Modelling and Simulation Methods of Particle Transport

10 credits

Syllabus, Master's level, 1FA351

A revised version of the syllabus is available.
Code
1FA351
Education cycle
Second cycle
Main field(s) of study and in-depth level
Physics A1N
Grading system
Pass with distinction (5), Pass with credit (4), Pass (3), Fail (U)
Finalised by
The Faculty Board of Science and Technology, 12 March 2009
Responsible department
Department of Physics and Astronomy

Entry requirements

120 credits. Basic knowledge of ionising radiation corresponding to Quantum Physics, Nuclear and particle physics, Nuclear Science with modern applications.

Learning outcomes

When the course is completed the student should be able to

  • master the modelling of test setups, experiments and systems
  • have the knowledge to choose for the formulated problem the appropriate parameters and libraries
  • evaluate the result from the simulation and to verify the simulation
  • be prepared to apply the knowledge in research and industrial applications

Content

The course will treat a number of modelling methods for ionising and non-ionising radiation used in nuclear , particle and in space physics but also very useful for calculations in industry. The tools covered are already being used in nuclear and medical industry which will make a student are well prepared for work outside academia. The course will introduce the most common simulation and modelling tools in this field.

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)

GEANT - Simulation package for particle transport trough matter (geant4.cern.ch)

FLUKA - Calculation of particle transport and interactions with matter (www.fluka.org)

The properties of the different packages will be reviewed. Elements contained by the project works are: Analysis and characterisation of problem, planning of modelling project, methods for modelling of complex geometries, selecting simulation parameters and library, optimising the simulation project, verification of the simulation result.

Instruction

Introductory lectures and supervised project work (PBL)

Assessment

Accomplished and passed project work.

No reading list found.

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