000 07438nam a22005175i 4500
001 978-0-387-30260-7
003 DE-He213
005 20161121230518.0
007 cr nn 008mamaa
008 100301s2006 xxu| s |||| 0|eng d
020 _a9780387302607
_9978-0-387-30260-7
024 7 _a10.1007/0-387-30260-3
_2doi
050 4 _aQA76.9.C65
072 7 _aUGK
_2bicssc
072 7 _aCOM072000
_2bisacsh
082 0 4 _a003.3
_223
100 1 _aCellier, François E.
_eauthor.
245 1 0 _aContinuous System Simulation
_h[electronic resource] /
_cby François E. Cellier, Ernesto Kofman.
264 1 _aBoston, MA :
_bSpringer US,
_c2006.
300 _aXXII, 644 p. 284 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aIntroduction, Scope, Definitions -- Modeling and Simulation: A Circuit Example -- Modeling vs. Simulation -- Time and Again -- Simulation as a Problem Solving Tool -- Simulation Software: Today and Tomorrow -- Basic Principles of Numerical Integration -- Introduction -- The Approximation Accuracy -- Euler Integration -- The Domain of Numerical Stability -- The Newton Iteration -- Semi–analytic Algorithms -- Spectral Algorithms -- Single–step Integration Methods -- Introduction -- Runge–Kutta Algorithms -- Stability Domains of RK Algorithms -- Stiff Systems -- Extrapolation Techniques -- Marginally Stable Systems -- Backinterpolation Methods -- Accuracy Considerations -- Step–size and Order Control -- Multi–step Integration Methods -- Introduction -- Newton–Gregory Polynomials -- Numerical Integration Through Polynomial Extrapolation -- Explicit Adams–Bashforth Formulae -- Implicit Adams–Moulton Formulae -- Adams–Bashforth–Moulton Predictor–Corrector Formulae -- Backward Difference Formulae -- Nyström and Milne Algorithms -- In Search for Stiffly–stable Methods -- High–order Backward Difference Formulae -- Newton Iteration -- Step–size and Order Control -- The Startup Problem -- The Readout Problem -- Second Derivative Systems -- Introduction -- Conversion of Second–derivative Models to State–space Form -- Velocity–free Models -- Linear Velocity Models -- Nonlinear Velocity Models -- Stability and Damping of Godunov Scheme -- Explicit and Implicit Godunov Algorithms of Different Orders -- The Newmark Algorithm -- Partial Differential Equations -- Introduction -- The Method of Lines -- Parabolic PDEs -- Hyperbolic PDEs -- Shock Waves -- Upwind Discretization -- Grid–width Control -- PDEs in Multiple Space Dimensions -- Elliptic PDEs and Invariant Embedding -- Finite Element Approximations -- Differential AlgebraicEquations -- Introduction -- Causalization of Equations -- Algebraic Loops -- The Tearing Algorithm -- The Relaxation Algorithm -- Structural Singularities -- Structural Singularity Elimination -- The Solvability Issue -- Differential Algebraic Equation Solvers -- Introduction -- Multi-step Formulae -- Single–step Formulae -- DASSL -- Inline Integration -- Inlining Implicit Runge–Kutta Algorithms -- Stiffly Stable Step–size Control of Radau IIA -- Stiffly Stable Step–size Control of Lobatto IIIC -- Inlining Partial Differential Equations -- Overdetermined DAEs -- Electronic Circuit Simulators -- Multibody System Dynamics Simulators -- Chemical Process Dynamics Simulators -- Simulation of Discontinuous Systems -- Introduction -- Basic Difficulties -- Time Events -- Simulation of Sampled–data Systems -- State Events (1. Multiple Zero Crossings, 2. Single Zero Crossings, Single–step Algorithms, 3. Single Zero Crossings, Multi-step Algorithms, 4. Non–essential State Events) -- Consistent Initial Conditions -- Object–oriented Descriptions of Discontinuities ( 1. The Computational Causality of if–Statements, 2. Multi–valued Functions) -- The Switch Equation -- Ideal Diodes and Parameterized Curve Descriptions -- Variable Structure Models -- Mixed–mode Integration -- State Transition Diagrams -- Petri Nets -- Real–time Simulation -- Introduction -- The Race Against Time -- Suitable Numerical Integration Methods -- Linearly Implicit Methods -- Multi–rate Integration -- Inline Integration -- Mixed–mode Integration -- Discontinuous Systems -- Simulation Architecture -- Overruns -- Discrete Event Simulation -- Introduction -- Space Discretization: A Simple Example -- Discrete Event Systems and DEVS -- Coupled DEVS Models -- Simulation of DEVS Models -- DEVS and Continuous Systems Simulation -- Quantized State Systems -- Quantization-based Integration -- Introduction.-.
520 _aContinuous System Simulation describes systematically and methodically how mathematical models of dynamic systems, usually described by sets of either ordinary or partial differential equations possibly coupled with algebraic equations, can be simulated on a digital computer. Modern modeling and simulation environments relieve the occasional user from having to understand how simulation really works. Once a mathematical model of a process has been formulated, the modeling and simulation environment compiles and simulates the model, and curves of result trajectories appear magically on the user’s screen. Yet, magic has a tendency to fail, and it is then that the user must understand what went wrong, and why the model could not be simulated as expected. Continuous System Simulation is written by engineers for engineers, introducing the partly symbolical and partly numerical algorithms that drive the process of simulation in terms that are familiar to simulation practitioners with an engineering background, and yet, the text is rigorous in its approach and comprehensive in its coverage, providing the reader with a thorough and detailed understanding of the mechanisms that govern the simulation of dynamical systems. Continuous System Simulation is a highly software-oriented text, based on MATLAB. Homework problems, suggestions for term project, and open research questions conclude every chapter to deepen the understanding of the student and increase his or her motivation. Continuous System Simulation is the first text of its kind that has been written for an engineering audience primarily. Yet due to the depth and breadth of its coverage, the book will also be highly useful for readers with a mathematics background. The book has been designed to accompany senior and graduate students enrolled in a simulation class, but it may also serve as a reference and self-study guide for modeling and simulation practitioners.
650 0 _aComputer science.
650 0 _aNumerical analysis.
650 0 _aComputer science
_xMathematics.
650 0 _aComputer simulation.
650 0 _aComputer mathematics.
650 0 _aComputational intelligence.
650 1 4 _aComputer Science.
650 2 4 _aSimulation and Modeling.
650 2 4 _aComputational Mathematics and Numerical Analysis.
650 2 4 _aNumeric Computing.
650 2 4 _aComputational Intelligence.
650 2 4 _aSymbolic and Algebraic Manipulation.
700 1 _aKofman, Ernesto.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387261027
856 4 0 _uhttp://dx.doi.org/10.1007/0-387-30260-3
912 _aZDB-2-SCS
950 _aComputer Science (Springer-11645)
999 _c499880
_d499880