Independent continuous mapping for topological optimization of frame structures

Based on the Independent Continuous Mapping method (ICM), a topological optimization model with continuous topological variables is built by introducing three filter functions for element weight, element allowable stress and element stiffness, which transform the 0-1 type discrete topological variables into continuous topological variables between 0 and 1. Two methods for the filter functions are adopted to avoid the structural singularity and recover falsely deleted elements: the weak material element method and the tiny section element method. Three criteria (no structural singularity, no violated constraints and no change of structural weight) are introduced to judge iteration convergence. These criteria allow finding an appropriate threshold by adjusting a discount factor in the iteration procedure. To improve the efficiency, the original optimization model is transformed into a dual problem according to the dual theory and solved in its dual space. By using MSC/Nastran as the structural solver and MSC/Patran as the developing platform, a topological optimization software of frame structures is accomplished. Numerical examples show that the ICM method is very efficient for the topological optimization of frame structures.The project supported by the National Natural Science Foundation of China (10472003) and Beijing Natural Science Foundation (3042002) The English text was polished by Yunming Chen.     

剪切散斑干涉与有限元优化计算相结合实现缺陷参数的定量求解

本文将剪切散斑干涉与有限元优化分析相结合，对薄壁压力容器缝缺陷进行了定量检测，通过对优化计算结果和已知的缺陷参数所构成的目标函数的求解，获得了较为精确的缺陷参数识别结果。     

用地面模拟试验识别卫星太阳电池翼伸展运动的各种阻尼参数

本文利用Lagnrange方程建立了卫星太阳电池翼伸展运动的数学模型.这是一个包含摩擦阻尼、结构阻尼和空气阻尼参数的非线性微分方程组.在用气垫消除了重力影响但存在空气阻尼的地面环境中,对实尺太阳电池翼模型进行了伸展运动的模拟试验并用频闪摄影技术记录了运动的时间历程.再利用最小p乘优化方法识别出该系统的各个阻尼参数.通过对系统运动方程进行数值积分求得的太阳电池翼的伸展运动历程与实测值相当吻合.取空气阻尼等于零,得出了太阳电池翼在无空气阻尼的太空中的伸展运动规律.     

Chemometric analysis for optimizing derivatization in gas chromatography‐based procedures

This paper focuses on the application of principal component analysis (PCA) to facilitate the optimization of the derivatization of oestrogenic steroids—estrone, 17β‐estradiol, estriol, 17α‐ethinylestradiol and diethylstilbestrol—in order to achieve (1) the complete derivatization of all the hydroxyl groups contained in the structure of the compounds and (2) the greatest effectiveness of this reaction. Six different derivatization reagents were used in this study, whereas 2‐methyl‐anthracene was applied as the internal standard to evaluate the effectiveness of the reactions. The experimental data were subjected to PCA. With PCA, the dimensionality of the original multivariable data set could be reduced and the selection of optimum conditions for derivatization facilitated. The mixture of 99% N,O‐bis(trimethylsilyl)trifluoroacetamide + 1% trimethylchlorosilane and pyridine (1:1, v/v) at 60 °C for 30 min has been established as the most convenient and efficient means of derivatizing the aforementioned oestrogenic steroids and diethylstilbestrol; the N‐methyl‐N‐(trimethylsilyl)trifluoroacetamide + pyridine (1:1, v/v) mixture seems to be a promising alternative. The application of PCA for optimizing the derivatization procedure, proposed for the first time in this study, is particularly useful in the development of multicomponent methods across several chemical classes of compounds. Copyright © 2011 John Wiley & Sons, Ltd.     

Efficient and reliable mixture critical points calculation by global optimization

Multicomponent systems may exhibit several critical points or no critical point at all. Local methods can find only one critical point for a given initial guess. Recently, several global methods have been proposed for finding all the solutions of the problem. In the present work, we propose a gradient-based calculation method using global optimization, with temperature and molar volume as primary variables, and with analytical partial derivatives calculated from a two-parameter cubic equation of state. The Tunneling global optimization method is used for finding all the global minima. The implementation is based on a unique feature of the Tunneling method, which is able to find efficiently and reliably multiple minima at the same level. Several mixtures from binaries to petroleum reservoir fluids are used to test the proposed method. Numerical experiments proved the efficiency and reliability of the Tunneling method for finding all mixture critical points.     

Reversed-phase dispersive liquid-liquid microextraction with central composite design optimization for preconcentration and HPLC determination of oleuropein

A reversed-phase dispersive liquid-liquid microextraction (RP-DLLME) method was developed for the preconcentration and direct HPLC determination of oleuropein in olive's processing wastewater (OPW) and olive leaves extracts. In conventional DLLME, the sedimented phase is a micro-drop of a chlorinated organic solvent that is not compatible with RP-HPLC. Therefore, solvent evaporation and reconstitution with an appropriate solvent is often required. In RP-DLLME, this problem was overcome by overturning the solvent polarity in the ordinary DLLME and replacing the organic solvent with water. A central composite chemometrics design was used for multivariate optimization of the effects of five different parameters influencing the extraction efficiency of the method. In the optimized conditions, a mixture of 1.4 mL of an ethyl acetate extract of sample and 40 μL water (pH 5.0) was rapidly injected into 5.3 mL of cyclohexane. After centrifugation of the formed cloudy mixture, a micro-drop of the aqueous phase was sedimented at the conical bottom of the centrifuge tube. This phase, that contained the preconcentrated and partially purified analyte, was directly injected into an RP-HPLC column for analysis. A mean extraction recovery of 102.5 (±4.5) % with enrichment factors exceeding 38, was obtained for five replicated analysis. The detection limit of the method (3σ) for OE was 0.02 μg L⁻¹ for OPW and 2 × 10⁻³ mg kg⁻¹ for olive leaves samples. The results showed that, RP-DLLME is a promising technique which is quick, easily operated and can be directly coupled to HPLC.     

Variable-weighted least-squares support vector machine for multivariate spectral analysis

Multivariate spectral analysis has been widely applied in chemistry and other fields. Spectral data consisting of measurements at hundreds and even thousands of analytical channels can now be obtained in a few seconds. It is widely accepted that before a multivariate regression model is built, a well-performed variable selection can be helpful to improve the predictive ability of the model. In this paper, the concept of traditional wavelength variable selection has been extended and the idea of variable weighting is incorporated into least-squares support vector machine (LS-SVM). A recently proposed global optimization method, particle swarm optimization (PSO) algorithm is used to search for the weights of variables and the hyper-parameters involved in LS-SVM optimizing the training of a calibration set and the prediction of an independent validation set. All the computation process of this method is automatic. Two real data sets are investigated and the results are compared those of PLS, uninformative variable elimination-PLS (UVE-PLS) and LS-SVM models to demonstrate the advantages of the proposed method.     

高效能接入网络助电信运营商从互联网价值链获益

面对成为互联网流量管道供应商的尴尬,运营商需要构建一张具有以下特征的高能效接入网：高带宽（每用户达到50M甚至更高）、低延时、成本最优化的全IP宽带接入;采用可以同时满足家庭宽带用户、商业用户和移动基站回程等应用的统一融合的接入网平台;具有用户/业务/应用智能感知功能来保障正确的流量处理。高效能接入网将帮助运营商成为急速增长的高附加值互联网内容产业链的一部分。     

一种降低OFDM信号峰平功率比的新方案

提出一种基于子块幅度加权处理降低正交频分复用（OFDM）信号峰值平均功率比的新方法。在确保性能满足系统需求的条件下,通过预设优化处理门限进行循环移位优化,从而大大降低了算法的复杂度。研究与仿真结果表明,基于子块幅度加权的循环移位优化方法可以有效降低OFDM信号峰值平均功率比,且具有复杂度低、处理灵活、无需边信息等优点。