國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Numerical approximation of the magne...

Romer, Ulrich.

Numerical approximation of the magnetoquasistatic model with uncertaintiesapplications in magnet design /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Numerical approximation of the magnetoquasistatic model with uncertaintiesby Ulrich Romer.
其他題名:	applications in magnet design /
作者:	Romer, Ulrich.
出版者:	Cham :Springer International Publishing :2016.
面頁冊數:	xxii, 114 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Approximation theory.
電子資源:	http://dx.doi.org/10.1007/978-3-319-41294-8
ISBN:	9783319412948$q(electronic bk.)

Numerical approximation of the magnetoquasistatic model with uncertaintiesapplications in magnet design /
Romer, Ulrich.

Numerical approximation of the magnetoquasistatic model with uncertaintiesapplications in magnet design /[electronic resource] :by Ulrich Romer. - Cham :Springer International Publishing :2016. - xxii, 114 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

Introduction -- Magnetoquasistatic Approximation of Maxwell's Equations, Uncertainty Quantification Principles -- Magnetoquasistatic Model and its Numerical Approximation -- Parametric Model, Continuity and First Order Sensitivity Analysis -- Uncertainty Quantification -- Uncertainty Quantification for Magnets -- Conclusion and Outlook.

This book presents a comprehensive mathematical approach for solving stochastic magnetic field problems. It discusses variability in material properties and geometry, with an emphasis on the preservation of structural physical and mathematical properties. It especially addresses uncertainties in the computer simulation of magnetic fields originating from the manufacturing process. Uncertainties are quantified by approximating a stochastic reformulation of the governing partial differential equation, demonstrating how statistics of physical quantities of interest, such as Fourier harmonics in accelerator magnets, can be used to achieve robust designs. The book covers a number of key methods and results such as: a stochastic model of the geometry and material properties of magnetic devices based on measurement data; a detailed description of numerical algorithms based on sensitivities or on a higher-order collocation; an analysis of convergence and efficiency; and the application of the developed model and algorithms to uncertainty quantification in the complex magnet systems used in particle accelerators.

ISBN: 9783319412948$q(electronic bk.)

Standard No.: 10.1007/978-3-319-41294-8doiSubjects--Topical Terms:

185327
Approximation theory.

LC Class. No.: QA221

Dewey Class. No.: 511.4

Numerical approximation of the magnetoquasistatic model with uncertaintiesapplications in magnet design /
LDR:02506nmm a2200337 a 4500 001 493019
003 DE-He213
005 20160727124416.0
006 m d
007 cr nn 008maaau
008 170220s2016 gw s 0 eng d
020 $a 9783319412948$q(electronic bk.)
020 $a 9783319412931$q(paper)
024 7 $a 10.1007/978-3-319-41294-8 $2 doi
035 $a 978-3-319-41294-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA221
072 7 $a TJFN $2 bicssc
072 7 $a TEC024000 $2 bisacsh
072 7 $a TEC030000 $2 bisacsh
082 0 4 $a 511.4 $2 23
090 $a QA221 $b .R763 2016
100 1 $a Romer, Ulrich. $3 753525
245 1 0 $a Numerical approximation of the magnetoquasistatic model with uncertainties $h [electronic resource] : $b applications in magnet design / $c by Ulrich Romer.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xxii, 114 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer theses, $x 2190-5053
505 0 $a Introduction -- Magnetoquasistatic Approximation of Maxwell's Equations, Uncertainty Quantification Principles -- Magnetoquasistatic Model and its Numerical Approximation -- Parametric Model, Continuity and First Order Sensitivity Analysis -- Uncertainty Quantification -- Uncertainty Quantification for Magnets -- Conclusion and Outlook.
520 $a This book presents a comprehensive mathematical approach for solving stochastic magnetic field problems. It discusses variability in material properties and geometry, with an emphasis on the preservation of structural physical and mathematical properties. It especially addresses uncertainties in the computer simulation of magnetic fields originating from the manufacturing process. Uncertainties are quantified by approximating a stochastic reformulation of the governing partial differential equation, demonstrating how statistics of physical quantities of interest, such as Fourier harmonics in accelerator magnets, can be used to achieve robust designs. The book covers a number of key methods and results such as: a stochastic model of the geometry and material properties of magnetic devices based on measurement data; a detailed description of numerical algorithms based on sensitivities or on a higher-order collocation; an analysis of convergence and efficiency; and the application of the developed model and algorithms to uncertainty quantification in the complex magnet systems used in particle accelerators.
650 0 $a Approximation theory. $3 185327
650 0 $a Measurement uncertainty (Statistics) $3 753526
650 1 4 $a Engineering. $3 210888
650 2 4 $a Microwaves, RF and Optical Engineering. $3 274186
650 2 4 $a Structural Mechanics. $3 274624
650 2 4 $a Engineering Design. $3 273752
650 2 4 $a Particle Acceleration and Detection, Beam Physics. $3 275493
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Springer theses. $3 557607
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-41294-8
950 $a Engineering (Springer-11647)