34628 - Radioprotection (Graduate Course)

Course Unit Page


This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Good health and well-being Industry, innovation and infrastructure

Academic Year 2020/2021

Learning outcomes

The module is devoted to the analysis of the radiation protection issues in various contexts:

- Radiation interaction with matter

- Medical applications

- Environmental issues as the consequence of accidental conditions

Due attention is devoted to the Monte Carlo methods as the reference tools in the simulation of the radiation transport.

Some reference Monte Carlo codes useful for practical applications are analysed and applied.


Course contents

Fundamentals of probability and statistics

Radiation interaction with matter: units and useful parameters

Biological effectiveness

Monte Carlo methods for particle transport simulation:

- Neutrons, photons and charged particles

- Analog Monte Carlo

- Bias and importance

- Convergence issues

Tools for the environmental analysis of radioactive pollutants diffusion: analysis of some reference accidental events (TMI, Chernobyl, Fukushima, Goiania)

Application of reference Monte Carlo codes to the solution of some classical problems in radiotherapy or radiation protections or as a consequence of environmental releases. 

Sessions devoted to increase the programming skills in FORTRAN, C and Python




W. L. Dunn, J. K. Shultis, Exploring Monte Carlo Methods, Elsevier, 2012

M. H. Kalos, P. A. Whitlock, Monte Carlo Methods, 2nd Edition, Wiley, 2008

User's Manuals for codes and nuclear and radiation protection libraries

Teaching methods

  • Direct instruction
  • Experiential Learning through numerical exercises

Assessment methods

Project set up to solve a paradigmatic radiation protection problem with a reference code.

Teaching tools

  • Open source Monte Carlo codes
  • Xsections Libraries
  • Nuclear Data Libraries

Office hours

See the website of Marco Sumini