Predicting Performance Margins (PPM) is a multi-disciplinary team that was created as an effort to integrate the many different areas of Materials Sciences, leveraging both experimental and modeling expertise at Sandia. The PPM project goal is to provide a science-based, probabilistic underpinning for design and analysis capabilities that links microstructure differences to macro-scale property variability.
One of the challenges at Sandia National Laboratories is addressing the issue of predictively connecting the macroscopic properties of metals to their micro– and nanostructures. While this issue may seem straightforward, it is anything but trivial. Materials are intrinsically inhomogeneous, and consequently, the specific relationship between microstructural variability and resulting properties and performance is often unknown.
PPM is comprised of a group of multidisciplinary staff, post-docs, and university collaborators. These individuals are dedicated to addressing major gaps in material science understanding in compelling and high-stakes mission-driven work. Staff from different centers actively seek science-based, probabilistic underpinnings which will provide much needed links between material variability and material performance. These centers include Physical, Chemical, Materials Science, Engineering Science, and Nano Science across both Sandia New Mexico and Sandia California sites.
Initial PPM efforts have focused largely on development of tools and insight towards ensuring the mechanical safety of welded components. The major benefit of the PPM approach is that it is a bellwether program designed to enable the core theme of the strategic investigation of material variability and then expand this same framework into many other topics, arenas, and materials needs.
For more information, please contact:
Amy Sun, Program Manager, email@example.com
Brad Boyce, Principal Investigator, firstname.lastname@example.org
Corbett Battaile, Co-Principal Investigator, email@example.com
Monica Riewe, firstname.lastname@example.org