000			04127nam a22005535i 4500
001			978-3-319-29994-5
003			DE-He213
005			20180206182939.0
007			cr nn 008mamaa
008			160301s2016 gw | s |||| 0|eng d
020			_a9783319299945 _9978-3-319-29994-5
050		4	_aTA405-409.3
050		4	_aQA808.2
072		7	_aTG _2bicssc
072		7	_aTEC009070 _2bisacsh
072		7	_aTEC021000 _2bisacsh
082	0	4	_a620.1 _223
100	1		_aCueto, Elías. _eauthor.
245	1	0	_aProper Generalized Decompositions _h[recurso electrónico] : _bAn Introduction to Computer Implementation with Matlab / _cby Elías Cueto, David González, Icíar Alfaro.
250			_a1st ed. 2016.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016.
300			_aXII, 96 p. 20 illus., 1 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		_aSpringerBriefs in Applied Sciences and Technology, _x2191-530X
505	0		_aIntroduction -- 2 To begin with: PGD for Poisson problems -- 2.1 Introduction -- 2.2 The Poisson problem -- 2.3 Matrix structure of the problem -- 2.4 Matlab code for the Poisson problem -- 3 Parametric problems -- 3.1 A particularly challenging problem: a moving load as a parameter -- 3.2 The problem under the PGD formalism -- 3.2.1 Computation of S(s) assuming R(x) is known -- 3.2.2 Computation of R(x) assuming S(s) is known -- 3.3 Matrix structure of the problem -- 3.4 Matlab code for the influence line problem -- 4 PGD for non-linear problems -- 4.1 Hyperelasticity -- 4.2 Matrix structure of the problem -- 4.2.1 Matrix form of the term T2 -- 4.2.2 Matrix form of the term T4 -- 4.2.3 Matrix form of the term T6 -- 4.2.4 Matrix form for the term T8 -- 4.2.5 Matrix form of the term T9 -- 4.2.6 Matrix form of the term T10 -- 4.2.7 Final comments -- 4.3 Matlab code -- 5 PGD for dynamical problems -- 5.1 Taking initial conditions as parameters -- 5.2 Developing the weak form of the problem -- 5.3 Matrix form of the problem -- 5.3.1 Time integration of the equations of motion -- 5.3.2 Computing a reduced-order basis for the field of initial conditions -- 5.3.3 Projection of the equations onto a reduced, parametric basis -- 5.4 Matlab code -- References -- Index.
520			_aThis book is intended to help researchers overcome the entrance barrier to Proper Generalized Decomposition (PGD), by providing a valuable tool to begin the programming task. Detailed Matlab Codes are included for every chapter in the book, in which the theory previously described is translated into practice. Examples include parametric problems, non-linear model order reduction and real-time simulation, among others. Proper Generalized Decomposition (PGD) is a method for numerical simulation in many fields of applied science and engineering. As a generalization of Proper Orthogonal Decomposition or Principal Component Analysis to an arbitrary number of dimensions, PGD is able to provide the analyst with very accurate solutions for problems defined in high dimensional spaces, parametric problems and even real-time simulation.
650		0	_aEngineering.
650		0	_aComputer mathematics.
650		0	_aPhysics.
650		0	_aContinuum mechanics.
650	1	4	_aEngineering.
650	2	4	_aContinuum Mechanics and Mechanics of Materials.
650	2	4	_aComputational Science and Engineering.
650	2	4	_aNumerical and Computational Physics.
700	1		_aGonzález, David. _eauthor.
700	1		_aAlfaro, Icíar. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319299938
830		0	_aSpringerBriefs in Applied Sciences and Technology, _x2191-530X
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://dx.doi.org/10.1007/978-3-319-29994-5
912			_aZDB-2-ENG
942			_cLIBRO_ELEC
999			_c225575 _d225575