10 1 Introduction
and concentrate on the smaller task,
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which is generally something that we are
completely confident we know how to do.
1.4.2 Inverse problems
Mechanics teachers are well aware of the fact that many different problems can be
generated from the same set of calculations by interchanging the order of the depen-
dent and independent variables. For example, in a given bending problem we might:-
(i) Give the dimensions of the cross section, the material and the loading and ask
for the factor of safety against yielding.
(ii) Give the loading and the maximum permissible tensile stress and ask for one of
the dimensions of the cross section to be determined.
(iii) Give the dimensions of the cross section and the maximum permissible tensile
stress and ask for the maximum bending moment that can be transmitted.
In more complicated problems, the number of permutations is enormous.
It is tempting in each case to try to devise a sequence of procedures that will start
from the given numerical data and lead by successive arithmetic calculations to the
desired result. However, algebra was invented to deal with precisely this problem.
The thinking here is ‘I don’t know how to solve this problem. If instead I were given
x,y,z and asked to find a,b,c, I would be able to do it. Therefore, if I write x,y,z as
symbols, pretend that they are given and perform the calculations I know until I reach
expressions for a,b, c, I can then use the given values of the latter to define equations
for the unknowns’. Solving the equations may be a mathematical challenge, but (i)
we know that we need as many equations as there are unknowns, which provides
a check on the viability of the method and (ii) it is easier to lose confidence in the
formulation of the mechanics problem than it is in the mathematical manipulations.
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As a simple example, in the bending problem (ii) above we might denote the
unknown dimension of the cross section by d, find the maximum stress in the beam
in terms of d and the given loading, and then equate it to the maximum permissible
tensile stress to obtain an equation that can be solved for d. Of course, this is a very
simple example, but the technique becomes more important when the overall com-
plexity of the problem is greater. A major advantage of using algebra to transform the
sequence in which the problem is solved is that we are thereby able to choose a se-
quence with which we are familiar, or for which we have a high degree of confidence
of success.
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It is interesting to note that procedures in computer programs generally adopt this same
‘restricted vision’. Variables defined inside procedures have no definition outside the pro-
cedure and vice versa, unless an explicit ‘common’ definition is invoked. The more general
parallel between problem solving and programming is also instructive. Computer programs
have to be written so as to be completely ‘foolproof’ and it also makes sense to devise
problem solving techniques that are as immune as possible to our occasional periods of
intellectual weakness.
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These days, many of the more routine mathematical operations can be performed in sym-
bolic languages such as Mathcad, Mathematica, MatLab and Maple.