Computational and Statistical Methods for Chemical Engineering

The book Computational and Statistical Methods for Chemical Engineering combines mathematical modeling and exploratory chemometrics to provide a comprehensive account of computational and statistical methods for chemical engineering. It is suitable for undergraduate students and covers calculus, linear algebra, probability, computational methods, statistical models, and designed experiments.

Format: Hardback
Length: 26 pages
Publication date: 19 December 2022
Publisher: Taylor & Francis Ltd

In recent years, the advent of novel molecular measurement techniques and their widespread accessibility in chemical databases has significantly facilitated the retrieval of associated data by chemical analysts. Prior to the data revolution, most books primarily focused on mathematical modeling of chemical processes or exploratory chemometrics.

Computational and Statistical Methods for Chemical Engineering seeks to bridge these two approaches and offer aspiring chemical engineers a comprehensive and unified account of computational and statistical methods. The book is structured into four parts:

Part I delves into the necessary calculus, linear algebra, and probability background that students may or may not have encountered before. It provides a foundational understanding of the mathematical tools required for subsequent chapters.

Part II offers an overview of standard computational methods and approximation techniques that are valuable for chemical engineering systems. It covers a range of techniques, including numerical integration, differential equations, and optimization algorithms.

Part III explores the most important statistical models, ranging from simple measurement models to linear models, and ultimately to multivariate, non-linear stochiometric models. It emphasizes the application of statistical principles to solve chemical engineering problems.

Part IV emphasizes the significance of designed experiments and robust analyses. It discusses the importance of experimental design, data collection, and statistical inference to make informed decisions based on experimental data.

Each chapter in the book is accompanied by an extensive selection of theoretical and practical exercises. These exercises help students apply the concepts learned in the text and develop their skills in computational and statistical methods.

The book is designed to be compatible with modern computational environments such as R, Python, and MATLAB. It provides detailed instructions and examples that can be executed using these software platforms, making it accessible to a wide range of students and researchers.

Furthermore, the book includes a bonus chapter that provides a simple introduction to R programming. R is a popular programming language used for data analysis and statistical computing, and its inclusion in the book enhances its utility and appeal to chemical engineering students.

Overall, Computational and Statistical Methods for Chemical Engineering is an invaluable resource for undergraduate students in Chemical Engineering who require a semester course in computational and statistical methods. The book's comprehensive coverage, self-contained background chapters, and practical exercises make it an essential tool for anyone interested in advancing their knowledge in this field.

Weight: 716g
Dimension: 162 x 241 x 27 (mm)
ISBN-13: 9781032013244