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NASA NTRS2004

Core Formation in the Earth: Constraints from Ni and Co

Due to their metal-loving nature, Ni and Co were strongly partitioned into the metallic core and were left depleted in the silicate mantle during core formation in the Earth. Based on experimental liquid metal- liquid silicate partition coefficients (D), studies have suggested that core formation in an early magma Ocean can explain the observed mantle depletions of Ni and Co [l-51. However, the conditions proposed by the magma ocean models have ranged from pressures of 24 to 59 GPa and temperatures of 2200 to < 4000 K. Furthermore, the proposed magma Ocean oxygen fugacities have differed by nearly two orders of magnitude.Chabot and Agee noted that the different models predicted contradictory behaviors for D(Ni) and D(Co) as a function of temperature. With the hope of resolving the discrepancies between the magma ocean models, we conducted a systematic experimental study to constrain the effects of temperature on D(Ni) and D(Co).

Chabot, N. L.↗

NASA NTRS1994

Dust extinction of the stellar continua in starburst galaxies: The ultraviolet and optical extinction law

We analyze the International Ultraviolet Explorer (IUE) UV and the optical spectra of 39 starburst and blue compact galaxies in order to study the average properties of dust extinction in extended regions of galaxies. The optical spectra have been obtained using an aperture which matches that of IUE, so comparable regions within each galaxy are sampled. The data from the 39 galaxies are compared with five models for the geometrical distribution of dust, adopting as extinction laws both the Milky Way and the Large Magellanic Cloud laws. The commonly used uniform dust screen is included among the models. We find that none of the five models is in satisfactory agreement with the data. In order to understand the discrepancy between the data and the models, we have derived an extinction law directly from the data in the UV and optical wavelength range. The resulting curve is characterized by an overall slope which is more gray than the Milky Way extinction law's slope, and by the absence of the 2175 A dust feature. Remarkably, the difference in optical depth between the Balmer emission lines H(sub alpha) and H(sub beta) is about a factor of 2 larger than the difference in the optical depth between the continuum underlying the two Balmer lines. We interpret this discrepancy as a consequence of the fact that the hot ionizing stars are associated with dustier regions than the cold stellar population is. The absence of the 2175 A dust feature can be due either to the effects of the scattering and clumpiness of the dust or to a chemical composition different from that of the Milky Way dust grains. Disentangling the two interpretations is not easy because of the complexity of the spatial distribution of the emitting regions. The extinction law of the UV and optical spectral continua of extended regions can be applied to the spectra of medium- and high-redshift galaxies, where extended regions of a galaxy are, by necessity, sampled.

Calzetti, Daniela↗

DOE OSTI2025

Anomalous electroweak physics unraveled via evidential deep learning

The ever-growing ecosystem of beyond standard model (BSM) calculations and parametrizations has motivated the development of systematic methods for making quantitative cross-comparisons over the wide range of possible models, especially with controllable uncertainties. In this setting, the language of uncertainty quantification (UQ) furnishes useful metrics for assessing statistical overlaps and discrepancies among BSM and related models. In this study, we leverage recent machine learning (ML) developments in evidential deep learning (EDL) for UQ to separate data (aleatoric) and knowledge (epistemic) uncertainties in a model-discrimination setting. We construct several potentially BSM-motivated scenarios for the anomalous electroweak interaction (AEWI) of neutrinos with nucleons in deep inelastic scattering ( v DIS). These scenarios are then quantitatively mapped, as a demonstration, alongside Monte Carlo replicas of the CT18 PDFs used to calculate the $\varDelta \chi ^{2}$ statistic for a typical multi-GeV v DIS experiment, CDHSW. Our framework effectively highlights areas of model agreement and provides a classification of out-of-distribution (OOD) samples. By offering the opportunity to quantitatively understand model overlaps, the approach presented in this work can help facilitate efficient BSM model exploration and exclusion for future New Physics searches.

AI↗

DOE OSTI2020

Experimentally Validated Computational Modeling of Creep and Creep-Cracking for Nuclear Concrete Structures

In a Nuclear Power Plant, one of the most important components is the concrete nuclear reactor cavity, which serves both a structural and protective function as the biological radiation shield. Given that creep has been identified as a major knowledge gap in the assessment of nuclear structures (NUREG/CR-7153), this work helps to further the understanding of creep behavior of massive concrete containment structures for decades to enable safe and long-term operation of these facilities. This project has developed a robust, experimentally validated model to predict creep in nuclear concrete structures for up 60 years using short-term creep data thereby enabling a longer service life of critical facilities and early detection of structural failure. The work presented in this report is a pairing of computational and experimental methods. For the first time, the time temperature superposition (TTS) principle was successfully used to generate a uniaxial creep compliance master curve to predict mortar creep response for up to 22,500 days (nearly 60 years) at a reference temperature of 20°C. These data were used as input into finite element analysis (FEA) codes that use highly realistic random, 3D concrete microstructures from reconstructed coarse limestone aggregates. Finite element analysis performed provides the ability to quickly upscale mortar viscoelastic behavior to long-term concrete creep/relaxation data. A master creep compliance curve, constructed from the TTS principle, spanning 27 years, was used to validate two and a half decades of simulated concrete creep. Concurrently, three different simulated wall specimens were designed to mimic the behavior of post-tensioned concrete nuclear containment facility vessel walls over time as a result of concrete creep. The specimens were designed with different thicknesses, transverse and longitudinal reinforcement ratios, and level of post-tensioning stress. Each specimen contained various instrumentation to measure internal concrete temperature, concrete strain, and post-tensioning strain hourly for over 3 years. The concrete creep model developed in this project, based on the FEA concrete simulations, was applied to simulate the structural-scale experiments of prestressed concrete walls conducted in this project using the Grizzly code. These models can represent the effects of reinforcing and prestressing. Although there are some discrepancies with the experimental data, the model can predict the overall trends of the creep response in these experiments. One of these experimental models was also applied to an extended time to demonstrate how the findings from this study can be used to predict the behavior of actual structures of interest that have been in service for extended periods of time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1981

The Theory and Practice of Estimating the Accuracy of Dynamic Flight-Determined Coefficients

Means of assessing the accuracy of maximum likelihood parameter estimates obtained from dynamic flight data are discussed. The most commonly used analytical predictors of accuracy are derived and compared from both statistical and simplified geometrics standpoints. The accuracy predictions are evaluated with real and simulated data, with an emphasis on practical considerations, such as modeling error. Improved computations of the Cramer-Rao bound to correct large discrepancies due to colored noise and modeling error are presented. The corrected Cramer-Rao bound is shown to be the best available analytical predictor of accuracy, and several practical examples of the use of the Cramer-Rao bound are given. Engineering judgement, aided by such analytical tools, is the final arbiter of accuracy estimation.

Maine, R. E.↗

NASA NTRS1998

Design, Evaluation and GCM-Performance of a New Parameterization for Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme (McRas)

A prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) was developed with the aim of improving cloud-microphysics, and cloud-radiation interactions in GCMs. McRAS distinguishes convective, stratiform, and boundary-layer clouds. The convective clouds merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds do so instantly. The cloud condensate transforms into precipitation following the auto-conversion relations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, and diffuse both horizontally and vertically with a fully active cloud-microphysics throughout its life-cycle, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry. An evaluation of McRAS in a single column model (SCM) with the GATE Phase III data has shown that McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. An evaluation with the ARM-CART SCM data in a cloud model intercomparison exercise shows reasonable but not an outstanding accurate simulation. Such a discrepancy is common to almost all models and is related, in part, to the input data quality. McRAS was implemented in the GEOS II GCM. A 50 month integration that was initialized with the ECMWF analysis of observations for January 1, 1987 and forced with the observed sea-surface temperatures and sea-ice distribution and vegetation properties (biomes, and soils), with prognostic soil moisture, snow-cover, and hydrology showed a very realistic simulation of cloud process, incloud water and ice, and cloud-radiative forcing (CRF). The simulated ITCZ showed a realistic time-mean structure and seasonal cycle, while the simulated CRF showed sensitivity to vertical distribution of cloud water which can be easily altered by the choice of time constant and incloud critical cloud water amount regulators for auto-conversion. The CRF and its feedbacks also have a profound effect on the ITCZ. Even though somewhat weaker than observed, the McRAS-GCM simulation produces robust 30-60 day oscillations in the 200 hPa velocity potential. Two ensembles of 4-summer (July, August, September) simulations, one each for 1987 and 1988 show that the McRAS-GCM simulates realistic and statistically significant precipitation differences over India, Central America, and tropical Africa. Several seasonal simulations were performed with McRAS-GEOS II GCM for the summer (June-July- August) and winter (December-January-February) periods to determine how the simulated clouds and CRFs would be affected by: i) advection of clouds; ii) cloud top entrainment instability, iii) cloud water inhomogeneity correction, and (iv) cloud production and dissipation in different cloud-processes. The results show that each of these processes contributes to the simulated cloud-fraction and CRF.

Sud, Y. C.↗

NASA NTRS1974

A line-blanketed model stellar atmosphere of Sirius

The method of artificial absorption edges is applied to a grid of model atmospheres to include the effects of hydrogen and metal line blanketing on the atmospheric structure. A best-fit model of Sirius is obtained which is free of the discrepancies inherent in unblanketed or partially blanketed models. All major spectral features calculated from the model agree with the corresponding observed features to within the observational uncertainty. Some additional properties of the models are discussed.

Fowler, J. W.↗

NASA NTRS2024

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Chengjia Han↗

DOE OSTI2024

Coupling-dependent antiferromagnetic-ferromagnetic ordering in a pinwheel artificial spin ice

Nanopatterned magnetic thin films offer a platform for exploration of tailored magnetic properties such as emergent long-range order. A prominent example is artificial spin ice (ASI), where an arrangement of nanoscale magnetic elements, acting as macrospins, interact via their dipolar fields. In this study, we discuss the transition from antiferromagnetic (AFM) to ferromagnetic (FM) long-range order in a square lattice ASI as the magnetic elements are gradually rotated through 45⁢° to a “pinwheel” configuration. The AFM-FM transition is observed experimentally using synchrotron radiation x-ray spectromicroscopy and occurs for a certain rotation angle of the nanomagnets, dependent on the dipolar coupling strength determined by the separation of the magnets in the lattice. Large-scale magnetic dipole simulations show that the point-dipole approximation fails to capture the correct AFM-FM transition angle. However, excellent agreement with experimental data is obtained using a dumbbell-dipole model, which better reflects the actual dipolar fields of the magnets. This model also explains the coupling dependence of the transition angle, another feature not captured by the point-dipole model. Our findings resolve a discrepancy between measurement and theory in previous work on “pinwheel” ASIs and establish the coupling dependence of the AFM-FM transition. The revised dipole model, with a more accurate representation of the stray field, offers more precise control of magnetic order in artificial spin systems.

Artificial spin ice↗

NASA NTRS1994

Constraints on hydrothermal heat flux through the oceanic lithosphere from global heat flow

A significant discrepancy exists between the heat flow measured at the seafloor and the higher values predicted by thermal models of the cooling lithosphere. This discrepancy is generally interpreted as indicating that the upper oceanic crust is cooled significantly by hydrothermal circulation. The magnitude of this heat flow discrepancy is the primary datum used to estimate the volume of hydrothermal flow, and the variation in the discrepancy with lithospheric age is the primary constraint on how the hydrothermal flux is divided between near-ridge and off-ridge environments. The resulting estimates are important for investigation of both the thermal structure of the lithosphere and the chemistry of the oceans. We reevaluate the magnitude and age variation of the discrepancy using a global heat flow data set substantially larger than in earlier studies, and the GDHI (Global Depth and Heat Flow) model that better predicts the heat flow. We estimate that of the predicted global oceanic heat flux of 32 x 10(exp 12) W, 34% (11 x 10(exp 12) W) occurs by hydrothermal flow. Approximately 30% of the hydrothermal heat flux occurs in crust younger than 1 Ma, so the majority of this flux is off-ridge. These hydrothermal heat flux estimates are upper bounds, because heat flow measurements require sediment at the site and so are made preferentially at topographic lows, where heat flow may be depressed. Because the water temperature for the near-ridge flow exceeds that for the off-ridge flow, the near-ridge water flow will be even a smaller fraction of the total water flow. As a result, in estimating fluxes from geochemical data, use of the high water temperatures appropriate for the ridge axis may significantly overestimate the heat flux for an assumed water flux or underestimate the water flux for an assumed heat flux. Our data also permit improved estimates of the 'sealing' age, defined as the age where the observed heat flow approximately equals that predicted, suggesting that hydrothermal heat transfer has largely ceased. Although earlier studies suggested major differences in sealing ages for different ocean basins, we find that the sealing ages for the Atlantic, Pacific, and Indian oceans are similar and consistent with the sealing age for the entire data set, 65 +/- 10 Ma. The previous inference of a young (approximately 20 Ma) sealing age for the Pacific appears to have biased downward several previous estimates of the global hydrothermal flux. The heat flow data also provide indirect evidence for the mechanism by which the hydrothermal heat flux becomes small, which has often been ascribed to isolation of the igneous crust from seawater due to the hydraulic conductivity of the intervening sediment. We find, however, that even the least sedimented sites show the systematic increase of the ratio of observed to predicted heat flow with age, although the more sedimented sites have a younger sealing age. Moreover, the heat flow discrepancy persists at heavily sedimented sites until approximately 50 Ma. It thus appears that approximately 100-200 m of sediment is neither necessary nor sufficient to stop hydrothermal heat transfer. We therefore conclude that the age of the crust is the primary control on the fraction of heat transported by hydrothermal flow and that sediment thickness has a lesser effect. This inference is consistent with models in which hydrothermal flow decreases with age due to reduced crustal porosity and hence permeability.

Stein, Carol A.↗

DOE OSTI2023

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗

NASA NTRS1976

Resolution of the discrepancy between Balmer alpha emission rates, the solar Lyman beta flux, and models of geocoronal hydrogen concentration

New satellite Balmer alpha measurements and solar Lyman beta flux and line profile measurements, together with new measurements of the zodiacal light intensity used in correcting both ground and satellite Balmer alpha measurements for the effects of the Fraunhofer line in the zodiacal light, have been used in a reevaluation of the long-standing discrepancy between ground-based Balmer alpha emission rates and other geocoronal hydrogen parameters. The solar Lyman beta line center flux is found to be (4.1 plus or minus 1.3) billion photons per sq cm per sec per angstrom at S(10.7) equals 110 and, together with a current hydrogen model which has 92,000 atoms per cu cm at 650 km for T(inf) equals 950 K, gives good agreement between calculated Balmer alpha emission rates and the ground-based and satellite measurements.

Levasseur, A.-C.↗

NASA NTRS1981

Ion plume/S-band carrier interaction study

A study was performed to determine the effects of a mercury ion thruster plume on an S-band telecommunication carrier. Experiments were carried out on a 30 cm thruster in a JPL test chamber. Results from simple analytical models were compared with the above measurements and major discrepancies were discovered. Modifications to the electron density model provided a qualitative explanation, but further work is necessary for a quantitative answer. The results indicate the effects of the plume, on S and X Band telecommunications will be minor, with the possible exception of critical angle blockage.

Stanton, P.↗

DOE OSTI2021

The Initial–Final Mass Relation for Hydrogen-deficient White Dwarfs

The initial–final mass relation represents the total mass lost by a star during the entirety of its evolution from the zero age main sequence to the white-dwarf cooling track. The semiempirical initial–final mass relation (IFMR) is largely based on observations of DA white dwarfs, the most common spectral type of white dwarf and the simplest atmosphere to model. We present a first derivation of the semiempirical IFMR for hydrogen-deficient (non-DA) white dwarfs in open star clusters. We identify a possible discrepancy between the DA and non-DA IFMRs, with non-DA white dwarfs ≈0.07 M {sub ⊙} less massive at a given initial mass. Such a discrepancy is unexpected based on theoretical models of non-DA formation and observations of field white dwarf mass distributions. If real, the discrepancy is likely due to enhanced mass loss during the final thermal pulse and renewed post-AGB evolution of the star. However, we are dubious that the mass discrepancy is physical and instead is due to the small sample size, to systematic issues in model atmospheres of non-DAs, and to the uncertain evolutionary history of Procyon B (spectral type DQZ). A significantly larger sample size is needed to test these assertions. In addition, we also present Monte Carlo models of the correlated errors for DA and non-DA white dwarfs in the initial–final mass plane. We find the uncertainties in initial–final mass determinations for individual white dwarfs can be significantly asymmetric, but the recovered functional form of the IFMR is grossly unaffected by the correlated errors.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Investigating Tropical Versus Extratropical Influences on the Southern Hemisphere Tropical Edge in the Unified Model

Abstract Since the late 1970s, observations have shown a widening of the tropical Hadley cell (HC) circulation. State‐of‐the‐art climate models reproduce the general trend along with a projected continuous expansion. Discrepancies in expansion rates of observation‐ and model‐based studies have been attributed to differences in applied methods, natural variability and model shortcomings. Furthermore, the driving influence of tropical or extratropical processes on these changes is not well understood. All of this highlights the dynamical mechanisms and the region of origin controlling the tropical width are still insufficiently understood. Here we examine the influence of systematic model biases of the atmosphere‐only Unified Model (UM) onto the simulation of the Southern Hemisphere (SH) tropical edge. We utilize nudged experiments with prescribed sea surface temperatures, where potential temperature and horizontal winds are relaxed back to ERA‐Interim reanalysis for a 20‐year period in selected regions. Correcting model biases in the tropics and extratropics separately allows us to dissect the dominant remote impacts of present model errors onto the SH tropical edge simulation. The experiments are applied to established tropical width metrics ranging from near‐surface to upper‐level metrics capturing the poleward flank of the HC. We find both regions work remotely to reduce errors in the UM fields and location of the tropical edge. Surprisingly, correcting the extratropical biases, south of 45°S, more consistently improves the tropical width across the metrics and seasons than nudging the tropics (10°N–10°S). These findings demonstrate the substantial role of extratropical influences in locating the SH tropical edge.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

Sounding rocket observation of a hot atomic oxygen geocorona

A sounding rocket measurement of the ultraviolet, atomic oxygen dayglow reveals an excess of emission compared to standard thermospheric model calculations at exospheric altitudes. We explore two explanations for this discrepancy: a breakdown of the radiative transfer model due to nonlocal thermal equilibrium (non-LTE) conditions above the exobase and a hot atomic oxygen geocorona. In particular, the effects of non-LTE on the 3P2, 1, 0 sublevel populations are modeled, and a hot O component in the upper thermosphere and lower exosphere is added to investigate the effects on the modeled emissions. For both cases, the data are reanalyzed and compared with the results using a standard LTE model. A hot O geocorona having a peak density of 10(exp 6)/cc at 550 km and a temperature of 4000 K is consistent with the data and appears to be the most reasonable explanation of the high-altitude enhanced emissions observed in the data.

Cotton, Daniel M.↗

DOE OSTI2019

Ratio method for estimating uncertainty in calculated gamma cascades

The assessment of uncertainty on deduced quantities obtained through both measurement and modeling must include contributions from both components. There are several methods to estimate the uncertainty due to modeling, such as the parametric uncertainty and that stemming from model bias. However, in the case where experimental data exists for partial cross sections, such as discrete gammas emitted in the de-excitation of the product nucleus following the reaction, the discrepancy between the measured and modeled gamma cascades provides more information and allows for uncertainty estimation that can account for all types of model and data uncertainty. This work presents a method for estimating that uncertainty, using ratios of gammas to get a measure of the accuracy of different parts of the modeled gamma cascade. The gamma with the lowest intensity uncertainty is shown to be the best for determining the channel cross section with realistic uncertainties, indicating that it should be used rather than the most intense gamma or a sum of gammas. In conclusion, this method provides both a simple procedure for calculating realistic uncertainties and identifies the best gamma for use in converting a set of measured partial gamma cross sections to the deduced total channel cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Reconstructing gravity on cosmological scales

We present the data-driven late-time reconstruction of gravitational theories and dark energy models on cosmological scales. We showcase the power of present cosmological probes at constraining these models and quantify the knowledge of their properties that can be acquired through state of the art data. This reconstruction exploits the power of the effective field theory approach to dark energy and modified gravity phenomenology, which compresses the freedom in defining such models into a finite set of functions that can be reconstructed across cosmic times using cosmological data. We consider several model classes described within this framework and thoroughly discuss their phenomenology and data implications. In this work, we find that some models can alleviate the present discrepancy in the determination of the Hubble constant as inferred from the cosmic microwave background and as directly measured. This results in a statistically significant preference for the reconstructed theories over the standard cosmological model.

79 ASTRONOMY AND ASTROPHYSICS↗