Wang Hai-jun

An investigation into the heat transfer characteristics of spiral wall with internal rib in a supercritical sliding-pressure operation once-through boiler

Within the pressure range of 9–28 MPa, mass velocity range of 600–1 200 kg/(m2·s), and heat flux range of 200–500 kW/m2, experiments were performed to investigate the heat transfer to water in the inclned upward internally ribbed tube with an inclined angle of 19.5 degrees, a maximum outer diameter of 38.1 mm, and a thickness of 7.5 mm. Based on the experiments, it was found that heat transfer enhancement of the internally ribbed tube could postpone departure from nucleate boiling at the sub-critical pressure. However, the heat transfer enhancement decreased near the critical pressure. At supercritical pressure, the temperature difference between the wall and the fluid increased near the pseudo-critical temperature, but the increase of wall temperature was less than that of departure from nucleate boiling at sub-critical pressure. When pressure is closer to the critical pressure, the temperature difference between the wall and the fluid increased greatly near the pseudo-critical temperature. Heat transfer to supercritical water in the inclined upward internally ribbed tube was enhanced or deteriorated near the pseudo-critical temperature with the variety of ratio between the mass velocity and the heat flux. Because the rotational flow of the internal groove reduced the effect of natural convection, the internal wall temperature of internally ribbed tube uniformly distributed along the circumference. The maximum internal wall temperature difference of the tube along the circumference was only 10 degrees when the fluid enthalpy exceeded 2 000 J/g. Considering the effect of acute variety of the fluid property on heat transfer, the coreelation of heat transfer coefficient on the top of the internally ribbed tube was provided.

A new time-frequency analysis based upon AR model

In this paper we analyzed the reasons why the discrete Wigner-Ville-distribution (WVD) of real-valued signal sampled at the Nyquist rate has spectral aliasing, whereas short time Fourier transform (STFT) has not such problems. For the time-frequency resolution of STFT spectrogram is very poor, a novel method of time-frequency analysis based on auto-regressive model (AR) is presented in this paper, which inherits merits of STFT spectrogram and has very good time-frequency resolution. When data for processing are very large, the new method may have excellent performance for promoting velocity of calculating, saving storage and keeping high time-frequency resolution. In addition, the applications of the new method were also illustrated for identifying ripple-fired explosions, the results were compared with that of spectrogram. Experiments showed that the performances of the new algorithm were superior than that of spectrogram.

Stability analysis of a square rod bundle sub-channel in supercritical water reactor

Extensive investigations on the flow and heat transfer behavior in SCWR fuel assembly have been undertaken worldwide. However, stability analysis of supercritical water in the sub-channels of tight lattices is still lacking. In this paper, the flow stability of a fuel bundle channel with square pitches has been analyzed using commercial CFD code-ANSYS Fluent. Typical dynamic instability of Density Wave Oscillation (DWO) has occurred in heated channel containing fluids at supercritical pressure. A further discussion about the impacts of various operational parameters (e.g. power input, system pressure, mass velocity, inlet temperature, etc) shows that the system becomes more stable as system pressure and/or mass flow rate increases. An increase in inlet temperature also has a stabilizing effect on the system.

Automatic signal detection based on support vector machine

Algorithm of STA/LTA is frequently used in automatic signal detection, in which the range of detection threshold is (0, ∞), the optimal threshold should be determined by experiment to make a balance between false detection and missing detection. By using the theory of pattern recognition, a new algorithm for automatic signal detection based on support vector machine was proposed and the method of preprocess and pattern feature extraction were discussed as well as the selection of kernel function for support vector machine. The detection performance of the new algorithm was analyzed by means of real seismic data. The experiments showed that the new method could simplify the selection of threshold and detect signal accurately. In addition to the better performance of anti-noise, the ratio of false detection could decrease 85% in comparison with that of STA/LTA.

Automatic spikes detection in seismogram

4 ConclusionsIn spikes automatic detection, the algorithm of WNEO present in this paper is superior to that of SNEO and Amplitude Comparing; While using WNEO, basic wavelet function is not important for spikes detection, and scale f/it=1 is enough for wavelet analysis; Processing for data recorded in station AAK shows that the new algorithm can to used in real seismic recores with broad frequency band or short period in different epicenter distance.