Numerical methods

ChE-312 / 3 credits

Teacher(s): Miskovic Ljubisa, Sivula Kevin

Language: English

Summary

This course introduces students to modern computational and mathematical techniques for solving problems in chemistry and chemical engineering. The use of introduced numerical methods will be demonstrated using the python programming language.

Content

  • Numerical differentiation (Euler forward, backward, Richardson extrapolation, error analysis)
  • Numerical integration (Trapezoid rule, Simpson rule, composite rules, Romberg integration)
  • Methods for solving nonlinear equations (bisection, Regula-Falsi, Newton-Raphson, error analysis)
  • Methods for solving ordinary differential equations (notion of stability of solutions, stiffness, Euler methods, Runge-Kutta methods, Adams-Bashfort-Moulton, adaptive methods)
  • Boundary value problems (finite difference method, FTCS scheme, Crank-Nicolson method, Finite difference methods in 2 and 3 spatial dimensions, Transient Boundary value problems)
  • Basic notions of data analysis/processing

Keywords

Numerical differentiation and integration, nonlinear equations, ordinary differential equations, partial differential equations

Assessment methods

The final grade will be the combination of exercises (30%) and written exams (70%)

Resources

Moodle Link

In the programs

  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Numerical methods
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 1 Hour(s) per week x 14 weeks
  • Type: mandatory
  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Numerical methods
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 1 Hour(s) per week x 14 weeks
  • Type: mandatory
  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Numerical methods
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 1 Hour(s) per week x 14 weeks
  • Type: optional

Reference week

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