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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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Compilation describes characteristics of truncated and censored samples, and presents six illustrations of practical use of tables in computing mean and variance estimates for normal distribution using selected samples.
Important factors to consider when optimizing Lithium-ion (Li-ion) battery thermal management systems, from a battery safety perspective, include the total energy released during a single cell thermal runaway (TR) event and the fraction of the total energy that is released through the cell casing versus through the ejecta material. A fractional thermal runaway calorimeter (FTRC) was used to examine the TR behavior of the following 18650-format Li-ion cells: (1) Molicel 18650-J, (2) LG 18650-HG2, (3) Samsung 18650-30Q, (4) 3.35 Ah LG 18650 test cell, (5) Sony 18650-VC7, and (6) LG 18650-MJ1. These cells were intentionally selected to represent a variety of manufacturers, chemistries, capacities, and safety features. Because of the large number of random and non-random variables associated with the FTRC results, a linear regression model, developed using engineering statistical methods, was utilized to provide final interpretation of the TR behavior for each cell type and design variable combination.
Moisture carryover (MCO) is modeled in the General Electric Type-4 boiling water reactor (BWR) using machine-learning methods and data from operating plants. Understanding MCO and the conditions that give rise to an elevated value is important since excessive MCO can damage critical turbine components, can result in elevated dose levels to on-site personnel, and can interfere with late-cycle power management. The analysis of MCO takes into account simplifying reactor symmetries and important geometric dependencies. The plant data are taken from several reactors and were collected over multiple years and multiple fuel cycles. A brief description of the origin of MCO in U.S. BWR plants is given. A machine-learning model is constructed from the data using applicable algorithms and data-reduction techniques. Matching model complexity with available data is one of the more challenging machine-learning tasks. Too many features and too little data will lead to overfitting. The data for each fuel cycle included over 6876 original features, 9 for each fuel bundle. Two approaches are used to reduce the data set into a manageable number of features. The first was an engineering analysis that resulted in the selection of steam quality Q and steam liquid phase velocity V L as the main features driving MCO. Using a Q and a V L for each fuel bundle gives 1528 Q and a V L feature describing the reactor behavior. An analysis of different functional forms of these two variables led to the actual inputs to the neural network model. The second approach involved the use of statistical techniques such as Pearson’s correlation and k-means analysis. The identified groupings of bundles behaved similarly. Treating each grouping as a single feature further reduced the input variable set to a manageable number. Here, a model selection criterion is proposed, and results are presented along with a discussion of related issues.
We present an extension to a Sunyaev–Zel’dovich Effect (SZE) selected cluster catalogue based on observations from the South Pole Telescope (SPT); this catalogue extends to lower signal to noise than the previous SPT–SZ catalogue and therefore includes lower mass clusters. Optically derived redshifts, centres, richnesses, and morphological parameters together with catalogue contamination and completeness statistics are extracted using the multicomponent matched filter (MCMF) algorithm applied to the S/N > 4 SPT–SZ candidate list and the Dark Energy Survey (DES) photometric galaxy catalogue. The main catalogue contains 811 sources above S/N = 4, has 91 per cent purity, and is 95 per cent complete with respect to the original SZE selection. It contains in total 50 per cent more clusters and twice as many clusters above z = 0.8 in comparison to the original SPT-SZ sample. The MCMF algorithm allows us to define subsamples of the desired purity with traceable impact on catalogue completeness. As an example, we provide two subsamples with S/N > 4.25 and S/N > 4.5 for which the sample contamination and cleaning-induced incompleteness are both as low as the expected Poisson noise for samples of their size. The subsample with S/N > 4.5 has 98 per cent purity and 96 per cent completeness and is part of our new combined SPT cluster and DES weak-lensing cosmological analysis. We measure the number of false detections in the SPT-SZ candidate list as function of S/N, finding that it follows that expected from assuming Gaussian noise, but with a lower amplitude compared to previous estimates from simulations.
Urban areas are known to modify the spatial pattern of precipitation climatology. Existing observational evidence suggests that precipitation can be enhanced downwind of a city. Among the proposed mechanisms, the thermodynamic and aerodynamic processes in the urban lower atmosphere interact with the meteorological conditions and can play a key role in determining the resulting precipitation patterns. In addition, these processes are influenced by urban form, such as the impervious surface extent. This study aims to unravel how different urban forms impact the spatial patterns of precipitation climatology under different meteorological conditions. We use the Multi-Radar Multi-Sensor quantitative precipitation estimation data products and analyze the hourly precipitation maps for 27 selected cities across the continental United States from the years 2015–2021 summer months. Results show that about 80% of the studied cities exhibit a statistically significant downwind enhancement of precipitation. Additionally, we find that the precipitation pattern tends to be more spatially clustered in intensity under higher wind speed; the location of radial precipitation maxima is located closer to the city center under low background winds but shifts downwind under high wind conditions. The magnitude of downwind precipitation enhancement is highly dependent on wind directions and is positively correlated with the city size for the south, southwest, and west directions. This study presents observational evidence through a cross-city analysis that the urban precipitation pattern can be influenced by the urban modification of atmospheric processes, providing insight into the mechanistic link between future urban land-use change and hydroclimates.
Pentaquark states have been extensively investigated theoretically in the context of the constituent quark model. In this paper results of an experimental search for pentaquarks in the Ξ – π – , Ξ – π + , Ξ ¯ + π – and Ξ ¯ + π + invariant mass spectra in proton-proton interactions at s = 17.3 GeV are presented. Previous possible evidence from the NA49 collaboration of the existence of a narrow Ξ – π – baryon resonance in p + p interactions is not confirmed with almost 10 times greater event statistics. The search was performed using the NA61/SHINE detector which reuses the main components of the NA49 apparatus. No signal was observed with either the selection cuts of NA49 or newly optimized cuts.
Material detection algorithms used in hyperspectral data processing are computationally efficient but can produce relatively high numbers of false positives. Material identification performed as a secondary processing step on detected pixels can help mitigate false positives. A material identification processing chain for longwave infrared hyperspectral data of solid materials collected from airborne platforms is presented. The algorithms utilize unwhitened radiance data and Nelder–Meade numerical optimization to estimate the temperature, humidity, and ozone levels of the atmospheric profile. Pixel unmixing is done using constrained linear regression and Bayesian information criteria for model selection. The resulting identification product includes an optimal atmospheric profile and a full radiance material model that includes material temperature, abundance values, and several fit statistics. A logistic regression method utilizing the model parameters to improve identification is also presented. Furthermore, several examples are provided using modeled data at several noise levels.
Genes belonging to the same functional group may include numerous and variable gene sequences, making characterizing and quantifying difficult. Therefore, high-throughput design tools are needed to simultaneously create primers for improved quantification of target genes. We developed MetaFunPrimer, a bioinformatic pipeline, to design primers for numerous genes of interest. This tool also enables gene target prioritization based on ranking the presence of genes in user-defined references, such as environment-specific metagenomes. Given inputs of protein and nucleotide sequences for gene targets of interest and an accompanying set of reference metagenomes or genomes, MetaFunPrimer generates primers for ranked genes of interest. To demonstrate the usage and benefits of MetaFunPrimer, a total of 78 primer pairs were designed to target observed ammonia monooxygenase subunit A (amoA) genes of ammonia-oxidizing bacteria (AOB) in 1,550 publicly available soil metagenomes. We demonstrate computationally that these amoA-AOB primers can cover 94% of the amoA-AOB genes observed in the 1,550 soil metagenomes compared with a 49% estimated coverage by previously published primers. Finally, we verified the utility of these primer sets in incubation experiments that used long-term nitrogen fertilized or unfertilized soils. High-throughput quantitative PCR (qPCR) results and statistical analyses showed significant differences in relative quantification patterns between the two soils, and subsequent absolute quantifications also confirmed that target genes enumerated by six selected primer pairs were significantly more abundant in the nitrogen-fertilized soils. This new tool gives microbial ecologists a new approach to assess functional gene abundance and related microbial community dynamics quickly and affordably.
Available are independent observations (continuous data) that are believed to be a random sample. Desired are distribution-free confidence intervals and significance tests for the population median. However, there is the possibility that either the smallest or the largest observation is an outlier. Then, use of a procedure for rejection of an outlying observation might seem appropriate. Such a procedure would consider that two alternative situations are possible and would select one of them. Either (1) the n observations are truly a random sample, or (2) an outlier exists and its removal leaves a random sample of size n-1. For either situation, confidence intervals and tests are desired for the median of the population yielding the random sample. Unfortunately, satisfactory rejection procedures of a distribution-free nature do not seem to be available. Moreover, all rejection procedures impose undesirable conditional effects on the observations, and also, can select the wrong one of the two above situations. It is found that two-sided intervals and tests based on two symmetrically located order statistics (not the largest and smallest) of the n observations have this property.
The author has identified the following significant results. Surface water statistics using data obtained by supporting aircraft were generated. Signature extraction and refinement preliminary to wetland and associated upland vegetation recognition were accomplished, using a selected portion of the aircraft data. Final classification mapping and analysis of surface water trends will be accomplished.
The justification for describing a spray by treating drop velocity as a random variable on an equal statistical basis with drop size was studied experimentally. A double exposure technique using fluorescent drop photography was used to make size and velocity measurements at selected locations in a steady ethanol spray formed by a swirl atomizer. The size velocity data were categorized to construct bivariate spray density functions to describe the spray immediately after formation and during downstream propagation. Bimodal density functions were formed by environmental interaction during downstream propagation. Large differences were also found between spatial mass density and mass flux size distribution at the same location.
The effects of random member length errors on the surface accuracy, the defocus, and the residual, internal loads of tetrahedral truss antenna reflectors have been studied analytically. The analytical procedure involves performing multiple, deterministic finite element structural analyses for a particular truss. For each analysis, the normally distributed, random member length errors are selected by random number generator. A best fit paraboloid analysis is used to determine a root mean square error and defocus from each analysis. The statistical properties of these quantities as well as the internal loads are calculated from the results of many independent analyses. Results indicate that the number of members in a tetrahedral truss antenna of a given diameter has a significant effect on surface accuracy, defocus and internal loads. It was also found that the member axial stiffnesses and antenna focal length have a very small effect on reflector surface accuracy.
Advanced Earth Orbital Spacecraft System (AEOSS) enables users to project the requried power, weight, and cost for a generic earth-orbital spacecraft system. These variables are calculated on the component and subsystem levels, and then the system level. The included six subsystems are electric power, thermal control, structure, auxillary propulsion, attitude control, and communication, command, and data handling. The costs are computed using statistically determined models that were derived from the flown spacecraft in the past and were categorized into classes according to their functions and structural complexity. Selected design and performance analyses for essential components and subsystems are also provided. AEOSS has the feature permitting a user to enter known values of these parameters, totally and partially, at all levels. All information is of vital importance to project managers of subsystems or a spacecraft system. AEOSS is a specially tailored software coded from the relational database program of the Acius; 4th Dimension with a Macintosh version. Because of the licensing agreement, two versions of the AEOSS documents were prepared. This version AEOSS Design Guide, is for users to exploit the full capacity of the 4th Dimension. It is for a user who wants to alter or expand the program structures, the program statements, and the program procedures. The user has to possess a 4th Dimension first.
Advanced earth orbital spacecraft system (AEOSS) enables users to project the required power, weight, and cost for a generic earth-orbital spacecraft system. These variables are calculated on the component and subsystem levels, and then the system level. The included six subsystems are electric power, thermal control, structure, auxiliary propulsion, attitude control, and communication, command, and data handling. The costs are computed using statistically determined models that were derived from the flown spacecraft in the past and were categorized into classes according to their functions and structural complexity. Selected design and performance analyses for essential components and subsystems are also provided. AEOSS has the feature permitting a user to enter known values of these parameters, totally and partially, at all levels. All information is of vital importance to project managers of subsystems or a spacecraft system. AEOSS is a specially tailored software coded from the relational database program of the Acius' 4th Dimension with a Macintosh version. Because of the licensing agreements, two versions of the AEOSS documents were prepared. This version, AEOSS Runtime Manual, is permitted to be distributed with a finite number of the restrictive 4D Runtime version. It can perform all contained applications without any programming alterations.
The TEAMS model analyzer is a supporting tool developed to work with models created with TEAMS (Testability, Engineering, and Maintenance System), which was developed by QSI. In an effort to reduce the time spent in the manual process that each TEAMS modeler must perform in the preparation of reporting for model reviews, a new tool has been developed as an aid to models developed in TEAMS. The software allows for the viewing, reporting, and checking of TEAMS models that are checked into the TEAMS model database. The software allows the user to selectively model in a hierarchical tree outline view that displays the components, failure modes, and ports. The reporting features allow the user to quickly gather statistics about the model, and generate an input/output report pertaining to all of the components. Rules can be automatically validated against the model, with a report generated containing resulting inconsistencies. In addition to reducing manual effort, this software also provides an automated process framework for the Verification and Validation (V&V) effort that will follow development of these models. The aid of such an automated tool would have a significant impact on the V&V process.
The new JPL Small-Body Automatic Mission-Design System comprises two main elements: a database of pre-computed mission options to all known asteroids and comets, and an interactive web interface that can be used to design transfers to each small body. The system is kept current with the JPL Small Body orbit catalog, is publicly available, and can be accessed from the JPL Solar System Dynamics Group website. The missions computed by the automatic system are impulsive. However, a low-thrust v estimate is also provided. The database of pre-computed missions can be filtered to find potential targets with certain orbital and physical properties, and that meet specific mission-design constraints. In addition to describing the system in detail, this paper presents empirical analytic expressions to approximate the impulsive v requirements of missions to comets and to each family of asteroids, obtained by fitting statistical data. To show how the interactive interface works, we consider mission options to asteroid 99942 Apophis. We also include optimal mission opportunities to other selected small bodies.
We present an analysis of the statistical properties of Mg II absorbers found in the spectra of 56 intrinsically faint, steep-spectrum radio quasars. We observe for the first time a significant excess of associated Mg II absorbers over the number expected from cosmologically distributed absorbers. This result is in contrast to previous Mg II surveys in which the QSOs were optically selected. This distinction is similar to the result for associated C IV absorbers, in which intrinsically faint, steep-spectrum quasars show excess associated absorption and intrinsically bright QSOs (both radio-loud and radio-quiet) do not show an excess. From our spectra a statistically complete list of absorption lines is derived, and we find 29 Mg II absorbers, 18 of which have not been previously reported. We also determine several characteristics of the quasar emission lines in our spectra. The Mg II absorber distribution as a function of redshift and equivalent width is calculated both for our sample alone and from our sample combined with spectra from other surveys. For the redshift distribution n(z) = n(1 + z)(exp gamma), we obtain, using the combined sample, the values gamma = 1.11 +/- 0.46 for W(min) = 0.6 A and gamma = 2.47 +/- 0.68 for W(min) = 1.0 A. We find that the distribution fo strong absorbers is inconsistent with no evolution at a confindence level between 2.2 and 2.9 sigma, depending on the deceleration parameter q(sub 0). The deviation from no evolution is similar to what had been previously reported.
Implementation, test, and evaluation of selective dissemination system for NASA scientific and technical information