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| Author | : Olga Maltseva |
| Publisher | : |
| Total Pages | : 910 |
| Release | : 2018-04 |
| Genre | : |
| ISBN | : 9781788021654 |
| Author | : Denis Constales |
| Publisher | : Elsevier |
| Total Pages | : 416 |
| Release | : 2016-08-23 |
| Genre | : Technology & Engineering |
| ISBN | : 0444594841 |
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 | : Guillermo Fernando Barreto |
| Publisher | : Springer Nature |
| Total Pages | : 151 |
| Release | : |
| Genre | : |
| ISBN | : 3031423755 |
| Author | : Douglas M. Considine |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 3529 |
| Release | : 2013-12-11 |
| Genre | : Technology & Engineering |
| ISBN | : 1475769180 |
Advancements in science and engineering have occurred at a surprisingly rapid pace since the release of the seventh edition of this encyclopedia. Large portions of the reference have required comprehensive rewriting and new illustrations. Scores of new topics have been included to create this thoroughly updated eighth edition. The appearance of this new edition in 1994 marks the continuation of a tradition commenced well over a half-century ago in 1938 Van Nostrand's Scientific Encyclopedia, First Edition, was published and welcomed by educators worldwide at a time when what we know today as modern science was just getting underway. The early encyclopedia was well received by students and educators alike during a critical time span when science became established as a major factor in shaping the progress and economy of individual nations and at the global level. A vital need existed for a permanent science reference that could be updated periodically and made conveniently available to audiences that numbered in the millions. The pioneering VNSE met these criteria and continues today as a reliable technical information source for making private and public decisions that present a backdrop of technical alternatives.
| Author | : Jack Belzer |
| Publisher | : Routledge |
| Total Pages | : 228 |
| Release | : 2018-02-06 |
| Genre | : Computers |
| ISBN | : 1351451693 |
""This comprehensive reference work provides immediate, fingertip access to state-of-the-art technology in nearly 700 self-contained articles written by over 900 international authorities. Each article in the Encyclopedia features current developments and trends in computers, software, vendors, and applications...extensive bibliographies of leading figures in the field, such as Samuel Alexander, John von Neumann, and Norbert Wiener...and in-depth analysis of future directions.
| Author | : Y. A. Liu |
| Publisher | : John Wiley & Sons |
| Total Pages | : 1027 |
| Release | : 2023-07-25 |
| Genre | : Technology & Engineering |
| ISBN | : 3527843825 |
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 | : |
| Publisher | : Elsevier |
| Total Pages | : 5142 |
| Release | : 2019-04-02 |
| Genre | : Science |
| ISBN | : 008101984X |
The third edition of the Encyclopedia of Analytical Science, Ten Volume Set is a definitive collection of articles covering the latest technologies in application areas such as medicine, environmental science, food science and geology. Meticulously organized, clearly written and fully interdisciplinary, the Encyclopedia of Analytical Science, Ten Volume Set provides foundational knowledge across the scope of modern analytical chemistry, linking fundamental topics with the latest methodologies. Articles will cover three broad areas: analytical techniques (e.g., mass spectrometry, liquid chromatography, atomic spectrometry); areas of application (e.g., forensic, environmental and clinical); and analytes (e.g., arsenic, nucleic acids and polycyclic aromatic hydrocarbons), providing a one-stop resource for analytical scientists. Offers readers a one-stop resource with access to information across the entire scope of modern analytical science Presents articles split into three broad areas: analytical techniques, areas of application and and analytes, creating an ideal resource for students, researchers and professionals Provides concise and accessible information that is ideal for non-specialists and readers from undergraduate levels and higher
| Author | : John J. McKetta Jr |
| Publisher | : CRC Press |
| Total Pages | : 520 |
| Release | : 1980-01-01 |
| Genre | : Science |
| ISBN | : 9780824724610 |
"Written by engineers for engineers (with over 150 International Editorial Advisory Board members),this highly lauded resource provides up-to-the-minute information on the chemical processes, methods, practices, products, and standards in the chemical, and related, industries. "
| Author | : Wang, John |
| Publisher | : IGI Global |
| Total Pages | : 3296 |
| Release | : 2023-01-20 |
| Genre | : Computers |
| ISBN | : 1799892212 |
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
| Author | : Christo Boyadjiev |
| Publisher | : Springer |
| Total Pages | : 199 |
| Release | : 2021-12-09 |
| Genre | : Science |
| ISBN | : 9783030876593 |
This book presents a theoretical analysis of the modern methods used for modeling various chemical engineering processes. Currently, the two primary problems in the chemical industry are the optimal design of new devices and the optimal control of active processes. Both of these problems are often solved by developing new methods of modeling. These methods for modeling specific processes may be different, but in all cases, they bring the mathematical description closer to the real processes by using appropriate experimental data. In this book, the authors detail a new approach for the modeling of chemical processes in column apparatuses. Further, they describe the types of neural networks that have been shown to be effective in solving important chemical engineering problems. Readers are also presented with mathematical models of integrated bioethanol supply chains (IBSC) that achieve improved economic and environmental sustainability. The integration of energy and mass processes is one of the most powerful tools for creating sustainable and energy efficient production systems. This book defines the main approaches for the thermal integration of periodic processes, direct and indirect, and the recent integration of small-scale solar thermal dryers with phase change materials as energy accumulators. An exciting overview of new approaches for the modeling of chemical engineering processes, this book serves as a guide for the important innovations being made in theoretical chemical engineering.
