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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 OSTI2018

Relativistic, Viscous, Radiation Hydrodynamic Simulations of Geometrically Thin Disks. I. Thermal and Other Instabilities

We introduce results from two-dimensional, general relativistic, viscous, radiation hydrodynamic numerical simulations of Shakura–Sunyaev thin disks accreting onto stellar-mass Schwarzschild black holes. We consider cases on both the gas- and radiation-pressure-dominated branches of the thermal equilibrium curve, with mass accretion rates spanning the range from $\dot{M}=0.01{L}_{\mathrm{Edd}}/{c}^{2}$ to 10L Edd/c 2 . The simulations directly test the stability of this standard disk model on the different branches. We find clear evidence of thermal instability for all radiation-pressure-dominated disks, resulting universally in the vertical collapse of the disks, which in some cases then settle onto the stable, gas-pressure-dominated branch. Although these results are consistent with decades-old theoretical predictions, they appear to be in conflict with available observational data from black hole X-ray binaries. Additionally, we find evidence for a radiation-pressure-driven instability that breaks the unstable disks up into alternating rings of high and low surface density on a timescale comparable to the thermal collapse. Since radiation is included self-consistently in the simulations, we are able to calculate light curves and power density spectra (PDS). Mostly, we measure radiative efficiencies (ratio of luminosity to mass accretion rate) close to 6%, as expected for a nonrotating black hole. The PDS appear as broken power laws, with a break typically around 100 Hz. There is no evidence of significant excess power at any frequencies, i.e., no quasi-periodic oscillations are observed.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

The influence of neutral winds on He(+) distributions in the equatorial ionospshere

The effects of F-region neutral winds on the distribution of He(+) in the equatorial ionosphere have been examined using a theoretical model and an observational data set. It is shown by the model that components of neutral wind in the magnetic meridian up to only 50 m/s can produce He(+) gradients in the northern and southern sectors of a flux tube that differ by more than 80 percent. This is associated with interhemisphere transport velocities of He(+) as large as 15 m/s at 800 km. A substantial latitude gradient in the He(+) distribution across the dip equator also results from the redistribution of He(+). The changes in the He(+) concentration at the dip equator and the latitude distribution of H(+) in response to different neutral wind components is determined from the model and used to construct longitude distributions of He(+) to compare with observations made at equinox. Good agreement between the calculations and observations is obtained both at the geographic and geomagnetic equators using the relationship between neutral winds, interhemispheric transport velocity and He(+) concentration derived from the model. If these relationships can be extrapolated to accommodate the different conditions expected during solstice, the He(+) distributions expected during this season can also be discussed.

Murphy, J. A.↗
DOE OSTI2020

Predicting lake surface water phosphorus dynamics using process-guided machine learning

Phosphorus (P) loading to lakes is degrading the quality and usability of water globally. Accurate predictions of lake P dynamics are needed to understand whole-ecosystem P budgets, as well as the consequences of changing lake P concentrations for water quality. However, complex biophysical processes within lakes, along with limited observational data, challenge our capacity to reproduce short-term lake dynamics needed for water quality predictions, as well as long-term dynamics needed to understand broad scale controls over lake P. Here we use an emerging paradigm in modeling, process-guided machine learning (PGML), to produce a phosphorus budget for Lake Mendota (Wisconsin, USA) and to accurately predict epilimnetic phosphorus over a time range of days to decades. In our implementation of PGML, which we term a Process-Guided Recurrent Neural Network (PGRNN), we combine a process-based model for lake P with a recurrent neural network, and then constrain the predictions with ecological principles. We test independently the process-based model, the recurrent neural network, and the PGRNN to evaluate the overall approach. The process-based model accounted for most of the observed pattern in lake P; however it missed the long-term trend in lake P and had the worst performance in predicting winter and summer P in surface waters. The root mean square error (RMSE) for the process-based model, the recurrent neural network, and the PGRNN was 33.0 μg P L -1 , 22.7 μg P L -1 , and 20.7 μg P L -1 , respectively. All models performed better during summer, with RMSE values for the three models (same order) equal to 14.3 μg P L -1 , 10.9 μg P L -1 , and 10.7 μg P L -1 . Although the PGRNN had only marginally better RMSE during summer, it had lower bias and reproduced long-term decreases in lake P missed by the other two models. For all seasons and all years, the recurrent neural network had better predictions than process alone, with root mean square error (RMSE) of 23.8 μg P L -1 and 28.0 μg P L -1 , respectively. The output of PGRNN indicated that new processes related to water temperature, thermal stratification, and long term changes in external loads are needed to improve the process model. By using ecological knowledge, as well as the information content of complex data, PGML shows promise as a technique for accurate prediction in messy, real-world ecological dynamics, while providing valuable information that can improve our understanding of process.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Mesoscale acid deposition modeling studies

The work performed in support of the EPA/DOE MADS (Mesoscale Acid Deposition) Project included the development of meteorological data bases for the initialization of chemistry models, the testing and implementation of new planetary boundary layer parameterization schemes in the MASS model, the simulation of transport and precipitation for MADS case studies employing the MASS model, and the use of the TASS model in the simulation of cloud statistics and the complex transport of conservative tracers within simulated cumuloform clouds. The work performed in support of the NASA/FAA Wind Shear Program included the use of the TASS model in the simulation of the dynamical processes within convective cloud systems, the analyses of the sensitivity of microburst intensity and general characteristics as a function of the atmospheric environment within which they are formed, comparisons of TASS model microburst simulation results to observed data sets, and the generation of simulated wind shear data bases for use by the aviation meteorological community in the evaluation of flight hazards caused by microbursts.

Kaplan, Michael L.↗
NASA NTRS1994

More missing stellar opacity?

Observational data for Population I stars have shown that blue loops on the Hertzsprung-Russell (H-R) diagram form for stellar masses as low as approximately 4 solar mass. However, current state-of-the-art stellar models, unlike the older ones that were based on smaller opacities, fail to loop out of the red-giant region during core helium burning for masses less than 7 solar mass. A possible explanation is that the currently used Livermore opacities need to be further increased, by at least 70%, at temperatures characteristic of the base of the outer convection zone, around 1 x 10(exp 6) K. Indeed, no other suggested remedy seems to yield a blue loop at the lowest observed loop luminosities.

Stothers, Richard B.↗
DOE OSTI2017

Search for associated production of dark matter with a Higgs boson decaying to $ \mathrm{b}\overline{\mathrm{b}} $ or $\gamma \gamma$ at $ \sqrt{s}=13$ TeV

A search for dark matter is performed looking for events with large missing transverse momentum and a Higgs boson decaying either to a pair of bottom quarks or to a pair of photons. The data from proton-proton collisions at a center-of-mass energy of 13 TeV, collected in 2015 with the CMS detector at the LHC, correspond to an integrated luminosity of 2.3 fb$^{−1}$. Results are interpreted in the context of a Z′-two-Higgs-doublet model, where the gauge symmetry of the standard model is extended by a U(1)$_{Z ′}$ group, with a new massive Z′ gauge boson, and the Higgs sector is extended with four additional Higgs bosons. In this model, a high-mass resonance Z′ decays into a pseudoscalar boson A and a light SM-like scalar Higgs boson, and the A decays to a pair of dark matter particles. No significant excesses are observed over the background prediction. Combining results from the two decay channels yields exclusion limits in the signal cross section in the m$_{Z ′}$ - m$_{A}$ phase space. For example, the observed data exclude the Z$^{′}$ mass range from 600 to 1860 GeV, for Z′ coupling strength g$_{Z ′}$ = 0.8, the coupling of A with dark matter particles g$_{χ}$ = 1, the ratio of the vacuum expectation values tan β = 1, and m$_{A}$ = 300 GeV. The results of this analysis are valid for any dark matter particle mass below 100 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Linking local impacts to changes in climate: a guide to attribution

© 2015, Springer-Verlag Berlin Heidelberg. Assessing past impacts of observed climate change on natural, human and managed systems requires detailed knowledge about the effects of both climatic and other drivers of change, and their respective interaction. Resulting requirements with regard to system understanding and long-term observational data can be prohibitive for quantitative detection and attribution methods, especially in the case of human systems and in regions with poor monitoring records. To enable a structured examination of past impacts in such cases, we follow the logic of quantitative attribution assessments, however, allowing for qualitative methods and different types of evidence. We demonstrate how multiple lines of evidence can be integrated in support of attribution exercises for human and managed systems. Results show that careful analysis can allow for attribution statements without explicit end-to-end modeling of the whole climate-impact system. However, care must be taken not to overstate or generalize the results and to avoid bias when the analysis is motivated by and limited to observations considered consistent with climate change impacts.

Hansen, Gerrit↗
DOE OSTI2016

Global leaf trait estimates biased due to plasticity in the shade

The study of leaf functional trait relationships, the so-called leaf economics spectrum , is based on the assumption of high-light conditions (as experienced by sunlit leaves). Owing to the exponential decrease of light availability through canopies, however, the vast majority of the world's vegetation exists in at least partial shade. Plant functional traits vary in direct dependence of light availability, with different traits varying to different degrees, sometimes in conflict with expectations from the economic spectrum. This means that the derived trait relationships of the global leaf economic spectrum are probably dependent on the extent to which observed data in existing large-scale plant databases represent high-light conditions. Here, using an extensive worldwide database of within-canopy gradients of key physiological, structural and chemical traits, along with three different global trait databases we show that: (1) accounting for light-driven trait plasticity can reveal novel trait relationships, particularly for highly plastic traits (for example, the relationship between net assimilation rate per area (A a ) and leaf mass per area (LMA)); and (2) a large proportion of leaf traits in current global plant databases reported as measured in full sun were probably measured in the shade. Our results show that even though the majority of leaves exist in the shade, along with a large proportion of observations, our current understanding is too focused on conditions in the sun.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Bayesian inference of Stochastic reaction networks using Multifidelity Sequential Tempered Markov Chain Monte Carlo

Stochastic reaction network models are often used to explain and predict the dynamics of gene regulation in single cells.These models usually involve several parameters, such as the kinetic rates of chemical reactions, that are not directly measurable and must be inferred from experimental data. Bayesian inference provides a rigorous probabilistic frame-work for identifying these parameters by finding a posterior parameter distribution that captures their uncertainty.Traditional computational methods for solving inference problems such as Markov Chain Monte Carlo methods based on classical Metropolis-Hastings algorithm involve numerous serial evaluations of the likelihood function, which in turn requires expensive forward solutions of the chemical master equation (CME). We propose an alternate approach based on a multifidelity extension of the Sequential Tempered Markov Chain Monte Carlo (ST-MCMC) sampler. This algorithm is built upon Sequential Monte Carlo and solves the Bayesian inference problem by decomposing it into a sequence of efficiently solved subproblems that gradually increase both model fidelity and the influence of the observed data. We reformulate the finite state projection (FSP) algorithm, a well-known method for solving the CME, to produce a hierarchy of surrogate master equations to be used in this multifidelity scheme. To determine the appropriate fidelity, we introduce a novel information-theoretic criteria that seeks to extract the most information about the ultimate Bayesian posterior from each model in the hierarchy without inducing significant bias. This novel sampling scheme is tested with high performance computing resources using biologically relevant problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Thermal Modeling of Comet-like Objects from AKARI Observation

We investigated the physical properties of the comet-like objects 107P/(4015) Wilson–Harrington (4015WH) and P/2006 HR30 (Siding Spring; HR30) by applying a simple thermophysical model to the near-infrared spectroscopy and broadband observation data obtained by the AKARIsatellite of JAXA when they showed no detectable comet-like activity. We selected these two targets because the tendency of thermal inertia to decrease with the size of an asteroid, which has been demonstrated in recent studies, has not been confirmed for comet-like objects. It was found that 4015WH, which was originally discovered as a comet but has not shown comet-like activity after its discovery, has effective size D = 3.74–4.39 km and geometric albedo p{sub V}≈0.040--0.055 with thermal inertia Γ=100--250 J m{sup −2} K{sup −1} s{sup −1/2}. The corresponding grain size is estimated as 1–3 mm. We also found that HR30, which was observed as a bare cometary nucleus at the time of our observation, has D=23.9--27.1 km and p{sub V}=0.035--0.045 with Γ=250--1000 J m{sup −2} K{sup −1} s{sup −1/2}. We conjecture the pole latitude −20{sup ∘}≲β{sub s}≲+60{sup ∘}. The results for both targets are consistent with previous studies. Based on the results, we propose that comet-like objects are not clearly distinguishable from their asteroidal counterparts on the D–Γ plane.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2019

Understanding Heating in Active Region Cores through Machine Learning. I. Numerical Modeling and Predicted Observables

To adequately constrain the frequency of energy deposition in active region cores in the solar corona, systematic comparisons between detailed models and observational data are needed. In this paper, we describe a pipeline for forward modeling active region emission using magnetic field extrapolations and field-aligned hydrodynamic models. We use this pipeline to predict time-dependent emission from active region NOAA 1158 for low-, intermediate-, and high-frequency nanoflares. In each pixel of our predicted multi-wavelength, time-dependent images, we compute two commonly used diagnostics: the emission measure slope and the time lag. We find that signatures of the heating frequency persist in both of these diagnostics. In particular, our results show that the distribution of emission measure slopes narrows and the mean decreases with decreasing heating frequency and that the range of emission measure slopes is consistent with past observational and modeling work. Furthermore, we find that the time lag becomes increasingly spatially coherent with decreasing heating frequency while the distribution of time lags across the whole active region becomes more broad with increasing heating frequency. In a follow-up paper, we train a random forest classifier on these predicted diagnostics and use this model to classify real observations of NOAA 1158 in terms of the underlying heating frequency.

UV radiation↗
NASA NTRS2015

Real-Time Kennedy Space Center and Cape Canaveral Air Force Station High-Resolution Model Implementation and Verification

NASA's Launch Services Program, Ground Systems Development and Operations, Space Launch System and other programs at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) use the daily and weekly weather forecasts issued by the 45th Weather Squadron (45 WS) as decision tools for their day-to-day and launch operations on the Eastern Range (ER). Examples include determining if they need to limit activities such as vehicle transport to the launch pad, protect people, structures or exposed launch vehicles given a threat of severe weather, or reschedule other critical operations. The 45 WS uses numerical weather prediction models as a guide for these weather forecasts, particularly the Air Force Weather Agency (AFWA) 1.67 km Weather Research and Forecasting (WRF) model. Considering the 45 WS forecasters' and Launch Weather Officers' (LWO) extensive use of the AFWA model, the 45 WS proposed a task at the September 2013 Applied Meteorology Unit (AMU) Tasking Meeting requesting the AMU verify this model. Due to the lack of archived model data available from AFWA, verification is not yet possible. Instead, the AMU proposed to implement and verify the performance of an ER version of the high-resolution WRF Environmental Modeling System (EMS) model configured by the AMU (Watson 2013) in real time. Implementing a real-time version of the ER WRF-EMS would generate a larger database of model output than in the previous AMU task for determining model performance, and allows the AMU more control over and access to the model output archive. The tasking group agreed to this proposal; therefore the AMU implemented the WRF-EMS model on the second of two NASA AMU modeling clusters. The AMU also calculated verification statistics to determine model performance compared to observational data. Finally, the AMU made the model output available on the AMU Advanced Weather Interactive Processing System II (AWIPS II) servers, which allows the 45 WS and AMU staff to customize the model output display on the AMU and Range Weather Operations (RWO) AWIPS II client computers and conduct real-time subjective analyses.

Meteorology↗
NASA NTRS1994

X-ray clusters from a high-resolution hydrodynamic PPM simulation of the cold dark matter universe

A new three-dimensional hydrodynamic code based on the piecewise parabolic method (PPM) is utilized to compute the distribution of hot gas in the standard Cosmic Background Explorer (COBE)-normalized cold dark matter (CDM) universe. Utilizing periodic boundary conditions, a box with size 85 h(exp-1) Mpc, having cell size 0.31 h(exp-1) Mpc, is followed in a simulation with 270(exp 3)=10(exp 7.3) cells. Adopting standard parameters determined from COBE and light-element nucleosynthesis, Sigma(sub 8)=1.05, Omega(sub b)=0.06, we find the X-ray-emitting clusters, compute the luminosity function at several wavelengths, the temperature distribution, and estimated sizes, as well as the evolution of these quantities with redshift. The results, which are compared with those obtained in the preceding paper (Kang et al. 1994a), may be used in conjuction with ROSAT and other observational data sets. Overall, the results of the two computations are qualitatively very similar with regard to the trends of cluster properties, i.e., how the number density, radius, and temeprature depend on luminosity and redshift. The total luminosity from clusters is approximately a factor of 2 higher using the PPM code (as compared to the 'total variation diminishing' (TVD) code used in the previous paper) with the number of bright clusters higher by a similar factor. The primary conclusions of the prior paper, with regard to the power spectrum of the primeval density perturbations, are strengthened: the standard CDM model, normalized to the COBE microwave detection, predicts too many bright X-ray emitting clusters, by a factor probably in excess of 5. The comparison between observations and theoretical predictions for the evolution of cluster properties, luminosity functions, and size and temperature distributions should provide an important discriminator among competing scenarios for the development of structure in the universe.

Bryan, Greg L.↗
NASA NTRS1995

Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models

This study outlines a method for the estimation of regional patterns of surface moisture availability (M(sub 0)) and fractional vegetation (Fr) in the presence of spatially variable vegetation cover. The method requires relating variations in satellite-derived (NOAA, Advanced Very High Resolution Radiometer (AVHRR)) surface radiant temperature to a vegetation index (computed from satellite visible and near-infrared data) while coupling this association to an inverse modeling scheme. More than merely furnishing surface soil moisture values, the method constitues a new conceptual and practical approach for combining thermal infrared and vegetation index measurements for incorporating the derived values of M(sub 0) into hydrologic and atmospheric prediction models. Application of the technique is demonstrated for a region in and around the city of Newcastle upon Tyne situated in the northeast of England. A regional estimate of M(sub 0) is derived and is probabbly good for fractional vegetation cover up to 80% before errors in the estimated soil water content become unacceptably large. Moreover, a normalization scheme is suggested from which a nomogram, `universal triangle,' is constructed and is seen to fit the observed data well. The universal triangle also simplifies the inclusion of remotely derived M(sub 0) in hydrology and meteorological models and is perhaps a practicable step toward integrating derived data from satellite measurements in weather forecasting.

Gillies, Robert R.↗
DOE OSTI2015

LIGHT BRIDGE IN A DEVELOPING ACTIVE REGION. I. OBSERVATION OF LIGHT BRIDGE AND ITS DYNAMIC ACTIVITY PHENOMENA

Light bridges, the bright structures that divide the umbra of sunspots and pores into smaller pieces, are known to produce a wide variety of activity events in solar active regions (ARs). It is also known that the light bridges appear in the assembling process of nascent sunspots. The ultimate goal of this series of papers is to reveal the nature of light bridges in developing ARs and the occurrence of activity events associated with the light bridge structures from both observational and numerical approaches. In this first paper, exploiting the observational data obtained by Hinode, the Interface Region Imaging Spectrograph, and the Solar Dynamics Observatory, we investigate the detailed structure of the light bridge in NOAA AR 11974 and its dynamic activity phenomena. As a result, we find that the light bridge has a weak, horizontal magnetic field, which is transported from the interior by a large-scale convective upflow and is surrounded by strong, vertical fields of adjacent pores. In the chromosphere above the bridge, a transient brightening occurs repeatedly and intermittently, followed by a recurrent dark surge ejection into higher altitudes. Our analysis indicates that the brightening is the plasma heating due to magnetic reconnection at lower altitudes, while the dark surge is the cool, dense plasma ejected from the reconnection region. From the observational results, we conclude that the dynamic activity observed in a light bridge structure such as chromospheric brightenings and dark surge ejections are driven by magnetoconvective evolution within the light bridge and its interaction with the surrounding magnetic fields.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Nuclear Reactions in the Crusts of Accreting Neutron Stars

X-ray observations of transiently accreting neutron stars during quiescence provide information about the structure of neutron star crusts and the properties of dense matter. Interpretation of the observational data requires an understanding of the nuclear reactions that heat and cool the crust during accretion and define its nonequilibrium composition. We identify here in detail the typical nuclear reaction sequences down to a depth in the inner crust where the mass density is $\rho =2\times {10}^{12}\,{\rm{g}}\,{\mathrm{cm}}^{-3}$ using a full nuclear reaction network for a range of initial compositions. The reaction sequences differ substantially from previous work. We find a robust reduction of crust impurity at the transition to the inner crust regardless of initial composition, though shell effects can delay the formation of a pure crust somewhat to densities beyond $\rho =2\times {10}^{12}\,{\rm{g}}\,{\mathrm{cm}}^{-3}$. This naturally explains the small inner crust impurity inferred from observations of a broad range of systems. The exception are initial compositions with A ≥ 102 nuclei, where the inner crust remains impure with an impurity parameter of Q imp ≈ 20 owing to the N = 82 shell closure. In agreement with previous work, we find that nuclear heating is relatively robust and independent of initial composition, while cooling via nuclear Urca cycles in the outer crust depends strongly on initial composition. As a result, this work forms a basis for future studies of the sensitivity of crust models to nuclear physics and provides profiles of composition for realistic crust models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1984

Interior structure of Saturn

The principal observational data that constrain interior models of Saturn are summarized, and why they are relevant is explained. The behavior of hydrogen, Saturn's major constituent, at pressures on the order of 0.1 to 10 Mbar and temperatures on the order of 10,000 K, is discussed. Possible behavior and distributions of minor constituents are also considered, along with processes for their transport. Saturn's external gravitational and magnetic fields are interpreted in terms of interior structure, and the relationship between atmospheric zonal flows and the deep interior is discussed. The constraint imposed by tidal evolution considerations is evaluated. Calculations for the thermal evolution of Saturn are presented, both with and without consideration of possible gravitational unmixing. Possible scenarios for Saturn's mode of origin and their implications for presently observed atmospheric abundances are discussed.

Hubbard, W. B.↗
DOE OSTI2024

Data assimilation for combustion ignition delay time simulation using schlieren image velocimetry

This study sought to improve the accuracy of simulating spray penetration and combustion ignition delay by means of data assimilation (DA). The simulations were conducted using the Reynolds-averaged Navier–Stokes (RANS) equations and assimilating the schlieren image data. In DA, an ensemble square root filter (EnSRF) was used to build the statistical model, making the simulation results more accurate without any change in the governing equations. Recognizing that the spray-cone injection angle has a large effect on penetration, we created ensemble members with different injection angles. And we applied the two-component velocity distribution calculated via SIV and updated both velocity and temperature by using a DA statistical model derived from RANS ensemble simulations. The ignition delay time is generally known to vary even under the same experimental conditions because it is influenced by many factors. In this study, we attempted the transient DA-assisted RANS simulation to predict the ignition delay time even when the temporal resolution and accuracy of the observation data ware insufficient. Our trials offer an example of how a combination of techniques can be effectively used to assimilate experimental data obtained under restricted conditions.

Combustion simulation↗

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