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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Vortex Generators in a Streamline-Traced, External-Compression Supersonic Inlet

Vortex generators within a streamline-traced, external-compression supersonic inlet for Mach 1.66 were investigated to determine their ability to increase total pressure recovery and reduce total pressure distortion. The vortex generators studied were rectangular vanes arranged in counter-rotating and co-rotating arrays. The vane geometric factors of interest included height, length, spacing, angle-of-incidence, and positions upstream and downstream of the inlet terminal shock. The flow through the inlet was simulated numerically through the solution of the steady-state, Reynolds-averaged Navier-Stokes equations on multi-block, structured grids using the Wind-US flow solver. The vanes were simulated using a vortex generator model. The inlet performance was characterized by the inlet total pressure recovery and the radial and circumferential total pressure distortion indices at the engine face. Design of experiments and statistical analysis methods were applied to quantify the effect of the geometric factors of the vanes and search for optimal vane arrays. Co-rotating vane arrays with negative angles-of-incidence positioned on the supersonic diffuser were effective in sweeping low-momentum flow from the top toward the sides of the subsonic diffuser. This distributed the low-momentum flow more evenly about the circumference of the subsonic diffuser and reduced distortion. Co-rotating vane arrays with negative angles-of-incidence or counter-rotating vane arrays positioned downstream of the terminal shock were effective in mixing higher-momentum flow with lower-momentum flow to increase recovery and decrease distortion. A strategy of combining a co-rotating vane array on the supersonic diffuser with a counter-rotating vane array on the subsonic diffuser was effective in increasing recovery and reducing distortion.

computational fluid dynamics↗
DOE OSTI2020

An improved method for direct incident solar radiation calculation from hourly solar insolation data in building energy simulation

Solar radiation considerably influences the energy consumption of buildings and the power production of building integrated photovoltaic (BIPV) systems. Hourly solar insolation (Wh/m 2 ), represented as the amount of solar irradiance collected on the ground during a 1-h period, is the most common solar radiation data available and widely used in weather files applied in building energy modeling programs (BEMPs). Because the solar beam and position vary over time, the use of hourly insolation data as the input might result in errors in the estimation of the direct incident solar radiation on a particular surface. In this study, methods used in BEMPs for direct incident solar radiation calculations are first analyzed, and an improved method adopting a new algorithm for estimating the solar irradiance is proposed. Furthermore, the algorithm assumes that the solar irradiance changes linearly within a 1-h period and can be estimated based on the solar irradiance at the half clock and slope. The collected direct normal solar irradiance data of 2016 from eight solar radiation stations in China were used to demonstrate the proposed method and evaluate its performance by comparing the results with those from three conventional methods used in BEMPs along with the ground truth measurements. In addition, in this study, factors affecting the accuracy of the calculation results are explored. The results of the estimated direct incident solar radiation show that the proposed method achieves the best accuracy, followed by the methods used in DOE-2, EnergyPlus, and DeST. The proposed method guarantees that the hourly direct solar insolation will remain the same and reflects the variation in the direct solar irradiance across a 1-h time frame. The proposed method can be adopted in BEMPs to improve the accuracy of the solar radiation calculation, thereby improving the accuracy of the simulated building performance and the BIPV production.

14 SOLAR ENERGY↗
DOE OSTI2026

Energy Emissions Accounting Methods Can Determine Whether Direct Air Capture with Storage Achieves Net Removal

The voluntary carbon market within the United States has expanded rapidly in recent years and enabled private companies and other organizations to provide revenue streams to carbon dioxide removal (CDR) technologies. For a CDR technology to participate in the voluntary carbon market (VCM), the emissions associated with constructing and operating the technology must be less than the CO 2 captured from the atmosphere. Assessing the extent to which this is true for direct air capture with storage (DACS), a relatively energy-intensive CDR technology, strongly depends on the accounting method used to assess the emissions intensity of purchased energy. We simulate the hourly weather-dependent operation of sorbent- and solvent-based DACS in California, Louisiana, Texas, and Wyoming, representing a wide range of local weather and electric and natural gas grid compositions. In all cases, the single most important emissions accounting decision is the method used to estimate the emissions intensity of purchased grid electricity, which varies the calculated net removal by −1049% to +108%. All other factors influencing net removal introduce a variation of at most ±14%. No electricity emissions accounting method is universally conservative across all scenarios, and none is objectively more accurate. High-spatiotemporal-resolution, high-quality, publicly available data sets and models for electricity emissions accounting do not currently exist and are urgently needed to enable standardization of emissions accounting methods to more accurately determine the true emissions impacts of DACS and other energy-intensive facilities.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Prediction of three sigma maximum dispersed density for aerospace applications

Free molecular heating (FMH) is caused by the transfer of energy during collisions between the upper atmosphere molecules and a space vehicle. The dispersed free molecular heating on a surface is an important constraint for space vehicle thermal analyses since it can be a significant source of heating. To reduce FMH to a spacecraft, the parking orbit is often designed to a higher altitude at the expense of payload capability. Dispersed FMH is a function of both space vehicle velocity and atmospheric density, however, the space vehicle velocity variations are insignificant when compared to the atmospheric density variations. The density of the upper atmosphere molecules is a function of altitude, but also varies with other environmental factors, such as solar activity, geomagnetic activity, location, and time. A method has been developed to predict three sigma maximum dispersed density for up to 15 years into the future. This method uses a state-of-the-art atmospheric density code, MSIS 86, along with 50 years of solar data, NASA and NOAA solar activity predictions for the next 15 years, and an Aerospace Corporation correlation to account for density code inaccuracies to generate dispersed maximum density ratios denoted as 'K-factors'. The calculated K-factors can be used on a mission unique basis to calculate dispersed density, and hence dispersed free molecular heating rates. These more accurate K-factors can allow lower parking orbit altitudes, resulting in increased payload capability.

Charles, Terri L.↗
NASA NTRS1994

Microbial community structure at the U.S.-Joint Global Ocean Flux Study Station ALOHA: Inverse methods for estimating biochemical indicator ratios

Modeling biogeochemical fluxes in the marine plankton requires the application of factors for extrapolation of biomass indicators measured in the field (chlorophyll a, adenosine triphosphate, bacterial counts) to biomass carbon or nitrogen. These are often inferred from culture studies and are poorly constrained for natural populations. At least squares inverse method with a simple linear model constrains the values of several common indicator ratios, giving self-consistent solutions that provide useful information about the structure of the microbial community at our North Pacific Ocean study site (Station ALOHA (A Long-term Oligotrophic Habitat Assessment)). These results indicate that the fraction of the microbial biomass that is autotrophic (pigmented) is greater in the mixed layer than at the deep chlorophyll maximum layer and that heterotrophic bacteria are a significant but not necessarily predominant component of the microbial community in the euphotic zone.

Christian, James R.↗
DOE OSTI2024

Agricultural practices influence soil microbiome assembly and interactions at different depths identified by machine learning

Agricultural practices affect soil microbes which are critical to soil health and sustainable agriculture. To understand prokaryotic and fungal assembly under agricultural practices, we use machine learning-based methods. We show that fertility source is the most pronounced factor for microbial assembly especially for fungi, and its effect decreases with soil depths. Fertility source also shapes microbial co-occurrence patterns revealed by machine learning, leading to fungi-dominated modules sensitive to fertility down to 30 cm depth. Tillage affects soil microbiomes at 0-20 cm depth, enhancing dispersal and stochastic processes but potentially jeopardizing microbial interactions. Cover crop effects are less pronounced and lack depth-dependent patterns. Machine learning reveals that the impact of agricultural practices on microbial communities is multifaceted and highlights the role of fertility source over the soil depth. Machine learning overcomes the linear limitations of traditional methods and offers enhanced insights into the mechanisms underlying microbial assembly and distributions in agriculture soils.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Application of a Chemical Index to Aerosol Mass Spectrometry: Delta Plots and Functional Group Distributions

A better understanding of the chemical properties of organic aerosol (OA) particles will improve our ability to characterize their sources and predict their lifetime. The high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is widely used to measure OA in real time using thermal vaporization followed by electron ionization (EI). EI creates fragment ions that can be assigned to functional groups using delta analysis, a method of classifying mass spectra according to the presence of different chemically related ion series. In this study, we demonstrate the application of delta analysis to characterize molecular structures using a new visualization method. We also use delta analysis to quantify the functional group distribution with an average absolute error of ∼5–6% for individual standard molecules, comparable to the error observed for OA mixtures from biomass and coal combustion fit with Fourier transform infrared spectroscopy. Finally, we apply delta functional group analysis to AMS positive matrix factorization (PMF) factors across seven different field campaigns and find a similar composition across the more oxidized factors with about 55% acid and 26% alcohol groups. The analysis method described here can be applied to any HR-ToF-AMS data set to provide quantitative relative functional group distributions for OA mixtures.

aerosol↗
NASA NTRS1993

Review of the probabilistic failure analysis methodology and other probabilistic approaches for application in aerospace structural design

Probabilistic structural analyses and design methods are steadily gaining acceptance within the aerospace industry. The safety factor approach to design has long been the industry standard, and it is believed by many to be overly conservative and thus, costly. A probabilistic approach to design may offer substantial cost savings. This report summarizes several probabilistic approaches: the probabilistic failure analysis (PFA) methodology developed by Jet Propulsion Laboratory, fast probability integration (FPI) methods, the NESSUS finite element code, and response surface methods. Example problems are provided to help identify the advantages and disadvantages of each method.

Townsend, J.↗
NASA NTRS2003

Electrophoretic Deposition for Fabricating Microbatteries

An improved method of fabrication of cathodes of microbatteries is based on electrophoretic deposition. Heretofore, sputtering (for deposition) and the use of photoresist and liftoff (for patterning) have been the primary methods of fabricating components of microbatteries. The volume of active electrode material that can be deposited by sputtering is limited, and the discharge capacities of prior microbatteries have been limited accordingly. In addition, sputter deposition is slow. In contrast, electrophoretic deposition is much faster and has shown promise for increasing discharge capacities by a factor of 10, relative to those of microbatteries fabricated by prior methods.

West, William↗
DOE OSTI2020

Soft x-ray spectrum unfold of K-edge filtered x-ray diode arrays using cubic splines

Cubic spline interpolation is able to recover temporally and spectrally resolved soft x-ray flux from an array of K-edge filtered x-ray diodes without the need for a priori assumptions about the spectrum or the geometry of the emitting volume. The mathematics of the cubic spline interpolation is discussed in detail. The analytic nature of the cubic spline solution allows for analytical error propagation, and the method of calculating the error for radiation temperature, spectral power, and confidence intervals of the unfolded spectrally resolved flux is explained. An unfold of a blackbody model demonstrates the accuracy of the cubic spline unfold. Tests of cubic spline performance using spectrally convolved detailed atomic model simulation results have been performed to measure the method's ability to conserve spectral power to within a factor of 2 or better in line-dominated regimes. The unfold is also demonstrated to work when information from the x-ray diode array is limited due to high signal-to-noise ratios or lack of signal due to over-attenuation or over-filtration of the x-ray diode signal. Here, the robustness of the unfold with respect to background subtraction and raw signal processing, signal alignment between diode traces, limited signal information, and initial conditions is discussed. Results from an example analysis of a halfraum drive are presented to demonstrate the capabilities of the unfold in comparison with previously established methods.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Graph coarsening: from scientific computing to machine learning

Abstract The general method of graph coarsening or graph reduction has been a remarkably useful and ubiquitous tool in scientific computing and it is now just starting to have a similar impact in machine learning. The goal of this paper is to take a broad look into coarsening techniques that have been successfully deployed in scientific computing and see how similar principles are finding their way in more recent applications related to machine learning. In scientific computing, coarsening plays a central role in algebraic multigrid methods as well as the related class of multilevel incomplete LU factorizations. In machine learning, graph coarsening goes under various names, e.g., graph downsampling or graph reduction. Its goal in most cases is to replace some original graph by one which has fewer nodes, but whose structure and characteristics are similar to those of the original graph. As will be seen, a common strategy in these methods is to rely on spectral properties to define the coarse graph.

Chen, Jie↗
NASA NTRS2002

Uncertainties in Estimates of the Risks of Late Effects from Space Radiation

The health risks faced by astronauts from space radiation include cancer, cataracts, hereditary effects, and non-cancer morbidity and mortality risks related to the diseases of the old age. Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Within the linear-additivity model, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain a Maximum Likelihood estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including ISS, lunar station, deep space outpost, and Mar's missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time, and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative objective's, i.e., the number of days in space without exceeding a given risk level within well defined confidence limits.

Cucinotta, F. A.↗
NASA NTRS1991

High order filtering methods for approximating hyperbolic systems of conservation laws

The essentially nonoscillatory (ENO) schemes, while potentially useful in the computation of discontinuous solutions of hyperbolic conservation-law systems, are computationally costly relative to simple central-difference methods. A filtering technique is presented which employs central differencing of arbitrarily high-order accuracy except where a local test detects the presence of spurious oscillations and calls upon the full ENO apparatus to remove them. A factor-of-three speedup is thus obtained over the full-ENO method for a wide range of problems, with high-order accuracy in regions of smooth flow.

Lafon, F.↗
DOE OSTI2025

Hybridization capture sequencing for Vibrio spp. and associated virulence factors

ABSTRACT Proliferation ofVibriospp. in aquatic ecosystems is associated with climate change and, concomitantly, increased incidence of vibriosis. They are autochthonous to aquatic environments globally, but traditional metagenomic methods for detecting and typing pathogenicVibriospp. are challenged by their presence in relatively low abundance and ability to persist in a viable but nonculturable state. In the study reported here, hybridization capture sequencing (HCS) was employed to profile low-abundanceVibriospp. in environmental samples. The HCS panel targeted a family of molecular chaperones (CPN60) specific to 69Vibriospp. and 162Vibrio-specific virulence factors. This approach was evaluated in parallel with traditional whole-community shotgun sequencing in a metagenomic analysis of water and oyster samples collected from the Chesapeake Bay. In addition,Vibrio parahaemolyticusandVibrio vulnificusstrains isolated from the samples were subjected to whole-genome sequencing to determine the genetic characteristics of pathogenicVibriospp. circulating in an aquatic environment. HCS, employed to determine the incidence and characterization of specificVibriospp., yielded significantly greater metagenomic insight, notably a variety of otherVibriospp., including detection ofVibrio cholerae,Vibrio fluvialis, andVibrio aestuarianus, in addition toVibrio parahaemolyticusandVibrio vulnificus, and also important virulence factors not detectable using traditional molecular methods. Thus, pathogenicVibriospp. in aquatic ecosystems may be far more common than currently understood. It is concluded that environmental surveillance should include HCS, a valuable tool for the detection and characterization of pathogenic agents in aquatic ecosystems, notably vibrios. IMPORTANCE The increasing prevalence of pathogenicVibriospp. in aquatic ecosystems, driven by climate change, is closely linked to a rise in cholera and vibriosis cases, emphasizing the need for improved environmental surveillance. Vibrios are naturally occurring in aquatic environments globally, but traditional metagenomic methods for detecting and typing pathogenicVibriospp. are challenged by their presence in relatively low abundance and ability to persist in a viable but nonculturable state. In the study reported here, hybridization capture sequencing was employed to profile low-abundanceVibriospp. in metagenomic samples, namely water and oysters collected from the Chesapeake Bay. This approach was evaluated in parallel with traditional whole-community shotgun sequencing and whole-genome sequencing ofVibrio parahaemolyticusandVibrio vulnificusstrains isolated from the samples. Results suggest pathogenicVibriospp. in aquatic ecosystems may be far more common than currently understood, when multiple methods are considered for environmental surveillance.

Microbiology↗
DOE OSTI2023

Optimizing foreground mitigation for CMB lensing with combined multifrequency and geometric methods

Here, a key challenge for current and upcoming cosmic microwave background lensing measurements is their sensitivity to biases from extragalactic foregrounds, such as Sunyaev-Zel'dovich signals or cosmic infrared background emission. Several methods have been developed to mitigate these lensing foreground biases, dividing broadly into multifrequency cleaning approaches and modifications to the estimator geometry, but how to optimally combine these methods has not yet been explored in detail. In this paper, we examine which combination of lensing foreground mitigation strategies is best able to reduce the impact of foreground contamination for a Simons Observatory-like experiment while preserving maximal signal-to-noise. Although the optimal combination obtained depends on whether bias reduction or variance reduction is prioritized and on whether polarization data is used, generally, we find that combinations involving both geometric (profile hardening, source hardening, or shear) and multifrequency (symmetric cleaning) methods perform best. For lensing power spectrum measurements from temperature (polarization and temperature), our combined estimator methods are able to reduce the bias below σ/4 or 0.3% (0.1%), a factor of 16 (30) lower than the standard quadratic estimator bias, at a modest signal-to-noise cost of only 18% (12%). In contrast, single-method foreground-mitigation approaches struggle to reduce the bias to a negligible level below σ/2 without incurring a large noise penalty. For upcoming and current experiments, our combined methods therefore represent a promising approach for making lensing measurements with negligible foreground bias.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2015

Helium Mass Spectrometer Leak Detection: A Method to Quantify Total Measurement Uncertainty

In applications where leak rates of components or systems are evaluated against a leak rate requirement, the uncertainty of the measured leak rate must be included in the reported result. However, in the helium mass spectrometer leak detection method, the sensitivity, or resolution, of the instrument is often the only component of the total measurement uncertainty noted when reporting results. To address this shortfall, a measurement uncertainty analysis method was developed that includes the leak detector unit's resolution, repeatability, hysteresis, and drift, along with the uncertainty associated with the calibration standard. In a step-wise process, the method identifies the bias and precision components of the calibration standard, the measurement correction factor (K-factor), and the leak detector unit. Together these individual contributions to error are combined and the total measurement uncertainty is determined using the root-sum-square method. It was found that the precision component contributes more to the total uncertainty than the bias component, but the bias component is not insignificant. For helium mass spectrometer leak rate tests where unit sensitivity alone is not enough, a thorough evaluation of the measurement uncertainty such as the one presented herein should be performed and reported along with the leak rate value.

error analysis↗
DOE OSTI2021

Magnetotransport in semiconductors and two-dimensional materials from first principles

Here we demonstrate a first-principles method to study magnetotransport in materials by solving the Boltzmann transport equation (BTE) in the presence of an external magnetic field. Our approach employs ab initio electron-phonon interactions and takes spin-orbit coupling into account. We apply our method to various semiconductors (Si and GaAs) and two-dimensional (2D) materials (graphene) as representative case studies. The magnetoresistance, Hall mobility, and Hall factor in Si and GaAs are in very good agreement with experiments. In graphene, our method predicts a large magnetoresistance, consistent with experiments. Analysis of the steady-state electron occupations in graphene shows the dominant role of optical phonon scattering and the breaking of the relaxation time approximation. Our paper provides a detailed understanding of the microscopic mechanisms governing magnetotransport coefficients, establishing the BTE in a magnetic field as a broadly applicable first-principles tool to investigate transport in semiconductors and 2D materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗