High-pressure spectroscopic studies of free and self-trapped excitons in alkali halides at low temperatures

Abstract

A brief survey of our studies of free and self-trapped excitons (FE and STE) in alkali halide crystals under hydrostatic pressure up to 12.5 kbar at 4.2–140 K is presented. Main attention is paid to the following effects observed: (1) the strong coupling of three energy levels of FE in CsI revealing itself as an exciton analog of pressure-scanned Fermi resonance; (2) emergence of a new emission band of STE in CsI under pressure; (3) a large pressure shift of the thermal quenching curve for STE emission in NaCl.     

Characterising the near-wake of a cross-flow turbine

The performance and detailed near-wake characteristics of a vertical axis, cross-flow turbine (CFT) of aspect ratio 1 were measured in a large cross-section towing tank. The near-wake at one turbine diameter downstream was examined using acoustic Doppler velocimetry, where essential features regarding momentum, energy, and vorticity are highlighted. Dominant scales and their relative importance were investigated and compared at various locations in the measurement plane. Estimates for the terms in the mean streamwise momentum and mean kinetic energy equation were computed, showing that the unique mean vertical velocity field of this wake, characterised by counter-rotating swirling motion, contributes significantly more to recovery than the turbulent transport. This result sheds light on previous CFT studies showing relatively fast downstream wake recovery compared to axial-flow turbines. Finally, predictions from a Reynolds-averaged Navier–Stokes simulation with the commonly used actuator disk model were compared with the experimental results, evaluating its use as an engineering tool for studying flow in CFT arrays. Unsurprisingly, the model was not able to predict the near-wake structure accurately. This comparison highlights the need for improved parameterised engineering models to accurately predict the near-wake physics of CFTs.     

Simulation of the inherent turbulence and wake interaction inside an infinitely long row of wind turbines

The turbulence in the interior of a wind farm is simulated using large eddy simulation and the actuator line technique implemented in the Navier–Stokes equations. The simulations are carried out for an infinitely long row of turbines simulated by applying cyclic boundary conditions at the inlet and outlet. The simulations investigate the turbulence inherent to the wind turbines as no ambient turbulence or shear is added to this idealised case. The simulated data give insight into the performance of the wind turbines operating in the wake of others as well as details on key turbulent quantities. One of the key features of wakes behind wind turbines is the dynamic wake meandering, which is shown to be related to the wind turbine spacing and the vortex shedding from the turbine as a bluff body. The flow is analysed and reconstructed by applying proper orthogonal decomposition.     

On the scale-to-scale coupling between a full-scale wind turbine and turbulence

The scale-dependent response of an instrumented full-scale wind turbine is studied under neutrally stratified conditions. The analysis is focused on the linkage between the incoming flow, turbine power output and foundation strain. Wind speed, measured from sonic anemometers installed on a meteorological tower, and foundation strain were sampled at 20 Hz, while the turbine power was sampled at 1 Hz. A wavelet framework and structure function are used to obtain cross correlations among flow turbulence, turbine power and strain across scales as well as to quantify intermittent signatures in both flow and turbine quantities. Results indicate that correlation between the streamwise velocity component of the wind flow and turbine power is maximised across all scales larger than the rotor radius for wind measured at the turbine hub height. The characteristic time lag associated with maximum correlation is shown to be consistent with the Taylor’s hypothesis for turbulent scales smaller than the separation between the meteorological tower and the turbine. However, it decreases with increasing scale size and diminishes to zero at scales on the order of the boundary layer thickness. Turbine power and strain fluctuations exhibited practically the same behaviour at scales larger than two rotor diameters. At those scales, the cross correlation between these quantities resulted ～0.99 and remains still over 0.9 at the scale of rotor radius. Below this scale, the correlation decreases logarithmically with scale. The strong linkage between power and strain for all the relevant scales would eventually allow the analysis of dynamic forcing on the foundation based on the power output. Intermittency on the flow is shown to be transferred and amplified by the turbine, leading to highly intermittent power output.     

有限区域风场分解方法及其在台风SAOMEI研究中的应用

介绍了有限区域水平风场分解的调和-余弦计算方法,该方法把函数分成两部分之和.第一部分是Laplace方程在给定边界条件下的解,由于Laplace方程的解是调和函数,这个部分可称为调和部分,又因为其与区域内部值无关,也称外部部分.第二部分是原始函数与调和部分之差,这个函数是齐次边条件下Poisson方程的解,只与区域内部的涡度或散度有关,故称为内部部分,可以展开成双傅氏的余旋函数系列.调和-余弦计算方法的求导都是用谱系数进行,计算精度比常用的差分方法高两阶以上.而且,由于外部部分对应的边界条件物理意义清楚,边界光滑,成功克服了有限区域流函数和速度势迭代求解出现的计算不稳定、原始风场无法还原、边界上的系统缺失等问题,可以准确分解和重建有限区域的风场.利用NCEP/NCAR 1°×1°的实时分析资料和日本气象厅区域谱模式(RSM)20km分辨率的再分析资料,利用调和-余弦算法得到的无辐散风分量和无旋风分量,对2006年的8号超强台风“桑美"(SAOMEI)进行风场结构的比较分析.结果发现,低层无辐散风比原始风场与台风中心的对应关系更好;同时,无旋风分量能更好地显示原始风场上并不明显的低层辐合高层辐散的特征,大尺度无辐散风分量可以更清晰地显示出台风的水汽输送通道.从与台风中心的对应关系看,台风在海上发展阶段,SAOMEI台风的旋转中心与辐合中心并不是时时重合,这个特点只能通过风场分解才能得到.此外,SAOMEI登陆以后,南部洋面上发展起来的对流活动从水汽和能量补充方面都不利于SAOMEI的维持.可见,分解后的无辐散风场和无旋风场能更清楚地体现出SAOMEI的风场结构,在台风结构分析中有重要的推广应用价值. 关键词： 台风 水平风场分解 调和-余弦算法     

多纵模激光F-P标准具双边缘测风可行性分析

讨论采用多纵模激光器作探测光源用于双边缘多普勒激光雷达测风的可行性。给出了多纵模激光器谐振腔腔长与边缘滤波器F-P标准具腔长之间的关系。分析了多纵模双边缘测风的主要特性,计算灵敏度、信噪比和径向测速误差,并与单纵模测风性能进行对比。可用类似单纵模测风中动态频率跟踪技术解决多纵模激光器频率漂移问题。     

多尺度分析在激光微多普勒效应特征提取中的应用

由于小波变换具有准确度高、抗噪性好等优点,在微多普勒效应探测方面具有很好的应用前景。利用多尺度分析（MRA）将信号进行分解并提取出含有微多普勒效应的低频平滑信息,获取了目标微小振动引起的微多普勒效应。用频谱分析和基于瞬时频率(Instfreq)的时-频域联合分析方法对原始信号及通过MRA分解得到的结果进行了对比研究。结果表明：利用时-频分析对MRA处理后的低频信号进行分析,可更加有效地提取微多普勒效应中振动信号的特征,为目标特征的识别、分类和探测提供了便利。