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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Fault Detection via Occupation Kernel Principal Component Analysis

Reliable operation of automatic systems is heavily dependent on the ability to detect faults in the underlying dynamics. While traditional model-based methods have been widely used for fault detection, data-driven approaches have garnered increasing attention due to their ease of deployment and minimal need for expert knowledge. In this letter, we present a novel principal component analysis (PCA) method that uses occupation kernels. Occupation kernels result in feature maps that are tailored to the measured data, have inherent noise-robustness due to the use of integration, and can utilize irregularly sampled system trajectories of variable lengths for PCA. The occupation kernel PCA method is used to develop a reconstruction error approach to fault detection and its efficacy is validated using numerical simulations.

42 ENGINEERING↗
DOE OSTI2021

Droplet Number Concentration Value-Added Product

The ndrop_mfrsr value-added product (VAP) provides an estimate of the cloud droplet number concentration of overcast water clouds retrieved from cloud optical depth from the multi-filter rotating shadowband radiometer (MFRSR) instrument and liquid water path (LWP) retrieved from the microwave radiometer (MWR). When cloud layer information is available from vertically pointing lidar and radars in the Active Remote Sensing of Clouds (ARSCL) product, the VAP also provides estimates of the adiabatic LWP and an adiabatic parameter (beta) that indicates how divergent the LWP is from the adiabatic case. quality control (QC) flags (qc_drop_number_conc), an uncertainty estimate (drop_number_conc_toterr), and a cloud layer type flag (cloud_base_type) are useful indicators of the quality and accuracy of any given value of the retrieval. Examples of these major input and output variables are given in sample plots in section 6.0.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Hydrogeochemical Investigation of Recharge Pathways to Intermediate and Regional Groundwater in Canon de Valle and Technical Area 16, Los Alamos National Laboratory

In aquifers consisting of fractured or porous igneous rocks, as well as conglomerate and sandstone products of volcanic formations, silicate minerals actively dissolve and precipitate (Eby, 2004; Eriksson, 1985; Drever, 1982). Dissolution of hydrated volcanic glass is also known to influence the character of groundwater to which it is exposed (White et al., 1980). Hydrochemical evolution, within saturated zones of volcanic formations, is modeled here as a means to resolve the sources feeding a perched groundwater zone. By observation of solute mass balances in groundwater, together with rock chemistry, this study characterizes the chemical weathering processes active along recharge pathways in a mountain front system. Inverse mass balance modeling, which accounts for mass fluxes between solid phases and solution, is used to contrive sets of quantitative reactions that explain chemical variability of water between sampling points. Model results are used, together with chloride mass balance estimation, to evaluate subsurface mixing scenarios generated by further modeling. Final model simulations estimate contributions of mountain block and local recharge to various contaminated zones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An Investigation of Nanoindentation as Quality Control [Slides]

Nanoindentation Continuous Stiffness Measurement (CSM) mapping, and Strain Rate Jump Testing (SRJT) proved effective to highlight and visualize the extent of property differences between the samples. From the analysis, Lot A has a significant dead zone at its center, especially when compared with the cross section of Lot B. Quick identification of property issues from one of the two feed stocks, both of which fit the specification. Mechanical performance was connected to the microstructure. Thus, using the structure-property results, it is noted that the processing of Lot A may have been insufficient. Nanoindentation allows for the sampling of quality control variables such as hardness and modulus in a short time span at high resolution, which is cheaper and faster than traditional strength experiments (tension and compression tests).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas

The Outer Continental Shelf along the U.S. east coast exhibits abundant wind resources and is now a geographic focus for offshore wind deployments. This analysis derives and presents expected extreme wind and wave conditions for the sixteen lease areas that are currently being developed. Using the homogeneous ERA5 reanalysis dataset it is shown that the fifty-year return period wind speed (U50) at 100 m a.s.l. in the lease areas ranges from 29.2 to 39.7 ms -1 . After applying corrections to account for spectral smoothing and averaging period, the associated pseudo-point U50 estimates are 34 to 46 ms -1 . The derived uncertainty in U50 estimates due to different distributional fitting is smaller than the uncertainty associated with under-sampling of the interannual variability in annual maximum wind speeds. It is shown that, in the northern lease areas, annual maximum wind speeds are generally associated with intense extratropical cyclones rather than cyclones of tropical origin. Extreme wave statistics are also presented and indicate that the 50-year return period maximum wave height may substantially exceed 15 m. From this analysis, there is evidence that annual maximum wind speeds and waves frequently derive from the same cyclone source and often occur within a 6 h time interval.

16 TIDAL AND WAVE POWER↗
DOE OSTI2018

Use of High-Throughput Automated Microbioreactor System for Production of Model IgG1 in CHO Cells

Automated microscale bioreactors (15 mL) can be a useful tool for cell culture engineers. They facilitate the simultaneous execution of a wide variety of experimental conditions while minimizing potential process variability. Applications of this approach include: clone screening, temperature and pH shifts, media and supplement optimization. Furthermore, the small reactor volumes are conducive to large Design of Experiments that investigate a wide range of conditions. This allows upstream processes to be significantly optimized before scale-up where experimentation is more limited in scope due to time and economic constraints. Automated microscale bioreactor systems offer various advantages over traditional small scale cell culture units, such as shake flasks or spinner flasks. However, during pilot scale process development significant care must be taken to ensure that these advantages are realized. When run with care, the system can enable high level automation, can be programmed to run DOE's with a higher number of variables and can reduce sampling time when integrated with a nutrient analyzer or cell counter. Integration of the expert-derived heuristics presented here, with current automated microscale bioreactor experiments can minimize common pitfalls that hinder meaningful results. In the extreme, failure to adhere to the principles laid out here can lead to equipment damage that requires expensive repairs. Furthermore, the microbioreactor systems have small culture volumes making characterization of cell culture conditions difficult. The number and amount of samples taken in-process in batch mode culture is limited as operating volumes cannot fall below 10 mL. This method will discuss the benefits and drawbacks of microscale bioreactor systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Follow-up Studies of Five Cataclysmic Variable Candidates Discovered by LAMOST

We report follow-up observations of five cataclysmic variable candidates from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) published by Hou et al. LAMOST J024048.51+195226.9 is the most unusual of the five; an early-M type secondary star contributes strongly to its spectrum, and its spectral and photometric behavior are strikingly reminiscent of the hitherto-unique propeller system AE Aqr. We confirm that a 7.34 hr period discovered in the Catalina survey data is orbital. Another object, LAMOST J204305.95+341340.6, appears to be a near twin of the novalike variable V795 Her, with an orbital period in the so-called 2–3 hr “gap.” LAMOST J035913.61+405035.0 is evidently an eclipsing, weakly outbursting dwarf nova with a 5.48 hr period. Our spectrum of LAMOST J090150.09+375444.3 is dominated by a late-type secondary and shows weak, narrow Balmer emission moving in phase with the absorption lines, but at lower amplitude; we do not see the He ii λ4686 emission evident in the published discovery spectrum. We again confirm that a period from the Catalina data, in this case 6.80 hr, is orbital. LAMOST J033940.98+414805.7 yields a radial-velocity period of 3.54 hr, and its spectrum appears to be typical of novalike variables in this period range. The spectroscopically selected sample from LAMOST evidently includes some interesting cataclysmic variables that have been unrecognized until now, apparently because of the relatively modest range of their photometric variations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Most Massive Active Galactic Nuclei at 1 ≲ z ≲ 2

We obtained near-infrared spectra of 26 Sloan Digital Sky Survey quasars at 0.7<z<2.5 with reported rest-frame ultraviolet M {sub BH} ∼ 10{sup 10} M {sub ⊙} to critically examine the systematic effects involved with their mass estimations. We find that active galactic nuclei (AGNs) heavier than 10{sup 10} M {sub ⊙} often display double-peaked Hα emission, extremely broad Fe ii complex emission around Mg ii, and highly blueshifted and broadenedC iv emission. The weight of this evidence, combined with previous studies, cautions against the use of M {sub BH} values based on any emission line with a width over 8000 km s{sup −1}. Also, the M {sub BH} estimations are not positively biased by the presence of ionized narrow line outflows, anisotropic radiation, or the use of line FWHM instead of σ for our sample, and unbiased with variability, scatter in broad line equivalent width, or obscuration for general type-1 quasars. Removing the systematically uncertain M {sub BH} values, ∼10{sup 10} M {sub ⊙} black holes (BHs) in 1 ≲ z ≲ 2 AGNs can still be explained by anisotropic motion of the broad line region from ∼10{sup 9.5} M {sub ⊙} BHs, although current observations support that they are intrinsically most massive, and overmassive to the host’s bulge mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Data from: Temporal dynamics of free‐living nitrogen fixation in the switchgrass rhizosphere

Here we present data associated with the manuscript, Temporal dyanmics of free-living nitrogen fixation in the switchgrass rhizosphere. Free-living nitrogen fixation (FLNF) represents an important terrestrial N source and is gaining interest for its potential to contribute plant available N to bioenergy cropping systems. Switchgrass, a cellulosic bioenergy crop, may be reliant on FLNF when particularly when grown on low N marginal lands. These potential contributions of FLNF to switchgrass and the controls on this process are not well understood. We evaluated drivers of FLNF rates and N-fixing microbial community composition in field-grown switchgrass systems over two years with high temporal sampling. We found climate variables to be strong drivers of FLNF in switchgrass systems, compared to other environmental and biological factors including soil nutrients and N-fixing microbial community composition. Increased soil moisture availability tended to promote FLNF, but extreme rainfall events appeared to be detrimental. These climate-related responses suggest FLNF-derived N contributions may be reduced under projected climate shifts. We also found a significant, but weak correlation between N-fixing microbial community composition and FLNF rates including an observed shift in community composition between 2017 and 2018 and a similarly significant difference in FLNF rates between years. Lastly, we found that seasonal FLNF N contributions, based on measurement with high temporal resolution, may meet up to 80% of switchgrass N demands.

09 BIOMASS FUELS↗
DOE OSTI2021

OzDES reverberation mapping program: Lag recovery reliability for 6-yr C iv analysis

ABSTRACT We present the statistical methods that have been developed to analyse the OzDES reverberation mapping sample. To perform this statistical analysis we have created a suite of customizable simulations that mimic the characteristics of each source in the OzDES sample. These characteristics include: the variability in the photometric and spectroscopic light curves, the measurement uncertainties, and the observational cadence. By simulating the sources in the OzDES sample that contain the C iv emission line, we developed a set of criteria that rank the reliability of a recovered time-lag depending on the agreement between different recovery methods, the magnitude of the uncertainties, and the rate at which false positives were found in the simulations. These criteria were applied to simulated light curves and these results used to estimate the quality of the resulting Radius–Luminosity relation. We grade the results using three quality levels (gold, silver, and bronze). The input slope of the R–L relation was recovered within 1σ for each of the three quality samples, with the gold standard having the lowest dispersion with a recovered a R–L relation slope of 0.454 ± 0.016 with an input slope of 0.47. Future work will apply these methods to the entire OzDES sample of 771 AGN.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Analyzing the Effect of Ocean Internal Variability on Depth-Integrated Steric Sea-Level Rise Trends Using a Low-Resolution CESM Ensemble

Ocean heat uptake is a key indicator of climate change, in part because it contributes to sea-level rise. Quantifying the uncertainties surrounding ocean heat uptake and sea-level rise are important in assessing climate-related risks. Here, comprehensive global climate model ensembles are used to evaluate uncertainties surrounding decadal trends in depth-integrated global steric sea-level rise due to thermal expansion of the ocean. Results are presented against observational estimates, which are used as a guide to the state of recent literature. The first ensemble uses the Community Earth System Model (CESM), which samples the effects of internal variability within the coupled Earth system including contributions from the sub-surface ocean. We compare and contrast these results with an ensemble based on the Coupled Model Intercomparison Project Phase 5 (CMIP5), which samples the combined effects of structural model differences and internal variability. The effects of both internal variability and structural model differences contribute substantially to uncertainties in modeled steric sea-level trends for recent decades, and the magnitude of these effects varies with depth. The 95% range in total sea-level rise trends across the CESM ensemble is 0.151 mm·year –1 for 1957–2013, while this range is 0.895 mm·year –1 for CMIP5. These ranges increase during the more recent decade of 2005–2015 to 0.509 mm·year –1 and 1.096 mm·year –1 for CESM and CMIP5, respectively. The uncertainties are amplified for regional assessments, highlighting the importance of both internal variability and structural model differences when considering uncertainties surrounding modeled sea-level trends. Results can potentially provide useful constraints on estimations of global and regional sea-level variability, in particular for areas with few observations such as the deep ocean and Southern Hemisphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Tracking of Nuclear Cable Insulation Polymer Structural Changes using the Gel Fraction and Uptake Factor Method

Cross-linked polyethylene (XLPE) cable insulation samples were exposed to heat and gamma radiation at a series of temperatures, dose rates, and exposure times to evaluate the effects of these variables on material degradation. The samples were tested using the solvent incubation method to collect gel fraction and uptake factor data in order to assess the crosslinking and chain scission occurring in polymer samples with aging. Consistent with previous reports, gel fraction values were observed to increase and uptake factor values to decrease with radiation and thermal exposure. The trends seen were also more prominent as exposure time increased, suggesting this to be a viable method of tracking structural changes in the XLPE-insulated cable material over extended periods. For the conditions explored, the cable insulation material evaluated did not indicate signs of anomalous aging such as inverse temperature effect in which radiation-induced aging is more severe at lower temperature. Ongoing aging under identical radiation conditions and at lower temperature will further inform conclusions regarding the importance of inverse temperature effects for this material under these conditions.

cable aging↗
DOE OSTI2018

Incremental nonnegative matrix factorization based on correlation and graph regularization for matrix completion

Matrix factorization is widely used in recommendation systems, text mining, face recognition and computer vision. As one of the most popular methods, nonnegative matrix factorization and its incremental variants have attracted much attention. The existing incremental algorithms are established based on the assumption of samples are independent and only update the new latent variable of weighting coefficient matrix when the new sample comes, which may lead to inferior solutions. To address this issue, we investigate a novel incremental nonnegative matrix factorization algorithm based on correlation and graph regularizer (ICGNMF). The correlation is mainly used for finding out those correlated rows to be updated, that is, we assume that samples are dependent on each other. We derive the updating rules for ICGNMF by considering the correlation. We also present tests on widely used image datasets, and show ICGNMF reduces the error by comparing other methods.

Zhang, Xiaoxia↗
DOE OSTI2025

Back trajectories for TBS flights (c1-level)

The ARMTRAJ VAP provides four trajectory datasets initialized at ARM deployment coordinates and configured using ARM datasets. The four trajectory datasets support aerosol, cloud, and planetary boundary layer research. Trajectory calculations use the HYSPLIT model informed by the ERA5 reanalysis dataset at its highest spatial resolution (~31 km). For each sample in each of the four datasets, HYSPLIT will also be run at multiple starting locations surrounding ARM deployments, enabling an ensemble of runs from which the mean and variability (estimated uncertainty) of each sample's trajectory coordinates, thermodynamic properties, or other fields will be reported.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Conformational space exploration of cryo-EM structures by variability refinement

Cryo-EM observation of biological samples enables visualization of sample heterogeneity, in the form of discrete states that are separable, or continuous heterogeneity as a result of local protein motion before flash freezing. Variability analysis of this continuous heterogeneity describes the variance between a particle stack and a volume, and results in a map series describing the various steps undertaken by the sample in the particle stack. While this observation is absolutely stunning, it is very hard to pinpoint structural details to elements of the maps. Here, in order to bridge the gap between observation and explanation, we designed a tool that refines an ensemble of structures into all the maps from variability analysis. Using this bundle of structures, it is easy to spot variable parts of the structure, as well as the parts that are not moving. Comparison with molecular dynamics simulations highlights the fact that the movements follow the same directions, albeit with different amplitudes. Ligand can also be investigated using this method. Variability refinement is available in the Phenix software suite, accessible under the program name phenix.varref.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Processing Aleatory and Epistemic Uncertainties in Experimental Data From Sparse Replicate Tests of Stochastic Systems for Real-Space Model Validation

This paper presents a practical methodology for propagating and processing uncertainties associated with random measurement and estimation errors (that vary from test-to-test) and systematic measurement and estimation errors (uncertain but similar from test-to-test) in inputs and outputs of replicate tests to characterize response variability of stochastically varying test units. Also treated are test condition control variability from test-to-test and sampling uncertainty due to limited numbers of replicate tests. These aleatory variabilities and epistemic uncertainties result in uncertainty on computed statistics of output response quantities. The methodology was developed in the context of processing experimental data for “real-space” (RS) model validation comparisons against model-predicted statistics and uncertainty thereof. The methodology is flexible and sufficient for many types of experimental and data uncertainty, offering the most extensive data uncertainty quantification (UQ) treatment of any model validation method the authors are aware of. It handles both interval and probabilistic uncertainty descriptions and can be performed with relatively little computational cost through use of simple and effective dimension- and order-adaptive polynomial response surfaces in a Monte Carlo (MC) uncertainty propagation approach. A key feature of the progressively upgraded response surfaces is that they enable estimation of propagation error contributed by the surrogate model. Sensitivity analysis of the relative contributions of the various uncertainty sources to the total uncertainty of statistical estimates is also presented. Finally, the methodologies are demonstrated on real experimental validation data involving all the mentioned sources and types of error and uncertainty in five replicate tests of pressure vessels heated and pressurized to failure. Simple spreadsheet procedures are used for all processing operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Autonomous organic synthesis for redox flow batteries via flexible batch Bayesian optimization

Traditional trial-and-error methods for materials discovery are inefficient to meet the urgent demands posed by the rapid progression of climate change. This urgency has driven the increasing interest in integrating robotics and machine learning into materials research to accelerate experimental learning. However, idealized decision-making frameworks to achieve maximum sampling efficiency are not always compatible with high-throughput experimental workflows inside a laboratory. For multi-step chemical processes, differences in hardware capacities can complicate the digital framework by introducing constraints on the maximum number of samples in each step of the experiment, hence causing varying batch sizes in variable selection within the same batch. Therefore, designing flexible sampling algorithms is necessary to accommodate the multi-step synthesis with practical constraints unique to each high-throughput workflow. In this work, we designed and employed three strategies on a high-throughput robotic platform to optimize the sulfonation reaction of redox-active molecules used in flow batteries. Our strategies adapt to the multi-step experimental workflow, where their formulation and heating steps are separate, causing varying batch size requirements. By strategically sampling using clustering and mixed-variable batch Bayesian optimization, we were able to iteratively identify optimal conditions that maximize the yields. Our work presents a flexible approach that allows tailoring the machine learning decision-making to suit the practical constraints in individual high-throughput experimental platforms, followed by performing resource-efficient yield optimization using available open-source Python libraries.

Tamura, Clara [Univ. of Washington, Seattle, WA (U↗
DOE OSTI2021

Variability in NGC 3201 Giant Stars and Its Impact on Their Spectroscopic [Fe/H] Determination

We present the analysis of 34 light curves in V and I of 17 giant stars in the globular cluster NGC 3201 to check if such stars are variable and if their variability has some kind of impact on the iron abundance as obtained from spectroscopic measurements. First, we computed the generalized Lomb–Scargle and phase dispersion minimization periodograms of the sample to check if the stars were variables. In this way, seven stars of the sample were found to be nonvariable, two stars are considered as possible variables, and eight stars were found to be variable, with periods ranging from 0.0881 ± 0.0001 to 0.5418 ± 0.0027 days. According to the literature, the variables have distinct values of [Fe I/H]: the three most metal-rich stars are in the red giant branch (RGB) stage, one has [Fe I/H] = −1.37 dex, while the other two have [Fe I/H] = −1.31 dex. The two most metal-poor variables have [Fe I/H] = −1.61 dex and [Fe I/H] = −1.62 dex, and are AGB stars; the remaining variables have [Fe I/H] = −1.44, −1.48, and −1.50 dex, the first two being RGB stars while the last is an AGB star. On the other hand, stars that appear to be nonvariable have −1.56 ≤ [Fe I/H] ≤ −1.40. We conclude that variability somehow affects the spectroscopic determination of the iron content of giant stars in NGC 3201, increasing the iron spread of the cluster. If variability is not taken into account, this spread could be incorrectly interpreted as due to an intrinsic iron spread affecting the stars of the cluster.

36 MATERIALS SCIENCE↗