Advanced Data Analysis And Modelling In Chemical Engineering

Author : Denis Constales,Gregory S. Yablonsky,Dagmar R. D'hooge,Joris W. Thybaut,Guy B. Marin
Publisher : Elsevier
Page : 414 pages
File Size : 54,8 Mb
Release : 2016-08-23
Category : Technology & Engineering
ISBN : 9780444594846

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Advanced Data Analysis and Modelling in Chemical Engineering by Denis Constales,Gregory S. Yablonsky,Dagmar R. D'hooge,Joris W. Thybaut,Guy B. Marin Pdf

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

Author : Y. A. Liu,Niket Sharma
Publisher : John Wiley & Sons
Page : 1027 pages
File Size : 54,6 Mb
Release : 2023-07-25
Category : Technology & Engineering
ISBN : 9783527843824

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Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing by Y. A. Liu,Niket Sharma Pdf

Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing Detailed resource on the “Why,” “What,” and “How” of integrated process modeling, advanced control and data analytics explained via hands-on examples and workshops for optimizing polyolefin manufacturing. Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing discusses, as well as demonstrates, the optimization of polyolefin production by covering topics from polymer process modeling and advanced process control to data analytics and machine learning, and sustainable design and industrial practice. The text also covers practical problems, handling of real data streams, developing the right level of detail, and tuning models to the available data, among other topics, to allow for easy translation of concepts into practice. Written by two highly qualified authors, Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing includes information on: Segment-based modeling of polymer processes; selection of thermodynamic methods; estimation of physical properties for polymer process modeling Reactor modeling, convergence tips and data-fit tool; free radical polymerization (LDPE, EVA and PS), Ziegler-Natta polymerization (HDPE, PP, LLPDE, and EPDM) and ionic polymerization (SBS rubber) Improved polymer process operability and control through steady-state and dynamic simulation models Model-predictive control of polyolefin processes and applications of multivariate statistics and machine learning to optimizing polyolefin manufacturing Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing enables readers to make full use of advanced computer models and latest data analytics and machine learning tools for optimizing polyolefin manufacturing, making it an essential resource for undergraduate and graduate students, researchers, and new and experienced engineers involved in the polyolefin industry.

Author : Scott A. Pardo
Publisher : Springer
Page : 247 pages
File Size : 41,8 Mb
Release : 2016-07-19
Category : Mathematics
ISBN : 9783319327686

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Empirical Modeling and Data Analysis for Engineers and Applied Scientists by Scott A. Pardo Pdf

This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions. While science is about discovery, the primary paradigm of engineering and "applied science" is design. Scientists are in the discovery business and want, in general, to understand the natural world rather than to alter it. In contrast, engineers and applied scientists design products, processes, and solutions to problems. That said, statistics, as a discipline, is mostly oriented toward the discovery paradigm. Young engineers come out of their degree programs having taken courses such as "Statistics for Engineers and Scientists" without any clear idea as to how they can use statistical methods to help them design products or processes. Many seem to think that statistics is only useful for demonstrating that a device or process actually does what it was designed to do. Statistics courses emphasize creating predictive or classification models - predicting nature or classifying individuals, and statistics is often used to prove or disprove phenomena as opposed to aiding in the design of a product or process. In industry however, Chemical Engineers use designed experiments to optimize petroleum extraction; Manufacturing Engineers use experimental data to optimize machine operation; Industrial Engineers might use data to determine the optimal number of operators required in a manual assembly process. This text teaches engineering and applied science students to incorporate empirical investigation into such design processes. Much of the discussion in this book is about models, not whether the models truly represent reality but whether they adequately represent reality with respect to the problems at hand; many ideas focus on how to gather data in the most efficient way possible to construct adequate models. Includes chapters on subjects not often seen together in a single text (e.g., measurement systems, mixture experiments, logistic regression, Taguchi methods, simulation) Techniques and concepts introduced present a wide variety of design situations familiar to engineers and applied scientists and inspire incorporation of experimentation and empirical investigation into the design process. Software is integrally linked to statistical analyses with fully worked examples in each chapter; fully worked using several packages: SAS, R, JMP, Minitab, and MS Excel - also including discussion questions at the end of each chapter. The fundamental learning objective of this textbook is for the reader to understand how experimental data can be used to make design decisions and to be familiar with the most common types of experimental designs and analysis methods.

Author : Guillermo Fernando Barreto
Publisher : Springer Nature
Page : 151 pages
File Size : 40,8 Mb
Release : 2024-07-01
Category : Electronic
ISBN : 9783031423758

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Applying Multiple-Reaction Stoichiometry to Chemical Reactor Modelling by Guillermo Fernando Barreto Pdf

Author : Anonim
Publisher : Academic Press
Page : 350 pages
File Size : 52,5 Mb
Release : 2020-10-31
Category : Technology & Engineering
ISBN : 9780128215227

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Advances in Polymer Reaction Engineering by Anonim Pdf

Advances in Polymer Reaction Engineering, Volume 56 in the Advances in Chemical Engineering series is aimed at reporting the latest advances in the field of polymer synthesis. Chapters in this new release include Polymer reaction engineering and composition control in free radical copolymers, Reactor control and on-line process monitoring in free radical emulsion polymerization, Exploiting pulsed laser polymerization to retrieve intrinsic kinetic parameters in radical polymerization, 3D printing in chemical engineering, Renewable source monomers in waterborne polymer dispersions, Importance of models and digitalization in Polymer Reaction Engineering, Recent Advances in Modelling of Radical Polymerization, and more. Covers recent advances in the control and monitoring of polymerization processes and in reactor configurations Provides modelling of polymerization reactions and up-to-date approaches to estimate reaction rate constants Includes authoritative opinions from experts in academia and industry

Author : Muhammad Akhyar Farrukh
Publisher : BoD – Books on Demand
Page : 226 pages
File Size : 46,9 Mb
Release : 2018-02-21
Category : Science
ISBN : 9789535138150

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Advanced Chemical Kinetics by Muhammad Akhyar Farrukh Pdf

The book on Advanced Chemical Kinetics gives insight into different aspects of chemical reactions both at the bulk and nanoscale level and covers topics from basic to high class. This book has been divided into three sections: (i) "Kinetics Modeling and Mechanism," (ii) "Kinetics of Nanomaterials," and (iii) "Kinetics Techniques." The first section consists of six chapters with a variety of topics like activation energy and complexity of chemical reactions; the measurement of reaction routes; mathematical modeling analysis and simulation of enzyme kinetics; mechanisms of homogeneous charge compression ignition combustion for the fuels; photophysical processes and photochemical changes; the mechanism of hydroxyl radical, hydrate electron, and hydrogen atom; and acceptorless alcohol dehydrogenation. The understanding of the kinetics of nanomaterials, to bridge the knowledge gap, is presented in the second section. The third section highlights an overview of experimental techniques used to study the mechanism of reactions.

Author : Yuri A.W. Shardt
Publisher : Springer Nature
Page : 454 pages
File Size : 55,8 Mb
Release : 2022-01-04
Category : Science
ISBN : 9783030831905

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Statistics for Chemical and Process Engineers by Yuri A.W. Shardt Pdf

A coherent, concise, and comprehensive course in the statistics needed for a modern career in chemical engineering covers all of the concepts required for the American Fundamentals of Engineering Examination. Statistics for Chemical and Process Engineers (second edition) shows the reader how to develop and test models, design experiments and analyze data in ways easily applicable through readily available software tools like MS Excel® and MATLAB® and is updated for the most recent versions of both. Generalized methods that can be applied irrespective of the tool at hand are a key feature of the text, and it now contains an introduction to the use of state-space methods. The reader is given a detailed framework for statistical procedures covering: data visualization; probability; linear and nonlinear regression; experimental design (including factorial and fractional factorial designs); and dynamic process identification. Main concepts are illustrated with chemical- and process-engineering-relevant examples that can also serve as the bases for checking any subsequent real implementations. Questions are provided (with solutions available for instructors) to confirm the correct use of numerical techniques, and templates for use in MS Excel and MATLAB are also available for download. With its integrative approach to system identification, regression, and statistical theory, this book provides an excellent means of revision and self-study for chemical and process engineers working in experimental analysis and design in petrochemicals, ceramics, oil and gas, automotive and similar industries, and invaluable instruction to advanced undergraduate and graduate students looking to begin a career in the process industries.

Author : Guy B. Marin,Gregory S. Yablonsky,Denis Constales
Publisher : John Wiley & Sons
Page : 462 pages
File Size : 51,5 Mb
Release : 2019-04-29
Category : Science
ISBN : 9783527342952

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Kinetics of Chemical Reactions by Guy B. Marin,Gregory S. Yablonsky,Denis Constales Pdf

This second, extended and updated edition presents the current state of kinetics of chemical reactions, combining basic knowledge with results recently obtained at the frontier of science. Special attention is paid to the problem of the chemical reaction complexity with theoretical and methodological concepts illustrated throughout by numerous examples taken from heterogeneous catalysis combustion and enzyme processes. Of great interest to graduate students in both chemistry and chemical engineering.

Author : Valeriy I. Bykov,Svetlana B. Tsybenova,Gregory Yablonsky
Publisher : Walter de Gruyter GmbH & Co KG
Page : 374 pages
File Size : 51,5 Mb
Release : 2018-01-22
Category : Science
ISBN : 9783110464948

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Chemical Complexity via Simple Models by Valeriy I. Bykov,Svetlana B. Tsybenova,Gregory Yablonsky Pdf

This book is focused on mathematical modelling of chemical kinetics. The authors present the classification of basic models of chemical kinetics, thermokinetics and macrokinetics, as well as their application for the most important chemical transformations, such as combustion and catalysis. Readers will find a detailed description and analysis of different mathematical instruments which can be applied for simulation of reaction dynamics.

Author : Ian T. Cameron,Katalin Hangos
Publisher : Elsevier
Page : 561 pages
File Size : 44,6 Mb
Release : 2001-05-23
Category : Technology & Engineering
ISBN : 9780080514925

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Process Modelling and Model Analysis by Ian T. Cameron,Katalin Hangos Pdf

Process Modelling and Model Analysis describes the use of models in process engineering. Process engineering is all about manufacturing--of just about anything! To manage processing and manufacturing systematically, the engineer has to bring together many different techniques and analyses of the interaction between various aspects of the process. For example, process engineers would apply models to perform feasibility analyses of novel process designs, assess environmental impact, and detect potential hazards or accidents. To manage complex systems and enable process design, the behavior of systems is reduced to simple mathematical forms. This book provides a systematic approach to the mathematical development of process models and explains how to analyze those models. Additionally, there is a comprehensive bibliography for further reading, a question and answer section, and an accompanying Web site developed by the authors with additional data and exercises. Introduces a structured modeling methodology emphasizing the importance of the modeling goal and including key steps such as model verification, calibration, and validation Focuses on novel and advanced modeling techniques such as discrete, hybrid, hierarchical, and empirical modeling Illustrates the notions, tools, and techniques of process modeling with examples and advances applications

Author : Fouzi Harrou,Ying Sun,Amanda S. Hering,Muddu Madakyaru,abdelkader Dairi
Publisher : Elsevier
Page : 330 pages
File Size : 41,6 Mb
Release : 2020-07-03
Category : Technology & Engineering
ISBN : 9780128193662

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Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches by Fouzi Harrou,Ying Sun,Amanda S. Hering,Muddu Madakyaru,abdelkader Dairi Pdf

Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. Uses a data-driven based approach to fault detection and attribution Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods Includes case studies and comparison of different methods

Author : S. Macchietto
Publisher : Elsevier
Page : 267 pages
File Size : 41,7 Mb
Release : 2003-08-04
Category : Technology & Engineering
ISBN : 9780080530574

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Dynamic Model Development: Methods, Theory and Applications by S. Macchietto Pdf

Detailed mathematical models are increasingly being used by companies to gain competitive advantage through such applications as model-based process design, control and optimization. Thus, building various types of high quality models for processing systems has become a key activity in Process Engineering. This activity involves the use of several methods and techniques including model solution techniques, nonlinear systems identification, model verification and validation, and optimal design of experiments just to name a few. In turn, several issues and open-ended problems arise within these methods, including, for instance, use of higher-order information in establishing parameter estimates, establishing metrics for model credibility, and extending experiment design to the dynamic situation. The material covered in this book is aimed at allowing easier development and full use of detailed and high fidelity models. Potential applications of these techniques in all engineering disciplines are abundant, including applications in chemical kinetics and reaction mechanism elucidation, polymer reaction engineering, and physical properties estimation. On the academic side, the book will serve to generate research ideas. Contains wide coverage of statistical methods applied to process modelling Serves as a recent compilation of dynamic model building tools Presents several examples of applying advanced statistical and modelling methods to real process systems problems

Author : Guy B. Marin
Publisher : Elsevier
Page : 322 pages
File Size : 53,6 Mb
Release : 2005-10-24
Category : Technology & Engineering
ISBN : 0080454364

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Advances in Chemical Engineering by Guy B. Marin Pdf

The theme of the present volume "Multiscale Analysis" has been introduced about a decade ago and is now reaching a stage where a first balance can be made and further research directions should be decided. Contributions have been carefully selected to ensure the reader will not be confronted with quantum mechanics at one side of the spectrum nor with chemical plants or even the environment on the other side. Maintaining a strong connection with reality i.e. experimental data was another selection criterion. Experimental validation remains the corner stone of any theoretical development and very powerful experimentel techniques are emerging. Areas covered include discussing in depth an important example of experimental techniques. Coming from the medical world, Magnetic Resonance techniques can now provide even quantitative answers to problems our community is faced with. The modeling issue is discussed further. Finally, the limitations of the classic reactor engineering models are outlined. * Original reviews * Leading chemical engineers as authors * Update on biomaterials use * Novel subject on use of biomaterials in drug delivery and gene therapy * Mathematical modeling

Author : Kohei Arai,Supriya Kapoor,Rahul Bhatia
Publisher : Springer
Page : 1426 pages
File Size : 48,5 Mb
Release : 2018-11-08
Category : Technology & Engineering
ISBN : 9783030010546

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Intelligent Systems and Applications by Kohei Arai,Supriya Kapoor,Rahul Bhatia Pdf

Gathering the Proceedings of the 2018 Intelligent Systems Conference (IntelliSys 2018), this book offers a remarkable collection of chapters covering a wide range of topics in intelligent systems and computing, and their real-world applications. The Conference attracted a total of 568 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer review process, after which 194 (including 13 poster papers) were selected to be included in these proceedings. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have made it possible to tackle many problems more effectively. This branching out of computational intelligence in several directions, and the use of intelligent systems in everyday applications, have created the need for such an international conference, which serves as a venue for reporting on cutting-edge innovations and developments. This book collects both theory and application-based chapters on all aspects of artificial intelligence, from classical to intelligent scope. Readers are sure to find the book both interesting and valuable, as it presents state-of-the-art intelligent methods and techniques for solving real-world problems, along with a vision of future research directions.

Author : Yuri A.W. Shardt
Publisher : Springer
Page : 414 pages
File Size : 43,8 Mb
Release : 2015-10-16
Category : Science
ISBN : 9783319215099

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Statistics for Chemical and Process Engineers by Yuri A.W. Shardt Pdf

A coherent, concise and comprehensive course in the statistics needed for a modern career in chemical engineering; covers all of the concepts required for the American Fundamentals of Engineering examination. This book shows the reader how to develop and test models, design experiments and analyse data in ways easily applicable through readily available software tools like MS Excel® and MATLAB®. Generalized methods that can be applied irrespective of the tool at hand are a key feature of the text. The reader is given a detailed framework for statistical procedures covering: · data visualization; · probability; · linear and nonlinear regression; · experimental design (including factorial and fractional factorial designs); and · dynamic process identification. Main concepts are illustrated with chemical- and process-engineering-relevant examples that can also serve as the bases for checking any subsequent real implementations. Questions are provided (with solutions available for instructors) to confirm the correct use of numerical techniques, and templates for use in MS Excel and MATLAB can also be downloaded from extras.springer.com. With its integrative approach to system identification, regression and statistical theory, Statistics for Chemical and Process Engineers provides an excellent means of revision and self-study for chemical and process engineers working in experimental analysis and design in petrochemicals, ceramics, oil and gas, automotive and similar industries and invaluable instruction to advanced undergraduate and graduate students looking to begin a career in the process industries.