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Control of Polymerization Reactors
Manufacturer: CRC
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ASIN: 082479043X |
Book Description
This reference and text provides an in-depth description of developments in control techniques and their application to polymerization reactors and offers important introductory background information on polymerization reaction engineering.;Discussing modelling, identification, linear, nonlinear and multivariable schemes, Control of Polymerization Reactors: presents all available techniques that can be used to control reactors properly for optimal performance; shows how to manipulate pivotal variables that affect reactor control; examines methods for deriving dynamic process models to improve reactor efficiency; reviews reactor control problems and points out end-use properties; supplies methods for measuring process variables, and ways to estimate variables that can't be measured; and explains how single-input, single-output (SISO) strategies can be effectively used for control.;Filled with illustrative examples to clarify concepts, including more than 730 figures, tables and equations, Control of Polymerization Reactors is intended for use as a reference for chemical, process development, process design, research and development, control systems, and polymer engineers; and polymer chemists and physicists; as well as a text for upper-level undergraduate and graduate students in polymerization reactor control courses.
Customer Reviews:
Batch Reactors.......1999-02-13
Batch Reactors Control Technique
Book Description
This digital document is an article from Polymer Engineering and Science, published by Society of Plastics Engineers, Inc. on February 1, 1996. The length of the article is 5456 words. The page length shown above is based on a typical 300-word page. The article is delivered in HTML format and is available in your Amazon.com Digital Locker immediately after purchase. You can view it with any web browser.
From the author: Continuous polymerization processes may be very sensitive to small changes of the operation conditions. Continuous VA (vinyl acetate) solution homopolymerization reactors may present multiple steady-states and oscillatory behavior. A predictive control scheme that uses an internal model of the process is employed to stabilize such reactors and make them less sensitive to disturbances while subject to "hard" control action constraints. An ANN (artificial neural network) is used as the internal model, leading to fairly good predictions of the reactor behavior, including its multiplicities. The performance of the resulting control algorithm is compared to that of a "well-tuned" conventional proportional-integral-derivative (PID) controller.
Citation Details
Title: Control of a chaotic polymerization reactor: a neural network based model predictive approach.
Author: Mauricio B., Jr. de Souza
Publication:
Polymer Engineering and Science (Refereed)
Date: February 1, 1996
Publisher: Society of Plastics Engineers, Inc.
Volume: v36
Issue: n4
Page: p448(10)
Distributed by Thomson Gale
Book Description
This digital document is an article from Polymer Engineering and Science, published by Society of Plastics Engineers, Inc. on June 1, 2002. The length of the article is 6000 words. The page length shown above is based on a typical 300-word page. The article is delivered in HTML format and is available in your Amazon.com Digital Locker immediately after purchase. You can view it with any web browser.
From the author: This paper concerns nonlinear temperature control of a batch polymerization reactor where suspension polymerization of methyl methacrylate (MMA) takes place. For this purpose, four control algorithms, namely, a fix proportional-integral (PI) controller, an adaptive proportional-integral-derivative (PID) controller and two globally linearizing control (GLC) schemes, one for known kinetic model (GLC-I) and the other for unknown kinetic model (GLC-II), are selected. The performances of these controllers are compared through simulation and real-time studies in the presence of different levels of parameter uncertainty. The results indicate that GLC-I and GLC-II have better performances than fix PI and adaptive PID, especially in case of strong gel effect. The worst performance belongs to adaptive PD) because of rapid model changes in gel effect region. GLC-II has a simpler structure than GLC-I and can be used without requiring the kinetic model. In implementation of GLC-I the closed loop observer should be used be cause of model uncertainties.
Citation Details
Title: Nonlinear temperature control of a batch suspension polymerization reactor.(Statistical Data Included)
Author: Mohammad Shahrokhi
Publication:
Polymer Engineering and Science (Refereed)
Date: June 1, 2002
Publisher: Society of Plastics Engineers, Inc.
Volume: 42
Issue: 6
Page: 1296(13)
Article Type: Statistical Data Included
Distributed by Thomson Gale
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Parallel Solution of Partial Differential Equations
Manufacturer: Springer
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Binding: Hardcover
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ASIN: 0387950087 |
Book Description
The papers in this volume are based on lectures given at the IMA workshop on the Parallel Solution of PDE during June 9-13, 1997. The numerical solution of partial differential equations has been of major importance to the development of many technologies and has been the target of much of the development of parallel computer hardware and software. Parallel computer offers the promise of greatly increased performance and the routine calculation of previously intractable problems.This volume contains papers on the development and assessment of new approximation and solution techniques that can take advantage of parallel computers. It will be of interest to applied mathematicians, computer scientists, and engineers concerned with investigating the state of the art and future directions in numerical computing.Topics include domain decomposition methods, parallel multi-grid methods, front tracking methods, sparse matrix techniques, adaptive methods, fictitious domain methods, and novel time and space discretizations. Applications discussed include fluid dynamics, radiative transfer, solid mechanics, and semiconductor simulation.
Book Description
The book is suitable for readers with a background in basic finite element and finite difference methods for partial differential equations who wants gentle introductions to advanced topics like parallel computing, multigrid methods, and special methods for systems of PDEs. The goal of all chapters is to *compute* solutions to problems, hence algorithmic and software issues play a central role. All software examples use the Diffpack programming environment, so to take advantage of these examples some experience with Diffpack is required. There are also some chapters covering complete applications, i.e., the way from a model, expressed as systems of PDEs, through discretization methods, algorithms, software design, verification, and computational examples.
Book Description
Tremendous progress has been made in the scientific and engineering disciplines regarding the use of iterative methods for linear systems. The size and complexity of linear and nonlinear systems arising in typical applications has grown, meaning that using direct solvers for the three-dimensional models of these problems is no longer effective. At the same time, parallel computing, becoming less expensive and standardized, has penetrated these application areas. Iterative methods are easier than direct solvers to implement on parallel computers but require approaches and solution algorithms that are different from classical methods. This second edition gives an in-depth, up-to-date view of practical algorithms for solving large-scale linear systems of equations, including a wide range of the best methods available today. A new chapter on multigrid techniques has been added, whilst material throughout has been updated, removed or shortened. Numerous exercises have been added, as well as an updated and expanded bibliography.
Customer Reviews:
Excellent work.......2006-08-12
We used this book to prove a theorem in our studies that is directly related to my PhD thesis on spatial data mining and spatial statistics. This book is a master-piece.
Thanks Dr. Saad.
Wonderful Book.......2005-06-30
This is one of my favorite books in my library on this subject. Also I have used this book for my class as main textbook along with "Iterative Methods for Solving Linear and Nonlinear Equations" by C. T. Kelley , which is another SIAM book.
Highly recommended.
Great Book.......2000-05-24
This is a great book for this subject. The book is easy to follow and Saad does a wonderful job of illustrating with examples. This is a great textbook or a book for reference. This book does a particularly good job with Krylov methods and does a reasonable job with preconditioning.
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Numerical Solution of Partial Differential Equations on Parallel Computers (Lecture Notes in Computational Science and Engineering)
Manufacturer: Springer
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The Sourcebook of Parallel Computing (The Morgan Kaufmann Series in Computer Architecture and Design)
ASIN: 3540290761 |
Book Description
This book surveys the major topics that are essential to high-performance simulation on parallel computers or computational clusters. These topics, including programming models, load balancing, mesh generation, efficient numerical solvers, and scientific software, are vital ingredients in the research fields of computer science, numerical analysis, and scientific computing. In addition to presenting the technological basis, this volume addresses selected applications that combine different techniques in order to meet demanding computational challenges. Through contributions from a wide range of internationally acknowledged experts, this book gives a to-the-point and self-containing overview of efficient ways to deal with large-scale simulation problems.
Book Description
This book contains contributions from the invited speakers to the fifth S.E.R.C Summer School in Numerical Analysis, which was held at Lancaster University from 19th to 31st July, 1992. The expositions were at a level which could be understood by post-graduate research students, yet would be advanced enough to stimulate established researchers. The book should therefore be useful to a wide class of readers. The topics which are covered include some of the most important areas of current research in numerical analysis. The contributors are: Jesse L. Barlow, Pennsylvania State University; Professor Jack Dongarra, Oak Ridge National Library; Professor Howard C. Elman, Institute for Advanced Computer Studies, Maryland; Professor Randolph E. Bank, University of California; Professor J.W. Jerome, Northwestern University, and Professor Maurizio Pandolfi, Politecnico di Torino, Italy.
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Algorithms for Elliptic Problems, Efficient Sequential and Parallel Solvers (Mathematics and its Applications)
Marián Vajtersic
Manufacturer: Springer
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ASIN: 0792319184 |
Book Description
This volume deals with problems of modern effective algorithms for the numerical solution of the most frequently occurring elliptic partial differential equations. From the point of view of implementation, attention is paid to algorithms for both classical sequential and parallel computer systems.
The first two chapters are devoted to fast algorithms for solving the Poisson and biharmonic equation. In the third chapter, parallel algorithms for model parallel computer systems of the SIMD and MIMD types are described. The implementation aspects of parallel algorithms for solving model elliptic boundary value problems are outlined for systems with matrix, pipeline and multiprocessor parallel computer architectures. A modern and popular multigrid computational principle which offers a good opportunity for a parallel realization is described in the next chapter. More parallel variants based in this idea are presented, whereby methods and assignments strategies for hypercube systems are treated in more detail. The last chapter presents VLSI designs for solving special tridiagonal linear systems of equations arising from finite-difference approximations of elliptic problems.
For researchers interested in the development and application of fast algorithms for solving elliptic partial differential equations using advanced computer systems.
Book Description
This book presents an easy-to-read discussion of domain decomposition algorithms, their implementation and analysis. The relationship between domain decomposition and multigrid methods is carefully explained at an elementary level, and discussions of the implementation of domain decomposition methods on massively parallel super computers are also included. All algorithms are fully described and explained, and a mathematical framework for the analysis and complete understanding of the methods is also carefully developed. In addition, numerous numerical examples are included to demonstrate the behaviour of this important class of numerical methods. This book is ideal for graduate students about to embark on a career in computational science. It will also be a valuable resource for all those interested in parallel computing and numerical computational methods.
Customer Reviews:
Good book that introduces domain decomposition.......1999-10-21
A little something for everyone in this text. Discussion of computational issues, references, algorithms, and some convergence analysis. The authors do a good job of covering the subject at an understandable level. A small fault with the book is it leaves you wanting more! Excellent way to learn about these methods on your own.
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Solving Partial Differential Equations on Parallel Computers an Introduction
Jianping Zhu
Manufacturer: World Scientific Publishing Company
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Binding: Hardcover
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ASIN: 9810215789 |
Book Description
This is an introductory book on supercomputer applications written by a researcher who is working on solving scientific and engineering application problems on parallel computers. The book is intended to quickly bring researchers and graduate students working on numerical solutions of partial differential equations with various applications into the area of parallel processing. The book starts from the basic concepts of parallel processing, like speedup, efficiency and different parallel architectures, then introduces the most frequently used algorithms for solving PDEs on parallel computers, with practical examples. Finally, it discusses more advanced topics, including different scalability metrics, parallel time stepping algorithms and new architectures and heterogeneous computing networks which have emerged in the last few years of high performance computing. Hundreds of references are also included in the book to direct interested readers to more detailed and in-depth discussions of specific topics.
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A Tutorial on Elliptic Pde Solvers and Their Parallelization (Software, Environments, and Tools)
Craig C. Douglas ,
Gundolf Haase , and
Ulrich Langer
Manufacturer: Society for Industrial and Applied Mathematic
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ASIN: 0898715415 |
Book Description
This compact yet thorough tutorial is the perfect introduction to the basic concepts of solving partial differential equations (PDEs) using parallel numerical methods. In just eight short chapters, the authors provide readers with enough basic knowledge of PDEs, discretization methods, solution techniques, parallel computers, parallel programming, and the run-time behavior of parallel algorithms to allow them to understand, develop, and implement parallel PDE solvers. Examples throughout the book are intentionally kept simple so that the parallelization strategies are not dominated by technical details.
A Tutorial on Elliptic PDE Solvers and Their Parallelization is a valuable aid for learning about the possible errors and bottlenecks in parallel computing. One of the highlights of the tutorial is that the course material can run on a laptop, not just on a parallel computer or cluster of PCs, thus allowing readers to experience their first successes in parallel computing in a relatively short amount of time.
Audience
This tutorial is intended for advanced undergraduate and graduate students in computational sciences and engineering; however, it may also be helpful to professionals who use PDE-based parallel computer simulations in the field.
Contents
List of figures; List of algorithms; Abbreviations and notation; Preface; Chapter 1: Introduction; Chapter 2: A simple example; Chapter 3: Introduction to parallelism; Chapter 4: Galerkin finite element discretization of elliptic partial differential equations; Chapter 5: Basic numerical routines in parallel; Chapter 6: Classical solvers; Chapter 7: Multigrid methods; Chapter 8: Problems not addressed in this book; Appendix: Internet addresses; Bibliography; Index.
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