Steel and Composite Structures

  • 제15권4호
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  • Pages.451-466
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  • 2013
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  • 1229-9367(pISSN)
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  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Generalized evolutionary optimum design of fiber-reinforced tire belt structure

  • Cho, J.R. (School of Mechanical Engineering, Pusan National University) ;
  • Lee, J.H. (School of Mechanical Engineering, Pusan National University) ;
  • Kim, K.W. (R&D Center of Kumho Tire Co. Ltd.) ;
  • Lee, S.B. (School of Mechanical Engineering, Pusan National University)
  • 투고 : 2012.11.04
  • 심사 : 2013.10.01
  • 발행 : 2013.10.25
⟨ 이전 논문 다음 논문 ⟩

초록

This paper deals with the multi-objective optimization of tire reinforcement structures such as the tread belt and the carcass path. The multi-objective functions are defined in terms of the discrete-type design variables and approximated by artificial neutral network, and the sensitivity analyses of these functions are replaced with the iterative genetic evolution. The multi-objective optimization algorithm introduced in this paper is not only highly CPU-time-efficient but it can also be applicable to other multi-objective optimization problems in which the objective function, the design variables and the constraints are not continuous but discrete. Through the illustrative numerical experiments, the fiber-reinforced tire belt structure is optimally tailored. The proposed multi-objective optimization algorithm is not limited to the tire reinforcement structure, but it can be applicable to the generalized multi-objective structural optimization problems in various engineering applications.

키워드

참고문헌

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피인용 문헌

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  2. Failure estimation of the composite laminates using machine learning techniques vol.25, pp.6, 2013, https://doi.org/10.12989/scs.2017.25.6.663