Created by W.Langdon from gp-bibliography.bib Revision:1.2031
@PhdThesis{Elsey:thesis,
author = "Justin Rae Elsey",
title = "Dynamic Modelling, Measurement and Control of
Co-rotating Twin-Screw Extruders",
school = "Department of Chemical Engineering, University of
Sydney",
year = "2002",
address = "Australia",
month = "25 " # aug,
keywords = "genetic algorithms, genetic programming, twin-screw
extrusion, extruder geometry, dynamic modelling,
process control, acoustic sensors, image analysis,
bubble growth",
URL = "
http://ses.library.usyd.edu.au/bitstream/2123/687/2/adt-NU20050131.14060102whole.pdf",
URL = "
http://hdl.handle.net/2123/687",
size = "242 pages",
abstract = "Co-rotating twin-screw extruders are unique and
versatile machines that are used widely in the plastics
and food processing industries. Due to the large number
of operating variables and design parameters available
for manipulation and the complex interactions between
them, it cannot be claimed that these extruders are
currently being optimally utilised. The most
significant improvement to the field of twin-screw
extrusion would be through the provision of a generally
applicable dynamic process model that is both
computationally inexpensive and accurate. This would
enable product design, process optimisation and process
controller design to be performed cheaply and more
thoroughly on a computer than can currently be achieved
through experimental trials.
This thesis is divided into three parts: dynamic
modelling, measurement and control. The first part
outlines the development of a dynamic model of the
extrusion process which satisfies the above mentioned
criteria. The dynamic model predicts quasi-3D spatial
profiles of the degree of fill, pressure, temperature,
specific mechanical energy input and concentrations of
inert and reacting species in the extruder. The
individual material transport models which constitute
the dynamic model are examined closely for their
accuracy and computational efficiency by comparing
candidate models amongst themselves and against full 3D
finite volume flow models. Several new modelling
approaches are proposed in the course of this
investigation. The dynamic model achieves a high degree
of simplicity and flexibility by assuming a slight
compressibility in the process material, allowing the
pressure to be calculated directly from the degree of
over-fill in each model element using an equation of
state. Comparison of the model predictions with dynamic
temperature, pressure and residence time distribution
data from an extrusion cooking process indicates a good
predictive capability. The model can perform dynamic
step-change calculations for typical screw
configurations in approximately 30 seconds on a 600 MHz
Pentium 3 personal computer.
The second part of this thesis relates to the
measurement of product quality attributes of extruded
materials. A digital image processing technique for
measuring the bubble size distribution in extruded
foams from cross sectional images is presented. It is
recognised that this is an important product quality
attribute, though difficult to measure accurately with
existing techniques. The present technique is
demonstrated on several different products. A
simulation study of the formation mechanism of polymer
foams is also performed. The measurement of product
quality attributes such as bulk density and hardness in
a manner suitable for automatic control is also
addressed. This is achieved through the development of
an acoustic sensor for inferring product attributes
using the sounds emanating from the product as it
leaves the extruder. This method is found to have good
prediction ability on unseen data.
The third and final part of this thesis relates to the
automatic control of product quality attributes using
multivariable model predictive controllers based on
both direct and indirect control strategies. In the
given case study, indirect control strategies, which
seek to regulate the product quality attributes through
the control of secondary process indicators such as
temperature and pressure, are found to cause greater
deviations in product quality than taking no corrective
control action at all. Conversely, direct control
strategies are shown to give tight control over the
product quality attributes, provided that appropriate
product quality sensors or inferential estimation
techniques are available.",
notes = "Uses GP, eg in chapter 6. See also his publications
pages iv-v",
}
Genetic Programming entries for Justin Elsey