Most numerical algorithms have been invented long before the widespread use of computers. Algorithms were designed
to speed up human computation, therefore constructed to minimize the number of operations to be carried out.
The advent of objectoriented type programming provided the channel for code reuse , which in principle also
include concepts of inheritance, polymorphism, and data encapsulation. While not particularly concerned with the
internal workings of object orientation one must be aware of the capability these concepts render. Take for
instance the ability to mix through inheritance a common set of methods, making implementation of numerical
algorithms intelligible and effortless. Minimizing the number of operations is paramount to speed up code execution.
In mining, as in any other industry, handling volumes of data bundled in large databases are commonplace. Consider
area selection which is a crucial step in professional mineral exploration. Area selection is based on applying
theories behind ore genesis, the knowledge of known ore occurrences and the method of their formation to determine
potential areas where a particular class of ore deposit being sought may exist. It usually requires some form of
geophysics such as downhole probing of drill holes in order to geophysically delineate ore body continuity within
the ground.
The use of polynomials in this area is quite important because they are often used in approximating
functions determined by experimental measurements like drill holes. For example, polynomial leastsquare fit numerical
algorithms can provide a representation of body continuity as defined by the set of core samples taken.
Additional benefits come from linear optimization often applied to mineral extraction, where the objective function may
consist of minimizing the total cost of operation based on constraint parameters like grade of ore, transportation costs,
manpower and others. Linear optimization algorithms like Simplex Algorithm, Powellâ€™s Algorithm and HillClimbing Algorithm
are widely used.
Numerical algorithms are representations of proven mathematical theory. Real world numerical algorithm applications are
coded statements strictly following accepted hypothesis. Specialty areas of function evaluation, interpolation, iterative
algorithms, series, linear algebra, statistical analysis, optimization, linear and nonlinear systems are heavily used
mining applications. Consider the use of differential equations: most problems in engineering, mining included, are
governed by either highorder equations or coupled differential equation
systems where Euler and RungeKutta numerical methods, which are actually a general class of algorithms, provide reasonable
generalizations for numerical implementation in mineral applications.
Many commercial mineral algorithms are available, however,
one size does not necessarily fit all. Large companies can afford
customization to fit their operations. Smaller outfits tend to write their own provided they have the expertise in house.
Assistance is always accessible through internet inquiry or other specialized software houses.
Numerical algorithms in mining provide fast,
accurate and reliable results. The scope of applications is as diverse as
resource type evaluation tasks like quantifying the grade and tonnage of a mineral occurrence, to everyday complexity
encountered in open pit mining or underground shaft sinking, block caving, cave mining , cut and fill, or similar
extraction operations. Added benefits incorporate code reusability and ease of use.
Practical samples and further interesting
discussions on mineral engineering can be found at http://www.keystoneminingpost.com
