科考船上的气流畸变与波浪相互作用:实验与数值比较

Niall O’Sullivan, Sebastian Landwehr, Brian Ward
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引用次数: 12

摘要

reynolds -average Navier-Stokes (RANS)和大涡模拟(LES)是模拟湍流的两种方法。在这里,为了模拟海洋研究船R/V Knorr上的流动畸变,它们进行了比较,这对于校正声波风速计的观测结果很重要。利用OpenFOAM RANS解算器SimpleFOAM和LES解算器PisoFOAM,将计算结果与科考船上各测风站的实验数据进行了比较。LES模拟的平均精度水平为~ 3%的风速偏差,而RANS模拟的平均精度为~ 7%。对风速矢量俯仰和偏航进行了LES分析。主要的强迫被发现是俯仰,这使得风矢量的总体大小增加了7%。研究还发现,风速的节距是造成水平流动扭曲的主要因素,这是由于10-20 ms−1范围内的流动分离造成的。我们还在- 60°到+60°的方向范围内使用LES模拟,增量为10°。数值分析结果表明,由于流动畸变的影响,预测结果与实验结果的平均差值接近6%。我们还探索了两种不同的方法来定义波浪引起的流动畸变校正,当最终加入气流畸变校正时,模型的整体精度提高了3%。
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Air-flow distortion and wave interactions on research vessels: An experimental and numerical comparison

Reynolds-averaged Navier–Stokes (RANS) and large eddy simulation (LES) are two schemes for modeling turbulent flows. Here they are compared for modeling flow distortion over the oceanographic research vessel R/V Knorr, which is important for correcting observations from sonic anemometers. Using the OpenFOAM RANS solver SimpleFOAM and the LES solver PisoFOAM, computations are compared with experimental data taken from various anemometer sites on-board the research vessel. The LES showed mean accuracy levels of ∼3% of the wind speed bias whereas the RANS simulations showed mean accuracies of ∼7%. A LES analysis of the wind speed vector pitch and yaw was also conducted. The dominant forcing was found to be the pitch, which gave a 7% increase to overall magnitude of the wind vector. It was also found that the pitch of the wind speed was the main component responsible for the horizontal flow distortions, found to be due to flow separation in the 10–20  ms1 range. We also use the LES simulations over a range of orientations from 60° to +60°, in increments of 10°. The numerical analysis showed close agreement to experimental measurements with a 6% mean difference prediction due to flow distortion effects. We also explore two different methods to define a wave induced flow distortion correction and when finally added to the air-flow distortion correction, improved the overall accuracy of the models by 3%.

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