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Reduced-Hermite bifold-interpolation assisted schemes for the simulation of random wind field

机译:降铁矿双折插补辅助方案用于模拟随机风场

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Interpolation techniques have been recently introduced to enhance the computational efficiency of the classical spectral representation method (SRM) in the simulation of random ergodic fluctuations in turbulence. However, the conventional interpolation assisted scheme (IAS) is not efficient enough to cater for cases with a large number of simulation points, where the computational demand of the Cholesky decomposition makes them less attractive. In this study, reduced-Hermite based bifold-interpolation assisted schemes (BIAS), which incorporate the reduced-Hermite interpolation in a bifold-interpolation scheme, are developed to further enhance the efficiency of SRM. The reduced-Hermite interpolation reduces the number of Cholesky decompositions in BIAS to half of that required by the conventional Hermite interpolation. The adoption of the bifold-interpolation technique fixes the number of Cholesky decompositions, thus eliminating the Cholesky decomposition as a cause for effecting the efficiency of SRM. Specifically, BIAS is further classified as the sequential BIAS (SeBIAS) that uses Hermite or reduced-Hermite interpolation and the synchronous BIAS (SyBIAS) based on a 2D reduced-Hermite interpolation, each highlighted by their respective merits. A parametric analysis is conducted to investigate the computational efficiency and associated modeling error of BIAS, which are also compared to those of conventional IAS and traditional SRM. The findings suggest that reduced-Hermite SyBIAS is the scheme of choice with higher computational efficiency and smaller modeling bias than other cases. In addition, it is a robust method in which the modeling error is not sensitive to the interpolation of the second part of the double-index frequency. The effectiveness of the wind samples generated by the reduced-Hermite SyBIAS is verified via a case study. Moreover, the results are compared to those from the proper orthogonal decomposition (POD) based approach, which proves that the reduced-Hermite SyBIAS offers a faster and more expedient simulation of random wind fields.
机译:最近引入了插值技术,以增强经典频谱表示法(SRM)在湍流中随机遍历波动的模拟中的计算效率。但是,传统的插值辅助方案(IAS)效率不足以应付具有大量仿真点的情况,在这些情况下,Cholesky分解的计算需求使其吸引力降低。在这项研究中,开发了基于减少铁矿的双倍插值辅助方案(BIAS),该方案将减少铁矿的插值合并到了双重插值方案中,以进一步提高SRM的效率。减少的赫尔姆特插值将BIAS中Cholesky分解的次数减少到常规Hermite插值所需的一半。采用双插值技术可固定Cholesky分解的次数,从而消除了Cholesky分解成为影响SRM效率的原因。具体而言,BIAS进一步分类为使用Hermite或减少Hermite插值的顺序BIAS(SeBIAS)和基于2D减少Hermite插值的同步BIAS(SyBIAS),它们各自都有各自的优点。进行了参数分析,以研究BIAS的计算效率和相关的建模误差,并与常规IAS和传统SRM进行了比较。研究结果表明,与其他情况相比,还原赫姆派SyBIAS是具有更高的计算效率和更小的建模偏差的首选方案。另外,这是一种鲁棒的方法,其中建模误差对双索引频率的第二部分的内插不敏感。通过案例研究验证了由还原型埃尔姆特SyBIAS产生的风样品的有效性。此外,将结果与基于适当正交分解(POD)的方法的结果进行了比较,这证明了简化的Hermite SyBIAS提供了更快,更方便的随机风场模拟。

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