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.
Models and simulations are widely being used for design, optimization, fault detection and diagnosis, and various other decision-making purposes. Increasingly, models are developed at different scales and levels, all the way from molecular level to the large-scale process systems scale. Modelling of Chemical Process Systems gives readers a feel for the multiscale modelling. As models have been developed for various applications, a general systematic method for building model has emerged. This book starts with the history of modelling and its usefulness, describing modelling steps in detail. Examples have been chosen carefully from both conventional chemical process systems to contemporary systems, including fuel cell and bioprocesses. Modelling theories are complemented with case studies that explain step-by-step modelling methodologies. This book also introduces the application of machine learning techniques to model chemical process systems. This makes the book an indispensable reference for academics and professionals working in modelling and simulation. - Includes case studies that explain step-by-step modelling methodologies - Covers detailed multiscale modelling of chemical processes, providing examples from traditional and novel areas - Provides modelling insight at micro and macro-scale levels, including machine learning techniques
A solid introduction, enabling the reader to successfully formulate, construct, simplify, evaluate and use mathematical models in chemical engineering.
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.
Latest Edition: Linear Mathematical Models in Chemical Engineering (2nd Edition)Understanding the mathematical modeling of chemical processes is fundamental to the successful career of a researcher in chemical engineering. This book reviews, introduces, and develops the mathematics that is most frequently encountered in sophisticated chemical engineering models.The result of a collaboration between a chemical engineer and a mathematician, both of whom have taught classes on modeling and applied mathematics, the book provides a rigorous and in-depth coverage of chemical engineering model formulation and analysis as well as a text which can serve as an excellent introduction to linear mathematics for engineering students. There is a clear focus in the choice of material, worked examples, and exercises that make it unusually accessible to the target audience. The book places a heavy emphasis on applications to motivate the theory, but simultaneously maintains a high standard of rigor to add mathematical depth and understanding.
In this textbook, the author teaches readers how to model and simulate a unit process operation through developing mathematical model equations, solving model equations manually, and comparing results with those simulated through software. It covers both lumped parameter systems and distributed parameter systems, as well as using MATLAB and Simulink to solve the system model equations for both. Simplified partial differential equations are solved using COMSOL, an effective tool to solve PDE, using the fine element method. This book includes end of chapter problems and worked examples, and summarizes reader goals at the beginning of each chapter.
This comprehensive and thoroughly revised text, now in its second edition, continues to present the fundamental concepts of how mathematical models of chemical processes are constructed and demonstrate their applications to the simulation of two of the very important chemical engineering systems: the chemical reactors and distillation systems. The book provides an integrated treatment of process description, mathematical modelling and dynamic simulation of realistic problems, using the robust process model approach and its simulation with efficient numerical techniques. Theoretical background materials on activity coefficient models, equation of state models, reaction kinetics, and numerical solution techniques—needed for the development of mathematical models—are also addressed in the book. The topics of discussion related to tanks, heat exchangers, chemical reactors (both continuous and batch), biochemical reactors (continuous and fed-batch), distillation columns (continuous and batch), equilibrium flash vaporizer, and refinery debutanizer column contain several worked-out examples and case studies to teach students how chemical processes can be measured and monitored using computer programming. The new edition includes two more chapters—Reactive Distillation Column and Vaporizing Exchangers—which will further strengthen the text. This book is designed for senior level undergraduate and first-year postgraduate level courses in “Chemical Process Modelling and Simulation”. The book will also be useful for students of petrochemical engineering, biotechnology, and biochemical engineering. It can serve as a guide for research scientists and practising engineers as well.
This book treats modeling and simulation in a simple way, that builds on the existing knowledge and intuition of students. They will learn how to build a model and solve it using Excel. Most chemical engineering students feel a shiver down the spine when they see a set of complex mathematical equations generated from the modeling of a chemical engineering system. This is because they usually do not understand how to achieve this mathematical model, or they do not know how to solve the equations system without spending a lot of time and effort. Trying to understand how to generate a set of mathematical equations to represent a physical system (to model) and solve these equations (to simulate) is not a simple task. A model, most of the time, takes into account all phenomena studied during a Chemical Engineering course. In the same way, there is a multitude of numerical methods that can be used to solve the same set of equations generated from the modeling, and many different computational languages can be adopted to implement the numerical methods. As a consequence of this comprehensiveness and combinatorial explosion of possibilities, most books that deal with this subject are very extensive and embracing, making need for a lot of time and effort to go through this subject. It is expected that with this book the chemical engineering student and the future chemical engineer feel motivated to solve different practical problems involving chemical processes, knowing they can do that in an easy and fast way, with no need of expensive software.
