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3 Enabling Tools and Databases
Pages 34-44

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From page 34...
... have made computational materials design based on mechanistic models a principal recommendation for research investment.2,3 ESTABLISHED COMMERCIAL PRACTICE: ACCELERATED DEVELOPMENT The aerospace original equipment manufacturer (OEM) community in particular has established a viable track record in the computation-assisted, accelerated development of materials and processes.
From page 35...
... discussed practices that are well established for the application of technical cost modeling tools throughout the development cycle. Based in a process cycle context, these tools allow the quantitative consideration of the economic consequences of choices regarding material, process, and design, with the goal of anticipating opportunities and tactical choices at very early stages while the costs of change are still small.
From page 36...
... The teams have integrated OEM, small company, university, and government laboratory activities in an IPT approach, to establish a new framework and methodology for the integration of available tools in the accelerated development and qualification of new materials and processes. The Phase I effort successfully demonstrated the ability of the methods to efficiently reconstruct both optimal processing conditions at the component level and observed property variation as established by legacy databases of existing materials; it also provided preliminary demonstrations of effective prediction of improved processing conditions for these materials.
From page 37...
... A natural consequence of the new linked concurrent materials modeling capability, however, has been to create a new, active form of DKB in which the system designer can assess process and property trade-offs on the basis of estimated properties as an active part of the system design process. An example presented by Schirra at the workshop from the AIM metals program indicates that active linking of materials models to the integrated design of a subscale disk and its thermal processing accurately predicted improved performance and failure modes validated in actual disk burst tests.
From page 38...
... Adopting a mechanistic approach in which property variation is tied back to process and composition variation through predictable microstructural variation, the numerical precipitation code has served as the central transfer function allowing extensive supply-chain legacy process data to be transformed into predicted property variation under the AIM metals program. The exercise demonstrated multisite computation under the iSIGHT integration system linking distributed software capabilities in Connecticut, Utah, and Illinois; the exercise combined heat transfer, microstructure, and property calculations under a Monte Carlo simulation, incorporating known process variation as well as quantified variation in model parameters such as surface heat transfer coefficients.
From page 39...
... In contrast to the intensive characterization effort that was essential for the DARPA-AIM capability demonstrations on existing turbine disk alloys, the inherent predictability of materials designed this way makes them suited for more efficient accelerated development and qualification, applying the same models and validation results that created them in the first place. As a specific example, the efficacy of computational materials design has been demonstrated with a family of high-performance gear and bearing steels designed to exploit capabilities of high 5 G.B.
From page 40...
... temperature carburizing processes.6 Aided by process modeling based on the DICTRA multicomponent diffusion code, control of the new processing has enabled consistent achievement of new performance levels in automotive gearing, providing winning results on the racetrack, in parallel with certification testing for critical aerospace applications. These designs have spanned a range of materials, including high-performance shape memory alloys, metallic glasses, and ceramic systems.
From page 41...
... The issues surrounding bringing modern engineering practices to such academic institutions as research universities and national laboratories has been a much-discussed issue in recent years. From the perspective of education, a series of workshops at Harvey Mudd College7 has broadly addressed the challenges and opportunities for embedding a new design culture across all engineering disciplines including materials.8 Under the current academic system, substantial investment in computational materials science has produced a wide array of computational tools.
From page 42...
... While the first demonstrations have integrated empirical materials models, a new level of capability has been demonstrated very recently in the development and application of more predictive mechanistic numerical models under federally funded initiatives such as the DARPA-AIM program. Demonstrated capabilities include the following: accelerated process optimization at the component level, reducing scale-up risk; efficient, accurate forecasting of property variation to support qualification, with reduced testing for early adoption; and the active linking of materials models (exploring broader process and property trade-offs)
From page 43...
... A dissemination initiative should provide ready access to a Web-based source of pre-competitive databases and freeware tools as well as accurate information on the range of existing, commercial software products and services. Integrated product team-based research collaborations should be deliberately structured so as to firmly establish a modern design culture in academic institutions to provide the necessary, pertinent, research and education environment.


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