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The Science of Predicting Pipeline Cracks

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Recently, I wrote about some technology under development by the University of Alberta's Dr Walied Moussa; technology that could help make pipeline breaks like the one that polluted Michigan's Kalamazoo river a thing of the past.

The various technologies Dr Moussa has been developing could in the near future detect pipeline breaks and weakpoints.

But there's more to Dr Moussa's work than simply detecting existing cracks and weak points. The data derived using the technologies Dr Moussa has been working on can actually help predict cracks and weak points before they ever become a problem.

According to a 1998 paper written by Dr Moussa the trick to this is in detecting micro-cracks.

You may think that the proliferation of micro-cracks would automatically compromise the integrity of the pipe. This isn't necessarily so. Sometimes the micro-cracks create what is called a "shielding effect;" the complex dynamics of how kinetic or thermal energy is conducted between the tips of these micro-cracks can lead to a strengthening effect that laypeople wouldn't expect.

This doesn't happen at random. It depends largely on how much these micro-cracks overlap, and how much they're offset from one another.

The data collected by Dr Moussa's technologies can be used to determine whether the proliferation of these micro-cracks strengthens or weakens the integrity of the pipe. This involves some very complex math.

But complex or not, the math works. As of 1998, this method successfully predicted the emergence of a problem spot 90% of the time.

This may not be as helpful as it could be in cases of pipelines not equipped with the kinds of monitoring devices Dr Walied Moussa has been developing. Right now, that's pretty much every pipeline in existence. Technology does exist that allows inspectors to detect these kinds of micro-cracks, but periodic inspections are a far cry from continuous monitoring.

But once such devices become common equipment for pipelines it will be another matter entirely.

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