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000754105 020__ $$a9783319299945$$q(electronic book)
000754105 020__ $$a3319299948$$q(electronic book)
000754105 020__ $$z9783319299938
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000754105 0247_ $$a10.1007/978-3-319-29994-5$$2doi
000754105 035__ $$aSP(OCoLC)ocn944157913
000754105 035__ $$aSP(OCoLC)944157913
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000754105 049__ $$aISEA
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000754105 08204 $$a518$$223
000754105 1001_ $$aCueto, Elias,$$eauthor.
000754105 24510 $$aProper generalized decompositions$$h[electronic resource] :$$ban introduction to computer implementation with Matlab /$$cElías Cueto, David González, Icíar Alfaro.
000754105 264_1 $$aCham :$$bSpringer,$$c2016.
000754105 300__ $$a1 online resource (xii, 96 pages) :$$billustrations.
000754105 336__ $$atext$$btxt$$2rdacontent
000754105 337__ $$acomputer$$bc$$2rdamedia
000754105 338__ $$aonline resource$$bcr$$2rdacarrier
000754105 4901_ $$aSpringerBriefs in applied sciences and technology,$$x2191-530X
000754105 504__ $$aIncludes bibliographical references and index.
000754105 5050_ $$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. .
000754105 506__ $$aAccess limited to authorized users.
000754105 520__ $$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. .
000754105 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed March 9, 2016).
000754105 63000 $$aMATLAB.
000754105 650_0 $$aDecomposition (Mathematics)
000754105 650_0 $$aMatrices.
000754105 7001_ $$aGonzález, David,$$eauthor.
000754105 7001_ $$aAlfaro, Icíar,$$eauthor.
000754105 77608 $$iPrint version:$$z331929993X$$z9783319299938$$w(OCoLC)935185867
000754105 830_0 $$aSpringerBriefs in applied sciences and technology.
000754105 852__ $$bebk
000754105 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-29994-5$$zOnline Access$$91397441.1
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000754105 980__ $$aBIB
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