Microstructure Design for a Turbine Disk

Sintay, Stephen D.; Adams, Brent L.

doi:10.1115/detc2004-57645

Cited by 2 publications

(8 citation statements)

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“…To prepare the 9 and 41 region models as phantoms, two implicit (voxel based) simulated materials models are created using mbuilder [4,24,27,28]. mbuilder is the name given to a collection of software tools and reconstruction strategies developed at Carnegie Mellon University for generation of digital polycrystalline materials.…”

Section: Methodsmentioning

confidence: 99%

“…As mentioned previously, the output of mbuilder is an implicit representation of a polycrystalline material. The explicit geometries of the 9 and 41 region phantoms are created using the dual grid reconstruction algorithm [27]. The dual grid algorithm first identifies the quad points of the 3D implicit microstructure and it then proceeds to use the dual grid of the image to connect and deform the triple lines that connect the quad points.…”

Section: Methodsmentioning

confidence: 99%

“…The persistence of the mean width error across all resolutions indicates that the geometry extraction techniques presented in [27] are not capable of modeling mean width accurately. Recall that mean width is a measure of curvature (see equation ( 1)); therefore the mean width errors in the bottom row of figure 5 suggest that there is a limitation of the reconstruction methods for capturing curvature accurately.…”

Section: Region Per Cent Error Versus Resolutionmentioning

confidence: 99%

“…The goal of this paper is to test the accuracy of a geometry extraction algorithm on a series of 3D images generated from digital phantoms of polycrystalline materials. Two phantoms, 9 and 41 regions respectively, are prepared, sampled and then explicit representations reconstructed using a dual grid based algorithm [27]. The accuracy of various features of the reconstructions are determined by comparing the phantoms with the reconstructed geometries.…”

Section: Introductionmentioning

confidence: 99%

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Testing the accuracy of microstructure reconstruction in three dimensions using phantoms

Sintay

Rollett

2012

Modelling Simul. Mater. Sci. Eng.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Region Per Cent Error Versus Resolutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Testing the accuracy of microstructure reconstruction in three dimensions using phantoms

Sintay

Rollett

2012

Modelling Simul. Mater. Sci. Eng.

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“…Furthermore, unlike CPFEM, the CPFFT method does not suffer from the challenges associated with creating meshed microstructures, which is non-trivial. For example, an entire thesis has been devoted to microstructure representation using meshes [45].…”

Section: Dld Process Modelingmentioning

confidence: 99%

A multi-scale, multi-physics modeling framework to predict spatial variation of properties in additive-manufactured metals

Herriott

Kouraytem

et al. 2019

Modelling Simul. Mater. Sci. Eng.

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The microstructure of additively manufactured (AM) metals has been shown to be heterogeneous and spatially non-uniform when compared to conventionally manufactured metals. Consequently, the effective mechanical properties of AM-metal parts are expected to vary both within and among builds. Here, we present a framework for simulating process-(micro)structureproperty relationships of AM metals produced via direct laser deposition (DLD). The framework predicts grain nucleation and competitive growth as a function of thermal history for a multi-pass, multi-layer DLD process. The resulting three-dimensional microstructure is automatically sub-sampled to perform virtual mechanical testing throughout the build domain using a parallelized elasto-viscoplastic fast Fourier transform code, accounting for grainboundary strengthening. The effective stress-strain response of each subsampled volume is automatically analyzed to extract effective mechanical properties, which are used to generate property maps showing the spatial variability of effective mechanical properties throughout the simulated build volume. As a demonstration, the framework is applied to different DLD stainless steel 316L build volumes having different process-induced microstructures. The multi-physics framework and property maps could provide a path toward qualification of AM-metal parts.

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Microstructure Design for a Turbine Disk

Cited by 2 publications

References 0 publications

Testing the accuracy of microstructure reconstruction in three dimensions using phantoms

Testing the accuracy of microstructure reconstruction in three dimensions using phantoms

A multi-scale, multi-physics modeling framework to predict spatial variation of properties in additive-manufactured metals

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