The use of computational simulation to predict the performance
of existing equipment or for the design of improved mineral
processing equipment will be referred to as Computational
Mineral Processing (CMP) in this paper. The emphasis will be on
solving the governing equations for liquid solid flows in
complex geometric domains to obtain, typically, the
three-dimensional distributions of velocity and pressure for the
liquid phase and the velocity and concentration for the solid
phase. The underlying technology, computational fluid dynamics
(CFD), is very well-developed in other industries (aircraft, car
and chemical) and forms a vital part of product design and
analysis. The subsequent design of improved mineral processing
equipment may also involve finite element structural analysis
(FESA). Computational fluid dynamics (CFD) and finite element
structural analysis (FESA) are part of the generic discipline of
Computational Engineering and Science (CES). Ciment and
Scherlis (1993) define CES as `The systematic application of
computing systems and computational solution techniques to
mathematical models formulated to describe and simulate
phenomena of scientific and engineering interest'. Increasing computer power (Kaufmann and Smarr, 1993), is a
dominant factor determining the rapid growth of industrial
utilisation of CES. This increase is happening at both the
supercomputer and the workstation level. Indeed, today's typical
workstation, a Hewlett-Packard 735, is as powerful as a CDC
7600, the leading supercomputer in 1970. Future computer
architectures are expected to become increasingly parallel
(Gartner Group, 1990) allowing a sustained performance of a
teraflop (a million megaflops) to be achieved well before the
Sydney Olympics in the year 2000. It is recognised that the modem development of most
disciplines in the physical sciences rests on the three
complementary strategies of experimentation, analysis and
computational simulation. As the 21st century is approached the
volume of computational simulation, both fundamental and
applied, is growing dramatically and the role of experimentation
is diminishing. In the area of equipment design, CES provides the following
advantages over experimental testing and measurement: 1. lead time in design and development is significantly
reduced; 2. CES can simulate conditions not reproducible in
experimental tests; 3. CES provides detailed and comprehensive information; and
4. CES is more cost-effective and time-efficient. The ultimate benefit for industry is greater productivity and
hence greater profitability. The broader issues in relation to CFD
are discussed by Fletcher (1993b). In the five- to ten-year time frame, growth in computer power
will make it practical to combine CFD and FESA with
optimisation procedures to produce a design process that is
almost fully computerised. It is expected that fully automatic