The basic physical properties of marine natural gas hydrate deposits are important to the understanding of seabed growth conditions, occurrence regularity, and occurrence environment of natural gas hydrates. A comprehensive analysis of the core samples of drilling pressure-holding hydrate deposits at a depth of 1310 m in the Shenhu area of the South China Sea was conducted. The experimental results indicate that the particle size in the hydrate sediment samples are mainly distributed in the range from 7.81 µm to 21.72µm, and the average particle size decreases as the depth of the burial increases. The X-ray CT analytical images and surface characteristics SEM scan images suggest that the sediment is mostly silty clay. There are a large number of bioplastics in the sediment, and the crack inside the core may be areas of hydrate formation.

Xin LYU ,   Qingping LI   et al.
Wind-lens turbines (WLTs) exhibit the prospect of a higher output power and more suitability for urban areas in comparison to bare wind turbines. The wind-lens typically comprises a diffuser shroud coupled with a flange appended to the exit periphery of the shroud. Wind-lenses can boost the velocity of the incoming wind through the turbine rotor owing to the creation of a low-pressure zone downstream the flanged diffuser. In this paper, the aerodynamic performance of the wind-lens is computationally assessed using high-fidelity transient CFD simulations for shrouds with different profiles, aiming to assess the effect of change of some design parameters such as length, area ratio and flange height of the diffuser shroud on the power augmentation. The power coefficient ( ) is calculated by solving the URANS equations with the aid of the SST model. Furthermore, comparisons with experimental data for validation are accomplished to prove that the proposed methodology could be able to precisely predict the aerodynamic behavior of the wind-lens turbine. The results affirm that wind-lens with cycloidal profile yield an augmentation of about 58% increase in power coefficient compared to bare wind turbine of the same rotor swept-area. It is also emphasized that diffusers (cycloid type) of small length could achieve a twice increase in power coefficient while maintaining large flange heights.

To improve the fault redundancy capability for the high reliability requirement of a brushless doubly-fed generation system applied to large offshore wind farms, the control winding of a brushless doubly-fed reluctance generator is designed as an open-winding structure. Consequently, the two ends of the control winding are connected via dual three-phase converters for the emerging open-winding structure. Therefore, a novel fault-tolerant control strategy based on the direct power control scheme is brought to focus in this paper. Based on the direct power control (DPC) strategy, the post-fault voltage vector selection method is explained in detail according to the fault types of the dual converters. The fault-tolerant control strategy proposed enables the open-winding brushless doubly-fed reluctance generator (BDFRG) system to operate normally in one, two, or three switches fault of the converter, simultaneously achieving power tracking control. The presented results verify the feasibility and validity of the scheme proposed.

Shi JIN ,   Long SHI   et al.
Since gas turbine plays a key role in electricity power generating, the requirements on the safety and reliability of this classical thermal system are becoming gradually strict. With a large amount of renewable energy being integrated into the power grid, the request of deep peak load regulation for satisfying the varying demand of users and maintaining the stability of the whole power grid leads to more unstable working conditions of gas turbines. The startup, shutdown, and load fluctuation are dominating the operating condition of gas turbines. Hence simulating and analyzing the dynamic behavior of the engines under such instable working conditions are important in improving their design, operation, and maintenance. However, conventional dynamic simulation methods based on the physic differential equations is unable to tackle the uncertainty and noise when faced with variant real-world operations. Although data-driven simulating methods, to some extent, can mitigate the problem, it is impossible to perform simulations with insufficient data. To tackle the issue, a novel transfer learning framework is proposed to transfer the knowledge from the physics equation domain to the real-world application domain to compensate for the lack of data. A strong dynamic operating data set with steep slope signals is created based on physics equations and then a feature similarity-based learning model with an encoder and a decoder is built and trained to achieve feature adaptive knowledge transferring. The simulation accuracy is significantly increased by 24.6% and the predicting error reduced by 63.6% compared with the baseline model. Moreover, compared with the other classical transfer learning modes, the method proposed has the best simulating performance on field testing data set. Furthermore, the effect study on the hyper parameters indicates that the method proposed is able to adaptively balance the weight of learning knowledge from the physical theory domain or from the real-world operation domain.

Dengji ZHOU ,   Jiarui HAO   et al.

Most Popular