Course information

EG2080 Monte Carlo Methods in Engineering 6.0 credits

Monte Carlo-metoder inom ingenjörskonsten

About course

Course information

Course development and history

Administrate

Monte Carlo methods comprises a number of different methods for solving complicated mathematical problems using sample surveys. Applications of Monte Carlo methods can be found in many fields, from opinion polls to simulations of technical systems. The focus of this course is going to be on the latter.

A typical example of a simulation problem considered in this course is a production system, where there is a randomly varying production capacity (for example due to failures in the machinery) and a randomly varying demand. The objective of the simulation is both to study the production costs of the system as well as the ability of the system to deliver goods when they are demanded.

Offering and execution

Course offering missing for current semester as well as for previous and coming semesters

Course information

Content and learning outcomes

Course contents *

Theory and examples are presented during the lectures and are then applied by the students in a number of home assignments, which are to be solved using appropriate software (for example Matlab). The course will include the following topics:

  • general probability theory
  • random variables
  • random number generation
  • simple sampling
  • complementary random numbers
  • dagger sampling
  • control variates
  • correlated sampling
  • stratified sampling
  • importance sampling

Intended learning outcomes *

The students should after the course be able to use given model of a technical system and appropriate software (for example Matlab) to write a program , which in an efficient manner can simulate the system using Monte Carlo methods.

Course Disposition

No information inserted

Literature and preparations

Specific prerequisites *

Courses in mathematics (including probabiliy theory) 30 HEC, courses in programming or numerical methods 15 HEC. English B or equivalent.

Recommended prerequisites

Courses in mathematics (including probabiliy theory) 30 HEC, courses in programming or numerical methods 15 HEC. English B or equivalent.

Equipment

No information inserted

Literature

“Monte Carlo Simulation”, course compendium, Electric Power Systems Lab, KTH.

Examination and completion

Grading scale *

A, B, C, D, E, FX, F

Examination *

  • TEN1 - Examination, 6.0 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.

Other requirements for final grade *

Written exam.

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Mikael Amelin

Further information

Course web

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 EG2080

Offered by

EES/Electric Power Systems

Main field of study *

Electrical Engineering

Education cycle *

Second cycle

Add-on studies

No information inserted

Contact

Mikael Amelin

Ethical approach *

  • 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.