# Melt-Blowing of Viscoelastic Jets in Turbulent Airflows: Stochastic   Modeling and Simulation

**Authors:** Manuel Wieland, Walter Arne, Nicole Marheineke, Raimund Wegener

arXiv: 1902.01811 · 2019-07-09

## TL;DR

This paper develops a stochastic modeling framework to simulate melt-blowing viscoelastic jets in turbulent airflow, revealing turbulence's crucial role in fiber thinning and producing realistic fiber diameter predictions.

## Contribution

It introduces a novel stochastic aerodynamic force model incorporating turbulence effects into viscoelastic jet simulations, improving accuracy over previous methods.

## Key findings

- Turbulence significantly influences jet thinning.
- Simulated fiber diameters match experimental observations.
- The model enables feasible industrial-scale simulations.

## Abstract

In melt-blowing processes mico- and nanofibers are produced by the extrusion of polymeric jets into a directed, turbulent high-speed airflow. Up to now the physical mechanism for the drastic jet thinning is not fully understood, since in the existing literature the numerically computed/predicted fiber thickness differs several orders of magnitude from those experimentally measured. Recent works suggest that this discrepancy might arise from the neglect of the turbulent aerodynamic fluctuations in the simulations. In this paper we confirm this suggestion numerically. Due to the complexity of the process direct numerical simulations of the multiscale-multiphase problem are not possible. Hence, we develop a numerical framework for a growing fiber in turbulent air that makes the simulation of industrial setups feasible. For this purpose we employ an asymptotic viscoelastic model for the fiber. The turbulent effects are taken into account by a stochastic aerodynamic force model where the underlying velocity fluctuations are reconstructed from a $k$-$\epsilon$ turbulence description of the airflow. Our numerical results show the significance of the turbulence on the jet thinning and give fiber diameters of realistic order of magnitude.

## Full text

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## Figures

22 figures with captions in the complete paper: https://tomesphere.com/paper/1902.01811/full.md

## References

36 references — full list in the complete paper: https://tomesphere.com/paper/1902.01811/full.md

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Source: https://tomesphere.com/paper/1902.01811