For decades, the cooling method of conventional superconducting magnets has been "pool-boiling" in liquid cryogen. The commercial availability of HTS superconductors with an operating temperature in the 20 K region however calls for a new cooling strategy due to cost and availability of the new coolants involved. In this paper an alternative to the traditional bath-cooling of magnets with liquid helium is presented by employing a network of dedicated cooling tube structures capable of satisfying the different operating conditions of the magnet as well as the conductor stability requirements. The proposed closed-loop cooling tube concept based on the thermosiphon principle without loss of coolants and minimizing the coolant inventory while at the same time requiring no operator intervention has been tested. The design and the test results are discussed.
To compensate for the seasonal imbalance between livestock and forage yield in the cold region of Northeast China, alfalfa (Medicago sativa L.) continuous cropping has been widely employed in animal husbandry. However, the effects of continuous cropping of alfalfa on soil properties, including physical, chemical and biological properties, are poorly understood. In this study, we investigated the soil properties and fungal community composition of alfalfa fields under continuous cropping for different time periods (i.e., 1, 2, 6, 9, 12, 13 and 35 years). The results showed that soil moisture, total C, total N, NO3--N and available K content decreased at less than 10 years of continuous cropping and then increased at more than 10 years of continuous cropping, but soil total P and available P content showed the opposite tendency. The soil fungal community composition determined using Illumina Miseq sequencing showed that continuous cropping increased the fungal alpha diversity and changed the fungal community structure. The relative abundances of Guehomyces and Chaetomium decreased, but the relative abundances of Phaeomycocentrospora and Paecilomyces increased with continuous cropping time. In addition, continuous cropping of alfalfa increased the relative abundances of some plant pathogens, such as Haematonectria haematococca and Cyphellophora sp. Soil total P and available P content were important soil factors affecting the soil fungal community diversity, fungal community structure and the relative abundances of specific fungi in this alfalfa continuous cropping system.
Abstract This paper aims to design a speed controller for PMSM so that the motor can track the given speed signal. Based on vector control strategy, united with SVPWM (Space Vector Pulse Width Modulation) technology, an on-off of inverter switches was regularly controlled to form the vector voltage to drive PMSM. Finally, the PMSM double closed-loop vector control system was built. Specifically, by the design of the speed controller method, a fuzzy PID control, according to the variable universe, was proposed to realize the high precision control requirements of the PMSM speed control system. Firstly, on the ground of the traditional PID controller, a fuzzy controller was introduced to realize the self-tuning of control parameters, and then a new function variable domain module was built to reach the self-adjustment of the fuzzy controller domain and to achieve self-tuning of control rules, improving control accuracy and response speed.
Generative artificial intelligence (GAI) and digital twin (DT) are advanced data processing and virtualization technologies to revolutionize communication networks. Thanks to the powerful data processing capabilities of GAI, integrating it into DT is a potential approach to construct an intelligent holistic virtualized network for better network management performance. To this end, we propose a GAI-driven DT (GDT) network architecture to enable intelligent closed-loop network management. In the architecture, various GAI models can empower DT status emulation, feature abstraction, and network decision-making. The interaction between GAI-based and model-based data processing can facilitate intelligent external and internal closed-loop network management. To further enhance network management performance, three potential approaches are proposed, i.e., model light-weighting, adaptive model selection, and data-model-driven network management. We present a case study pertaining to data-model-driven network management for the GDT network, followed by some open research issues.
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