• Title/Summary/Keyword: Modal Stress Recovery

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Analysis of Durability of Torsion Beam Axle Using Modal Stress Recovery Method (모달 응력 회복법(Modal Stress Recovery)을 이용한 Torsion Beam Axle 내구해석)

  • Ko, Jun-Bok;Lim, Young-Hoon;Lee, Dong-Cheol
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.34 no.10
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    • pp.1339-1344
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    • 2010
  • MSM (Modal Superposition Method) is a technique for analyzing structural durability by taking the vibration characteristics into consideration. In this paper, MSR (Modal Stress Recovery) method, which is similar to MSM, was reviewed to check its validity as a durability analysis method. The MSR method directly calculates the modal displacement time history in multibody dynamics analysis; as a result, the total analysis time is shorter than that of MSM method. We conduct durability analysis using the MSR method and a durability test of a torsion beam axle that is affected by various road loads within the natural frequency of the beam axle. The analysis results for critical location and durability were in good agreement with the respective test results. Therefore, durability analysis using the MSR method is effective in predicting the durability of the structures of various dynamic systems.

FATIGUE LIFE PREDICTION OF THE PARTS USED IN THE SUSPENSION SYSTEM FOR TRUCKS (화물차량용 현가계 부품의 피로 수명 예측)

  • Jun, Kab-Jin;Park, Tae-Won;Lee, Su-Ho;Yoon, Ji-Won;Kwon, Soon-Ki
    • Proceedings of the KSME Conference
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    • 2007.05a
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    • pp.1051-1056
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    • 2007
  • The air suspension system is widely used in commercial vehicles such as buses or special purpose trucks because it improves ride better than any other types of suspension. Since the durability of vehicle parts is directly related to the safety, the evaluation of the durability at the design stage is necessary. In this research, the fatigue life of the air suspension frame for trucks is predicted by the modal stress recovery(MSR) method. Using the process proposed in this research, the fatigue life of vehicle parts can be predicted efficiently at the design stage.

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