About this Abstract |
Meeting |
MS&T21: Materials Science & Technology
|
Symposium
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Additive Manufacturing of Metals: Microstructure, Properties and Alloy Development
|
Presentation Title |
Location-specific Fatigue Life Predictions in AM Parts Using Physics-based Models within an ICME Framework |
Author(s) |
Manisha Banker, Ayman Salem, Dan P. Satko, Jan Kasprzak, Nam Phan |
On-Site Speaker (Planned) |
Manisha Banker |
Abstract Scope |
Conventional qualification of fatigue critical structures requires experimental fatigue life assessments supported by a large number of tests at coupon, subcomponent, component and system levels. A model-based fatigue life prediction method will be presented as a step towards model-based qualification of additively manufactured (AM) components. The physics-based fatigue life prediction model, developed by MRL, will be used to guide and/or replace experimental testing gradually for lower cost and rapid prediction of fatigue life in AM parts. Fracture mechanics principles are employed, capturing uncertainties and underlying physics in the deposited material as a function of processing and post-processing through location-specific digital identities and using extreme value statistics to predict corresponding fatigue strength and fatigue life under cyclic loading. With such an approach significant cost and time reductions are anticipated by the transferability of predictions from one AM part to another using MRL’s Integrated Computational Adaptive Additive Manufacturing (iCAAM) machine learning tools. |