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Content and learning outcomes
Basic ideas and concepts: algorithm, local linearisation, iteration, extrapolation, discretisation, convergence, stability, condition.
Estimation of reliability: parameter sensitivity, experimental perturbation calculation, precision.
Numerical methods for: linear systems of equations, nonlinear equations and systems of equations, interpolation, model adaptation with the least squares method, optimisation, integrals and differential equations.
Using mathematical software to solve engineering mathematical problems, make numerical experiments and present solutions.
Intended learning outcomes
A general aim with the course is to give the student the understanding that numerical methods and programming techniques are needed to make reliable and efficient simulations of technical and scientific processes based on mathematical models.
For a general formulation of a technical or scientific problem: be able to identify and classify the mathematical subproblems that need to be solved, and reformulate them to be suitable for numerical treatment.
Be able to choose, apply and implement numerical methods to produce a solution to a given problem.
Be able to use concepts in numerical analysis to describe, characterize and analyze numerical methods and estimate the reliability of numerical results.
Be able to clearly present problem statements, solution approaches and results.
Literature and preparations
Active participation in SF1625 Calculus in one variable or SF1673 Analysis in one variable.
Active participation in DD1310 Programming Techniques or DD1312 Programming Techniques and Matlab or DD1316 Programming Techniques and C.
SF1624 Algebra and Geometry, SF1626 Calculus in Several Variable
Announced no later than 4 weeks before the start of the course on the course web page
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
- LABA - Laboratory Work, 1.5 credits, grading scale: P, F
- LABB - Laboratory Work, 1.5 credits, grading scale: P, F
- TEN1 - Exaination, 3.0 credits, grading scale: A, B, C, D, E, FX, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
In this course, the code of honour of the school is applied, see: http://www.sci.kth.se/institutioner/math/avd/na/utbildning/hederskodex-for-studenter-och-larare-vid-kurser-pa-avdelningen-for-numerisk-analys-1.357185
The examiner decides, in consultation with KTHs Coordinator of students with disabilities (Funka), about any customized examination for students with documented, lasting disability.
Opportunity to complete the requirements via supplementary examination
Opportunity to raise an approved grade via renewed examination
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.
Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.Course web SF1546
Main field of study
SF2520 Applied Numerical Methods, SF2521 Numerical Solutions of Differential Equations,
SF2561 The Finite Element Method, SF2568 Parallel Computations for Large- Scale Problems