|About this Abstract
||2017 TMS Annual Meeting & Exhibition
||Additive Manufacturing: Building the Pathway towards Process and Material Qualification
||A-51: Experimental Technique for Extracting Local Mechanical Behavior from AM Components with Spatially Varying Mechanical Properties for Correlation with FEA Modeling
||Denver Seely, David Francis
|On-Site Speaker (Planned)
Predictively modeling the constitutive behavior of as deposited metal AM parts presents a challenge. Complex thermal histories can produce heterogeneous microstructures with varied mechanical behavior within a single part having a single chemical composition. In addition, by making use of the AM capability of varying composition locally, functional grading of mechanical properties can be intentionally introduced. Computational models of heterogeneous material distribution rely on accurate material models and valid assumptions about interactions between materials. Obtaining accurate local mechanical behavior is important for calibrating microstructurally sensitive constitutive models. This presents a challenge for calibration experiments with regard to specimen design. Validating the assumptions of computational models that make use of functionally graded properties also require accurate local mechanical measurements. We show the application of a digital image correlation technique to extract local mechanical behavior for model calibration, then show the application to a functionally graded experiment compared with an FEA model.
||Planned: Supplemental Proceedings volume