Sandia National Laboratories' Predicting Performance Margins (PPM) project is working on improving the understanding of material science. The long-term, multidisciplinary program aims at identifying how material variability affects performance margins for an engineering component or machine part. The goal is to determine a science-based foundation for materials design and analysis to help predict how they will perform in specific applications. The research could lead to safer and more reliable spacecraft, bridges, power grids, cars, nuclear power plants and other complex engineered systems.
“Too often, we are unable to predict precisely how a material will behave, and instead we must rely on expensive performance tests,” says Amy Sun, program manager. The PPM simultaneously tackles fundamental materials science issues at the atomic and microstructural scales and engineering problems at the visible scale, she says.
Lead investigator Brad Boyce explains that the research focuses on where the scales connect—where the atomistic level and a single crystal intersect and where the crystal level and the component level intersect—to predict collective behavior.