Michael D. Sangid
Elmer F. Bruhn Professor of Aeronautics and Astronautics
Professor of Materials Engineering (by courtesy)
Seminar: Incorporating Microstructure Sensitive Modeling into Component Lifetime Assessments
Abstract: Historically, component lifing is based on regression analysis from coupon-level fatigue tests, including Basquin and Coffin-Manson Equations. These approaches have served the community well, but rely on large scale testing programs followed by overly conservative statistical analysis. Further, these techniques are entirely based on empiricism, without any connection to the material’s microstructure or failure mechanisms. Alternatively, location specific lifing of components can be tailored to the processing route and structure of the material and can leverage model-based approaches. In this work, advancements in a model-based engineering framework are discussed to support probabilistic location specific lifing, including capturing the relevant product data across the lifecycle of a component.
Microstructure sensitive fatigue modeling is based on creation of a series of statistically equivalent microstructures. Afterwards, crystal plasticity is used to assess the micromechanical fields relative to the grain and defect level attributes during cyclic loading. Uncertainty within the crystal plasticity model parameters are assessed and the model’s resulting micromechanical fields are validated against high-energy x-ray diffraction (HEDM) experiments. The model hotspots are used to calculate the evolution of the accumulated plastic strain energy density, which is correlated to the onset of crack initiation. For experimental validation, the in situ HEDM techniques are directly compared to simulated mirror replicates of the experiments, representing the exact same microstructure, in order to measure the point-by-point evolution of material damage over time and compare directly to the simulation results. The fatigue modeling framework is combined with uncertainty quantification and propagation efforts of the model’s readiness level, in order to build trust in the predictive capabilities of the model.
About the Speaker: Michael D. Sangid received his B.S. (2002) and M.S. (2005) in Mechanical Engineering from the University of Illinois at Urbana-Champaign (UIUC). After his Master’s degree, Dr. Sangid spent two years working in Indianapolis, IN for Rolls-Royce Corporation, specializing in material characterization, fatigue, fracture, and creep of high temperature aerospace materials before resuming his education in 2007. He received his PhD in Mechanical Engineering from UIUC in 2010 and continued as a post-doctoral associate. In the spring of 2012, Dr. Sangid started as an assistant professor at Purdue University in the School of Aeronautics and Astronautics with a courtesy appointment in Materials Engineering, where he continues his work on building computational materials models for failure of structural materials with experimental validation efforts focused at characterization of the stress/strain evolution at the microstructural scale during in situ loading. He is a recipient of the TMS Young Leaders Award, the ASME Orr Award, TMS Early Career Faculty Fellow, the NSF CAREER Award, and the AFOSR, ONR, and DARPA Young Investigator/Faculty Awards. He is currently serving as an editor of the International Journal of Fatigue. Dr. Sangid has started and serves as the Executive Director of the Hypersonics Advanced Manufacturing Technology Center as the first contract within the Purdue Applied Research Institute.
Host: James T. Burns, Heinz and Doris Wilsdorf Distinguished Research Professor of Materials Science and Engineering and Associate Professor of Materials Science and Engineering.