Design loads for wave impacts -- introducing the Probabilistic Adaptive Screening (PAS) method for predicting extreme non-linear loads on maritime structures

Wave impact loads on a maritime structure can cause casualties, damage, pollution of the sea and operational delays. Their extreme (or design) values should therefore be considered in the design of these structures. However, this is challenging because these events are both rare and complex, requiring high-fidelity computation and long analysis durations to obtain such design loads. Existing extreme value prediction methods are not tailored or validated for wave impacts. We therefore introduce the new Probabilistic Adaptive Screening (PAS) method for predicting extreme non-linear loads on maritime structures. The method introduces a probabilistic approach to multi-fidelity screening, allowing efficient linear potential flow indicators to be used in the low-fidelity stage, even for strongly non-linear load cases. The method is validated against a range of cases, including non-linear waves, ship vertical bending moments, green water impact loads, and slamming loads. It can be concluded that PAS accurately estimates both the short-term distributions and extreme values in these test cases, with most probable maximum (MPM) values within 10% of the available full brute-force Monte-Carlo Simulation (MCS) results. In addition, PAS achieves this performance very efficiently, requiring less than 4% of the high-fidelity simulation time needed for conventional MCS. These results demonstrate that PAS can reliably reproduce the statistics of both weakly and strongly non-linear extreme load problems, while significantly reducing the associated computational cost. The present study validates the statistical PAS framework; further work should focus on validating the full procedure including CFD load simulations, and on validating it for long-term extremes.