Back to results

Department of Chemical Engineering

Use of artificial neural network models to derive particle size distributions and their moments from chord length distributions

Abstract

dc:description.abstract

The objective of this study was to develop a method for in-lie measurement of a particle size distribution (PSD) of suspended solids and its moments. This was part of a wider study, the aim of which was to develop a system for controlling a crystallisation process. The control strategy to be used is dependent on kinetic models of the process. These are in turn dependent on the zeroth to fifth moments of the particle size distribution and the supersaturation levels of the solution. In order to apply advanced control to a process, continuous monitoring of the process to provice real time information for the process model is required.

Degree

thesis:*
Grantor dc:publisher.institution
Department of Chemical Engineering
Year dc:date.issued
2006

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Maússe, Celestino Fernando

Rights

Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11427/5296
OAI identifier oai:identifier
oai:open.uct.ac.za:11427/5296

Chain of custody

source
Harvested from
University of Cape Town
Base URL
open.uct.ac.za/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Maússe, Celestino Fernando. Use of artificial neural network models to derive particle size distributions and their moments from chord length distributions. Department of Chemical Engineering, 2006. http://hdl.handle.net/11427/5296