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Reduced order modeling, nonlinear an...

Kasnakoglu, Cosku.

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Reduced order modeling, nonlinear analysis and control methods for flow control problems.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Reduced order modeling, nonlinear analysis and control methods for flow control problems./
Author:	Kasnakoglu, Cosku.
Description:	162 p.
Notes:	Adviser: Andrea Serrani.
Contained By:	Dissertation Abstracts International68-10B.
Subject:	Engineering, Aerospace. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3286787
ISBN:	9780549299622

Reduced order modeling, nonlinear analysis and control methods for flow control problems.
Kasnakoglu, Cosku.

Reduced order modeling, nonlinear analysis and control methods for flow control problems. - 162 p.

Adviser: Andrea Serrani.

Thesis (Ph.D.)--The Ohio State University, 2007.

Flow control refers to the ability to manipulate fluid flow so as to achieve a desired change in its behavior, which offers many potential technological benefits, such as reducing fuel costs for vehicles and improving effectiveness of industrial processes. An interesting case of flow control is cavity flow control, which has been the motivation of this study: When air flow passes over a shallow cavity a strong resonance is produced by a natural feedback mechanism, scattering acoustic waves that propagate upstream and reach the shear layer, and developing flow structures. These cause many practical problems including damage and fatigue in landing gears and weapons bays in aircrafts. Presently there is a lack of sufficient mathematical analysis and control design tools for flow control problems. This includes mathematical models that are amenable to control design. Recently reduced-order modeling techniques, such as those based on proper orthogonal decomposition (POD) and Galerkin projection (GP), have come to interest. However, a main issue with these models is that the effect of boundary conditions, which is where the control input is, gets embedded into system coefficients. This results in a form quite different from what one deals with in standard control systems framework, which is a set of ordinary differential equations (ODE) where the input appears as an explicit term. Another issue with the standard POD/GP models is that they do not yield to systems that have any apparent structure in their coefficients. This leaves one with little choice other than to neglect the nonlinearities of the models and employ standard linear control theory based designs.

ISBN: 9780549299622Subjects--Topical Terms:

1018395
Engineering, Aerospace.

Reduced order modeling, nonlinear analysis and control methods for flow control problems.
LDR:03190nam 2200313 a 45 001 958212
005 20110704
008 110704s2007 ||||||||||||||||| ||eng d
020 $a 9780549299622
035 $a (UMI)AAI3286787
035 $a AAI3286787
040 $a UMI $c UMI
100 1 $a Kasnakoglu, Cosku. $3 1281670
245 1 0 $a Reduced order modeling, nonlinear analysis and control methods for flow control problems.
300 $a 162 p.
500 $a Adviser: Andrea Serrani.
500 $a Source: Dissertation Abstracts International, Volume: 68-10, Section: B, page: 6856.
502 $a Thesis (Ph.D.)--The Ohio State University, 2007.
520 $a Flow control refers to the ability to manipulate fluid flow so as to achieve a desired change in its behavior, which offers many potential technological benefits, such as reducing fuel costs for vehicles and improving effectiveness of industrial processes. An interesting case of flow control is cavity flow control, which has been the motivation of this study: When air flow passes over a shallow cavity a strong resonance is produced by a natural feedback mechanism, scattering acoustic waves that propagate upstream and reach the shear layer, and developing flow structures. These cause many practical problems including damage and fatigue in landing gears and weapons bays in aircrafts. Presently there is a lack of sufficient mathematical analysis and control design tools for flow control problems. This includes mathematical models that are amenable to control design. Recently reduced-order modeling techniques, such as those based on proper orthogonal decomposition (POD) and Galerkin projection (GP), have come to interest. However, a main issue with these models is that the effect of boundary conditions, which is where the control input is, gets embedded into system coefficients. This results in a form quite different from what one deals with in standard control systems framework, which is a set of ordinary differential equations (ODE) where the input appears as an explicit term. Another issue with the standard POD/GP models is that they do not yield to systems that have any apparent structure in their coefficients. This leaves one with little choice other than to neglect the nonlinearities of the models and employ standard linear control theory based designs.
520 $a The research presented in this thesis makes an effort at closing the gaps mentioned above by (1) presenting a reduced-order modeling method utilizing a novel technique for input separation on POD/GP models, (2) introducing a technique based on averaging theory and center manifold theory so as to reveal certain structures embedded in the model, and (3) developing nonlinear analysis and control design approaches for the resulting model. The theory is complemented by examples and case studies as appropriate, including the case of cavity flow control.
590 $a School code: 0168.
650 4 $a Engineering, Aerospace. $3 1018395
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, Mechanical. $3 783786
650 4 $a Physics, Fluid and Plasma. $3 1018402
690 $a 0538
690 $a 0544
690 $a 0548
690 $a 0759
710 2 $a The Ohio State University. $3 718944
773 0 $t Dissertation Abstracts International $g 68-10B.
790 $a 0168
790 1 0 $a Serrani, Andrea, $e advisor
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3286787