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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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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Analysis of radially resolved thermal conductivity in high burnup mixed oxide fuel and comparison to thermal conductivity correlations implemented in fuel performance codes

The thermal diffusivity and thermal conductivity of high burnup (19 % FIMA) mixed oxide (U, Pu)O 2 nuclear fuel has been measured along the radial direction using a thermoreflectance-based method. Measured thermal conductivity exhibits a notable radial variation consistent with the expectations that a large temperature gradient across the annular fuel pellet leads to a heterogeneous microstructure. A common fuel performance model of thermal conductivity, the Lucuta-Inoue model, is used to analyze the measured thermal conductivity profile. Further, this model adequately captures the radial dependence of thermal conductivity except in the periphery. The analysis suggests that the characteristic radial shape of the thermal conductivity profile follows the burnup profile within the fuel pin. In the periphery, the high burnup structure is formed and the conductivity model, not capturing this effect, likely overestimates the thermal conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Landscape of nuclear deformation softness with spherical quasiparticle random-phase approximation

We investigate the stability and softness of nuclei against quadrupole, octupole, and hexadecapole deformation. By applying the spherical Skyrme-force Hartree-Fock Bardeen-Cooper-Schrieffer quasiparticle random phase approximation, we diagnose ground-state deformation when imaginary solutions are obtained, i.e., the spherical ground state collapses. We also calculate the multipole polarizability in spherical nuclei with no collapse, as a measure of softness. This numerically light and theoretically sound method is found able to capture deformation patterns across the nuclide chart. As a result, the connection between the intrinsic shape of nuclei and the dynamics of their low-lying collective states is established and the role of shell structure is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

High-Fidelity Modeling and Experiments to Inform Safety Analysis Codes for Heat Pipe Microreactors

Heat pipe microreactors are reactor designs that primarily use liquid-metal heat pipes to cool the core. The main interest in heat pipes is the fact that they can remove heat passively. This, along with the use of liquid metal, allows the reactor to operate at higher temperatures. Although the use of heat pipes in nuclear reactors is new, liquid-metal heat pipe technology is mature. Nevertheless, experimental data on heat pipes are scarce, and very little is known about their behavior during abnormal operations and close to their thermal limits. Therefore, new experiments and accurate heat pipe simulations are needed to develop reliable closure models. This work describes a joint experimental and numerical investigation into heat pipes that attempts an initial closure of this gap. Further, the numerical and experimental efforts are currently proceeding in parallel, aimed at different aspects of heat pipes. The numerical part is focused on gaps in local closures, and the experiments capture the overall heat pipe behavior.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

MRWFD Kr Capture Project

Progress report presentation to DOE program representatives.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A view on the current and future impact of research reactors

Full text of publication follows. The current fleet of nuclear research reactors worldwide is nearly 70 years old. These reactors have proven to be extremely valuable tools of nuclear science and engineering with a broad and interdisciplinary impact. To date, research reactors are utilized as tools for understanding the physics, operations, and safety of nuclear fission systems. In addition, they are used as intense sources of radiation in support of irradiation testing and nondestructive examination of materials. As this fleet of reactors ages, an urgent need exists to establish new facilities that can propel the benefit of these reactors into the 21. century. In fact, an opportunity exists to build research reactors based on technology concepts that are being considered for nuclear energy reactors. This may include high temperature gas cooled and/or molten salt based advanced and micro reactor concepts. Such future reactors should be designed to maintain the broad utility of current reactors in research and education. However, modern research reactors can be purposefully designed and instrumented to access neutronic and thermal hydraulic information that would support the development and validation of reactor multi-physics modeling and simulation techniques. In this case, the entire phenomenological paradigm of the reactor may be captured to understand the neutronic multiscale and its impact on operations and safety. Moreover, the generated data can be channeled to drive anticipatory examination of the state of the reactor. In general, a symbiotic relation may be envisioned between the modern research reactor and power reactor fleets, which could facilitate the safe and efficient implementation of clean nuclear energy. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Survey of Dynamic Mode Decomposition Methods

Dynamic mode decomposition (DMD) is a data-driven reduced order modeling (ROM) technique used for dynamic systems. The widely adopted algorithm was first introduced and demonstrated on fluid flow data by Schmid. In recent years, various other fields, such as nuclear engineering, have begun to adopt this method. For example, DMD has been used for estimating α-eigenvalues, as an ROM for pulsed neutron problems, for predicting isotopic composition in burnup calculations, as acceleration techniques for iterative methods, and in capturing dynamic behaviors in molten salt reactor transients. This report seeks to demonstrate the capabilities and limits of the standard DMD algorithm, and identify problem spaces where variants may be better suited. The primary variant this report considers is Multi-Resolution DMD (mrDMD). Because this serves as a survey, synthetically produced data is used in lieu of simulation results. The remainder of this report will go into detail on the DMD theory, outline the standard DMD and mrDMD algorithms, present test cases highlighting the applicability of each, and finally present a discussion on how to determine the best suited algorithm for a given problem. All calculations performed in this report are carried out using the open source DMD library, PyDMD.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Machine Learning Approaches for Nuclear Material Accounting Data from Irradiation and Reprocessing

We are currently exploring data analysis methods for their ability to strengthen the synthesis and evaluation of information generated within domestic and international safeguard regimes. Safeguard data typically includes rich heterogenous datasets amenable to advanced data analytics methods, such as machine learning. We have converted transactional data containing both numerical and categorical attributes from a domestic nuclear material control and accountability (NMC&A) system into a low-dimensional numerical structure via linear principal component analysis. This data representation allows for global structure discovery via cluster analysis, which can characterize the typical behavior of each of the primary types of transaction events. Furthermore, the structure of the top principal components captures the “typical behavior” of the data and is thus amenable to anomaly detection through statistical hypothesis testing. We explored this capability by generating erroneous permutations of the data and computing the Q-residual quantity increase associated with the information loss when these data are projected into the low-dimensional principal component analysis space representative of typical transactions.Future work will focus on identifying data transformations (e.g., graph networks) that more closely align with the inherent structure of these transactions to explain more salient information and disambiguate the underlying nuclear process—in this case, irradiation and reprocessing—from artifacts of NMC&A system transactional record keeping data.

Drescher, Adam↗
DOE OSTI2020

Development of Monitoring Techniques for Binderjet Additive Manufacturing of Silicon Carbide Structures

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear components to be assembled into a fully functional microreactor core. Compared with traditional manufacturing technologies, AM technologies allow (1) observation of the manufacturing process at a much higher resolution in real-time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on binder jetting in situ process monitoring and associated data analytics results, as well as sample placement and tracking for the subsequent chemical vapor infiltration (CVI) process. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Kinetic Plasma Simulation in the MOOSE Framework: Verification of Electrostatic Particle In Cell Capabilities

In magnetic confinement nuclear fusion reactors, the interaction between the plasma edge and plasma facing components is extremely important. At the plasma edge, a kinetic representation such as particle-in-cell (rather than a fluid representation) is required to accurately capture the plasma behavior. General purpose particle-in-cell plasma simulation capabilities have been developed in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. This new capability is a part of the development of a new MOOSE-based framework for modeling plasma facing components, the Fusion ENergy Integrated multiphys-X (FENIX) framework. In this work, the verification of foundational particle-in-cell capabilities in FENIX is presented. This new plasma simulation capability has three main components: moving particles in discrete steps on the finite element mesh, mapping charge density from the particle's location to the finite element mesh, and solving for the electrostatic potential based on the charge density mapped from particles to the mesh. In this paper, simple verification problems demonstrating each of these new capabilities are presented, and future work includes electromagnetic capabilities and Monte Carlo collisions with neutral gas particles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Tritium adsorption and absorption on (100) and (001) surfaces of pure and tin defective zirconium

Zirconium alloys such as zircaloy-4 are used as tritium (T) getter materials in tritium-producing burnable absorber rods (TPBARs) due to their ability to capture T, thereby forming metal hydrides. Developing an understanding of T adsorption onto zircaloy prior to diffusion into the subsurface is relevant for rational tritium getter and TPBAR design, to improve material properties for nuclear applications. Herein, density functional theory calculations revealed the preferred binding sites for T adsorption on Zr(001) and Zr(100). The energy barriers of T transfer, along the surface and from the surface to the subsurface were computed. The adsorption properties of Zr(001) were found to be superior to those of Zr(100). Surface tin impurities were found to strongly repel T. The presence of subsurface and surface tin resulted in higher absorption energy barriers for both the forward and reverse processes. Based on the calculated energy barriers, a surface to surface T diffusion coefficient of 9.53 × 10 -10 m 2 s -1 is expected for pristine Zr(001). Finally, a surface to subsurface T diffusion coefficient on the order of 10 -13 m 2 s -1 is predicted in pristine Zr, decreasing to 10 -19 m 2 s -1 for the transfer with a subsurface tin impurity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Exploration for astromers near 132 Sn with the Canadian Penning Trap

Nuclear isomers can have significant impacts on astrophysical nucleosynthesis processes, with recent efforts demonstrating that the population of isomeric states with different half-lives may require separate treatment in reaction networks to accurately capture the differences in heating or in identifiable electromagnetic signals. Several potential so-called “astromers” in tin and antimony isotopes near doubly magic 132 Sn were identified and direct mass measurements of their ground and isomeric states were performed with the Canadian Penning Trap at Argonne National Laboratory's CARIBU facility, and their impact on astrophysical reaction rates and in reaction networks was calculated. Finally, it was found that 129⁢𝑔,𝑚 Sn , with measured mass excesses of −80593.2⁢(25) and −80557.4⁢(25) keV, respectively, and an excitation energy of 35.8(35) keV, behaves as an astromer during neutron capture in the 𝑖-process and in the 𝑟-process.

isomer decays↗
DOE OSTI2022

Neutron transfer reactions on the ground state and isomeric state of a 130 Sn beam

The structure of nuclei around the neutron-rich nucleus 132 Sn is of particular interest due to the vicinity of the Z = 50 and N = 82 shell closures and the r-process nucleosynthetic path. Four states in 131 Sn with a strong single-particle-like component have previously been studied via the (d,p) reaction, with limited excitation energy resolution. Here, the 130 Sn( 9 Be, 8 Be) 131 Sn and 130 Sn( 13 C, 12 C) 131 Sn single-neutron transfer reactions were performed in inverse kinematics at the Holifield Radioactive Ion Beam Facility using particle-γ coincidence spectroscopy. The uncertainties in the energies of the single-particle-like states have been reduced by more than an order of magnitude using the energies of γ rays. The previous tentative J π values have been confirmed. Decays from high-spin states in 131 Sn have been observed following transfer on the isomeric component of the 130 Sn beam. The improved energies and confirmed spin-parities of the p-wave states important to the r-process lead to direct-semidirect cross-sections for neutron capture on the ground state of 130 Sn at 30 keV that are in agreement with previous analyses. A similar assessment of the impact of neutron-transfer on the isomer would require significant nuclear structure and reaction theory input. There are few measurements of transfer reaction on isomers, and this is the first on an isomer in the 132 Sn region.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Development of Monitoring Techniques for Laser Powder Bed Additive Manufacturing of Metal Structures (Progress Report)

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear grade components to be assembled into a fully functional microreactor core. Compared to traditional manufacturing technologies, additive manufacturing technologies allow (1) observation of the manufacturing process at a much higher resolution in real time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space, and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on laser powder bed fusion in-situ process monitoring and associated data analytics results. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Coolant Pump Predictive Data Analytics from Signatures Generated by the Recursive Short Time Fast Fourier Transform

Although a nuclear reactor is a hostile environment for sensors and signal transmissions, the reactor core is amenable to acoustic communication. An acoustic measurement infrastructure installed at the Advanced Test Reactor (ATR) nozzle trench area records acoustic signals that can capture reactor operating states. The distinct states produce unique signatures that can be identified and tracked using data processing and data analytics. The infrastructure relies on acoustic transmission through ATR in-pile structural components, piping, and coolant that transmit acoustically modified signals generated by the coolant pumps. This paper will discuss results from using the Recursive Short Time Fast Fourier Transform (RSTFFT) technique used to process acoustic signals and provide signatures that are identified and monitored by analytics. The RSTFFT is applied to ATR data to understand the vibration levels and signatures for different operating regimes as displayed by the spectrogram. The combination of coolant pumps for normal and high-power operation generate unique signatures. These acoustic signatures are used to develop machine learning approaches to automatically classify operating regimes. Two machine-learning models, Support Vector Machines and Linear Discriminant Analysis, were developed to classify two event classes. Class 1 is a normal steady-state operation, and Class 2 is any event that is due to start up, shut down, or other actions. Both types of machine learning models had over a 96% prediction accuracy for the two classes. These results lay the foundation for predictive analytic frameworks that can be leveraged by ATR to optimize operations and maintenance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

In-beam γ-ray spectroscopy of 32 Mg via direct reactions

Background: The nucleus 32 Mg (N=20 and Z=12) plays a central role in the so-called “island of inversion,” where in the ground states sd-shell neutrons are promoted to the fp-shell orbitals across the shell gap, resulting in the disappearance of the canonical neutron magic number N=20. Purpose: The primary goals of this work are to extend the level scheme of 32Mg, provide spin-parity assignments to excited states, and discuss the microscopic structure of each state through comparisons with theoretical calculations. Method: In-beam γ-ray spectroscopy of 32 Mg was performed using two direct-reaction probes: one-neutron (two-proton) knockout reactions on 33 Mg ( 34 Si). Final-state exclusive cross sections and parallel momentum distributions were extracted from the experimental data and compared with eikonal-based reaction model calculations combined with shell-model overlap functions. Results: Owing to the remarkable selectivity of the one-neutron and two-proton knockout reactions, a significantly updated level scheme for 32 Mg, which exhibits negative-parity intruder and positive-parity normal states, was constructed. The experimental results were confronted with four different nuclear structure models. Conclusions: In some of these models, different aspects of 32 Mg and the transition into the island of inversion are well described. However, unexplained discrepancies remain, and, even with the help of these state-of-the-art theoretical approaches, the structure of this key nucleus is not yet fully captured.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

An Electrochemically Mediated Amine Regeneration Process with a Mixed Absorbent for Postcombustion CO 2 Capture

Electrochemically mediated amine regeneration (EMAR) was recently developed to avoid the use of thermal means to release CO2 captured from postcombustion flue gas in the benchmark amine process. To address concerns related to the high vapor pressure of ethylenediamine (EDA) as the primary amine used in EMAR, a mixture of EDA and aminoethylethanolamine (AEEA) was investigated. The properties of the mixed amine systems, including the absorption rates, electrolyte pH and conductivity, and CO2 capacity, were evaluated in comparison with those of solely EDA. The mixed amine system had similar properties to that of EDA, indicating no significant changes would be necessary for the future implementation of the EMAR process with mixed amines as opposed to that with just EDA. The electrochemical performance of the mixed amines in terms of the cell voltage, gas desorption rate, electron utilization, and energetics was also investigated. A 50/50 mixture of EDA and AEEA displayed the lowest energetics: ~10% lower than that of 100% EDA. With this mixture, a continuous EMAR process, in which the absorption column was connected to the electrochemical cell as the desorption stage, was tested over 100 h. The cell voltage was very stable and there was a steady gas output close to theoretical values. The desorbed gas was further analyzed and found to be 100% CO2, confirming no evaporation of the amine. The mixed absorbent composition was also characterized using titration and nuclear magnetic resonance (NMR) spectroscopy, and the results showed no amine degradation. Furthermore, these findings that demonstrate a stable, low vapor pressure absorbent with improved energetics are promising and could be a guideline for the future development of EMAR for CO2 capture from flue gas and other sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Phase transition phenomenology with nonparametric representations of the neutron star equation of state

Astrophysical observations of neutron stars probe the structure of dense nuclear matter and have the potential to reveal phase transitions at high densities. Most recent analyses are based on parametrized models of the equation of state with a finite number of parameters and occasionally include extra parameters intended to capture phase-transition phenomenology. However, such models restrict the types of behavior allowed and may not match the true equation of state. We introduce a complementary approach that extracts phase transitions directly from the equation of state without relying on, and thus being restricted by, an underlying parametrization. We then constrain the presence of phase transitions in neutron stars with astrophysical data. Current pulsar mass, tidal deformability, and mass-radius measurements disfavor only the strongest of possible phase transitions (latent energy per particle ≳ 100 MeV). Weaker phase transitions are consistent with observations. Here we further investigate the prospects for measuring phase transitions with future gravitational-wave observations and find that catalogs of O (100) events will (at best) yield Bayes factors of ~ 10 : 1 in favor of phase transitions even when the true equation of state contains very strong phase transitions. Our results reinforce the idea that neutron star observations will primarily constrain trends in macroscopic properties rather than detailed microscopic behavior. Fine-tuned equation of state models will likely remain unconstrained in the near future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Proton discrimination in CLYC for fast neutron spectroscopy

The Cs 2 LiYCl 6 :Ce (CLYC) elpasolite scintillator is known for its response to fast and thermal neutrons along with good γ-ray energy resolution. While the 35 Cl(n,p) reaction has been identified as a potential means for CLYC-based fast neutron spectroscopy in the absence of time-of-flight (TOF), previous efforts to functionalize CLYC as a fast neutron spectrometer have been thwarted by the inability to isolate proton interactions from 6 Li(n,α) and 35 Cl(n,α) signals. This work introduces a new approach to particle discrimination in CLYC for fission spectrum neutrons using a multi-gate charge integration algorithm that provides excellent separation between protons and heavier charged particles. Neutron TOF data were collected using a 252 Cf source, an array of EJ-309 organic liquid scintillators, and a 6 Li-enriched CLYC scintillator outfitted with fast electronics. Modal waveforms were constructed corresponding to the different reaction channels, revealing significant differences in the pulse characteristics of protons and heavier charged particles at ultrafast, fast, and intermediate time scales. These findings informed the design of a pulse shape discrimination algorithm, which was validated using the TOF data. This study also proposes an iterative subtraction method to mitigate contributions from confounding reaction channels in proton and heavier charged particle pulse height spectra, opening the door for CLYC-based fast neutron and γ-ray spectroscopy while preserving sensitivity to thermal neutron capture signals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗