Search Results: advanced-data-analysis-and-modelling-in-chemical-engineering

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

ISBN: 0444594841

Category: Technology & Engineering

Page: 414

View: 9185

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

Chemical Complexity via Simple Models

MODELICS

Author: N.A

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 3110464942

Category: Science

Page: 374

View: 8674

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.

Hydrogeological Conceptual Site Models

Data Analysis and Visualization

Author: Neven Kresic,Alex Mikszewski

Publisher: CRC Press

ISBN: 1439852227

Category: Science

Page: 600

View: 553

A reference for students, researchers, and environmental professionals, Hydrogeological Conceptual Site Models: Data Analysis and Visualization explains how to develop effective conceptual site models, perform advanced spatial data analysis, and generate informative graphics for applications in hydrogeology and groundwater remediation. Written by expert practitioners, this full-color book illustrates how fundamental hydrogeological concepts are translated into quantitative, high-resolution computer visualizations. In addition, the authors discuss topics not typically covered in conventional textbooks, including GIS technology and the relationship between conceptual site models and environmental policy. Advanced Methods for Data Analysis and Visualization Featuring more than 500 color illustrations, this unique and visually powerful book outlines the required elements of a conceptual site model and provides numerous examples of supporting charts, cross-sections, maps, and 3D graphics. The authors describe advanced analytical methods such as geospatial processing, kriging, and groundwater modeling through practical real-life examples. They also present numerous case studies in groundwater supply and remediation to help explain key engineering design concepts. Data-Driven Assessments of Groundwater Management Policy The authors tackle controversial topics, ranging from technical impracticability of groundwater remediation to sustainable management of groundwater resources. They encourage discussion and independent thought about how current environmental policies and practices can evolve to achieve better outcomes at less cost to society. Practical Strategies for Communicating Your Findings to the General Public While the book is technical in nature, equations and advanced theory are kept to a minimum. The text focuses on practical strategies to help you create easy-to-understand data tables, graphs, maps, and illustrations for technical and nontechnical audiences alike. A companion DVD includes animations, reference material, modeling software, and more.

Applied Mathematics And Modeling For Chemical Engineers

Author: Richard G. Rice,Duong D. Do

Publisher: John Wiley & Sons

ISBN: 1118343026

Category: Technology & Engineering

Page: 396

View: 5802

This Second Edition of the go-to reference combines the classical analysis and modern applications of applied mathematics for chemical engineers. The book introduces traditional techniques for solving ordinary differential equations (ODEs), adding new material on approximate solution methods such as perturbation techniques and elementary numerical solutions. It also includes analytical methods to deal with important classes of finite-difference equations. The last half discusses numerical solution techniques and partial differential equations (PDEs). The reader will then be equipped to apply mathematics in the formulation of problems in chemical engineering. Like the first edition, there are many examples provided as homework and worked examples.

Process Modelling and Model Analysis

Author: Ian T. Cameron,Katalin Hangos

Publisher: Elsevier

ISBN: 9780080514925

Category: Technology & Engineering

Page: 543

View: 4278

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

Empirical Modeling and Data Analysis for Engineers and Applied Scientists

Author: Scott Pardo

Publisher: Springer

ISBN: 3319327682

Category: Mathematics

Page: 247

View: 976

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.

Statistics for Chemical and Process Engineers

A Modern Approach

Author: Yuri A.W. Shardt

Publisher: Springer

ISBN: 3319215094

Category: Science

Page: 414

View: 1900

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.

Modeling, Analysis and Optimization of Process and Energy Systems

Author: F. Carl Knopf

Publisher: John Wiley & Sons

ISBN: 1118121147

Category: Technology & Engineering

Page: 400

View: 1737

Energy costs impact the profitability of virtually all industrial processes. Stressing how plants use power, and how that power is actually generated, this book provides a clear and simple way to understand the energy usage in various processes, as well as methods for optimizing these processes using practical hands-on simulations and a unique approach that details solved problems utilizing actual plant data. Invaluable information offers a complete energy-saving approach essential for both the chemical and mechanical engineering curricula, as well as for practicing engineers.

Advanced Excel for Scientific Data Analysis

Author: Robert De Levie

Publisher: Oxford University Press, USA

ISBN: 0195152751

Category: Science

Page: 615

View: 1789

Excel is by far the most widely distributed data analysis software but few users are aware of its full powers. Advanced Excel For Scientific Data Analysis takes off from where most books dealing with scientific applications of Excel end. It focuses on three areas-least squares, Fourier transformation, and digital simulation-and illustrates these with extensive examples, often taken from the literature. It also includes and describes a number of sample macros and functions to facilitate common data analysis tasks. These macros and functions are provided in uncompiled, computer-readable, easily modifiable form; readers can therefore use them as starting points for making their own personalized data analysis tools. Detailed descriptions and sample applications of standard and specialized uses of least squares for fitting data to a variety of functions, including resolving multi-component spectra; standard processes such as calibration curves and extrapolation; custom macros for general "error" propagation, standard deviations of Solver results, weighted or equidistant least squares, Gram-Schmidt orthogonalization, Fourier transformation, convolution and deconvolution, time-frequency analysis, and data mapping. There are also worked examples showing how to use centering, the covariance matrix, imprecision contours, and Wiener filtering and custom functions for bisections, Lagrange interpolation, Euler and Runge-Kutta integration.

Modeling and Analysis of Chemical Engineering Processes

Author: K. Balu,K. Padmanabhan

Publisher: I. K. International Pvt Ltd

ISBN: 8189866311

Category: Chemical processes

Page: 420

View: 7846

The chemical process industry faces serious problems with regard to new materials and efficient methods of production due to increasing costs of energy, stringent environmental regulations and global competition. A clear understanding of the processes is required in order to solve these problems. One way is through crisp modeling method; another is through an optimal operation of the process to improve profitability and efficiency. The book is in two parts. The first part discusses the methods of modeling chemical engineering processes through well known mathematical methods involving numerical calculations. This includes the recent concepts of Fuzzy logic and neural nets. The second part describes the efficient optimization methods, which are available for the effective application in many chemical processes. This involves methods of search for extrema as well as optimization, with and without constraint relations. Most books on nonlinear programming are of theoretical type, and the exact procedures of computation are often obscure. But in this book, a number of problems have been worked out. In addition to this, computer programs are included for almost all the topics. Due to the intricacy of optimization programs, the flow charts and the program in clear BASIC language have been provided so that the reader can understand the mathematical methods. The book will be useful for students and practising engineers in the field of chemical engineering, biotechnology, environmental engineering, and applied mathematics

Advanced Data Analysis in Neuroscience

Integrating Statistical and Computational Models

Author: Daniel Durstewitz

Publisher: Springer

ISBN: 3319599763

Category: Medical

Page: 292

View: 6915

This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanat ory frameworks, but become powerful, quantitative data-analytical tools in themselves that enable researchers to look beyond the data surface and unravel underlying mechanisms. Interactive examples of most methods are provided through a package of MatLab routines, encouraging a playful approach to the subject, and providing readers with a better feel for the practical aspects of the methods covered. "Computational neuroscience is essential for integrating and providing a basis for understanding the myriads of remarkable laboratory data on nervous system functions. Daniel Durstewitz has excellently covered the breadth of computational neuroscience from statistical interpretations of data to biophysically based modeling of the neurobiological sources of those data. His presentation is clear, pedagogically sound, and readily useable by experts and beginners alike. It is a pleasure to recommend this very well crafted discussion to experimental neuroscientists as well as mathematically well versed Physicists. The book acts as a window to the issues, to the questions, and to the tools for finding the answers to interesting inquiries about brains and how they function." Henry D. I. Abarbanel Physics and Scripps Institution of Oceanography, University of California, San Diego “This book delivers a clear and thorough introduction to sophisticated analysis approaches useful in computational neuroscience. The models described and the examples provided will help readers develop critical intuitions into what the methods reveal about data. The overall approach of the book reflects the extensive experience Prof. Durstewitz has developed as a leading practitioner of computational neuroscience. “ Bruno B. Averbeck

Kinetics of Chemical Reactions

Author: Guy Marin,Gregory S. Yablonsky

Publisher: John Wiley & Sons

ISBN: 3527317635

Category: Science

Page: 428

View: 5670

This systematic presentation covers both experimental and theoretical kinetic methods, as well as fundamental and applied. The identification of dominant reaction paths, reaction intermediates and rate-determining steps allows a quantification of the effects of reaction conditions and catalyst properties, providing guidelines for catalyst optimization. In addition, the form in which the equations are presented allows for their straightforward implementation for scale-up and chemical reactor design purposes. Throughout, the methodologies given are illustrated by many examples.

Chemical Reactor Analysis and Design, 3rd Edition

Author: Gilbert F. Froment,Kenneth B. Bischoff,Juray De Wilde

Publisher: Wiley Global Education

ISBN: 1118136535

Category: Technology & Engineering

Page: 900

View: 7288

This is the Third Edition of the standard text on chemical reaction engineering, beginning with basic definitions and fundamental principles and continuing all the way to practical applications, emphasizing real-world aspects of industrial practice. The text includes updated coverage of computer modeling methods and many new worked examples. Most of the examples use real kinetic data from processes of industrial importance.

Sustainability in the Design, Synthesis and Analysis of Chemical Engineering Processes

Author: Gerardo Ruiz Mercado,Heriberto Cabezas

Publisher: Butterworth-Heinemann

ISBN: 0128020644

Category: Technology & Engineering

Page: 426

View: 2391

Sustainability in the Design, Synthesis and Analysis of Chemical Engineering Processes is an edited collection of contributions from leaders in their field. It takes a holistic view of sustainability in chemical and process engineering design, and incorporates economic analysis and human dimensions. Ruiz-Mercado and Cabezas have brought to this book their experience of researching sustainable process design and life cycle sustainability evaluation to assist with development in government, industry and academia. This book takes a practical, step-by-step approach to designing sustainable plants and processes by starting from chemical engineering fundamentals. This method enables readers to achieve new process design approaches with high influence and less complexity. It will also help to incorporate sustainability at the early stages of project life, and build up multiple systems level perspectives. Ruiz-Mercado and Cabezas’ book is the only book on the market that looks at process sustainability from a chemical engineering fundamentals perspective. Improve plants, processes and products with sustainability in mind; from conceptual design to life cycle assessment Avoid retro fitting costs by planning for sustainability concerns at the start of the design process Link sustainability to the chemical engineering fundamentals

Analysis, Synthesis, and Design of Chemical Processes

Author: Richard Turton

Publisher: Prentice Hall

ISBN: 0132618125

Category: Technology & Engineering

Page: 1007

View: 5391

"Process design is the focal point of chemical engineering practice: the creative activity through which engineers continuously improve facility operations to create products that enhance life. Effective chemical engineering design requires students to integrate a broad spectrum of knowledge and intellectual skills, so they can analyze both the big picture and minute details - and know when to focus on each. Through three previous editions, this book has established itself as the leading resource for students seeking to apply what they've learned in real-world, open-ended process problems. The authors help students hone and synthesize their design skills through expert coverage of preliminary equipment sizing, flowsheet optimization, economic evaluation, operation and control, simulation, and other key topics. This new Fourth Edition is extensively updated to reflect new technologies, simulation techniques, and process control strategies, and to include new pedagogical features including concise summaries and end-of-chapter lists of skills and knowledge."--pub. desc.

Process Analysis and Simulation in Chemical Engineering

Author: Iván Darío Gil Chaves,Javier Ricardo Guevara López,José Luis García Zapata,Alexander Leguizamón Robayo,Gerardo Rodríguez Niño

Publisher: Springer

ISBN: 3319148125

Category: Science

Page: 523

View: 4799

This book offers a comprehensive coverage of process simulation and flowsheeting, useful for undergraduate students of Chemical Engineering and Process Engineering as theoretical and practical support in Process Design, Process Simulation, Process Engineering, Plant Design, and Process Control courses. The main concepts related to process simulation and application tools are presented and discussed in the framework of typical problems found in engineering design. The topics presented in the chapters are organized in an inductive way, starting from the more simplistic simulations up to some complex problems.

Towards Advanced Data Analysis by Combining Soft Computing and Statistics

Author: Christian Borgelt,María Ángeles Gil,João M.C. Sousa,Michel Verleysen

Publisher: Springer

ISBN: 3642302785

Category: Computers

Page: 378

View: 1231

Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis. Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty. Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analyzing the possible situations and their (relative) likelihood. It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance. Combining the two fields enhances the robustness and generalizability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively.

Chemical Engineering Design and Analysis

An Introduction

Author: T. Michael Duncan,Jeffrey A. Reimer

Publisher: Cambridge University Press

ISBN: 9780521639569

Category: Technology & Engineering

Page: 380

View: 1235

Students taking their first chemical engineering course plunge into the 'nuts and bolts' of mass and energy balances and often miss the broad view of what chemical engineers do. This 1998 text offers a well-paced introduction to chemical engineering. Students are first introduced to the fundamental steps in design and three methods of analysis: mathematical modeling, graphical methods, and dimensional analysis. The book then describes how to apply engineering skills, such as how to simplify calculations through assumptions and approximations; how to verify calculations, significant figures, spreadsheets, graphing (standard, semi-log and log-log); and how to use data maps. In addition, the book teaches engineering skills through the design and analysis of chemical processes and process units in order to assess product quality, economics, safety, and environmental impact. This text will help undergraduate students in chemical engineering develop engineering skills early in their studies. Lecturer's solution manual available from the publisher on request.

Advances in Data Analysis with Computational Intelligence Methods

Dedicated to Professor Jacek Żurada

Author: Adam E Gawęda,Janusz Kacprzyk,Leszek Rutkowski,Gary G. Yen

Publisher: Springer

ISBN: 3319679465

Category: Computers

Page: 412

View: 3443

This book is a tribute to Professor Jacek Żurada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek Żurada, Full Professor at the Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, J.B. Speed School of Engineering, University of Louisville, Kentucky, USA, as a token of appreciation for his scientific and scholarly achievements, and for his longstanding service to many communities, notably the computational intelligence community, in particular neural networks, machine learning, data analyses and data mining, but also the fuzzy logic and evolutionary computation communities, to name but a few. At the same time, the book recognizes and honors Professor Żurada’s dedication and service to many scientific, scholarly and professional societies, especially the IEEE (Institute of Electrical and Electronics Engineers), the world’s largest professional technical professional organization dedicated to advancing science and technology in a broad spectrum of areas and fields. The volume is divided into five major parts, the first of which addresses theoretic, algorithmic and implementation problems related to the intelligent use of data in the sense of how to derive practically useful information and knowledge from data. In turn, Part 2 is devoted to various aspects of neural networks and connectionist systems. Part 3 deals with essential tools and techniques for intelligent technologies in systems modeling and Part 4 focuses on intelligent technologies in decision-making, optimization and control, while Part 5 explores the applications of intelligent technologies.

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