Nonlinear Fourier Analysis of Free-Surface Buoy Data Using the Software Library FNFT

S. Wahls, M. Brühl, Yang-Ming Fan, Ching-Jer Huang
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Abstract

Nonlinear Fourier Analysis (NFA) is a powerful tool for the analysis of hydrodynamic processes. The unique capabilities of NFA include, but are not limited to, the detection of hidden solitons and the detection of modulation instability, which are essential for the understanding of nonlinear phenomena such as rogue waves. However, even though NFA has been applied to many interesting problems, it remains a non-standard tool. Recently, an open source software library called FNFT has been released to the public. (FNFT is short for “Fast Nonlinear Fourier Transforms”.) The library in particular contains code for the efficient numerical NFA of hydrodynamic processes that are approximately governed by the nonlinear Schroedinger equation with periodic boundary conditions. Waves in deep water are a prime example for such a process. In this paper, we use FNFT to perform an exemplary NFA of typhoon data collected by wave buoys at the coast of Taiwan. Our goals are a) to demonstrate the application of FNFT in a practical scenario, and b) to compare the results of a NFA to an analysis based on the conventional linear Fourier transform. The exposition is deliberately educational, hopefully enabling others to use FNFT for similar analyses of their own data.
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利用FNFT软件库对自由水面浮标数据进行非线性傅立叶分析
非线性傅立叶分析(NFA)是分析水动力过程的有力工具。NFA的独特功能包括,但不限于,检测隐藏孤子和检测调制不稳定性,这对于理解非线性现象(如异常波)至关重要。然而,尽管NFA已经应用于许多有趣的问题,它仍然是一个非标准的工具。最近,一个名为FNFT的开源软件库已经向公众发布。(FNFT是“快速非线性傅立叶变换”的缩写。)该库特别包含了由具有周期边界条件的非线性薛定谔方程近似控制的流体动力过程的有效数值NFA代码。深水中的波浪就是这一过程的典型例子。本文利用FNFT对台湾沿海浮标所收集的台风资料进行典型的NFA分析。我们的目标是a)演示FNFT在实际场景中的应用,b)将NFA的结果与基于传统线性傅里叶变换的分析结果进行比较。本文的阐述具有教育意义,希望其他人能够使用FNFT对他们自己的数据进行类似的分析。
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