• Title/Summary/Keyword: CAE 시뮬레이션

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Light-Weight Design of Automotive Torque Strut Based on Computer Aided Engineering (컴퓨터 시뮬레이션을 이용한 자동차용 Torque Strut의 경량 설계)

  • Kim, Kee Joo
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.41 no.10
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    • pp.975-981
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    • 2017
  • Savings in weight using lightweight materials such as aluminum alloy can lead to increase fuel economy. However, compared to steel, aluminum alloys have a lower strength for an equivalent life cycle. To reduce the weight of automobiles, research is being performed on the fabrication of lighter and stronger torque struts without having to sacrifice the safety of automotive components. In this study, a weight reduction design process for torque struts is proposed that is based on varying von-Mises stress contours using an aluminum alloy (A356) having a tensile strength of 245 MPa, instead of STKM11A steels. The optimized design can reduce the weight of the original steel torque strut by over 42% and it can contribute to the design of light-weight components and to the safe design of torque struts.

False Data Reduction Strategy for P2P Environment (P2P 환경을 위한 허위 데이터 감축 정책)

  • Kim, Seung-Yun;Lee, Won-Joo;Jeon, Chang-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.5
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    • pp.93-100
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    • 2011
  • In this paper, we propose a FDR(False Data Reduction) strategy for P2P environment that reduces false data. The key idea of our strategy is that we use FDR algorithm to stop transmitting of false data and to delete that. If a user recognizes false data in downloaded-data and the user's peer requests the others to stop the transmission of the false data immediately. Also, the FDR algorithm notifies the other peers to prohibit spreading of the false data in the environment. All this procedure is possible to be executed in each peer without any lookup server. The FDR algorithm needs only a little data exchange among peers. Through simulation, we show that it is more effective to reduce the network traffic than the previous P2P strategy. We also show that the proposed strategy improves the performance of network compared to previous P2P strategy. As a result, The FDR strategy is decreased 9.78 ~ 16.84% of mean true data transmission time.

The study of a Vehicle Dynamic Simulation Including Powertrain About the Coordinate System Connectivity (좌표계 연성에 의한 동력전달계 포함 차량 운동 시뮬레이션 연구)

  • Jung Il Ho;Yang Hong Ik;Yoon Ji Won;Park Tae Won;Han Hyung Suk
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.5 s.170
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    • pp.130-137
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    • 2005
  • Recently, the importance of CAE research is growing with the advances of the automotive and computer industry. In addition, multi-body dynamics and powertrain analysis are the most important factors in improving the vehicle design. Since engine torque with curve-data was used for analyzing full car simulation in the multi-body dynamics system for many years, it is impossible to assess the concurrent analysis of the engine and powertrain element included in a real full car system. In powertrain, since vehicle are usually modeled as a simple mass and a inertia, they can not be seen as real cars. Moreover, it is hard to obtain additional dynamics data other than the longitudinal velocity value in movement. Because of the reason that was previously discussed, it is necessary to consolidate the two parts as one routine program for design and development through the coordinate system connectivity, and presented here is a program named O-DYN. Using an object-oriented language C++, this program has a good structure with the valuable characteristics of objectivity, inheritance, and reusability. The reliability of this multi-body dynamics program is examined by DADS, which is the general dynamics program, using DAE solver and PECE integral function with the common coordinator separation method. As a result, we can obtain a better solution and total dynamics data in either area through this process. This program will be useful for analyzing full car simulation with powertrain.