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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Petrov, R. H. | Madrid |
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Casati, R. |
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Kočí, Jan | Prague |
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Azam, Siraj |
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Blanpain, Bart |
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Ali, M. A. |
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Rančić, M. |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Farooqi, J.
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Investigating predictive capabilities of image-based modeling for woven composites in a scalable computing environment
Abstract
This paper covers research on preparing a nearly exact 3D composite material model that captures the complexity of a woven textile used in these Carbon-Carbon composites. X-ray microtomography has been used for this purpose. Higher resolution models, necessary to establish phase separation between constituents, form very large data sets that have been accommodated in parallel-processing supercomputers. Basic stress/strain behavior has been simulated with due agreement with experimental results through in-situ measurement in a tension test. Elastic modulus measured through either technique bears decent resemblance to the other, thus validating the image-based modeling route for this and other future applications. © 2008 MS&T'08 ®.