Collaborative Research: DMREF: NSF-NSERC: Structural Alloys for Fatigue Endurance (SAFE)

Fatigue refers to the mechanical failure of materials subjected to repeated cyclic loads. It occurs in all materials including metals and alloys, and is a significant limitation that affects all engineering structures and devices (both structural and functional). It is a common cause of failure (and accidents) in devices including computers, cars, bridges and airplanes, and thus a significant economic, societal and national defense challenge. Unfortunately many fundamental aspects of fatigue remain incompletely understood, even though decades of empirical knowledge have provided (conservative) material specific guidelines for the design of engineering components to avoid fatigue in specific materials. The advent of additive manufacturing and advanced alloys have pushed us beyond this empirical knowledge base. In particular, recent experimental observations suggest situations where additively manufactured metallic alloys have fatigue strength that greatly exceed their conventionally manufactured counterparts, and other situations where they greatly underperform. The investigators will develop a new data-driven approach predicated on the view that the spread of fatigue life can be attributed to particular details of defects and microstructure, and a fundamental understanding of this relationship can lead to new Structural Alloys for Fatigue Endurance (SAFE). The approach is to create an integrated database and knowledge map of material and processing parameters, microstructure, comprehensive mechanical characterization, post-failure analysis and computational experiments on the fatigue behavior of additively manufactured structural alloys. Innovations in methodology including efficient high throughput testing and serial sectioning combined with Electron Backscatter Diffraction (EBSD) to acquire three-dimensional images of microstructure with orientation around individual crack initiation sites, in operando synchrotron observation and accelerated approaches to simulation enable the creation of this database. New methodologies are developed to sample the knowledge map and add new experimental results and simulation until there is a significant area of knowledge where the control parameters predict the quantities of interest. This leads to a deep fundamental understanding of the exact mechanisms and features that initiate, inhibit and accelerate fatigue cracks, and subsequently to the inverse problem of designing new SAFE materials. The approach is developed with a focus on the widely used aerospace alloy Ti-6Al-4V. The team consists of experts in additive manufacturing, texture & characterization, fatigue, computational modeling and the application of machine learning to materials. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.