three different machine learning models was developed to assist in a faster estimation of these curves from steady-state drainage coreflooding experimental runs. The three different models that were tested and compared were extreme gradient boosting (XGB), deep neural network (DNN) and recurrent neural network (RNN) algorithms. Based on existing mathematical models, a leading edge framework was developed where a large database of Kr and Pc curves were generated. This database was used to perform thousands of coreflood simulation runs representing oil-water drainage steady-state experiments. The results obtained from these simulation runs, mainly pressure drop along with other conventional core analysis data, were utilized to estimate Kr curves based on Darcy's law. These analytically estimated Kr curves along with the previously generated Pc curves were fed as features into the machine learning model. The entire data set was split into 80% for training and 20% for testing. K-fold cross validation technique was applied to increase the model accuracy by splitting the 80% of the training data into 10 folds. In this manner, for each of the 10 experiments, 9 folds were used for training and the remaining one was used for model validation. Once the model is trained and validated, it was subjected to blind testing on the remaining 20% of the data set. The machine learning model learns to capture fluid flow behavior inside the core from the training dataset. The trained/tested model was thereby employed to estimate Kr curves based on available experimental results. The performance of the developed model was assessed using the values of the coefficient of determination (R2) along with the loss calculated during training/validation of the model. The respective cross plots along with comparisons of ground-truth versus AI predicted curves indicate that the model is capable of making accurate predictions with error percentage between 0.2 and 0.6% on history matching experimental data for all the three tested ML techniques (XGB, DNN, and RNN). This implies that the AI-based model exhibits better efficiency and reliability in determining Kr curves when compared to conventional methods. The results also include a comparison between classical machine learning approaches, shallow and deep neural networks in terms of accuracy in predicting the final Kr curves. The various models discussed in this research work currently focusses on the prediction of Kr curves for drainage steady-state experiments; however, the work can be extended to capture the imbibition cycle as well.

Time Transformation Simulation of 1.5 Stage Transonic Compressor

2015 ◽  
Author(s):  
Laith Zori ◽  
Paul Galpin ◽  
Rubens Campregher ◽  
Juan Carlos Morales
Keyword(s):  
Steady State ◽  
Transient Flow ◽  
Computational Cost ◽  
Aerodynamic Performance ◽  
Forced Response ◽  
Time Transformation ◽  
Pitch Change ◽  
Transonic Compressor ◽  
Blade Row ◽  
State Mixing

The accurate prediction of the aerodynamic and aeromechanical performance in a modern transonic compressor often exceeds the capability of traditional steady state mixing plane simulation methods. Time accurate transient blade row simulation approaches are required when there is a close coupling of the flow between the blade rows, and for fundamentally transient flow phenomena such as aeromechanical analysis including blade flutter and forced response, aerothermodynamic analysis and aero-acoustic analysis. Transient blade row simulations can be computationally impractical when all of the blade passages must be modeled to account for the unequal pitch between the blade rows. Most turbomachines consist of multiple stages, further exacerbating the computational challenge. In order to reduce the computational cost, time accurate pitch-change methods are utilized so that only a sector of the turbomachine (one or few passages per row) is modeled. The extension of the time-transformation pitch-change method to multistage machines has recently shown good promise in predicting both aerodynamic performance and resolving dominant blade passing frequencies for a subsonic compressor, while keeping the computational cost affordable. In this work, a modified one and a half stage Purdue transonic compressor (modified for unequal pitch for all three blade rows) is examined. The goal is to assess the ability of the multistage time-transformation method to accurately predict the aerodynamic performance and transient flow details in the presence of transonic blade row interactions. The results from the multistage time-transformation simulation are compared in detail with a transient full-wheel simulation, a profile transformation simulation, as well as to a steady-state mixing-plane model. Flow details are examined including an FFT analysis of select signals, and the onset of stall is compared between all methods. The relative computational effort is compared between all of the analysis methods.

scholarly journals Analysing omics data sets with weighted nodes networks (WNNets)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gabriele Tosadori ◽  
Dario Di Silvestre ◽  
Fausto Spoto ◽  
Pierluigi Mauri ◽  
Carlo Laudanna ◽  
...  
Keyword(s):  
Experimental Data ◽  
Network Models ◽  
Experimental Information ◽  
Data Sets ◽  
Proteomics Data ◽  
Experimental Conditions ◽  
Data Set ◽  
Current Trends ◽  
Network Properties ◽  
The Individual

AbstractCurrent trends in biomedical research indicate data integration as a fundamental step towards precision medicine. In this context, network models allow representing and analysing complex biological processes. However, although effective in unveiling network properties, these models fail in considering the individual, biochemical variations occurring at molecular level. As a consequence, the analysis of these models partially loses its predictive power. To overcome these limitations, Weighted Nodes Networks (WNNets) were developed. WNNets allow to easily and effectively weigh nodes using experimental information from multiple conditions. In this study, the characteristics of WNNets were described and a proteomics data set was modelled and analysed. Results suggested that degree, an established centrality index, may offer a novel perspective about the functional role of nodes in WNNets. Indeed, degree allowed retrieving significant differences between experimental conditions, highlighting relevant proteins, and provided a novel interpretation for degree itself, opening new perspectives in experimental data modelling and analysis. Overall, WNNets may be used to model any high-throughput experimental data set requiring weighted nodes. Finally, improving the power of the analysis by using centralities such as betweenness may provide further biological insights and unveil novel, interesting characteristics of WNNets.

Mistuning Identification of Bladed Disks Utilizing Neural Networks

2010 ◽  
Author(s):  
M. Ersin Yu¨mer ◽  
Ender Cig˘erog˘lu ◽  
H. Nevzat O¨zgu¨ven
Keyword(s):  
Neural Networks ◽  
Mathematical Model ◽  
Case Studies ◽  
Natural Frequencies ◽  
Forced Response ◽  
Response Analysis ◽  
Bladed Disks ◽  
Data Set ◽  
Bladed Disk ◽  
New Methods

Mistuning affects forced response of bladed disks drastically; therefore, its identification plays an essential role in the forced response analysis of realistic bladed disk assemblies. Forced response analysis of mistuned bladed disk assemblies has drawn wide attention of researchers but there are a very limited number of studies dealing with identification of mistuning, especially if the component under consideration is a blisk (integrally bladed disk). This paper presents two new methods to identify mistuning of a rotor from the assembly modes via utilizing neural networks. It is assumed that a tuned mathematical model of the rotor under consideration is readily available, which is always the case for today’s realistic bladed disk assemblies. In the first method, a data set of selected mode shapes and natural frequencies is created by a number of simulations performed by mistuning the tuned mathematical model randomly. A neural network created by considering the number of modes, is then trained with this data set. Upon training the network, it is used to identify mistuning of the rotor from measured data. The second method further improves the first one by using it as starting point of an optimization routine and carries out an optimization to identify mistuning. To carry out identification analysis by means of the proposed methods, there are no limitations on the number of modes or natural frequencies to be used. Thus, they are suitable for incomplete data as well. Moreover, since system modes are used rather than blade alone counterparts, the techniques are ready to be used for analysis of blisks. Case studies are performed to demonstrate the capabilities of the new methods, using two different mathematical models to create training data sets; a lumped-parameter model and a relatively realistic reduced order model. Throughout the case studies, the effects of using incomplete mode families and random errors in assembly modes are investigated.

Separation of Up and Downstream Forced Response Excitations of an Embedded Compressor Rotor

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
Shreyas Hegde ◽  
Zhiping Mao ◽  
Tianyu Pan ◽  
Laith Zori ◽  
Rubens Campregher ◽  
...  
Keyword(s):  
Forced Response ◽  
Response Analysis ◽  
Wave Reflections ◽  
Compressor Rotor ◽  
Forcing Function ◽  
Engine Order ◽  
Aerodynamic Interaction ◽  
Stator Vane ◽  
Modal Force ◽  
The Individual

The aerodynamic interaction of upstream and downstream blade rows can have a significant impact on the forced response of the compressor. Previously, the authors carried out the forced response analysis of a three-row stator-rotor-stator (S1-R2-S2) configuration from a 3.5-stage compressor. However, since the stator vane counts in both the stators (S1 and S2) were the same, it was not possible to separate the excitations from both the rows as they excited the rotor at the same frequency. Hence, a new configuration was developed and tested in which the stator 1 blade count was changed to 38 and stator 2 blade count was maintained at 44 in order to study the individual influences of the stator on the embedded rotor. By using this method, the excitations from both rows can be determined, and the excitations can be quantified to determine the row having the maximum influence on the overall forcing. To achieve this, two sets of simulations were carried out. The three-row stator-rotor (S1-R2-S2) simulation was carried out at both the 38EO (engine order) and 44EO crossings at the peak efficiency (PE) operating condition. The two-row stator-rotor analysis (S1-R2) was carried out at the 38EO crossing, and the other two-Row (R2-S2) analyses were carried out at the 44EO crossing. The steady aerodynamics was preserved in both the cases. A study was done to determine the contribution of wave reflections from the stator inlet and exit planes to the forcing function. Two conclusions drawn from this study are as follows: (1) the modal force value decreased after the upstream stator was removed, which proved that wave reflections from this stator were significant and (2) the increase in modal force was in-line with experimental observations.

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