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Research on the Ejection Gas Generator to Improve Ejecting Performance (사출성능 개선을 위한 사출용 가스발생기 연구)

  • Oh, Seok-Jin;Jang, Seung-Gyo;Cha, Hong-Seok
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.41 no.5
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    • pp.383-390
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    • 2013
  • The reduction of the maximum acceleration which causes shock for a missile is very important to prevent abnormal operation of a missile and decrease size and cost of missile components. Because the maximum acceleration created by operation of an ejection gas generator occurs in the initial ejection stage, the design parameters which affect initial ejection stage were examined. The igniter and the nozzle closure were selected as design parameters of a gas generator. The maximum acceleration created by the gas generator was examined experimentally by changing of the design parameters. Finally the reduction effect of the maximum acceleration was compared quantitatively by static fire test of a gas generator. The maximum acceleration of the best model which was applied to each optimal design parameter was about 68% reduced than that of the reference model.

Edge Computing-based Differential Positioning Method for BeiDou Navigation Satellite System

  • Wang, Lina;Li, Linlin;Qiu, Rui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.69-85
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    • 2019
  • BeiDou navigation satellite system (BDS) is one of the four main types of global navigation satellite systems. The current system has been widely used by the military and by the aerospace, transportation, and marine fields, among others. However, challenges still remain in the BeiDou system, which requires rapid responses for delay-sensitive devices. A differential positioning algorithm called the data center-based differential positioning (DCDP) method is widely used to avoid the influence of errors. In this method, the positioning information of multiple base stations is uploaded to the data center, and the positioning errors are calculated uniformly by the data center based on the minimum variance or a weighted average algorithm. However, the DCDP method has high delay and overload risk. To solve these problems, this paper introduces edge computing to relieve pressure on the data center. Instead of transmitting the positioning information to the data center, a novel method called edge computing-based differential positioning (ECDP) chooses the nearest reference station to perform edge computing and transmits the difference value to the mobile receiver directly. Simulation results and experiments demonstrate that the performance of the ECDP outperforms that of the DCDP method. The delay of the ECDP method is about 500ms less than that of the DCDP method. Moreover, in the range of allowable burst error, the median of the positioning accuracy of the ECDP method is 0.7923m while that of the DCDP method is 0.8028m.

Analysis and Modeling of Traffic at Ntopia Subscriber Network of Korea Telecom (KT의 Ntopia가입자 망 트래픽 분석 및 모델링)

  • 주성돈;이채우
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.41 no.5
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    • pp.37-45
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    • 2004
  • As Internet technologies are mature, many new applications that are different characteristics are emerging. Recently we see wide use of P2P(Peer to Peer) applications of which traffic shows different statistical characteristics compared with traditional application such as web(HTTP) and FTP(File Transfer Protocol). In this paper, we measured subscriber network of KT(Korea Telecom) to analyze P2P traffic characteristics. We show flow characteristics of measured traffic. We also estimate Hurst parameter of P2P traffic and compare self-similarity with web traffic. Analysis results indicate that P2P traffic is much bustier than web traffic and makes both upstream traffic and downstream traffic be symmetric. To predict parameters related QoS such as packet loss and delays we model P2P traffic using two self-similar traffic models and predict both loss probability and mm delay then compare their accuracies. With simulation we show that the self-similar traffic models we derive predict the performance of P2P traffic accurately and thus when we design a network or evaluate its performance, we can use the P2P traffic model as reference input traffic.