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Application of Genetic Algorithm Opt...
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ProQuest Information and Learning Co.
Application of Genetic Algorithm Optimization of Thermodynamic Fluids Designs.
Record Type:
Language materials, manuscript : Monograph/item
Title/Author:
Application of Genetic Algorithm Optimization of Thermodynamic Fluids Designs./
Author:
Yobby, Jason.
Description:
1 online resource (63 pages)
Notes:
Source: Masters Abstracts International, Volume: 57-01.
Subject:
Mechanical engineering. -
Online resource:
click for full text (PQDT)
ISBN:
9780355357325
Application of Genetic Algorithm Optimization of Thermodynamic Fluids Designs.
Yobby, Jason.
Application of Genetic Algorithm Optimization of Thermodynamic Fluids Designs.
- 1 online resource (63 pages)
Source: Masters Abstracts International, Volume: 57-01.
Thesis (M.S.)--Southern Illinois University at Edwardsville, 2017.
Includes bibliographical references
Several engineering problems exist that require optimization. Most design cases on paper are usually one or two dimensional and are used in theoretical approaches to design problems. Here, the genetic algorithm based optimization will be applied to real world thermo-fluidic applications, optimization of cooling fin parameters for an internal combustion engine and dollar cost optimization of a high bypass ratio turbofan engine component improvements with specified flight constraints. The time study of the optimization of the second case is also presented to show the significant reduction of computation time from other methods when high degrees of freedom are required in computations.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9780355357325Subjects--Topical Terms:
557493
Mechanical engineering.
Index Terms--Genre/Form:
554714
Electronic books.
Application of Genetic Algorithm Optimization of Thermodynamic Fluids Designs.
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Adviser: Terry X. Yan.
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Includes bibliographical references
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Several engineering problems exist that require optimization. Most design cases on paper are usually one or two dimensional and are used in theoretical approaches to design problems. Here, the genetic algorithm based optimization will be applied to real world thermo-fluidic applications, optimization of cooling fin parameters for an internal combustion engine and dollar cost optimization of a high bypass ratio turbofan engine component improvements with specified flight constraints. The time study of the optimization of the second case is also presented to show the significant reduction of computation time from other methods when high degrees of freedom are required in computations.
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Ann Arbor, Mich. :
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ProQuest,
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2018
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Mode of access: World Wide Web
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Mechanical engineering.
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click for full text (PQDT)
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