基于设计空间的基本开关电容电路滤波器设计

提出了一种运用符号和数值计算与离散非线性优化相结合的滤波器设计方法——设计空间法,把滤波器的技术指标,即滤波器设计中要用到的一组参数映射到设计空间,并根据给定的准则寻找这一设计空间的最佳解决方案。然后介绍了一种新型的具有独立零点设置的基本二阶开关电容电路,最后通过实例阐述了用设计空间法设计一开关电容（SC）低通滤波器,实验证明了该方法的可行性,并且得到了预期的效果。     

Dynamic characteristics of an NC table with phase space reconstruction

The dynamic properties of a numerical control (NC) table directly interfere with the accuracy and surface quality of work pieces machined by a computer numerical control (CNC) machine. Phase space reconstruction is an effective approach for researching dynamic behaviors of a system with measured time series. Based on the theory and method for phase space reconstruction, the correlation dimension, maximum Lyapunov exponent, and dynamic time series measured from the NC table were analyzed. The characteristic quantities such as the power spectrum, phase trajectories, correlation dimension, and maximum Lyapunov exponent are extracted from the measured time series. The chaotic characteristic of the dynamic properties of the NC table is revealed via various approaches. Therefore, an NC table is a nonlinear dynamic system. This research establishes a basis for dynamic system discrimination of a CNC machine.     

Data-driven approach to machine condition prognosis using least square regression tree

Machine fault prognosis techniques have been profoundly considered in the recent time due to their substantial profit for reducing unexpected faults or unscheduled maintenance. With those techniques, the working conditions of components, the trending of fault propagation, and the time-to-failure are precisely forecasted before they reach the failure thresholds. In this work, we propose the least square regression tree (LSRT) approach, which is an extension of the classification and regression tree (CART), in association with one-step-ahead prediction of time-series forecasting techniques to predict the future machine condition. In this technique, the number of available observations is first determined by using Cao’s method and LSRT is employed as a prediction model in the next step. The proposed approach is evaluated by real data of a low methane compressor. Furthermore, a comparative study of the predicted results obtained from CART and LSRT are carried out to prove the accuracy. The predicted results show that LSRT offers the potential for machine condition prognosis. This paper was recommended for publication in revised form by Associate Editor Eung-Soo Shin Van Tung Tran is a lecturer at the Hochiminh City University of Technology in Vietnam. He received his B.S. and M.S. degrees in mechanical engineering from Hochiminh City University of Technology, Vietnam, in 1997 and 2003, respectively, and Ph.D. from Pukyong National University, South Korea in 2009. His research interests include machine fault diagnosis and condition prognosis. Bo-Suk Yang is a professor at the Puyong National University in Korea. He received his Ph.D. degree in mechanical engineering from Kobe University, Japan in 1985. His main research fields cover machine dynamics and vibration engineering, intelligent optimum design, and condition monitoring and diagnostics in rotating machinery. He has published well over 190 research papers in the research areas of vibration analysis, intelligent optimum design and diagnosis of rotating machinery. He is listed in Who’s Who in the World, Who’s Who in Science and Engineering, among others.     

Effective preparation of the N-dimension spin Greenberger–Horne–Zeilinger state with quantum dots embedded in microcavities

We propose a scheme for preparation of the N-dimension spin Greenberger–Horne–Zeilinger state by exploiting quantum dots (QDs) embedded in microcavities. Numerically analysed results show that with the spin-selective photon reflection from the cavity, we can complete the scheme assisted by one polarized photon with high fidelity and 100% successful probability in principle. Furthermore, the set-up is just composed of simple linear optical elements, delay lines and conventional photon detectors, which are feasible with existing experimental technology. Moreover, QDs have numerous admirable features in weak-coupling regime, which are practicable in realistic cavity quantum electrodynamics system shown by previous numerical simulations and experiments. Therefore, our scheme might be realized in near future.     

汇流曲线的定义与因次

将汇流曲线的概念引入到线性时不变汇流系统,给出了汇流曲线的定义及汇流曲线之间的相互关系,这些关系适用于线性时不变汇流系统。诠释了汇流曲线的因次问题,过去认为基本单位线(通常称为时段单位线)无因次是不妥的,它应该具有流量的因次,即m3/s。利用基本单位线也可进行地面净雨的汇流计算。     

不同分维值的铀矿浸出研究

对不同分维值的铀矿石进行柱浸试验。结果表明,在硫酸质量浓度为25g/L、布液强度为30L/(m2.h)、浸出时间30d、液固比2∶1的条件下,分维值为2的铀矿石的堆浸效果较好,铀浸出率达到97.31%。     

不同粒径分布分维数铀矿石的浸出规律

为了研究堆浸铀矿石粒径分布对堆浸效果的影响,配置5组不同粒径分布分维数的铀矿样进行室内柱浸试验,测定不同时刻浸出液的铀浓度和pH值,计算对应时刻的浸出率和酸耗。结果表明：分维数越大的铀矿样,浸出液中铀离子浓度峰值出现得越迟、峰值越小,且在峰值出现后,铀离子浓度越大;在浸出初期,分维数越大的铀矿样,浸出率越低,这种差距在浓度峰值出现之前逐渐增大,峰值过后逐渐减小;而在浸出后期,分维数大的铀矿样的浸出率依次逐渐超过分维数较小的铀矿样的浸出率,并保持进一步扩大的趋势;在浸出初期,若要获得相同的浸出率,分维数越大的铀矿样,其酸耗量也越大,酸耗量的差距随着浸出时间的延长先增大而后逐渐减小;在浸出后期,要获得相同的浸出率,酸耗则出现相反的变化情况。     

Uncertainty quantification of high‐dimensional complex systems by multiplicative polynomial dimensional decompositions

The central theme of this paper is multiplicative polynomial dimensional decomposition (PDD) methods for solving high‐dimensional stochastic problems. When a stochastic response is dominantly of multiplicative nature, the standard PDD approximation, predicated on additive function decomposition, may not provide sufficiently accurate probabilistic solutions of a complex system. To circumvent this problem, two multiplicative versions of PDD, referred to as factorized PDD and logarithmic PDD, were developed. Both versions involve a hierarchical, multiplicative decomposition of a multivariate function, a broad range of orthonormal polynomial bases for Fourier‐polynomial expansions of component functions, and a dimension‐reduction or sampling technique for estimating the expansion coefficients. Three numerical problems involving mathematical functions or uncertain dynamic systems were solved to corroborate how and when a multiplicative PDD is more efficient or accurate than the additive PDD. The results show that indeed, both the factorized and logarithmic PDD approximations can effectively exploit the hidden multiplicative structure of a stochastic response when it exists. Since a multiplicative PDD recycles the same component functions of the additive PDD, no additional cost is incurred. Finally, the random eigensolutions of a sport utility vehicle comprising 40 random variables were evaluated, demonstrating the ability of the new methods to solve industrial‐scale problems. Copyright © 2013 John Wiley & Sons, Ltd.     

Correlation of Rheological and Microstructural Properties in a Model Lipid System

Model systems having different microstructures and rheological properties were obtained by controlled crystallization from a mixture of high-melting and low-melting lipids. Based on analysis of confocal scanning light microscopic images, the microstructural characteristics of the systems were quantified by use of different approaches including microstructure density, Euler characteristic, nearest-neighbor analysis, fractal dimension of microstructure interface, and fractal dimension by the particle-counting method (PCM). The solid-fat content (SFC) of semisolid lipid samples was measured by nuclear magnetic resonance (NMR) spectroscopy and rheological properties were analyzed by compressive penetration tests with a texture analyzer. As expected, SFC had a major impact on rheological properties, but lipid crystalline microstructure also had significant effects. Correlation analysis showed that rheological properties were highly correlated with the various quantitative microstructural parameters, with the exception of the fractal dimension by the PCM. Empirical models adequately correlated rheological properties with SFC and microstructure density. Compression modulus increased by a factor of about ten as SFC increased from 0.28 to 0.51. However, for systems with the same SFC, compression modulus was dependent on microstructure. At low SFC compression modulus increased by about a factor of seven over the range of microstructures formed, whereas at higher SFC compression modulus only increased by a factor of about two.