You find here a series of free software tools developed in our group, which can be used for teaching and research activities.

The software is provided "as is" without warranty of any kind.


A MATLAB class for the convenient definition and use of probability distributions. It allows defining the joint distribution through the marginal distributions and correlation coefficients. The Nataf transformation (Gaussian copula) is then used to construct the joint distribution. 

The distributions can be defined through their parameters, through their moments or through data fitting.

Bayesian network discretization of reliability problems

A MATLAB based software prototype performing efficient static discretization for structural reliability problems, such that they can be updated in a discrete Bayesian network framework.

Subset Simulation

A MATLAB software tool for reliability assessment with Subset Simulation that includes an implementation of the adaptive Conditional Sampling approach for MCMC sampling conditional on intermediate failure events.

Bayesian Inference Tools

A set of tools for sampling-based Bayesian inference.


Fesslix is an application to perform stochastic analysis (e.g. reliability analysis and Bayesian updating). The source code is written in C++ and is available free of charge. Fesslix comes with a powerful and flexible input language that allows coupling of almost any model (external application) to Fesslix.

Risk Analysis Tool (RAT)

“RAT” is an Excel based tool for scenario-based risk assessment and for Cost Benefit Analysis (CBA) of alternative risk mitigation strategies. It consists of three modules: (1) Risk estimation, (2) Cost estimation and (3) Evaluation of strategies using CBA. It is applicable for problems related to natural hazards such as floods as well as other types of hazards for which the risk is assessed through scenarios representing varying magnitudes of the hazard. Results are presented in tables and figures that can directly be used in reports and presentations. A comprehensive documentation of the methodology utilised in RAT and illustrative examples are also provided.