Comparison of stationary internal cooling passage numerical simulations to experimental data
Turbine blade internal cooling analysis is currently improving with a shift from the application of wall averaged empirical correlations to spatially resolved numerical simulations. However, verification of the numerical tools is required before industry would apply and rely upon a more costly tool...
| Main Authors: | , , , , |
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| Format: | Conference item |
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Euroturbo
2014
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| _version_ | 1797075860912603136 |
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| author | McGilvray, M Pineiro, C Axe, T Ryley, J Gillespie, D |
| author_facet | McGilvray, M Pineiro, C Axe, T Ryley, J Gillespie, D |
| author_sort | McGilvray, M |
| collection | OXFORD |
| description | Turbine blade internal cooling analysis is currently improving with a shift from the application of wall averaged empirical correlations to spatially resolved numerical simulations. However, verification of the numerical tools is required before industry would apply and rely upon a more costly tool in the design stage. This paper presents the numerical simulation of a stationary, generalised rib turbulated internal cooling passage with a 1:2 aspect ratio with engine realistic features over a Reynolds range of 18000-112000. Direct comparisons of numerical simulations using both the realizable k- ε and k- ω SST turbulence models and experimental results are presented in terms of spatially resolved Nusselt number, streamwise averaged Nusselt number, and wall averaged Nusselt number and friction factor. This showed that similar behaviour, with averaged differences in Nusselt number of 5-30% between the experiment and the simulations, with the end section of the passage being well predicted by the k- ε turbulence model. The friction factor agrees well between the two sets of numerical predictions and with the experimental results for Reynolds numbers below 70000 with a maximum under-prediction of 12%. Both turbulence models resulted in similar wall averaged Nusselt numbers, though the best point-wise match with experimental data was Reynolds number dependent. |
| first_indexed | 2024-03-06T23:56:12Z |
| format | Conference item |
| id | oxford-uuid:744dbf00-b767-485f-b95c-03af3057d74d |
| institution | University of Oxford |
| last_indexed | 2024-03-06T23:56:12Z |
| publishDate | 2014 |
| publisher | Euroturbo |
| record_format | dspace |
| spelling | oxford-uuid:744dbf00-b767-485f-b95c-03af3057d74d2022-03-26T20:01:51ZComparison of stationary internal cooling passage numerical simulations to experimental dataConference itemhttp://purl.org/coar/resource_type/c_5794uuid:744dbf00-b767-485f-b95c-03af3057d74dSymplectic Elements at OxfordEuroturbo2014McGilvray, MPineiro, CAxe, TRyley, JGillespie, DTurbine blade internal cooling analysis is currently improving with a shift from the application of wall averaged empirical correlations to spatially resolved numerical simulations. However, verification of the numerical tools is required before industry would apply and rely upon a more costly tool in the design stage. This paper presents the numerical simulation of a stationary, generalised rib turbulated internal cooling passage with a 1:2 aspect ratio with engine realistic features over a Reynolds range of 18000-112000. Direct comparisons of numerical simulations using both the realizable k- ε and k- ω SST turbulence models and experimental results are presented in terms of spatially resolved Nusselt number, streamwise averaged Nusselt number, and wall averaged Nusselt number and friction factor. This showed that similar behaviour, with averaged differences in Nusselt number of 5-30% between the experiment and the simulations, with the end section of the passage being well predicted by the k- ε turbulence model. The friction factor agrees well between the two sets of numerical predictions and with the experimental results for Reynolds numbers below 70000 with a maximum under-prediction of 12%. Both turbulence models resulted in similar wall averaged Nusselt numbers, though the best point-wise match with experimental data was Reynolds number dependent. |
| spellingShingle | McGilvray, M Pineiro, C Axe, T Ryley, J Gillespie, D Comparison of stationary internal cooling passage numerical simulations to experimental data |
| title | Comparison of stationary internal cooling passage numerical simulations to experimental data |
| title_full | Comparison of stationary internal cooling passage numerical simulations to experimental data |
| title_fullStr | Comparison of stationary internal cooling passage numerical simulations to experimental data |
| title_full_unstemmed | Comparison of stationary internal cooling passage numerical simulations to experimental data |
| title_short | Comparison of stationary internal cooling passage numerical simulations to experimental data |
| title_sort | comparison of stationary internal cooling passage numerical simulations to experimental data |
| work_keys_str_mv | AT mcgilvraym comparisonofstationaryinternalcoolingpassagenumericalsimulationstoexperimentaldata AT pineiroc comparisonofstationaryinternalcoolingpassagenumericalsimulationstoexperimentaldata AT axet comparisonofstationaryinternalcoolingpassagenumericalsimulationstoexperimentaldata AT ryleyj comparisonofstationaryinternalcoolingpassagenumericalsimulationstoexperimentaldata AT gillespied comparisonofstationaryinternalcoolingpassagenumericalsimulationstoexperimentaldata |