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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 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Data-driven Thermal Model Inference with ARMAX, in Smart Environments, based on Normalized Mutual Information

Understanding the models that characterize the thermal dynamics in a smart building is important for the comfort of its occupants and for its energy optimization. Here, a significant amount of research has attempted to utilize thermodynamics (physical) models for smart building control, but these approaches remain challenging due to the stochastic nature of the intermittent environmental disturbances. This paper presents a novel data-driven approach for indoor thermal model inference, which combines an Autoregressive Moving Average with eXogenous inputs model (ARMAX) with a Normalized Mutual Information scheme (NMI). Based on this information-theoretic method, NMI, causal dependencies between the indoor temperature and exogenous inputs are explicitly obtained as a guideline for the ARMAX model to find the dominating inputs. For validation, we use three datasets based on building energy systems-against which we compare our method to an autoregressive model with exogenous inputs (ARX), a regularized ARMAX model, and state-space models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Performance Study of Distance-Weighting Approach with Loopy Sum-Product Algorithm for Multi-Object Tracking in Clutter

In this paper, we explore the performance of the distance-weighting probabilistic data association (DWPDA) approach in conjunction with the loopy sum-product algorithm (LSPA) for tracking multiple objects in clutter. First, we discuss the problem of data association (DA), which is to infer the correspondence between targets and measurements. DA plays an important role when tracking multiple targets using measurements of uncertain origin. Second, we describe three methods of data association: probabilistic data association (PDA), joint probabilistic data association (JPDA), and LSPA. We then apply these three DA methods for tracking multiple crossing targets in cluttered environments, e.g., radar detection with false alarms and missed detections. We are interested in two performance metrics: tracking accuracy and computation time. LSPA is known to be superior to PDA in terms of the former and to dominate JPDA in terms of the latter. Last, we consider an additional DA method that is a modification of PDA by incorporating a weighting scheme based on distances between position estimates and measurements. This distance-weighting approach, when combined with PDA, has been shown to enhance the tracking accuracy of PDA without significant change in the computation burden. Since PDA constitutes a crucial building block of LSPA, we hypothesize that DWPDA, when integrated with LSPA, would perform better under the two performance metrics above. Contrary to expectations, the distance-weighting approach does not enhance the performance of LSPA, whether in terms of tracking accuracy or computation time.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Uniform Atmospheric Retrieval Analysis of Ultracool Dwarfs. II. Properties of 11 T dwarfs

Brown dwarf spectra are rich in information revealing of the chemical and physical processes operating in their atmospheres. We apply a recently developed atmospheric retrieval tool to an ensemble of late-T dwarf (600–800 K) near-infrared (1–2.5 μ m) spectra. With these spectra we are able to directly constrain the molecular abundances for the first time of H{sub 2}O, CH{sub 4}, CO, CO{sub 2}, NH{sub 3}, H{sub 2}S, and Na+K, surface gravity, effective temperature, thermal structure, photometric radius, and cloud optical depths. We find that ammonia, water, methane, and the alkali metals are present and that their abundances are well constrained in all 11 objects. We find no significant trend in the water, methane, or ammonia abundances with temperature, but find a very strong (>25 σ ) decreasing trend in the alkali metal abundances with decreasing effective temperature, indicative of alkali rainout. As expected from previous work, we also find little evidence for optically thick clouds. With the methane and water abundances, we derive the intrinsic atmospheric metallicity and carbon-to-oxygen ratios. We find in our sample that metallicities are typically subsolar (−0.4 < [ M /H] < 0.1 dex) and carbon-to-oxygen ratios are somewhat supersolar (0.4 < C/O < 1.2), different than expectations from the local stellar population. We also find that the retrieved vertical thermal profiles are consistent with radiative equilibrium over the photospheric regions. Finally, we find that our retrieved effective temperatures are lower than previous inferences for some objects and that some of our radii are larger than expectations from evolutionary models, possibly indicative of unresolved binaries. This investigation and method represent a new and powerful paradigm for using spectra to determine the fundamental chemical and physical processes governing cool brown dwarf atmospheres.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Catalytic considerations in temperature measurement.

Literature discussing catalytic activity in platinum group temperature sensors is surveyed. Methods for the determination and/or elimination of catalytic activity are reported. A particular application of the literature is discussed in which it is possible to infer that a shielded platinum total temperature probe does not experience significant catalytic activity in the wake of a supersonic hydrogen burner, while a bare iridium plus rhodium, iridium thermocouple does. It is concluded that catalytic data corrections are restricted and that it is preferable to coat the temperature sensor with a noncatalytic coating. Furthermore, the desirability of transparent coatings is discussed.

Ash, R. L.↗
NASA NTRS1976

Environmental dynamics at orbital altitudes

The work reported involved the improvement of aerodynamic theory for free molecular and transition flow regimes. The improved theory was applied to interpretation of the dynamic response of objects traveling through the atmosphere. Satellite drag analysis includes analysis methods, atmospheric super rotation effects, and satellite lift effects on orbital dynamics. Transition flow regimes were studied with falling sphere data and errors resulting in inferred atmospheric parameters from falling sphere techniques. Improved drag coefficients reveal considerable error in previous falling sphere data. The drag coefficient has been studied for the entire spectrum of Knudsen Number and speed ratio, with particular emphasis on the theory of the very low-speed ratio regime.

Karr, G. R.↗
NASA NTRS1985

A new method for determining temperature and emission measure during solar flares from light curves of soft X-ray line fluxes

A method for using the shapes of the light curves of soft X-ray line fluxes observed during the decay phase of solar flares to infer the temperature and emission measure with time is described. Light curves of the November 5, 1980 flare and several additional flares that exhibit breaks are presented, and possible causes for these breaks are discussed. Numerical models that incorporate the effects of temperature changes on the emissivity function are examined, and the model calculations are compared with the line fluxes observed during the November 5, 1980 flare. The model results are used to derive other properties of the flare.

Bornmann, P. L.↗
NASA NTRS1993

A statistical analysis of mesoscale rainfall as a random cascade

The paper considers the random cascade theory for spatial rainfall. Particular attention was given to the following four areas: (1) the relationship of the random cascade theory of rainfall to the simple scaling and the hierarchical cluster-point-process theories, (2) the mathematical foundations for some of the formalisms commonly applied in the develpment of statistical cascade theory, (3) the empirical evidence for a random cascade theory of rainfall, and (4) the way of using data for making estimates of parameters and for making statistical inference within this theoretical framework. An analysis of space-time rainfall data is presented. Cascade simulations are carried out to provide a comparison with methods of analysis that are applied to the rainfall data.

Gupta, Vijay K.↗
NASA NTRS1998

Contributions of Nimbus 7 TOMS Data to Volcanic Study and Hazard Mitigation

Nimbus TOMS data have led to advancements among many volcano-related scientific disciplines, from the initial ability to quantify SO2 clouds leading to derivations of eruptive S budgets and fluxes, to tracking of individual clouds, assessing global volcanism and atmospheric impacts. Some of the major aspects of TOMS-related research, listed below, will be reviewed and updated: (1) Measurement of volcanic SO2 clouds: Nimbus TOMS observed over 100 individual SO2 clouds during its mission lifetime; large explosive eruptions are now routinely and reliably measured by satellite. (2) Eruption processes: quantification of SO2 emissions have allowed assessments of eruption sulfur budgets, the evaluation of "excess" sulfur, and inferences of H2S emissions. (3) Detection of ash: TOMS data are now used to detect volcanic particulates in the atmosphere, providing complementary analyses to infrared methods of detection. Paired TOMS and AVHRR studies have provided invaluable information on volcanic cloud compositions and processes. (4) Cloud tracking and hazard mitigation: volcanic clouds can be considered gigantic tracers in the atmosphere, and studies of the fates of these clouds have led to new knowledge of their physical and chemical dispersion in the atmosphere for predictive models. (5) Global trends: the long term data set has provided researchers an unparalleled record of explosive volcanism, and forms a key component in assessing annual to decadal trends in global S emissions. (6) Atmospheric impacts: TOMS data have been linked to independent records of atmospheric change, in order to compare cause and effect processes following a massive injection of SO2 into the atmosphere. (7) Future TOMS instruments and applications: Nimbus TOMS has given way to new satellite platforms, with several wavelength and resolution modifications. New efforts to launch a geostationary TOMS could provide unprecedented observations of volcanic activity.

Krueger, Arlin J.↗
NASA NTRS2013

Herschel's "Cold Debris Disks": Background Galaxies or Quiescent Rims of Planetary Systems?

Infrared excesses associated with debris disk host stars detected so far peak at wavelengths around approx, 100 micron or shorter. However, 6 out of 31 excess sources studied in the Herschel Open Time Key Programme, DUNES, have been seen to show significant-and in some cases extended-excess emission at 160 micron, which is larger than the 100 micron excess. This excess emission has been attributed to circumstellar dust and has been suggested to stem from debris disks colder than those known previously. Since the excess emission of the cold disk candidates is extremely weak, challenging even the unrivaled sensitivity of Herschel, it is prudent to carefully consider whether some or even all of them may represent unrelated galactic or extragalactic emission, or even instrumental noise. We re-address these issues using several distinct methods and conclude that it is highly unlikely that none of the candidates represents a true circumstellar disk. For true disks, both the dust temperatures inferred from the spectral energy distributions and the disk radii estimated from the images suggest that the dust is nearly as cold as a blackbody. This requires the grains to be larger than approx. 100 micron, even if they are rich in ices or are composed of any other material with a low absorption in the visible. The dearth of small grains is puzzling, since collisional models of debris disks predict that grains of all sizes down to several times the radiation pressure blowout limit should be present. We explore several conceivable scenarios: transport-dominated disks, disks of low dynamical excitation, and disks of unstirred primordial macroscopic grains. Our qualitative analysis and collisional simulations rule out the first two of these scenarios, but show the feasibility of the third one. We show that such disks can indeed survive for gigayears, largely preserving the primordial size distribution. They should be composed of macroscopic solids larger than millimeters, but smaller than a few kilometers in size. If larger planetesimals were present, then they would stir the disk, triggering a collisional cascade and thus causing production of small debris, which is not seen. Thus, planetesimal formation, at least in the outer regions of the systems, has stopped before "cometary" or "asteroidal" sizes were reached.

Herschel↗
NASA NTRS2013

Bayesian Revision of Residual Detection Power

This paper addresses some issues with quality assessment and quality assurance in response surface modeling experiments executed in wind tunnels. The role of data volume on quality assurance for response surface models is reviewed. Specific wind tunnel response surface modeling experiments are considered for which apparent discrepancies exist between fit quality expectations based on implemented quality assurance tactics, and the actual fit quality achieved in those experiments. These discrepancies are resolved by using Bayesian inference to account for certain imperfections in the assessment methodology. Estimates of the fraction of out-of-tolerance model predictions based on traditional frequentist methods are revised to account for uncertainty in the residual assessment process. The number of sites in the design space for which residuals are out of tolerance is seen to exceed the number of sites where the model actually fails to fit the data. A method is presented to estimate how much of the design space in inadequately modeled by low-order polynomial approximations to the true but unknown underlying response function.

DeLoach, Richard↗
NASA NTRS2020

Multimessenger Gravitational-wave Searches with Pulsar Timing Arrays: Application to 3C 66B Using the NANOGrav 11-year Data Set

When galaxies merge, the supermassive black holes in their centers may form binaries and emit low-frequency gravitational radiation in the process. In this paper, we consider the galaxy 3C 66B, which was used as the target of the first multimessenger search for gravitational waves. Due to the observed periodicities present in the photometric and astrometric data of the source, it has been theorized to contain a supermassive black hole binary. Its apparent 1.05-year orbital period would place the gravitational-wave emission directly in the pulsar timing band. Since the first pulsar timing array study of 3C 66B, revised models of the source have been published, and timing array sensitivities and techniques have improved dramatically. With these advances, we further constrain the chirp mass of the potential supermassive black hole binary in 3C 66B to less than (1.65±0.02)×109Me using data from the NANOGrav 11-year data set. This upper limit provides a factor of 1.6 improvement over previous limits and a factor of 4.3 over the first search done. Nevertheless, the most recent orbital model for the source is still consistent with our limit from pulsar timing array data. In addition, we are able to quantify the improvement made by the inclusion of source properties gleaned from electromagnetic data over “blind” pulsar timing array searches. With these methods, it is apparent that it is not necessary to obtain exact a priori knowledge of the period of a binary to gain meaningful astrophysical inferences.

Zaven Arzoumanian↗
NASA NTRSDate not supplied

TIME-SERIES SOIL MOISTURE RETRIEVAL USING S-BAND BACKSCATTER MEASUREMENTS FROM THE SMEX02 CAMPAIGN

S-band observations from NASA’s Passive/Active L/S Band (PALS) radar from theSMEX02 campaign were used to estimate soil moisture. The “alpha”method is applied for this process, in which a time series of ratios of normalized radar cross section values at successive measurements is used to infer the corresponding soil moisture time series given ancillary information on the minimum and maximum soil moisture values expected over the time series. Results are examined as a function of the polarization and crop type. The results show reasonable retrieval performance, indicating the potential of usingS-band observations from the future NASA/ISRO SAR(NISAR)mission.

Dustin Horton↗
DOE OSTI2021

On the Stochastic Stability of Deep Markov Models

Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we present a novel stability analysis method and provide sufficient conditions of DMM's stochastic stability. The proposed stability analysis is based on the contraction of probabilistic maps modeled by deep neural networks. We make connections between the spectral properties of neural network's weights and different types of used activation function on the stability and overall dynamic behavior of DMMs with Gaussian distributions. Based on the theory, we propose a few practical methods for designing constrained DMMs with guaranteed stability. We empirically substantiate our theoretical results via intuitive numerical experiments using the proposed stability constraints.

Drgona, Jan↗
DOE OSTI2018

Inferring Strength of Tantalum from Hydrodynamic Instability Recovery Experiments

Hydrodynamic instability experiments allow access to material properties at extreme conditions, where strain rates exceed 105 s -1 and pressures reach 100 GPa. Current hydrodynamic instability experimental methods require in-flight radiography to image the instability growth at high pressure and high strain rate, limiting the facilities where these experiments can be performed. An alternate approach, recovering the sample after loading, allows measurement of the instability growth with profilometry. Tantalum samples were manufactured with different 2D and 3D initial perturbation patterns and dynamically compressed by a blast wave generated by laser ablation. The samples were recovered from peak pressures between 30 and 120 GPa and strain rates on the order of 107 s -1 , providing a record of the growth of the perturbations due to hydrodynamic instability. These records are useful validation points for hydrocode simulations using models of material strength at high strain rate. Recovered tantalum samples were analyzed, providing an estimate of the strength of the material at high pressure and strain rate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1984

Effects of mass motions on solar emission measures inferred from transition-region emission lines

Extreme ultraviolet emission line intensities predicted by a numerical model which includes nonequilibrium ionization balance are used as input 'observational' intensities to calculate volume emission measures following a standard method which assumes ionization equilibrium. These 'observational' emission measures are then compared with the actual emission measure distribution in the atmospheric model. For static equilibrium models, the two sets of emission measures are in good agreement. When mass motions are present, the emission measures calculated from the line intensities differ significantly from the actual values.

Mariska, J. T.↗
DOE OSTI2014

Bayesian Proteoform Modeling Improves Protein Quantification of Global Proteomic Measurements

As the capability of mass spectrometry-based proteomics has matured, tens of thousands of peptides can be measured simultaneously, which has the benefit of offering a systems view of protein expression. However, a major challenge is that with an increase in throughput, protein quantification estimation from the native measured peptides has become a computational task. A limitation to existing computationally-driven protein quantification methods is that most ignore protein variation, such as alternate splicing of the RNA transcript and post-translational modifications or other possible proteoforms, which will affect a significant fraction of the proteome. The consequence of this assumption is that statistical inference at the protein level, and consequently downstream analyses, such as network and pathway modeling, have only limited power for biomarker discovery. Here, we describe a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. We verify the approach using a dilution study from mouse plasma samples and demonstrate that BP-Quant achieves similar accuracy as the current state-of-the-art methods at proteoform identification with significantly better specificity. BP-Quant is available as a MatLab ® and R packages at https://github.com/PNNL-Comp-Mass-Spec/BP-Quant.

Protein Quantitation, proteomics↗
DOE OSTI2021

Solar position confounds the relationship between ecosystem function and vegetation indices derived from solar and photosynthetically active radiation fluxes

Vegetation indices derived from solar and photosynthetically active radiation (PAR) sensors (i.e. radiation derived) have been under-utilized in inferring ecosystem function, despite measurement capability at hundreds of sites. This under-utilization may be attributed to reported mismatches among the seasonality of radiation- and satellite-derived vegetation indices and canopy photosynthesis; herein referred to as measurement biases. In this work, biases in radiation derived reflectance and vegetation indices were assessed using a decadal record of satellite and ground based spectroradiometer data, ecosystem phenology and CO 2 fluxes, and radiation derived vegetation indices (i.e. the Normalized Difference Vegetation Index [NDVI], the two band Enhanced Vegetation Index [EVI2]) from a high latitude tundra site (i.e. Imnaviat). At Imnaviat, we found poor correspondence between the three types of reflectance and vegetation indices, especially during the latter part of the growing season. Radiation derived vegetation indices resulted in incorrect estimates of phenological timing of up to a month and poor relationships with canopy photosynthesis (i.e. Gross Ecosystem Exchange (GEE)). These mismatches were attributed to solar position (i.e. solar zenith and azimuth angle) and a method, based on the diel visible and near-infrared albedo variation, was developed to improve the performance of the vegetation indices. The ability of radiation derived vegetation indices to infer GEE and phenological dates drastically improved once radiation derived vegetation indices were corrected for solar position associated biases at Imnaviat. Moreover, radiation derived vegetation indices became better aligned with MODerate resolution Imaging Spectroradiometer (MODIS) satellite estimates after solar position associated biases were corrected at Imnaviat and at 25 Fluxnet sites (~90 site years) across North America. Corrections developed here provide a way forward in understanding daily ecosystem function or filling large gaps in eddy covariance data at a significant number of Fluxnet sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evaluation of Methods for Causal Discovery in Hydrometeorological Systems

Understanding causal relations is of utmost importance in hydrology and climate research for systems identification, prediction, and understanding systems behavior in a changing climate. Traditionally, researchers in hydrometeorology attempted to study causal questions by conducting controlled experiments using numerical models. This approach, however, in most cases of interest provides uncertain results because the models are approximate representation of the natural system. An alternative approach that has recently drawn significant attention in several fields is to infer causal relations from purely observational data. It possesses several traits to its utility particularly in hydrometeorology due to the rapid accumulation of in situ and remotely sensed data records. The first objective of this study is to present a brief description of four causal discovery methods (Granger causality, Transfer Entropy, graph-based algorithms, and Convergent Cross Mapping) with special emphasis on the assumptions on which they are built. Second, using synthetic data generated from a hydrological model, we assess their performance in retrieving causal information taking into account sensitivity to sample size and presence of noise. Last, we use causal analysis to examine and formulate hypotheses on causal drivers of evapotranspiration in a shrubland region during summer and winter seasons. An interpretation of the hypotheses based on canopy seasonal dynamics and evapotranspiration processes is presented. It is hoped that the results presented here can be useful in guiding researchers studying hydrometeorological systems as to which causal method is most appropriate to the characteristics of the system under study.

54 ENVIRONMENTAL SCIENCES↗