Computational Methods in Simulation (CMIS)
Practical information  

Study year  2016/2017 
Time 
Block 4 
Programme level  Full Degree Master 
ECTS  7,5 ECTS 
Course responsible  
 

Course content
Computational methods in simulation is an important computer
tool in many disciplines like bioinformatics, eScience, scientific
computing and computational physics, computational chemistry,
computational biology, computer animation and many more. A wide
range of problems can be solved using computational methods like:
biomechanical modeling of humans such as computing the stress
field of bones or computational fluid dynamics solving for motion
of liquids, gasses and thin films. Dealing with motion of atoms and
molecules using molecular dynamics. Computing the dynamic motion of
Robots or mechanical systems and many more.
This course will build up a toolbox of simulation methods which the
student can use when building solutions in his or her future
studies. Therefore this course is an ideal supplement for students
coming from many different fields in science.
The aim of this course is to create an overview of typically used
simulation methods and techniques. The course seek to give insight
into the application of methods and techniques on examples such as
motion of deformable models, fluid flows, heat diffusion etc.
During the course the student will be presented with mathematical
models such as a system of partial differential equations. The
course seek to learn the student the classical approaches to
reformulate and approximate mathematical models in such a way that
they can be used for computations on a computer.
This course teaches the basic theory of simulation methods. The
focus is on deep learning of how the methods covered during the
course works. Both on a theoretical level but also on an
implementation level with focus on computer science and good
programming practice.
There will be weekly programming exercises where students will
implement the algorithms and methods introduced from theory and
apply their own implementations to casestudy problems like
computing the motion of a gas or granular material.
The course will cover topics such as finite difference
approximations (FDM), finite volume method (FVM) and finite element
method (FEM) etc.
Learning outcome
Knowledge
 Computer Simulation
 Theory of discretization methods (FEM, FVM, FDM etc)
Skills
 Apply finite element method (FEM) on a PDE
 Apply finite volume method (FVM) on a PDE
 Apply finite difference method (FDM) on a PDE
Competences
 Apply a discretization method to a given partial differential equation (PD)E to derive a computer simulation model
 Implement a computer simulator using a high level programming language
Recommended prerequisites
It is expected that students know how to install and use Matlab by themselves. It is also expected that students know what matrices and vectors are and that students are able to differentiate vector functions.Theorems like fundamental theorem of calculus, mean value theorem or Taylors theorem will be used during the course. The inquisitive students may find more in depth knowledge from Chapters 2, 3, 5, 6 and 13 of R. A. Adams, Calculus, 3rd ed. Addison Wesley.
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Education
MSc programme in Computer Science
MSc programme in Physics
Studyboard
Study Board of Mathematics and Computer ScienceCourse type
Single subject courses (day)Duration
1 blockSchedulegroup
Teaching and learning methods
Mixture of lectures, study groups and project group work with handins.Capacity
No limitLanguage
EnglishLiterature
See Absalon when the course is set up.
Workload
Category  Hours 
Lectures  21 
Preparation  36 
Exercises  49 
Project work  100 
English  206 
Exam
Type of assessment
Marking scale
7point grading scaleCriteria for exam assessment
In order to achieve the highest grade 12, a student must be able to:
 Describe computational meshes and evaluate their geometric and numerical properties.
 Apply finite difference method (FDM)on a partial differential equation, and account for approximation and numerical errors.
 Account for the main principle in the finite volume method.
 Apply the finite volume method (FVM) on a partial differential equation.
 Derive the Weighted Residual (Galerkin) Method.
 Apply the finite element method (FEM) on a partial differential equation.
Censorship form
No external censorshipReexam
Resubmission of written assignments and a 15 minute oral presentation without preparation. The assignments must be submitted no later than two weeks before the date of the reexam.
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