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Multi-scale analysis and simulation in 3D crystal plasticity large deformation finite element platforms to predicting and designing thermomechanical responses of metallic nano-layers
Crystalline nano-layers formed by alternating nanoscale metallic lamellae exhibit exceptional physicochemical attributes notably depart from those of the bulk counterparts. This work centers on theoretical concepts and computational approaches to simulate, predict, and design metallic nano-layers thermomechanical responses in crystal plasticity large deformation finite element platforms. The novelty of the work is in the essence of a fundamentally multi-scale method coupled with artificial intelligence techniques to provide a predictive model of deformation in a class of materials for which a model that can address changes in properties of individual layers in a predictive manner has not been properly dealt with. The present study utilizes diverse theoretical domains including thermodynamical entropic kinetics and statistical analyses in order to create a robust framework capable of addressing the main features and mechanisms of metallic nano-systems in diverse setups. Here, thermomechanical properties in nano, micro, and homogenized levels are individually analyzed where associated novel constitutive models are developed followed by implementing those in a three-dimensional object-oriented code. Sensitivity analyses are performed by realizing the prioritized constitutive parameters with decisive impacts on the behavioral main features of these nano-composites. Ultimately, precipitate strengthening is investigated through specific dominated mechanisms and particle morphologies. The entire process at each spatial spectrum is in solid agreement with experimental data and highly capable of delivering precise, targeted responses in a variety of loading and spatial conditions.
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