By Ambrosetti A., Wang Zh.-Q.

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**Extra info for Positive solutions to a class of quasilinear elliptic equations on R**

**Example text**

So the model looks feasible. For full verification we would run an experiment, sampling the concentration at intervals and comparing with values obtained from the above result. Most likely, we would find some discrepancies and, after checking the experimental findings, we would look for ways of improving the model to remove these. 32 Ordinary Differential Equations Before leaving this section, a philosophical comment might interest you. A couple of decades ago there was little talk of 'models' - one talked of 'applied mathematics', 'Newton's theory', etc.

That we need an estimate of the difference on the left-hand side of the above inequality. Taking that estimate to be the one given (~ ml Y2 - y\1) simply makes the method of the proof work conveniently. This is a standard trick in pure mathematics - if you scan the books on analysis, theory of differential equations, etc. you will see lots of such peculiar conditions. Invariably, their primary purpose is to restrict us to a situation in which the proof may be carried through! 3. Letf(x, y) be a function which (a) is bounded in R with If (x, Y)I ~ M, (b) satisfies a Lipschitz condition with respect to y at all points in R.

We note that when t == 0, m(t) == 0, which is simply the initial condition - it does not verify the model, but just confirms we have applied the initial condition correctly. We must look to other cases for confirmation of the model. In particular, as t ~ 00 we find that the concentration becomes 1 kg 1-1. This is what we would expect - it is the concentration of the brine flowing into the tank. So the model looks feasible. For full verification we would run an experiment, sampling the concentration at intervals and comparing with values obtained from the above result.