COMPUTER AIDED DESIGN OF HORN RADIATORS FOR SATELLITE COMMUNICATION BY LEAST SQUARES OPTIMIZATION

Computer aided design optimization of corrugated horns became a powerful tool to reduce development costs on the one hand and to improve performance of space antennas on the other. In this paper the physical model is outlined, based on Maxwell's equations, and it is shown how a complete numerical simulation of a circular corrugated horn can be achieved, assuming that the interior geometry of the horn is known. In order to compute the electromagnetic properties of a horn, the so-called scattering matrix is assembled. This matrix is needed to relate mode amplitudes of reflected and transmitted waves in horn sections with different diameters. Envelope functions, determined by a few geometric design parameters, are used to describe the inner geometry of a horn. These parameters are applied to formulate a least squares optimization problem. As a starting point, an amplitude spectrum in the aperture has to be determined which radiates a given far field. The differences between those amplitudes and the amplitudes predicted by the model are to become as small as possible by adapting the design variables. Moreover, the return loss is to be minimized. The resulting least squares optimization problem can be solved by a standard sequential quadratic programming (SQP) code after a suitable transformation into a nonlinear programming problem, by which typical features of Gauss-Newton methods are retained. Some numerical results are included to show the successful application of the introduced advance to design a circular corrugated horn which radiates a given far field.     

The TTP Transonic wind tunnel Mach number uniformity analysis

The distribution of the Mach number in the test section of the Brazilian Pilot Transonic Wind Tunnel was evaluated for the subsonic, transonic and low supersonic regimes. A convergent–divergent nozzle was designed and manufactured to increase the TTP envelope up to Mach number 1.3. Static and total pressures of the airflow are input quantities for the isentropic equation used for Mach number estimation. Static pressure measurements at the test section stations are accomplished by a centreline pressure probe and by distributing pressure taps along the upper and lower walls. Data reduction includes the evaluation of the uncertainties associated with the measured quantities, as well as their propagation to the output quantity, by employing the Monte Carlo method. Least squares fitting is applied to the experimental data in order to supply Mach number calibration curves. Sources of error causing non-uniform flow for Mach number equal to 1.3 are pointed out.     

Electronic nose and GC–MS analysis of volatile compounds in Tuber magnatum Pico: Evaluation of different storage conditions

The characteristic aromatic composition of white truffles (Tuber magnatum Pico) determines its culinary and commercial value. However modifications of truffle organoleptic proprieties occur during preservation. A study of headspace of white truffles by using Electronic nose (E-nose), gas chromatography–mass spectrometry (GC–MS) and sensory analyses was performed. Truffles were stored at different conditions for 7 days: +4 and +8 °C wrapped in blotting paper or covered by rice or none of the above. Headspace E-nose measurements and sensory analyses were performed each day. Statistical multivariate analysis of the data showed the capability of E-nose to predict sensorial analysis scores and to monitor aroma profile changes during storage. Truffle’s volatile molecules were also extracted by headspace solid phase microextraction technique and separated and identified by GC–MS. Partial Components Analysis of data was performed. E-nose and GC–MS results were in agreement and showed that truffle storage in paper at +8 °C seemed to be the best storage condition.     

LS-SVM and Monte Carlo methods based reliability analysis for settlement of soft clayey foundation

A method which adopts the combination of least squares support vector machine (LS-SVM) and Monte Carlo (MC) simulation is used to calculate the foundation settlement reliability. When using LS-SVM, choosing the training dataset and the values for LS-SVM parameters is the key. In a representative sense, the orthogonal experimental design with four factors and five levels is used to choose the inputs of the training dataset, and the outputs are calculated by using fast Lagrangian analysis continua (FLAC). The decimal ant colony algorithm (DACA) is also used to determine the parameters. Calculation results show that the values of the two parameters, γ and δ² have great effect on the performance of LS-SVM. After the training of LS-SVM, the inputs are sampled according to the probabilistic distribution, and the outputs are predicted with the trained LS-SVM, thus the reliability analysis can be performed by the MC method. A program compiled by Matlab is employed to calculate its reliability. Results show that the method of combining LS-SVM and MC simulation is applicable to the reliability analysis of soft foundation settlement.     

风险树分析在钻井工程事故中的应用

结合概率统计知识,利用风险树分析引发钻井工程事故的顶事件,重点讨论各底事件的相互联系及对系统的影响程度,从而寻找系统的漏洞,分析顶事件的发生概率,在此基础上采取相应的纠正措施,为最大程度地减少钻井工程事故的发生及其损失提供理论依据。     

Improved MLV filter to remove multiplicative noise

More methods can be used to remove the additive noise, such as the Mean of Least Variance （MLV） filter. When the signal is noised by the multiplicative noise, it is difficult to remove. The paper presents an improved filter to remove multiplicative noise by changing the multiplicative noise to the additive noise, and then using the MLV-like to remove the additive noise. The simulation results show that the performance is better than Minimum Coefficient of Variation （MCV） filter and MLV filter. Both one-dimension and image experiments demonstrate its theoretical performance.     

A novel indoor geo-location method using MIMO array

In a Multiple-Input Multiple-Output （MIMO） Orthogonal Frequency Division Multiplexing （OFDM） based Wireless Local Area Network （WLAN） system, both Access Points （APs） and Mobile Terminals （MTs） are configured with multiple antennas, to make novel indoor geo-location method possible. In this paper, we presented a novel Least Square Support Vector Machine （LS-SVM） based data fusion algorithm to fuse signal strength measurements for indoor geo-location using only a single AP with MIMO arrays. We evaluate our proposed algorithms under indoor environments by MATLAB simulations. Simulation results show that our MIMO-based algorithm is superior to conventional least square algorithm.     

奶茶粉脂肪酸指纹特征及真实性判别模型建立

目的 评价以脂肪酸(fatty acid, FAs)指纹建立奶茶粉真实性判别模型的可行性。方法 采集生牛乳喷雾干燥(湿法)和植脂末、乳粉、炼乳粉粉末原料混合制备(干法)奶茶粉138种产品,并采集植脂末、奶油粉和奶粉为参照样品,气相色谱法检测FAs,进行差异性比较,并进行正交偏最小二乘判别分析(orthogonalpartial least squares discriminant analysis, OPLS-DA)和层聚类分析(hierarchical cluster analysis,HCA),观察各种类奶茶粉样品聚类特征,评价模式相似度。构建奶茶粉掺植脂末OPLS-DA和偏最小二乘(partial least square, PLS)预测模型。结果 生牛乳湿法制备的奶茶粉与其他3种干法制备的奶茶粉FAs指纹显著不同,与奶粉有同质性,两者模式相似度为94.9%; 3种干法制备的奶茶粉与植脂末、奶油粉存在同质性,可归入同一个大类,模式相似度为27.2%。OPLS-DA和PLS模型有良好的预测能力,可以区分0%植脂末(奶粉)与添加12.5%植脂末的人工奶茶粉样品。3种市售干法制备奶茶粉...     

1400F铝带轧机板形缺陷识别处理

要对铝带材的板形进行有效的控制,必须对实际的板形进行识别,以判断当前带材板形的缺陷模式,才能有效的利用轧机装备的板形控制装置对板形实施控制。本文通过最小二乘法,建立板形缺陷的识别理论,并根据实际数据和现场应用,证明了该理论的可行性。     

支持向量机在钻井工程数据拟合中的应用

支持向量机(SVM)是近年来发展起来的一种通用的机器学习方法,在小样本数据的拟合中已获得了很好的效果。对于常见的支持向量回归机方法:ε-支持向量回归机和最小二乘支持向量回归机进行了归纳总结,并给出了一具体应用案例。