Efficient computation of temporal exceeding probability of ship responses in a random wave field
Xianliang Gong, Katerina Siavelis, Zhou Zhang, Yulin Pan

TL;DR
This paper presents a new computational framework that efficiently estimates the probability over time that ship responses exceed thresholds in random wave fields, especially for rare, extreme events, using Bayesian experimental design.
Contribution
It introduces novel developments to Bayesian experimental design for robustly estimating temporal exceeding probabilities, extending previous work on extreme response statistics.
Findings
Framework accurately predicts exceedance probabilities.
Results are consistent regardless of wave group definitions.
Couples with CFD models for realistic ship response analysis.
Abstract
In this work, we develop a computational framework to efficiently quantify the temporal exceeding probability of ship responses in a random wave field, i.e., the fraction of time that ship responses exceed a given threshold. In particular, we consider large thresholds so that the response exceedance needs to be treated as rare events. Our computational framework builds on the parameterization of wave field into wave groups and efficient sampling in the group parameter space through Bayesian experimental design (BED). Previous works following this framework exclusively studied extreme statistics of group-maximum response, i.e., the maximum response within a wave group, which is however not straightforward to interpret in practice (e.g., its value depends on the subjective definition of the wave group). In order to adapt the framework to the more robust measure by the temporal exceeding…
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Taxonomy
TopicsShip Hydrodynamics and Maneuverability · Structural Integrity and Reliability Analysis · Probabilistic and Robust Engineering Design
