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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Bayesian Analysis for Risk Assessment of Selected Medical Events in Support of the Integrated Medical Model Effort

The Exploration Medical Capability project is creating a catalog of risk assessments using the Integrated Medical Model (IMM). The IMM is a software-based system intended to assist mission planners in preparing for spaceflight missions by helping them to make informed decisions about medical preparations and supplies needed for combating and treating various medical events using Probabilistic Risk Assessment. The objective is to use statistical analyses to inform the IMM decision tool with estimated probabilities of medical events occurring during an exploration mission. Because data regarding astronaut health are limited, Bayesian statistical analysis is used. Bayesian inference combines prior knowledge, such as data from the general U.S. population, the U.S. Submarine Force, or the analog astronaut population located at the NASA Johnson Space Center, with observed data for the medical condition of interest. The posterior results reflect the best evidence for specific medical events occurring in flight. Bayes theorem provides a formal mechanism for combining available observed data with data from similar studies to support the quantification process. The IMM team performed Bayesian updates on the following medical events: angina, appendicitis, atrial fibrillation, atrial flutter, dental abscess, dental caries, dental periodontal disease, gallstone disease, herpes zoster, renal stones, seizure, and stroke.

Gilkey, Kelly M.↗
DOE OSTI2018

Inter-annual variability of net and gross ecosystem carbon fluxes: A review

As the lifetime of regional flux networks approach twenty years, there is a growing number of papers that have published long term records (5 years or more) of net carbon fluxes between ecosystems and the atmosphere. Unanswered questions from this body of work are: 1) how variable are carbon fluxes on a year to year basis?; 2) what are the biophysical factors that may cause interannual variability and/or temporal trends in carbon fluxes?; and 3) how does the biophysical control on this carbon flux variability differ by climate and ecological spaces? To address these questions, we surveyed published data from 59 sites that reported on five or more years of continuous measurements, yielding 544 site-years of data. We found that the standard deviation of the interannual variability in net ecosystem carbon exchange (162 gC m -2 y -1 ) is large relative to its population mean (-200 gC m -2 y -1 ). Broad-leaved evergreen forests and crops experienced the greatest absolute variability in interannual net carbon exchange (greater than ±300 gC m -2 y -1 ) and boreal evergreen forests and maritime wetlands were among the least variable (less than ±40 gC m -2 y -1 ). A disproportionate fraction of the yearly variability in net ecosystem exchange was associated with biophysical factors that modulated ecosystem photosynthesis rather than ecosystem respiration. Yet, there was appreciable and statistically significant covariance between ecosystem photosynthesis and respiration. Consequently, biophysical conditions that conspired to increase ecosystem photosynthesis to from one year to the next were associated with an increase in ecosystem respiration, and vice versa; on average, the year to year change in respiration was 40% as large as the year to year change in photosynthesis. The analysis also identified sets of ecosystems that are on the verge of switching from being carbon sinks to carbon sources. These include sites in the Arctic tundra, the evergreen forests in the Pacific northwest and some grasslands, where year to year changes in respiration are outpacing those in photosynthesis. While a select set of climatic and ecological factors (e.g. light, rainfall, temperature, phenology) played direct and indirect roles on this variability, their impact differed conditionally, as well as by climate and ecological spaces. For example, rainfall had both positive and negative effects. Deficient rainfall caused a physiological decline in photosynthesis in temperate and semi-arid regions. Too much rain, in the humid tropics, limited photosynthesis by limiting light. In peatlands and tundra, excess precipitation limited ecosystem respiration when it raised the water table to the surface. For deciduous forests, warmer temperatures lengthened the growing season, increasing photosynthesis, but this effect also increased soil respiration. Finally, statistical analysis was performed to evaluate the detection limit of trends; we computed the confidence intervals of trends in multi-year carbon fluxes that need to be resolved to conclude whether the differences are to be attributed to randomness or biophysical forcings. Ongoing studies and reports on interannual variations need to consider the role of the duration of the time series on random errors when quantifying potential trends and extreme events.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Trophic classification of selected Colorado lakes

Multispectral scanner data, acquired over several Colorado lakes using LANDSAT-1 and aircraft, were used in conjunction with contact-sensed water quality data to determine the feasibility of assessing lacustrine trophic levels. A trophic state index was developed using contact-sensed data for several trophic indicators. Relationships between the digitally processed multispectral scanner data, several trophic indicators, and the trophic index were examined using a supervised multispectral classification technique and regression techniques. Statistically significant correlations exist between spectral bands, several of the trophic indicators and the trophic state index. Color-coded photomaps were generated which depict the spectral aspects of trophic state.

Blackwell, R. J.↗
DOE OSTI2022

Pyomo.DOE: An open-source package for model-based design of experiments in Python

Predictive mathematical models are a cornerstone of science and engineering. Yet selecting, calibrating, and validating said science-based models often remains an art in practice. Model-based design of experiments (MBDoE) provides a systematic framework to maximize information gain from experiments while minimizing time and resource costs. But MBDoE remains limited to niche application areas, in part because practitioners must integrate expertise in statistics, computational optimization, and modeling. To help reduce this barrier, we introduce Pyomo.DOE, an open-source package for MBDoE. Pyomo.DOE uses a nonlinear sensitivity analysis code k_aug to quickly approximate the Fisher information matrix and leverages a new stochastic programming abstraction. We demonstrate Pyomo.DOE with the first application of MBDoE to fixed-bed breakthrough experiments, which highlights the power of Pyomo.DOE to quantify the value of experimental modifications a priori for large-scale partial differential-algebraic equation (PDAE) models. Here we also provide a mathematical primer on MBDoE targeted at general chemical engineers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Impact of global atmospheric reanalyses on statistical precipitation downscaling

Statistical downscaling based on a perfect prognosis approach often relies on global reanalyses to infer the statistical relationship between synoptic predictors and the local variable of interest, here daily precipitation. Nowadays, many reanalyses are available and their impact on the downscaled variable is not often considered. The present work assessed the impact of ten reanalyses on the performance of seven variants of analogue methods for statistical precipitation downscaling at 301 stations in Switzerland. Even though the study location is in a data-rich region, significant differences were found between reanalyses and their impact on the performance of the method can be even higher than the choice of the predictor variables. There was no single overall winner, but a selection of recommended reanalyses resulting in higher skill scores depending on the considered predictor variables. The impact of the output spatial resolution was assessed for different types of variables. Output resolutions below one degree were found to be often of low to no interest. Reanalyses with longer archives allow the pool of potential analogues to be increased, resulting in better performance. However, when adding variables affected by errors in a more distant past, the skill score decreased again. The use of multiple members from two reanalyses was also tested over a recent and a past period. The benefit of using members to increase the performance by better incorporating the uncertainties was found to be limited, and even problematic with methods using multiple analogy levels.

Meteorology & Atmospheric Sciences↗
DOE OSTI2021

Implementation of Perdew–Zunger self-interaction correction in real space using Fermi–Löwdin orbitals

Most widely used density functional approximations suffer from self-interaction error, which can be corrected using the Perdew–Zunger (PZ) self-interaction correction (SIC). We implement the recently proposed size-extensive formulation of PZ-SIC using Fermi–Löwdin Orbitals (FLOs) in real space, which is amenable to systematic convergence and large-scale parallelization. Here, we verify the new formulation within the generalized Slater scheme by computing atomization energies and ionization potentials of selected molecules and comparing to those obtained by existing FLOSIC implementations in Gaussian based codes. The results show good agreement between the two formulations, with new real-space results somewhat closer to experiment on average for the systems considered. We also obtain the ionization potentials and atomization energies by scaling down the Slater statistical average of SIC potentials. The results show that scaling down the average SIC potential improves both atomization energies and ionization potentials, bringing them closer to experiment. Finally, we verify the present formulation by calculating the barrier heights of chemical reactions in the BH6 dataset, where significant improvements are obtained relative to Gaussian based FLOSIC results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

A deep, multi-epoch Chandra HETG study of the ionized outflow from NGC 4051

Actively accreting supermassive black holes significantly impact the evolution of their host galaxies, truncating further star formation by expelling large fractions of gas with wide-angle outflows. The X-ray band is key to understanding how these black hole winds affect their environment, as the outflows have high temperatures ~10 5–8 K). We have developed a Bayesian framework for characterizing active galactic nucleus outflows with an improved ability to explore parameter space and perform robust model selection. We applied this framework to a new 700 ks and an archival 315 ks Chandra High Energy Transmission Gratings observation of the Seyfert galaxy NGC 4051. We have detected six absorbers intrinsic to NGC 4051. These wind components span velocities from 400 to 30000 km s -1 . We have determined that the most statistically significant wind component is purely collisionally ionized, which is the first detection of such an absorber. This wind has T ≈ 10 7 K and v ≈ 880 km s -1 and remains remarkably stable between the two epochs. Other slow components also remain stable across time. Fast outflow components change their properties between 2008 and 2016, suggesting either physical changes or clouds moving in and out of the line of sight. For one of the fast components, we obtain one of the tightest wind density measurements to date, log n/(cm -3 ) = 13.0$^{+0.01}_{-0.02}$, and determine that it is located at ~240 gravitational radii. The estimated total outflow power surpasses 5 percent of the bolometric luminosity (albeit with large uncertainties) making it important in the context of galaxy–black hole interactions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

An empirical approach to model selection: weak lensing and intrinsic alignments

ABSTRACT In cosmology, we routinely choose between models to describe our data, and can incur biases due to insufficient models or lose constraining power with overly complex models. In this paper, we propose an empirical approach to model selection that explicitly balances parameter bias against model complexity. Our method uses synthetic data to calibrate the relation between bias and the χ2 difference between models. This allows us to interpret χ2 values obtained from real data (even if catalogues are blinded) and choose a model accordingly. We apply our method to the problem of intrinsic alignments – one of the most significant weak lensing systematics, and a major contributor to the error budget in modern lensing surveys. Specifically, we consider the example of the Dark Energy Survey Year 3 (DES Y3), and compare the commonly used non-linear alignment (NLA) and tidal alignment and tidal torque (TATT) models. The models are calibrated against bias in the Ωm–S8 plane. Once noise is accounted for, we find that it is possible to set a threshold Δχ2 that guarantees an analysis using NLA is unbiased at some specified level Nσ and confidence level. By contrast, we find that theoretically defined thresholds (based on, e.g. p-values for χ2) tend to be overly optimistic, and do not reliably rule out cosmological biases up to ∼1–2σ. Considering the real DES Y3 cosmic shear results, based on the reported difference in χ2 from NLA and TATT analyses, we find a roughly $30{{\ \rm per\ cent}}$ chance that were NLA to be the fiducial model, the results would be biased (in the Ωm–S8 plane) by more than 0.3σ. More broadly, the method we propose here is simple and general, and requires a relatively low level of resources. We foresee applications to future analyses as a model selection tool in many contexts.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Insights into metastability of photovoltaic materials at the mesoscale through massive I–V analytics

The authors demonstrate the feasibility of quantifying cell-level performance heterogeneity from module-level I–V curves by determining conditions of bypass diode turn-on. Analysis of these curves falls outside of typical diode-based models of photovoltaic (PV) performance. The authors show that this approach can leverage statistical and machine learning techniques for broad application to massive datasets, and combine those insights with simulations and laboratory-based experiments to provide useful information into the metastability of the interfaces of a PV cell. The authors find good agreement between the experimentally determined curves and the simulated curves, which guide the variable selection in the massive dataset collected from sites in Cleveland, OH, USA, the Negev Desert, Israel, Isla Gran Canaria, Spain, and Mount Zugspitze, Germany.

Peshek, Timothy J.↗
DOE OSTI2024

Assessing the Expansion of Ground-Motion Sensing Capability in Smart Cities via Internet Fiber-Optic Infrastructure

Monitoring ground motion in smart cities can improve the public safety by providing critical insights on natural and anthropogenic hazards, for example, earthquakes, landslides, explosions, infrastructure failures, and so forth. Although seismic activity is typically measured using dedicated point sensors (e.g., geophones and accelerometers), techniques such as distributed acoustic sensing have demonstrated the utility of using fiber-optic cable to detect seismic activity over comparable distances. In this article, we present the results of a study that quantifies the expansion in an area monitored for low-amplitude ground-motion events by augmenting existing point sensors with the internet fiber-optic cable infrastructure. Here we begin by describing our methodology, which utilizes geospatial data on point sensors and internet optical fiber deployed in metropolitan statistical areas (MSAs) in the United States. We extend these data to identify the area that can be monitored by (1) considering the observed seismic noise data in target locations, (2) applying the model from Wilson et al. (2021) to understand the potential coverage area gains using optical fiber sensing, and (3) optimizing the selection of fiber segments to maximize coverage and minimize deployment costs. We implement our methodology in ArcGIS to assess the additional area that can be monitored for low-amplitude ground-motion events (i.e., magnitude >0.5) by utilizing internet fiber-optic cables in the 100 most populous MSAs in the United States. We find that the addition of internet fiber-based sensors in MSAs would increase the area monitored on average by over an order of magnitude from 1% to 12%, if the subset of fiber cable segments that maximize coverage and minimize deployment costs is chosen even if only 20% of all fibers are used.

58 GEOSCIENCES↗
DOE OSTI2016

A Search for WW$\gamma$ and WZ$\gamma$ Triboson Production and Anomalous Quartic Gauge Couplings at $\sqrt{s}$ = 8 and 13~TeV within the Compact Muon Solenoid

An analysis probing for the standard model production of three electroweak vector bosons, WV$\gamma$ with V = W or Z gauge boson, is presented. The W boson decays leptonically to an electron or muon, or their respective antiparticle, paired with the appropriate neutrino. The second boson V decays hadronically into two jets, and additionally a photon is required in the event. The data analyzed correspond to an integrated luminosity of 19.6~fb$^{-1}$ and 2.3~fb$^{-1}$ from proton-proton collisions at $\sqrt{s}$ = 8~TeV and 13~TeV, respectively, collected in 2012 and 2015 by the CMS detector at the Large Hadron Collider. The event selection criteria used in these analyses yields 322 and 46 observed events in data in 2012 and 2015, respectively, while the estimated background yield from theoretical predictions is 342.1~$\pm$~22.2 and 54.3~$\pm$~17.7. These observations are consistent with the standard model next-to-leading order QCD predictions. Given the limitation in statistics to measure the cross section for this production process, an upper limit of 3.4 times the standard model predictions is made at a 95\% confidence level for WV$\gamma$ with photon $p_{T}$ greater than 30~GeV and absolute pseudorapidity less than 1.44. Physics beyond the standard model, such as anomalous couplings between the gauge bosons at the quartic vertex, may lead to enhancement in the number of WV$\gamma$ events produced within high energy collisions. Such enhancements can be observed in kinematic distributions, particularly in the higher energy regions. No evidence of anomalous WW$\gamma\gamma$ and WWZ$\gamma$ quartic gauge boson couplings is found, while 95\% confidence level upper limits are obtained for various couplings.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1975

Psychological stress measurement through voice output analysis

Audio tape recordings of selected Skylab communications were processed by a psychological stress evaluator. Strip chart tracings were read blind and scores were assigned based on characteristics reported by the manufacturer to indicate psychological stress. These scores were analyzed for their empirical relationships with operational variables in Skylab judged to represent varying degrees of situational stress. Although some statistically significant relationships were found, the technique was not judged to be sufficiently predictive to warrant its use in assessing the degree of psychological stress of crew members in future space missions.

Older, H. J.↗
NASA NTRS1977

Snow parameters from Nimbus-6 electrically scanned microwave radiometer

Two sites in Canada were selected for detailed analysis of the ESMR-6/ snow relationships. Data were analyzed for February 1976 for site 1 and January, February and March 1976 for site 2. Snowpack water equivalents were less than 4.5 inches for site 1 and, depending on the month, were between 2.9 and 14.5 inches for site 2. A statistically significant relationship was found between ESMR-6 measurements and snowpack water equivalents for the Site 2 February and March data. Associated analysis findings presented are the effects of random measurement errors, snow site physiolography, and weather conditions on the ESMR-6/snow relationship.

Abrams, G.↗
NASA NTRS1984

Prediction of the space adaptation syndrome

The univariate and multivariate relationships of provocative measures used to produce motion sickness symptoms were described. Normative subjects were used to develop and cross-validate sets of linear equations that optimally predict motion sickness in parabolic flights. The possibility of reducing the number of measurements required for prediction was assessed. After describing the variables verbally and statistically for 159 subjects, a factor analysis of 27 variables was completed to improve understanding of the relationships between variables and to reduce the number of measures for prediction purposes. The results of this analysis show that none of variables are significantly related to the responses to parabolic flights. A set of variables was selected to predict responses to KC-135 flights. A series of discriminant analyses were completed. Results indicate that low, moderate, or severe susceptibility could be correctly predicted 64 percent and 53 percent of the time on original and cross-validation samples, respectively. Both the factor analysis and the discriminant analysis provided no basis for reducing the number of tests.

Reschke, M. F.↗
NASA NTRS1991

Visible and infrared investigations of planet-crossing asteroids and outer solar system objects

The project is supporting lightcurve photometry, colorimetry, thermal radiometry, and astrometry of selected asteroids. Targets include the planet-crossing population, particularly Earth approachers, which are believed to be the immediate source of terrestrial meteorites, future spacecraft targets, and those objects in the outer belt, primarily the Hilda and Trojan populations, that are dynamically isolated from the main asteroid belt. Goals include the determination of population statistics for the planet-crossing objects, the characterization of spacecraft targets to assist in encounter planning and subsequent interpretation of the data, a comparison of the collisional evolution of dynamically isolated Hilda and Trojan populations with the main belt, and the determination of the mechanism driving the activity of the distant object 2060 Chiron.

Tholen, David J.↗
NASA NTRS1992

Greenhouse Effect Detection Experiment (GEDEX). Selected data sets

This CD-ROM contains selected data sets compiled by the participants of the Greenhouse Effect Detection Experiment (GEDEX) workshop on atmospheric temperature. The data sets include surface, upper air, and/or satellite-derived measurements of temperature, solar irradiance, clouds, greenhouse gases, fluxes, albedo, aerosols, ozone, and water vapor, along with Southern Oscillation Indices and Quasi-Biennial Oscillation statistics.

Olsen, Lola M.↗
NASA NTRS1995

SWICS/Ulysses and MASS/wind observations of solar wind sulfur charge states

As Ulysses journeys from the southern to the northern solar pole, the newly launched Wind spacecraft is monitoring the solar wind near 1 AU, slightly upstream of the Earth. Different solar wind structures pass over both spacecraft as coronal holes and other features rotate in and out of view. Ulysses and Wind are presently on opposing sides of the sun allowing us to monitor these streams for extended periods of time. Composition measurements made by instruments on both spacecraft provide information concerning the evolution and properties of these structures. We have combined data from the Solar Wind Ion Composition Spectrometer (SWICS) on Ulysses and the high mass resolution spectrometer (MASS) on Wind to determine the charge state distribution of sulfur in the solar wind. Both instruments employ electrostatic deflection with time-of-flight measurement. The high mass resolution of the MASS instrument (M/Delta-M approximately 100) allows sulfur to be isolated easily while the stepping energy/charge selection provides charge state information. SWICS measurements allow the unique identification of heavy ions by their mass and mass/charge with resolutions of M/Delta-M approximately 3 and M/q/Delta(M/q) approximately 20. The two instruments complement each other nicely in that MASS has the greater mass resolution while SWICS has the better mass/charge resolution and better statistics.

Cohen, C. M. S.↗