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Completed TRL 5 (started at 3, targeting 5)
Lacking AM material properties and appropriate analysis factors present hurdles to the increased use of additive manufacturing in engine applications. Highly conservative analysis factors protect systems from failure but reduce flexibility and limit use of AM materials. Current analysis factors limit feature thickness and geometry in favor of conservatism in lieu of extensive material characterization. To fully realize the benefits of additive manufacturing accurate analyses factors must be generated through three series of tests and evaluations: 1) Evaluate static and dynamic properties of laser powder bed fusion 718, 625, and GRCop-42 compared to wrought and other material forms; 2)Characterization of the impact of surface roughness on the static properties of AM Inconel 718, Inconel 625, and GRCop-42; and 3) Characterization of powder degradation with reuse in laser powder bed manufacturing of GRCop-42 and existing data on Inconel 718.
This partnership has been set in place to evaluate these analysis factors. Utilizing MSFC AM experience and capabilities to understand historical AM data, determine gaps and execute test plans to collect the necessary data to generate these analysis factors.
Improved engine designs using Additive Manufacturing (AM) will allow for optimization of weight, efficiency, and manufacturability. Lacking material properties and appropriate analysis factors highly conservative analysis factors are used to protect systems from failure, thus limiting use of AM materials. Improving understanding of AM material properties enables higher-fidelity component life analysis via elimination of unnecessary conservatism. This ACO will evaluate static and dynamic properties for GRCop-42, Inconel 718 and Inconel 625 including comparisons to wrought alloys, characterized surface and size effects on properties, and characterization of powder feedstock degradation with reuse. This data set, combined with detailed process documentation, provide a characterized process and data set that can be used for analysis to optimize weight, increase efficiency, and enable improved engine designs.
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