Sandia Labs researches materials variability

Sandia National Laboratories researcher Brad Salzbrenner tests laser-welded objects in pure tension, shear and mixed tension-shear loading. One pilot study in Sandia’s long-term Predicting Performance Margins program involves laser welds, which are widely used in engineered systems. (Courtesy of Sandia National Labs)

From the atomic level to full-scale components, the research links variability in materials’ atomic configurations and microstructures with how actual parts perform. Just how much stretching, bending or compression a particular metal will take is determined by mechanical properties that can vary widely, even within parts made of the same material.

PPM aims to identify how material variability affects performance margins for an engineering component or machine part.

The goal is a science-based foundation for materials design and analysis – predicting how a material will perform in specific applications and how it might fail compared with its requirements, then using that knowledge to design high-reliability components and systems.

Materials are such things as alloys, polymers or composites; components are switches, engines or aircraft wings, for example, while systems can be entire airplanes, appliances or even bridges.

Performance is crucial to safety and reliability in spacecraft, bridges, power grids, automobiles, nuclear power plants and other complex engineered systems.

The PPM approach has become a prototype for tackling other difficult materials issues.

“Too often, we are unable to predict precisely how a material will behave, and instead we must rely on expensive performance tests,” said program manager Amy Sun. “Capturing variability by testing alone is too expensive and not predictive.”

PPM simultaneously tackles fundamental materials science issues at the atomic and microstructural scales and engineering problems at the visible scale.

Researchers examine how and why metals deform so they can predict that behavior and ultimately make metals stronger. Better understanding could lead both to better materials and improvements in processing.

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