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Power flow prediction in vibrating s...

Li, Xianhui.

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Power flow prediction in vibrating systems via model reduction.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Power flow prediction in vibrating systems via model reduction./
Author:	Li, Xianhui.
Description:	128 p.
Notes:	Source: Dissertation Abstracts International, Volume: 65-03, Section: B, page: 1514.
Contained By:	Dissertation Abstracts International65-03B.
Subject:	Engineering, Mechanical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3124851
ISBN:	0496721542

Power flow prediction in vibrating systems via model reduction.
Li, Xianhui.

Power flow prediction in vibrating systems via model reduction. - 128 p.

Source: Dissertation Abstracts International, Volume: 65-03, Section: B, page: 1514.

Thesis (Ph.D.)--Boston University, 2004.

This dissertation focuses on power flow prediction in vibrating systems. Reduced order models (ROMs) are built based on rational Krylov model reduction which preserve power flow information in the original systems over a specified frequency band. Stiffness and mass matrices of the ROMs are obtained by projecting the original system matrices onto the subspaces spanned by forced responses. A matrix-free algorithm is designed to construct ROMs directly from the power quantities at selected interpolation frequencies. Strategies for parallel implementation of the algorithm via message passing interface are proposed. The quality of ROMs is iteratively refined according to the error estimate based on residual norms. Band capacity is proposed to provide a priori estimate of the sizes of good quality ROMs. Frequency averaging is recast as ensemble averaging and Cauchy distribution is used to simplify the computation. Besides model reduction for deterministic systems, details of constructing ROMs for parametric and nonparametric random systems are also presented. Case studies have been conducted on testbeds from Harwell-Boeing collections. Input and coupling power flow are computed for the original systems and the ROMs. Good agreement is observed in all cases.

ISBN: 0496721542Subjects--Topical Terms:

783786
Engineering, Mechanical.

Power flow prediction in vibrating systems via model reduction.
LDR:02150nmm 2200277 4500 001 1850613
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008 130614s2004 eng d
020 $a 0496721542
035 $a (UnM)AAI3124851
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040 $a UnM $c UnM
100 1 $a Li, Xianhui. $3 1938532
245 1 0 $a Power flow prediction in vibrating systems via model reduction.
300 $a 128 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-03, Section: B, page: 1514.
500 $a Major Professor: James G. McDaniel.
502 $a Thesis (Ph.D.)--Boston University, 2004.
520 $a This dissertation focuses on power flow prediction in vibrating systems. Reduced order models (ROMs) are built based on rational Krylov model reduction which preserve power flow information in the original systems over a specified frequency band. Stiffness and mass matrices of the ROMs are obtained by projecting the original system matrices onto the subspaces spanned by forced responses. A matrix-free algorithm is designed to construct ROMs directly from the power quantities at selected interpolation frequencies. Strategies for parallel implementation of the algorithm via message passing interface are proposed. The quality of ROMs is iteratively refined according to the error estimate based on residual norms. Band capacity is proposed to provide a priori estimate of the sizes of good quality ROMs. Frequency averaging is recast as ensemble averaging and Cauchy distribution is used to simplify the computation. Besides model reduction for deterministic systems, details of constructing ROMs for parametric and nonparametric random systems are also presented. Case studies have been conducted on testbeds from Harwell-Boeing collections. Input and coupling power flow are computed for the original systems and the ROMs. Good agreement is observed in all cases.
590 $a School code: 0017.
650 4 $a Engineering, Mechanical. $3 783786
650 4 $a Physics, Acoustics. $3 1019086
690 $a 0548
690 $a 0986
710 2 0 $a Boston University. $3 1017454
773 0 $t Dissertation Abstracts International $g 65-03B.
790 1 0 $a McDaniel, James G., $e advisor
790 $a 0017
791 $a Ph.D.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3124851