1.
J. Baltazar, Rijpkema; Falcão de Campos, J. A. C.
Fifth International Symposium on Marine Propulsors (SMP), Espoo, Finland, 2017.
@conference{Baltazar2017,
title = {On the Use of the γ−Re˜ θ Transition Model for the Prediction of the Propeller Performance at Model-Scale},
author = {Baltazar, J., Rijpkema, D. and Falcão de Campos, J.A.C.},
url = {http://www.marin.nl/web/Publications/Publication-items/On-the-Use-of-the-gReth-Transition-Model-for-the-Prediction-of-the-Propeller-Performance-at-ModelScale.htm},
year = {2017},
date = {2017-06-01},
booktitle = {Fifth International Symposium on Marine Propulsors (SMP), Espoo, Finland},
abstract = {The goal of the present work is to improve the prediction of propeller performance at model-scale using a local correlation transition model. Results are presented for two marine propellers for which paint-tests have been conducted and experimental open-water data is available. The numerical results using the k − ω SST turbulence model and the γ − Re˜ θ transition model are compared with the experiments. In order to distinguish between numerical and modelling errors in the comparison with experimental results, a verification study using a range of geometrically similar grids with different grid densities is made. The influence of the turbulence inlet quantities on the numerical results is discussed and boundary-layer characteristics are presented. Finally, the numerical predictions are compared with the experimental results. An improvement in the flow pattern is achieved with the transition model. However, the model strongly depends on the turbulence inlet quantities for the prediction of the transition location. Both propellers show an increase in thrust of 2% to 4% and similar torque when using the transition model.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The goal of the present work is to improve the prediction of propeller performance at model-scale using a local correlation transition model. Results are presented for two marine propellers for which paint-tests have been conducted and experimental open-water data is available. The numerical results using the k − ω SST turbulence model and the γ − Re˜ θ transition model are compared with the experiments. In order to distinguish between numerical and modelling errors in the comparison with experimental results, a verification study using a range of geometrically similar grids with different grid densities is made. The influence of the turbulence inlet quantities on the numerical results is discussed and boundary-layer characteristics are presented. Finally, the numerical predictions are compared with the experimental results. An improvement in the flow pattern is achieved with the transition model. However, the model strongly depends on the turbulence inlet quantities for the prediction of the transition location. Both propellers show an increase in thrust of 2% to 4% and similar torque when using the transition model.
2017
J. Baltazar, Rijpkema; Falcão de Campos, J. A. C.
Fifth International Symposium on Marine Propulsors (SMP), Espoo, Finland, 2017.
Abstract | Links | BibTeX | Tags: Marine Propeller, RANS Equations, Transitional Flow, Turbulence and Transition Models.
@conference{Baltazar2017,
title = {On the Use of the γ−Re˜ θ Transition Model for the Prediction of the Propeller Performance at Model-Scale},
author = {Baltazar, J., Rijpkema, D. and Falcão de Campos, J.A.C.},
url = {http://www.marin.nl/web/Publications/Publication-items/On-the-Use-of-the-gReth-Transition-Model-for-the-Prediction-of-the-Propeller-Performance-at-ModelScale.htm},
year = {2017},
date = {2017-06-01},
booktitle = {Fifth International Symposium on Marine Propulsors (SMP), Espoo, Finland},
abstract = {The goal of the present work is to improve the prediction of propeller performance at model-scale using a local correlation transition model. Results are presented for two marine propellers for which paint-tests have been conducted and experimental open-water data is available. The numerical results using the k − ω SST turbulence model and the γ − Re˜ θ transition model are compared with the experiments. In order to distinguish between numerical and modelling errors in the comparison with experimental results, a verification study using a range of geometrically similar grids with different grid densities is made. The influence of the turbulence inlet quantities on the numerical results is discussed and boundary-layer characteristics are presented. Finally, the numerical predictions are compared with the experimental results. An improvement in the flow pattern is achieved with the transition model. However, the model strongly depends on the turbulence inlet quantities for the prediction of the transition location. Both propellers show an increase in thrust of 2% to 4% and similar torque when using the transition model.},
keywords = {Marine Propeller, RANS Equations, Transitional Flow, Turbulence and Transition Models.},
pubstate = {published},
tppubtype = {conference}
}
The goal of the present work is to improve the prediction of propeller performance at model-scale using a local correlation transition model. Results are presented for two marine propellers for which paint-tests have been conducted and experimental open-water data is available. The numerical results using the k − ω SST turbulence model and the γ − Re˜ θ transition model are compared with the experiments. In order to distinguish between numerical and modelling errors in the comparison with experimental results, a verification study using a range of geometrically similar grids with different grid densities is made. The influence of the turbulence inlet quantities on the numerical results is discussed and boundary-layer characteristics are presented. Finally, the numerical predictions are compared with the experimental results. An improvement in the flow pattern is achieved with the transition model. However, the model strongly depends on the turbulence inlet quantities for the prediction of the transition location. Both propellers show an increase in thrust of 2% to 4% and similar torque when using the transition model.