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001			86230
003			ES-MaUEC
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007			cr nn 008mamaa
008			160727s2016 gw | s |||| 0|eng d
020			_a9783319412948
024	7		_a10.1007/978-3-319-41294-8 _2doi
040			_aES-MaUEC
050		4	_aQA221 _b.R66 2016 EB
082	0	4	_a621.3
100	1		_aRömer, Ulrich _999792 _0Local
245	1	0	_aNumerical Approximation of the Magnetoquasistatic Model with Uncertainties : _bApplications in Magnet Design _cby Ulrich Römer
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XXII, 114 p.) _b20 ilustraciones, 8 ilustraciones en color
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
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
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, EBSPRINGER
650		7	_aAproximación, Teoría de la _0comprobar BNE20030337496 _2embne _9160958
650		7	_aAceleradores de partículas _9139563 _0comprobar BNE19900973975 _2embne
650		7	_aAnálisis estructural (Ingeniería) _0comprobar BNE19951016435 _2embne _9150495
830		0	_aSpringer Theses, Recognizing Outstanding Ph.D. Research _x2190-5053 _9133434
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-41294-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319412948
907			_a.b12955085 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b09-09-17 _cm _dz _eo _feng _ggw _h0
945			_aQA221 .R66 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11597318 _z06-04-17
999			_c86230 _d86230 _x1