Computers and Concrete

  • 제25권4호
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  • Pages.303-310
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  • 2020
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  • 1598-8198(pISSN)
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  • 1598-818X(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Optimal fiber volume fraction prediction of layered composite using frequency constraints- A hybrid FEM approach

  • Anil, K. Lalepalli (National Institute of Technology Rourkela) ;
  • Panda, Subrata K. (National Institute of Technology Rourkela) ;
  • Sharma, Nitin (School of Mechanical Engineering, KIIT) ;
  • Hirwani, Chetan K. (Deparment of Mechanical Engineering, National Institute of Technology Patna) ;
  • Topal, Umut (Department of Civil Engineering, Karadeniz Technical University, Faculty of Technology)
  • 투고 : 2019.07.13
  • 심사 : 2020.03.14
  • 발행 : 2020.04.25
⟨ 이전 논문 다음 논문 ⟩

초록

In this research, a hybrid mathematical model is derived using the higher-order polynomial kinematic model in association with soft computing technique for the prediction of best fiber volume fractions and the minimal mass of the layered composite structure. The optimal values are predicted further by taking the frequency parameter as the constraint and the projected values utilized for the computation of the eigenvalue and deflections. The optimal mass of the total layered composite and the corresponding optimal volume fractions are evaluated using the particle swarm optimization by constraining the arbitrary frequency value as mass/volume minimization functions. The degree of accuracy of the optimal model has been proven through the comparison study with published well-known research data. Further, the predicted values of volume fractions are incurred for the evaluation of the eigenvalue and the deflection data of the composite structure. To obtain the structural responses i.e. vibrational frequency and the central deflections the proposed higher-order polynomial FE model adopted. Finally, a series of numerical experimentations are carried out using the optimal fibre volume fraction for the prediction of the optimal frequencies and deflections including associated structural parameter.

키워드

참고문헌

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