Название: Introduction to Software for Chemical Engineers, 3rd EditionАвтор: Mariano Martín Martín
Издательство: CRC Press
Год: 2025
Страниц: 888
Язык: английский
Формат: pdf (true)
Размер: 39.8 MB
The field of chemical engineering and its link to computer science is in constant evolution, and engineers have an ever-growing variety of tools at their disposal to tackle everyday problems. Introduction to Software for Chemical Engineers, Third Edition provides a quick guide to the use of various computer packages for chemical engineering applications. It covers a range of software applications, including Excel and general mathematical packages such as MATLAB, MathCAD, R, and Python. Coverage also extends to process simulators such as CHEMCAD, HYSYS, and Aspen; equation-based modeling languages such as gPROMS; optimization software such as GAMS, AIMS, and Julia; and specialized software like CFD or DEM codes. The different packages are introduced and applied to solve typical problems in fluid mechanics, heat and mass transfer, mass and energy balances, unit operations, reactor engineering, and process and equipment design and control.
This new edition is updated throughout to reflect software updates and new packages. It emphasizes the addition of SimaPro due to the importance of life cycle assessment, as well as general statistics software, SPSS, and Minitab that readers can use to analyze lab data. The book also includes new chapters on flowsheeting drawing, process control, and LOOP Pro, as well as updates to include Pyomo as an optimization platform, reflecting current trends. The text offers a global idea of the capabilities of the software used in the chemical engineering field and provides examples for solving real-world problems.
Microsoft Excel forms part of the package Microsoft Office. It is a spreadsheet application that features calculation; graphing tools; tables; and a macro programming language, Visual Basic. The main advantage of Excel is that it has spread and is widely used in industry and academia, which makes it a perfect tool or interface not only to perform calculations but also to connect different software so that the end user can interact with Excel, and behind the scenes other software such as CHEMCAD, MATLAB, Mathcad, or GAMS is running and reporting the results back to Excel. Therefore, we consider that this book should start by presenting the main features of this software and its application to chemical engineering.
Excel has the built-in capability to generate customized functions using Visual Basic for Applications (VBA). This is a powerful tool that can save time without requiring the used to become an expert on programming, as it opens the possibilities to run loops and conditionals in the background. This capability also allows the user to build relatively large equations that are used in several areas of the worksheet (e.g. polynomials for the estimation of specific heat of components) and that allows the user to read calculations easily when looking at formulas in the cells.
Python is an open-source programming language created by Guido van Rossum in 1991. Like MATLAB, it is an interpreted high-level language, which enhances the readability of the code. This allows the user to create programs in an easier way and produce shorter codes than other programming languages. Python has a large user community that provides support and creates packages, libraries and modules that extend the capabilities and applications of Python to areas such as scientific and engineering simulations, machine learning, computational chemistry, data visualization and its implementation in embedded systems, among others. It is available for the major operating systems, including Linux-based OS and Windows and Mac OS.
R is free, multiplatform, open source software for statistical analysis, programming, data mining and graphics, created by Robert Gentleman and Ross Ihaka in 1993. R has grown in popularity in the past decade becoming one of the most widely used statistical packages, ranked the sixth most popular of all data science languages by the IEEE in 2017. R is in continuous development, coordinated by the R Core Team Development (R Project), and enjoys a large, active community of users, which provides invaluable support. This is particularly important for neophytes, as it enables them to quickly pick up the programming language, but it is also useful for expert users should they need advice on a specific problem. The Comprehensive R Archive Network (CRAN) makes available a wide range of packages that provide R with extensive capabilities for computation, statistical analysis, data visualization and cloud deployment.
Julia is an open-source programming language that uses just-in-time (JIT) compilation. This means that it compiles code at run time rather than before the code is executed. Julia is a high-level language but can achieve run times similar to native C code for many problems. In addition, Julia provides a package manager for adding, updating, and loading packages, and the packages used in the following scripts can be added directly by the user without requiring any building or installation outside of Julia’s package manager.
Written by leading experts, this handbook is a must-have reference for chemical engineers looking to grow in their careers through the use of new and improving computer software. Its user-friendly approach to simulation and optimization, as well as its example-based presentation of the software, makes it a perfect teaching tool for both undergraduate- and graduate-level readers.
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