• Title/Summary/Keyword: $\hat{J}$ Integral

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Design Study of Adhesively Bonded Structures

  • Chung, Jae-Ung
    • Korean Journal of Computational Design and Engineering
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    • v.14 no.2
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    • pp.122-128
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    • 2009
  • The failure responses of adhesively bonded, hat stiffened structures are studied through numerical analysis using the finite element method. The responses are evaluated numerically for the bonded hat section/substrate structures containing different combinations of materials. It is studied what kind of material combinations causes the easier crack initiation in the structure. This study is conducted under plane strain conditions and J-integral via a commercial code ABAQUS as a total critical energy release criterion was used for observation on crack initiation. Also, the influence of adhesive on the structure is studied.

A Study on the Estimation of Dynamic Interlaminar Fracture Toughness on CFRP Laminates Plates (CFRP 적층판의 동적 층간파괴인성의 평가법)

  • 김지훈;김영남;판부직규;양인영
    • Transactions of the Korean Society of Automotive Engineers
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    • v.6 no.2
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    • pp.80-91
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    • 1998
  • In this paper, the estimation of dynamic interlaminar fracture toughness on fracture mode II in CFRP(carbon fiber reinforced plastics) laminates in made. Dynamic ENF(End Notched Flexure) apparatus used in this paper is manufactured by suing Split Hopkinson Pressure Bar. The static and impact load history in the CFRP specimen is measured by using manufactured dynamic ENF tester and 3-point bending test is carried out to find the load history. Also dynamic interlaminar fracture toughness can be found by using the J integral obrained from dynamic analysis in consideration of intertia-force effect.

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A Study on Best Generation Mix using Sensitivity Analysis of Fuzzy Multi Attribute Decision Making (퍼지 다속성 의사결정문제의 감도해석을 이용한 최적전원구성에 관한 연구)

  • Song, K.Y.;Cha, J.M.;Kim, Y.H.
    • Proceedings of the KIEE Conference
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    • 1993.07a
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    • pp.177-179
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    • 1993
  • Best generation mix belongs to a multi attribute decision making, because we should consider many uncertain factors and choose the best one of the alternatives. Sugeno's fuzzy integral has been used as the solution of multi attribute decision making, but the exact value of the coefficient $\lambda$ hat not known yet which is needed to calculate fuzzy measure. This paper proposes the new method to calculate fuzzy measure without fixing the value of $\lambda$. The proposed method considers $\lambda$ as a probability distribution function and calculated expectation of fuzzy measure. The method is applied to the test system and the validity of the method is verified.

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