Numerical Simulation of Distributed Parameter Processes, 1st Edition

  • Published By:
  • ISBN-10: 3319000144
  • ISBN-13: 9783319000145
  • DDC: 003.78
  • Grade Level Range: College Freshman - College Senior
  • 343 Pages | eBook
  • Original Copyright 2013 | Published/Released June 2014
  • This publication's content originally published in print form: 2013

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The present monograph defines, interprets and uses the matrix of partial derivatives of the state vector with applications for the study of some common categories of engineering. The book covers broad categories of processes that are formed by systems of partial derivative equations (PDEs), including systems of ordinary differential equations (ODEs). The work includes numerous applications specific to Systems Theory based on Mpdx, such as parallel, serial as well as feed-back connections for the processes defined by PDEs. For similar, more complex processes based on Mpdx with PDEs and ODEs as components, we have developed control schemes with PID effects for the propagation phenomena, in continuous media (spaces) or discontinuous ones (chemistry, power system, thermo-energetic) or in electro-mechanics (railway – traction) and so on.The monograph has a purely engineering focus and is intended for a target audience working in extremely diverse fields of application (propagation phenomena, diffusion, hydrodynamics, electromechanics) in which the use of PDEs and ODEs is justified.

Table of Contents

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
1: Processes with Lumped Parameters.
2: Linear Processes Invariant in Time.
3: Time-Varying Linear Processes.
4: Nonlinear Processes with Lumped Parameters.
5: Processes with Distributed Parameters.
6: Linear Processes with Distributed Parameters.
7: Nonlinear Processes with Distributed Parameters.
8: Truncated Errors of the Operator Matrix Mpdx.
9: Simulation Examples.
10: Modeling and Simulation Examples for Lumped Parameters Processes.
11: Modeling: Simulation Examples for Distributed Parameters Processes.
12: Case Studies for Establishing the Mpdx Matrix.
13: Partial Derivative Equations in the Cartesian Space.
14: Parallel, Serial and with Feed-Back Connections, for the Processes Modeled through PDE.
15: Control Systems with Distributed and Lumped Parameters in the Cartesian Space: Cases Studies.
16: Numerical Simulation Using Partial Differential Equations, for Propagation and Control in Discontinuous Structures Processes.
17: Conclusions.
Summary for Mpdx Matrix.
Local-Iterative Linearization Method.
Regarding the Convergence of the Local-Iterative Linearization Method.