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1.
A flow model in combination with a statistical-dynamical turbulence generator and a linearised Euler time-domain model for sound waves were used to simulate the effect of screen-induced turbulence on the noise level in the acoustical shadow of a screen in wind. Instead of simulating a great number of different frozen turbulence realisations, the concept of transient turbulence was successfully tested and applied. This concept is adequate to the time-domain model and reduces the computational demands. Several two-dimensional simulations allowed to isolate the individual effects of wind and screen on the propagation of 500 Hz sound waves over a 4-m high noise barrier. At a distance of 250 m from the source (240 m behind the screen) the sheltering effect of the screen and the refraction effect of the wind are in the order of 6 and 4 dB, respectively. The screen-induced turbulence leads to fluctuations in the noise level with a standard deviation of 1.2 dB and a maximum amplitude of 3 dB. However, the time averaged effect turned out to be in the order of merely 0.2 dB. The effect of the screen-induced turbulence on the average noise level behind the screen is therefore negligible. 相似文献
2.
This paper is concerned with windshear detection in connection with real-time wind identification (Ref. 1). It presents a comparative evaluation of two techniques, one based on the shear/downdraft factor and one based on the wind difference index. The comparison is done with reference to a particular microburst, that which caused the 1985 crash of Flight Delta 191 at Dallas-Fort Worth International Airport.The shear/downdraft factor has the merit of combining the effects of the shear and the downdraft into a single entity. However, its effectiveness is hampered by the fact that, in a real situation, the windshear is accompanied by free-stream turbulence, which tends to blur the resulting signal. In turn, this results in undesirable nuisance warnings if the magnitude of the shear factor due to free-stream turbulence is temporarily larger than that due to true windshear. Therefore, proper filtering is necessary prior to using the shear/downdraft factor in detection and guidance. One effective way for achieving this goal is to average the shear/downdraft factor over a specified time interval . The effect of on the average shear/downdraft factor is studied. 相似文献
3.
Standard wind identification techniques employed in the analysis of aircraft accidents are post-facto techniques; they are processed after the event has taken place and are based on the complete time histories of the DFDR/ATCR data along the entire trajectory. By contrast, real-time wind identification techniques are processed while the event is taking place; they are based solely on the knowledge of the preceding time histories of the DFDR/ATCR data.In this paper, a real-time wind identification technique is developed. First, a 3D-kinematic approach is employed in connection with the DFDR/ATCR data covering the time interval preceding the present time instant. The aircraft position, inertial velocity, and accelerometer bias are determined by matching the flight trajectory computed from the DFDR data with the flight trajectory available from the ATCR data. This leads to a least-square problem, which is solved analytically every seconds, with / small.With the inertial velocity and accelerometer bias known, an extrapolation process takes place so as to predict the inertial velocity profile over the subsequent -subinterval. At the end of this subinterval, the extrapolated inertial velocity and the newly identified inertial velocity are statistically reconciled and smoothed. Then, the process of identification, extrapolation, reconciliation, and smoothing is repeated. Subsequently, the wind is computed as the difference between the inertial velocity and the airspeed, which is available from the DFDR data. With the wind identified, windshear detection can take place (Ref. 1).As an example, the real-time wind identification technique is applied to Flight Delta 191, which crashed at Dallas-Fort Worth International Airport on August 2, 1985. The numerical results show that the wind obtained via real-time identification is qualitatively and quantitatively close to the wind obtained via standard identification. This being the case, it is felt that real-time wind identification can be useful in windhsear detection and guidance, above all if the shear/downdraft factor signal is replaced by the wind difference signal (Ref. 1).This paper and its companion (Ref. 1) are based on Refs. 2–4.This research was supported by the Aviation Research and Education Foundation and by Texas Advanced Technology Program, Grant No. TATP-003604020. 相似文献
4.
地球影像浏览技术在卫星数据服务中的应用 总被引:2,自引:0,他引:2
给出了基于3维地球模型的卫星影像交互武浏览与显示系统的架构以及关键技术的实现;创新性地将地球影像浏览技术应用于对地观测卫星的编程数据服务系统中,并针对服务流程需求实现相关信息的显示与处理功能。 相似文献
5.
近45年北太平洋海表风速特征统计分析 总被引:1,自引:0,他引:1
本文利用来自欧洲中期天气预报中心(ECMWF——European Centre for Medium-Range Weather Forecasts)的1957年8月—2002年7月逐6 h的ERA-40海表10 m风场资料,统计分析了近45年期间北太平洋海表风场的月变化特征,以及多年平均海表风速的分布特征,为海洋水文保障、海洋工程等提供参考。结果表明:(1)北太平洋的海表风场具有明显的月变化特征,10月至来年2月的风速整体高于其余月份。(2)从年平均风速来看,阿留申群岛附近海域为北太平洋年平均风速的明显大值中心,年平均风速基本在8 m/s以上;中纬度海域的年平均风速在6~7 m/s;15°N-20°N的东部海域存在一相对大值区,年平均风速在7 m/s以上;赤道西部海域的年平均风速较小,基本在4 m/s以内。 相似文献
6.
本文中,通过UG软件的三维绘图功能创建了750KW大型风力机轮毂的实体模型,并采用有限元进行了静力学结构分析。计算出了轮毂的最大应力和最大应变。经过校核可知,最大值在材料的许用范围内。分析结果表明,通过ANSYS软件分析的结果与实际情况很接近。本文为后续设计出高性能的大型风机轮毂以及大型风力发电机机组的设计、优化提供一定的设计依据。 相似文献
7.
成功的字幕翻译不仅使得影视的观看效果不受影响,而且不需要花费太多的精力和时间观众就能够做到字幕的认读。以《乱世佳人》为例,从表达、内容、语境和文化四个层面来阐述多模态话语视角下电影字幕的翻译。 相似文献
8.
根据自立式塔架结构脉动风荷载的空间分布形式,实现了本征特征分解(proper orthogonal decomposition,POD)和基于荷载-里兹模态分析相结合的Ritz-POD算法求解Ritz振型,并结合谐波激励法(harmonic excitation method,HEM)和荷载-响应相关法(load response correlation method,LRC)实现了塔架结构风振响应和等效静力风荷载(equivalent static wind load,ESWL)的高效分析。计算结果表明:采用40阶基于荷载-里兹振型和100阶传统自由振动振型计算的节点风振响应和等效静力风荷载结果及变化规律一致且二者吻合度高,说明较少阶Ritz振型的计算精度是能够保障的。并且较少阶Ritz振型减少了谐波激励法与荷载-响应相关法的运算工作量,提高了风致振动分析的效率。另外,本文利用大型通用有限元软件SAP2000基于MATLAB系统的应用程序接口(API)开发环境,实现了塔架结构风致动力响应和等效静力风荷载的高效分析平台,可为其他大型复杂工程的风致振动分析提供参考。 相似文献
9.
10.
趋势分析和变化点检测是时间序列分析中常用的工具. 变化点检测是识别过程行为的自然或人为的突然的变化,而趋势可以定义为对逐渐偏离过去的规范的估计. 本文使用了Cox-Stuart方法和变化点算法分析时间序列数据趋势的存在,并以澳大利亚的近地表风速时间序列为例. 澳大利亚的近地表风速趋势是根据研究出的新开发的风速数据集,通过使用局部表面粗糙度信息,以及不同高度收集的混合观测数据构建. 10 m处的风的速度趋势通常会增加,而2 m处则趋于减小. 假设检验测试,变化点分析和人工检查记录表明有几个因素可能是导致差异的原因,例如伴随仪器变化的系统性偏差,随机数据错误(例如累积日错误)和数据采样问题. 均质化以及基于变化点检测的技术和多期趋势分析阐明了风速趋势不一致的根源. 相似文献