dc.contributor.advisor |
Groot, D.R. |
en |
dc.contributor.postgraduate |
Sililo, Bernard Liswani |
en |
dc.date.accessioned |
2017-07-13T13:29:00Z |
|
dc.date.available |
2017-07-13T13:29:00Z |
|
dc.date.created |
2017-04-20 |
en |
dc.date.issued |
2016 |
en |
dc.description |
Dissertation (MSc)--University of Pretoria, 2016. |
en |
dc.description.abstract |
The uranium price decline has negatively impacted on the uranium mining industry. This
decline in price requires that uranium metallurgical processes be made to operate more
efficiently. Some key parameters that influence the dissolution and kinetics of leaching
uraninite (one of the main minerals from which uranium can be extracted) are pH, oxidationreduction
potential and iron concentration. A good understanding of the effect these
parameters have on the leach kinetics would lead to an efficient operation of metallurgical
processes. The objective of this work was therefore to investigate the effects of these key
drivers on leach kinetics of Rӧssing Uranium ore. Added to this, was an attempt to come up
with a mathematical model which can successfully replicate the leach kinetics. A series of
laboratory leach experiments were performed on Rӧssing ore where the pH, oxidationreduction
potential and total iron were varied, one at a time, to establish the effects they
have on the leach kinetics and on the uranium extraction.
Analysis of the data collected from this study showed that the leach kinetics are more
dependent on the oxidation-reduction potential, followed by the iron concentration and least
affected by the pH. It was further shown that oxidation-reduction potential is a function of
total iron. An integral method was used to analyse the kinetic data. A literature study reveals
that uraninite dissolution follows first order kinetics, but of interest in these results was that
the uranium dissolution was found to closely follow the second order. Further research is
recommended to look at ascertaining these results. Two models were developed, one using regression and the other by curve fitting method. Both models could fit the
experimental data well enough. |
en_ZA |
dc.description.availability |
Unrestricted |
en |
dc.description.degree |
MSc |
en |
dc.description.department |
Materials Science and Metallurgical Engineering |
en |
dc.identifier.citation |
Sililo, BL 2016, Modelling uranium leaching kinetics, MSc Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/61336> |
en |
dc.identifier.other |
A2017 |
en |
dc.identifier.uri |
http://hdl.handle.net/2263/61336 |
|
dc.language.iso |
en |
en |
dc.publisher |
University of Pretoria |
en |
dc.rights |
© 2017 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
en |
dc.subject |
UCTD |
en |
dc.subject |
Uraninite |
en |
dc.subject |
Leach kinetics |
en |
dc.subject |
Oxidation-reduction potential |
en |
dc.subject |
Integral method |
en |
dc.title |
Modelling uranium leaching kinetics |
en_ZA |
dc.type |
Dissertation |
en |