Numerical Symbolic And Statistical Computing For Chemical Engineers Using Matlab

Chemical engineering is a field that heavily relies on computational tools for solving complex equations and analyzing data. Matlab, a powerful programming language and software environment, provides chemical engineers with a wide range of capabilities for numerical, symbolic, and statistical computing. In this article, we will explore how Matlab can benefit chemical engineers in their daily tasks and projects.

Numerical Computing

Numerical computing involves solving mathematical problems using numerical methods. Matlab offers a comprehensive set of built-in functions and libraries specifically designed for numerical calculations. For chemical engineers, this means they can solve complex equations, perform simulations, and analyze experimental data with ease.

Matlab's numerical computing capabilities are particularly useful for chemical reaction modeling. Chemical engineers often need to solve systems of nonlinear equations to determine reaction rates, equilibrium concentrations, and optimal operating conditions. With Matlab, they can use advanced numerical methods like Newton-Raphson and Runge-Kutta to find accurate solutions efficiently.

NUMERICAL, SYMBOLIC AND STATISTICAL COMPUTING FOR CHEMICAL ENGINEERS USING MATLAB

by Gerald E Marsh(Kindle Edition)

4.4 out of 5

Language	:	English
File size	:	21544 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	556 pages

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Additionally, Matlab provides tools for optimizing processes. Chemical engineers can define and solve optimization problems to find the optimal operating conditions that maximize yield, minimize costs, or achieve specific performance targets. The built-in optimization toolbox in Matlab offers various algorithms and techniques to tackle these problems.

Symbolic Computing

Symbolic computing involves manipulating mathematical expressions and equations symbolically rather than numerically. This capability is particularly beneficial for chemical engineers who deal with complex formulas and equations in their work.

Matlab's Symbolic Math Toolbox enables chemical engineers to perform symbolic calculations easily. They can create symbolic variables, define symbolic functions, and manipulate symbolic expressions to simplify equations or derive new mathematical formulas. This helps them gain a deeper understanding of the underlying principles and relationships that govern chemical processes.

Symbolic computing is invaluable when it comes to solving differential equations. Chemical engineers often encounter differential equations that describe the behavior of chemical systems over time. Matlab's symbolic toolbox allows them to analytically solve these equations, obtaining closed-form solutions that can provide valuable insights into the system's dynamics.

Statistical Computing

Statistical computing involves analyzing and interpreting data using statistical methods. In chemical engineering, statistical analysis plays a crucial role in experimental design, process optimization, and quality control. Matlab offers a range of powerful statistical tools that enable chemical engineers to make data-driven decisions.

With Matlab, chemical engineers can perform descriptive statistics to explore data distributions, calculate measures of central tendency and dispersion, and identify outliers. They can also conduct hypothesis testing to determine whether observed differences in data are statistically significant.

Furthermore, Matlab's statistical toolbox provides tools for regression analysis, design of experiments, multivariate data analysis, and reliability analysis. These capabilities help chemical engineers analyze experimental data, model relationships between variables, optimize process parameters, and ensure product quality.

, Matlab is a powerful tool for numerical, symbolic, and statistical computing, making it extremely valuable for chemical engineers. Its numerical capabilities enable engineers to solve complex equations, simulate chemical reactions, and optimize processes. The symbolic computing capabilities allow engineers to manipulate equations symbolically, gain a deeper understanding of chemical principles, and solve differential equations. Lastly, Matlab's statistical tools provide chemical engineers with the means to analyze and interpret data, make data-driven decisions, and optimize process parameters.

By leveraging Matlab's capabilities, chemical engineers can enhance their productivity, improve their understanding of chemical processes, and make informed decisions that lead to more efficient and cost-effective operations.

NUMERICAL, SYMBOLIC AND STATISTICAL COMPUTING FOR CHEMICAL ENGINEERS USING MATLAB

by Gerald E Marsh(Kindle Edition)

4.4 out of 5

Language	:	English
File size	:	21544 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	556 pages

FREE

Numerical, analytical and statistical computations are routine affairs for chemical engineers. They usually prefer a single software to solve their computational problems, and at present, MATLAB has emerged as a powerful computational language, which is preferably used for this purpose, due to its built-in functions and toolboxes.

Considering the needs and convenience of the students, the author has made an attempt to write this book, which explains the various concepts of MATLAB in a systematic way and makes its readers proficient in using MATLAB for computing. It mainly focuses on the applications of MATLAB, rather than its use in programming basic numerical algorithms.

Commencing with the to MATLAB, the text covers vector and matrix computations, solution of linear and non-linear equations, differentiation and integration, and solution of ordinary and partial differential equations. Next, analytical computations using the Symbolic Math Toolbox and statistical computations using the Statistics and Machine Learning Toolbox are explained. Finally, the book describes various curve fitting techniques using the Curve Fitting Toolbox. Inclusion of all these advanced-level topics in the book stands it out from the rest.

KEY FEATURES

Numerous worked-out examples to enable the readers understand the steps involved in solving the chemical engineering problems

MATLAB codes to explain the computational techniques

Several snapshots to help the readers understand the step-by-step procedures of using the toolboxes

Chapter-end exercises, including short-answer questions and numerical problems

Appendix comprising the definitions of some important and special matrices

Supplemented with Solutions Manual containing complete detailed solutions to the unsolved analytical problems

Accessibility of selected colour figures (including screenshots and results/outputs of the programs) cited in the text at www.phindia.com/Pallab_Ghosh.