Steel and Composite Structures

  • 제41권2호
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  • Pages.279-292
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  • 2021
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  • 1229-9367(pISSN)
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  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

A strain-rate-dependent analytical model for composite bolted joints

  • Shamaei-Kashani, Alireza (Department of Mechanical Engineering, Composites Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, Iran University of Science and Technology) ;
  • Shokrieh, Mahmood M. (Department of Mechanical Engineering, Composites Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, Iran University of Science and Technology)
  • 투고 : 2020.10.28
  • 심사 : 2021.09.15
  • 발행 : 2021.10.25
⟨ 이전 논문 다음 논문 ⟩

초록

In the present research, a novel analytical approach was developed to predict the bearing chord stiffness and the damage initiation bearing-load of single-lap composite bolted joints under medium strain rate loading. First, the elastic moduli, Poisson's ratio, and strength of a unidirectional composite ply at an arbitrary strain rate were predicted by available micromechanical equations. Then, the bearing chord stiffness of the joint at any arbitrary strain rate was predicted. For this purpose, the available spring-based model was modified. The strain-rate-dependent damage initiation bearing-load of the joint was predicted by using the moduli and the stress concentration factor of a pin-loaded unidirectional ply. Four types of single-lap joints with [-45/0/+45/90]s and [90/-452/+45]s layups with and without carbon nanofibers were tested at the strain rates of 0.0048 s-1, 0.36 s-1, and 0.89 s-1. The results of experiments showed that mechanical properties of single-lap composite bolted joints increased with increasing the strain rate. Also, employing carbon nanofibers has a significant effect on the mechanical properties of the joints. The predicted results in comparison with the conducted experimental data show good agreements.

키워드

과제정보

The authors would like to thank the financial support of the Iran National Science Foundation (INSF), Grants No. 96000574, and 97024007.

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