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001 978-3-319-41294-8
003 DE-He213
005 20200421112042.0
007 cr nn 008mamaa
008 160727s2016 gw | s |||| 0|eng d
020 _a9783319412948
_9978-3-319-41294-8
024 7 _a10.1007/978-3-319-41294-8
_2doi
050 4 _aTK7876-7876.42
072 7 _aTJFN
_2bicssc
072 7 _aTEC024000
_2bisacsh
072 7 _aTEC030000
_2bisacsh
082 0 4 _a621.3
_223
100 1 _aR�omer, Ulrich.
_eauthor.
245 1 0 _aNumerical Approximation of the Magnetoquasistatic Model with Uncertainties
_h[electronic resource] :
_bApplications in Magnet Design /
_cby Ulrich R�omer.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXXII, 114 p. 20 illus., 8 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5053
505 0 _aIntroduction -- 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 _aThis 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 _aEngineering.
650 0 _aParticle acceleration.
650 0 _aStructural mechanics.
650 0 _aEngineering design.
650 0 _aMicrowaves.
650 0 _aOptical engineering.
650 1 4 _aEngineering.
650 2 4 _aMicrowaves, RF and Optical Engineering.
650 2 4 _aStructural Mechanics.
650 2 4 _aEngineering Design.
650 2 4 _aParticle Acceleration and Detection, Beam Physics.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319412931
830 0 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5053
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-41294-8
912 _aZDB-2-ENG
942 _cEBK
999 _c56676
_d56676