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RAP opportunity at National Institute of Standards and Technology NIST Dynamic Atomistic Predictions of Crystalline, Crystal Defect and Liquid Metal Properties Location Material Measurement
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RAP opportunity at National Institute of Standards and Technology NIST Fundamental measurements of the metal additive manufacturing process Location Physical Measurement Laboratory, Sensor
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-mechanical processing. Some of these modeling tools include density functional theory (DFT), CALPHAD-based models, phase-field models, and finite-element models (FEM) to predict as-built microsegregation
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materials. The primary focus of this work is on mechanical characterization, microstructural analysis, and finite element analysis (FEA) and artificial intelligence (AI)/machine learning (ML) modeling
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and utilize equipment such as high- and low- field NMR/MRI systems and non-traditional systems such as single-sided magnets. In addition to this equipment, techniques such as finite-element modeling and
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thermomechanical finite element modeling, CALPHAD-based thermodynamics, and crystal plasticity and to both powder-scale and atomic-scale simulations. Emphasis will be on integration of model predictions with
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image correlation (DIC) datasets with fully three-dimensional finite element analysis (FEA) results in mechanical test setups on metals and polymers including uni-axial and bi-axial loading at different
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, Materials and Structural Systems Division opportunity location 50.73.11.C1032 Gaithersburg, MD NIST only participates in the February and August reviews. Advisers name email phone Stephanie J. Watson
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not be effectively analyzed. DIC data are combined with finite element modeling to analyze non-uniform stress and strain states within samples during dynamic loading, and in some cases to deduce
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. Emphasis is placed on model validation against both high-fidelity finite element simulations and experimental tests of structural subassemblies. key words Blast loading; Computational modeling; Finite