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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

TAG… You’re It, Synechocystis sp. PCC 6803!

Triacylglycerol (TAG), a ubiquitous energy storage molecule found mainly in eukaryotes, comprises glycerol esterified with three fatty acids of variable lengths and saturation states. TAG is also considered as a high-value biochemical because it can be converted into fatty acid methyl esters, key components of biodiesel, through transesterification with methanol. Thus, considerable efforts have been made to produce TAGs from CO2 as a renewable energy source.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗
DOE OSTI2021

Self-interacting neutrinos, the Hubble parameter tension, and the cosmic microwave background

Here, we perform a comprehensive study of cosmological constraints on nonstandard neutrino self-interactions using cosmic microwave background and baryon acoustic oscillation data. We consider different scenarios for neutrino self-interactions distinguished by the fraction of neutrino states allowed to participate in self-interactions and how the relativistic energy density, N eff , is allowed to vary. Specifically, we study cases in which all neutrino states self-interact and N eff varies; two species free-stream, which we show alleviates tension with laboratory constraints, while the energy in the additional interacting states varies; and a variable fraction of neutrinos self-interact with either the total N eff fixed to the Standard Model value or allowed to vary. In no case do we find compelling evidence for new neutrino interactions or nonstandard values of N eff . In several cases, we find additional modes with neutrino decoupling occurring at lower redshifts z dec ~ 10 3–4 . We do a careful analysis to examine whether new neutrino self-interactions solve or alleviate the so-called H 0 tension and find that, when all Planck 2018 CMB temperature and polarization data are included, none of these examples eases the tension more than allowing a variable N eff comprised of free-streaming particles. Although we focus on neutrino interactions, these constraints are applicable to any light relic particle.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Sensor Drift Estimation for Reactor Systems by Fusing Multiple Sensor Measurements

A nuclear power plant is instrumented with a variety of sensors that monitor its variables to estimate the state and initiate safety actions, if needed. We address the problem of estimating drifts or errors in sensor measurements due to factors such as calibration changes. We propose an information fusion method that uses measurements from other sensors to generate an estimate of a sensor measurement, and its difference from an actual measurement provides an error estimate. We present two fusers based on the ensemble of trees and support vector machine that are trained using sensor measurements collected at an emulated test loop of a pressurized water reactor under no-drift conditions. We present error estimates for a differential pressure sensor of the heat exchanger of the primary coolant system, under twenty controlled scenarios using the test loop. Both positive and negative errors are captured by both methods in scenarios involving calibration drifts, blocking, air gap and electromagnetic interference. The root mean square errors of estimated drifts are typically within 2% percent of the maximum.

Rao, Nageswara↗
DOE OSTI2021

Multisource Data Fusion Outage Location in Distribution Systems via Probabilistic Graphical Models

Efficient outage location is critical to enhancing the resilience of power distribution systems. However, accurate outage location requires combining massive evidence received from diverse data sources, including smart meter (SM) last gasp signals, customer trouble calls, social media messages, weather data, vegetation information, and physical parameters of the network. This is a computationally complex task due to the high dimensionality of data in distribution grids. In this paper, we propose a multi-source data fusion approach to locate outage events in partially observable distribution systems using Bayesian networks (BNs). A novel aspect of the proposed approach is that it takes multi-source evidence and the complex structure of distribution systems into account using a probabilistic graphical method. Our method can radically reduce the computational complexity of outage location inference in high-dimensional spaces. The graphical structure of the proposed BN is established based on the network’s topology and the causal relationship between random variables, such as the states of branches/customers and evidence. Utilizing this graphical model, accurate outage locations are obtained by leveraging a Gibbs sampling (GS) method, to infer the probabilities of de-energization for all branches. Compared with commonly-used exact inference methods that have exponential complexity in the size of the BN, GS quantifies the target conditional probability distributions in a timely manner. As a result, a case study of several real-world distribution systems is presented to validate the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Tidal–hydrological dynamics of water temperature across freshwater forested wetlands on the northeastern Pacific coast

Abstract Tidal freshwater forests were once extensive across temperate coastlines, but loss and fragmentation have made estimation of their ecosystem functions challenging. We measured water temperature for 2 years in three Sitka spruce tidal forests, a restoration site, and an adjacent emergent marsh on the Columbia River, Washington, United States. We assessed spatial variability of water temperature within sites including the effects of hydrology, differences among bay and tributary tidal forests, and differences between the tidal forests and the mainstem Columbia, the restoration site, and the emergent marsh. The tidal forests nearest to the bay had lower interior water temperatures than their channel confluences by up to 2.5°C (weekly median temperature) and 2.0°C (weekly maximum temperature), with most cooling occurring during the low‐flow months of July–September. Tributary sites had maximum temperatures up to 1.9°C cooler than bay sites and 4.2°C cooler than the mainstem. Temperatures in the two bay sites decreased by −0.16°C/100 m and −0.07°C/100 m, on average. The restoration site had the smallest within‐site temperature gradient. Differences in maximum temperatures were greatest when tidal range was low, while higher tidal ranges were associated with warmer and more variable site interiors relative to their confluences. These results suggest that water temperatures in these tidal forests can provide temperature refugia for cold water biota including salmon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A XANES and Raman investigation of sulfur speciation and structural order in Murchison and Allende meteorites

Abstract Insoluble organic matter ( IOM ) and hydrothermally treated IOM extracted from two carbonaceous chondrites, Murchison and Allende, was studied using sulfur K‐edge XANES (X‐ray absorption near edge structure) and μ‐Raman spectroscopy, with the aim to understand their IOM 's sulfur speciation and structural order, and how aqueous alteration or thermal metamorphism may have transformed these materials. We found that the sulfur‐functional group chemistry of both the Murchison IOM and hydrothermally treated IOM samples have a large chemical variability ranging from oxidation states of S −2 to S +6 , and exhibit a transformation in their oxidation state after the hydrothermal treatment ( HT ) to produce thiophenes and thiol compounds. Sulfoxide and sulfite peaks are also present in Murchison. Sulfates considered intrinsic to Murchison are most likely preaccretionary in nature, and not a result of reactions with water at high temperatures on the asteroid parent body. We argue that the reduced sulfides may have formed in the CM parent body, while the thiophenes and thiol compounds are a result of the HT . Micro‐Raman spectra show the presence of aliphatic and aromatic moieties in Murchison's material as observed previously, which exhibits no change after HT . Because the Murchison IOM was modified, as seen by XANES analysis, absence of a change observed using micro‐Raman indicated that although the alkyl carbons of IOM were cleaved, the aromatic network was not largely modified after HT . By contrast, Allende IOM contains primarily disulfide and elemental sulfur, no organic sulfur, and shows no transformation after HT . This nontransformation of Allende IOM after HT would indicate that parent body alteration of sulfide to sulfate is not feasible up to temperatures of 300°C. The reduced sulfur products indicate extreme secondary chemical processing from the precursor compounds in its parent body at temperatures as high as 624°C, as estimated from μ‐Raman D band parameters. The Raman parameters in Allende IOM that was interpreted in terms of amorphous carbon with regions of large clusters of benzene rings, was transformed after the HT to those with fewer benzene rings.

Bose, M.↗
DOE OSTI2015

High T{sub c} in cuprates as a universal property of the electron–phonon system

The Eliashberg theory, which is generalized due to peculiar properties of the finite-width electron band for electron–phonon (EP) systems with a variable electron density of states (DOS), as well as with allowance for the electron–hole nonequivalence of the frequency behavior of the chemical potential renormalization depending on the doping level and electron correlations in the vertex function, is used to study T{sub c} in cuprates. The phonon contribution to the nodal anomalous electron Green’s function (GF) is considered. Pairing within the total width of the electron band, and not only in a narrow layer at the Fermi surface, is taken into account. The calculated frequency and temperature dependences, as well as the dependence on the doping level of the complex renormalization ReZ, ImZ of the mass, complex renormalization Reχ(ω), Imχ(ω) of the chemical potential, and DOS N(ε) renormalized due to the EP interaction are used to calculate the electron nodal anomalous GF. It is found that the effect of suppressing the high-frequency contribution to the Eliashberg equations derived anew for the EP system with a finite width of the electron band is a decisive factor for the manifestation of the effect of high-temperature superconductivity (HTSC). It is shown that in the vicinity of the optimal hole-type doping level in cuprates, the high value of T{sub c} is reproduced by the spectral function of the electron–phonon interaction, which is obtained from tunneling experiments. Upon an increase in the doping level, leading to an increase in the degree of electron–hole nonequivalence, the new logarithmic term appearing in the equations for T{sub c} has a tendency to increase T{sub c}, while intensification of damping of charge carriers (especially suppression of the cutoff factor) leads to a decrease in T{sub c}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Uncovering the relationships between military community health and affects expressed in social media

Military populations present a small, unique community whose mental and physical health impacts the security of the nation. Recent literature has explored social media's ability to enhance disease surveillance and characterize distinct communities with encouraging results. We present a novel analysis of the relationships between influenza-like illnesses (ILI) clinical data and affects (i.e., emotions and sentiments) extracted from social media around military facilities. Our analyses examine (1) differences in affects expressed by military and control populations, (2) affect changes over time by users, (3) differences in affects expressed during high and low ILI seasons, and (4) correlations and cross-correlations between ILI clinical visits and affects from an unprecedented scale –171M geo-tagged tweets across 31 global geolocations. Key findings include: Military and control populations dier in the way they express affects in social media over space and time. Control populations express more positive and less negative sentiments and less sadness, fear, disgust, and anger emotions than military. However, affects expressed in social media by both populations within the same area correlate similarly with ILI visits to military health facilities. We have identified potential responsible co-factors leading to location variability, e.g., region or state locale, military service type and/or the ratio of military to civilian populations. For most locations, ILI proportions positively correlate with sadness and neutral sentiment, which are the affects most often expressed during high ILI season. The ILI proportions negatively correlate with fear, disgust, surprise, and positive sentiment. These results are similar to the low ILI season where anger, surprise, and positive sentiment are highest. Finally, cross-correlation analysis shows that most affects lead ILI clinical visits, i.e. are predictive of ILI data, with affect-ILI leading intervals dependent on geo-location and affect type. Altogether, information gained in this study exemplifies a usage of social media data to understand the correlation between psychological behavior and health in the military population and the potential for use of social media affects for prediction of ILI cases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Exploring small-scale chemostats to scale up microbial processes: 3-hydroxypropionic acid production in S. cerevisiae

The physiological characterization of microorganisms provides valuable information for bioprocess development. Chemostat cultivations are a powerful tool for this purpose, as they allow defined changes to one single parameter at a time, which is most commonly the growth rate. The subsequent establishment of a steady state then permits constant variables enabling the acquisition of reproducible data sets for comparing microbial performance under different conditions. We performed physiological characterizations of a 3-hydroxypropionic acid (3-HP) producing Saccharomyces cerevisiae strain in a miniaturized and parallelized chemostat cultivation system. The physiological conditions under investigation were various growth rates controlled by different nutrient limitations (C, N, P). Based on the cultivation parameters obtained subsequent fed-batch cultivations were designed.We report technical advancements of a small-scale chemostat cultivation system and its applicability for reliable strain screening under different physiological conditions, i.e. varying dilution rates and different substrate limitations (C, N, P). Exploring the performance of an engineered 3-HP producing S. cerevisiae strain under carbon-limiting conditions revealed the highest 3-HP yields per substrate and biomass of 16.6 %C-mol and 0.43 g gCDW -1 , respectively, at the lowest set dilution rate of 0.04 h -1 . 3-HP production was further optimized by applying N- and P-limiting conditions, which resulted in a further increase in 3-HP yields revealing values of 21.1 %C-mol and 0.50 g gCDW -1 under phosphate-limiting conditions. The corresponding parameters favoring an increased 3-HP production, i.e. dilution rate as well as C- and P-limiting conditions, were transferred from the small-scale chemostat cultivation system to 1-L bench-top fermenters operating in fed-batch conditions, revealing 3-HP yields of 15.9 %C-mol and 0.45 g gCDW -1 under C-limiting, as well as 25.6 %C-mol and 0.50 g gCDW -1 under phosphate-limiting conditions. Small-scale chemostat cultures are well suited for the physiological characterization of microorganisms, particularly for investigating the effect of changing cultivation parameters on microbial performance. In our study, optimal conditions for 3-HP production comprised (i) a low dilution rate of 0.04 h -1 under carbon-limiting conditions and (ii) the use of phosphate-limiting conditions. Similar 3-HP yields were achieved in chemostat and fed-batch cultures under both C- and P-limiting conditions proving the growth rate as robust parameter for process transfer and thus the small-scale chemostat system as powerful tool for process optimization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Final Technical Report for Collaborative Research: Developing and Implementing Ocean-Atmosphere Reanalyses for Climate Applications (OARCA)

As an important step toward a coupled data assimilation system for generating reanalysis fields needed to assess climate model projections, the Ocean Atmosphere Coupled Reanalysis for Climate Applications (OARCA) project assesses and improves the longest reanalyses currently available of the atmosphere and ocean: the 20th Century Reanalysis Project (20CR) and the Simple Ocean Data Assimilation with sparse observational input (SODAsi) system, respectively. In this project, we make off-line but coordinated improvements in the 20CR and SODAsi datasets, with improvements in one feeding into improvements of the other through an iterative generation of new versions. These datasets now span from the 19th to 21st centuries. We then study the extreme weather and variability from days to decades of the resulting datasets. A total of 24 publications have been produced in this project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Kinetics of C 10 H 7 Br Pyrolysis

Here, the temperature and pressure-dependent rate constants for the process C 10 H 7 Br ↔ C 10 H 7 +Br were evaluated using the variable reaction coordinate transition state theory VRC-TST. The calculated rate constants and computational fluid dynamics (CFD) calculations were employed to estimate the pyrolysis efficiency of 2-bromonaphthalene in the resistively-heated SiC high-temperature “chemical reactor” at the temperature of about 1500 K. The observed 40% pyrolysis efficiency is reproduced by CFD calculations if the value of the calculated rate constant for the C 10 H 7 Br pyrolysis is increased by a factor of 2.

Zagidullin, M. V.↗
DOE OSTI2022

Predicting Rare Earth Element Potential in Produced and Geothermal Waters of the United States via Emergent Self-Organizing Maps

This work applies emergent self-organizing map (ESOM) techniques, a form of machine learning, in the multidimensional interpretation and prediction of rare earth element (REE) abundance in produced and geothermal waters in the United States. Visualization of the variables in the ESOM trained using the input data shows that each REE, with the exception of Eu, follows the same distribution patterns and that no single parameter appears to control their distribution. Cross-validation, using a random subsample of the starting data and only using major ions, shows that predictions are generally accurate to within an order of magnitude. Using the same approach, an abridged version of the U.S. Geological Survey Produced Waters Database, Version 2.3 (which includes both data from produced and geothermal waters) was mapped to the ESOM and predicted values were generated for samples that contained enough variables to be effectively mapped. Results show that in general, produced and geothermal waters are predicted to be enriched in REEs by an order of magnitude or more relative to seawater, with maximum predicted enrichments in excess of 1000-fold. Cartographic mapping of the resulting predictions indicates that maximum REE concentrations exceed values in seawater across the majority of geologic basins investigated and that REEs are typically spatially co-associated. The factors causing this co-association were not determined from ESOM analysis, but based on the information currently available, REE content in produced and geothermal waters is not directly controlled by lithology, reservoir temperature, or salinity.

Engle, Mark A. (ORCID:0000000152587374)↗
DOE OSTI2017

A Continuum of Accretion Burst Behavior in Young Stars Observed by K2

We present 29 likely members of the young ρ Oph or Upper Sco regions of recent star formation that exhibit “accretion burst” type light curves in K2 time series photometry. The bursters were identified by visual examination of their ∼80-day light curves, though all satisfy the M<−0.25 flux asymmetry criterion for burst behavior defined by Cody et al. The burst sources represent ≈9% of cluster members with strong infrared excess indicative of circumstellar material. Higher amplitude burster behavior is correlated with larger inner disk infrared excesses, as inferred from WISE W1−W2 color. The burst sources are also outliers in their large Hα emission equivalent widths. No distinction between bursters and non-bursters is seen in stellar properties such as multiplicity or spectral type. The frequency of bursters is similar between the younger, more compact ρ Oph region, and the older, more dispersed Upper Sco region. The bursts exhibit a range of shapes, amplitudes (∼10%–700%), durations (∼1–10 days), repeat timescales (∼3–80 days), and duty cycles (∼10%–100%). Our results provide important input to models of magnetospheric accretion, in particular, by elucidating the properties of accretion-related variability in the low state between major longer duration events such as EX Lup and FU Ori type accretion outbursts. We demonstrate the broad continuum of accretion burst behavior in young stars—extending the phenomenon to lower amplitudes and shorter timescales than traditionally considered in the theory of pre-main sequence accretion history.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Balancing aggregation and smoothing errors in inverse models

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.

Turner, A. J.↗
NASA NTRS1970

An endpoint sufficiency test

Endpoint sufficiency test based on differential calculus method, considering Bolza problem of continuous state and piecewise control variables

Vincent, T. L.↗