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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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TYPE SAND Report YEAR 2018
OSTIDOI

Materials and Hydrogen Isotope Science at Sandia's California Laboratory

Zimmerman, Jonathan A.; Balch, Dorian K.; Bartelt, Norman C.; Buchenauer, D.A.; Catarineu, Noelle R.; Cowgill, D.F.; El Gabaly Marquez, Farid E.; Karnesky, Richard A.; Kolasinski, Robert K.; Medlin, Douglas L.; Robinson, David R.; Ronevich, Joseph A.; Sabisch, Julian E.; San Marchi, Christopher W.; Sills, Ryan B.; Smith, Thale R.; Sugar, Joshua D.; Zhou, Xiaowang Z.

Abstract not provided.

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TYPE Conference Poster YEAR 2018
OSTI

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.

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TYPE Presentation YEAR 2018
OSTI

A thermal-mechanical finite element workflow for directed energy deposition additive manufacturing process modeling

Additive Manufacturing

Stender, Michael S.; Beghini, Lauren L.; Sugar, Joshua D.; Veilleux, Michael V.; Subia, Samuel R.; Smith, Thale R.; San Marchi, Christopher W.; Brown, Arthur B.; Dagel, Daryl D.

This work proposes a finite element (FE) analysis workflow to simulate directed energy deposition (DED) additive manufacturing at a macroscopic length scale (i.e. part length scale) and to predict thermal conditions during manufacturing, as well as distortions, strength and residual stresses at the completion of manufacturing. The proposed analysis method incorporates a multi-step FE workflow to elucidate the thermal and mechanical responses in laser engineered net shaping (LENS) manufacturing. For each time step, a thermal element activation scheme captures the material deposition process. Then, activated elements and their associated geometry are analyzed first thermally for heat flow due to radiation, convection, and conduction, and then mechanically for the resulting stresses, displacements, and material property evolution. Simulations agree with experimentally measured in situ thermal measurements for simple cylindrical build geometries, as well as general trends of local hardness distribution and plastic strain accumulation (represented by relative distribution of geometrically necessary dislocations).

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TYPE Journal Article YEAR 2018
ScopusOSTIDOI
Results 51–75 of 151
Results 51–75 of 151