Masters Thesis: Development of a data fusion framework for the aerodynamic analysis of launchers

110 Pages·2017·13.51 MB·English

Master of Science Thesis
Development of a data fusion
framework for the aerodynamic
analysis of launchers
Q.Zhang
January 24, 2017
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Development of a data fusion
framework for the aerodynamic
analysis of launchers
Master of Science Thesis
For obtaining the degree of Master of Science in Aerospace Engineering
at Delft University of Technology
Q.Zhang
January 24, 2017
Faculty of Aerospace Engineering Delft University of Technology
·
Delft University of Technology
Copyright c Aerospace Engineering, Delft University of Technology
�
All rights reserved.
DELFT UNIVERSITY OF TECHNOLOGY
DEPARTMENT OF AERODYNAMICS
The undersigned hereby certify that they have read and recommend to the Faculty of
Aerospace Engineering for acceptance the thesis entitled “Development of a data fusion
framework for the aerodynamic analysis of launchers” by Q.Zhang in fulfillment of
the requirements for the degree of Master of Science.
Dated: January 24, 2017
Supervisors:
Dr.ir. F.F.J. Schrijer
Dr.ir. B.W. van Oudheusden
Ir. B.T.C. Zandbergen

Preface
This thesis concludes my Flight Performance and Propulsion master program in the faculty
of Aerospace Engineering of Delft University of Technology. The time spent on this thesis is
longer than expected and the reason is multiple, but I really learnt a lot. If I kept working
as an engineer as two years ago, I will never feel the bitter and sweet of the master study.
I would like to show my sincere gratitude to my supervisor Dr. ir. Ferry Schrijer and Dr.
ir. Bas van Oudheusden for providing me this experimental topic, thanks for their kindness
when they introduced me to this project. I’m grateful to Dr. ir. Ferry Schrijer for his
great guidance through the project, and for the understanding and encouragement he gave
me. Special thanks to Dr. ir. Sander van Zuijlen, who provided me great support on the
application of CFD software. Thanks Ir. B.T.C. Zandbergen for his help at the beginning of
my thesis and all the useful literature provided.
I would like to thank my family, especially my dear wife Fanyi Yang, for always having faith
in me and supporting my foreign study from the beginning to the end. Without her love, I
will never finish the master study. I also want to show my gratitude to my dear friends who
have given me a lot of help during this thesis. They are Li Mo, Ye Zhang, Li Cui, William
Mulkens, Qingqing Ye, Rucheet Tipnis, Zaoxu Zhu, Qingxi Li, Remco van de Meerendonk,
Lin Liu, Lijian Qi, Shuanghou Deng, etc.
Quan Zhang
Delft, The Netherlands
24th January, 2017
MSc. Thesis Q.Zhang
vi Preface
Q.Zhang M.Sc. Thesis
Abstract
During the launching vehicles design and their optimization process, the implementing of
aerodynamic characteristics (AC) database is quite important. Accuracy of such database
determines quality of the pre-flight simulation, trajectory and even the whole design direc-
tion. However, the database building process is one of the most challenging steps. For
most launchers, the flight envelopes cover a wide range of Mach number and Reynolds num-
ber. Traditionally, two basic practices are mostly adopted to carry out this kind of job, the
experimental-based wind tunnel test (WTT) and the computational fluid dynamics (CFD)
simulation. However, both methods have their own weaknesses, either being economically
or computationally expensive. These disadvantages disenable them to be the best routines.
There is another kind of technique to achieve the AC database, the industrial semi-empirical
computer programs, such as DATCOM from U.S. Air Force and Aeroprediction from U.S.
NavalSurfaceWarfareCenter. ForscenarioswhereWTTisnotapplicable,thecomputational
intensity of CFD can be reduced by the combination of CFD and industrial semi-empirical
methods. In this project, such approach is proposed to develop the aerodynamic database for
launchers, in an e�cient and accurate way.
The basic idea is to apply the Co-Kriging-based data fusion algorithm on CFD data and esti-
mation results. Generally, the results from semi-empirical methods tend to have low fidelity.
By performing the data fusion, the accuracy of low fidelity estimation data (from DATCOM)
can be improved significantly by adding a small sum of expensive data (from CFD). Dur-
ing the fusion process, one important step is the sampling process, namely determining the
simulation points among all the flight regime where CFD simulations should be performed.
Before adopting the CFD simulation results as the accurate and expensive benchmark, val-
idation of the CFD codes should be carried out in advance. The evaluation is performed
on a U.S. launcher, of which some WTT data is available from public literature. The CFD
codes are based on the Navier-Stocks governing equations and are dealt with the Reynolds-
Average Navier-Stocks (RANS) concept. In this project, the one-equation turbulence model,
Sparlart-Allmaras Model, is adopted for its robustness in the chosen CFD codes. After the
grid-independence study, the simulation results prove satisfactory, with an error lower than
10%forthenormalforcecoe�cient(C )andaxialforcecoe�cient(C ). Forthepitching-up
N A
moment coe�cient (C ), the error can be as large as 24%. The reason for it is complicated,
M
and the most possible reason is the existence of the double backward-facing steps at the end
ofthepayloadstage, flowaroundwhichisdi�cultfortheCFDcodetoestimateandsimulate.
MSc. Thesis Q.Zhang
viii Abstract
After the evaluation, the data fusion is implemented to the VEGA launcher. The first step
is to establish the low-fidelity AC database from DATCOM. Three kinds of information are
writtenintotheinputfiles,thegeometryofthelauncher,thedefinitionoftheflightconditions,
thedesiredoutputs. ThesecondstepisperformingCFDsimulationsonflightscenarioswhich
are chosen based on the low-fidelity AC database and the Latin Hypercube Sampling (LHS)
scheme. The final step, called the fusion process, is carried out based on the Co-Kriging
algorithm. The fusion results are evaluated by comparing them with corresponding new CFD
simulations. The evaluation demonstrates that the proposed method is capable of improving
the low-fidelity AC database to a great extent, with only a small quantity of computationally
expensiveCFDsimulations. Inthisproject, theerrorisreducedfromaslargeas60%tolower
than 15%. Should more expensive data is added, the accuracy can be further improved.
Thisprojectsuggestsane�cientwayofestablishingahigh-fidelityACdatabasebyharnessing
Co-Kriging algorithm. Data from industrial semi-empirical methods is improved to high
accuracywithasmallquantityofCFDsimulations. Thesuggestedschemehasabigadvantage
in saving time. In this project, 90% CFD computation time is saved to achieve the same
accurate AC database.
Q.Zhang M.Sc. Thesis