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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 NTRS2020

A Statistical Model to Predict the Extratropical Transition of Tropical Cyclones

This paper introduces a logistic regression model for the extratropical transition(ET) of tropical cyclones in the North Atlantic and the Western North Pacific, using elastic net regularization to select predictors and estimate coefficients.Predictors are chosen from the 1979-2017 best track and reanalysis datasets, and verification is done against the tropical/extratropical labels in the best track data. In an independent test set, the model skillfully predicts ET at lead times up to two days, with latitude and sea surface temperature as its most important predictors. At a lead time of 24 h, it predicts ET with a Matthews correlation coefficient of 0.4 in the North Atlantic, and 0.6 in the Western North Pacific. It identifies 80% of storms undergoing ET in the North Atlantic, and 92% of those in the Western North Pacific. 90% of transition time errors are less than 24 h. Select examples of the model's performance on individual storms illustrate its strengths and weaknesses.Two versions of the model are presented: an "operational model" that may provide baseline guidance for operational forecasts, and a "hazard model"that can be integrated into statistical TC risk models. As instantaneous diagnostics for tropical/extratropical status, both models' zero lead time predictions perform about as well as the widely used Cyclone Phase Space (CPS) in the Western North Pacific and better than the CPS in the North Atlantic, and predict the timings of the transitions better than CPS in both basins.

Melanie Bieli↗
DOE OSTI2020

Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models

The co-expression extrapolation (COXEN) method has been successfully used in multiple studies to select genes for predicting the response of tumor cells to a specific drug treatment. Here, we enhance the COXEN method to select genes that are predictive of the efficacies of multiple drugs for building general drug response prediction models that are not specific to a particular drug. The enhanced COXEN method first ranks the genes according to their prediction power for each individual drug and then takes a union of top predictive genes of all the drugs, among which the algorithm further selects genes whose co-expression patterns are well preserved between cancer cases for building prediction models. We apply the proposed method on benchmark in vitro drug screening datasets and compare the performance of prediction models built based on the genes selected by the enhanced COXEN method to that of models built on genes selected by the original COXEN method and randomly picked genes. Models built with the enhanced COXEN method always present a statistically significantly improved prediction performance (adjusted p-value ≤ 0.05). Our results demonstrate the enhanced COXEN method can dramatically increase the power of gene expression data for predicting drug response.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Understanding and improving anode performance in an alkaline membrane electrolyzer using statistical design of experiments

The behavior of the oxygen-evolving positive electrode (i.e. anode) in the anion exchange membrane water electrolyzer (AEMEL) is complex and influenced by several factors. Very few studies have been performed to understand oxygen evolution reaction (OER) behavior by optimizing the individual factors that influence performance. Here, this study highlights the effects of catalyst loading, catalyst selection, porous transport layer (PTL) type and conductive additive content. The influence of each factor is elucidated through a design of experiments (DoE) approach with a full statistical analysis. Electrochemical data, alongside Pareto charts, parametric trends and their mutual interactions are discussed. This DoE approach is also helpful in making useful predictions and discovering new combinations to be tested. The end result was a high-performance AEMEL able to operate at a current density of 1.0 A/cm 2 at 1.80 V with IrOx OER and PtNi hydrogen evolution reaction (HER) catalysts using 0.3 M KOH fed to the anode. Even lower operating voltage was observed with PbRuOx catalyst at the anode, 1.64 V @ 1.0 A/cm 2 , though the cell decay rate was higher. Lastly, a IrOx/PtNi cell was stably operated continuously for 30 days (720 h) at 1.0 A/cm 2 . This study can serve as a guide for optimal electrode design with insights into component-performance compromises, which can aid in making design choices and performing techno-economic analyses.

08 HYDROGEN↗
DOE OSTI2017

Feature Selection and Inferential Procedures for Video Data [Slides]

With the rise of electronic and high-dimensional data, new and innovative feature detection and statistical methods are required to perform accurate and meaningful statistical analysis of these datasets that provide unique statistical challenges. In the area of feature detection, much of the recent feature detection research in the computer vision community has focused on deep learning methods, which require large amounts of labeled training data. However, in many application areas, training data is very limited and often difficult to obtain. We develop methods for fast, unsupervised, precise feature detection for video data based on optical flows, edge detection, and clustering methods. We also use pretrained neural networks and interpretable linear models to extract features using very limited training data. In the area of statistics, while high-dimensional data analysis has been a main focus of recent statistical methodological research, much focus has been on populations of high-dimensional vectors, rather than populations of high-dimensional tensors, which are three-dimensional arrays that can be used to model dependent images, such as images taken of the same person or ripped video frames. Our feature detection method is a non-model-based method that fusses information from dense optical flow, raw image pixels, and frame differences to generate detections. Our hypothesis testing methods are based on the assumption that dependent images are concatenated into a tensor that follows a tensor normal distribution, and from this assumption, we derive likelihood-ratio, score, and regression-based tests for one- and multiple-sample testing problems. Our methods will be illustrated on simulated and real datasets. We conclude this report with comments on the relationship between feature detection and hypothesis testing methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Pilot personality and crew coordination - Implications for training and selection

It is contended that past failures to find linkages between performance and personality were due to a combination of premature performance evaluation, inadequate statistical modeling, and/or the reliance on data gathered in contrived as opposed to realistic situations. The goal of the research presented is to isolate subgroups of pilots along performance-related personality dimensions and to document limits on the impact of crew coordination training between the groups. Three different profiles were identified through cluster analysis of personality scales that replicated across samples and predicted attitude change following training in crew coordination.

Chidester, Thomas R.↗
NASA NTRS1992

A methodology for selective removal of orbital debris

Earth-orbiting objects, large enough to be tracked, were surveyed for possible systematic debris removal. Based upon the statistical collision studies of others, it was determined that objects in orbits approximately 1000 km above the Earth's surface are at greatest collisional risk. Russian C-1B boosters were identified as the most important target of opportunity for debris removal. Currently, more than 100 in tact boosters are orbiting the Earth with apogees between 950 km and 1050 km. Using data provided by Energia USA, specific information on the C-1B booster, in terms of rendezvous and capture strategies, was discussed.

Ash, R. L.↗
DOE OSTI2016

The ALMA spectroscopic survey in the Hubble Ultra Deep Field: search for [C II] line and dust emission in 6 < z < 8 galaxies

We present a search for [C ii] line and dust continuum emission from optical dropout galaxies at z > 6 using ASPECS, our Atacama Large Millimeter submillimeter Array Spectroscopic Survey in the Hubble Ultra-deep Field (UDF). Our observations, which cover the frequency range of 212–272 GHz, encompass approximately the range of 6 < z < 8 for [C ii] line emission and reach a limiting luminosity of L {sub [C ii]} ∼ (1.6–2.5) × 10{sup 8} L {sub ⊙}. We identify 14 [C ii] line emitting candidates in this redshift range with significances >4.5σ, two of which correspond to blind detections with no optical counterparts. At this significance level, our statistical analysis shows that about 60% of our candidates are expected to be spurious. For one of our blindly selected [C ii] line candidates, we tentatively detect the CO(6-5) line in our parallel 3 mm line scan. None of the line candidates are individually detected in the 1.2 mm continuum. A stack of all [C ii] candidates results in a tentative detection with S {sub 1.2 mm} = 14 ± 5 μJy. This implies a dust-obscured star-formation rate (SFR) of (3 ± 1) M {sub ⊙} yr{sup −1}. We find that the two highest-SFR objects have candidate [C ii] lines with luminosities that are consistent with the low-redshift L {sub [C ii]} versus SFR relation. The other candidates have significantly higher [C ii] luminosities than expected from their UV-based SFR. At the current sensitivity, it is unclear whether the majority of these sources are intrinsically bright [C ii] emitters, or spurious sources. If only one of our line candidates was real (a scenario greatly favored by our statistical analysis), we find a source density for [C ii] emitters at 6 < z < 8 that is significantly higher than predicted by current models and some extrapolations from galaxies in the local universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Approximate Latent Factor Algorithm for Scenario Selection and Weighting in Transmission Expansion Planning

One major difficulty in transmission expansion planning is selecting the representative scenarios to use to evaluate candidate transmission networks. The variability in demand and renewable generation makes the inclusion of several scenarios critical when calculating reliability and cost, but including too many scenarios in an optimization is computationally intractable. To reduce the number of representative operating conditions needed to obtain an accurate approximation of the system, we propose a method rooted in multivariate statistics that exploits the latent correlative structure between different scenarios and network configurations. The proposed algorithm includes an objective and rigorous way to select a subset of scenarios that provide as much information about the system as possible, and a method to accurately approximate the system cost from that scenario subset. The result is a set of scenarios and weights that are easily incorporated into traditional transmission expansion planning formulations. We apply this to a 312-bus WECC model with 8,736 distinct operating conditions. The transmission plans found with the proposed method are more reliable and have a lower total cost than those from other scenario reduction techniques, as well as a smaller error between the expected system performance from the optimization objective and the actual system performance.

42 ENGINEERING↗
DOE OSTI2023

Study of the muon decay-in-flight in the τ - → μ - ν ¯ μ ν τ decay to measure the Michel parameter ξ '

We present the first measurement of the Michel parameter ξ' in the $\tau$ - → μ¯ $\overline{v}$ μ v $\tau$ decay using the full data sample of 988 fb -1 collected by the Belle detector operating at the KEKB asymmetric energy e + ⁢e - collider. The method is based on the reconstruction of the μ¯ → e⁢¯$\overline{v}$ e v μ decay-in-flight in the Belle central drift chamber and relies on the correlation between muon spin and its daughter electron momentum. We study the main sources of the background that can imitate the signal decay, such as kaon and pion decays-in-flight and charged particle scattering on the detector material. Highly efficient methods of their suppression are developed and applied to select 165 signal-candidate events. We obtain ξ' = 0.22±0.94±0.42 where the first uncertainty is statistical, and the second one is systematic. The result is in agreement with the Standard Model prediction of ξ' = 1.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

3013 Inner Can Lid Leak Test System Development

Contained in this report is a description of the 3013 inner container lid leak detection system, a listing of the data collected to validate the system and a statistical analysis of collected data. The 3013 Container Surveillance Program provides assessment criteria and evaluates 3013 containers selected from the storage inventory for potential degradation mechanisms. The 3013 outer container is the boundary credited to prevent release of material to the environment. The integrity of the outer container is only at risk if the inner container loses its seal and allows corrosive gases to diffuse into the outer container. To date, the determination of potential outer container exposure to corrosive gases has been through comparison of the gas analysis of the annular space and the inner container. If the two volumes have the same gas composition and pressure, then the inner container may have leaked. The leak detection system described in this report will provide a direct measurement of the integrity of the inner container, and if approved, will provide for the elimination of gas analysis. The inner container lid leak testing system consists of two basic parts: the Agilent leak testing instrument and the leak test fixture. The test fixture base provides the connection between the leak test instrument and the test sample. This connection allows helium to flow into the leak detector when a leak path exists in the test sample allowing leak measurement to be performed. The tests reported here were conducted in a cold lab using a configuration very similar, but not identical to, the configuration anticipated when installed in a glove box. A total of sixty-five leak rate measurements were made on 10 containers and the data is included in the report. The data analysis shows that the leak detection system can identify leaks in the lid, including the weld and heat affected zone of 3013 inner containers, during destructive examination. The measurements taken support that a 3013 IC lid with a leak rate value greater than 2.0 x 10 -7 atm cc/sec will be identified using the leak test system prior to introduction into a glove box. These results from the baseline for future tests of the leak test system after it is installed in the glove box for use as part of surveillance DE.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

The Role of Viscosity in Causing the Plasma Poloidal Motion in Magnetic Clouds

An interesting phenomenon, plasma poloidal motion, has been found in many magnetic clouds (MCs), and viscosity has been proposed as a possible mechanism. However, it is not clear how significant the role of viscosity is in generating such motion. In this paper, we conduct a statistical study of the MCs detected by the Wind spacecraft during 1995–2012. It is found that, for 19% of all the studied MCs (186), the poloidal velocities of the MC plasma near the MC boundaries are well correlated with those of the corresponding ambient solar wind plasma. A non-monotonic increase from inner to outer MCs suggests that the viscosity does play a role, albeit weak, on the poloidal motion in the MC statistically. The possible dependence on the solar wind parameters is then studied in detail for the nine selected crossings, which represent the viscosity characteristic. There is an evident negative correlation between the viscosity and the density, a weak negative correlation between the viscosity and the turbulence strength, and no clear correlation between the viscosity and the temperature.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1974

An optimized buffer controlled data compression system

The digital data compression system considered uses a buffer controlled aperture algorithm which minimizes the mean-squared error between the reconstructed receiver output and transmitter input. The data compression technique selected is based on the zero-order floating aperture prediction rule. It is assumed that the statistics of the input data are initially uniformly distributed, stationary, and first-order Markov. The problem is solved for stationary data. An approach is presented for extending the results to slowly varying uniformly distributed nonstationary Markov data.

Dosik, P. H.↗
NASA NTRS1976

Closure and ratio correlation analysis of lunar chemical and grain size data

Major element and major element plus trace element analyses were selected from the lunar data base for Apollo 11, 12 and 15 basalt and regolith samples. Summary statistics for each of the six data sets were compiled, and the effects of closure on the Pearson product moment correlation coefficient were investigated using the Chayes and Kruskal approximation procedure. In general, there are two types of closure effects evident in these data sets: negative correlations of intermediate size which are solely the result of closure, and correlations of small absolute value which depart significantly from their expected closure correlations which are of intermediate size. It is shown that a positive closure correlation will arise only when the product of the coefficients of variation is very small (less than 0.01 for most data sets) and, in general, trace elements in the lunar data sets exhibit relatively large coefficients of variation.

Butler, J. C.↗
NASA NTRS1977

On the alignment of plasma anisotropies and the magnetic field direction in the solar wind

One year's Imp 6 solar wind plasma and magnetic field data are examined to determine whether anisotropies in particle velocity distributions are aligned with the measured interplanetary magnetic field vector. Alignment of components in the analysis plane was generally found to be excellent whenever plasma parameter magnitudes were larger than determination uncertainties, although some spread exists (typical rms approximately equal to 10 deg). By assuming cylindrical symmetry about the simultaneously measured magnetic field vector during the 1-year interval under study, three-dimensional values of selected solar wind plasma thermal parameters were constructed from the two-dimensional plasma measurements, and the statistical properties of their distributions have been tabulated.

Asbridge, J. R.↗
NASA NTRS2013

The Galex Time Domain Survey. I. Selection And Classification of Over a Thousand Ultraviolet Variable Sources

We present the selection and classification of over a thousand ultraviolet (UV) variable sources discovered in approximately 40 deg(exp 2) of GALEX Time Domain Survey (TDS) NUV images observed with a cadence of 2 days and a baseline of observations of approximately 3 years. The GALEX TDS fields were designed to be in spatial and temporal coordination with the Pan-STARRS1 Medium Deep Survey, which provides deep optical imaging and simultaneous optical transient detections via image differencing. We characterize the GALEX photometric errors empirically as a function of mean magnitude, and select sources that vary at the 5 sigma level in at least one epoch. We measure the statistical properties of the UV variability, including the structure function on timescales of days and years. We report classifications for the GALEX TDS sample using a combination of optical host colors and morphology, UV light curve characteristics, and matches to archival X-ray, and spectroscopy catalogs. We classify 62% of the sources as active galaxies (358 quasars and 305 active galactic nuclei), and 10% as variable stars (including 37 RR Lyrae, 53 M dwarf flare stars, and 2 cataclysmic variables). We detect a large-amplitude tail in the UV variability distribution for M-dwarf flare stars and RR Lyrae, reaching up to absolute value(Δm) = 4.6 mag and 2.9 mag, respectively. The mean amplitude of the structure function for quasars on year timescales is five times larger than observed at optical wavelengths. The remaining unclassified sources include UV-bright extragalactic transients, two of which have been spectroscopically confirmed to be a young core-collapse supernova and a flare from the tidal disruption of a star by dormant supermassive black hole. We calculate a surface density for variable sources in the UV with NUV less than 23 mag and absolute value(Δm) greater than 0.2 mag of approximately 8.0, 7.7, and 1.8 deg(exp −2) for quasars, active galactic nuclei, and RR Lyrae stars, respectively. We also calculate a surface density rate in the UV for transient sources, using the effective survey time at the cadence appropriate to each class, of approximately 15 and 52 deg(exp −2 yr−1 for M dwarfs and extragalactic transients, respectively.

Gezari, S.↗
NASA NTRS2018

Follow-up Imaging of Disk Candidates from the Disk Detective Citizen Science Project: New Discoveries and False Positives in WISE Circumstellar Disk Surveys

The Disk Detective citizen science project aims to find new stars with excess 22 m emission from circumstellar dust in the All WISE data release from the Wide-field Infrared Survey Explorer. We evaluated 261 Disk Detective objects of interest with imaging with the Robo-AO adaptive optics instrument on the 1.5 m telescope at Palomar Observatory and with RetroCam on the 2.5 m du Pont Telescope at Las Campanas Observatory to search for background objects at 0 15–12 separations from each target. Our analysis of these data leads us to reject 7% of targets. Combining this result with statistics from our online image classification efforts implies that at most7.9%±0.2% of All WISE-selected infrared excesses are good disk candidates. Applying our false-positive rates to other surveys, we find that the infrared excess searches of McDonald et al. and Marton et al. all have false-positiverates >70%. Moreover, we find that all 13 disk candidates in Theissen & West with W4 signal-to-noise ratio >3are false positives. We present 244 disk candidates that have survived vetting by follow-up imaging. Of these,213 are newly identified disk systems. Twelve of these are candidate members of comoving pairs based on Gaia astrometry, supporting the hypothesis that warm dust is associated with binary systems. We also note the discovery of 22 m excess around two known members of the Scorpius–Centaurus association, and we identifyknown disk host WISEA J164540.79-310226.6 as a likely Sco-Cen member. Thirty of these disk candidates arecloser than 125 pc (including 26 debris disks), making them good targets for both direct-imaging exoplanetsearches.

Wide-field Infrared Survey Explorer↗
DOE OSTI2020

CODEX weak lensing mass catalogue and implications on the mass–richness relation

The COnstrain Dark Energy with X-ray clusters (CODEX) sample contains the largest flux limited sample of X-ray clusters at 0.35 < z < 0.65. It was selected from ROSAT data in the 10 000 square degrees of overlap with BOSS, mapping a total number of 2770 high-z galaxy clusters. We present here the full results of the CFHT CODEX programme on cluster mass measurement, including a reanalysis of CFHTLS Wide data, with 25 individual lensing-constrained cluster masses. We employ lensfit shape measurement and perform a conservative colour–space selection and weighting of background galaxies. Using the combination of shape noise and an analytic covariance for intrinsic variations of cluster profiles at fixed mass due to large-scale structure, miscentring, and variations in concentration and ellipticity, we determine the likelihood of the observed shear signal as a function of true mass for each cluster. We combine 25 individual cluster mass likelihoods in a Bayesian hierarchical scheme with the inclusion of optical and X-ray selection functions to derive constraints on the slope α, normalization β, and scatter σln λ|μ of our richness–mass scaling relation model in log-space: ${\langle {\rm In}\,\, \lambda\!\!\mid\!\!\mu\rangle = \alpha\mu + \beta,} $ with μ = ln (M 200c /M piv ), and M piv = 10 14.81 M ⊙ . We find a slope $\alpha = 0.49^{+0.20}_{-0.15}$, normalization $\exp (\beta) = 84.0^{+9.2}_{-14.8}$, and $\sigma _{\ln \lambda | \mu } = 0.17^{+0.13}_{-0.09}$ using CFHT richness estimates. In comparison to other weak lensing richness–mass relations, we find the normalization of the richness statistically agreeing with the normalization of other scaling relations from a broad redshift range (0.0 < z < 0.65) and with different cluster selection (X-ray, Sunyaev–Zeldovich, and optical).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Characterization and differentiation of aluminum powders used in improvised explosive devices – Part 1: Proof of concept of the utility of particle micromorphometry

Abstract Aluminum (Al) powders are commonly used in improvised explosive devices as metallic fuels, a component of explosive mixtures. These powders can be obtained readily from industrial‐scale and consumer products, and produced using unsophisticated “kitchen chemistry” techniques. This research demonstrates the potential of automated particle micromorphometry for comparisons between known source and questioned Al powders recovered from IEDs, as well as for insight into the method of Al powder manufacture. Al powder samples were obtained from legitimate manufacturers, and 56 samples were produced “in‐house” from Al‐containing spray paints and ball‐milled Al foils. Transmitted light microscope images of Al powder particles were acquired using an automated stage with automated z‐focus; 17 size and shape parameters were measured for all particles. Approximately 37,000–2,500,000 particles/sample were analyzed using an open‐source statistical package with customized code. Dimensionality reduction was required for processing the large datasets: eight of the 17 measured variables were selected based on inspection of the correlation matrix. Data from four subsamples from each of the 56 samples produced using “in‐house” methods were analyzed using ANOVA to assess the within‐ and between‐sample variation. High within‐sample variation was noted; however, ANOVA and post‐hoc Tukey's honestly significant difference (HSD) tests demonstrated that the between‐sample variation was substantially larger than the within‐sample variation. Each sample could be differentiated from all other samples in the test set. Future experiments will focus on ways to reduce the within‐sample variation, and additional statistical and microanalytical methods to classify sources and confidently constrain the method of Al powder manufacture.

Baldaino, JenaMarie↗