Random field sampling for a simplified model of melt-blowing considering turbulent velocity fluctuations

TL;DR

This paper introduces a numerical method to incorporate turbulent velocity fluctuations as Gaussian random fields in melt-blowing models, aiming to resolve discrepancies between measured and simulated fiber attenuation.

Contribution

It develops an efficient sampling procedure for Gaussian random fields with a specific covariance structure, improving the modeling of turbulence effects in melt-blowing simulations.

Findings

Turbulent velocity fluctuations significantly impact fiber jet attenuation.

The proposed sampling method is computationally efficient and scalable.

Inclusion of turbulence effects reduces the gap between experimental and simulated results.

Abstract

In melt-blowing very thin liquid fiber jets are spun due to high-velocity air streams. In literature there is a clear, unsolved discrepancy between the measured and computed jet attenuation. In this paper we will verify numerically that the turbulent velocity fluctuations causing a random aerodynamic drag on the fiber jets -- that has been neglected so far -- are the crucial effect to close this gap. For this purpose, we model the velocity fluctuations as vector Gaussian random fields on top of a k-epsilon turbulence description and develop an efficient sampling procedure. Taking advantage of the special covariance structure the effort of the sampling is linear in the discretization and makes the realization possible.