Predicting failure of solid metal materials from first stage of cyclic stress

Take a wire paperclip. Now, bend it back and forth in the same spot 15, maybe 20 times. Chances are the paperclip will have broken before you finish. This is due to what’s called metal fatigue, which occurs when a metal component is cyclically stressed until it fails.

While the broken paperclip is a trivial example of metal fatigue, the phenomenon is a huge problem in the wider world. “Most unexpected failures — bridges, airplanes, oil rigs, heart valves — fail by that process,” said UC Santa Barbara materials science professor Tresa Pollock, who specializes in the mechanical and and environmental performance of materials in extreme environments. Virtually any structural metal that is subjected to cyclic stress — deformations, vibrations, extreme temperatures, impacts and the like — is vulnerable, with results that can cost hundreds of billions of dollars each year.

To forsee and avoid such catastrophic fates, Pollock and fellow researchers at UCSB, University of Illinois at Urbana-Champaign and Université de Poitiers in France have developed a theory that predicts the limits to which metals can be subjected to cyclic stress before failing. And they can predict failure from the first cycle. Their research is published in the journal Science.

Being able to predict when a metal component is likely to fail from cyclic stress has long been a priority when designing an engineered system, whether it’s an artificial heart valve or a nuclear power plant. However, according to Pollock, who also serves as the interim dean of the College of Engineering at UC Santa Barbara, the process of making this determination hasn’t changed much in almost two centuries.

“They take something, cycle it and measure the cycles to failure,” she said.

But these empirically-driven results often come without the deeper, quantitative insights that would enable predictions across a broad range of metals under various conditions. Further complicating the matter is that failures can often occur after millions or billions of cycles. “And if you have to test something for a year or 10 years before it fails, then it’s a little difficult to generate enough test results to design against that failure,” Pollock said.

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