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SH2704 Monte Carlo Methods and Simulations in Nuclear Technology 6.0 credits

About course offering

For course offering

Autumn 2024 Start 28 Oct 2024 programme students

Target group


Part of programme

Master's Programme, Energy Innovation, åk 1, NUEY, Conditionally Elective

Master's Programme, Nuclear Energy Engineering, åk 1, Optional


Autumn 2024: P2 (3.0 hp)

Spring 2025: P3 (3.0 hp)


28 Oct 2024
16 Mar 2025

Pace of study


Form of study

Normal Daytime

Language of instruction


Course location


Number of places

Places are not limited

Planned modular schedule


For course offering

Autumn 2024 Start 28 Oct 2024 programme students

Application code



For course offering

Autumn 2024 Start 28 Oct 2024 programme students


Jan Dufek (


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Course coordinator

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Headings with content from the Course syllabus SH2704 (Spring 2022–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Theory of Monte Carlo methods.

General variance reduction techniques.

Pseudo-random and quasi-random sequences.

Monte Carlo simulation of particle transport.

Monte Carlo simulation of nuclear reactors.

Variance reduction techniques in Monte Carlo reactor physics.

Trends in Monte Carlo reactor physics.

Monte Carlo in other fields like nuclear medicine, radiation protection etc.

Intended learning outcomes

The Monte Carlo method is a stochastic way of solving various problems through numerical simulations utilizing sequences of random numbers. The method is commonly used when the solution cannot be derived easily in any other way. In reactor physics, the method is, practically, the only one capable of giving detail insight into neutron transport problems in complex fissile systems. Monte Carlo methods are today very widely used in different fields of physics and engineering ranging from astrophysics to e.g. nuclear medicine, particular in modeling of radiation treatment of cancer.

After completed course, the student should be able to:

  • apply various Monte Carlo techniques, such as the simple sampling, control variates, correlated sampling, stratified sampling and importance sampling, in solving various mathemetical and physical problems.
  • program and choose a generator or pseudo-random and quasi-random sequences.
  • interpret and evaluate the results of statistical nature.
  • master the theory behind the Monte Carlo simulation of neutron transport in fissile systems and non-fissile systems with an extrenal source of neutrons.
  • activiely use Monte Carlo codes established in reactor physics. The student should be able to create a mathemetical model of any fissle system, prepare point-wise nuclear data libraries for specific conditions, choose appropriate values for a number of free parameters that influence the statistical and systematic errors, run the simulation, and derive, interpret and evaluate the results of interest.

Literature and preparations

Specific prerequisites

Familiarity with computer programming.

English B / English 6

Recommended prerequisites

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Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

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


  • INL1 - Home Assignments, 3.0 credits, grading scale: A, B, C, D, E, FX, F
  • LAB1 - Computer Laboratory, 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.

Computer laboratory, 3 cr.

Written home assignments, 3 cr.

Opportunity to complete the requirements via supplementary examination

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Opportunity to raise an approved grade via renewed examination



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.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Engineering Physics

Education cycle

Second cycle

Add-on studies

No information inserted


Jan Dufek (