Evaluation of
Multidisciplinary Optimization (MDO)
Techniques Applied to a
Reusable Launch Vehicle
Author(s)
Brown, Nichols
Advisor(s)
Olds, John R.
Editor(s)
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Abstract
Optimization of complex engineering systems has always been an integral part of
design. Due to the size and complexity of aerospace systems the design of a whole
system is broken down into multiple disciplines. Traditionally these disciplines have
developed local design tools and computer codes (legacy codes) allowing them to
perform optimization with respect to some aspect of their local discipline. Unfortunately,
this approach can produce sub-optimal systems as the disciplines are not optimizing with
respect to a consistent global objective. Multidisciplinary design optimization (MDO)
techniques have been developed to allow for multidisciplinary systems to reach a global
optimum. The industry accepted All-at-Once (AAO) technique has practical limitations
and is confined to only small, conceptual level problems.
New multi-level MDO techniques have been proposed which may allow for the
global optimization of the large, complex systems involved in higher levels of design.
Three of the most promising multi-level MDO techniques, Bi-Level Integrated System
Synthesis (BLISS), Collaborative Optimization (CO) and Modified Collaborative
Optimization (MCO) are applied, evaluated and compared in this study.
The techniques were evaluated by applying them to the optimization of a next
generation Reusable Launch Vehicle (RLV). The RLV model was composed of three
loosely coupled disciplines, Propulsion, Performance, and Weights & Sizing, composed
of stand-alone, legacy codes not originally intended for use in a collaborative
environment.
Results from the multi-level MDO techniques will be verified through the use of
the AAO approach and their benefits measured against the traditional approach where the
multiple disciplines are converged using the fixed point iteration (FPI) process.
All the techniques applied will be compared against each other and rated
qualitatively on such metrics as formulation and implementation difficulty, optimization
deftness and convergence errors.
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Sponsor
Date
2004-04-29
Extent
Resource Type
Text
Resource Subtype
Masters Project
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