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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

2SXPS: An Improved and Expanded Swift X-Ray Telescope Point-source Catalog

We present the 2SXPS (Swift-XRT Point Source) catalog, containing 206,335 point sources detected by the Swift X-ray Telescope (XRT) in the 0.3–10 keV energy range. This catalog represents a significant improvement over 1SXPS, with double the sky coverage (now 3790 deg2), and several significant developments in source detection and classification. In particular, we present for the first time techniques to model the effect of stray light—significantly reducing the number of spurious sources detected. These techniques will be very important for future, large effective area X-ray missions, such as the forthcoming Athena X-ray observatory. We also present a new model of the XRT point-spread function and a method for correctly localizing and characterizing piled-up sources. We provide light curves—in four energy bands, two hardness ratios, and two binning timescales—for every source, and from these deduce that over 80,000 of the sources in 2SXPS are variable in at least one band or hardness ratio. The catalog data can be queried or downloaded via a web interface at https://www.swift.ac.uk/2SXPS, via HEASARC, or in Vizier (IX/58).

Catalogs↗
DOE OSTI2023

Light elements Na and Al in 58 bulge spheroid stars from APOGEE

ABSTRACT We identified a sample of 58 candidate stars with metallicity [Fe/H] ≲ −0.8 that likely belong to the old bulge spheroid stellar population, and analyse their Na and Al abundances from Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectra. In a previous work, we inspected APOGEE-Stellar Parameter and Chemical Abundance Pipeline abundances of C, N, O, Mg, Al, Ca, Si, and Ce in this sample. Regarding Na lines, one of them appears very strong in about 20 per cent of the sample stars, but it is not confirmed by other Na lines, and can be explained by sky lines, which affect the reduced spectra of stars in a certain radial velocity range. The Na abundances for 15 more reliable cases were taken into account. Al lines in the H band instead appear to be very reliable. Na and Al exhibit a spread in abundances, whereas no spread in N abundances is found, and we found no correlation between them, indicating that these stars could not be identified as second-generation stars that originated in globular clusters. We carry out the study of the behaviour of Na and Al in our sample of bulge stars and literature data by comparing them with chemodynamical evolution model suitable for the Galactic bulge. The Na abundances show a large spread, and the chemodynamical models follow the main data, whereas for aluminum instead, the models reproduce very satisfactorily the nearly secondary-element behaviour of aluminum in the metallicity range below [Fe/H] ≲ −1.0. For the lower-metallicity end ([Fe/H < −2.5), hypernovae are assumed to be the main contributor to yields.

Astronomy & Astrophysics↗
DOE OSTI2022

When Will MISR Detect Rising High Clouds?

It is predicted by both theory and models that high-altitude clouds will occur higher in the atmosphere as a result of climate warming. This produces a positive longwave feedback and has a substantial impact on the Earth's response to warming. This effect is well established by theory, but is poorly constrained by observations, and there is large spread in the feedback strength between climate models. For this study, we use the NASA Multi-angle Imaging SpectroRadiometer (MISR) to examine changes in Cloud-Top-Height (CTH). MISR uses a stereo-imaging technique to determine CTH. This approach is geometric in nature and insensitive to instrument calibration and therefore is well suited for trend analysis and studies of variability on long time scales. In this article we show that the current MISR record does have an increase in CTH for high-altitude cloud over Southern Hemisphere (SH) oceans but not over Tropical or the Northern Hemisphere (NH) oceans. We use climate model simulations to estimate when MISR might be expected to detect trends in CTH, that include the NH. The analysis suggests that according to the models used in this study MISR should detect changes over the SH ocean earlier than the NH, and if the model predictions are correct should be capable of detecting a trend over the Tropics and NH very soon (3–10 years). This result highlights the potential value of a follow-on mission to MISR, which no longer maintains a fixed equator crossing time and is unlikely to be making observations for another 10 years.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Hyper Suprime-Cam Year 3 results: Cosmology from cosmic shear power spectra

Here, we measure weak lensing cosmic shear power spectra from the 3-year galaxy shear catalog of the Hyper Suprime-Cam (HSC) Subaru Strategic Program imaging survey. The shear catalog covers 416 deg 2 of the northern sky, with a mean i-band seeing of 0.59 arcsec and an effective galaxy number density of 15 arcmin —2 within our adopted redshift range. With an i-band magnitude limit of 24.5 mag, and four tomographic redshift bins spanning 0.3 ≤ z ph ≤ 1.5 based on photometric redshifts, we obtain a high-significance measurement of the cosmic shear power spectra, with a signal-to-noise ratio of approximately 26.4 in the multipole range 300 < ℓ < 1800. The accuracy of our power spectrum measurement is tested against realistic mock shear catalogs, and we use these catalogs to get a reliable measurement of the covariance of the power spectrum measurements. We use a robust blinding procedure to avoid confirmation bias, and model various uncertainties and sources of bias in our analysis, including point spread function systematics, redshift distribution uncertainties, the intrinsic alignment of galaxies and the modeling of the matter power spectrum. For a flat Λ CDM model, we find S 8 ≡ σ 8 (Ω m /0.3) 0.5 = ${0.776}_{—0.033}^{+0.032}$, which is in excellent agreement with the constraints from the other HSC Year 3 cosmology analyses, as well as those from a number of other cosmic shear experiments. This result implies a ~2σ-level tension with the Planck 2018 cosmology. We study the effect that various systematic errors and modeling choices could have on this value, and find that they can shift the best-fit value of S 8 by no more than ~ 0.5σ, indicating that our result is robust to such systematics.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1979

Theoretical analysis of an augmentor wing for a VTOL fighter

A method based on potential flow theory was developed for predicting forces and moments acting on augmentor wings for prescribed ejector jet characteristics. A three dimensional nonplanar vortex lattice is laid out on the chordal planes of the augmentor wing components. Jet induced effects are included in the boundary condition from which the horseshoe vortex strengths are obtained. The jet within the diffusor is made to expand from the primary nozzles to the diffusor exit and is represented by a distribution of vorticity on the jet boundary to provide proper entrainment. The jet downstream of the diffusor exit is modeled by a vorticity distribution and blockage panels and its centerline location and spreading rate are taken from experimental data. The vortex lattice and jet models are used in an iterative manner until the predicted diffusor exit velocity matches the specified one. Some comparisons with available data show good agreement at lower power settings.

Dillenius, M. F. E.↗
NASA NTRS2015

Calibration of Predictor Models Using Multiple Validation Experiments

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Crespo, Luis G.↗
DOE OSTI2020

A thermodynamics-based damage model for the non-linear mechanical behavior of SiC/SiC ceramic matrix composites in irradiation and thermal environments

A damage model is developed and validated with experimental data for the non-linear mechanical behavior of SiC/SiC composite materials in nuclear applications. Cyclic thermal and mechanical loading associated with neutron irradiation effects of these composites leads to wide-spread and progressive micro-cracking that leads to loss of thermal conductivity and further enhancement of thermo-mechanical damage. A physics-based model of wide-spread micro-cracking is developed within the thermodynamic framework of continuum damage mechanics. Evolution equations for damage parameters that describe the growth of continuum damage are developed, where the material variables are obtained from experiments. The model novelty is in coupling mechanical, thermal, and irradiation damage through a consistent thermodynamic framework, including loss of thermal conductivity due to the evolution of mechanically induced micro-cracks. A number of thermo-mechanical experiments were conducted to confirm model assumptions. The model is shown to be validated with out-of-pile experiments, and then implemented using commercial finite element code COMSOL to the fuel cladding problem with normal and high radiation dose cases.

Materials Science↗
NASA NTRS1984

Dynamics of dendritic pattern formation

This paper is a brief review of recent and ongoing developments in the theory of dendritic pattern formation. A marginal stability hypothesis has achieved some success in predicting dendritic growth rates, but a fully nonlinear dynamic theory of the dendritic growth mechanism has yet to be developed. A possible clue for the construction of such a theory is the existence of a class of one-dimensional models in which a pattern is found to spread into an unstable region by propagating at the slowest stable speed. This mathematical realization of the marginal stability mechanism has led to the development of a boundary layer model which describes localized dynamics of fully two- or three-dimensional solidification fronts and which retains some of the mathematical features of the propagating systems. Preliminary results of numerical calculations using the boundary layer model indicate that it is capable of probing fully nonlinear features of dendritic pattern formation.

Langer, J. S.↗
NASA NTRS2002

A Good Neighborhood for Cells: Bioreactor Demonstration System (BDS-05)

Good neighborhoods help you grow. As with a city, the lives of a cell are governed by its neighborhood connections Connections that do not work are implicated in a range of diseases. One of those connections - between prostate cancer and bone cells - will be studied on STS-107 using the Bioreactor Demonstration System (BDS-05). To improve the prospects for finding novel therapies, and to identify biomarkers that predict disease progression, scientists need tissue models that behave the same as metastatic or spreading cancer. This is one of several NASA-sponsored lines of cell science research that use the microgravity environment of orbit in an attempt to grow lifelike tissue models for health research. As cells replicate, they "self associate" to form a complex matrix of collagens, proteins, fibers, and other structures. This highly evolved microenvironment tells each cell who is next door, how it should grow arid into what shapes, and how to respond to bacteria, wounds, and other stimuli. Studying these mechanisms outside the body is difficult because cells do not easily self-associate outside a natural environment. Most cell cultures produce thin, flat specimens that offer limited insight into how cells work together. Ironically, growing cell cultures in the microgravity of space produces cell assemblies that more closely resemble what is found in bodies on Earth. NASA's Bioreactor comprises a miniature life support system and a rotating vessel containing cell specimens in a nutrient medium. Orbital BDS experiments that cultured colon and prostate cancers have been highly promising.

Chung, Leland W. K.↗
DOE OSTI2021

Machine learning and artificial intelligence for wildfire prediction

Wildfire ignition, intensity, and spread rates are tightly linked with water cycle extremes. The science of wildfire prediction has traditionally encompassed the use of physical and empirical models to quantify the direction and speed of fire spread, plume injection and fire-aerosol impacts on atmospheric composition, predictions of fire season severity on subseasonal-to-seasonal (S2S) time scales, and assessment of the spatial and temporal patterns of fire risk across landscapes. Together with expanding observation networks, machine learning and artificial intelligence (AI) have the potential to revolutionize the application of such models for fire science, saving lives, protecting critical infrastructure, and providing more accurate estimates of wildfire-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

A Statistical Model of Tropical Cyclone Tracks in the Western North Pacific with ENSO-Dependent Cyclogenesis

A new statistical model for western North Pacific Ocean tropical cyclone genesis and tracks is developed and applied to estimate regionally resolved tropical cyclone landfall rates along the coasts of the Asian mainland, Japan, and the Philippines. The model is constructed on International Best Track Archive for Climate Stewardship (IBTrACS) 1945-2007 historical data for the western North Pacific. The model is evaluated in several ways, including comparing the stochastic spread in simulated landfall rates with historic landfall rates. Although certain biases have been detected, overall the model performs well on the diagnostic tests, for example, reproducing well the geographic distribution of landfall rates. Western North Pacific cyclogenesis is influenced by El Nino-Southern Oscillation (ENSO). This dependence is incorporated in the model s genesis component to project the ENSO-genesis dependence onto landfall rates. There is a pronounced shift southeastward in cyclogenesis and a small but significant reduction in basinwide annual counts with increasing ENSO index value. On almost all regions of coast, landfall rates are significantly higher in a negative ENSO state (La Nina).

Yonekura, Emmi↗
DOE OSTI2021

The APOGEE Library of Infrared SSP Templates (A-LIST): High-resolution Simple Stellar Population Spectral Models in the H Band

Integrated light spectroscopy from galaxies can be used to study the stellar populations that cannot be resolved into individual stars. This analysis relies on stellar population synthesis (SPS) techniques to study the formation history and structure of galaxies. However, the spectral templates available for SPS are limited, especially in the near-infrared (near-IR). We present A-LIST (APOGEE Library of Infrared SSP Templates), a new set of high-resolution, near-IR SSP spectral templates spanning a wide range of ages (2–12 Gyr), metallicities ( − 2.2 < [M/H] < + 0.4) and α abundances ( − 0.2 < [α/M] < + 0.4). This set of SSP templates is the highest resolution (R ∼ 22, 500) available in the near-IR, and the first such based on an empirical stellar library. Our models are generated using spectra of ∼300,000 stars spread across the Milky Way, with a wide range of metallicities and abundances, from the APOGEE survey. We show that our model spectra provide accurate fits to M31 globular cluster spectra taken with APOGEE, with best-fit metallicities agreeing with those of previous estimates to within ∼0.1 dex. We also compare these model spectra to lower-resolution E-MILES models and demonstrate that we recover the ages of these models to within ∼1.5 Gyr. This library is available in https://github.com/aishashok/ALIST-library.

47 OTHER INSTRUMENTATION↗
NASA NTRS1993

Formation of perched lava ponds on basaltic volcanoes: Interaction between cooling rate and flow geometry allows estimation of lava effusion rates

Perched lava ponds are infrequent but distinctive topographic features formed during some basaltic eruptions. Two such ponds, each approximately 150 m in diameter, formed during the 1968 eruption at Napau Crater and the 1974 eruption of Mauna Ulu, both on Kilauea Volcano, Hawaii. Each one formed where a channelized, high volume flux lava flow encountered a sharp reduction of slope: the flow spread out radially and stalled, forming a well-defined terminal levee enclosing a nearly circular lava pond. We describe a model of how cooling limits the motion of lava spreading radially into a pond and compare this with the case of a channelized flow. The difference in geometry has a major effect, such that the size of a pond is a good indicator of the volume flux of the lava forming it. Lateral spreading on distal shallow slopes is a major factor limiting the lengths of lava flows.

Wilson, L.↗
DOE OSTI2020

System Design of a 2.0 MWth Sodium/Molten Salt Pilot System

Nitrate molten salt concentrating solar power (CSP) systems are currently deployed globally and are considered state-of the art heat transfer fluids (HTFs) for present day high-temperature operation. Although slightly higher limits may be possible with molten salt, to fully realize SunShot efficiency goals of $15/kWhth HTFs and an LCOE of 6¢/kWh, HTF technologies working at higher temperatures (e.g., 650 °C to 750 °C) will require an alternative to molten salts, such as with alkali metal systems. This investigation explores the development of a 2.0 MWth sodium receiver system that employs a sodium receiver as the HTF, as well as with a ternary chloride (20%NaCl/40%MgCl/40%KCl by mol wt.%) salt as a thermal energy storage (TES) medium to facilitate a 6-hr. storage duration. A sodium-to-salt heat exchanger model as well as a salt-to-sCO2 primary heat exchanger model are employed and evaluated in this investigation. A thermodynamic system design model was developed using Engineering Equation Solver (EES) where state properties were calculated at inlets and outlets along both hot and cold legs of the pilot-scale plant. This investigation assesses receiver performance as well as system efficiency studies for the pump and system operational ranges. Results found that high efficiency sodium receivers were found to have higher heat transfer coefficients and required far less spreading of incident flux. The system performance model results suggest that for a pump speed of 2400 RPM, respective hot and cold pump TDH values were determined to be 260.1–307 ft. and 260.1–307 ft for pump flow rates of 90–120 GPM.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

Mathematical Model of ATM Activation and Chromatin Relaxation by Ionizing Radiation

We propose a comprehensive mathematical model to study the dynamics of ionizing radiation induced Ataxia-telangiectasia mutated (ATM) activation that consists of ATM activation through dual mechanisms: the initiative activation pathway triggered by the DNA damage-induced local chromatin relaxation and the primary activation pathway consisting of a self-activation loop by interplay with chromatin relaxation. The model is expressed as a series of biochemical reactions, governed by a system of differential equations and analyzed by dynamical systems techniques. Radiation induced double strand breaks (DSBs) cause rapid local chromatin relaxation, which is independent of ATM but initiates ATM activation at damage sites. Key to the model description is how chromatin relaxation follows when active ATM phosphorylates KAP-1, which subsequently spreads throughout the chromatin and induces global chromatin relaxation. Additionally, the model describes how oxidative stress activation of ATM triggers a self-activation loop in which PP2A and ATF2 are released so that ATM can undergo autophosphorylation and acetylation for full activation in relaxed chromatin. In contrast, oxidative stress alone can partially activate ATM because phosphorylated ATM remains as a dimer. The model leads to predictions on ATM mediated responses to DSBs, oxidative stress, or both that can be tested by experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2019

Taking Climate Model Evaluation to the Next Level

Earth system models are complex and represent a large number of processes, resulting in a persistent spread across climate projections for a given future scenario. Owing to different model performances against observations and the lack of independence among models, there is now evidence that giving equal weight to each available model projection is suboptimal. This Perspective discusses newly developed tools that facilitate a more rapid and comprehensive evaluation of model simulations with observations, process-based emergent constraints that are a promising way to focus evaluation on the observations most relevant to climate projections, and advanced methods for model weighting. These approaches are needed to distil the most credible information on regional climate changes, impacts, and risks for stakeholders and policy-makers.

Eyring, Veronika↗
DOE OSTI2025

CANA v1.0.0: efficient quantification of canalization in automata networks

The biomolecular networks underpinning cell function exhibit canalization, or the buffering of fluctuations required to function in a noisy environment. We present a new major release of $\tt{CANA}$, v1.0.0, an open-source Python package for understanding canalization in automata network models, discrete dynamical systems in which activation of biomolecular entities (e.g. transcription of genes) is modeled as the activity of coupled automata. One understudied putative mechanism for canalization is the functional equivalence of biomolecular regulators (e.g. among the transcription factors for a gene). We study this mechanism using the theory of symmetry in discrete functions. We present a new exact method, $\tt{schematodes}$, for finding maximal symmetry groups among the inputs to discrete functions, and integrate it into $\tt{CANA}$. The $\tt{schematodes}$ method substantially outperforms the inexact method of previous $\tt{CANA}$ versions both in speed and accuracy. We apply $\tt{CANA}$ v1.0.0 to study symmetry in 74 experimentally supported automata network models from the Cell Collective (CC) repository. The symmetry distribution is significantly different in the CC than in random automata with the same in-degree (connectivity) and bias (average output) (Kolmogorov–Smirnov test, P ≪ .001). Its spread is much wider than in a null model (IQR 0.31 versus IQR 0.20 with equal medians), demonstrating that the CC is enriched in functions with extreme symmetry or asymmetry.

Boolean networks↗
DOE OSTI2026

Effects of slope steepness and cross-slope wind speed on fire spreading behavior for various vegetation

Wildland fire behavior is significantly influenced by environmental factors such as slope steepness, wind speed, and fuel type. Understanding these interactions is critical for improving predictive models and fire management. This study explores how slope steepness and cross-slope wind speed influence fire spread dynamics in various fuel bed types. Simulations are conducted using a physics-based wildland fire model, HIGRAD/FIRETEC, across six slope angles (0–50 %), four cross-slope wind speeds (4–10 m s –1 ), and three fuel bed types (grass, shrubland, and forest). Representative cases are additionally compared with FARSITE fireline evolution. Fire behavior is categorized into distinct propagation types based on spread characteristics and analyzed. The fire propagation angle, which indicates deviation from the wind direction, generally increases with steeper slopes and decreases with stronger cross-slope winds. Secondary upslope propagation is observed in shrubland under moderate slopes, while secondary downwind propagation occurs in all fuel beds at higher wind speeds. These findings highlight fire spread characteristics that differ from predictions by traditional models like Rothermel’s. By capturing complex propagation patterns and dynamics, this study demonstrates the value of a physics-based, atmosphere-fire coupled model for accurate wildland fire prediction. Incorporating secondary propagations and the influence of fuel bed complexities into predictive models can improve the accuracy of fire spread forecasts, enabling more effective fire management and risk mitigation efforts.

54 ENVIRONMENTAL SCIENCES↗