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Genetic Algorithm-Based Optimization of Curved-Tube Nozzle Parameters for Rotating Spinning
Wenhui Li1, Kang Liu2, Qinghua Guo2
1Hubei Digital Textile Equipment Key Laboratory, Wuhan Textile University, Wuhan, China.
Frontiers in Bioengineering and Biotechnology
|December 20, 2021
Summary
This study optimizes curved-tube nozzle design using a genetic algorithm, finding optimal parameters for maximum outlet power. The enhanced design improves flow distribution and reduces jet instability for high-quality nanofiber production.
Area of Science:
- Fluid dynamics
- Materials science
- Computational engineering
Background:
- Nozzle design is critical for processes like nanofiber production.
- Optimizing curved-tube nozzles requires understanding complex structure-performance relationships.
- Existing designs may suffer from suboptimal flow fields and jet instability.
Purpose of the Study:
- To develop an optimization paradigm for curved-tube nozzle structure design.
- To identify optimal nozzle parameters for maximizing outlet power.
- To validate the performance improvements of the optimized nozzle.
Main Methods:
- Mathematical modeling to establish relationships between nozzle parameters and outlet power.
- Application of genetic algorithms to simulate natural evolution and selection for optimization.
- Comparison of optimized designs with simulations and experimental rotating spinning.
Main Results:
- A mathematical model was established linking nozzle structure to outlet power.
- Genetic algorithms successfully optimized the curved-tube nozzle.
- Optimal parameters identified: 10.8° bending angle, 0.5 mm diameter, 8 mm curvature radius for maximum outlet power.
Conclusions:
- Optimized curved-tube nozzles enhance flow field distribution.
- The optimized design effectively reduces jet instability.
- Improved flow and stability are crucial for high-quality nanofiber fabrication.
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