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Shanghai, China

Shanghai University of Electric Power is a public university in Shanghai, People's Republic of China. Wikipedia.

Liu Z.,Shanghai JiaoTong University | Zhu Q.,Shanghai University of Electric Power
Energy Conversion and Management | Year: 2011

An experimental study was carried out to investigate the effects of aqueous CuO nanofluids on thermal performance of a horizontal mesh heat pipe working at steady sub-atmospheric pressures. The nanofluid was composed of deionized water and CuO nanoparticles with an average diameter of 50 nm. The experimental results show that adding CuO nanoparticles into deionized water can significantly enhance heat transfer coefficients of both evaporator and condenser, and the maximum heat flux of the heat pipe. There is an optimal mass concentration of nanoparticles corresponding to the maximum heat transfer enhancement. The operating pressure has an apparent impact on both the evaporating and condensing heat transfer enhancements. The heat transfer enhancement effects increase distinctly with the decrease of the pressure. The present investigation discovers that the thermal performance of a mesh heat pipe can be evidently strengthened by substituting CuO nanofluids for deionized water under sub-atmospheric pressures. © 2010 Elsevier Ltd. All rights reserved.

Cai J.,Shanghai University of Electric Power
Nonlinear Analysis: Real World Applications | Year: 2014

We study a free boundary problem for the Fisher-KPP equation modeling the spreading of a biological or chemical species. In this model, the free boundaries represent the spreading fronts of the species. We discuss the asymptotic behavior of bounded solutions and obtain a trichotomous result: spreading (the free boundaries amounts to the whole space and the solution converges to 1), transition (the free boundaries stay in a bounded interval and the solution converges to a stationary solution with positive compact support) and vanishing (the free boundaries converge to the same point and the solution tends to 0 within a finite time). © 2013 Elsevier Ltd. All rights reserved.

Tang Z.,Shanghai University of Electric Power
International Journal of Electrical Power and Energy Systems | Year: 2012

Ice accretion of overhead conductors is a serious problem for power utilities. Among various de-icing approaches, short circuit based de-icing is one of the most frequently used ones. Since the short circuit based de-icing requires cumbersome and tricky operations, and some lines are taken out of service, pre-planned short circuit schemes are usually adopted in order to prevent mis-operation. Whereas, since some transmission lines might be tripped and system topology varies notably during ice storm, fast forming of short circuit de-icing scheme is not a simple task. Based on thorough investigation of pre-established de-icing schemes in Changsha power grid, rules to set up de-icing schemes are concluded. An expert system combining the power of graph theory has been developed in the paper to enumerate all the feasible de-icing routes. Thereafter, short circuit current and de-icing time of each route are calculated to single out candidate routes, and thus, dispatchers can form de-icing scheme at easy. © 2012 Elsevier Ltd. All rights reserved.

Li Y.,Shanghai University of Electric Power
International Journal of Digital Content Technology and its Applications | Year: 2012

By research of traditional traffic prediction model it is found that the defects will decrease the performance of network and the methods are unsuitable for modeling of self-similar network traffic. So we put forward a novel model for predicting based on the wavelet transform and BP neural network. First we use wavelet transform on the traffic time series to acquire the detailed signals and approximate signals at different scales. Then the autocorrelated degree of approximate signals is calculated by correlation analysis to determine the input and output of the neural network, which is used to construct BP neural network and training. ARMIA algorithm is used for prediction of the detailed signals. At last we take wavelet reconstruction to acquire the final result of prediction. The experiment has verified that this model has better prediction effect, scientificity and accuracy, compared with the single models.

Zhao Y.,Shanghai University of Electric Power
Journal of Computational Information Systems | Year: 2012

In this paper, a new image hashing method based on texture and shape feature is proposed. At first the input image is pre-processed and divided into non-overlapped blocks. These blocks are mapped to a circle by equal interval sampling and Zernike moments of these blocks after mapping are calculated. Then the amplitudes of Zernike moments and the texture features of each block are connected to form the intermediate hash. Lastly, the final hash sequence is obtained by pseudo-randomly permuting the intermediate hash sequence. Similarity between hashes is measured by a new distance. Experimental results show that this method is robust against most content-preserving attacks. The threshold can be got by robustness and uniqueness tests. The distance of hashes between two different images or original and tampering images is bigger than the threshold. So this method can be used in image authentication and tampering detection. © 2012 Binary Information Press.

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