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It is expected that fusion energy development, which is at a critical stage of breaking through energy break-even in the engineering sense, has the potential to reshape the future pattern of energy development with both opportunities and challenges. This study reviews the main progress of fusion energy research and summarizes the major challenges regarding energy balance, tritium selfsustainability, high availability, development of irradiation-resistant materials, and economical efficiency in general sense. On the basis of sorting out the common basic technology breakthroughs of the International Thermonuclear Experimental Reactor (ITER) program and the supporting research activities of its member states, the study summarizes the progress of China’s magnetic confinement fusion research in terms of overall planning, self-developed projects, and technical tracking. Furthermore, focusing on the Z-pinch-driven fusion-fission hybrid reactor (Z-FFR) concept, which is independently proposed by China, this study elaborates on the basic principles, application advantages, and series of progresses, and proposes a development plan toward commercial energy supply by 2040, covering the task objectives in the stages of key technology campaign, engineering demonstration, and promotion of commercial power generation. To comprehensively promote China’s fusion energy development, several suggestions are given. In the magnetic confinement fusion area, it is suggest that China deeply participate in the ITER program and relevant international cooperation, overcome key physics and engineering technologies of commercial fusion reactors, promote the research and development of key components of China Fusion Engineering Test Reactor (CFETR) device, and construct and operate CFETR in due course. In the Z-FFR area, it is of first priority to start the construction of electromagnetic-driven large-scale scientific devices the soonest possible, develop key technologies for fusion energy, and promote both engineering demonstrations and commercial projects in proper time.

The informatization and intelligence of wind farm lock and key management is the key to further improve the level of wind farm operation and maintenance management. This paper designs a smart key security management and control architecture for wind farms. Combined with the proposed short-range wireless communication anti-jamming technology, key encryption, and dynamic attack detection technology, a set of wind farm smart key security management and control system has been developed. The system can realize the functions of opening and closing information traceability and risk prevention, etc., which improves the network, digital and intelligent level of wind farm operation and maintenance.

The properties of the failure shots on an induction voltage adder are described. This induction voltage adder is composed of six identical prime pulsed power sources, six induction cavities, and a lossless vacuum insulation output transmission line which is terminated by a rod-pinch diode. The failure modes include too early and too late firing of the laser-triggered gas switch in the prime pulsed power sources and abnormal diode impedance declining. The amplitudes of the voltage pulses across the feed port and azimuthal transmission line of the induction cavity are increased by 38% and 48%, respectively, in the event that this cell is driven too early. On the contrary, a reverse voltage pulse will be produced at the induction cavity when it is fired too late. The peak value of the reverse voltage pulse is about 50% of that of the normal polarity pulse. The abnormal rod-pinch diode impedance declining taking place occasionally decreases the load voltage and x-ray dose remarkably. However, the average amplitude of the voltage pulses across the six induction cavities is almost the same as that of a normal shot. We have also analyzed the property of the voltage pulses across the induction cell under the circumstance that only one induction cavity is fired. Both the experimental and circuit simulation data suggest that in this case the voltage pulses on the induction cell are nearly identical even though the load impedance varies vastly.

The design and test results of a pulsed power-driven X-ray source which is named Hawkeye-I are described. The Hawkeye-I is developed to execute flash X-ray radiography. It is a six-stage induction voltage adder and terminated by a positive polarity rod-pinch diode. The six stages are identical and the prime energy of each stage is provided by a tesla transformer elevating the output voltage from a discharge brick which consists of two 4 μF capacitors and a three-electrode gas switch. Comparing to the induction voltage adders driven by Marx generators, the numbers of gas switches and capacitors in the energy storage sections of Hawkeye-I decrease significantly. The Hawkeye-I can produce a maximum output voltage of about 4.2 MV. The corresponding X-ray source spot size and dose at 1 m are 1.4 mm and 17.9 rad, respectively. Fifty consecutive shots have been conducted to evaluate the reliability of the machine and 98% of the shots are successful. Furthermore, as the energy propagating in the accelerator is mainly determined by seven laser-triggered gas switches, the Hawkeye-I is capable of controlling the timing of the X-ray pulse accurately.

Aerial scene classification, which aims to automatically label an aerial image with a specific semantic category, is one of the most challenging tasks in computer vision. With the improvement of spatial resolution of aerial images, the texture details of ground objects become increasingly abundant. Although many classification algorithms have been proposed in recent years, accuracy and completeness of the classification results are still imperative problems to be solved. We propose an algorithm via a two-stage voting fusion strategy. First, the superpixels obtained by simple linear iterative cluster algorithm are treated as the input of a random forest classifier. Then, the region growth strategy is applied to complete the clustering of similar local regions, and the learning of mosaic zero pieces is simultaneously realized. Finally, a Bayesian framework is exploited to fuse the classification results in order to get the final classification results. Experiments on two benchmarks demonstrate the superiority of the proposed method (TSS) compared with other state-of-the-art methods, whether in terms of the integrity of big targets or the accuracy of small objects. [ABSTRACT FROM AUTHOR]