Master’s studies

Syllabus for Modelling and Simulation Methods of Particle Transport

Modellering och simuleringsmetoder för partikeltransport

Syllabus

  • 5 credits
  • Course code: 1FA451
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Physics A1N
  • Grading system: Fail (U), 3, 4, 5.
  • Established: 2011-11-10
  • Established by: The Faculty Board of Science and Technology
  • Revised: 2017-05-04
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: week 30, 2017
  • Entry requirements: 120 credits in mathematics, technology and science. Basic knowledge of ionising radiation corresponding to Modern Physics or Nuclear Physics and Particle Physics.
  • Responsible department: Department of Physics and Astronomy

Learning outcomes

After passing the course the student should be able to

  • model and simulate experimental systems with different tools for particle transport
  • choose the correct tools for a given situation, motivate the choice and identify the pros and cons.
  • evaluate the result from the simulation and describe methods to verify the tool.

Content

The course will treat a number of modelling and simulation methods for ionising and non-ionising radiation Examples of tools that students may use during the course and which are commonly used in, e.g., research, medicine and nuclear technology are:

PENELOPE - Monte Carlo simulation package for photon and electron transport (www.nea.fr)
MNCP - Monte Carlo package for neutron and photon simulation (www.lanl.gov)
SERPENT (montecarlo.vtt.fi/)
GEANT - Simulation package for particle transport trough matter (geant4.cern.ch)
FLUKA - Calculation of particle transport and interactions with matter (www.fluka.org)

Typically, students are introduced to three or four different tools. The course will be taught so that the students can construct solids (geometries) and choose parameters for the simulation and optimization of these. 
Miscellaneous: Variance reduction. Differences between deterministic and Monte Carlo methods. Experimental validation.
 

Instruction

The course consists of a series of lectures where the student is introduced to the different tools, the principles by which they work, their strengths and weaknesses. Introductory lectures to how selected tools work are given. The students work with the tools using tutorials, demos, reading material and guidance.

Assessment

Assignments

Reading list

Applies from: week 30, 2017