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Screening wave conditions for the occurrence of green water events on sailing ships

机译:帆船上绿水事件发生的筛选波条件

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摘要

Design loads for extreme wave events on ships, such as slamming and green water, are hard to define. These events depend on details in the incoming waves, ship motions and structure layout, which requires high-fidelity tools such as CFD or experiments to obtain the correct loads. These tools (presently) do not have the capability to fully resolve the long-term statistics of rare events in all metocean conditions over the ship's lifetime. The idea of 'screening' is to use lower-fidelity numerical methods to identify the occurrence of extreme load events based on an indicator. A good indicator has a strong correlation to the design load, but is easier to calculate. A high-fidelity tool can then be used to find the loads in these events. The low-fidelity statistics and the high-fidelity loads can be combined to define a design load and its probability. The present study compares different numerical screening indicators for green water loads on a containership against experiments. The quality of the identification of the critical events and the required computational time served as comparison metrics. This showed that screening both with potential flow tools and with coarse mesh CFD tools is feasible, provided the indicator, grid, time step and wave input settings are well chosen. The results from coarse mesh CFD are slightly better than from potential flow, but the computational costs are much higher. The results also show that the peaks and steepness of the relative wave elevation around the bow are suitable green water load indicators, as well as the undisturbed wave crests at the bow. Fine mesh CFD calculations were done for the identified events based on an example indicator, which resulted in a green water load distribution very close to that of the experiments. This study shows that screening could potentially reduce the required high-fidelity modelling time with up to similar to 90% compared to common practice.
机译:在船上的极端波浪事件的设计负荷,例如砰的绿水,很难定义。这些事件依赖于进入波浪,船舶运动和结构布局中的细节,这需要高保真工具,例如CFD或实验以获得正确的负载。这些工具(目前)没有能力完全解决船舶一生中所有地区条件中罕见事件的长期统计数据。 “筛选”的想法是使用低保真数值方法,以基于指示符识别极端负载事件的发生。一个良好的指示器与设计负荷有很强的相关性,但更容易计算。然后可以使用高保真工具来找到这些事件中的负载。可以组合低保真统计和高保真载荷以定义设计负载及其概率。本研究比较了对实验集容器的不同数值筛选指标。识别关键事件的质量和所需的计算时间用作比较度量。这表明,屏蔽具有潜在的流动工具和具有粗网状CFD工具是可行的,提供了很好地选择指示灯,电网,时间步骤和波输入设置。来自粗网格CFD的结果略高于潜在流量,但计算成本要高得多。结果还表明,船头周围相对波升高的峰值和陡度是合适的绿色水负荷指示器,以及弓的未受干扰的波峰。基于示例指示器对所识别的事件进行细网CFD计算,这导致绿色水负荷分布非常接近实验。本研究表明,与常规实践相比,筛选可能会降低高达90%的所需高保真建模时间。

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