Optimization of Inertia Friction Welding of Dissimilar Polymeric PA6-PVC Hollow Cylinders by Genetic Algorithm | ||||
| Port-Said Engineering Research Journal | ||||
| Article 11, Volume 25, Issue 1, March 2021, Page 91-100 PDF (939.89 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/pserj.2020.33683.1048 | ||||
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| Authors | ||||
Samar Elsanabary   ; Hanan Kamel Kouta
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| Department of production engineering and mechanical design, Faculty of Engineering, Port Said University, Port Said, Egypt | ||||
| Abstract | ||||
| Three-dimensional elasto-plastic thermal-mechanical transient axisymmetric explicit finite element models were used to simulate the friction joining of hollow cylinder dissimilar polymeric materials PA6-PVC. The FE model takes into account the mechanical and thermal properties of PA6 and PVC as an input date. Also, the simulation analysis considered three independent variables namely, rotational speed of (500, 775, and 1200 rpm), axial displacement of (0.045, 0.09, and 0.18 mm), and total welding time of (4, 6, and 8 seconds). With respect to the FE model, the regression model is built. The minimum and maximum error percentage between FE and predicted results by regression model of welding temperature are 0.08% and 17.26% respectively. On the other hand, the error percentages of Von Mises residual stress start from 0.34% to 26.15%. The regression model is used to formulate the GA's fitness function for end welding temperature and Von Mises residual stresses. This paper showed that the GA technique is capable of estimating the optimum welding conditions that yield the value of the minimum end welding temperature and the Von Mises residual stresses relative to the results of FE and regression. | ||||
| Keywords | ||||
| Inertia friction welding; Thermoplastics; Numerical Simulation; Regression model; Genetic Algorithm | ||||
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