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Results for “THERMAL EXPANSION”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

Crystal structure, compressibility, and thermal expansion of uranium mononitride

The behavior of the uranium mononitride (UN) crystal structure at nonambient conditions is disputed, with studies proposing various mutually exclusive distortions and transformations of the conventional face-centered-cubic structure at extreme temperatures and pressures. Here, in this study, we investigated the UN lattice with diamond anvil cell x-ray diffraction experiments at pressures up to 92 GPa and with density functional theory calculations at temperatures up to 1000 K and pressures up to 90 GPa. We determined that while the UN structure is nearly cubic at ambient conditions, its lattice angle (𝛼) varies as a function of pressure and temperature, meaning its structure can be more precisely described as face-centered-rhombohedral with 𝛼 ≈ 90∘. Over the range of conditions we investigated, UN exhibits a single, isostructural phase transition at ≈ 35 GPa, where 𝛼 collapses to ≈ 86°. Measurements and calculations agree that the compressibility of UN increases significantly beyond this transition, with the bulk modulus falling from ≈ 200 GPa in the low-pressure phase to 121 ± 3 GPa (according to calculations) or 58 ± 4 GPa (according to measurements) in the high-pressure phase. Our measurements also allowed us to constrain the bulk modulus of 𝛼−U 2 ⁢N 3 to 240 ± 10 GPa.

36 MATERIALS SCIENCE↗

Machine-Learning-aided Approach for Predicting the Thermal Expansion Behaviors in Advanced Test Reactor Capsules (NURETH-20 full paper)

Instrumented experiments at test reactors are essential to deploying new advanced reactor systems. Designing new experiments and generating data on specific conditions require both time and cost investment. A high-fidelity model of the experiment environment can be created using finite element analysis software to support the actual experiments, but computation time is still a concern in applying outcomes to real-time usage (e.g., a digital twin). This research proposes a machine-learning-aided approach to temperature and displacement predictions, based on the thickness of the outer gas gap on the experimental capsule used for the in-pile demonstration of a novel thermal conductivity probe in the Advanced Test Reactor. The capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. There were gas gaps between the fuel and rodlet and between the inner and outer capsule. The learning data consisted of an experimental capsule’s radial distributions of temperature and displacement, as obtained from Abaqus and the physical features. For the first step, temperature was predicted using three positional parameters. Then the displacement was predicted using six different positional parameters. Each physical feature was normalized to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement in all cases involving interpolation and extrapolation. Also, data similarity enhancement increased the similarity between training and target data increasing the predictive accuracy of machine-learning models. In some cases of extrapolation, the accuracy of the machine-learning model showed limited performance, but still data similarity enhancement improved the accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modeling The Effects of Loading Scenario and Thermal Expansion Coefficient on Potential Failure of Cryo-compressed Hydrogen Vessels

A multiscale thermomechanical model for a simplified Type-3 cryogenic compressed hydrogen (H2) storage vessel is developed in this paper. The model accounts for the temperature-dependent elastic-plastic behavior of the vessel carbon/epoxy composite overwrap and aluminum alloy liner. The homogenized thermo-elastic-plastic behavior for the individual laminas of the vessel layup is obtained by an incremental Eshelby-Mori-Tanka approach associated with a micromechanical failure criterion to predict lamina failure while a standard elastic-plastic constitutive model is used to describe the behavior of a typical aluminum alloy assumed for the liner. The vessel response to external loadings is achieved by a finite element method. Four loading scenarios representing four thermomechanical cycles applied to the vessel are analyzed to evaluate constituent and lamina stresses as well as the associate failure criterion during the cycle according to these scenarios. The model can provide helpful guidance to mitigate thermal stresses by an adequate selection of loading scenario, optimizing the layup and by tailoring thermomechanical properties of the resin matrix.

36 MATERIALS SCIENCE↗