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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

EUV spectroscopic plasma diagnostics for the solar wind acceleration region

Possibilities are considered for probing physical conditions in the solar corona with strong EUV resonance lines from ions such as N V, O VI, Ne VIII, Mg X, and Si XII. Through measurements of the intensities and profiles of EUV spectral lines with coronagraphic instrumentation employing normal incidence reflecting optics, it is possible to acquire information on electron, proton, and ion temperatures and velocity distributions; electron, H I, and ion densities; mass flow and nonthermal velocities; and chemical abundances. This information will provide critical empirical constraints on physical processes responsible for plasma heating, solar wind acceleration, and transport of mass, momentum, and energy in the solar corona, as well as providing constraints on theoretical models for solar and stellar coronae and mass loss.

Kohl, J. L.↗
NASA NTRS1982

Ammonia and the NOx budget of the troposphere

Liu et al. (1980) suggested that NOx transported from the stratosphere, as opposed to the anthropogenic source of NOx, may be the dominant source that controls the distribution of NOx in the global troposphere. These ideas require a reinvestigation, and, in particular, an assessment of the role of the oxidation of ammonia as a source of NOx. Attention is given to the results of an ammonia measurement program, in which the vertical distribution of ammonia in the troposphere and lower stratosphere could be studied with the aid of the Infrared Heterodyne Radiometer (IHR), a solar-viewing remote sensor. A one-dimensional photochemical model of the troposphere reported by Levine et al. (1980) was employed to study the chemical and physical processes that control the loss of ammonia in the troposphere. The results of the considered investigation suggest that the oxidation of ammonia may indeed be a significant source of NOx in the troposphere.

Levine, J. S.↗
NASA NTRS1988

Studies of blackbody-pumped lasers

Laser action was achieved in a large-scale pulsed system and meaningful experiments were carried out in the axial flow facility to understand the physics of solar-pumped lasers. Studies of the variation of laser mixture composition were done for mixtures of CO2 and N2O additions. Theoretical analysis and modeling of the system were also performed based on a model including radiative pumping, diffusion and wall deactivation, and vibrational energy transfer between two optically active species. Qualitative agreement between predictions in the parameter variation and the experimental results were obtained with CO and N2O mixtures. Several experimental studies were performed to quantify the properties of carbon monoxide as absorber and storage of energy in the blackbody pumped system.

Christiansen, W. H.↗
NASA NTRS2017

Early Estimation of Solar Activity Cycle: Potential Capability and Limits

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and longterm sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Kitiashvili, Irina N.↗
NASA NTRS2017

Using Data Assimilation Methods of Prediction of Solar Activity

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and long-term sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Prediction↗
NASA NTRS2017

Using Data Assimilation Methods for Prediction of Solar Activity

The variability of solar magnetic activity known as the 11-­‐year solar cycles has the longest history of observations. These solar cycles dramatically affect conditions in the heliosphere and the Earth’s space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-­‐term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model complemented by the equation of magnetic helicity conservation and long-­‐term sunspot data series. This approach has allowed us to reproduce the general properties of the solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Solar Activity↗
DOE OSTI2021

Potential vorticity transport in weakly and strongly magnetized plasmas

Tangled magnetic fields, often coexisting with an ordered mean field, have a major impact on turbulence and momentum transport in many plasmas, including those found in the solar tachocline and magnetic confinement devices. We present a novel mean field theory of potential vorticity mixing in β-plane magnetohydrodynamic (MHD) and drift wave turbulence. Our results show that mean square stochastic fields strongly reduce Reynolds stress coherence. This decoherence of potential vorticity flux due to stochastic field scattering leads to suppression of momentum transport and zonal flow formation. A simple calculation suggests that the breaking of the shear-eddy tilting feedback loop by stochastic fields is the key underlying physics mechanism. Furthermore, a dimensionless parameter that quantifies the increment in power threshold is identified and used to assess the impact of stochastic field on the L-H transition. We discuss a model of stochastic fields as a resisto-elastic network.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2022

Constraining Global Coronal Models with Multiple Independent Observables

Global coronal models seek to produce an accurate physical representation of the Sun's atmosphere that can be used, for example, to drive space-weather models. Assessing their accuracy is a complex task, and there are multiple observational pathways to provide constraints and tune model parameters. Here, we combine several such independent constraints, defining a model-agnostic framework for standardized comparison. We require models to predict the distribution of coronal holes at the photosphere, and neutral line topology at the model's outer boundary. We compare these predictions to extreme-ultraviolet (EUV) observations of coronal hole locations, white-light Carrington maps of the streamer belt, and the magnetic sector structure measured in situ by Parker Solar Probe and 1 au spacecraft. We study these metrics for potential field source surface (PFSS) models as a function of source surface height and magnetogram choice, as well as comparing to the more physical Wang–Sheeley–Arge (WSA) and the Magnetohydrodynamic Algorithm outside a Sphere (MAS) models. We find that simultaneous optimization of PFSS models to all three metrics is not currently possible, implying a trade-off between the quality of representation of coronal holes and streamer belt topology. WSA and MAS results show the additional physics that they include address this by flattening the streamer belt while maintaining coronal hole sizes, with MAS also improving coronal hole representation relative to WSA. We conclude that this framework is highly useful for inter- and intra-model comparisons. Integral to the framework is the standardization of observables required of each model, evaluating different model aspects.

S. T. Badman↗
DOE OSTI2020

Interpreting High-resolution Spectroscopy of Exoplanets using Cross-correlations and Supervised Machine Learning

We present a new method for performing atmospheric retrieval on ground-based, high-resolution data of exoplanets. Our method combines cross-correlation functions with a random forest, a supervised machine-learning technique, to overcome challenges associated with high-resolution data. A series of cross-correlation functions are concatenated to give a “CCF-sequence” for each model atmosphere, which reduces the dimensionality by a factor of ∼100. The random forest, trained on our grid of ∼65,000 models, provides a likelihood-free method of retrieval. The precomputed grid spans 31 values of both temperature and metallicity, and incorporates a realistic noise model. We apply our method to HARPS-N observations of the ultra-hot Jupiter KELT-9b and obtain a metallicity consistent with solar (logM = − 0.2 ± 0.2). Our retrieved transit chord temperature (T=6000{sub −200}{sup +0}K) is unreliable as strong ion lines lie outside of the extent of the training set, which we interpret as being indicative of missing physics in our atmospheric model. We compare our method to traditional nested sampling, as well as other machine-learning techniques, such as Bayesian neural networks. We demonstrate that the likelihood-free aspect of the random forest makes it more robust than nested sampling to different error distributions, and that the Bayesian neural network we tested is unable to reproduce complex posteriors. We also address the claim in Cobb et al. 2019 that our random forest retrieval technique can be overconfident but incorrect. We show that this is an artifact of the training set, rather than of the machine-learning method, and that the posteriors agree with those obtained using nested sampling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Analysis of thermal and mechanical properties with inventory level of the molten salt storage tank in central receiver concentrating solar power plants

Molten salt thermal energy storage (TES) tanks ensure steady power output of concentrating solar power (CSP) plants; however, recent tank failures have highlighted the need for further analysis. Current studies primarily focus on analyzing the molten salt flow, heat transfer, and thermal efficiency. Additionally, research on the latest tank structures is limited and lacks newest experimental validation. This study measures temperature and molten salt inventory levels in the high-temperature tank at a 50 MW central receiver CSP plant, connected to the power grid in 2019. A multi-physics model was developed to evaluate thermal and mechanical properties of TES tanks by combining computational fluid dynamics and finite element modeling using real plant data. Heat loss, temperature, displacement, and stress distribution of the tank at different inventory levels were investigated. Results show that ambient air velocity near the tank roof reaches 2.14 m/s, much higher than 0.2 m/s near the wall. The temperatures of inventory fluid and tank are close, varying slightly at different levels due to thermal conduction and radiation. Because the heat loss strongly depends on temperature, the total tank loss remains nearly constant across inventory levels. Larger temperature gradients and thermal stresses are primarily localized along the tank floor edge and the air-salt interface. Notably, the maximum thermal stress at the tank edge is three times higher than that at the interface. The magnitude of total stress changes by less than 5 MPa with and without thermal load, indicating that high temperatures exert only a minor impact on tank stress. In contrast, thermal load significantly affects tank deformation, particularly at the roof edge, where values exceed 150 mm. Despite the large variation in molten salt levels, tank wall temperatures and displacements present a minor change, suggesting a weak correlation with inventory levels. In conclusion, the findings obtained in this study provide important insights on the TES tank that could be used to optimize tank design and operation strategies.

14 SOLAR ENERGY↗
NASA NTRS2021

Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar

Understanding the spatial variability of the snowpack is valuable for hydrologists and ecologists seeking to predict hydrological processes in a cold region. Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as solar radiation, wind speed and direction, and soil moisture. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenging due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) model to identify primary controls over open terrain and forests at the University of New Hampshire Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in the MaxEnt framework to predict locations of deeper or shallower snowpacks, respectively, across a mixed temperate forested and field landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, down-scaling remotely sensed snow products, and understanding field scale snow states.

Eunsang Cho↗
NASA NTRS1980

Ultraviolet spectroscopy of the outer layers of stars

Ultraviolet observations of the extended atmospheres and circumstellar envelopes of early-type and cool stars are reviewed. UV spectra of OB stars have shown that mass loss occurs in virtually all these stars and in many Be stars, and the Copernicus satellite has also provided information on the physical conditions and variability of the winds. The winds have been interpreted in terms of hot coronal wind models, imperfect flow models and radiation pressure models, and estimates of mass loss ranging from 10 to the -10th to 9 x 10 to the -6th solar masses/year have been obtained. Further UV data of faint stars, additional wavelengths and time variability are required. Recent UV and X-ray experiments have detected stellar chromospheres, transition regions coronas and winds in cool stars. Semiempirical line-profile and line-flux models and purely theoretical atmospheric models have been constructed to explain chromosphere, corona and wind data, and future observations of the physical properties of stellar chromospheres, coronas and winds, terms in the energy balance equation, stellar activity and its long-term variability and atmospheric modifications due to the presence of companion stars are proposed for such missions as Spacelab.

Snow, T. P., Jr.↗
NASA NTRS1992

Parameterization of solar cells

The aggregation (sorting) of the individual solar cells into an array is commonly based on a single operating point on the current-voltage (I-V) characteristic curve. An alternative approach for cell performance prediction and cell screening is provided by modeling the cell using an equivalent electrical circuit, in which the parameters involved are related to the physical phenomena in the device. These analytical models may be represented by a double exponential I-V characteristic with seven parameters, by a double exponential model with five parameters, or by a single exponential equation with four or five parameters. In this article we address issues concerning methodologies for the determination of solar cell parameters based on measured data points of the I-V characteristic, and introduce a procedure for screening of solar cells for arrays. We show that common curve fitting techniques, e.g., least squares, may produce many combinations of parameter values while maintaining a good fit between the fitted and measured I-V characteristics of the cell. Therefore, techniques relying on curve fitting criteria alone cannot be directly used for cell parameterization. We propose a consistent procedure which takes into account the entire set of parameter values for a batch of cells. This procedure is based on a definition of a mean cell representing the batch, and takes into account the relative contribution of each parameter to the overall goodness of fit. The procedure is demonstrated on a batch of 50 silicon cells for Space Station Freedom.

Appelbaum, J.↗
NASA NTRS1992

A study of shock-associated magnetohydrodynamic waves in the solar wind

Three major topics were addressed, one theoretical and two observational. The topics were: (1) an attempt to understand the evolution of the large-amplitude magnetohydrodynamic (MHD) waves in the foreshock, using a nonlinear wave equation called the Derivative Nonlinear Schrodinger equation (henceforth DNLS) as a model, (2) using the extensive set of ISE data to test for the presence of various nonlinear wave processes which might be present, and (3) a study of plasma turbulence in the interstellar medium which might be physically similar to that in the solar wind. For these investigations we used radioastronomical techniques. Good progress was made in each of these areas and a separate discussion of each is given.

Spangler, Steven R.↗
NASA NTRS1983

Shape of the magnetosphere

The shape of the magnetosphere has been studied by using a global MHD model of the magnetosphere. It is found that MHD and the Chapman-Ferraro models agree in total magnetopause current distributions, but that the MHD model presents a very different physical picture from that of the Chapman-Ferraro model. In the MHD model with B(IMF) = 0 or northward, the cusp is not exposed directly to the solar wind because the dayside magnetic field lines drape around the nightside magnetosphere. Furthermore, in the MHD model a current sheet exists above the cusp region.

Wu, C. C.↗
NASA NTRS2005

Studies of Particle Acceleration, Transport and Radiation in Impulsive Phase of Solar Flares

Solar activity and its most prominent aspect, the solar flares, have considerable influence on terrestrial and space weather. Solar flares also provide a suitable laboratory for the investigation of many plasma and high energy processes important in the magnetosphere of the Earth and many other space and astrophysical situations. Hence, progress in understanding of flares will have considerable scientific and societal impact. The primary goal of this grant is the understanding of two of the most important problems of solar flare physics, namely the determination of the energy release mechanism and how this energy accelerates particles. This is done through comparison of the observations with theoretical models, starting from observations and gradually proceeding to theoretically more complex situations as the lower foundations of our understanding are secured. It is generally agreed that the source of the flare energy is the annihilation of magnetic fields by the reconnection process. Exactly how this energy is released or how it is dissipated remains controversial. Moreover, the exact mechanism of the acceleration of the particles is still a matter of debate. Data from many spacecrafts and ground based instruments obtained over the past decades have given us some clues. Theoretical analyses of these data have led to the standard thick target model (STT) where most of the released energy goes into an (assumed) power law spectrum of accelerated particles, and where all the observed radiations are the consequence of the interaction of these particles with the flare plasma. However, some theoretical arguments, and more importantly some new observations, have led us to believe that the above picture is not complete. It appears that plasma turbulence plays a more prominent role than suspected previously, and that it is the most likely agent for accelerating particles. The model we have developed is based on production of a high level of plasma waves and turbulence in the reconnection region above a flare loop. This turbulence accelerates particles stochastically which radiate some of their energy in this region but carry most of their energy to the footpoints of the loop, where they lose all their energy and radiate bulk of the observed radiation as in the traditional thick target model. In the past we have worked on various aspects of this model. We have evaluated the interaction rates of the plasma waves with electrons and ions, developed theoretical frameworks for the acceleration, transport and radiative processes, and produced numerical codes for the investigation of these processes. The goal of this grant has been further development and testing of this new paradigm, with emphases on the relative acceleration of electrons and ions and on a comprehensive investigation of the turbulence generation, cascade, and damping processes. We review several pieces of important evidence that we have uncovered indicating the crucial roles of turbulence, in and we describe accomplishments during the past two years of this grant.

Petrosian, Vahe↗
DOE OSTI2024

Probing quarkyonic matter in neutron stars with the Bayesian nuclear-physics multimessenger astrophysics framework

The interiors of neutron stars contain matter at the highest densities realized in our Universe. Interestingly, theoretical studies of dense matter, in combination with the existence of two-solar-mass neutron stars, indicate that the speed of sound $c_s$ has to increase to values well above the conformal limit ($c_s^2$ = 1/3) before decreasing again at higher densities. Further, the decrease could be explained by either a strong first-order phase transition or a crossover transition from hadronic to quark matter. The latter scenario leads to a pronounced peak in the speed of sound, reaching values above the conformal limit, naturally explaining the inferred behavior. In this work, we use the nuclear-physics multimessenger astrophysics (NMMA) framework to compare predictions of the quarkyonic matter model with astrophysical observations of neutron stars, with the goal of constraining model parameters. Assuming quarkyonic matter to be realized within neutron stars, we find that there can be a significant amount of quarks inside the cores of neutron stars with masses in the two-solar-mass range, amounting to up to ≈0.13$M$ ⊙ , contributing ≈ 5.9% of the total mass. Furthermore, for the quarkyonic matter model investigated here, the radius of a 1.4$M$ ⊙ neutron star would be $13.44_{–1.54}^{+1.69}(13. 54_{–1.04}^{+1.02})$ km, at 95% credibility, without (with) the inclusion of AT2017gfo.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2004

Comparison of Local Scale Measured and Modeled Brightness Temperatures and Snow Parameters from the CLPX 2003 by Means of a Dense Medium Radiative Transfer Theory Model

Microwave remote sensing offers distinct advantages for observing the cryosphere. Solar illumination is not required, and spatial and temporal coverage are excellent from polar-orbiting satellites. Passive microwave measurements are sensitive to the two most useful physical quantities for many hydrological applications: physical temperature and water content/state. Sensitivity to the latter is a direct result of the microwave sensitivity to the dielectric properties of natural media, including snow, ice, soil (frozen or thawed), and vegetation. These considerations are factors motivating the development of future cryospheric satellite remote sensing missions, continuing and improving on a 26-year microwave measurement legacy. Perhaps the biggest issues regarding the use of such satellite measurements involve how to relate parameter values at spatial scales as small as a hectare to observations with sensor footprints that may be up to 25 x 25 km. The NASA Cold-land Processes Field Experiment (CLPX) generated a dataset designed to enhance understanding of such scaling issues. CLPX observations were made in February (dry snow) and March (wet snow), 2003 in Colorado, USA, at scales ranging from plot scale to 25 x 25 km satellite footprints. Of interest here are passive microwave observations from ground-based, airborne, and satellite sensors, as well as meteorological and snowpack measurements that will enable studies of the effects of spatial heterogeneity of surface conditions on the observations. Prior to performing such scaling studies, an evaluation of snowpack forward modelling at the plot scale (least heterogeneous scale) is in order. This is the focus of this paper. Many forward models of snow signatures (brightness temperatures) have been developed over the years. It is now recognized that a dense medium radiative transfer (DMRT) treatment represents a high degree of physical fidelity for snow modeling, yet dense medium models are particularly sensitive to snowpack structural parameters such as grain size, density, and depth---parameters that may vary substantially within a snowpack. Microwave radiometric data and snow pit measurements collected at the Local-Scale Observation Site (LSOS) during the third Intensive Observation Period (IOP3) of the CLPX have been used to test the capabilities of a DMRT model using the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). The radiometric measurements were made by the University of Tokyo s Ground Based Microwave Radiometer-7 (GBMR-7) system. We evaluate the degree to which a DMRT-based model can accurately reproduce the GBMR-7 brightness temperatures at different frequencies and incidence angles.

Tedescol, Marco↗