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This paper presents a new component within the flexible ac-transmission system (FACTS) family, called distributed power-flow controller (DPFC). The DPFC is derived from the unified power-flow controller (UPFC). The DPFC can be considered as a UPFC with an eliminated common dc link. The active power exchange between the shunt and series converters, which is through the common dc link in the UPFC, is now through the transmission lines at the third-harmonic frequency. The DPFC employs the distributed FACTS (D-FACTS) concept, which is to use multiple small-size single-phase converters instead of the one large-size three-phase series converter in the UPFC. The large number of series converters provides redundancy, thereby increasing the system reliability. As the D-FACTS converters are single-phase and floating with respect to the ground, there is no high-voltage isolation required between the phases. Accordingly, the cost of the DPFC system is lower than the UPFC. The DPFC has the same control capability as the UPFC, which comprises the adjustment of the line impedance, the transmission angle, and the bus voltage. The principle and analysis of the DPFC are presented in this paper and the corresponding experimental results that are carried out on a scaled prototype are also shown.Index Terms-AC-DC power conversion, load flow control, power electronics, power semiconductor devices, power system control, power-transmission control.

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Bridge detection from Synthetic Aperture Radar (SAR) images has very important strategic significance and practical value, but there are still many challenges in end-to-end bridge detection. In this paper, a new deep learning-based network is proposed to identify bridges from SAR images, namely, multi-resolution attention and balance network (MABN). It mainly includes three parts, the attention and balanced feature pyramid (ABFP) network, the region proposal network (RPN), and the classification and regression. First, the ABFP network extracts various features from SAR images, which integrates the ResNeXt backbone network, balanced feature pyramid, and the attention mechanism. Second, extracted features are used by RPN to generate candidate boxes of different resolutions and fused. Furthermore, the candidate boxes are combined with the features extracted by the ABFP network through the region of interest (ROI) pooling strategy. Finally, the detection results of the bridges are produced by the classification and regression module. In addition, intersection over union (IOU) balanced sampling and balanced L1 loss functions are introduced for optimal training of the classification and regression network. In the experiment, TerraSAR data with 3-m resolution and Gaofen-3 data with 1-m resolution are used, and the results are compared with faster R-CNN and SSD. The proposed network has achieved the highest detection precision (P) and average precision (AP) among the three networks, as 0.877 and 0.896, respectively, with the recall rate (RR) as 0.917. Compared with the other two networks, the false alarm targets and missed targets of the proposed network in this paper are greatly reduced, so the precision is greatly improved.

The microstructural evolution of loess had a significant impact on the collapsibility of loess during wetting-drying cycles. Based on the analysis of scanning electron microscope (SEM) images by using Image-Pro Plus, the present study quantitatively compared the microstructural parameters of original loess and remoulded loess with different moisture content before and after wetting-drying cycles in size, shape, and arrangement. In size, the average diameter of both original loess particles and remoulded loess particles increased with the increasing of initial moisture content. However, the average diameter of original loess particles was slightly larger than that of remoulded loess particles before wetting-drying cycles. In contrast, the average diameter of both original loess particles and remoulded loess particles were very close to each other after three wetting-drying cycles. In shape, before wetting-drying cycles, the average shape factor of original loess particles was higher than that of remoulded loess particles. After three wetting-drying cycles, the difference in the average shape factor of both two loess samples with 5% initial moisture content is similar to that before wettingdrying cycles. Nevertheless, the average shape factor of both original loess particles and remouled loess particles with 15% initial moisture content were very close to that with 25% initial moisture content. in the arrangement, directional frequency indicated remoulded loess appeared to be more vertically aligned than original before and after three wetting-drying cycles. Furthermore, the directed anisotropy rate of remoulded loess was higher than that of the original loess before and after three wetting-drying cycles. In summary, the size, shape, and arrangement of both original loess particles and remoulded loess particles varied in different degrees before and after three wetting-drying cycles. Combined with the water retention curve of the loess, we analyzed the microstructural evolution mechanism of two loess particles during wetting-drying cycles. It is an excellent significance to study the engineering properties of original loess and remoulded loess. As widespread continental sediment, loess covers about 10% of the total land area of the world. At the same time, China exhibits the most extensive distribution in the loess region of the world, especially for Chinese loess plateau, with a total area of about 640,000 km 2. In China, loess deposits account for more than 6% of the territory and are mainly distributed in the regions of Shanxi, Shaanxi, Gansu, and Ningxia 1. Shallow loess (Q 3 loess) in the Loess Plateau over northwestern china is typical aeolian loess, which is mainly composed of coarse powders, including a fraction of clay minerals, soluble salts, and CaCO 3. Therefore, loess soil has a metastable structure with aggregates and bracket macropores 2,3. The main engineering-geological problem of this loess is significantly reduced strength and large collapsing deformation under wet stress path and external load.