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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multigeneration Pedigrees to Monitor Hatchery Broodstock Composition and Genetic Variation of Spring/Summer Chinook Salmon in the Columbia River Basin

Abstract Hatchery production of Chinook Salmon Oncorhynchus tshawytscha in the Columbia River basin comprises most of the anadromous salmonid production in this region. Hatchery facilities and programs serve to mitigate for impacts to salmonids due to the construction and operation of hydropower dams and habitat impacts from development in addition to the conservation and restoration of natural populations. A genetic method referred to as parentage-based tagging (PBT) enables highly reliable detection of hatchery-origin fish and inference of multigeneration pedigrees. This study compiles 11 years of PBT data from nearly 125,000 interior stream-type Chinook Salmon from 24 spawning hatcheries located on tributaries of the mid- and upper Columbia River and in the Salmon, Clearwater, and Grande Ronde River subbasins. Multigenerational pedigrees allowed for investigation of the proportions of natural- and hatchery-origin broodstock (pNOB and pHOB, respectively) for each hatchery and enumeration of the scale of production between segregated and integrated programs. We then compared how pHOB and the scale of production influenced the number of stray fish observed, genetic diversity, relatedness, and age-class compositions within broodstocks. Over 91.0% of hatchery broodstock could be assigned back to their parents, and overall less than 1.0% of broodstock consisted of fish that were unintentionally incorporated into nonnatal hatchery programs. We evaluated 11 segregated programs with 0.0–10.0% pNOB, 9 intermediate programs (10.1–50.0% pNOB), and 3 integrated programs (>50.0% pNOB). There was no correlation between the scale of production or pNOB with the level of genetic diversity, but as production size increased, so did the effective number of breeders. This study demonstrates the utility of PBT as a monitoring tool for hatchery broodstocks, and results suggest that segregated and integrated programs have tradeoffs that generally align with their intended broodstock management purpose of providing fish for harvest and/or fish for supplementation or reintroduction.

Horn, Rebekah L.↗
DOE OSTI2026

Optimizing a chemical cleaning protocol to determine the nickel isotopic composition of ancient seawater from carbonates

Reconstructing the ancient marine cycle of Ni, a trace metal in the oceans essential to enzymes regulating the C, N, and O cycles, would inform how Ni bioavailability shaped early life. The Ni isotopic composition of seawater (δ 60 Ni SW ) through time could provide insight, but this approach requires sedimentary archives that faithfully record δ 60 Ni SW . Carbonates are an often-used record of seawater chemistry, but contaminants could bias the measured δ 60 Ni of bulk sediment. To isolate the true carbonate-bound δ 60 Ni signal, we optimized a chemical cleaning protocol designed to minimize non‑carbonate Ni contributions and maximize carbonate recovery. We analyzed ODP Site 1007 sediments and evaluated oxidative and reductive pre-cleaning steps and carbonate dissolution protocols. Our results show that only reductive cleaning significantly altered the subsequent carbonate leachate composition, lowering Ni/Ca ratios by up to 60% and δ 60 Ni values by as much as 0.4 ‰. In contrast, δ 60 Ni values were largely insensitive to premature carbonate dissolution during pre-cleaning or to partial leaching of silicates during carbonate dissolution, even at higher acid molarities or longer reaction times. We recommend an evidence-based protocol that removes hydro-soluble salts and clays, applies reductive cleaning and oxidative cleaning for certain sample compositions, and dissolves carbonate using 0.5 M acetic acid, adjusted to pH 5. Using these results, we infer a ∼ 0.9 ‰ Ni isotopic fractionation between chemically cleaned deep-water carbonates (+0.4 ± 0.1 ‰) and deep seawater. This method development is a key step toward accurately reconstructing ancient marine Ni cycles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Uncertainties in cylindrical anode current inferences on pulsed power drivers

For over a decade, velocimetry based techniques have been used to infer the electrical current delivered to dynamic materials properties experiments on pulsed power drivers such as the Z Machine. Though originally developed for planar load geometries, in recent years, inferring the current delivered to cylindrical coaxial loads has become a valuable diagnostic tool for numerous platforms. Presented is a summary of uncertainties that can propagate through the current inference technique when applied to expanding cylindrical anodes. An equation representing quantitative uncertainty is developed which shows the unfold method to be accurate to a few percent above 10 MA of load current.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

X-ray spectroscopy evidence for plasma shell formation in experiments modeling accretion columns in young stars

Recent achievements in laboratory astrophysics experiments with high-power lasers have allowed progress in our understanding of the early stages of star formation. In particular, we have recently demonstrated the possibility of simulating in the laboratory the process of the accretion of matter on young stars [G. Revet et al., Sci. Adv. 3, e1700982 (2017)]. The present paper focuses on x-ray spectroscopy methods that allow us to investigate the complex plasma hydrodynamics involved in such experiments. We demonstrate that we can infer the formation of a plasma shell, surrounding the accretion column at the location of impact with the stellar surface, and thus resolve the present discrepancies between mass accretion rates derived from x-ray and optical-radiation astronomical observations originating from the same object. In our experiments, the accretion column is modeled by having a collimated narrow (1 mm diameter) plasma stream first propagate along the lines of a large-scale external magnetic field and then impact onto an obstacle, mimicking the high-density region of the stellar chromosphere. A combined approach using steady-state and quasi-stationary models was successfully applied to measure the parameters of the plasma all along its propagation, at the impact site, and in the structure surrounding the impact region. The formation of a hot plasma shell, surrounding the denser and colder core, formed by the incoming stream of matter is observed near the obstacle using x-ray spatially resolved spectroscopy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Veridical data science

Building and expanding on principles of statistics, machine learning, and scientific inquiry, we propose the predictability, computability, and stability (PCS) framework for veridical data science. Our framework, composed of both a workflow and documentation, aims to provide responsible, reliable, reproducible, and transparent results across the data science life cycle. The PCS workflow uses predictability as a reality check and considers the importance of computation in data collection/storage and algorithm design. It augments predictability and computability with an overarching stability principle. Stability expands on statistical uncertainty considerations to assess how human judgment calls impact data results through data and model/algorithm perturbations. As part of the PCS workflow, we develop PCS inference procedures, namely PCS perturbation intervals and PCS hypothesis testing, to investigate the stability of data results relative to problem formulation, data cleaning, modeling decisions, and interpretations. We illustrate PCS inference through neuroscience and genomics projects of our own and others. Moreover, we demonstrate its favorable performance over existing methods in terms of receiver operating characteristic (ROC) curves in high-dimensional, sparse linear model simulations, including a wide range of misspecified models. Finally, we propose PCS documentation based on R Markdown or Jupyter Notebook, with publicly available, reproducible codes and narratives to back up human choices made throughout an analysis. The PCS workflow and documentation are demonstrated in a genomics case study available on Zenodo.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

CO 2 fertilization of terrestrial photosynthesis inferred from site to global scales

Significance The magnitude of the CO 2 fertilization effect on terrestrial photosynthesis is uncertain because it is not directly observed and is subject to confounding effects of climatic variability. We apply three well-established eco-evolutionary optimality theories of gas exchange and photosynthesis, constraining the main processes of CO 2 fertilization using measurable variables. Using this framework, we provide robust observationally inferred evidence that a strong CO 2 fertilization effect is detectable in globally distributed eddy covariance networks. Applying our method to upscale photosynthesis globally, we find that the magnitude of the CO 2 fertilization effect is comparable to its in situ counterpart but highlight the potential for substantial underestimation of this effect in tropical forests for many reflectance-based satellite photosynthesis products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

THE GALAXY-HALO/SUBHALO CONNECTION: MASS RELATIONS AND IMPLICATIONS FOR SOME SATELLITE OCCUPATIONAL DISTRIBUTIONS

We infer the local stellar-to-halo/subhalo mass relations (MRs) for central and satellite galaxies separately. Our statistical method is an extension of the abundance matching, halo occupation distribution, and conditional stellar mass function formalisms. We constrain the model using several combinations of observational data, consisting of the total galaxy stellar mass function (GSMF), its decomposition into centrals and satellites, and the projected two-point correlation functions (2PCFs) measured in different stellar mass (M{sub *}) bins. In addition, we use the {Lambda}CDM halo and subhalo mass functions. The differences among the resulting MRs are within the model-fit uncertainties (which are very small, smaller than the intrinsic scatter between galaxy and halo mass), no matter what combination of data are used. This shows that matching abundances or occupational numbers is equivalent, and that the GSMFs and 2PCFs are tightly connected. We also constrain the values of the intrinsic scatter around the central-halo (CH) and satellite-subhalo (SS) MRs assuming them to be constant: {sigma}{sub c} = 0.168 {+-} 0.051 dex and {sigma}{sub s} = 0.172 {+-} 0.057 dex, respectively. The CH and SS MRs are actually different, in particular when we take the subhalo mass at the present-day epoch instead of at their accretion time. When using the MRs for studying the satellite population (e.g., in the Milky Way, MW), the SS MR should be chosen instead of the average one. Our model allows one to calculate several population statistics. We find that the central galaxy M{sub *} is not on average within the mass distribution of the most massive satellite, even for cluster-sized halos, i.e., centrals are not a mere realization of the high end of the satellite mass function; however for >3 Multiplication-Sign 10{sup 13} M{sub Sun} halos, {approx}15% of centrals could be. We also find that the probabilities of MW-sized halos of having N Magellanic Cloud (MC) sized satellites agree well with observational measures; for a halo mass of 2 Multiplication-Sign 10{sup 12} M{sub Sun }, the probability to have two MCs is 5.4%, but if we exclude those systems with satellites larger than the MCs, then the probability decreases to <2.2%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Divertor detachment and heat exhaust mitigation control in KSTAR with tungsten divertor

KSTAR has recently undergone an upgrade to use a new tungsten divertor to run experiments in ITER-relevant scenarios. Even with a high melting point of tungsten, it is important to control the heat flux impinging on tungsten divertor targets to minimize sputtering and contamination of the core plasma. Heat flux on the divertor is often controlled by increasing the degree of detachment of scrape-off layer plasma from the target plates. In this work, we have demonstrated successful divertor detachment and heat exhaust dissipation control experiments using two different methods. The first method uses attachment fraction as a control variable which is estimated using ion saturation current measurements from embedded Langmuir probes in the divertor. The second method uses a novel machine-learning-based surrogate model of 2D UEDGE simulation database, DivControlNN. We demonstrated running inference operation of DivControlNN in realtime to estimate heat flux at the divertor and use it as the control variable in a feedback loop with impurity gas flow. We present interesting insights from these experiments including a systematic approach to tuning controllers and discuss future improvements in the control infrastructure and control variables for future burning plasma experiments.

KSTAR tungsten divertor operations↗
DOE OSTI2024

Neural simulation-based inference of the neutron star equation of state directly from telescope spectra

Neutron stars provide a unique opportunity to study strongly interacting matter under extreme density conditions. The intricacies of matter inside neutron stars and their equation of state are not directly visible, but determine bulk properties, such as mass and radius, which affect the star's thermal X-ray emissions. However, the telescope spectra of these emissions are also affected by the stellar distance, hydrogen column, and effective surface temperature, which are not always well-constrained. Uncertainties on these nuisance parameters must be accounted for when making a robust estimation of the equation of state. In this study, we develop a novel methodology that, for the first time, can infer the full posterior distribution of both the equation of state and nuisance parameters directly from telescope observations. This method relies on the use of neural likelihood estimation, in which normalizing flows use samples of simulated telescope data to learn the likelihood of the neutron star spectra as a function of these parameters, coupled with Hamiltonian Monte Carlo methods to efficiently sample from the corresponding posterior distribution. Our approach surpasses the accuracy of previous methods, improves the interpretability of the results by providing access to the full posterior distribution, and naturally scales to a growing number of neutron star observations expected in the coming years.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The high-mass end of the red sequence at z ~ 0.55 from SDSS-III/BOSS: completeness, bimodality and luminosity function

The history of the expanding universe is encoded in the large-scale distribution of galaxies throughout space. By mapping out the three-dimensional locations of millions of galaxies with powerful telescopes, we can directly measure this expansion history. When interpreted using Einstein's theory of gravity, this expansion history lets us infer the contents of the universe, including the amount and nature of "dark energy", an as-yet unexplained energy density associated with the empty vacuum of space. However, to make these measurements and inferences accurately, we must understand and control for a large number of experimental effects. This paper develops a novel method for large cosmological galaxy surveys, and applies it to data from the "BOSS" experiment of the Third Sloan Digital Sky Survey. This method enables an accurate statistical characterization of the "completeness" of the BOSS experiment: the probability that a given galaxy at a given place in the universe is actually detected and successfully measured. It also enables the accurate determination of the underlying demographics of the galaxy population being studied by the experiment. These two ingredients can then be used to make a more accurate comparison between the results of the experiment and the theoretical models that predict the observable effects of dark energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Assessing Machine Learning as a Tool to Explain Variance in Deployed Photovoltaic (PV) System Degradation

Degradation remains a large uncertainty in forecasting production for PV plants, creating significant risk for developers and financiers. This study aims to quantify the distribution and drivers of degradation across 10,000 PV systems deployed for distributed or utility generation by training a machine learning model to predict year-over-year degradation rates from metadata characteristics. A combination of K-Means clustering and random forest regressor were found to associate multiple metadata features as potential drivers of degradation, including module characteristics, system design, and climate features. From this, it is inferred that if machine learning is able to find complex patterns between metadata features and system performance loss, such methods can be employed to help developers and financiers make data-informed decisions when estimating long-term energy production forecasts in financial models.

Dunn, Jimmy C.↗
DOE OSTI2020

Connecting Activation Calculations with Gamma Spectroscopy

For many years Lawrence Livermore National Laboratory (LLNL) has used gamma spectroscopy to determine quantities of radioactive nuclides created by irradiation of stable species with neutrons and light charged particles. LLNL has also maintained activation codes and nuclear cross sections for the purpose of modeling activations under the experimental conditions, and the cross section sets used in those calculations typically include nuclear isomers. Connecting the measurements to activation calculations that include isomers is a non-trivial matter because an activation calculation must be followed by a procedure for bookkeeping of calculated isomer populations after the irradiation to simulate what radiochemists would infer about isotope populations from gamma spectroscopy performed days or weeks after the irradiation. Traditionally we have used the method of “isomer sums” for this bookkeeping. This report explains our formulation of isomer sums and application to specific cross section sets for different nuclides that were detected.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

End-to-end deep learning pipeline for real-time Bragg peak segmentation: from training to large-scale deployment

X-ray crystallography reconstruction, which transforms discrete X-ray diffraction patterns into three-dimensional molecular structures, relies critically on accurate Bragg peak finding for structure determination. As X-ray free electron laser (XFEL) facilities advance toward MHz data rates (1 million images per second), traditional peak finding algorithms that require manual parameter tuning or exhaustive grid searches across multiple experiments become increasingly impractical. While deep learning approaches offer promising solutions, their deployment in high-throughput environments presents significant challenges in automated dataset labeling, model scalability, edge deployment efficiency, and distributed inference capabilities. We present an end-to-end deep learning pipeline with three key components: (1) a data engine that combines traditional algorithms with our peak matching algorithm to generate high-quality training data at scale, (2) a modular architecture that scales from a few million to hundreds of million parameters, enabling us to train large expert-level models offline while deploying smaller, distilled models at the edge, and (3) a decoupled producer-consumer architecture that separates specialized data source layer from model inference, enabling flexible deployment across diverse computing environments. Using this integrated approach, our pipeline achieves accuracy comparable to traditional methods tuned by human experts while eliminating the need for experiment-specific parameter tuning. Although current throughput requires optimization for MHz facilities, our system's scalable architecture and demonstrated model compression capabilities provide a foundation for future high-throughput XFEL deployments.

Wang, Cong↗
DOE OSTI2016

A BAYESIAN ESTIMATE OF THE CMB–LARGE-SCALE STRUCTURE CROSS-CORRELATION

Evidences for late-time acceleration of the universe are provided by multiple probes, such as Type Ia supernovae, the cosmic microwave background (CMB), and large-scale structure (LSS). In this work, we focus on the integrated Sachs–Wolfe (ISW) effect, i.e., secondary CMB fluctuations generated by evolving gravitational potentials due to the transition between, e.g., the matter and dark energy (DE) dominated phases. Therefore, assuming a flat universe, DE properties can be inferred from ISW detections. We present a Bayesian approach to compute the CMB–LSS cross-correlation signal. The method is based on the estimate of the likelihood for measuring a combined set consisting of a CMB temperature and galaxy contrast maps, provided that we have some information on the statistical properties of the fluctuations affecting these maps. The likelihood is estimated by a sampling algorithm, therefore avoiding the computationally demanding techniques of direct evaluation in either pixel or harmonic space. As local tracers of the matter distribution at large scales, we used the Two Micron All Sky Survey galaxy catalog and, for the CMB temperature fluctuations, the ninth-year data release of the Wilkinson Microwave Anisotropy Probe ( WMAP 9). The results show a dominance of cosmic variance over the weak recovered signal, due mainly to the shallowness of the catalog used, with systematics associated with the sampling algorithm playing a secondary role as sources of uncertainty. When combined with other complementary probes, the method presented in this paper is expected to be a useful tool to late-time acceleration studies in cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1977

Comparison of H-alpha synoptic charts with the large-scale solar magnetic field as observed at Stanford

Two methods of observing the neutral line of the large-scale photospheric magnetic field are compared: neutral line positions inferred from H-alpha photographs (McIntosh and Nolte, 1975) and observations of the photospheric magnetic field made with low spatial resolution (three minutes) and high sensitivity using the Stanford magnetograph. The comparison is found to be very favorable.

Duvall, T. L., Jr.↗
NASA NTRS1983

Comparison of heliospheric current sheet structure obtained from potential magnetic field computations and from observed polarization coronal brightness

A comparison is conducted of the structure of the heliospheric current sheet early in sunspot cycle 21 as computed from the observed photospheric magnetic field with a potential field approximation and as inferred from synoptic maps of the observed coronal polarization brightness. On most of the solar rotations compared, the two methods give essentially the same results; the basic shape of the warped current sheet and the amplitude (in solar latitude) of the displacements of the sheet from the solar equator are similar. On one rotation the current sheet computed with the potential field approximation appears to be distorted by a large photospheric region of unbalanced magnetic flux.

Wilcox, J. M.↗
NASA NTRS1990

A tomographic glimpse of the upper mantle source of magmas of the Jemez lineament, New Mexico

In this study, the lateral variations of the P wave velocity as a function of depth were examined for the regions of the Rio Grande rift and the Jemez lineament, to infer spatial distributions of partial melt in the upper mantle source zones for the rift and the lineament. The method involved measurements of teleismic P wave delays at a 22-station network followed by performing a damped least-squares three-dimensional inversion for these lateral variations. Results indicate that, directly beneath the Jemez lineament (but not beneath the Rio Grande rift), there is a 100-km-wide 1-2-percent low-P-wave-velocity feature in the depth range of 50-160 km. This implies that the volcanic potential of the Jemez lineaments continues to greatly exceed that of the Rio Grande rift.

Spence, William↗
NASA NTRS1992

Establishing the existence of lines in gamma-ray bursts

A rigorous method for establishing the existence of lines in gamma-ray bursts is described which is based on Bayesian inference. In particular, it is shown how the problem of line detection can be reduced to that of comparing two models, a model consisting only of a continuum spectrum and a model with an additional feature in it. The simple case of a Gaussian line is considered, and it is noted that the results can be readily extended to the case of time-dependent lines.

Loredo, T. J.↗