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Using additive manufacturing as a pathway to change the qualification paradigm

Solid Freeform Fabrication 2018: Proceedings of the 29th Annual International Solid Freeform Fabrication Symposium - An Additive Manufacturing Conference, SFF 2018

Roach, R.A.; Bishop, Joseph E.; Johnson, Kyle J.; Rodgers, Theron R.; Boyce, B.L.; Swiler, L.; van Bloemen Waanders, Bart G.; Chandross, M.; Kammler, Daniel K.; Balch, Dorian K.; Jared, B.; Martinez, Mario J.; Leathe, Nicholas L.; Ford, K.

Additive Manufacturing (AM) offers the opportunity to transform design, manufacturing, and qualification with its unique capabilities. AM is a disruptive technology, allowing the capability to simultaneously create part and material while tightly controlling and monitoring the manufacturing process at the voxel level, with the inherent flexibility and agility in printing layer-by-layer. AM enables the possibility of measuring critical material and part parameters during manufacturing, thus changing the way we collect data, assess performance, and accept or qualify parts. It provides an opportunity to shift from the current iterative design-build-test qualification paradigm using traditional manufacturing processes to design-by-predictivity where requirements are addressed concurrently and rapidly. The new qualification paradigm driven by AM provides the opportunity to predict performance probabilistically, to optimally control the manufacturing process, and to implement accelerated cycles of learning. Exploiting these capabilities to realize a new uncertainty quantification-driven qualification that is rapid, flexible, and practical is the focus of this paper.

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Born Qualified Grand Challenge LDRD Final Report

Roach, R.A.; Argibay, Nicolas A.; Allen, Kyle M.; Balch, Dorian K.; Beghini, Lauren L.; Bishop, Joseph E.; Boyce, Brad B.; Brown, Judith A.; Burchard, Ross L.; Chandross, M.; Cook, Adam W.; DiAntonio, Christopher D.; Dressler, Amber D.; Forrest, Eric C.; Ford, Kurtis R.; Ivanoff, Thomas I.; Jared, Bradley H.; Johnson, Kyle J.; Kammler, Daniel K.; Koepke, Joshua R.; Kustas, Andrew K.; Lavin, Judith M.; Leathe, Nicholas L.; Lester, Brian T.; Madison, Jonathan D.; Mani, Seethambal S.; Martinez, Mario J.; Moser, Daniel M.; Rodgers, Theron R.; Seidl, Daniel T.; Brown-Shaklee, Harlan J.; Stanford, Joshua S.; Stender, Michael S.; Sugar, Joshua D.; Swiler, Laura P.; Taylor, Samantha T.; Trembacki, Bradley T.

This SAND report fulfills the final report requirement for the Born Qualified Grand Challenge LDRD. Born Qualified was funded from FY16-FY18 with a total budget of ~$13M over the 3 years of funding. Overall 70+ staff, Post Docs, and students supported this project over its lifetime. The driver for Born Qualified was using Additive Manufacturing (AM) to change the qualification paradigm for low volume, high value, high consequence, complex parts that are common in high-risk industries such as ND, defense, energy, aerospace, and medical. AM offers the opportunity to transform design, manufacturing, and qualification with its unique capabilities. AM is a disruptive technology, allowing the capability to simultaneously create part and material while tightly controlling and monitoring the manufacturing process at the voxel level, with the inherent flexibility and agility in printing layer-by-layer. AM enables the possibility of measuring critical material and part parameters during manufacturing, thus changing the way we collect data, assess performance, and accept or qualify parts. It provides an opportunity to shift from the current iterative design-build-test qualification paradigm using traditional manufacturing processes to design-by-predictivity where requirements are addressed concurrently and rapidly. The new qualification paradigm driven by AM provides the opportunity to predict performance probabilistically, to optimally control the manufacturing process, and to implement accelerated cycles of learning. Exploiting these capabilities to realize a new uncertainty quantification-driven qualification that is rapid, flexible, and practical is the focus of this effort.

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Data Analysis for the Born Qualified Grand LDRD Project

Swiler, Laura P.; van Bloemen Waanders, Bart G.; Jared, Bradley H.; Koepke, Joshua R.; Whetten, Shaun R.; Madison, Jonathan D.; Ivanoff, Thomas I.; Jackson, Olivia D.; Cook, Adam W.; Brown-Shaklee, Harlan J.; Kammler, Daniel K.; Johnson, Kyle J.; Ford, Kurtis R.; Bishop, Joseph E.; Roach, R.A.

This report summarizes the data analysis activities that were performed under the Born Qualified Grand Challenge Project from 2016 - 2018. It is meant to document the characterization of additively manufactured parts and processe s for this project as well as demonstrate and identify further analyses and data science that could be done relating material processes to microstructure to properties to performance.

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Changing the Engineering Design & Qualification Paradigm in Component Design & Manufacturing (Born Qualified)

Roach, R.A.; Bishop, Joseph E.; Jared, Bradley H.; Keicher, David M.; Cook, Adam W.; Whetten, Shaun R.; Forrest, Eric C.; Stanford, Joshua S.; Boyce, Brad B.; Johnson, Kyle J.; Rodgers, Theron R.; Ford, Kurtis R.; Martinez, Mario J.; Moser, Daniel M.; van Bloemen Waanders, Bart G.; Chandross, M.; Abdeljawad, Fadi F.; Allen, Kyle M.; Stender, Michael S.; Beghini, Lauren L.; Swiler, Laura P.; Lester, Brian T.; Argibay, Nicolas A.; Brown-Shaklee, Harlan J.; Kustas, Andrew K.; Sugar, Joshua D.; Kammler, Daniel K.; Wilson, Mark A.

Abstract not provided.

Solidification Diagnostics for Joining and Microstructural Simulations

Robino, Charles V.; Robino, Charles V.; Hall, Aaron C.; Headley, Thomas J.; Roach, R.A.

Solidification is an important aspect of welding, brazing, soldering, LENS fabrication, and casting. The current trend toward utilizing large-scale process simulations and materials response models for simulation-based engineering is driving the development of new modeling techniques. However, the effective utilization of these models is, in many cases, limited by a lack of fundamental understanding of the physical processes and interactions involved. In addition, experimental validation of model predictions is required. We have developed new and expanded experimental techniques, particularly those needed for in-situ measurement of the morphological and kinetic features of the solidification process. The new high-speed, high-resolution video techniques and data extraction methods developed in this work have been used to identify several unexpected features of the solidification process, including the observation that the solidification front is often far more dynamic than previously thought. In order to demonstrate the utility of the video techniques, correlations have been made between the in-situ observations and the final solidification microstructure. Experimental methods for determination of the solidification velocity in highly dynamic pulsed laser welds have been developed, implemented, and used to validate and refine laser welding models. Using post solidification metallographic techniques, we have discovered a previously unreported orientation relationship between ferrite and austenite in the Fe-Cr-Ni alloy system, and have characterized the conditions under which this new relationship develops. Taken together, the work has expanded both our understanding of, and our ability to characterize, solidification phenomena in complex alloy systems and processes.

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6 Results
6 Results