Thesis (PhD (Process Engineeering))--University of Stellenbosch, 1995. / The hydrometallurgical leaching of sulphide concentrates was introduced in the
1950's. Generally the leaching mechanisms of these processes are not understood
fundamentally. The reasons for this are the inherently complex nature of sulphide
chemistry and that the sulphide concentrates usually consist of highly intergrown
sulphide minerals. The leaching kinetics of sulphide concentrates where only one
metal-sulphide mineral occurs have been investigated intensively, but not for
sulphide concentrates with more than one metal-sulphide mineral. The behaviour of
these mixed metal-sulphide minerals has mostly been investigated on plant scale to
qualitatively determine the leaching trends of the process. The consequence of the
relatively unKnown leaching mechanism and kinetics is that these processes are not
controlled efficiently.
This study was conducted on the acid-oxygen pressure leaching of Ni-Cu matte (the
first stage leach process at the Ni-Cu refinery of Impala Platinum Ltd.). As a first step
to improve the control efficiency of the process, the process must be stabilised.
Therefore, an off line computer simulation program is proposed to control the
repulping section of the plant that has previously been controlled solely by an
operator. Controlling the repulping section is very important, because conditions exist
in the repulping tanks for leaching to occur. This causes perturbations in the pulp
entering the pressure leach autoclave. Due to the fast reaction kinetics of the matte
in the pressure leach autoclave the perturbations entering the autoclave will influence
the performance of the acid-oxygen pressure leach process. The simulation program
was tested on the plant and indicated that considerable improvement in the stability
of the operation could be achieved.
In obtaining a better understanding of the behaviour of this process, it is essential
that key variables and trends are identified. A methodology is proposed to analyse
and model this ill-defined and poorly understood process from historical data by
v
artificial neural networks (ANN), inductive learning by decision trees and statistical
techniques. The back propagation neural network, learning vector quantization neural
network and the decision trees yielded comparable classification rates between 73%
and 84%, and could serve as a basis for the adjustment of operating conditions to
improve the efficiency of the process. The relative importance of the process
variables is determined by a method of sensitivity analysis and together with the
statistical mean, the effect of an increase or decrease in the variable on the process
is quantified. These results are substantiated by experimental findings.
A leaching mechanism for the acid-oxygen pressure leach of Ni-Cu matte is
postulated. The leaching sequence of the nickel and copper sulphides is Ni3Sr Ni7S"
NiS-Ni3S4, and CU2S-CU31SWCU1.BS-CUS, respectively. Ni7Sa and CU31 S1a are
intermediate nickel and copper sulphide phases that form during the leaching
process. Ni alloy has a galvanic effect on the sulphide minerals which inhibits the
overall leaching rate and results in the formation of H2S and the intermediate nickel
and copper sulphides (Ni7Sa and CU31 S1a). A semi-empirical kinetic model was
developed based on the chemical reaction rate expressions of the leaching
mechanism. This model can accurately simulate the batch leaching process for
variations in the oxygen partial pressure, oxygen flowrate, temperature, particle size,
initial acid concentration and pulp density. A sensitivity analysis on the model
indicated that for a matte with a lower initial Ni alloy content the leaching rate of
nickel is much faster.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/1255 |
| Date | 12 1900 |
| Creators | Rademan, Johan Andries Muller |
| Contributors | Lorenzen, L., Van Deventer, J. S. J., University of Stellenbosch. Faculty of Engineering. Dept. of Process Engineering. |
| Publisher | Stellenbosch : University of Stellenbosch |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Rights | University of Stellenbosch |
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