人工智能方法在数值波槽中的波浪标定

C. Gillan, P. Schmitt, C. Finnegan
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引用次数: 0

摘要

目前数值波槽的解析解仅限于简单的测深和三阶精度。此外,储罐通常使用线性传递函数来描述位于储罐内的探头处的制波器强迫振幅与波高之间的关系。本文报道了一个用OpenFOAM软件包实现的数值波槽。该研究的目的是训练神经网络来表示非线性传递函数,将探测器所需的波面高程时间轨迹映射到创建它所需的波源输入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wave calibration in numerical wave tanks using AI methods
Analytical solutions for numerical wavetanks are limited presently to a simple bathymetry and third order accuracy. Furthermore, tanks are generally characterised using linear transfer functions to relate the wavemaker forcing amplitude to wave elevation at a probe located in the wavetank. This paper reports on a numerical wavetank implemented using the OpenFOAM software package. The aim of the research is to train neural networks to represent non-linear transfer functions mapping a desired wave surface-elevation time-trace at a probe to the wavemaker input required to create it.
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