Numerical Methods

Course - second cycle - 7.5 credits

Syllabus for students spring 2021, spring 2020

Course Code:
MA623A revision 1.1
Swedish name:
Numeriska metoder
Level of specialisation
Main fields of study:
No main fields
Date of ratification:
16 August 2018
Decision-making body:
Faculty of Technology and Society
Enforcement date:
01 January 2020
Replaces Syllabus ratified:
30 March 2017

Entry requirements

1. Degree of Engineering in Mechanical Engineering or a degree in a related field. All degrees must be equivalent to at least 180 higher education credits.
2. At least 22.5 credits of Mathematics.
3. The equivalent of English B in Swedish secondary school or equivalent
4. Passed courses: MA620A Scientific Programming, 7,5 hp

Specialisation and progression relative to the degree regulations

This course is included in Materials Science: Master Programme (two years).


The course objective is for the student to learn certain fundamental methods for identifying numerical solutions to linear and non-linear equation systems, integrals, optimisation problems, interpolation and to be able to apply these methods to solve simplified problems in materials science.


The course comprises:
• accuracy and convergence for numeric approximation;
• linear and non-linear equation system;
• least square method and data adaptation;
• interpolation;
• optimisation;
• numerical differentiation and integration; and
• Runge-Kutta method for ordinary differential equations.

Learning outcomes

Knowledge and understanding

Once the course is completed, the student shall:
• be able to identify different types of numerical approximations;
• demonstrate the ability to set up correct algorithm for numerical calculation;
• demonstrate the ability to perform stability and convergence analysis for different types of numerical schedules;
• demonstrate the ability to implement numerical algorithms in computer programs such as Matlab; and
• apply these methods to simulate certain problems within materials science.

Skills and abilities

Once the course is completed, the student shall:
• demonstrate the ability to plan the correct setup of formula for numerical calculations; and
• demonstrate the ability to conduct numerical simulations via computer programs.

Judgement and approach

Once the course is completed, the student shall:
• demonstrate the ability to understand strengths and weaknesses of applied methods;
• demonstrate the ability to evaluate whether the obtained calculation results concur with expectations; and
• demonstrate the ability to follow and take part in developments within the area of numerical calculations.

Learning activities

Lectures, exercises and computer laboratory sessions (approximately 40 hours) and independent study (approximately 160 hours).


Requirements for pass (grade A-E): Passed laboratory report (1 credit) and passed written exam (6.5 credits).
The final grade is based on the written exam.

Grading system

Excellent (A), Very Good (B), Good (C), Satisfactory (D), Pass (E) or Fail (U).

Course literature and other teaching materials

Recommended reading:

• Michael Heath (2002). Scientific computing: An introductory survey, 2nd edition. McGraw-Hill

Course evaluation

The University provides students who are taking or have completed a course with the opportunity to share their experiences of and opinions about the course in the form of a course evaluation that is arranged by the University. The University compiles the course evaluations and notifies the results and any decisions regarding actions brought about by the course evaluations. The results shall be kept available for the students. (HF 1:14).

Interim rules

When a course is no longer given, or the contents have been radically changed, the student has the right to re-take the examination, which will be given twice during a one year period, according to the syllabus which was valid at the time of registration.

Other Information

The syllabus is a translation of a Swedish source text.