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ObjectivesIn order to support the testing requirements of the international thermonuclear experimental reactor AC/DC converter system and apply to high-precision control standards for future fusion magnet power supplies, a real-time control system suitable for high-power DC test platforms was developed.MethodsChoosing the QNX real-time operating system as the core platform and combining it with reflective memory technology provided by GE company in the United States, a network architecture for real-time high-speed data exchange was built. The system was designed with multiple operation modes to cope with different testing scenarios, while implementing different levels of safety interlocking mechanisms to ensure equipment safety. This system possessed the capabilities of setting converter operating parameters, fault identification, equipment status monitoring, and millisecond-level real-time control and safety protection functions.ResultsExperimental validation has demonstrated the system’s stability and reliability in high-power environments, achieving precise control of 120 kA steady-state current and 500 kA pulse current. Furthermore, the system not only meets the basic requirements of real-time control but also ensures safe interlocking and continuous stable operation of the equipment during multi-mode operation.ConclusionsThe designed real-time control system for the high-power DC test platform achieves efficient multi-module synchronous management and fully complies with strict millisecond-level control cycle requirements.

Purpose - As main mode of modern service industry and future economy society, the research on crowd network can greatly facilitate governances of economy society and make it more efficient, humane, sustainable and at the same time avoid disorders. However, because most results cannot be observed in real world, the research of crowd network cannot follow a traditional way. Simulation is the main means to put forward related research studies. Compared with other large-scale interactive simulations, simulation for crowd network has challenges of dynamic, diversification and massive participants. Fortunately, known as the most famous and widely accepted standard, high level architecture (HLA) has been widely used in large-scale simulations. But when it comes to crowd network, HLA has shortcomings like fixed federation, limited scale and agreement outside the software system. Design/methodology/approach - This paper proposes a novel reflective memory-based framework for crowd network simulations. The proposed framework adopts a two-level federation-based architecture, which separates simulation-related environments into physical and logical aspect to enhance the flexibility of simulations. Simulation definition is introduced in this architecture to resolve the problem of outside agreements and share resources pool (constructed by reflective memory) is used to address the systemic emergence and scale problem. Findings - With reference to HLA, this paper proposes a novel reflective memory-based framework toward crowd network simulations. The proposed framework adopts a two-level federation-based architecture, system-level simulation (system federation) and application-level simulation (application federations), which separates simulation-related environments into physical and logical aspect to enhance the flexibility of simulations. Simulation definition is introduced in this architecture to resolve the problem of outside agreements and share resources pool (constructed by reflective memory) is used to address the systemic emergence and scale problem. Originality/value - Simulation syntax and semantic are all settled under this framework by templates, especially interface templates, as simulations are separated by two-level federations, physical and logical simulation environment are considered separately; the definition of simulation execution is flexible. When developing new simulations, recompile is not necessary, which can acquire much more reusability, because reflective memory is adopted as share memory within given simulation execution in this framework; population can be perceived by all federates, which greatly enhances the scalability of this kind of simulations; communication efficiency and capability has greatly improved by this share memory-based framework.