Artificial Intelligence In Chemical Engineering

Author: Thomas E. Quantrille
Publisher: Elsevier
ISBN: 0080571212
Size: 57.60 MB
Format: PDF
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Artificial intelligence (AI) is the part of computer science concerned with designing intelligent computer systems (systems that exhibit characteristics we associate with intelligence in human behavior). This book is the first published textbook of AI in chemical engineering, and provides broad and in-depth coverage of AI programming, AI principles, expert systems, and neural networks in chemical engineering. This book introduces the computational means and methodologies that are used to enable computers to perform intelligent engineering tasks. A key goal is to move beyond the principles of AI into its applications in chemical engineering. After reading this book, a chemical engineer will have a firm grounding in AI, know what chemical engineering applications of AI exist today, and understand the current challenges facing AI in engineering. Allows the reader to learn AI quickly using inexpensive personal computers Contains a large number of illustrative examples, simple exercises, and complex practice problems and solutions Includes a computer diskette for an illustrated case study Demonstrates an expert system for separation synthesis (EXSEP) Presents a detailed review of published literature on expert systems and neural networks in chemical engineering

Artificial Intelligence In Chemical Engineering

Author: Thomas E. Quantrille
Publisher:
ISBN:
Size: 39.84 MB
Format: PDF, Docs
View: 6364
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Artificial intelligence (AI) is the part of computer science concerned with designing intelligent computer systems (systems that exhibit characteristics we associate with intelligence in human behavior). This book is the first published textbook of AI in chemical engineering, and provides broad and in-depth coverage of AI programming, AI principles, expert systems, and neural networks in chemical engineering. This book introduces the computational means and methodologies that are used to enable computers to perform intelligent engineering tasks. A key goal is to move beyond the principles of AI into its applications in chemical engineering. After reading this book, a chemical engineer will have a firm grounding in AI, know what chemical engineering applications of AI exist today, and understand the current challenges facing AI in engineering. Key Features * Allows the reader to learn AI quickly using inexpensive personal computers * Contains a large number of illustrative examples, simple exercises, and complex practice problems and solutions * Includes a computer diskette for an illustrated case study * Demonstrates an expert system for separation synthesis (EXSEP) * Presents a detailed review of published literature on expert systems and neural networks in chemical engineering

Artificial Intelligence In Process Engineering

Author: Michael Mavrovouniotis
Publisher: Elsevier
ISBN: 0323153143
Size: 52.92 MB
Format: PDF, ePub, Docs
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Artificial Intelligence in Process Engineering aims to present a diverse sample of Artificial Intelligence (AI) applications in process engineering. The book contains contributions, selected by the editors based on educational value and diversity of AI methods and process engineering application domains. Topics discussed in the text include the use of qualitative reasoning for modeling and simulation of chemical systems; the use of qualitative models in discrete event simulation to analyze malfunctions in processing systems; and the diagnosis of faults in processes that are controlled by Programmable Logic Controllers. There are also debates on the issue of quantitative versus qualitative information. The control of batch processes, a design of a system that synthesizes bioseparation processes, and process design in the domain of chemical (rather than biochemical) systems are likewise covered in the text. This publication will be of value to industrial engineers and process engineers and researchers.

Refinery Engineering

Author: Ai-Fu Chang
Publisher: John Wiley & Sons
ISBN: 3527666850
Size: 71.21 MB
Format: PDF, Kindle
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A pioneering and comprehensive introduction to the complex subject of integrated refinery process simulation, using many of the tools and techniques currently employed in modern refineries. Adopting a systematic and practical approach, the authors include the theory, case studies and hands-on workshops, explaining how to work with real data. As a result, senior-level undergraduate and graduate students, as well as industrial engineers learn how to develop and use the latest computer models for the predictive modeling and optimization of integrated refinery processes. Additional material is available online providing relevant spreadsheets and simulation files for all the models and examples presented in the book.

Applications Of Metaheuristics In Process Engineering

Author: Jayaraman Valadi
Publisher: Springer
ISBN: 3319065084
Size: 20.38 MB
Format: PDF, ePub, Mobi
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Metaheuristics exhibit desirable properties like simplicity, easy parallelizability and ready applicability to different types of optimization problems such as real parameter optimization, combinatorial optimization and mixed integer optimization. They are thus beginning to play a key role in different industrially important process engineering applications, among them the synthesis of heat and mass exchange equipment, synthesis of distillation columns and static and dynamic optimization of chemical and bioreactors. This book explains cutting-edge research techniques in related computational intelligence domains and their applications in real-world process engineering. It will be of interest to industrial practitioners and research academics.

Using Artificial Intelligence In Chemistry And Biology

Author: Hugh Cartwright
Publisher: CRC Press
ISBN: 9780849384141
Size: 59.21 MB
Format: PDF, ePub, Mobi
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Possessing great potential power for gathering and managing data in chemistry, biology, and other sciences, Artificial Intelligence (AI) methods are prompting increased exploration into the most effective areas for implementation. A comprehensive resource documenting the current state-of-the-science and future directions of the field is required to furnish the working experimental scientist and newcomer alike with the background necessary to utilize these methods. In response to the growing interest in the potential scientific applications of AI, Using Artificial Intelligence in Chemistry and Biology explains in a lucid, straightforward manner how these methods are used by scientists and what can be accomplished with them. Designed for those with no prior knowledge of AI, computer science, or programming, this book efficiently and quickly takes you to the point at which meaningful scientific applications can be investigated. The approach throughout is practical and direct, employing figures and illustrations to add clarity and humor to the topics at hand. Unique in scope, addressing the needs of scientists across a range of disciplines, this book provides both a broad overview and a detailed introduction to each of the techniques discussed. Chapters include an introduction to artificial intelligence, artificial neural networks, self-organizing maps, growing cell structures, evolutionary algorithms, cellular automata, expert systems, fuzzy logic, learning classifier systems, and evolvable developmental systems. The book also comes with a CD containing a complete version of the EJS software with which most of the calculations were accomplished. Encouraging a broader application of AI methods, this seminal work gives software designers a clearer picture of how scientists use AI and how to address those needs, and provides chemists, biologists, physicists, and others with the tools to increase the speed and efficiency of their work.

Artificial Intelligence In Engineering Design

Author: Gerard Meurant
Publisher: Academic Press
ISBN: 0323139957
Size: 32.62 MB
Format: PDF, Kindle
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Artificial Intelligence in Engineering Design is a three-volume edited collection of key papers from the field of AI and design, aimed at providing a state-of-the art description of the field, and focusing on how ideas and methods from artificial intelligence can help engineers in the design of physical artifacts and processes. The books survey a wide variety of applications in the areas of civil, chemical, electrical, computer, VLSI, and mechanical engineering.

Composite Materials Technology

Author: S.M. Sapuan
Publisher: CRC Press
ISBN: 9781420093339
Size: 57.38 MB
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Artificial neural networks (ANN) can provide new insight into the study of composite materials and can normally be combined with other artificial intelligence tools such as expert system, genetic algorithm, and fuzzy logic. Because research on this field is very new, there is only a limited amount of published literature on the subject. Compiling information from diverse sources, Composite Materials Technology: Neural Network Applications fills the void in knowledge of these important networks, covering composite mechanics, materials characterization, product design, and other important aspects of polymer matrix composites. Light weight, corrosion resistance, good stiffness and strength properties, and part consolidation are just some of the reasons that composites are useful in areas including civil engineering and structure, chemical processing, management, agriculture, space study, and manufacturing. ANN has already been used to carry out design prediction, mechanical property prediction, and selection processes in the evolution of composites, but although it has already been used with great success in various branches of scientific and technological research, it is still in the nascent stage of its development. Featuring contributions from leading researchers throughout the world, this book is divided into four parts, starting with an introduction to neural networks and a review of existing literature on the subject. The text then covers structural health monitoring and damage detection in composites, addresses mechanical properties, and discusses design, analysis, and materials selection. Training, testing, and validation of experimental data were carried out to optimize the results presented in the book. This book will be an important aid to researchers as they work on the future implementation of ANN in industries such as aerospace, automotive, marine, sporting goods, furniture, and electronics and communication.

Intelligent Systems In Process Engineering Part Ii Paradigms From Process Operations

Author:
Publisher: Academic Press
ISBN: 9780080565699
Size: 75.85 MB
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Volumes 21 and 22 of Advances in Chemical Engineering contain ten prototypical paradigms which integrate ideas and methodologies from artificial intelligence with those from operations research, estimation andcontrol theory, and statistics. Each paradigm has been constructed around an engineering problem, e.g. product design, process design, process operations monitoring, planning, scheduling, or control. Along with the engineering problem, each paradigm advances a specific methodological theme from AI, such as: modeling languages; automation in design; symbolic and quantitative reasoning; inductive and deductive reasoning; searching spaces of discrete solutions; non-monotonic reasoning; analogical learning;empirical learning through neural networks; reasoning in time; and logic in numerical computing. Together the ten paradigms of the two volumes indicate how computers can expand the scope, type, and amount of knowledge that can be articulated and used in solving a broad range of engineering problems. Sets the foundations for the development of computer-aided tools for solving a number of distinct engineering problems Exposes the reader to a variety of AI techniques in automatic modeling, searching, reasoning, and learning The product of ten-years experience in integrating AI into process engineering Offers expanded and realistic formulations of real-world problems

Artificial Intelligence And Expert Systems For Engineers

Author: C.S. Krishnamoorthy
Publisher: CRC Press
ISBN: 1351465589
Size: 28.98 MB
Format: PDF, Kindle
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This book provides a comprehensive presentation of artificial intelligence (AI) methodologies and tools valuable for solving a wide spectrum of engineering problems. What's more, it offers these AI tools on an accompanying disk with easy-to-use software. Artificial Intelligence and Expert Systems for Engineers details the AI-based methodologies known as: Knowledge-Based Expert Systems (KBES); Design Synthesis; Design Critiquing; and Case-Based Reasoning. KBES are the most popular AI-based tools and have been successfully applied to planning, diagnosis, classification, monitoring, and design problems. Case studies are provided with problems in engineering design for better understanding of the problem-solving models using the four methodologies in an integrated software environment. Throughout the book, examples are given so that students and engineers can acquire skills in the use of AI-based methodologies for application to practical problems ranging from diagnosis to planning, design, and construction and manufacturing in various disciplines of engineering. Artificial Intelligence and Expert Systems for Engineers is a must-have reference for students, teachers, research scholars, and professionals working in the area of civil engineering design in particular and engineering design in general.