dc.contributor.author	Tyll, Jason Scott	en
dc.contributor.committeechair	Schetz, Joseph A.	en
dc.contributor.committeemember	Mook, Dean T.	en
dc.contributor.committeemember	Mason, William H.	en
dc.contributor.committeemember	Marchman, James F. III	en
dc.contributor.committeemember	Deisenroth, Michael P.	en
dc.contributor.department	Aerospace and Ocean Engineering	en
dc.date.accessioned	2014-03-14T21:23:54Z	en
dc.date.adate	1997-08-05	en
dc.date.available	2014-03-14T21:23:54Z	en
dc.date.issued	1997-07-24	en
dc.date.rdate	1998-08-05	en
dc.date.sdate	1997-07-24	en
dc.description.abstract	A multidisciplinary design optimization (MDO) methodology is developed to link the aerodynamic shape design to the system costs for magnetically levitated (MAGLEV) vehicles. These railed vehicles can cruise at speeds approaching that of short haul aircraft and travel just inches from a guideway. They are slated for high speed intercity service of up to 500 miles in length and would compete with air shuttle services. The realization of this technology hinges upon economic viability which is the impetus for the design methodology presented here. This methodology involves models for the aerodynamics, structural weight, direct operating cost, acquisition cost, and life cycle cost and utilizes the DOT optimization software. Optimizations are performed using sequential quadratic programming for a 5 design variable problem. This problem is reformulated using 7 design variables to overcome problems due to non-smooth design space. The reformulation of the problem provides a smoother design space which is navigable by calculus based optimizers. The MDO methodology proves to be a useful tool for the design of MAGLEV vehicles. The optimizations show significant and sensible differences between designing for minimum life cycle cost and other figures of merit. The optimizations also show a need for a more sensitive acquisition cost model which is not based simply on weight engineering. As a part of the design methodology, a low-order aerodynamics model is developed for the prediction of 2-D, ground effect flow over bluff bodies. The model employs a continuous vortex sheet to model the solid surface, discrete vortices to model the shed wake, the Stratford Criterion to determine the location of the turbulent separation, and the vorticity conservation condition to determine the strength of the shed vorticity. The continuous vortex sheet better matches the mechanics of the flow than discrete singularities and therefore better predicts the ground effect flow. The predictions compare well with higher-order computational methods and experimental data. A 3-D extension to this model is investigated, although no 3-D design optimizations are performed. NOTE: An updated copy of this ETD was added on 05/29/2013.	en
dc.description.degree	Ph. D.	en
dc.identifier.other	etd-63097-162653	en
dc.identifier.sourceurl	http://scholar.lib.vt.edu/theses/available/etd-63097-162653/	en
dc.identifier.uri	http://hdl.handle.net/10919/40514	en
dc.publisher	Virginia Tech	en
dc.relation.haspart	appx.pdf	en
dc.relation.haspart	bib.pdf	en
dc.relation.haspart	ch1.pdf	en
dc.relation.haspart	ch2.pdf	en
dc.relation.haspart	ch3.pdf	en
dc.relation.haspart	ch4.pdf	en
dc.relation.haspart	ch5.pdf	en
dc.relation.haspart	ch6.pdf	en
dc.relation.haspart	ch7.pdf	en
dc.relation.haspart	ch8.pdf	en
dc.relation.haspart	2013_full_etd.pdf	en
dc.rights	In Copyright	en
dc.rights.uri	http://rightsstatements.org/vocab/InC/1.0/	en
dc.subject	ground effect aerodynamics	en
dc.subject	aerodynamics	en
dc.subject	Design	en
dc.subject	Optimization	en
dc.subject	MAGLEV	en
dc.title	Concurrent Aerodynamic Shape / Cost Design Of Magnetic Levitation Vehicles Using Multidisciplinary Design Optimization Techniques	en
dc.type	Dissertation	en
thesis.degree.discipline	Aerospace and Ocean Engineering	en
thesis.degree.grantor	Virginia Polytechnic Institute and State University	en
thesis.degree.level	doctoral	en
thesis.degree.name	Ph. D.	en

Concurrent Aerodynamic Shape / Cost Design Of Magnetic Levitation Vehicles Using Multidisciplinary Design Optimization Techniques

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