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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 127 records · Page 7

Appraising constrained second-order power corrections in HQET with Λ b →Λ c Ι⁢ν

We derive the Λ b →Λ c form factors for the Standard Model and beyond at second order in heavy quark effective theory, applying the recently proposed residual chiral expansion to reduce the set of unknown subsubleading hadronic functions to a single, highly constrained function, that is fully determined by hadron mass parameters at zero recoil. We fit a form factor parametrization based on these results to all available lattice QCD predictions and experimental data. We find that the constrained and predictive structure of the form factors under the residual chiral expansion is in excellent agreement with lattice QCD predictions and experimental data, as well as prior heavy-quark-effective-theory-based fits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Nuclear Data Sheets for A=69

Experimental data on ground- and excited-state properties for all known nuclei with mass number A=69 have been compiled and evaluated. States populated in radioactive decay, as well as in nuclear reactions, have been considered. For these nuclei, level and decay schemes, as well as tables of nuclear properties, are given in detail. In conclusion, this work supersedes the 2013 evaluation by C.D. Nesaraja (2014Ne01).

Nesaraja, Caroline D. [Oak Ridge National Laborato↗

Nuclear Structure and Decay Data for A=216 Isobars

Experimental data from reaction and decay studies on nuclei with A=216 have been reviewed. Elements included in this review span from mercury (Z=80) to uranium (Z=92). Based on the published data, level and decay schemes are presented for the evaluated nuclides. In conclusion, this work updates and supersedes the previous A=216 evaluation (2007Wu02).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Analysis of fusion alphas interaction with RF waves in D-T plasma at JET

This work studies the influence of RF waves in ICRH range of frequency on fusion alphas during the recent JET D-T campaign. Fusion alphas from D-T reactions are born with energies of about 3.5MeV and therefore have significant Doppler shift enabling synergistic interaction between them and RF waves at broad range of frequencies including the ones foreseen for future fusion machines ITER and SPARC. Resonant interaction between RF waves and alphas, also called synergistic effects, will modify the alpha distribution and ultimately will have an impact on alpha orbit losses and heating. Data from JET 3.43T/2.3MA pulses based on the hybrid scenario during the DTE2 campaign were used for the analysis in this study. The impact of synergistic effects on alpha orbit losses and alpha heating is assessed. Conclusions are based on analysis of experimental data for fast alphas losses, i.e. measurements from neutral particle analyser, fast ion losses scintillator detector, Faraday cups, and TRANSP simulations. Experimental data and TRANSP analysis indicate that there are indeed changes in the alphas' distribution function due to interaction with RF waves. Data from the scintillator detector and the Faraday cups were compared for pulses with and without ICRH power and versus cases with enhanced alpha losses due to MHD activities. The trends from these diagnostics consistently show no additional alpha losses due to interaction with RF waves. TRANSP predictions for the impact of the synergistic effects on alpha heating show up to 42% increase in alpha electron heating and up to 25% increase in alpha ion heating. These effects however become negligibly small, less than 1%, when alpha heating is compared to the total auxiliary hearting power in the investigated JET pulses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Spectral and Temperature-Dependent Optical Metrology: Towards More Robust, Effective and Durable Materials for Concentrated Solar Power

The primary objective of this project is to develop reliable and standardized spectroscopic measurement techniques to determine radiative properties, specifically the emittance and reflectance, of materials relevant for the next generation (Gen3) concentrated solar power (CSP) technologies. Experimental measurements will span near- and mid-infrared wavelengths (1–20 µm) with emphasis on quantifying the influences of: (1) operating temperatures of 25–1000 °C, (2) thermal cycling, and (3) environmental exposure of materials during operation (vacuum/air). A secondary goal is to develop open-access and digitized databases to host and share experimental data, together with standardized measurement protocols and operating procedures to determine optical properties of materials. This project will also include reasonable emphasis on developing predictive modeling tools to augment experimental data to extract more fundamental and material-specific radiative properties.

14 SOLAR ENERGY↗

Modeling of Additively Manufactured Ceramic Heat Exchangers with Semi-Elliptical Cross-Section Flow Channels

An approximate and easily applied analytical model was developed for heat transfer calculations of heat exchangers consisting of multiple rows and columns of heat transfer fluid flow channels with semi-elliptical cross sections. Heat exchangers of this type are being developed by using ceramic material and additive manufacturing for high temperature and pressure-concentrating solar electric power plants. Calculations using the model require only the geometrical dimensions and flow conditions of the heat exchanger. Comparisons of modeling predictions, with both simulation results and experimental data, were conducted to verify the viability of the model. The results showed good agreement where almost all the modeling predictions were within 20% of the simulation results or the experimental data. Finally, the proposed modeling approach is more generally applicable to heat transfer analysis of heat exchangers with similar flow channel configurations to those considered in this study.

Ceramic↗

Fully Bayesian Analysis With Model Inadequacy Correction For Nuclear Graphite Property Models With Hierarchical Variance Structure

Nuclear-grade graphites are extensively utilized in the core designs of various advanced nuclear reactors. Within the reactor environment, graphite is subjected to prolonged exposure to extreme conditions, including high temperatures, radiation, and potentially molten salt and oxygen. Such exposure can induce several degradation mechanisms in graphite, such as nonuniform volumetric strains caused by irradiation and thermal expansion, leading to stresses that may compromise the performance of graphite components. Assessing component integrity, forecasting component performance over the reactor's lifespan, and developing design standards necessitate robust tools for predicting fracture initiation and propagation in graphite structural components within nuclear reactors. This code enables the Bayesian calibration of properties for nuclear-grade graphites. Using a hierarchical Bayesian approach, multiple experimental data sources are combined to develop Gaussian process models for the properties. Using the Kennedy O'Hagan framework, the uncertainties due inadequacies in the model and the inherent spread in the experimental data are quantified.

Dhulipala, Som Lakshmi NarasimhaLakshmi Narasimha ↗

Bayesian Calibration of Nuclear Graphite Property Models Accounting for Model Inadequacy and Impacts on Component Performance

Nuclear-grade structural graphite is extensively utilized in the core designs of various advanced nuclear reactors. In the reactor environment, graphite is subjected to prolonged exposure to extreme conditions, including high temperatures, radiation, and potentially molten salt and oxygen. Such exposure can induce several degradation mechanisms in graphite, including nonuniform volumetric strains caused by irradiation and thermal expansion, leading to stresses that may compromise the performance of graphite components. Assessing component integrity requires accurate models of graphite's thermomechanical response. This report documents the Bayesian calibration of thermomechanical properties for nuclear-grade graphite and their application to graphite component modeling and simulation using the Grizzly code. As part of this work, uncertainty-quantified models were developed for the elastic modulus, coefficient of thermal expansion, irradiation-induced dimensional change, and irradiation-induced creep for graphite grades IG-110, NBG-18, NBG-17, PCEA, and 2114. Using a hierarchical Bayesian approach, multiple experimental data sources were combined to develop Gaussian process models for the properties. Using the Kennedy O'Hagan framework, the uncertainties due to inadequacies in the model and the inherent spread in the experimental data were quantified for three different models. These uncertainty-quantified models, with a model-form correction, were subsequently applied to a coupled-physics simulation of representative graphite components, revealing that the uncertainties have a large impact on the components' deformation.

36 - MATERIALS SCIENCE↗

Dynamic Modeling of Near Isothermal Compressor for Transcritical Carbon Dioxide Cycle

Compressors are the major energy consumption components in vapor compression systems, drawing much research effort in reducing carbon emissions. The isothermal compressor integrates the compressor chamber and gas cooler to achieve near isothermal compression, reaching up to 30% energy reduction compared to the traditional isentropic compression work. This paper presents a detailed isothermal compressor model combined with a generalized liquid piston model to account for the carbon dioxide (CO2) isothermal compression process. The model is established based on MATLAB environment. The model uses the real experimental data as boundary conditions and initial settings, which also considers the CO2 solubility in liquid piston (mineral oil) for designing, optimizing and customizing the compression chambers. The validation was carried out with experimental data using a prototype with 3.5 kW capacity. The results have demonstrated the accuracy of the dynamic model (6.2% relative error for chamber pressure and 0.5 K deviation for chamber temperature), which provide a guideline for designing and customizing the isothermal compression cycle.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Phase transformation kinetics model for metals

We develop a new model for phase transformation kinetics in metals by generalizing the Levitas–Preston (LP) phase field model of martensite phase transformations (see Levitas and Preston (2002a,b) and Levitas et al. (2003)) to arbitrary pressure. Furthermore, we account for and track: the interface speed of the pressure-driven phase transformation, properties of critical nuclei, as well as nucleation at grain sites and on dislocations and homogeneous nucleation. The volume fraction evolution of each phase is described by employing KJMA (Kolmogorov, 1937; Johnson and Mehl, 1939; Avrami, 1939, 1940, 1941) kinetic theory. We then test our new model for iron under ramp loading conditions and compare our predictions for the α → ϵ iron phase transition to experimental data of Smith et al. (2013). In conclusion, more than one combination of material and model parameters (such as dislocation density and interface speed) led to good agreement of our simulations to the experimental data, thus highlighting the importance of having accurate microstructure data for the sample under consideration.

36 MATERIALS SCIENCE↗

Impact of composition and symmetry energy on the temperature of quasiprojectiles simulated with antisymmetrized molecular dynamics

The equation of state describes the emergent physical properties of matter. Experimental data is needed to help constrain the equation of state for nuclear matter. These constraints can help distinguish between an “asy-stiff” and an “asy-soft” equation of state, which has astrophysical implications. One path to help constrain the models is to analyze the nuclear caloric curve; some experiments have shown dependence on neutron excess, and may thus be sensitive to the asymmetry. A difference in the caloric curve based on the asymmetry of the reconstructed quasiprojectile (QP) had been observed using 70 Zn on 70 Zn at 35 MeV/nucleon taken with the NIMROD array. Antisymmetrized molecular dynamics calculations were performed for the same system and deexcited with gemini++. Both Gogny (asy-soft) and Gogny-as (asy-stiff) data sets were generated. The particles were then filtered based on detector geometric acceptance and thresholds. From the accepted particles, the excitation energy and temperature were calculated in the same way as for experimental data. Additionally, filter effects on the observed nuclear caloric curves were investigated. A tendency for the asy-stiff nuclear caloric curves to have higher temperatures than their asy-soft counterparts was observed for a number of probes. In addition, some probes may show sensitivity to the reconstructed composition of the QP, but this is inconclusive due to high statistical fluctuations and a large dependence on the exact method of event selection.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Techno-Economic Analysis of Gas-Liquid Contactors for Tritium Extraction from Lead-Lithium

To enable a sustainable fuel cycle, any deuterium-tritium fusion reactor must breed its tritium fuel onsite. Lead-lithium (PbLi), a eutectic metal, is a leading liquid breeder material for tritium generation. One challenge with PbLi blanket technology is the extraction of tritium from the molten eutectic. Three technologies are the focus of worldwide research: the vacuum permeator, the vacuum sieve tray, and the gas-liquid contactor (GLC). The present work offers a methodology for designing, sizing, optimizing, and costing a trickle-bed GLC. Here, we analyzed tritium extraction from PbLi using MELODIE experimental data by applying traditional packed bed mass transfer efficiency models along with supplementary models, like film theory. Our analysis revealed that traditional packed bed mass transfer efficiency models do not fit the MELODIE loop experimental data. Moreover, uncertainty in PbLi solubility resulted in a 325-fold increase in required gas flow rates when comparing identical packing heights. The film theory liquid mass transfer coefficient, Delt-Olujic wettability model, and Reiter tritium solubility values fit the MELODIE data best and were used both in the design and to conduct the economic analysis. Techno-economic analysis of the GLC was performed to evaluate three design sizes, all achieving a minimum extraction efficiency of 90 [%] for a total tritium extraction of 31 [kg/yr].

Fusion Fuel Cycle↗

Toward first principles-based simulations of dense hydrogen

Accurate knowledge of the properties of hydrogen at high compression is crucial for astrophysics (e.g., planetary and stellar interiors, brown dwarfs, atmosphere of compact stars) and laboratory experiments, including inertial confinement fusion. There exists experimental data for the equation of state, conductivity, and Thomson scattering spectra. However, the analysis of the measurements at extreme pressures and temperatures typically involves additional model assumptions, which makes it difficult to assess the accuracy of the experimental data rigorously. On the other hand, theory and modeling have produced extensive collections of data. They originate from a very large variety of models and simulations including path integral Monte Carlo (PIMC) simulations, density functional theory (DFT), chemical models, machine-learned models, and combinations thereof. At the same time, each of these methods has fundamental limitations (fermion sign problem in PIMC, approximate exchange–correlation functionals of DFT, inconsistent interaction energy contributions in chemical models, etc.), so for some parameter ranges accurate predictions are difficult. Recently, a number of breakthroughs in first principles PIMC as well as in DFT simulations were achieved which are discussed in this review. Here we use these results to benchmark different simulation methods. We present an update of the hydrogen phase diagram at high pressures, the expected phase transitions, and thermodynamic properties including the equation of state and momentum distribution. Furthermore, we discuss available dynamic results for warm dense hydrogen, including the conductivity, dynamic structure factor, plasmon dispersion, imaginary-time structure, and density response functions. We conclude by outlining strategies to combine different simulations to achieve accurate theoretical predictions that are based on first principles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Cross Section Evaluation for Exclusive Channels of K+Λ and K+Σ0 Electroproduction off Protons Using CLAS Detector Data

In this work, a method for evaluating the cross sections of electroproduction of K+Λ0 and K+Σ0 off protons in the region of invariant masses of final hadrons MK + MY <W < 2.65 GeV (MK and MY being the masses of the kaon and hyperon, respectively) and squares of four-momentum transfers of virtual photons, i.e., photon virtualities 0 < Q2 < 5 GeV2, is developed based on experimental data of these exclusive channels’ cross sections measured by the CLAS detector in Hall B at Jefferson Lab. A set of algorithms has been implemented to evaluate the differential cross sections of these channels, along with their statistical and systematic uncertainties. A program was developed for the evaluation of differential cross sections and structure functions using C++ and Python libraries. An interactive website was created for working with the program, enabling the analysis of one-dimensional and two-dimensional dependences of structure functions and differential cross sections. The evaluation of differential cross sections for the K+Λ and K+Σ0 electroproduction channels is necessary for extracting the structure function σLT from the data on the polarization asymmetry of electroproduction reactions of these final states with longitudinally polarized electrons. The obtained results are also important for the development of realistic Monte Carlo event generators in planning future experiments and for evaluating the efficiency of detecting final particles when extracting reaction cross sections from experimental data.

Golda, A. V.↗

Review: Pre-Darcy flows in low-permeability porous media

The widely used Darcy’s law specifies a linear relation between the Darcy velocity of fluid flow and the pressure gradient that drives the flow. However, studies have shown that Darcy velocity can exhibit a nonlinear dependence on the pressure gradient in low-permeability porous media such as clay and shale when the pressure gradient is adequately low. This phenomenon is referred to as low-velocity non-Darcian flow or pre-Darcy flow. This paper provides a comprehensive review of the theories, experimental data, and modeling methods for pre-Darcy flow in low-permeability porous media. The review begins by outlining the fundamental mechanisms underlying pre-Darcy flow that regulate the unique characteristics such as nonlinear dependence of the Darcy velocity on the pressure gradient and its relevance to fluid–rock interactions. The review then proceeds to present a thorough compilation of experimental investigations performed in various low-permeability geomaterials including tight sandstones, shales, and clays. Next, empirical and theoretical models and simulation methods that have been developed to fit and interpret experimental data are reviewed. Finally, the review underscores the challenges encountered in conducting and interpreting pre-Darcy flow experiments and suggests future research directions. By analyzing previous experimental investigations, this review aims to offer a valuable resource for researchers and practitioners seeking to enhance their understanding of fluid dynamics in low-permeability geomaterials. This provides insights into the application of pre-Darcy flow in numerous natural and engineered processes such as shale oil and gas recovery, contaminant transport in low-permeability aquifers, and geological disposal of nuclear waste.

58 GEOSCIENCES↗

Neutron generation dynamics inside a MA-class dense plasma focus Z-pinch

Dense plasma focii (DPFs) are appealing as energy efficient sources of short pulses of ions, neutrons, and x rays. The output of these sources is expected to scale with input current (I4), but has been shown to drop at the MA level [S. K. H. Auluck, “On the failure of neutron yield scaling in the dense plasma focus,” Phys. Plasmas 30, 080701 (2023)]. New results on the MegaJOuLe Neutron Imaging Radiography DPF showed neutron yield production in agreement with the input current scaling beyond the previously observed drop. This work provides insight into the pinch formation on a DPF and reports on the two different mechanisms leading to neutron generation inside a DPF using a combination of kinetic simulations and experimental data. A combination of particle-in-cell (PIC) and 1D shock theory results are used to describe the pinch formation and disassembly and the corresponding thermonuclear and beam-target mechanisms. The temporal evolution of the pinch column predicted by the PIC simulations shows qualitative agreement with the experimental data from plasma photon emission as well as temporal neutron pulse shapes. In MJ-class DPFs, both thermonuclear and beam-target mechanisms can occur over the course of the implosion and contribute to the total neutron production. Hence the neutron source size of a DPF will change throughout the implosion. Experimental neutron radiographs show the increase in source size as the pinch breaks apart, in agreement with simulation's prediction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A roadmap toward scaling, reasoning and self-evolving foundation models for nuclear and particle physics

Foundation models have revolutionized artificial intelligence, with Large Language Models demonstrating unprecedented capabilities in multimodal understanding, reasoning and tool use. Nuclear and particle physics stands at a critical juncture where similar transformative potential awaits realization. The field generates exabytes of experimental data, exascale simulations, and decades of theoretical insights — yet these remain largely disconnected from modern Artifical Intelligence (AI) capabilities, with most physics AI applications confined to narrow, task-specific models that suffer from domain shifting when applied to real experimental data. We present a roadmap for FM4NPP (Foundation Model for Nuclear and Particle Physics), systematically scaling from current proof-of-concept models to trillion-parameter architectures capable of autonomous discovery. Our approach advances three critical frontiers: unified data infrastructure integrating detector data, scientific knowledge and computational tools across global facilities; multi-facility foundation models enabling cross-experiment knowledge transfer and accelerated discovery; and agentic AI capabilities for reasoning and autonomous tool use. The resulting self-evolving FM4NPP will transform physics research by converting time-intensive data analysis, theory derivation and computational bottlenecks into rapid AI–human collaborative discovery. This paradigm shift promises to fundamentally accelerate scientific progress in nuclear and particle physics, enabling researchers to focus on high-level insights while AI handles routine analysis and explores vast parameter spaces beyond human capacity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Uncertainty-Guided Prediction Horizon of Phase-Resolved Ocean Wave Forecasting Under Data Sparsity: Experimental and Numerical Evaluation

Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often depend on environmental sensors (e.g., waverider buoys, wave-sensing LIDAR). Challenges arise when upstream sensor data are missing, sparse, or phase-shifted due to drift. This study investigates the performance of two machine learning models, time-series dense encoder (TiDE) and long short-term memory (LSTM), for forecasting phase-resolved ocean surface elevations under varying degrees of data degradation. We introduce the τ-trimming algorithm, which adapts the prediction horizon based on uncertainty thresholds derived from historical forecasts. Numerical wave tank (NWT) and wave basin experiments are used to benchmark model performance under short- and long-term data masking, spatially coarse sensor grids, and upstream phase shifts. Results show under a 50% probability of upstream data loss, the τ-trimmed TiDE model achieves a 46% reduction in error at the most upstream target, compared to 22% for LSTM. Furthermore, phase misalignment in upstream data introduces a near-linear increase in forecast error. Under moderate model settings, a ±3 s misalignment increases the mean absolute error by approximately 0.5 m, while the same error is accumulated at ±4 s using the more conservative approach. These findings inform the design of resilient, uncertainty-aware wave forecasting systems suited for realistic offshore sensing environments.

42 ENGINEERING↗