Название: Numerical Methods in Chemical Process Engineering Using Python: Tools for Modeling, Simulation, and Optimization
Автор: Hector Jorquera, Claudio A. Gelmi
Издательство: Springer
Год: 2027
Страниц: 270
Язык: английский
Формат: True PDF, True EPUB
Размер: 41.7 MB

This book provides an overview of the most widely used numerical methods in chemical process engineering organized by increasing levels of complexity.

The first part of the text reviews the available numerical methods and shows how they can be implemented with Python libraries built-in functions, providing a perspective that complements the software’s user manual and programming guides. Various techniques and algorithms are presented, highlighting which ones are best suited to each problem. Although “universal” algorithms rarely exist, we discuss the kinds of difficulties that may arise, how to diagnose them, and how to avoid them. Ordinary differential equations are then addressed, covering both initial value and boundary value problems, with an emphasis on their role in describing dynamic behavior and transport phenomena. The section concludes with partial differential equations, which are fundamental for capturing spatial and temporal variations in heat, mass, and momentum transfer.

The second part of the book presents a curated set of solved problems, each supported by Python code and figures. Covering topics such as parameter estimation, confidence intervals, and bioreactor optimization, the problems emphasize both steady-state and dynamic systems. Each example covers the deriving governing equations, related code, and interpreting results, providing a consistent learning path, while additional discussions encourage students to explore related concepts beyond the presented problem.

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