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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tracking the ancestry of known and ‘ghost’ homeologous subgenomes in model grass Brachypodium polyploids

Unraveling the evolution of plant polyploids is a challenge when their diploid progenitor species are extinct or unknown or when genome sequences of known progenitors are unavailable. Existing subgenome identification methods cannot adequately infer the homeologous genomes that are present in the allopolyploids if they do not take into account the potential existence of unknown progenitors. We addressed this challenge in the widely distributed dysploid grass genus Brachypodium, which is a model genus for temperate cereals and biofuel grasses. We used a transcriptome-based phylogeny and newly designed subgenome detection algorithms coupled with a comparative chromosome barcoding analysis. Our phylogenomic subgenome detection pipeline was validated in Triticum allopolyploids, which have known progenitor genomes, and then used to infer the identities of three subgenomes derived from extant diploid species and four subgenomes derived from unknown diploid progenitors (ghost subgenomes) in six Brachypodium polyploids (B. mexicanum, B. boissieri, B. retusum, B. phoenicoides, B. rupestre and B. hybridum), of which five contain undescribed homeologous subgenomes. The existence of the seven Brachypodium progenitor genomes in the polyploids was confirmed by their karyotypic barcode profiles. Comparative phylogenomics of nuclear versus plastid trees allowed us to formulate hypothetical homoploid hybridizations and allo- and autopolyploidization scenarios that could have generated the six Brachypodium polyploids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

XRD-PUAT (X-Ray Diffraction - Parameter Uncertainty Analysis Toolkit)

This XRD uncertainty toolkit was built to investigate uncertainty and local least squares topology over a specified parameter space on a single histogram in a gpx GSAS-II file. The parameter uncertainty can be investigated using either a frequentist F-test approach or a Bayesian Inference statistical inversion method on a weighted least squares or peak fit refinements.SAND Number: SAND2020-12227 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Moore, Alexander↗
DOE OSTI2024

Forward variable selection enables fast and accurate dynamic system identification with Karhunen-Loève decomposed Gaussian processes

A promising approach for scalable Gaussian processes (GPs) is the Karhunen-Loève (KL) decomposition, in which the GP kernel is represented by a set of basis functions which are the eigenfunctions of the kernel operator. Such decomposed kernels have the potential to be very fast, and do not depend on the selection of a reduced set of inducing points. However KL decompositions lead to high dimensionality, and variable selection thus becomes paramount. This paper reports a new method of forward variable selection, enabled by the ordered nature of the basis functions in the KL expansion of the Bayesian Smoothing Spline ANOVA kernel (BSS-ANOVA), coupled with fast Gibbs sampling in a fully Bayesian approach. It quickly and effectively limits the number of terms, yielding a method with competitive accuracies, training and inference times for tabular datasets of low feature set dimensionality. Theoretical computational complexities are O ( N P 2 ) in training and O ( P ) per point in inference, where N is the number of instances and P the number of expansion terms. The inference speed and accuracy makes the method especially useful for dynamic systems identification, by modeling the dynamics in the tangent space as a static problem, then integrating the learned dynamics using a high-order scheme. The methods are demonstrated on two dynamic datasets: a ‘Susceptible, Infected, Recovered’ (SIR) toy problem, along with the experimental ‘Cascaded Tanks’ benchmark dataset. Comparisons on the static prediction of time derivatives are made with a random forest (RF), a residual neural network (ResNet), and the Orthogonal Additive Kernel (OAK) inducing points scalable GP, while for the timeseries prediction comparisons are made with LSTM and GRU recurrent neural networks (RNNs) along with the SINDy package.

Hayes, Kyle↗
DOE OSTI2018

Bayesian characterization and forward propagation of the uncertainty in thermodynamic models for redox active materials

Demonstrating the thermodynamic efficiency of hydrogen conversion processes using various materials is a critical step in developing new technologies for storing concentrated solar energy, and is largely accomplished by using a thermodynamic model derived from experimental data. A main goal of this project is to calculate the uncertainty of the thermodynamic efficiency by calculating the uncertainty of the components that feed into the efficiency. Many different models and data sets were used to test the workflow. First, the models were fit to the data using a Bayesian Inference and a method called Markov Chain Monte Carlo (MCMC), which found the maximum a priori parameters, and a posterior probability distribution of the parameters. Next, the different models were compared to each other using model evidence values. It was found that for cleaner data sets, overfitting had not yet been reached, and the most complicated model was ideal, but on the noisier data sets, the less complex models were favored because the more complicated models resulted in overfitting. Next, forward propagation was used to calculate the enthalpy change and its associated uncertainty. A few variations on the models were tried, such as fitting in a different variable, producing negligible or negative effects on the fits of the models. Thus, the original models were used. A sensitivity analysis was performed, and used to calculate the model error. On the cleaner data sets, there was very minimal experimental noise, and thus, all resulting error was from the model. With consideration of the model error, the models fit the data very well, and the simpler model had a high model error, as expected. All these components will then be used to calculate the thermodynamic efficiency of the different materials.

14 SOLAR ENERGY↗
DOE OSTI2024

Hydra: Computer Vision for Data Quality Monitoring

Hydra: Computer Vision for Data Quality Monitoring Mar 13, 2024, 4:15 PM 30m Charles B. Wang Center, Stony Brook University Poster Track 1: Computing Technology for Physics Research Poster session with coffee break Speaker Ayan Roy Description Hydra is an extensible framework for training, managing, and deploying machine learning models for near real-time data quality monitoring. It is designed to take some of the burden off of shift crews by providing ‘round-the-clock’ monitoring of plots representing the data being collected. The Hydra system is backed by a database which is leveraged for near push button training and is primarily controlled and viewed through a set of web interfaces. This web interface contains a simple-to-use web based GUI for labeling of the datasets used in training; making it possible to label thousands of images quickly and efficiently. To aid in the analysis of Hydra inferences gradCAM, a method of interpretability, is performed and overlaid on the target image, highlighting regions of interest, making diagnosis of problems much faster. Development began in 2019 for the GlueX Experiment in Hall-D, the Hydra system has grown to encompass all of the experimental halls at Jefferson Laboratory. This talk will focus on the features of Hydra as well as provide details of the challenges present with deploying to disparate experimental halls. With a roadmap of development established, Hydra aims to continue to grow in richness of feature set and expand to encompass other monitoring tasks in differing communities.

Roy, Ayan↗
NASA NTRS1978

The augmentation algorithm and molecular phylogenetic trees

Moore's (1977) augmentation procedure is discussed, and it is concluded that the procedure is valid for obtaining estimates of the total number of fixed nucleotide substitutions both theoretically and in practice, for both simulated and real data, and in agreement, for experimentally dense data sets, with stochastic estimates of the divergence, provided the restrictions on codon mutability resulting from natural selection are explicitly allowed for. Tateno and Nei's (1978) critique that the augmentation procedure has a systematic bias toward overestimation of the total number of nucleotide replacements is disputed, and a data analysis suggests that ancestral sequences inferred by the method of parsimony contain a large number of incorrectly assigned nucleotides.

Holmquist, R.↗
NASA NTRS1991

Plan recognition and generalization in command languages with application to telerobotics

A method for pragmatic inference as a necessary accompaniment to command languages is proposed. The approach taken focuses on the modeling and recognition of the human operator's intent, which relates sequences of domain actions ('plans') to changes in some model of the task environment. The salient feature of this module is that it captures some of the physical and linguistic contextual aspects of an instruction. This provides a basis for generalization and reinterpretation of the instruction in different task environments. The theoretical development is founded on previous work in computational linguistics and some recent models in the theory of action and intention. To illustrate these ideas, an experimental command language to a telerobot is implemented. The program consists of three different components: a robot graphic simulation, the command language itself, and the domain-independent pragmatic inference module. Examples of task instruction processes are provided to demonstrate the benefits of this approach.

Yared, Wael I.↗
NASA NTRS1992

Shot noise limits to sensitivity of optical interferometry

By arguing that the limiting noise is the photoelectron shot noise, we show that the sensitivity of image synthesis by an ideal optical interferometer is independent of the details of beam-splitting and recombination. The signal-to-noise ratio of the synthesized image is proportional to the square root of the total number of photoelectrons detected by the entire array. For non-ideal interferometers, which are forced to employ a closure-phase method of indirect inference of the visibility data, essentially the same result holds for strong sources, but at weak light levels beam-splitting degrades sensitivity.

Prasad, Sudhakar↗
NASA NTRS1994

Kinematics of the ion tail of comet P/Swift-Tuttle

We have obtained long-slit high resolution spectra of the H2O(+) 6199 A complex in the near tail of comet P/Swift-Tuttle. The observations were made using the Hamilton echelle spectrometer fed by the Lick Observatory 0.6 m coude auxiliary telescope. For most of our observations, the spectral slit was aligned along the Sun-tail axis and the cometary nucleus was placed at one end of the slit, giving us spectra having the spatial and spectral resolution needed to measure the radial velocity and velocity dispersion continuously down the cometary tail out to a distance of 4X10(exp 5) km. The radial velocities confirm the earlier more restricted observations by Rauer & Jockers (1993) and by Wyckoff & Lindholm (1994) showing that the tail motions are indeed bulk flows in the antisolar direction. Out to 3X10(exp 5) km in the tail typical bulk flows are at a speed of approximately 30 km/s. The velocity dispersion, (sigma(sub r)), of the H2O(+) lines follows a pattern that is quite systematic; sigma(sub r) is smallest near the cometary nucleus, and steadily increases down the tail. The highest velocity dispersions are found ahead of the nucleus and off the tail axis. These velocity dispersions are equivalent to ion temperatures ranging from 10(exp 5) to 10(exp 6) K. We note a clear anticorrelation between the H2O(+) line intensities (related to the ion density) and the bulk flow and dispersion velocities; direct mass loading of the solar wind by the observed water ions may be responsible. We discuss several approximate equipartition methods used to infer local magnetic fields induced by the interaction of the cometary ions with the solar wind particle/field stream. Typical fields derived are near 50 nT. The measured tailward accelerations are consistent with this order of magnitude B field.

Spinrad, Hyron↗
NASA NTRS1991

The sequence of Methanospirillum hungatei 23S rRNA confirms the specific relationship between the extreme halophiles and the Methanomicrobiales

We have determined the sequence of the 23S rRNA from the methanogenic archaeon Methanospirillum hungatei. This is the first such sequence from a member of the Methanomicrobiales. Moreover, it brings additional evidence to bear on the possible specific relationship between this particular group of methanogens and the extreme halophiles. Such evidence is critical in that several new (and relatively untested) methods of phylogenetic inference have lead to the controversial conclusion that the extreme halophiles are either not related to the archaea, or are only peripherally so. Analysis of the Methanospirillum hungatei 23S rRNA sequence shows the Methanomicrobiales are indeed a sister group of the extreme halophiles, further strengthening the conclusions reached from analysis of 16S rRNA sequences.

Non-NASA Center↗
NASA NTRS2007

Differences in the Optical Characteristics of Continental US Ground and Cloud Flashes as Observed from Space

Continental US lightning flashes observed by the Optical Transient Detector (OTD) are categorized according to flash type (ground or cloud flash) using US National Lightning Detection Network (TM) (NLDN) data. The statistics of the ground and cloud flash optical parameters (e.g., radiance, area, duration, number of optical groups, and number of optical events) are inter-compared. On average, the ground flash cloud-top emissions are more radiant, illuminate a larger area, are longer lasting, and have more optical groups and optical events than those cloud-top emissions associated with cloud flashes. Given these differences, it is suggested that the methods of Bayesian Inference could be used to help discriminate between ground and cloud flashes. The ability to discriminate flash type on-orbit is highly desired since such information would help researchers and operational decision makers better assess the intensification, evolutionary state, and severe weather potential of thunderstorms. This work supports risk reduction activities presently underway for the future launch of the GOES-R Geostationary Lightning Mapper (GLM).

Koshak, William↗
NASA NTRS2013

Interior of the Moon

A variety of geophysical measurements made from Earth, from spacecraft in orbit around the Moon, and by astronauts on the lunar surface allow us to probe beyond the lunar surface to learn about its interior. Similarly to the Earth, the Moon is thought to consist of a distinct crust, mantle, and core. The crust is globally asymmetric in thickness, the mantle is largely homogeneous, and the core is probably layered, with evidence for molten material. This chapter will review a range of methods used to infer the Moon's internal structure, and briefly discuss the implications for the Moon's formation and evolution.

Weber, Renee C.↗
NASA NTRS2012

Photosystem Trap Energies and Spectrally-Dependent Energy-Storage Efficiencies in the Chl d-Utilizing Cyanobacterium, Acaryochloris Marina

Acaryochloris marina is the only species known to utilize chlorophyll (Chl) d as a principal photopigment. The peak absorption wavelength of Chl d is redshifted approx. 40 nm in vivo relative to Chl a, enabling this cyanobacterium to perform oxygenic phototrophy in niche environments enhanced in far-red light. We present measurements of the in vivo energy-storage (E-S) efficiency of photosynthesis in A. marina, obtained using pulsed photoacoustics (PA) over a 90-nm range of excitation wavelengths in the red and far-red. Together with modeling results, these measurements provide the first direct observation of the trap energies of PSI and PSII, and also the photosystem-specific contributions to the total E-S efficiency. We find the maximum observed efficiency in A. marina (40+/-1% at 735 nm) is higher than in the Chl a cyanobacterium Synechococcus leopoliensis (35+/-1% at 690 nm). The efficiency at peak absorption wavelength is also higher in A. marina (36+/-1% at 710 nm vs. 31+/-1% at 670 nm). In both species, the trap efficiencies are approx. 40% (PSI) and approx. 30% (PSII). The PSI trap in A. marina is found to lie at 740+/-5 nm, in agreement with the value inferred from spectroscopic methods. The best fit of the model to the PA data identifies the PSII trap at 723+/-3 nm, supporting the view that the primary electron-donor is Chl d, probably at the accessory (ChlD1) site. A decrease in efficiency beyond the trap wavelength, consistent with uphill energy transfer, is clearly observed and fit by the model. These results demonstrate that the E-S efficiency in A. marina is not thermodynamically limited, suggesting that oxygenic photosynthesis is viable in even redder light environments.

Mielke, Steven P.↗
NASA NTRS2015

Towards the 1 mm/y Stability of the Radial Orbit Error at Regional Scales

An estimated orbit error budget for the Jason-1 and Jason-2 GDR-D solutions is constructed, using several measures of orbit error. The focus is on the long-term stability of the orbit time series for mean sea level applications on a regional scale. We discuss various issues related to the assessment of radial orbit error trends; in particular this study reviews orbit errors dependent on the tracking technique, with an aim to monitoring the long-term stability of all available tracking systems operating on Jason-1 and Jason-2 (GPS, DORIS, SLR). The reference frame accuracy and its effect on Jason orbit is assessed. We also examine the impact of analysis method on the inference of Geographically Correlated Errors as well as the significance of estimated radial orbit error trends versus the time span of the analysis. Thus a long-term error budget of the 10-year Jason-1 and Envisat GDR-D orbit time series is provided for two time scales: interannual and decadal. As the temporal variations of the geopotential remain one of the primary limitations in the Precision Orbit Determination modeling, the overall accuracy of the Jason-1 and Jason-2 GDR-D solutions is evaluated through comparison with external orbits based on different time-variable gravity models. This contribution is limited to an East-West "order-1" pattern at the 2 mm/y level (secular) and 4 mm level (seasonal), over the Jason-2 lifetime. The possibility of achieving sub-mm/y radial orbit stability over interannual and decadal periods at regional scales and the challenge of evaluating such an improvement using in situ independent data is discussed.

Precision Orbit Determination (POD)↗
NASA NTRSDate not supplied

Characterization of NU-LHT-4M Lunar Regolith Simulant Using Different Raman Configurations

As much as possible, structures to help sustain a long-term human presence on the moon will be constructed via in-situ resource utilization (ISRU) from lunar regolith. Various processes have been proposed to make lunar regolith-based construction materials, but one complication is that the lunar regolith is relatively complex in terms of composition and can vary quite significantly from one site to another. Some of these methods to make lunar regolith-based construction materials are quite sensitive to the composition and so in-situ methods for evaluating the composition of the lunar regolith could be critical. Various analytical instrumentation has been proposed for in-situ characterization of the composition of regolith on planetary bodies. Raman spectroscopy has been suggested and has some advantages over other in-situ techniques, such as potential for relatively high spatial resolution, direct determination of the mineralogy (while other methods may only infer the mineralogy), nondestructive analysis, relatively simple instrument configurations, and minimal sample preparation/handling. For example, Raman instrumentation has already been deployed in rover-based missions to Mars. Previously, we developed the Standoff Ultracompact Micro-Raman Sensor (SUCR), which is a portable Raman spectroscopy instrument capable to be integrated into a rover or onto a lander. Here, we present work on Raman spectroscopy measurements of NU-LHT-4M lunar simulant using three different Raman instruments with different configurations for collecting Raman data with the goal to explore the effect of these different configurations on the results, especially for use in a lunar environment.

Raman Spectroscopy↗
DOE OSTI2026

Alcock-Paczynski Blinding Scheme for the Ly-$α$ Forest Analysis

We present and validate a blinding method for the Lyman-$α$ (Ly$α$) forest analysis based on a modification of the Alcock-Paczynski test. In order to hide the background expansion history, the method employs a geometrical shift of each quasar (QSO) forest in wavelength space, once the quasar continuum has been fitted and the fluctuation field is extracted. The redshift positions for the QSO sample are also changed in a consistent manner. We show that the method remains effective when applied to real data, where contamination from metals and Lyman-$β$ is intrinsically mixed with the Lyman-$α$ forest. This limitation is primarily visible in the 1D correlation function, where other blinding strategies can mitigate the effect. To assess its effectiveness, the prescription is tested against a series of datasets of increasing complexity: from idealized low-noise mocks, to realistic DESI year one synthetic datasets, and finally to data from DESI first data release (DR1), using both the auto (Ly$α\times$Ly$α$) and cross (Ly$α\times$ QSO) correlations. We find that the method robustly shifts the BAO peak position from the 3D correlation functions to the expected value for cosmology changes of around 5% in the matter content, without altering the shape of the posteriors in the model parameters. In conclusion, this catalog-level blinding strategy is a viable method for cosmological inference with the Lyman-$α$ forest, particularly if a cross-analysis with other tracers using the same blinding strategy is pursued.

Perez-Sanchez, G. [Guanajuato U.] (ORCID:000900096↗
NASA NTRS1988

The effects of thermal accretion disk spectra on the emission lines from active galactic nuclei

Although most ratios of AGN emission lines depend primarily on global averages over the ionizing spectrum of the thermal accretion disk, there are some which behave quite differently for different spectra. Using these, it may be possible to infer the shape of the spectrum in the unobservable ultraviolet. Two classes of methods for making this inference are discussed, one based upon as many line ratios as can be observed, the other singling out those best at distinguishing different spectral shapes. Because of a variety of technical difficulties, only the first class, which uses global measures of goodness-of-fit, is practical. Application of this method to a compilation of quasar line ratios yields a weak conclusion, however, with the best fit favoring the presence of a thermal accretion disk with T(b) of roughly 20 eV.

Krolik, Julian H.↗