Type of Document Dissertation Author Kim, Hongman Author's Email Address email@example.com URN etd-07252001-160717 Title Statistical Modeling of Simulation Errors and Their Reduction via Response Surface Techniques Degree PhD Department Aerospace and Ocean Engineering Advisory Committee
Advisor Name Title Mason, William H. Committee Chair Cliff, Eugene M. Committee Member Grossman, Bernard M. Committee Member Haftka, Raphael T. Committee Member Watson, Layne T. Committee Member Keywords
- Weibull distribution
- response surface technique
- convergence error
- discretization error
Date of Defense 2001-06-18 Availability unrestricted AbstractErrors of computational simulations in design of
a high-speed civil transport (HSCT) are investigated.
First, discretization error from a supersonic panel code,
WINGDES, is considered. Second, convergence error from
a structural optimization procedure using GENESIS is
considered along with the Rosenbrock test problem.
A grid converge study is performed to estimate
the order of the discretization error in the lift
coefficient (CL) of the HSCT calculated from WINGDES.
A response surface (RS) model using several mesh sizes
is applied to reduce the noise magnification problem
associated with the Richardson extrapolation. The RS model
is shown to be more efficient than Richardson extrapolation
via careful use of design of experiments.
A programming error caused inaccurate optimization
results for the Rosenbrock test function, while
inadequate convergence criteria of the structural
optimization produced error in wing structural weight
of the HSCT. The Weibull distribution is successfully
fit to the optimization errors of both problems.
The probabilistic model enables us to estimate average
errors without performing very accurate optimization runs
that can be expensive, by using differences between
two sets of results with different optimization control
parameters such as initial design points or convergence
Optimization results with large errors, outliers,
produced inaccurate RS approximations. A robust regression
technique, M-estimation implemented by iteratively
reweighted least squares (IRLS), is used to identify
the outliers, which are then repaired by higher fidelity
optimizations. The IRLS procedure is applied to the
results of the Rosenbrock test problem, and wing structural
weight from the structural optimization of the HSCT.
A nonsymmetric IRLS (NIRLS), utilizing one-sidedness
of optimization errors, is more effective than IRLS in
identifying outliers. Detection and repair of the outliers
improve accuracy of the RS approximations. Finally,
configuration optimizations of the HSCT are performed
using the improved wing bending material weight RS models.
Filename Size Approximate Download Time (Hours:Minutes:Seconds)
28.8 Modem 56K Modem ISDN (64 Kb) ISDN (128 Kb) Higher-speed Access dissertation_hongmankim.pdf 725.88 Kb 00:03:21 00:01:43 00:01:30 00:00:45 00:00:03
If you have questions or technical problems, please Contact DLA.