Supercritical carbon dioxide as a new working medium for pneumatic launch: A theoretical study

Compared with the conventionally gaseous or liquid working media, the specific internal energy of supercritical carbon dioxide (SCD) is higher at the same temperature and pressure, and the critical temperature of carbon dioxide is close to room temperature, making SCD a potential new working medium for pneumatic launch. To analyze the feasibility of this conception, an analytical model of a pneumatic catapult is established on basis of the conservations of mass and energy. The model consists of a high-pressure chamber and a low-pressure chamber connected by multiple valves, and there is a movable piston in the low-pressure chamber that can push an aircraft to accelerate. The effects of the launch readiness state of SCD in the high-pressure chamber, the initial volume of the low-pressure chamber and the valve control on the movement of the aircraft are analyzed. It is found that there is a restrictive relation between the temperature and pressure of the launch readiness state of SCD, i.e., there is a maximum allowable launch readiness pressure when the launch readiness temperature is fixed. If this restrictive relation is not satisfied, the working medium in the low-pressure chamber will drop to its triple point within a few milliseconds, leading to a launch failure. Owing to this restrictive relation, there is an optimal launch readiness state of SCD with the highest working capacity for any allowable launch readiness temperature. The pressure of the low-pressure chamber will decrease significantly as the initial volume increases, leading to a decreased acceleration of the aircraft. The ac-celeration can be controlled below a critical value by a designed sequential blasting technique of multiple valves. The calculated results show that a 500 kg aircraft can be accelerated from 0 to 58 m/s in 0.9 s with 36 kg of carbon dioxide. This research provides a new technique for the controllable cold launch of an aircraft.     

基于AKF的AUV对接回收组合导航研究

针对自主水下机器人(Autonomous Underwater Vehicle,AUV)在回收过程中的组合导航精度问题,提出了一种改进的高斯距离迭代法及改进的自适应卡尔曼滤波算法(Adaptive Kalman Filter,AKF).基于AUV回收对接系统,研究并建立了针对惯导SINS、超短基线USBL、多普勒计程仪DVL和深度计的基于斜距的组合导航模型.通过对SINS/USBL/DVL/深度计组合导航量测信息误差特性分析,设计了改进的基于斜距的SINS/USBL/DVL/深度计组合导航模型;针对该模型突出的滤波发散问题,设计了基于滤波收敛性判据和强跟踪滤波思想改进的AKF滤波算法进行有机融合.仿真结果表明,此研究使实际AUV系统具有更高的滤波精度和可靠性.     

网络舆论智能引导仿真推演模型与系统构建

传统马甲机械发帖的网络舆论引导方式存在智能水平不高、效果不佳的缺点。人工智能的快速发展为网络舆论智能引导奠定了坚实的理论与技术基础。本文突破新闻传播学的思维定式，利用智能体、系统建模与仿真等理论技术，研究网络舆论智能引导，提出“态势感知-仿真推演-舆论引导”的网络舆论智能引导思路，构建网络舆论智能引导仿真推演模型，明确仿真推演工具，进而构建网络舆论智能引导系统，在仿真推演的基础上实施网络舆论引导，从而颠覆传统马甲的机械式发帖引导方式，破解难以在真实网络环境中直接尝试各种引导策略的困局。本文的研究成果对于丰富网络舆论斗争理论，占领网络舆论制高点，具有重要理论意义和参考价值。