Genetic Algorithm-Based Optimization of Curved-Tube Nozzle Parameters for Rotating Spinning - Li, Wenhui; Liu, Kang; Guo, Qinghua; Zhang, Zhiming; Ji, Qiaoling; Wu, Zijun (Frontiers in Bioengineering and Biotechnology, 2021)
In rotating spinning process, a proper combination of curved-tube nozzle structure parameters can effectively counteract flow field in-homogeneity as well as jet fluctuation phenomena. An optimization paradigm of nozzle structure is proposed for structure parameters design via genetic algorithm. Firstly, the mathematical model is established to reveal the functional relationship between outlet power and the nozzle structure parameters for nozzle. Secondly, genetic algorithms transform the optimization process of curved-tube nozzle structural into natural evolution and selection. It is found that curved-tube nozzle with bending angle of 10.8 °, nozzle diameters of 0.5 and curvature radius of 8, yield maximum outlet power. Finally, we compare the optimal result with simulations and experiments of the rotating spinning. It is found that optimized curved-tube nozzle can improve flow field distribution and reduce the jet instability, which is critical to obtain high-quality nano-fibers.