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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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273 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Nuclear Structure and Decay Data for A=35 Isobars

Here, this work presents a comprehensive and critical evaluation of experimental nuclear spectroscopic data from reactions and decays for all 11 known nuclides with mass number 35 (Ne, Na, Mg, Al, Si, P, S, Cl, Ar, K, Ca). Recommended values are produced for level energies, spins and parities, half-lives, and radiation properties including energies, branching ratios, and multipolarities of γ rays, as well as characteristics of β radiation decays, based on a rigorous assessment of all available experimental data. Discrepancies among existing results are carefully addressed. This work supersedes earlier full evaluations of A=35 published by 2011Ch48, 1990En08 (also 1998En04 update) and 1978En02.

Sun, Lijie [Michigan State University, East Lansin↗
NASA NTRS1992

An improved heat transfer configuration for a solid-core nuclear thermal rocket engine

Interrupted flow, impingement cooling, and axial power distribution are employed to enhance the heat-transfer configuration of a solid-core nuclear thermal rocket engine. Impingement cooling is introduced to increase the local heat-transfer coefficients between the reactor material and the coolants. Increased fuel loading is used at the inlet end of the reactor to enhance heat-transfer capability where the temperature differences are the greatest. A thermal-hydraulics computer program for an unfueled NERVA reactor core is employed to analyze the proposed configuration with attention given to uniform fuel loading, number of channels through the impingement wafers, fuel-element length, mass-flow rate, and wafer gap. The impingement wafer concept (IWC) is shown to have heat-transfer characteristics that are better than those of the NERVA-derived reactor at 2500 K. The IWC concept is argued to be an effective heat-transfer configuration for solid-core nuclear thermal rocket engines.

John S Clark↗
DOE OSTI2026

Stoichiometric effects on grain growth in zirconium carbide coatings for high-temperature nuclear fuel

Interest in coated particle fuel for space nuclear propulsion (SNP) has expanded in recent years due to successful demonstrations of the resiliency of the coatings to extreme environments. For SNP applications, the coating layer for the particle design needs to be able to withstand exposure to high temperature hydrogen during operating conditions. ZrC has been proposed as a protective layer, however, it is important to understand the high temperature behavior to ensure adequate protection to this fuel. In this study, surrogate ZrC coated particles were heat treated at 1900 °C up to 300 min, to examine how the microstructure evolves when exposed to high temperature. Scanning electron microscopy and electron backscatter diffraction (EBSD) were conducted to determine grain size and grain boundary character and orientation to determine the degree of change in the ZrC layer post heat treatment. Raman spectroscopy provided insight to understand how the as-fabricated stoichiometry of each sample contributed to the differences in grain growth behavior. Despite the as-fabricated samples showing a similar initial grain size and grain boundary character, the samples with a higher amount of excess carbon exhibited smaller grain areas and slower growth rates when exposed to 1900 °C. In conclusion, this investigation details the as-fabricated microstructure of the ZrC layer, specifically grain size, evolved under high temperature as this can impact the performance of the fuel under operating conditions.

EBSD↗
DOE OSTI2026

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗
DOE OSTI2025

Effect of magnetic fields on Urca rates in neutron star mergers

Isospin-equilibrating weak processes, called “Urca” processes, are of fundamental importance in astrophysical environments like (proto-)neutron stars, neutron star mergers, and supernovae. In these environments, matter can reach high temperatures of tens of MeVs and be subject to large magnetic fields. We thus investigate Urca rates at different temperatures and field strengths by performing the full temperature and magnetic-fielddependent rate integrals for different equations of state. We find that the magnetic fields play an important role at temperatures of a few MeV, especially close to or below the direct Urca threshold, which is softened by the magnetic field. At higher temperatures, the effect of the magnetic fields can be overshadowed by the thermal effects. Finally, we observe that the magnetic field influences the neutron decay rates more strongly than the electron-capture rates, leading to a shift in the flavor equilibrium.

electroweak interactions in nuclear physics↗
NASA NTRSDate not supplied

SERENE: Saturn Enceladus Return Explorer with Nuclear Electric Propulsion

A ‘quick’ Enceladus sample return mission concept was developed based on the scientist recommendations at the recent ‘Accelerating Space Science with Nuclear Technology Workshop’. The Nuclear Electric Propulsion spacecraft assumed a follow-on 40 kWe nuclear reactor using the demonstrated 40 kWe Fission Surface Power system, expected in the early 2030s. The NEP vehicle also utilized a set of NEXT-C ion thrusters as well as planned Artemis commercial launchers. By launching the 40 kW NEP vehicle on a Starship and adding the propellants of 15 tankers, the 27t probe could be sent on a direct trajectory to Saturn (no Earth or Jupiter flybys) where NEP was used for Saturn capture, spiral down, spiral up and return to the Earth. A small lander obtained the surface Enceladus sample. Using the 40 kW NEP provided a round-trip time of only 16.5 years. A second option was more attractive from a science perspective whereby the NEP vehicle would deliver a large, 6t chemical lander to low Enceladus orbit where it would grab and return a sample to Earth (similar to the recent Orbilander design but in reverse). After deploying the lander, the NEP vehicle would stay in Saturn space performing a moon tour by orbiting four more moons and mapping the large moon of Titan. This option took slightly longer (18.5 yrs) due to the chemical return leg limitations. Both options demonstrated the agility, payload capability, and sample return goals the workshop recommended. An all-chemical option with two stages was roughly analyzed but took 21.5 yrs and required a Jupiter gravity assist.

Nuclear Electric Propulsion↗
NASA NTRSDate not supplied

NASA’s Electric Propulsion Development Activities for Space Nuclear Propulsion Applications

Given increased worldwide support for advanced nuclear technology for terrestrial applications, there is a renewed interest in the possibility of nuclear-reactor-powered spacecraft. NASA continues investing in the technology areas necessary to support NASA’s future scientific and exploration goals. One of those technologies areas is electric propulsion, a highly efficient means for in-space propulsion that increases fuel economy by ionizing and accelerating an onboard propellant using spacecraft electrical power. The current NASA portfolio of electric propulsion investments in support of space nuclear applications focuses on a range of future applications with total system power levels of 50 kilowatts to multimegawatt. These investments support a fast-paced incremental rate for technology development advancement to support these applications. Systems at the 50-kilowatt power level can be accomplished today with existing technology and systems at the multimegawatt level will require further technology developments over the coming decade. Propulsion systems based an array of multiple Hall thrusters have been identified the most likely technology option for the near-term applications and systems utilizing lithium-fueled magneto-plasma-dynamic thrusters have been identified as the most promising alternative technology option for the far-term applications at very high-power levels.

Electric Propulsion↗
NASA NTRSDate not supplied

NASA’s Electric Propulsion Development Activities for Space Nuclear Propulsion Applications

Given increased worldwide support for advanced nuclear technology for terrestrial applications, there is a renewed interest in the possibility of nuclear-reactor-powered spacecraft. NASA continues investing in the technology areas necessary to support NASA’s future scientific and exploration goals. One of those technologies areas is electric propulsion, a highly efficient means for in-space propulsion that increases fuel economy by ionizing and accelerating an onboard propellant using spacecraft electrical power. The current NASA portfolio of electric propulsion investments in support of space nuclear applications focuses on a range of future applications with total system power levels of 50 kilowatts to multimegawatt. These investments support a fast-paced incremental rate for technology development advancement to support these applications. Systems at the 50-kilowatt power level can be accomplished today with existing technology and systems at the multimegawatt level will require further technology developments over the coming decade. Propulsion systems based an array of multiple Hall thrusters have been identified the most likely technology option for the near-term applications and systems utilizing lithium-fueled magneto-plasma-dynamic thrusters have been identified as the most promising alternative technology option for the far-term applications at very high-power levels.

Electric propulsion↗
DOE OSTI2025

Imprints of High-Density Nuclear Symmetry Energy on Crustal Fraction of Neutron Star Moment of Inertia

The density dependence of nuclear symmetry energy E sym (ρ) remains the most uncertain aspect of the equation of state (EOS) of supradense neutron-rich nucleonic matter. Utilizing an isospin-dependent parameterization of the nuclear EOS, we investigate the implications of the observational crustal fraction of the neutron star (NS) moment of inertia ΔI/I for the E sym (ρ). We find that symmetry energy parameters significantly influence the ΔI/I, while the EOS of symmetric nuclear matter has a negligible effect. In particular, an increase in the slope L and skewness J sym of symmetry energy results in a larger ΔI/I, whereas an increase in the curvature K sym leads to a reduction in ΔI/I. Moreover, the ΔI/I is shown to have the potential for setting a lower limit of symmetry energy at densities exceeding 3 ρ 0 , particularly when L is constrained to values less than 60 MeV, thereby enhancing our understanding of supradense NS matter.

equation of state↗
NASA NTRSDate not supplied

Preliminary Findings of the Experimental Development Unit Cold Flow Test for a Generation Zero Nuclear Propulsion Engine

Nuclear thermal propulsion (NTP) technology will greatly benefit human travel to Mars by significantly shortening transit times, improving crew safety, and providing more mission flexibility than traditional chemical rockets. As part of DRACO follow-on work to develop, build, and fly a generation zero NTP engine, a full scale flight-like experimental design unit (EDU) reactor was constructed to collect sufficient on-ground performance data to characterize flow induced vibrations (FIV) of critical reactor structures/components, inform development of the engine and reactor control algorithm, and collect pressure drop and flow distribution data across the reactor. The fluid conditions for the test program were designed to achieve system responses equivalent to that of an operational engine through all phases of engine operation including reactor startup, mainstage operation, reactor shutdown, and reactor cooldown. Over 100 tests were executed, flowing either GN2 or GHe through the EDU at varying flow rates and pressures. This experiment provided early validation of flow behavior and vibration risks before nuclear testing, boosted critical subsystem TRLs, informed design iterations, and reduced future test costs. The steady-state flow parameters for the experiment were modeled in Ansys Thermal Desktop, allowing rapid tuning and experiment-informed updates to a flight-like test matrix. The EDU dynamic environment was characterized with accelerometers, strain gauges, and high-frequency pressure transducers all sampled at 20 kHz. While many narrow-band oscillations were identified, no significant FIV occurred; the reactor structural responses tend to be enveloped by typical launch vehicle ascent vibration environments (defined up to 2 kHz), although significant energy is also present at higher frequencies.

Flow Induced Vibration↗
DOE OSTI2026

The Role of Nuclear Data Sensitivities in Prompt α-Eigenvalue Predictions of Delayed Critical Benchmarks

Alpha (α) eigenvalues, which describe the logarithmic time derivative of the neutron population in a multiplying system, are integral to time-dependent behavior and diagnostic applications. However, uncertainties in the evaluated nuclear data can significantly impact the accuracy of transport simulations for such quantities. This work explores the use of machine learning models to predict two key outputs, α-eigenvalues and keff bias, using input features derived from α-eigenvalue sensitivities to nuclear data. The criticality safety benchmark models used in this study come from the International Handbook of Evaluated Criticality Safety Benchmark Experiments. Three models, random forest, XGBoost, and NGBoost, are trained on both energy-resolved and energy-summed α sensitivities. For the α-eigenvalue bias prediction, NGBoost achieved the highest R 2 (0.9476) using energy-resolved features, while XGBoost performed best using summed sensitivities. In contrast, when predicting the keff bias, all the models showed moderate predictive capability (best R 2 ≈ 0.72), as the mapping from the static α-sensitivities to the static keff bias was less direct. SHAP (SHapley Additive exPlanations) analysis was used to interpret the model predictions. Across both prediction tasks, the features associated with neutron capture [H-1 (n, γ)], uranium scattering reactions (such as 235 U elastic/inelastic), and actinide capture/fission reactions (such as 239 Pu and 234 U) were consistently identified as the most impactful. This highlights the key role of specific nuclear reactions and energy ranges in shaping both time-dependent and steady-state criticality behavior. These results demonstrated that α-sensitivities, despite being computed for time-dependent metrics, can provide valuable insights for predicting both α-eigenvalues and the keff bias. Moreover, machine learning models offer a promising pathway for uncovering important nuclear data dependencies and guiding future data evaluation efforts.

Nuclear data↗
DOE OSTI2026

Mechanical and durability properties of ultra-high-performance concrete of spent nuclear fuel dry storage systems: a review

Dry storage systems are used for interim storage of spent nuclear fuel (SNF). However, with the growing need to extend the operational periods of these systems, there are concerns about the degradation of their concrete overpacks, which could compromise the system's structural integrity and safety during hazardous events. Traditional concrete mixtures used in SNF dry storage systems have remained largely unchanged since their inception and often use conventional ingredients. These materials are susceptible to degradation mechanisms such as chemical attacks, alkali-silica reactions (ASR), and freeze–thaw cycles, which can lead to a loss of strength and durability over time. To address these challenges, this paper reviews the application of ultra-high-performance concrete (UHPC) as a promising alternative for spent nuclear fuel dry storage system overpacks. UHPC offers superior mechanical properties, exceptional durability, and reduced susceptibility to degradation mechanisms compared to conventional concrete. This paper focuses on the role of supplementary cementitious materials (SCMs) such as silica fume, fly ash, and metakaolin in enhancing UHPC performance for SNF storage applications. These SCMs have been shown to significantly improve the material’s microstructure, strength, and resistance to environmental stressors typically encountered in SNF storage environments. Moreover, incorporating SCMs supports sustainable construction by reducing cement consumption and associated carbon emissions. The review brings together existing research and experimental data, providing insights for engineers and researchers on developing UHPC mixtures that meet the rigorous demands of spent nuclear fuel dry storage systems, extending their service life and minimizing inspection intervals.

36 - MATERIALS SCIENCE↗