DOI QR코드

DOI QR Code

Determination of optimal parameters for perforated plates with quasi-triangular cutout by PSO

  • Jafari, Mohammad (Department of Mechanical Engineering, Shahrood University of Technology) ;
  • Hoseyni, Seyed A. Mahmodzade (Department of Mechanical Engineering, Shahrood University of Technology) ;
  • Chaleshtari, Mohammad H. Bayati (Department of Mechanical Engineering, Shahrood University of Technology)
  • 투고 : 2016.02.07
  • 심사 : 2016.09.21
  • 발행 : 2016.12.10

초록

This study tries to examine the effect of different parameters on stress analysis of infinite plates with central quasi-triangular cutout using particle swarm optimization (PSO) algorithm and also an attempt has been made to introduce general optimum parameters in order to achieve the minimum amount of stress concentration around this type of cutout on isotropic and orthotropic plates. Basis of the presented method is expansion of analytical method conducted by Lekhnitskii for circular and elliptical cutouts. Design variables in this study include fiber angle, load angle, curvature radius of the corner of the cutout, rotation angle of the cutout and at last material of the plate. Also, diagrams of convergence and duration time of the desired problem are compared with Simulated Annealing algorithm. Conducted comparison is indicative of appropriateness of this method in optimization of the plates. Finite element numerical solution is employed to examine the results of present analytical solution. Overlap of the results of the two methods confirms the validity of the presented solution. Results show that by selecting the aforementioned parameters properly, less amounts of stress can be achieved around the cutout leading to an increase in load-bearing capacity of the structure.

키워드

참고문헌

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피인용 문헌

  1. Optimization of finite plates with polygonal cutout under in-plane loading by gray wolf optimizer vol.52, pp.6, 2017, https://doi.org/10.1177/0309324717716270
  2. Optimized design for perforated plates with quasi-square hole by grey wolf optimizer vol.63, pp.3, 2017, https://doi.org/10.12989/sem.2017.63.3.269