04517nam 22006975 450 991025425580332120251202121824.03-319-29994-810.1007/978-3-319-29994-5(CKB)3710000000611079(EBL)4428784(SSID)ssj0001653790(PQKBManifestationID)16432834(PQKBTitleCode)TC0001653790(PQKBWorkID)14982503(PQKB)10716006(DE-He213)978-3-319-29994-5(MiAaPQ)EBC4428784(PPN)192770446(EXLCZ)99371000000061107920160301d2016 u| 0engur|n|---|||||txtccrProper Generalized Decompositions An Introduction to Computer Implementation with Matlab /by Elías Cueto, David González, Icíar Alfaro1st ed. 2016.Cham :Springer International Publishing :Imprint: Springer,2016.1 online resource (103 p.)SpringerBriefs in Applied Sciences and Technology,2191-5318Description based upon print version of record.3-319-29993-X Includes bibliographical references and index.Introduction -- 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. .This 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. .SpringerBriefs in Applied Sciences and Technology,2191-5318Mechanics, AppliedSolidsMathematicsData processingMathematical physicsSolid MechanicsComputational Science and EngineeringTheoretical, Mathematical and Computational PhysicsMechanics, Applied.Solids.MathematicsData processing.Mathematical physics.Solid Mechanics.Computational Science and Engineering.Theoretical, Mathematical and Computational Physics.518.2Cueto Elíasauthttp://id.loc.gov/vocabulary/relators/aut0González Davidauthttp://id.loc.gov/vocabulary/relators/autAlfaro Icíarauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910254255803321UNINA