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dc.contributorMcAdams, Daniel
dc.creatorHutcheson, Ryan S.
dc.date.accessioned2010-01-16T00:09:43Z
dc.date.accessioned2017-04-07T19:54:28Z
dc.date.available2010-01-16T00:09:43Z
dc.date.available2017-04-07T19:54:28Z
dc.date.created2009-05
dc.date.issued2010-01-16
dc.identifier.urihttp://hdl.handle.net/1969.1/ETD-TAMU-2009-05-682
dc.description.abstractComplex 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.
dc.language.isoen_US
dc.subjectfunctional modeling
dc.subjectcomplex systems design
dc.subjectdesign theory
dc.subjectsystems engineering
dc.subjecthybrid vehicle design
dc.subjectsensitivity analysis
dc.subjectbehavioral modeling
dc.titleFunction-based Design Tools for Analyzing the Behavior and Sensitivity of Complex Systems During Conceptual Design
dc.typeBook
dc.typeThesis


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