investigation into the flow behaviour of a naca 0021 airfoil with leading edge undulations simulated

79 Pages·2015·20.42 MB·English

INVESTIGATION INTO THE
FLOW BEHAVIOUR OF A NACA
0021 AIRFOIL WITH LEADING
EDGE UNDULATIONS
SIMULATED WITH RANS IN
STAR-CCM+
A THESIS SUBMITTED TO THE UNIVERSITY OF MANCHESTER
FOR THE DEGREE OF MASTER OF PHILOSOPHY
IN THE FACULTY OF ENGINEERING AND PHYSICAL SCIENCES
September 2015
By
Kevin Robert Atkins
School of Mechanical, Aerospace and Civil Engineering
Contents
Abstract 3
Declaration 3
Copyright 3
Acknowledgements 3
1 Introduction 8
1.1 Computational Fluid Dynamics . . . . . . . . . . . . . . . . . 8
1.2 Biomimetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.2.1 Whale Wing Biomimetics . . . . . . . . . . . . . . . . 12
1.3 Thesis Objectives and Outline . . . . . . . . . . . . . . . . . . 14
2 Literature Review 16
2.1 Research on Tubercles for Airfoils . . . . . . . . . . . . . . . . 16
2.2 RANS Turbulence Models . . . . . . . . . . . . . . . . . . . . 23
3 Geometry and Mesh Generation 26
3.1 Domain and Geometry Generation . . . . . . . . . . . . . . . 26
1
3.2 Mesh Development . . . . . . . . . . . . . . . . . . . . . . . . 29
3.3 2D and 3D Mesh Sensitivity . . . . . . . . . . . . . . . . . . . 38
4 Validation Study 42
4.1 Turbulence Model Comparison . . . . . . . . . . . . . . . . . . 43
4.2 Model Comparison . . . . . . . . . . . . . . . . . . . . . . . . 59
5 3D Modified Airfoil Study 62
5.1 RANS Turbulence Model Evaluation . . . . . . . . . . . . . . 63
6 Conclusions and Future Work 74
Bibliography 76
2
Abstract
This thesis serves to validate and evaluate Reynolds Averaged Navier Stokes
(RANS) turbulence models of STAR-CCM+ version 9.04 for the purpose of
simulating an airfoil with leading edge undulations. The models of interest
include Standard K-Epsilon, SST K-Omega, Elliptic Blended Eddy Viscosity
Model and the LRR Reynolds Stress Model.
To begin, the models of interest were validated against a trusted test case
using a mesh independent domain. With validated models, the case of an
airfoil with leading edge undulations with an ampltiude (A) of 0.0075c and
a wavelength (λ) of 0.11c was simulated at 20 degree incidence angle at a
Reynolds Number of 150,000. With the above listed test configuration, the
results were comparable to previous wind tunnel and CFD analyses. It was
found that the RANS models adequately predicted the force,pressure and
skin friction coefficients as has been determined in previous studies. Specifi-
cally, the K-Epsilon model provided the weakest correlation to experimental
results, but exhibited similar behaviour to other CFD studies. Of interest,
the remaining models predicted the gentle stall behaviour associated with
this geometry. The LRR-RSM model provided the best results overall by
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recording the most realistic coefficients while modelling the intricacies of
the flow behaviour. However, the SST and Blended EVM models provided
slightly less realistic behaviour but did so at a fraction of the computational
cost. Thus, should RANS be used as an avenue for parametric sweeps of ge-
ometry, Reynolds Number or any other variables of interest, if computational
expense is of less concern, the LRR-RSM model would provide the best re-
sults. Alternatively, if computational budget is a factor, the B-EVM model
would be the model of choice, followed by the SST K-Omega formulation.
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Declaration
Noportionoftheworkreferredtointhisthesishasbeensubmittedinsupport
of an application for another degree or qualification of this or any other
university or institute of learning.
5
Copyright
Copyright in text of this thesis rests with the Author. Copies (by any pro-
cess) either in full, or of extracts, may be made only in accordance with
instructions given by the Author and lodged in the John Rylands University
Library of Manchester. Details may be obtained from the Librarian. This
page must form part of any such copies made. Further copies (by any pro-
cess) of copies made in accordance with such instructions may not be made
without the permission (in writing) of the Author. The ownership of any
intellectual property rights which may be described in this thesis is vested in
the University of Manchester, subject to any prior agreement to the contrary,
and may not be made available for use by third parties without the written
permission of the University, which will prescribe the terms and conditions
of any such agreement. Further information on the conditions under which
disclosures and exploitation may take place is available from the Head of
School of Mechanical, Aerospace and Civil Engineering.
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Acknowledgements
To begin, I’d like to thank my supervisor Dr. Alistair Revell for his guidance
over the course of my thesis. While the process may have been a bit different
than we both expected when this started, it wouldn’t have come to close
without your help.
Without the continuing advice of both Dr. Alex Skillen and Dr. Neil
Ashton, I don’t think there would be results to present and for that I’m in-
credibly grateful!
To my parents. Thank you for getting me to England and encouraging
me along the way. I imagine you’re both more excited that this is finished
than I am!
Finally to Brigitte, without you keeping me motivated, the submission of
this thesis may have been nothing but a figment of my imagination.
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Chapter 1
Introduction
1.1 Computational Fluid Dynamics
Since the 1960s, Computational Fluid Dynamics (CFD) has been an ever
developing area for fluid dynamicists to gain valuable insight into the phys-
ical behaviour of fluid flow in a wide variety of applications. In the present
day, these applications include but are not limited to the development of air-
craft and automobiles to understanding structural implications of a bridge
in water. CFD has also become an area of great interest for the medical
industry where potentially life-saving simulations can help assess patients in
a efficient and non-invasive manner. It is evident that these applications of
CFD were not always practical in the early days of development. With the
limited computational power of the time, CFD simulations were limited to
simple flows which did not consider the affects of boundary layers or any
associated turbulence.
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Astechnologydeveloped,asdidmodellingcapabilities. Simulationstrans-
formed from being conducted on a hand full of cells to multiple million cells
over the decades. Within the computational landscape of today, it is feasi-
ble to simulate a case down to the characteristics of the smallest turbulent
eddies. However, despite the computational power of today, these direct nu-
merical simulations (DNS) lack practicality due to their immense cost. It
has been predicted that such simulations will become readily available for
development towards the end of the century [Spalart, 2000].
Turbulence remains as the limiting factor in the efficiency of CFD simu-
lations. As such, until technology is developed to allow for DNS to be used
throughout all industries, the simplification and approximation of turbulence
modelling has been a primary focus. The three principle classes of turbulence
simulation include Reynold’s Averaged Navier Stokes (RANS), Large Eddy
Simulation (LES) and Detatched Eddy Simulations (DES). Where RANS
time-averagesthefluidflowwhilesolvingfortheReynoldsstresses. LESmod-
els turbulence by ignoring all eddies smaller than the size of Kolmogorov’s
Scalewithinthespecificflow. Finally, DESisthecombinationofthetwopre-
vious techniques whereas RANS is used to model the complicated near wall
region and the rest of the flow is solved in the LES process. In a commercial
application, RANS modelling has long been the standard for developments
in industry. However, many are opting for DES simulations due to the im-
proved accuracy. While LES is common in acadaemia, it’s place in industry
is limited due to its cost. While less expensive than DNS, it is predicted that
LES will become readily available by mid century [Spalart, 2000].
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