Advanced Modelling and Simulation in the Chemical and Biochemical Process Industry explores modelling and simulation of chemical and biochemical processes at the industrial scale using a variety of approaches. Particular attention is devoted to simulations in different scales, which help achieve a wide-spectrum and more efficient analysis of several problems, ranging from the design of novel materials to the optimization of industrial processes as a function of the operating conditions. This book not only covers optimization with experimental data but also offers readers a thorough understanding and analysis of different parameters of a whole process stream. Covers a wide range of advanced modelling and simulation of chemical technologies: ab initio, atomistic molecular dynamics (MD), Lattice-Boltzmann (LB), dissipative particle dynamics (DPD), computational fluid dynamics (CFD), and finite element (FEM) Addresses issues associated with process control in different phases of the chemical industry Features modelling approaches that allow the design of novel processes/materials in a faster and more reliable way This book will be of interest to researchers and advanced readers in chemical, biochemical, environmental, and materials engineering and industrial chemistry.

The use of simulation plays a vital part in developing an integrated approach to process design. By helping save time and money before the actual trial of a concept, this practice can assist with troubleshooting, design, control, revamping, and more. Process Modelling and Simulation in Chemical, Biochemical and Environmental Engineering explores effective modeling and simulation approaches for solving equations. Using a systematic treatment of model development and simulation studies for chemical, biochemical, and environmental processes, this book explains the simplification of a complicated process at various levels with the help of a "model sketch." It introduces several types of models, examines how they are developed, and provides examples from a wide range of applications. This includes the simple models based on simple laws such as Fick’s law, models that consist of generalized equations such as equations of motion, discrete-event models and stochastic models (which consider at least one variable as a discrete variable), and models based on population balance. Divided into 11 chapters, this book: Presents a systematic approach of model development in view of the simulation need Includes modeling techniques to model hydrodynamics, mass and heat transfer, and reactors for single as well as multi-phase systems Provides stochastic and population balance models Covers the application and development of artificial neural network models and hybrid ANN models Highlights gradients based techniques as well as statistical techniques for model validation and sensitivity analysis Contains examples on development of analytical, stochastic, numerical, and ANN-based models and simulation studies using them Illustrates modeling concepts with a wide spectrum of classical as well as recent research papers Process Modelling and Simulation in Chemical, Biochemical and Environmental Engineering includes recent trends in modeling and simulation, e.g. artificial neural network (ANN)-based models, and hybrid models. It contains a chapter on flowsheeting and batch processes using commercial/open source software for simulation.

This book features selected contributions in the areas of modeling, simulation, and optimization. The contributors discusses requirements in problem solving for modeling, simulation, and optimization. Modeling, simulation, and optimization have increased in demand in exponential ways and how potential solutions might be reached. They describe how new technologies in computing and engineering have reduced the dimension of data coverage worldwide, and how recent inventions in information and communication technology (ICT) have inched towards reducing the gaps and coverage of domains globally. The chapters cover how the digging of information in a large data and soft-computing techniques have contributed to a strength in prediction and analysis, for decision making in computer science, technology, management, social computing, green computing, and telecom. The book provides an insightful reference to the researchers in the fields of engineering and computer science. Researchers, academics, and professionals will benefit from this volume. Features selected expanded papers in modeling, simulation, and optimization from COMPSE 2016; Includes research into soft computing and its application in engineering and technology; Presents contributions from global experts in academia and industry in modeling, simulation, and optimization.

The role of theory in science was formulated very brilliantly by Max Planck: Experimenters are the striking force of science. The experiment is a question which science puts to nature. The measurement is the registration of nature’s answer. But before the question is put to nature,it must be formulated. Before the measurement result is used,itmust be explained, i.e., the answer must be understood correctly. These two problems are obligations of the theoreticians. Chemical engineering is an experimental science, but theory permits us to formulate correct experimental conditions and to understand correctly the exp- imental results. The theoretical methods of chemical engineering for modeling and simulation of industrial processes are surveyed in this book. Theoretical chemical engineering solves the problems that spring up from the necessity for a quantitative description of the processes in the chemical industry. They are quite different at the different stages of the quantitative description, i.e., a wide circle of theoretical methods are required for their solutions. Modeling and simulation are a united approach to obtain a quantitative description of the processes and systems in chemical engineering and chemical technology, which is necessary to clarify the process mechanism or for optimal process design, process control, and plant renovation. Modeling is the creation of the mathematical model, i.e., construction of the mathematical description (on the basis of the process mechanism), calculation of the model parameters (using experimental data), and statistical analysis of the model adequacy.

Chemical Engineering Process Simulation, Second Edition guides users through chemical processes and unit operations using the main simulation software used in the industrial sector. The book helps predict the characteristics of a process using mathematical models and computer-aided process simulation tools, as well as how to model and simulate process performance before detailed process design takes place. Content coverage includes steady-state and dynamic simulation, process design, control and optimization. In addition, readers will learn about the simulation of natural gas, biochemical, wastewater treatment and batch processes. - Provides an updated and expanded new edition that contains 60-70% new content - Guides readers through chemical processes and unit operations using the primary simulation software used in the industrial sector - Covers the fundamentals of process simulation, theory and advanced applications - Includes case studies of various difficulty levels for practice and for applying developed skills - Features step-by-step guides to using UniSim Design, SuperPro Designer, Symmetry, Aspen HYSYS and Aspen Plus for process simulation novices

A description of the use of computer aided modeling and simulation in the development, integration and optimization of industrial processes. The two authors elucidate the entire procedure step-by-step, from basic mathematical modeling to result interpretation and full-scale process performance analysis. They further demonstrate similitude comparisons of experimental results from different systems as a tool for broadening the applicability of the calculation methods. Throughout, the book adopts a very practical approach, addressing actual problems and projects likely to be encountered by the reader, as well as fundamentals and solution strategies for complex problems. It is thus equally useful for student and professional engineers and chemists involved in industrial process and production plant design, construction or upgrading.

The main object of this advanced textbook is modelling and simulation of energetic processes by bond graphs. But even without knowledge of this powerful method, it can be used to a certain extent as an introduction to simulation in thermodynamics.

This book provides a rigorous treatment of the fundamental concepts and techniques involved in process modeling and simulation. The book allows the reader to: (i) Get a solid grasp of “under-the-hood” mathematical results (ii) Develop models of sophisticated processes (iii) Transform models to different geometries and domains as appropriate (iv) Utilize various model simplification techniques (v) Learn simple and effective computational methods for model simulation (vi) Intensify the effectiveness of their research Modeling and Simulation for Chemical Engineers: Theory and Practice begins with an introduction to the terminology of process modeling and simulation. Chapters 2 and 3 cover fundamental and constitutive relations, while Chapter 4 on model formulation builds on these relations. Chapters 5 and 6 introduce the advanced techniques of model transformation and simplification. Chapter 7 deals with model simulation, and the final chapter reviews important mathematical concepts. Presented in a methodical, systematic way, this book is suitable as a self-study guide or as a graduate reference, and includes examples, schematics and diagrams to enrich understanding. End of chapter problems with solutions and computer software available online at www.wiley.com/go/upreti/pms_for_chemical_engineers are designed to further stimulate readers to apply the newly learned concepts.

In this book, the modelling of dynamic chemical engineering processes is presented in a highly understandable way using the unique combination of simplified fundamental theory and direct hands-on computer simulation. The mathematics is kept to a minimum, and yet the nearly 100 examples supplied on www.wiley-vch.de illustrate almost every aspect of chemical engineering science. Each example is described in detail, including the model equations. They are written in the modern user-friendly simulation language Berkeley Madonna, which can be run on both Windows PC and Power-Macintosh computers. Madonna solves models comprising many ordinary differential equations using very simple programming, including arrays. It is so powerful that the model parameters may be defined as "sliders", which allow the effect of their change on the model behavior to be seen almost immediately. Data may be included for curve fitting, and sensitivity or multiple runs may be performed. The results can be seen simultaneously on multiple-graph windows or by using overlays. The resultant learning effect of this is tremendous. The examples can be varied to fit any real situation, and the suggested exercises provide practical guidance. The extensive experience of the authors, both in university teaching and international courses, is reflected in this well-balanced presentation, which is suitable for the teacher, the student, the chemist or the engineer. This book provides a greater understanding of the formulation and use of mass and energy balances for chemical engineering, in a most stimulating manner. This book is a third edition, which also includes biological, environmental and food process examples.

Advanced Data Analysis and Modeling in Chemical Engineering provides the mathematical foundations of different areas of chemical engineering and describes typical applications. The book presents the key areas of chemical engineering, their mathematical foundations, and corresponding modeling techniques. Modern industrial production is based on solid scientific methods, many of which are part of chemical engineering. To produce new substances or materials, engineers must devise special reactors and procedures, while also observing stringent safety requirements and striving to optimize the efficiency jointly in economic and ecological terms. In chemical engineering, mathematical methods are considered to be driving forces of many innovations in material design and process development. - Presents the main mathematical problems and models of chemical engineering and provides the reader with contemporary methods and tools to solve them - Summarizes in a clear and straightforward way, the contemporary trends in the interaction between mathematics and chemical engineering vital to chemical engineers in their daily work - Includes classical analytical methods, computational methods, and methods of symbolic computation - Covers the latest cutting edge computational methods, like symbolic computational methods