Entity

Time filter

Source Type

Park City, UT, United States

Grant
Agency: Department of Commerce | Branch: National Institute of Standards and Technology | Program: SBIR | Phase: Phase II | Award Amount: 300.00K | Year: 2016

Additive manufacturing lacks efficient, composable physics-based computational frameworks to predict quality and performance for arbitrary geometry, orientation, location and process parameter combinations. A new set of composable computational tools capable of accurately predicting the geometrical accuracy, residual stress and microstructure of the parts made using metal based AM has been developed. The tool(s) demonstrate scaling and composability of models to support geometry-independent reusability while providing a range of parameter values (e.g. user-defined build orientation, laser power, scan speed, hatch pattern, recoat time, material properties, powder layer thickness, choice of mesh motifs, and more) supporting reliability and accuracy.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase I | Award Amount: 149.73K | Year: 2015

ABSTRACT:Additive Manufacturing (AM) technologies are bringing significant new capabilities to manufacturing. However, a number of technical challenges remain before these capabilities can be fully exploited. The design, modeling and data management tools developed for subtractive, formative and mold-based manufacturing are not well suited for additive processes that allow pointwise and layerwise specification and control of 3D part fabrication. Specific challenges remain in specifying and designing material variations within a part, in utilizing process model information during the design process, in transmitting design decisions to various commercial AM machines, and in capturing process monitor data for part qualification. Currently there is no single integrated software solution to capture and manage large volumes of complex AM data. 3DSIM will leverage our knowledge, experience, and understanding to synthesize a comprehensive AM data management tool to capture, manage, and manipulate AM data sets. Specifically, 3DSIM proposes to develop a AM data management tool that would bridge the gap between existing CAD tools and proprietary AM planning and processing software, incorporate process modeling and process monitoring data, and further enable the potential of AM technologies.BENEFIT:An effective AM data management strategy will encompass all types and ranges of data that may be required for current and future AM processes. Such a strategy will fundamentally prescribe part shape, and will also provide a format for specifying location-specific properties of the part. The AM data management tool will support the expanding qualification, certification, simulation and design capabilities of AM users.


Grant
Agency: Department of Defense | Branch: Navy | Program: SBIR | Phase: Phase I | Award Amount: 79.77K | Year: 2015

Additive Manufacturing (AM) is of increasing interest for production of Naval aircraft components. The geometric complexity, mechanical properties, and cost competitiveness for small lot production make AM techniques particularly suited for Ti-6Al-4V aircraft applications. However, microstructural and material property variability issues inherent to AM make rapid qualification of metal AM parts difficult. 3DSIM has significant experience with thermal modeling of metal laser sintering of Ti64, including prediction of Ti64 phases and phase transitions. These models have been validated experimentally over several years of research at the University of Louisville. To fully predict microstructural evolution in Ti64, accurate prediction of the initial crystal microstructure and subsequent solid state phase transitions is required. However, accurate prediction of initial microstructure is difficult to validate using Ti64 due to solid state phase transformations. To address Phase I objectives, 3DSIM proposes to: develop algorithms which predict microstructural characteristics, including phase evolution, grain size and grain orientation, from metal AM thermal histories; conduct validation of the predicted microstructural characteristics by comparison with as-built microstructures for metal laser sintered CoCrMoC parts; and conduct validation of the predicted microstructural characteristics by comparison with as-built microstructures for LENS-deposited Ti64 parts.

Discover hidden collaborations