Modeling Crossing Random Seas by Fully Non-Linear Numerical Simulations
Wang, Jinghua Ma, Qingwei Yan, Shiqiang Liang, Bingchen
Ma, Qingwei
Yan, Shiqiang
Liang, Bingchen
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Abstract
Bimodal spectrum wave conditions, known as crossing seas, can produce extreme waves which are hostile to humans during oceanic activities. This study reports some new findings of the probability of extreme waves in deep crossing random seas in response to the variation of spectral bandwidth through fully non-linear numerical simulations. Two issues are addressed, namely (i) the impacts of the spectral bandwidth on the changes of extreme wave statistics, i.e., the kurtosis and crest exceedance probability, and (ii) the suitability of theoretical distribution models for accurately describing the wave crest height exceedance probability in crossing seas. The numerical results obtained by simulating a large number of crossing sea conditions on large spatial-temporal scale with a variety of spectral bandwidth indicate that the kurtosis and crest height exceedance probability will be enhanced when the bandwidth of each wave train becomes narrower, suggesting a higher probability of encountering extreme waves in narrowband crossing seas. Meanwhile, a novel empirical formula is suggested to predict the kurtosis in crossing seas provided the bandwidth is known in advance. In addition, the Rayleigh and second-order Tayfun distribution underestimate the crest height exceedance probability, while the third-order Tayfun distribution only yields satisfactory predictions for cases with relatively broader bandwidth regarding the wave conditions considered in this study. For crossing seas with narrower bandwidth, all the theoretical distribution models failed to accurately describe the crest height exceedance probability of extreme waves. © Copyright © 2021 Wang, Ma, Yan and Liang.
Keywords
crossing seas, exceedance probability, extreme waves, fully non-linear potential theory, kurtosis
Source Title
Frontiers in Physics
Publisher
Frontiers Media S.A.
Series/Report No.
Collections
Rights
Attribution 4.0 International
Date
2021-04-28
DOI
10.3389/fphy.2021.593394
Type
Article