Improvements in the IS method for climate change ‐ focused reliability assessment of steel portal frames

Abstract Assessing the adequacy of the reliability formulation of structural Eurocodes for the design of structural systems requires a good understanding of their failure zone to verify not only the reliability level, but also the impact that the different random variables have on it. Bearing in mind the nature of structural system behaviour, simulation techniques are the most adequate for this task. Alongside the basic method, the crude Monte Carlo (CMC), there are several variance reduction techniques that enable reduction of the sample size of CMC. Sample size reduction is crucial for structural systems, due to the computational requirements of their input‐output (I/O) models and their probability of failure regularly being a small value. Another very important aspect in reliability assessment is the description of the basic random variables. While several random variables are well‐established, others, like for example the atmospheric loads, are expected to change over time as a consequence of external factors. In the framework of structural steel frames, this paper examines the application of black box optimization results for the exploration of the failure zone and incorporation of these results in the reliability assessment with Importance Sampling (IS), with the goal of significantly reducing the sample size. Additionally, the paper proposes a method for re‐evaluation of wind loading, which has been proven [1] as a relevant time‐dependent random variable affecting the safety of steel portal frames.