GT2017-63994

FLOW AND HEAT TRANSFER ANALYSIS IN A SINGLE ROW NARROW IMPINGEMENT CHANNEL COMPARISON OF PIV LES AND RANS TO IDENTIFY RANS LIMITATIONS Jahed Hossain Erik Fernandez Christian Garrett Jay Kapat University of Central Florida Laboratory for Turbine Aerodynamics Heat Transfer and Durability Center for Advanced Turbomachinery and Energy Research Orlando FL USA ABSTRACT The present study aims to understand the flow turbulence and heat transfer in a single row narrow impingement channel for gas turbine heat transfer applications Since the advent of several advanced manufacturing techniques narrow wall cooling schemes have become more practical In this study the Reynolds number based on jet diameter was 15 000 with the jet plate having fixed jet hole diameters and hole spacing The height of the channel is 3 times the impingement jet diameter The channel width is 4 times the jet diameter of the impingement hole The channel configuration was chosen such that the crossflow air is drawn out in the streamwise direction maximum crossflow configuration The impinging jets and the wall jets play a substantial role in removing heat in this kind of configuration Hence it is important to understand the evolution of flow and heat transfer in a channel of this configuration The dynamics of flow and heat transfer in a single row narrow impingement channel are experimentally and numerically investigated Particle Image Velocimetry PIV was used to reveal the detailed information of flow phenomena The detailed PIV experiment was performed on this kind of impingement channel to satisfy the need for experimental data for this kind of impingement configuration in order to validate turbulence models PIV measurements were taken at a plane normal to the target wall along the jet centerline The mean velocity field and turbulent statistics generated from the mean flow field were analyzed The experimental data from the PIV reveals that flow is highly anisotropic in a narrow impingement channel To support experimental data wall modeled Large Eddy Simulation LES and Reynolds Averaged Navier Stokes RANS simulations SST k 2 and Reynolds Stress Model RSM were performed in the same channel geometry The Wall Adapting Local Eddy viscosity SGS mdoel WALE 1 is used for the LES calculation Mean velocities calculated from the RANS and LES were compared with the PIV data Turbulent kinetic energy budgets were calculated from the experiment and were compared with the LES and RSM model highlighting the major shortcomings of RANS models to predict correct heat transfer behavior for the impingement problem Temperature Sensitive Paint TSP was also used to experimentally obtain a local heat transfer distribution at the target and the side walls An attempt was made to connect the complex aerodynamic flow behavior with results obtained from heat transfer indicating heat transfer is a manifestation of flow phenomena The accuracy of LES in predicting the mean flow field turbulent statistics and heat transfer is shown in the current work as it is validated against the experimental data through PIV and TSP INTRODUCTION Modern advanced gas turbines are operated at exceedingly high temperatures by running at such high temperatures engines can achieve greater power output and thermal efficiency However the current firing temperatures for combustion exceeds the turbine blade material limit 2 As this firing temperature increases heat transfer into turbine components increases as well A small increment of 50K in firing temperature can result in a 8 9 increase in power output and a 2 4 improvement in cycle efficiency 3 Therefore it is necessary to introduce a cooling mechanism to these blades in order to protect the material as the engine is run at these elevated temperatures Because turbine blades inherently have complex geometry several cooling schemes have been introduced to cool the various parts of each blade A detailed overview of several cooling methods can be found in open literature for external as well as internal turbine blade cooling Impingement inside a narrow channel can be a potential way to implement near wall cooling of turbine blades and vanes as the narrow wall channel allows the coolant to flow closely to the heated surface Figure 1 shows an example of an application of near wall cooling In this figure the crossflow can be described as flowing in one direction perpendicular to the page This cooling scheme has become more practical since the advent of several advanced manufacturing techniques including Proceedings of ASME Turbo Expo 2017 Turbomachinery Technical Conference and Exposition GT2017 June 26 30 2017 Charlotte NC USA GT2017 63994 1Copyright 2017 ASME additive manufacturing One of the benefits of this cooling technique is that with the same amount of mass flow four sides of the heated wall can be cooled simultaneously hence this cooling is also sometimes called double wall cooling Figure 1 Impingement channels with narrow wall cooling concept in a turbine airfoil 4 LITERATURE REVIEW ON NARROW WALL IMPINGEMENT The correlations developed by Florschuetz et al 5 6 7 are widely known in the industry for array impingement cooling however there is limited research on a single row narrow channel impingement cooling The way narrow wall impingement differs from the conventional array impingement configuration is that the sidewall alters the flow physics and overall heat transfer inside the channel Chyu and Alvin 8 compared the traditional internal cooling passages with narrow wall cooling and found that narrow wall cooling technique can reduce the blade material temperature by about 50 to 1000C Ricklick and Kapat 9 investigated the effect of sidewalls on heat transfer coefficient It was reported that sidewalls contribute significant heat transfer in a narrow wall impingement channel as the crossflow builds up The study reveals that with configuration such as narrow wall the impinging jets not only augment the heat transfer but also enhance the mixing inside the cooling passage indicating the technique is an extremely effective cooling method More recently Terzis et al 3 investigated a detailed analysis of the local heat transfer distributions for narrow impingement channels over a wide range of engine representative Reynolds numbers The author investigated the effects of jet to jet spacing channel width and height impingement jet pattern and varying jet diameter Target wall sidewall and jet plate heat transfer data were provided Claretti et al 4 studied the relationship between target wall and side wall heat transfer by varying impingement channel height The results indicate that Z D 3 channel height provides the best heat transfer rate when both sidewall and target wall are taken into account Very few studies have been conducted in impingement literature where both flow and heat transfer are considered to understand the relationship between flow and heat transfer Geers et al 10 performed an in depth flow visualization study using PIV in an array impingement configuration Hossain et al 11 performed an aerothermal investigation of a single row narrow wall impingement channel using PIV TSP and CFD According to the author s knowledge this was the first work on this kind of channel where flow and heat transfer was connected experimentally and numerically to understand the behavior of flow and heat transfer Terzis et al 12 performed an aerothermal investigation of a single row narrow wall impingement channel using PIV and Liquid Crystal Thermography LCT A divergent impingement channel was investigated and compared to a uniform channel of the same open area ratio More recently Trezis et al 13 investigated the impact of near wall flow structures developed in a narrow wall impingement configuration and its impact on the convective heat transfer augmentation using PIV Table 1 shows a summary of narrow wall impingement work and the scope of the present study Table 1 Literature Review on Narrow Wall Impingement Authors Heat Transfer Study PIV RANS comparison LES comparison Gillespie et al 14 1998 Yes No No No Chambers et al 15 2005 Yes No No No Uysal et al 16 2006 Yes No No No Ricklick and Kapat 9 2010 Yes No No No Miller et al 17 2013 Yes No No No Trezis et al 3 2013 Yes No No No Claretti et al 4 2013 Yes No No No Fechter et al 18 2013 Yes No Yes No Hossain et al 11 2014 Yes Yes Yes No Trezis et al 12 2015 Yes Yes No No Trezis et al 13 2016 Yes Yes No No Hossain et al 19 2016 No Yes Yes Yes Present Study 2016 Yes Yes Yes Yes Zuckerman and Lior 20 reported that the common RANS based models predict a higher stagnation heat transfer coefficient by as much as 100 compared to the measured 2Copyright 2017 ASME values The paper also indicated that LES can provide results that are within 10 of measured values Fechter et al 18 numerically studied the heat transfer characteristics of narrow impingement channels with five jets and compared them with experimental heat transfer data The Shear Stress Transport SST k was used in the study It was reported that the stagnation point heat transfer was significantly over predicted Hossain et al 11 reported CFD 2 turbulence model under predicts the crossflow magnitude which leads to different jet trajectories compared to experiment Hence the discrepancies in peak locations of the surface heat transfer distribution are attributed to the difficulty of CFD in predicting the correct jet trajectories More recently Hossain 19 et al studied a comparison of PIV LES and RANS of a single row narrow wall impingement channel with five jets The mean velocities at different locations inside the channel was compared The current study differs from the author s previous work by addressing RANS limitations and the accuracy of LES in modeling heat transfer The present study highlights the importance of understanding flow physics in impingement heat transfer applications According to the author s knowledge this is the first work in a single jet per row narrow impingement cooling configuration where flow and heat transfer are connected together via particle image velocimetry PIV computational fluid dynamics both RANS and LES and heat transfer analysis using temperature sensitive paint TSP Prior to this work no study was found where a Large Eddy Simulation LES technique was validated against experimental data in array impingement cooling channels The objective of the present study is to provide a better understanding of impingement heat transfer in relation to the associated flow physics The study also aims to identify the shortcomings of the typical RANS models for the impingement heat transfer problem where typical RANS models yield erroneous results LITERATURE REVIEW LARGE EDDY SIMULATION WORK IN JET ARRAY IMPINGEMENT Table 2 shows that there has not been any effort made on implementing LES techniques on an array impingement problem in the published literature Table 2 Large Eddy Simulation Work on Circular Jet Impingement Authors Year Rej Jet Configuration Hallqvist et al 21 2006 20 000 Single Round Jet Hadziabdic the correlation statistics method of Wieneke 27 Figure 4 highlights the uncertainty fields for the in plane velocity components In Figure 4 u is the velocity in the crossflow direction x direction and w is the wall normal velocity z direction Note the highest regions of uncertainty are in the jet shear layer and impingement regions Due to the large number of image pairs used for the ensemble average these random uncertainties are minimized as can be seen by the magnitude of the velocity uncertainties For reference the maximum jet velocity measured was 36 m s Figure 4 PIV measured velocity uncertainty fields EXPERIMENTAL SETUP HEAT TRANSFER The heated area on the sidewall and target wall is comprised of temperature sensitive paint TSP a Kapton adhesive and a foil heater The foil heaters are made of type 321 stainless steel with an average electrical resistivity of el 720 10 7 m Since resistivity is a function of temperature the variation in local resistance was calculated at each data point The maximum variation of resistivity was found to be 4 The foil heaters are then attached to the TSP using double sided adhesive Kapton tape Prior to experimentation calibration of TSP is performed on a separate test section forming a calibration curve based on the Intensity Ratio vs Temperature All of the acquired images are processed using Matlab s image processing software More information on TSP and the calibration process can be found in Liu 28 Details of the data reduction procedure can be found in 29 Uncertainty Heat Transfer Experimental uncertainty was calculated for the Nusselt number and the Reynolds number using the methods outlined in Figliola and Beasley 30 The uncertainty values were calculated on a 95 confidence interval The overall uncertainties for the Nusselt number and the Reynolds number are shown in Table 3 Table 3 Experimental Uncertainty Nusselt number 9 2 Reynolds number 1 5 COMPUTATIONAL METHODOLOGIES Boundary Conditions and Computational Grid For wall modeled LES calculations a mesh was generated using unstructured grids with hexahedral elements using ANSYS ICEMCFD version 15 0 Figure 5 shows the mesh structure used for the LES calculation Cell orthogonality was ensured by applying O grid type blocks for all Maximum local values were 1 0 at the target wall for all the cases Very fine grids were used near the jet shear layer jet cores and near the target wall region The Same mesh was used for RANS calculations Grid resolution used in the present study shown in Table 4 resolves 80 of the turbulent kinetic energy in the near wall region as well as in the rest of the computational domain as recommended by 31 Table 4 Mesh Criteria for wall modeled LES Dimensionless grid spacing Recommended by Piomelli and Chasnov 32 Present Study x 100 600 50 y 100 300 60 z 25 30 1 Figure 5 Mesh at the centerline plane of the channel A mass flow inlet boundary condition was applied to the top face located 1 jet diameter from the face where the jets originate In order to achieve a turbulence like flow at the inlet inlet flow was initialized using the synthetic eddy method 33 A hotwire probe was traversed across the plenum in the experiment 1 jet diameter above the jet orifice to calculate the turbulent intensity and length scale at the inlet These values were specified at the inlet of the numerical model All boundary conditions are selected to be as close as possible to the experimental conditions The plenum walls end wall cap and jet plate were all considered no slip adiabatic walls In order to account for the heat flux generated by the experimental heaters a uniform heat flux boundary condition was applied to the target wall and sidewalls At the outlet a pressure outlet boundary condition was applied All the calculations were performed using the commercial CFD solver StarCCM A second order discretization method was used in the simulations and a segregated flow solver was used for all calculations The CFL number was maintained 2 i e the length of the potential core is 1D in PIV and LES calculation Also the velocity decay rate is very similar between PIV and LES A different jet behavior was noticed from all the RANS simulations The length of the potential core was found to be 2D for all models Predicting the correct stagnation point heat transfer has always been the most challenging task for RANS models as they generally over predict 20 The difference in the jet axial velocity profile obtained from RANS and PIV reveals the underlying reason for this discrepancy as the behavior of the jet being different in RANS models than in the experiment 5Copyright 2017 ASME Figure 8 Centerline jet axial velocity for the first jet Turbulent Kinetic Energy Budget Turbulent kinetic energy can give information about the main characteristics of turbulence in a flow Taking the trace of the mean Reynolds stress equation yields the turbulent kinetic energy and can be written as 23 8 Where indicates mean flow convection denotes production of turbulent kinetic energy due to shear and normal stresses is the diffusive transport and is the viscous dissipation One of the purposes of the current study is to validate LES s capability in predicting mean flow and turbulent statistics for the narrow wall impingement problem In addition to that to identify the key terms in RANS s formulation where experimental data can be compared and visualized against By comparing the key terms in the turbulent kinetic energy budget the shortcomings of the RANS models can be assessed The experiment was performed on this kind of impingement channel to satisfy the need for experimental data to validate turbulence models which was not available in the published literature for this kind of impingement channel prior to this work Even though all the individual terms in the turbulent kinetic energy budget shown in equation 8 can be calculated from the current 3D LES simulation the current study is limited only to the terms that can be calculated directly from 2D PIV data In the RSM model the production term is not modeled rather it is calculated directly Hence this term was chosen as a good candidate to compare between all the three techniques PIV LES and RSM Therefore the fidelity of the LES and RANS technique for a narrow wall impingement problem can be assessed All the production terms in the Figures are normalized by The production of turbulent kinetic energy was calculated from the 2D PIV and compared with the LES and RSM at the centerline plane of the channel Since the purpose of the impingement is to remove heat from the target surface a location close to the target wall z D 0 5 is used for comparison Only the second jet inside the channel was considered for analysis of the turbulent kinetic energy budget Turbulent Kinetic Energy Production Due to Normal Stresses Turbulent kinetic energy production due to normal stresses can be expressed as 9 where