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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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61 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Molten Salt Reactors: What about Materials? An Overview and Future Needs

ORNL Molten Salt Reactor Experiment (MSRE) – 60’s- early 70’s Developed INOR-8 (aka Hastelloy N); MSRE operated over the period Dec 1965 to 1969. (not continuous); Operated for >13,000 hr at T from ~550 to ~650°C using U, Li-7, Be and Zr fluoride salt fuel; Post-Irradiation Material Evaluation (corrosion + neutron irradiation) of surveillance specimens; Noted ”beneficial effect of Nb” in alloy (on intergranular Te embrittlement) More recent (post-1980) Materials R&D for Gen IV …. Alloys 316L, 316H, 304, Alloy 800H, Alloy 617 (!!), Hastelloy N (mod), plus numerous experimental alloys developed

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Experimental measurements of fluid flow in an 84-pin hexagonal rod bundle with spacer grid for a gas-cooled fast modular reactor

A 50 MW e helium-cooled fast modular reactor (FMR) is under development, and as part of the Department of Energy Integrated Research Project (IRP), Texas A&M University is conducting the thermal-hydraulic characterization of its baseline core configuration. Here, we experimentally investigated the axial and cross flow fields characteristics in the hexagonal fuel rod bundle composed of 84 rods, a central rod, and spacer grids at a Reynolds number of 12,000. A fully transparent experimental facility resembling of one unit of the fuel assembly was constructed. Time-resolved particle image velocimetry (TR-PIV) measurements were performed to characterize hydraulic behavior downstream the spacer grid. Velocity measurements were conducted in the axial and radial direction of the rod bundle. From the PIV velocity vector fields, the full-field flow statistics were computed for the mean velocity, vorticity, and Reynolds stresses. An analysis of the energy decay downstream of the spacer grid was conducted with calculations of secondary-flow intensities, turbulent kinetic energy, power spectrum, and spatial-temporal velocity cross correlations. The vorticity field was obtained and pairs of counter-rotating vortexes were identified using a 3D reconstruction of several measurement planes. The data from this experimental campaign will be used to validate numerical models based on Computational Fluid Dynamics and other codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Design and Development of Novel Equiatomic Refractory Multi Principal elemental Alloys Based on MoNbTi System for Use in Irradiation Environments

Multi Principal Elemental Alloys (MPEA) have emerged as promising materials for next-generation nuclear reactors due to their exceptional irradiation resistance. Eight equiatomic MPEA based on the MoNbTi system, comprising of elements with low thermal neutron absorption cross-sections were explored using a combined approach employing empirical parameter estimations, and CALPHAD simulations by which the phases and elemental segregation observed in all the alloys in the as-cast state were predicted. Solution heat treatment at 1500°C transformed five alloys into single-phase matrix materials, enhancing homogeneity and reducing hardness. The densities of the alloys ranged between 6.47 to 7.68 g/cm3, hardness between 472 and 656 VHN, Young’s modulus between 142 GPa to 169 GPa, shear modulus between 54 GPa and 62 GPa, bulk modulus between 117 GPa to 194 GPa and Poisson’s ratio between 0.3 to 0.35. The in-situ high temperature Xray diffraction results, differential scanning calorimetry and dilatometry results up to 1000°C suggested the high temperature phase stability of the MPEA. Subsequent ageing heat treatment at 800 and 1000 oC for 96 hours revealed significant secondary phase precipitation in MoNbTiZr, MoNbTiZrV, and MoNbTiCrA. Oxidation studies at 800 oC for 24 hours in air revealed superior oxidation resistance and cubic rate law dependence in Cr containing MPEA especially in MoNbTiCrAl, while severe mass gain resulting in total disintegration and exfoliation in MoNbTiZr and MoNbTiZrV. This comprehensive study underscores the potential of novel MPEA as promising materials for advanced nuclear reactor applications, shedding light on their microstructural control, mechanical properties, thermal stability, and oxidation resistance.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Metallic Fuels Beyond SFRs

Metallic nuclear fuels have traditionally been used for sodium cooled fast reactor applications, but recent work has been done in applying metal fuel technologies to the light water reactor and molten salt reactor spaces. This presentation offers a brief history of metallic fuel use in SFRs and an overview of metallic fuel uses in the LWR and MSR spaces.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Replace Human Intelligence with Fast and Smart Geometric Reasoning and Graph Neural Network to Accelerate Next Gen ModSim Workflows

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

97 MATHEMATICS AND COMPUTING↗