Simulation of Turbulent Flow Inside and Above Wind Farms: Model Validation and Layout Effects

A recently-developed large-eddy simulation framework is validated and used to investigate turbulent flow within and above wind farms under neutral conditions. Two different layouts are considered, consisting of thirty wind turbines occupying the same total area and arranged in aligned and staggered configurations, respectively. The subgrid-scale (SGS) turbulent stress is parametrized using a tuning-free Lagrangian scale-dependent dynamic SGS model. The turbine-induced forces are modelled using two types of actuator-disk models: (a) the ‘standard’ actuator-disk model (ADM-NR), which calculates only the thrust force based on one-dimensional momentum theory and distributes it uniformly over the rotor area; and (b) the actuator-disk model with rotation (ADM-R), which uses blade-element momentum theory to calculate the lift and drag forces (that produce both thrust and rotation), and distributes them over the rotor disk based on the local blade and flow characteristics. Validation is performed by comparing simulation results with turbulence measurements collected with hot-wire anemometry inside and above an aligned model wind farm placed in a boundary-layer wind tunnel. In general, the ADM-R model yields improved predictions compared with the ADM-NR in the wakes of all the wind turbines, where including turbine-induced flow rotation and accounting for the non-uniformity of the turbine-induced forces in the ADM-R appear to be important. Another advantage of the ADM-R model is that, unlike the ADM-NR, it does not require a priori specification of the thrust coefficient (which varies within a wind farm). Finally, comparison of simulations of flow through both aligned and staggered wind farms shows important effects of farm layout on the flow structure and wind-turbine performance. For the limited-size wind farms considered in this study, the lateral interaction between cumulated wakes is stronger in the staggered case, which results in a farm wake that is more homogeneous in the spanwise direction, thus resembling more an internal boundary layer. Inside the staggered farm, the relatively longer separation between consecutive downwind turbines allows the wakes to recover more, exposing the turbines to higher local wind speeds (leading to higher turbine efficiency) and lower turbulence intensity levels (leading to lower fatigue loads), compared with the aligned farm. Above the wind farms, the area-averaged velocity profile is found to be logarithmic, with an effective wind-farm aerodynamic roughness that is larger for the staggered case.     

Velocity and Surface Shear Stress Distributions Behind a Rough-to-Smooth Surface Transition: A Simple New Model

A simple new model is proposed to predict the distribution of wind velocity and surface shear stress downwind of a rough-to-smooth surface transition. The wind velocity is estimated as a weighted average between two limiting logarithmic profiles: the first log law, which is recovered above the internal boundary-layer height, corresponds to the upwind velocity profile; the second log law is adjusted to the downwind aerodynamic roughness and local surface shear stress, and it is recovered near the surface, in the equilibrium sublayer. The proposed non-linear form of the weighting factor is equal to ln(z/z ₀₁)/ln(δ _i /z ₀₁), where z, δ _i and z ₀₁ are the elevation of the prediction location, the internal boundary-layer height at that downwind distance, and the upwind surface roughness, respectively. Unlike other simple analytical models, the new model does not rely on the assumption of a constant or linear distribution for the turbulent shear stress within the internal boundary layer. The performance of the new model is tested with wind-tunnel measurements and also with the field data of Bradley. Compared with other existing analytical models, the proposed model shows improved predictions of both surface shear stress and velocity distributions at different positions downwind of the transition.     

瓮安生物群中海绵化石的新证据

近年来笔者依据现存的瓮安生物群中一些海绵及动物胚胎化石标本的研究，对那些可能的球形海绵体及有争议的海绵幼虫标本进行了简略的评述。本文提供的保存完好的具单轴骨针的球形海绵体化石及可能的海绵幼虫标本，对于陡山沱期出现海绵动物的推测提出了新的证据。     

小波神经网络研究进展及展望

关于小波分析与人工神经网络结合的研究,近些年来已成为信号处理学科的热点之一,已有大量的研究成果见诸各种学术刊物和会议论文。小波变换具有良好的时频局部性质,神经网络则具有自学习功能和良好的容错能力,小波神经网络（ＷＮＮ）由于较好地结合了两者的优点而具有强大的优势。作者较系统地综述了小波神经网络的研究进展,讨论了小波神经网络的主要模型和算法,并就其存在的一些问题,应用与发展趋势进行了探讨     

同化海温观测数据研究波浪破碎对海洋上层结构的影响

首先利用考虑波浪破碎效应的Mellor-Yamada 2.5阶湍流闭合方案,探讨了海表温度(SST)对波能因子α和Charnock数β的敏感性问题。然后采用变分数据同化途径,基于Papa海洋天气站(OWS Papa Station)的上层温度观测数据,对该参数化方案中的波能因子α和Charnock数β两个参数进行了最优估计。最优估计的结果表明,当α约为167、β约为4.1×105时,价值函数达到最小值。利用上述参数的最优估计进行海温的数值模拟,可以较好地反映出海表温度的日变化和月变化过程,模拟的上混合层的温度和深度也与观测较为一致。最后利用以上参数的最优估计结果对湍动能方程进行诊断计算,研究了波浪破碎对海洋上层湍能量收支的影响。     

集合滤波和三维变分混合数据同化方法研究

发展了一种新的混合数据同化方法——基于集合滤波和三维变分的混合数据同化方法。该方法将集合调整卡尔曼滤波(ensemble adjustment Kalman filter,EAKF)得到的集合样本扰动通过一个转换矩阵的形式直接作用到背景场上,利用顺序滤波的思想得到分析场的一个扰动;然后在三维变分(three dimensional variational analysis,3D-Var)的框架下与观测数据进行拟合,从而给出分析场的最优估计。文中以Lorenz63模型为例,开展了理想数据同化试验,结果表明,相比于集合调整卡尔曼滤波,这种新的混合同化方法可以给出更好的同化结果。     

GPS观测得到的天津地区的现今变形

1995年为了监测天津市的地面变形，配合地面沉降的精密水准测量，在天津市布设了一个GPS监测网。从1995年开始，每年的10月或11月进行一次精密GPS测量，到2001年已连续观测7年，在重新系统处理这7年资料的基础上，对天津地区的现今变形进行了研究，并与同时进行的精密水准复测的垂直变形结果进行了比较。结果表明，在扣除了天津地区随同欧亚板块在地球表面的整体运动之后。天津地区仍然有以东向运动为主要特征的水平运动，年速率约为8.4mm/a，这与整个华北地区的东向运动一臻。天津地区的垂直变形主要是因抽用地下水，油，气引起的地面沉降。用GPS测得的沉降量与用精密水准得到的结果相当一致，天津地区的垂直变形主要是因抽用地下水，油，气引起的地面沉降，用GPS测得的沉降量与用精密水准得到的结果相当一致，其偏差均方根值为11.6mm/a。据此对天津地区的地面沉降监测问题提出了建议。