• Title/Summary/Keyword: 컴플라이언스 효과

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A Study on the Application of the Steering Control to Increase Roll Stiffness for the Relatively Tall Vehicles (무게중심이 높은 차량의 롤 강성계수 증대를 위한 스티어링 제어기법의 응용에 관한 연구)

  • 소상균;변기식
    • Journal of the Institute of Convergence Signal Processing
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    • v.4 no.2
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    • pp.53-60
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    • 2003
  • For the high center of gravity vehicles the roll stiffness of their suspensions is arranged to be very high because such vehicles are in some danger of tipping over in cornering. In some cases, the effective roll stiffness is determined significantly by the compliance of the tires because of the very stiff anti-roll members incorporated in the suspension. In such cases, it is clear that the shock absorbers which may be effective in damping heave oscillations have little effect on roll oscillations. Therefore, wind gusts and roadway unevenness may cause large swaying oscillations. In this paper, to improve the stability for the high center of gravity vehicles a control scheme to augment the damping of the roll mode is proposed. As the feedback signals needed to provide damping of the roll motion, the front or rear steer angles or both are chosen because they are very related to roll motion. The scheme is effective from moderate to high speeds and stabilizes the roll mode without introducing disturbance moments from roadway unevenness as shock absorbers do. The validity on the proposed method is verified through the computer simulation.

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A study on the selection of the target scope for destruction of personal credit information of customers whose financial transaction effect has ended (금융거래 효과가 종료된 고객의 개인신용정보 파기 대상 범위 선정에 관한 연구)

  • Baek, Song-Yi;Lim, Young-Bin;Lee, Chang-Gil;Chun, Sam-Hyun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.3
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    • pp.163-169
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    • 2022
  • According to the Credit Information Act, in order to protect customer information by relationship of credit information subjects, it is destroyed and stored separately in two stages according to the period after the financial transaction effect is over. However, there is a limitation in that the destruction of personal credit information of customers whose financial transaction effect has expired cannot be collectively destroyed when the transaction has been terminated, depending on the nature of the financial product and transaction. To this end, the IT person in charge is developing a computerized program according to the target and order of destruction by investigating the business relationship by transaction type in advance. In this process, if the identification of the upper relation between tables is unclear, a compliance issue arises in which personal credit information cannot be destroyed or even information that should not be destroyed because it depends on the subjective judgment of the IT person in charge. Therefore, in this paper, we propose a model and algorithm for identifying the referenced table based on SQL executed in the computer program, analyzing the upper relation between tables with the primary key information of the table, and visualizing and objectively selecting the range to be destroyed. presented and implemented.

Functionally Graded Structure Design for Heat Conduction Problems using Machine Learning (머신 러닝을 사용한 열전도 문제에 대한 기능적 등급구조 설계)

  • Moon, Yunho;Kim, Cheolwoong;Park, Soonok;Yoo, Jeonghoon
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.3
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    • pp.159-165
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    • 2021
  • This study introduces a topology optimization method for the simultaneous design of macro-scale structural configuration and unit structure variation to ensure effective heat conduction. Shape changes in the unit structure depending on its location within the macro-scale structure result in micro- as well as macro-scale design and enable better performance than using isotropic unit structures. They result in functionally graded composite structures combining both configurations. The representative volume element (RVE) method is applied to obtain various thermal conductivity properties of the multi-material based unit structure according to its shape change. Based on the RVE analysis results, the material properties of the unit structure having a certain shape can be derived using machine learning. Macro-scale topology optimization is performed using the traditional solid isotropic material with penalization method, while the unit structures composing the macro-structure can have various shapes to improve the heat conduction performance according to the simultaneous optimization process. Numerical examples of the thermal compliance minimization issue are provided to verify the effectiveness of the proposed method.