Understanding Pressure in Structured Optical Fibre Drawing

Citation Author(s):
Ghazal
Tafti
John
Canning
Shuai
Wang
Yanhua
Luo
Kevin
Cook
Gang-Ding
Peng
Submitted by:
ghazal tafti
Last updated:
Sat, 12/28/2019 - 19:40
DOI:
10.21227/shyc-1b71
License:
0
0 ratings - Please login to submit your rating.

Abstract 

The impact of drawing parameters on the structure of solid-core axisymmetric structured optical fibres (SOF) stacked to form four hexagonal rings of air-holes is investigated. The modelling of the internal capillary structure on optical fibre drawing using an unconstrained applied internal pressure in analogous single-capillary is contested. A corrected single-capillary function to cater for multi-capillary structural constraint within a larger single capillary draw, whilst retaining analytical simplicity, is proposed and shown to give reasonable and meaningful fits with experiments. This simple analytical approach provides an intuitive approach to both quantify and understand the impact of internal pressure on structured optical fibre drawing. It predicts that the actual effective pressure experienced by the fibre is approximately one-fifth less than that of the applied pressure in the holes. The explanation for this is the lateral pressures including opposing pressure and sideways spread of the hole shape observed experimentally in SEM images when the pressure is able to overcome silica viscosity. To confirm this, weakly birefringent axially symmetric SOF fibres with asymmetric holes having thinner walls were examined – the reduction in effective outward pressure is found to be larger than the uniform case, about one-quarter of the applied internal pressure supporting the explanation. This understanding provides new insight and a novel avenue for tuning the properties of structured optical fibres and waveguides with greater finesse and control.

Instructions: 

All data derived or used during the study are available from the corresponding author by request.

Dataset Files

    Files have not been uploaded for this dataset