The 1990 CIME course on Mathematical Modelling of Industrial Processes set out to illustrate some advances in questions of industrial mathematics, i.e.of the applications of mathematics (with all its "academic" rigour) to real-life problems. The papers describe the genesis of the models and illustrate their relevant mathematical characteristics. Among the themesdealt with are: thermally controlled crystal growth, thermal behaviour of a high-pressure gas-discharge lamp, the sessile-drop problem, etching processes, the batch-coil- annealing process, inverse problems in classical dynamics, image representation and dynamical systems, scintillation in rear projections screens, identification of semiconductor properties,pattern recognition with neural networks. CONTENTS: H.K. Kuiken: Mathematical Modelling of Industrial Processes.- B. Forte: Inverse Problems in Mathematics for Industry.- S. Busenberg: Case Studies in Industrial Mathematics.

This book presents mathematical modelling and the integrated process of formulating sets of equations to describe real-world problems. It describes methods for obtaining solutions of challenging differential equations stemming from problems in areas such as chemical reactions, population dynamics, mechanical systems, and fluid mechanics. Chapters 1 to 4 cover essential topics in ordinary differential equations, transport equations and the calculus of variations that are important for formulating models. Chapters 5 to 11 then develop more advanced techniques including similarity solutions, matched asymptotic expansions, multiple scale analysis, long-wave models, and fast/slow dynamical systems. Methods of Mathematical Modelling will be useful for advanced undergraduate or beginning graduate students in applied mathematics, engineering and other applied sciences.

Polymers are substances made of macromolecules formed by thousands of atoms organized in one (homopolymers) or more (copolymers) groups that repeat themselves to form linear or branched chains, or lattice structures. The concept of polymer traces back to the years 1920's and is one of the most significant ideas of last century. It has given great impulse to indus try but also to fundamental research, including life sciences. Macromolecules are made of sm all molecules known as monomers. The process that brings monomers into polymers is known as polymerization. A fundamental contri bution to the industrial production of polymers, particularly polypropylene and polyethylene, is due to the Nobel prize winners Giulio Natta and Karl Ziegler. The ideas of Ziegler and Natta date back to 1954, and the process has been improved continuously over the years, particularly concerning the design and shaping of the catalysts. Chapter 1 (due to A. Fasano ) is devoted to a review of some results concerning the modelling of the Ziegler- Natta polymerization. The specific ex am pie is the production of polypropilene. The process is extremely complex and all studies with relevant mathematical contents are fairly recent, and several problems are still open.

These notes are based on the material presented in a series of lec tures in the IBM Systems Research Institute (ESRI) in Geneva durJng 1967-1969 to systems engineers working in the design and programming of computer systems for control and monitoring of i~nustrial proc esses. The purpose of the lectures and this book is to give a survey of dif ferent approaches in developing models to describe the behavior of the process in terms of controllable variables. It does not cover the theory of control, stability of control systems, nor techniques in data acquisition or problems in instrumentation and sampling. But certain aspects in the organization of data collection and design of experiments are obtained as side products, notably the concept of orthogonality. The reader is assumed to have a working knowledge of elementary prob ability theory and mathematical statistics. Therefore, the text con tains no introduction to these concepts. The author is aware of some inaccuracies in not making proper dis tinction between population parameters and their sample estimates in the text, but this should alw~s be evident from the context. The same applies to the occasional replacement of number of degrees of freedom by the number of samples in the data. In practice, computer collected sets of data consist of a high number of samples and the difference between the two is inSignificant.

Designed for undergraduate and postgraduate students, academic researchers and industrial practitioners, this book provides comprehensive case studies on numerical computing of industrial processes and step-by-step procedures for conducting industrial computing. It assumes minimal knowledge in numerical computing and computer programming, making it easy to read, understand and follow. Topics discussed include fundamentals of industrial computing, finite difference methods, the Wavelet-Collocation Method, the Wavelet-Galerkin Method, High Resolution Methods, and comparative studies of various methods. These are discussed using examples of carefully selected models from real processes of industrial significance. The step-by-step procedures in all these case studies can be easily applied to other industrial processes without a need for major changes. Thus, they provide readers with useful frameworks for the applications of engineering computing in fundamental research problems and practical development scenarios.

Computer simulation is the key to comprehending and controlling the full-scale industrial plant used in the chemical, oil, gas and electrical power industries. Simulation of Industrial Processes for Control Engineers shows how to use the laws of physics and chemistry to produce the equations to simulate dynamically all the most important unit operations found in process and power plant.The book explains how to model chemical reactors, nuclear reactors, distillation columns, boilers, deaerators, refrigeration vessels, storage vessels for liquids and gases, liquid and gas flow through pipes and pipe networks, liquid and gas flow through installed control valves, control valve dynamics (including nonlinear effects such as static friction), oil and gas pipelines, heat exchangers, steam and gas turbines, compressors and pumps, as well as process controllers (including three methods of integral desaturation). The phenomenon of markedly different time responses ("stiffness") is considered and various ways are presented to get around the potential problem of slow execution time. The book demonstrates how linearization may be used to give a diverse check on the correctness of the as-programmed model and explains how formal techniques of model validation may be used to produce a quantitative check on the simulation model's overall validity.The material is based on many years' experience of modelling and simulation in the chemical and power industries, supplemented in recent years by university teaching at the undergraduate and postgraduate level. Several important new results are presented. The depth is sufficient to allow real industrial problems to be solved, thus making the book attractive to engineers working in industry. But the book's step-by-step approach makes the text appropriate also for post-graduate students of control engineering and for undergraduate students in electrical, mechanical and chemical engineering who are studying process control in their second year or later.

Mathematical modelling is a powerful tool for solving optimisation problems in chemical engineering. In this work several models are proposed aimed at helping to make decisions about different aspects of the processes lifecycle, from the synthesis and design steps up to the operation and scheduling. Using an example of the Sugar Cane industry, several models are formulated and solved in order to assess the trade-offs involved in optimisation decisions. Thus, the power and versatility of mathematical modelling in the area of chemical processes optimisation is analysed and evaluated.

This is the first book on mathematical simulation on glass technology, and covers all production steps of special glass manufacturing. The enclosed CD-ROM shows 27 simulations of different aspects, such as surprising details of the pressing and casting process.

Written by international experts from industry, research centers, and academia, Mathematical Modeling of Food Processing discusses the physical and mathematical analysis of transport phenomena associated with food processing. The models presented describe many of the important physical and biological transformations that occur in food during proces

The proposed book will be divided into three parts. The chapters in Part I provide an overview of certain aspect of process retrofitting. The focus of Part II is on computational techniques for solving process retrofit problems. Finally, Part III addresses retrofit applications from diverse process industries. Some chapters in the book are contributed by practitioners whereas others are from academia. Hence, the book includes both new developments from research and also practical considerations. Many chapters include examples with realistic data. All these feature make the book useful to industrial engineers, researchers and students.