Real-time onboard wind and windshear determination,part 2: Detection

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.     

Real-time onboard wind and windshear determination,part 1: Identification

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.     

Fastiterative methods for least squares estimations

Least squares estimations have been used extensively in many applications, e.g. system identification and signal prediction. When the stochastic process is stationary, the least squares estimators can be found by solving a Toeplitz or near-Toeplitz matrix system depending on the knowledge of the data statistics. In this paper, we employ the preconditioned conjugate gradient method with circulant preconditioners to solve such systems. Our proposed circulant preconditioners are derived from the spectral property of the given stationary process. In the case where the spectral density functions() of the process is known, we prove that ifs() is a positive continuous function, then the spectrum of the preconditioned system will be clustered around 1 and the method converges superlinearly. However, if the statistics of the process is unknown, then we prove that with probability 1, the spectrum of the preconditioned system is still clustered around 1 provided that large data samples are taken. For finite impulse response (FIR) system identification problems, our numerical results show that annth order least squares estimator can usually be obtained inO(n logn) operations whenO(n) data samples are used. Finally, we remark that our algorithm can be modified to suit the applications of recursive least squares computations with the proper use of sliding window method arising in signal processing applications.Research supported in part by HKRGC grant no. 221600070, ONR contract no. N00014-90-J-1695 and DOE grant no. DE-FG03-87ER25037.     

新型尾式硫代苯并噻唑基卟啉化合物的合成与表征

通过不对称的单羟基卟啉化合物、溴代烷烃和巯基苯并噻唑合成了一系列新型硫代苯并噻唑基尾式卟啉化合物, 并采用核磁共振氢谱、碳谱、红外光谱、质谱和元素分析对卟啉化合物的结构进行了表征.     

Computer interactive identification system for polycyclic aromatic hydrocarbons in reversed-phase microcolumn liquid chromatography

Summary A computer interactive identification system is proposed which is based on the relationship between retention and molecular properties such as the size and shape of polycyclic aromatic hydrocarbons (PAHs). This system offers an automatic analytical process for liquid chromatography, providing a reliable identification of the separated components. The identification can be further enhanced by the use of multiple detectors such as a multichannel UV detector. The system can be used for optimization procedures, resulting in a highly automatic complex analytical system.     

傅里叶变换红外光谱和傅里叶变换拉曼光谱法无损鉴别药材的真伪

利用傅里叶变换红外（FT-IR）和近红外傅里叶变换拉曼（NIR FT-aman）光谱法对大黄（西宁大黄）与伪品大黄（华北大黄、山大黄、水根大黄）进行了无损快速的鉴别。结果表明：尽管正品大黄与伪品大黄差别较小，有大部分的化学成分有很大的相同之处，但在红外、拉曼谱图中各自的特征峰较突出，根据谱峰的强度和位置可容易地将它们区别开来。红外和拉曼光谱法相互印证，相互补充，具有快速、准确、操作简单、重复性好、不需对样品进行分离提取，可直接鉴别等特点。     

皱叶香茶菜化学成分的研究

从采自西藏的皱叶香茶菜中分离鉴定了3对B-闭联对映贝壳杉烯型二萜化合物:二萜化合物皱叶香茶菜素(Ⅰ)和二氢皱叶香茶菜素(Ⅱ);isodocarpin(Ⅲ)和dihydroisodocarpin(Ⅳ)及Carpalasionin(Ⅴ)和dihydrocarpalasionin(Ⅵ)。(Ⅰ)、(Ⅲ)和(Ⅴ)分别与对应的二氢化合物(Ⅱ)、(Ⅳ)和(Ⅵ)以混合物的形式被分离和鉴定。化合物(Ⅱ)为新化合物,(Ⅰ)、(Ⅳ)和(Ⅵ)首次在自然界发现,(Ⅲ)和(Ⅴ)为已知化合物。     

A New Technique of Synthesizing 10—Hydroxy—5—methyl—5,10—dihydrophenophosphazine 10—Oxide

10-Hydroxy-5-methyl-5,10-dihydrophenophosphazine 10-oxide(1)was prepared by a new technique of treating 10-methoxy-5,10-dihydrophenophosphazine 10-oxide(2)with an equivalent of NaH in anhydrous DMF,and then at 120℃ for 3-4h,which not only avoided poisonous and expensive methyl iodide used in literature,but made the consumption of NaH greatly decrease as well.The possible reaction mechanism was also described.The chemical structure of 1 was confiremed by IR,NMR,and mass spectroscopy.     

Analysis of polynuclear aromatic hydrocarbons by glass capillary gas chromatography using simultaneous flame ionization and electron capture detection

The possibility of simultaneous application of an electron capture (ECD) and a flame ionization detector (FID) connected to a glass capillary column for analyzing polynuclear aromatic hydrocarbons (PNA) has been investigated. The ECD/FID ratio is determined for 46 PNA compounds. The ratios vary from 0.02 to 117 with relative standard deviations better than 20 percent determined from 10 replicate analyses. The results suggest that the method may be used for obtaining additional evidence in identifying PNA in environmental samples. Impurities and transformation products in the standard were identified by computerized glass capillary gas chromatography/mass spectrometry. Quinones and diones are responsible for the high EC-response determined in some trace components in the standard. An application of the method is shown for PNA from particulates in urban atmospheres.