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- W4382893992 abstract "In this paper friction stir welding process has been studied whereby utilized FEM method (Ansys software ver. 20). The main effective parameter in this process were rotational speed, linear speed, tool shoulder radius, heat transfer coefficient and clamping percentage to study their influence on represent temperature, von misses stress and frictional stress distribution. Because of the difficulty to obtained the number of the simulation cases in order to get the most important results, Taguchi L27 orthogonal array was apply to reduce the total number of the simulation cases. Pure copper (t = 3.18 mm) material type was applied as work plate material. ANOVA statistical tool was utilized to achieved the optimization process after the simulation cases done. Percentage of contribution of each parameter can be obtained by ANOVA table and mean of S/N ratio plot. Validation process was achieved between the Current study and experiment work in the temperature distribution field with percentage of error 2.7 %. From optimization result It is found that the optimum condition in order to obtained good results for temperature was rotational speed of (450 rpm), linear speed (2.75 mm/s), tool shoulder radius (7 mm), heat transfer coefficient (300 w/m2 K), clamping distance percentage (40 %). And for von misses stress was rotational speed of (550 rpm), linear speed (3 mm/s), tool shoulder radius (7 mm), heat transfer coefficient (300 w/m2 K), clamping distance percentage (20 %). While for frictional stress was rotational speed of (450 rpm), linear speed (2.5 mm/s), tool shoulder radius (7 mm), heat transfer coefficient (300 w/m2 K), clamping distance percentage (30 %)." @default.
- W4382893992 created "2023-07-03" @default.
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- W4382893992 date "2023-07-02" @default.
- W4382893992 modified "2023-09-27" @default.
- W4382893992 title "Numerical Simulation and Optimization of Friction Stir Welding Parameters" @default.
- W4382893992 doi "https://doi.org/10.33971/bjes.23.1.10" @default.
- W4382893992 hasPublicationYear "2023" @default.
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