论文标题
通过多指数随机搭配和径向基函数替代船舶阻力的不确定性定量：比较
Uncertainty Quantification of Ship Resistance via Multi-Index Stochastic Collocation and Radial Basis Function Surrogates: A Comparison
论文作者
论文摘要
本文介绍了复杂工业问题的正向不确定性定量（UQ）的两种方法。具体而言，评估了多指数随机配置（MISC）和自适应多余性随机径向基础功能（SRBF）替代物的替代物的替代物的替代品的UQ，滚动/滚动乘客渡轮在平静的水中前进并遵守两种操作不确定性，即船上的速度和速度。提出和讨论（模型尺度）电阻的期望值，标准偏差和概率密度函数的估计；所需的仿真是由内部不稳定的多网格雷诺平均Navier-Stokes（RANS）求解器$χ$ NAVIS获得的。 MISC和SRBF用作多忠诚度水平的评估对兰斯求解器本质上使用的不同网格水平的评估用于多机芯加速度；此处使用了四个网格水平，作为最初最好的网格的各向同性块。结果表明，只有有限的数据集可用时，可能会首选杂项。对于较大的数据集，MISC和SRBF代表了一个有效的选项，由于其稳健性对噪声，因此对SRBF略有偏爱。
This paper presents a comparison of two methods for the forward uncertainty quantification (UQ) of complex industrial problems. Specifically, the performance of Multi-Index Stochastic Collocation (MISC) and adaptive multi-fidelity Stochastic Radial Basis Functions (SRBF) surrogates is assessed for the UQ of a roll-on/roll-off passengers ferry advancing in calm water and subject to two operational uncertainties, namely the ship speed and draught. The estimation of expected value, standard deviation, and probability density function of the (model-scale) resistance is presented and discussed; the required simulations are obtained by the in-house unsteady multi-grid Reynolds Averaged Navier-Stokes (RANS) solver $χ$navis. Both MISC and SRBF use as multi-fidelity levels the evaluations on the different grid levels intrinsically employed by the RANS solver for multi-grid acceleration; four grid levels are used here, obtained as isotropic coarsening of the initial finest mesh. The results suggest that MISC could be preferred when only limited data sets are available. For larger data sets both MISC and SRBF represent a valid option, with a slight preference for SRBF, due to its robustness to noise.
