Numerical Methods in Chemical Engineering

About this course

Numerical Methods in Chemical Engineering covers a range of conventional numerical methods that are common in chemical engineering calculations. The course is designed for BSc. students. In each lecture, the solution procedure and the algorithm for implementing this procedure into a source code are explained in details. Matlab and Python are selected as the programming platforms. Students have access to source codes (Matlab and Python) of the most of the covered methods. In each semester, some programming projects are designed to enforce students to enhance their programming skills and learn how to convert a problem into a numerical code.

The topics that are covered are:

  • Errors in computer calculations and numerical methods;
  • Solution to non-linear equations: re-visit of EOS and calculation of thermodynamic properties;
  • Solution to a system of linear equation;
  • Numerical differentiation and integration: problems related to experimental data, heat transfer and reactor calculations;
  • Curve fitting: finding correlations and reaction kinetics from experimental data;
  • Ordinary differential equations (IVPs): reactor and heat transfer dynamics;
  • Ordinary differential equations (BVPs): solution to heat and mass transfer equations;
  • Partial differential equations (PDEs): solution to steady-state and unsteady-state heat and mass transfer problems;

Course lectures

Course lectures are distributed among students in PDF format through lms (learning management system). For now, they are not shared here. 


Source codes of all the numerical methods and other extra codes are listed here. You have access to all these source codes on the GitHub repository.

Matlab Codes
Python codes