Complex engineering systems involve large numbers of functional elements. Each
functional element can exhibit complex behavior itself. Ensuring the ability of such
systems to meet the customer's needs and requirements requires modeling the behavior
of these systems. Behavioral modeling allows a quantitative assessment of the ability of
a system to meet specific requirements. However, modeling the behavior of complex
systems is difficult due to the complexity of the elements involved and more importantly
the complexity of these elements' interactions.
In prior work, formal functional modeling techniques have been applied as a means of
performing a qualitative decomposition of systems to ensure that needs and requirements
are addressed by the functional elements of the system. Extending this functional
decomposition to a quantitative representation of the behavior of a system represents a
significant opportunity to improve the design process of complex systems.
To this end, a functionality-based behavioral modeling framework is proposed along
with a sensitivity analysis method to support the design process of complex systems.
These design tools have been implemented in a computational framework and have been
used to model the behavior of various engineering systems to demonstrate their maturity,
application and effectiveness. The most significant result is a multi-fidelity model of a
hybrid internal combustion-electric racecar powertrain that enabled a comprehensive
quantitative study of longitudinal vehicle performance during various stages in the design process. This model was developed using the functionality-based framework
and allowed a thorough exploration of the design space at various levels of fidelity. The
functionality-based sensitivity analysis implemented along with the behavioral modeling
approach provides measures similar to a variance-based approach with a computation
burden of a local approach. The use of a functional decomposition in both the
behavioral modeling and sensitivity analysis significantly contributes to the flexibility of
the models and their application in current and future design efforts. This contribution
was demonstrated in the application of the model to the 2009 Texas A&M Formula
Hybrid powertrain design.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2009-05-682 |
| Date | 16 January 2010 |
| Creators | Hutcheson, Ryan S. |
| Contributors | McAdams, Daniel |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation |
| Format | application/pdf |
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