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","parentProgram":{"ableToSelect":false,"isActive":true,"description":"Catalyst is a portfolio of early stage programs that specialize in different innovation constituencies and mechanisms to push the state of the art in aerospace technology development","programId":92327,"responsibleMd":{"canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":""},"title":"Catalyst","acronymOrTitle":"Catalyst"},"parentProgramId":92327,"programId":69,"responsibleMd":{"organizationId":4875,"organizationName":"Space Technology Mission Directorate","acronym":"STMD","organizationType":"NASA_Mission_Directorate","canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":"NASA Mission Directorate"},"responsibleMdOffice":4875,"stockImageFileId":36658,"title":"Space Technology Research Grants","acronymOrTitle":"STRG"},"description":"The goal of the proposed research is to characterize the influence of process parameter variability inherent to Selective Laser Melting (SLM) and performance effect on components manufactured with the SLM technique for space flight systems. Specific objectives are: To develop, verify, and validate robust physics-based numerical models for predictive SLM simulation using a DOE multi-physics, multi-scale massively parallel code called ALE3D for powder-scale SLM process simulations. To quantify the uncertainty in the prediction of material density and maximum tensile residual stress during laser melting and solidification of cubic coupons. A synergistic computational and experimental approach is proposed. The team assembled for this project includes J-P Delplanque (PI) and E. J. Lavernia (co-I) at UC Davis and collaborators R. McCallen, A. Anderson, and C. Kamath at Lawrence Livermore National Laboratory. The approach focuses on the melt-pool/powder-scale phenomena. A simple configuration (single track and cubic coupons) is considered. An uncertainty quantification strategy will be developed using PSUADE (LLNL) and surrogate models. Quantities of interest are: density and maximum tensile residual stress. ALE3D (LLNL) will be used to perform detailed numerical simulations. Laser melting experiments will be conducted to validate detailed numerical simulations and a surrogate process model will be developed on the basis of detailed numerical simulations. An important outcome will be a path to predictive numerical simulation of SLM processes and the identification of strategies to mitigate part variability. It is noted that the development of the surrogate model will also provide insight and guidance for the future development of reduced-order models and, in the longer term, process control strategies. The validation and uncertainty quantification methodology developed will be relevant to other additive manufacturing technologies (e.g., Direct Laser Deposition). The proposed work will constitute a cornerstone of the improved understanding of uncertainty quantification of the SLM process needed for the certification of components produced by these techniques. The proposed work will benefit from active collaborations between UCD, LLNL, and NASA ARC. Geographic proximity will facilitate regular meetings and provide ample opportunities for information exchange to ensure that the research is consistent with NASA’s needs and that it benefits from and complements ongoing efforts at NASA and LLNL. Existing collaboration between UC Davis and LLNL in the context of Accelerated Certification of the Additively Manufactured Metals initiative at LLNL will be leveraged. The proposed work directly addresses subtopic 2(a) of the solicitation (Uncertainty quantification for additive manufacturing). Since the outcomes will contribute to the development of model-based certification methods the proposed research is pertinent to Technology Area 12 (Materials, Structures, Mechanical Systems and Manufacturing) of NASA's Space Technology Roadmaps.
","benefits":"This work constitutes a cornerstone of the improved understanding of uncertainty quantification of the SLM process needed for the certification of components produced by these techniques.
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Additive manufacturing techniques, and Laser Powder-Bed Fusion (e.g. Selective Laser Melting, SLM) in particular, have a demonstrated capacity to manufacture such components. In fact, a recent report of the National Research Council1 emphasizes the potential of additive manufacturing for the development of aerospace systems with increased performance. However, the adoption of these relatively new manufacturing techniques for the development of space systems will require the integration of computational techniques in the certification process of such components. The primary goal of the research described in this report was to enable the characterization of the influence of process parameter variability on components manufactured with the SLM technique for space flight systems and their performance. To this end, a physics-based surrogate model was developed that enables the fast prediction of thermal field and melt pool geometry during the SLM process. Two variants of the model were constructed one for uniform properties the other for non-uniform properties. The development effort was informed by a joint experimental effort and by high-fidelity numerical simulations of the process. An Uncertainty Quantification (UQ) strategy was developed in which this physics-based surrogate model is calibrated with experimental data (e.g. track width) using Bayesian analysis. The low-order uniform property surrogate model is fast enough to enable extensive UQ analysis for a wide range of process parameters. It was found that the non-uniform property surrogate model is subject to conflicting constraints that affect its usability in the context of UQ. A case study demonstrating how that UQ strategy can be used to explore the prediction and uncertainty of surface porosity in two dimensions was conducted. The architecture of the suite of algorithms constituting the UQ framework, including the surrogate models, was rendered more user-friendly under the sponsorship of the Jet Propulsion Laboratory (JPL) and is now accessible to both NASA Ames Research Center (ARC) and JPL. The uniform property surrogate model could potentially constitute the basis for the development of forward-process control strategies. However, its validation is still limited, and a more extensive effort is needed in that area. The availability of the model permits a wide-ranging sensitivity analysis that is on-going under JPL sponsorship. The experimental investigation of the complex interactions between process parameters, powder characteristics, and dominating physical phenomena during the laser melting process showed that normalized enthalpy should be used as basis to judge the quality of single tracks. A design of experiment study conducted on three-dimensional builds showed that components printed with minimal energy inputs exhibit both higher top-surface longitudinal stress values and higher vertical displacement of free end after wire-EDM cut were performed on the samples. The work was conducted at UC Davis and UC Irvine in close collaboration with teams at the Lawrence Livermore National Laboratory and at NASA ARC. The collaborations with both LLNL and NASA ARC are continuing beyond the period of performance and these activities led to the development of new collaborations with JPL. This project constitutes a necessary step toward a scientifically based numerical prediction of the SLM process which will enable the certification of components manufactured using SLM techniques for use in mission-critical roles.","infoText":"Closed out","infoTextExtra":"Project closed out","isIndirect":false,"technologyOutcomeRationalePretty":"","infusionPretty":"","isBiDirectional":false,"technologyOutcomeDateString":"Jan 2019","technologyOutcomeDateFullString":"January 2019","technologyOutcomePartnerPretty":"","technologyOutcomePathPretty":"Closed Out"}],"libraryItems":[{"files":[],"libraryItemId":364049,"title":"Project Website","libraryItemType":"Link","url":"https://www.nasa.gov/directorates/spacetech/home/index.html","projectId":91489,"internalOnly":false,"publishedDateString":"","entryDateString":"01/22/25 01:10 AM","libraryItemTypePretty":"Link","modifiedDateString":"10/25/24 02:23 PM"}],"states":[{"abbreviation":"CA","country":{"abbreviation":"US","countryId":236,"name":"United States"},"countryId":236,"name":"California","stateTerritoryId":59,"isTerritory":false}],"endDateString":"Jan 2019","startDateString":"Jan 2015"}}