A new method for calculating loss coefficients [of power systems]

A method is proposed which avoids many limitations associated with traditional B-coefficient loss coefficient calculation. The proposed method, unlike the traditional B-coefficient method, is very fast and can handle line outages. The method utilizes network sensitivity factors which are established from DC load flow solutions, Line outage distribution factors (ODFs) are formulated using changes in network power generations to simulate the outaged line from the network. The method avoids the use of complicated reference frame transformations based upon Kron's tenser analysis. The necessity of data normalization used in least squares and the evaluation of the slope of &thetas;_j versus PG_n is not necessary with the proposed method. Using IEEE standard 14-bus and 30-bus systems, the method's results are compared against results obtained from an AC load flow program (LFED). The method's solution speed is compared to that of the LFED method, the base case database method and the conventional B-coefficient method based on A_jn-factor. The proposed method is easy to implement and, when compared to other methods, has exhibited good accuracy and rapid execution times. The method is well suited to online dispatch applications     

影响DT岩石粉状铵梯炸药爆速的因素探索

文章从ＤＴ岩石粉状铵梯炸药的原材料细度，复合油相，混药时间，投料顺序，混药药温，装药密度等方面，探讨了该炸药爆速的影响因素。     

新年贺词

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Optimal phases for a family of quadriphase CDMA sequences

Signature sequences with good even even and odd (or polyphase) correlations are crucial for asynchronous code-division multiple access (CDMA). When the data sequence is random, the even and odd (or polyphase) correlations are equally important. However, for most known signature sequences, only their even correlations were analyzed. It appears that determining the odd (or the polyphase) correlations is generally a very hard problem since the odd (or the polyphase) correlations depend on the phases of the signature sequences. Sole (1989), Boztas, Hammons, and Kumar (1992) found a family of quadriphase sequences that are asymptotically optimal. These sequences gain a factor √2 in terms of their maximum periodic even correlations when compared with the best possible binary phase-shift keying (BPSK) sequences. We find the optimal phases of these sequences. The optimality is in the sense that at these phases, the mean square values of the even, odd, and the polyphase correlations are minimal, and achieve the Welch (1974) bound-equality simultaneously. Furthermore, we show that at these phases, the average user interference of these sequences is always smaller than that of the ideal random signature sequences. Comprehensive analytical and numerical results show that good phase sequences can offer a nonnegligible amount of gain over bad phase sequences at modest and high signal-to-noise ratios     

Optimization of a schottky barrier mixer diode in the submillimeter wave region

We have designed a mixer Schottky barrier diode (SBD) for use in the submillimeter wave region with a structure optimized for minimum noise temperature. The dependence of mixer noise temperature upon thickness and doping density of the epitaxial layer and diode diameter of SBDs was simulated within the framework of existing theories. Special care was taken to formulate the SBD current-voltage and capacitance-voltage relations in a way that correctly describes the behavior of real SBDs.     

微波高压提取快速测定饲料含氟量的探讨

采用微波高压制样技术,快速提取饲料中的氟元素,结合氟离子选择性电极标准添加和电位极差测试方法,能够快速、准确地测试饲料中的含氟量     

Analogue implementation of a neural network controller for UPSinverter applications

An analogue neural-network controller for UPS inverter applications is presented. The proposed neural-network controller is trained off-line using patterns obtained from a simulated controller, which had an idealized load-current-reference. Simulation results show that the proposed neural-network controller can achieve low total harmonic distortion under nonlinear loading condition and good dynamic responses under transient loading condition. To verify the performance of the proposed NN controller, a hardware inverter with an analogue neural network (NN) controller (using mainly operational amplifiers and resistors) is built. Additionally, for comparison purposes, a PI controller with optimized parameters is built. Experimental results confirm the simulation results and show the superior performance of the NN controller especially under rectifier-type loading condition. Implementing the analogue neural-network controller using programmable integrated circuits is also discussed     

Nonregular feedback linearization: a nonsmooth approach

In this note, we address the problem of exact linearization via nonsmooth nonregular feedback. A criterion of nonregular static state feedback linearizability is presented for a class of nonlinear affine systems with two control inputs, and its application to nonholonomic systems is briefly discussed.