Implementation of Reliability Methods in a New Developed Open-Source Software Library

Structural reliability methods aim at the computation of failure probabilities of structural systems with methods of statistical analysis due to varied uncertainties occurring during their design, building or even operating conditions. However, in the field of civil engineering, the use of structural reliability methods unfortunately remains limited to specific cases. Most of the software available has still a limited range concerning wide parametric studies for analysis with reliability methods in civil engineering. This paper describes a new open-source software library as an effective tool for reliability analysis in civil engineering. The goal is to facilitate the adoption of reliability methods among engineers in practice as well as to provide an open platform for further scientific collaboration. The new library is being developed as a so-called “R package” in open-source programming software “R”. The package is capable of carrying out systematic parameter studies using different probabilistic reliability methods, as FORM, SORM, Monte Carlo Simulation. Based on this, an overview on the probabilistic reliability methods implemented in the package as well as results of parametric studies is given. The performance of the package will be shown with a parametric study on a practical example. Most important results of the parametric study as well as the correctness of different reliability methods will be described in the paper. By describing probabilistic methods using an example in practice, engineers can get a basic understanding behind the ideas of probability theories. Further work will result in large parameter studies, which will support the development of a new guideline for reliability in civil engineering. This guideline describes techniques of code calibration as well as to determine new partial safety factors (e.g. for non-metallic reinforced concrete, fixing anchors, etc.). Furthermore, advanced reliability methods (e.g. Monte Carlo with Subset Sampling) will be implemented in the new R package.