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RAP opportunity at National Institute of Standards and Technology NIST Scientific machine learning methods for trustable accelerated materials characterization and design Location Material
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RAP opportunity at National Institute of Standards and Technology NIST Burning Velocity Measurement and Predictive Methods for Marginally Flammable Refrigerants Location Engineering Laboratory
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Advanced Materials and Methods for Quantitative Nuclear Magnetic Resonance Spectroscopy: Standardization for the Second Century of Analytical NMR NIST only participates in the February and August
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properties to them, generates a finite element mesh, and performs virtual measurements. The goal is to build a computational platform that can predict the macroscopic behavior of a material from knowledge of
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on nondestructively measured properties and associated mechanical performance. key words Additively Manufactured Materials; Nondestructive Evaluation; NDE; Ultrasonics; Resonant Acoustics; X-ray CT; Finite-element
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Computational Methods for NMR Structural Biology and Biomanufacturing of Protein and Live Cell Therapeutics NIST only participates in the February and August reviews. Protein therapeutics
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experiments and datasets for model validation of multi-phase computation fluid dynamics (CFD), discrete element method (DEM), or data-driven modelling. Measurement of defect types and populations using micro- x
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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. Keywords Blast loading; Computational modeling; Finite element
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; Defect nucleation; Density functional theory; Embedded atom method; Finite element modeling; Molecular dynamics; Multiscale modeling; Nanoindentation; Nanomechanics; Eligibility citizenship Open to U.S