Optimize Air Flow Field Of The Melt Blowing Slot Die Via Numerical Simulation And Multi-Objective Genetic Algorithm

Dual slot die has been widely applied in the manufacturing of melt blowing fibers. The polymer melt extruded from the die is rapidly attenuated into microfibers by two strands of converged hot air jet ejected from both slots. Studies on both velocity field and temperature filed of dual slot die can help learn the drawing mechanism of melt blowing fibers, and then direct the optimal design and further improve the quality of melt blowing production.Firstly, measurement is carried out to verify numerical simulation. FLUENT 6.3 is adopted to simulate the 3D flow field of dual slot die of which both velocity field and temperature field are then measured by Hot Ware Anemometer. The numerical simulation of 3D flow field of dual slot die is proven to be practical by comparing results of experiments and computation. Furthermore, the comparison also suggests and supports the subsequent parameters optimization of slot die.Secondly, numerical simulation and multi-objective genetic algorithm are combined to optimize structure parameters of melt blowing slot die, in order to obtain the lowest velocity decay and temperature decay in the air flow field. The data of optimization is based on the result of numerical simulation. The objects of optimization are 4 main structure parameters, including slot width, head width, slot angle and setback. The genetic algorithm operation ends at the 50th generation.Finally, multi-objective programming approach is introduced to achieve the optimal result. The results also show that smaller slot angle and bigger slot width can contribute to lower air velocity decay and temperature decay, and that slot width and setback have no significant impact on the decay of velocity and temperature.