一个新的统一形式的壁面律公式及其在壁面模化大涡模拟中的应用

本研究中,我们提出了一个新的统一形式的壁面律公式(称为LOG-EXP公式),用于预测壁面附近不同区域的平均速度剖面。在推导LOG-EXP公式时,我们通过引入修正项来模化混合长度涡粘模型与近壁雷诺应力之间的差异。文中使用不同雷诺数的槽道湍流直接数值模拟数据、平板上边界层流动以及圆管流动的实验数据对公式进行了验证。此外,我们基于LOG-EXP公式训练了一个能够显式计算壁面切应力的神经网络壁模型。然后,我们将其成功地应用在壁模型大涡模拟中,并使用三个不同雷诺数的槽道湍流进行测试。对于文中考虑的所有算例中,LOG-EXP公式的整体性能表现良好。在细化网格时,雷诺应力的计算没有得到显著的改善。这是因为影响壁面模化大涡模拟的因素有很多,例如,所采用的网格和亚格子模型等等。未来需要进一步的工作来量化这些因素的影响并改进壁面模化大涡模拟在较精细网格上的预测

Multiscale analysis of a very long wind turbine wake in an atmospheric boundary layer

In this paper, we investigate the dynamics of a wind turbine wake for three different ground surface roughness lengths, i.e., k(0) = 0.001, 0.01, 0.1 m. The computational domain is very long [until 215D (D is the rotor diameter) wind turbine downwind], with the attempt to include the entire recovery process of a wind turbine wake. The streamwise variations of velocity deficit and turbulence intensity are analyzed. The focus of this paper is how flow structures of different scales vary as they pass through a wind turbine and travel to further downwind locations. Three different trends depending on scales are observed: (1) energy is added to motions of small scales (<1D) immediately in wind turbine's downwind, (2) energy for motions of scales in the range of 1D to 3.2D is first extracted by the wind turbine and then increased by the wake to a level higher than the inflow, and (3) energy for motions of scales greater than 3.4D is first extracted by the wind turbine, and then monotonically increase to the inflow level without a maximum. Finally, the energy density in scale space and its evolution in the streamwise direction are examined, showing the range of scales affected by a wind turbine and its wake

1.3μm InGaAsP—InP双异质结边发光管

本文报道一种短条结构的高速大功率1.3μmInGaAsP—InP双异质结边发光管。在100mA的驱动电流下,耦合进入芯径50μm,数值孔径0.2的梯度折射率光纤的光功率大于60μW,上升时间、下降时间均约2ns,光谱半宽600～800A

2005～2014年CERN野外台站气象观测场土壤含水量数据集

土壤水分是影响陆地–大气边界层能量和物质传输的重要因子。土壤水分含量是中国生态系统研究网络(CERN)陆地生态系统水环境长期定位观测的重要指标。截至2014年,CERN全国范围内包括农田、森林、草地、荒漠与湿地等生态类型的34个陆地生态系统台站,依据陆地水环境观测规范、质量保证与质量控制规范,设立观测样地,并开展土壤含水量的长期定位观测与数据汇交及质控工作。CERN水分分中心选取了这34个台站2005～2014年气象观测场的土壤含水量长期监测数据,通过进一步统一规范数据格式,形成了全国范围内较长时间序列的公开共享数据集,为土壤含水量时空动态的遥感反演、模型估算验证提供地面实测数据支撑