Modeling of Laminar-Turbulent Transition in Boundary Layers and Rough Turbine Blades
Author(s) -
Liang Wei,
Xuan Ge,
Jacob George,
Paul A. Durbin
Publication year - 2017
Publication title -
journal of turbomachinery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 112
eISSN - 1528-8900
pISSN - 0889-504X
DOI - 10.1115/1.4037670
Subject(s) - freestream , turbulence , mechanics , boundary layer , laminar flow , intermittency , turbine blade , leading edge , reynolds averaged navier–stokes equations , pressure gradient , laminar turbulent transition , materials science , reynolds number , surface finish , turbine , physics , thermodynamics , composite material
A local, intermittency-function-based transition model was developed for the prediction of laminar-turbulent transitional flows with freestream turbulence intensity Tu at low (Tu 3% levels, and roughness effects in a broad range of industrial applications such as turbine and helicopter rotor blades, and in nature. There are many mechanisms (natural or bypass) that lead to transition. Surface roughness due to harsh working conditions could have great influence on transition. Accurately predicting both the onset location and length of transition has been persistently difficult. The current model is coupled with the k–ω Reynolds-averaged Navier–Stokes (RANS) model, that can be used for general computational fluid dynamics (CFD) purpose. It was validated on the ERCOFTAC experimental zero-pressure-gradient smooth flat plate boundary layer with both low and high leading-edge freestream turbulence intensities. Skin friction profiles agree well with the experimental data. The model was then tested on ERCOFTAC experimental flat plate boundary layer with favorable/adverse pressure gradients cases, periodic wakes, and flows over Stripf's turbine blades with roughness from hydraulically smooth to fully rough. The predicted skin friction and heat transfer properties by the current model agree well with the published experimental and numerical data.
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