Enhancing Drafter Performance in Spunbonding of Polymeric Fibers via Airflow Simulation

Area of Science:

• Materials Science
• Fluid Dynamics
• Nonwovens Engineering

Background:

• Spunbonding drafters critically influence nonwoven fabric quality.
• Internal airflow in drafters is poorly understood due to accessibility issues and empirical design.

Purpose of the Study:

• To characterize airflow within spunbonding drafters using high-fidelity computational fluid dynamics (CFD).
• To quantify the impact of geometric variables on fiber drawing conditions and nonwoven quality.
• To optimize drafter design for improved fiber attenuation, uniformity, and reduced air demand.

Main Methods:

• Employed high-fidelity computational fluid dynamics (CFD) to simulate airflow inside a laboratory-scale drafter.
• Conducted parametric virtual experimentation across seven geometric variables.
• Utilized a performance-oriented optimization framework targeting shear drag, drawing uniformity, and air demand.
• Implemented and validated CFD-guided design modifications on a prototype.

Main Results:

• Identified a novel
• braking effect
• hindering fiber drawability and increasing breakage.
• Demonstrated that drafter geometry significantly impacts shear distribution, flow uniformity, and energy consumption.
• CFD-guided modifications led to substantial reductions in fiber breakage and enhanced drawing stability for PP and HDPE fibers.

Conclusions:

• Simulation-driven design optimization is effective for improving spunbonding equipment.
• Optimized drafter geometry, informed by CFD, enhances fiber attenuation and nonwoven quality.
• Understanding and controlling internal airflow is key to advancing spunbonding technology.