SYNOPSISAnalysis of the injection-molding process based on Leonov viscoelastic fluid model has been employed to study the effects of process conditions on the residual stress and birefringence development in injection-molded parts during the entire molding process. An integrated formulation was derived and numerically implemented to solve the nonisothermal, compressible, and viscoelastic nature of polymer melt flow. Simulations under process conditions of different melt temperatures, mold temperatures, filling speeds, and packing pressures are performed to predict the birefringence variation in both gapwise and planar direction. It has been found that melt temperature and the associated frozen layer thickness are the dominant factors that determine the birefringence development within the molded part. For a higher mold temperature, melt temperature, and injection speed, the averaged birefringence along gapwise direction is lower. The birefringence also increases significantly with the increased packing pressure especially along gate area. The simulated results show good consistency with those measured experimentally.
The birefringence of injection molded parts was measured using a digital photoelasticity system, which combines a digital image analysis technique and the half‐fringe photoelasticity (HFP) method The effects of processing conditions, including melt temperature, mold temperature, filling time and packing pressure, on the birefringence development in the molded parts were investigated. It was found that temperature and pressure are the two dominant factors that determine the birefringence development in the parts during the molding process. Frozen‐in birefringence of the molded parts decreases with increasing melt temperature, mold temperature and injection speed. Birefringence of the parts also increases with increased packing pressure, especially around the gate area. Numerical simulations using the Leonov viscoelastic fluid model predict similar dependence of birefringence of parts on processing conditions. Simulated results are also consistent with measured values.
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