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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Uniform Foam Crush Testing for Multi-Mission Earth Entry Vehicle Impact Attenuation

Multi-Mission Earth Entry Vehicles (MMEEVs) are blunt-body vehicles designed with the purpose of transporting payloads from outer space to the surface of the Earth. To achieve high-reliability and minimum weight, MMEEVs avoid use of limited-reliability systems, such as parachutes and retro-rockets, instead using built-in impact attenuators to absorb energy remaining at impact to meet landing loads requirements. The Multi-Mission Systems Analysis for Planetary Entry (M-SAPE) parametric design tool is used to facilitate the design of MMEEVs and develop the trade space. Testing was conducted to characterize the material properties of several candidate impact foam attenuators to enhance M-SAPE analysis. In the current effort, four different Rohacell foams are tested at three different, uniform, strain rates (approximately 0.17, approximately 100, approximately 13,600%/s). The primary data analysis method uses a global data smoothing technique in the frequency domain to remove noise and system natural frequencies. The results from the data indicate that the filter and smoothing technique are successful in identifying the foam crush event and removing aberrations. The effect of strain rate increases with increasing foam density. The 71-WF-HT foam may support Mars Sample Return requirements. Several recommendations to improve the drop tower test technique are identified.

Patterson, Byron W.↗
DOE OSTI2020

Uncertainty in Experimental Data Analysis [Slides]

The talk was presented virtually to the Institute of Fundamental Technological Research, Polish Academy of Sciences in Warsaw, Poland, December 21, 2020. Astronomical observations, unusual medical cases, physics experiments too costly to repeat, natural events like earthquakes, hurricanes – all of them are impossible to repeat yet produce important scientific information not achievable in other way. This data should not be treated as qualitative, anecdotal evidence only. It should be analyzed in a mathematically rigorous way to produce quantitative experimental data. Analysis method for one-of-a-kind event data differs from analysis of a repeated experiment data. For a repeated experiments the experimental error includes a range of true values generated by repetitions of the experiment, and measurement uncertainty caused by detectors. They are independent. Repetitions of any experiment, as similar as achievable, always have built-in differences resulting in a range of the true values rather than in a single true experimental value. Measurement uncertainty depends on the measurement system only. Modern digital measurements have very small uncertainty, frequently smaller than the range of true experimental values resulting from built-in differences in the experiment repetitions. When data from one-of-a-kind experiment are analyzed, only the measurement uncertainty can be reported.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

nautilus : boosting Bayesian importance nested sampling with deep learning

ABSTRACT We introduce a novel approach to boost the efficiency of the importance nested sampling (INS) technique for Bayesian posterior and evidence estimation using deep learning. Unlike rejection-based sampling methods such as vanilla nested sampling (NS) or Markov chain Monte Carlo (MCMC) algorithms, importance sampling techniques can use all likelihood evaluations for posterior and evidence estimation. However, for efficient importance sampling, one needs proposal distributions that closely mimic the posterior distributions. We show how to combine INS with deep learning via neural network regression to accomplish this task. We also introduce nautilus, a reference open-source python implementation of this technique for Bayesian posterior and evidence estimation. We compare nautilus against popular NS and MCMC packages, including emcee, dynesty, ultranest, and pocomc, on a variety of challenging synthetic problems and real-world applications in exoplanet detection, galaxy SED fitting and cosmology. In all applications, the sampling efficiency of nautilus is substantially higher than that of all other samplers, often by more than an order of magnitude. Simultaneously, nautilus delivers highly accurate results and needs fewer likelihood evaluations than all other samplers tested. We also show that nautilus has good scaling with the dimensionality of the likelihood and is easily parallelizable to many CPUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Hacking Limnology Workshop and DSOS22: Creating a Community of Practice for the Nexus of Data Science, Open Science, and the Aquatic Sciences

The 2nd Aquatic Ecosystem Modeling-Junior (AEMON-J) Hacking Limnology Workshop and 3rd Virtual Summit: Incorporating Data Science and Open Science in the Aquatic Sciences (DSOS) took place on 25–29 July 2022. These virtual events were developed to bring together researchers from diverse backgrounds to share developments in data-intensive research in the aquatic sciences and train participants in cutting-edge data analysis methods related to remote sensing, data pipelines, and modeling of aquatic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

A New Machine Learning Based Analysis for Improving Satellite Retrieved Atmospheric Composition Data: OMI SO2 as an Example

Despite recent progress, satellite retrievals of anthropogenic SO2 still suffer from relatively low signal-tonoise ratios. In this study, we demonstrate a new machine learning data analysis method to improve the quality of satellite SO2 products. In the absence of large ground-truth datasets for SO2, we start from SO2 slant column densities (SCDs) retrieved from the Ozone Monitoring Instrument (OMI) using a data-driven, physically based algorithm and calculate the ratio between the SCD and the root mean square (rms) of the fitting residuals for each pixel. To build the training data, we select presumably clean pixels with small SCD / rms ratios (SRRs) and set their target SCDs to zero. For polluted pixels with relatively large SRRs, we set the target to the original retrieved SCDs. We then train neural networks (NNs) to reproduce the target SCDs using predictors including SRRs for individual pixels, solar zenith, viewing zenith and phase angles, scene reflectivity, and O3 column amounts, as well as the monthly mean SRRs. For data analysis, we employ two NNs: (1) one trained daily to produce analyzed SO2 SCDs for polluted pixels each day and (2) the other trained once every month to produce analyzed SCDs for less polluted pixels for the entire month. Test results for 2005 show that our method can significantly reduce noise and artifacts over background regions. Over polluted areas, the monthly mean NN-analyzed and original SCDs generally agree to within ±15 %, indicating that our method can retain SO2 signals in the original retrievals except for large volcanic eruptions. This is further confirmed by running both the NN-analyzed and original SCDs through a topdown emission algorithm to estimate the annual SO2 emissions for ∼ 500 anthropogenic sources, with the two datasets yielding similar results. We also explore two alternative approaches to the NN-based analysis method. In one, we employ a simple linear interpolation model to analyze the original SCD retrievals. In the other, we develop a PCA–NN algorithm that uses OMI measured radiances, transformed and dimension-reduced with a principal component analysis (PCA) technique, as inputs to NNs for SO2 SCD retrievals. While the linear model and the PCA–NN algorithm can reduce retrieval noise, they both underestimate SO2 over polluted areas. Overall, the results presented here demonstrate that our new data analysis method can significantly improve the quality of existing OMI SO2 retrievals. The method can potentially be adapted for other sensors and/or species and enhance the value of satellite data in air quality research and applications.

Can Li↗
NASA NTRS1976

Turbulence excited frequency domain damping measurement and truncation effects

Existing frequency domain modal frequency and damping analysis methods are discussed. The effects of truncation in the Laplace and Fourier transform data analysis methods are described. Methods for eliminating truncation errors from measured damping are presented. Implications of truncation effects in fast Fourier transform analysis are discussed. Limited comparison with test data is presented.

Soovere, J.↗
NASA NTRS1982

Analysis of the nature and cause of turbulence upset using airline flight records

The development and application of methods for determining aircraft motions and related winds, using data normally recorded during airline flight operations, are described. The methods are being developed, in cooperation with the National Transportation Safety Board, to aid in the analysis and understanding of circumstances associated with aircraft accidents or incidents. Data from a recent DC-10 encounter with severe, high-altitude turbulence are used to illustrate the methods. The analysis of this encounter shows the turbulence to be a series of equally spaced horizontal swirls known as 'cat's eyes' vortices. The use of flight-data analysis methods to identify this type of turbulence phenomenon is presented for the first time.

Parks, E. K.↗
NASA NTRS2012

Changes in Extratropical Storm Track Cloudiness 1983-2008: Observational Support for a Poleward Shift

Climate model simulations suggest that the extratropical storm tracks will shift poleward as a consequence of global warming. In this study the northern and southern hemisphere storm tracks over the Pacific and Atlantic ocean basins are studied using observational data, primarily from the International Satellite Cloud Climatology Project, ISCCP. Potential shifts in the storm tracks are examined using the observed cloud structures as proxies for cyclone activity. Different data analysis methods are employed, with the objective to address difficulties and uncertainties in using ISCCP data for regional trend analysis. In particular, three data filtering techniques are explored; excluding specific problematic regions from the analysis, regressing out a spurious viewing geometry effect, and excluding specific cloud types from the analysis. These adjustments all, to varying degree, moderate the cloud trends in the original data but leave the qualitative aspects of those trends largely unaffected. Therefore, our analysis suggests that ISCCP data can be used to interpret regional trends in cloudiness, provided that data and instrumental artefacts are recognized and accounted for. The variation in magnitude between trends emerging from application of different data correction methods, allows us to estimate possible ranges for the observational changes. It is found that the storm tracks, here represented by the extent of the midlatitude-centered band of maximum cloud cover over the studied ocean basins, experience a poleward shift as well as a narrowing over the 25 year period covered by ISCCP. The observed magnitudes of these effects are larger than in current generation climate models (CMIP3). The magnitude of the shift is particularly large in the northern hemisphere Atlantic. This is also the one of the four regions in which imperfect data primarily prevents us from drawing firm conclusions. The shifted path and reduced extent of the storm track cloudiness is accompanied by a regional reduction in total cloud cover. This decrease in cloudiness can primarily be ascribed to low level clouds, whereas the upper level cloud fraction actually increases, according to ISCCP. Independent satellite observations of radiative fluxes at the top of the atmosphere are consistent with the changes in total cloud cover. The shift in cloudiness is also supported by a shift in central position of the mid-troposphere meridional temperature gradient. We do not find support for aerosols playing a significant role in the satellite observed changes in cloudiness. The observed changes in storm track cloudiness can be related to local cloud-induced changes in radiative forcing, using ERBE and CERES radiative fluxes. The shortwave and the longwave components are found to act together, leading to a positive (warming) net radiative effect in response to the cloud changes in the storm track regions, indicative of positive cloud feedback. Among the CMIP3 models that simulate poleward shifts in all four storm track areas, all but one show decreasing cloud amount on a global mean scale in response to increased CO2 forcing, further consistent with positive cloud feedback. Models with low equilibrium climate sensitivity to a lesser extent than higher-sensitivity models simulate a poleward shift of the storm tracks.

Bender, Frida A-M.↗
DOE OSTI2022

For your consideration: Distance Analysis for PDV Data

An analytical study that discusses photonic Doppler velocimetry data analysis methods. The author intends to share this study with experts in this field at National Laboratory partners, e.g., LLNL, LANL, and Sandia. There is no plan to submit this work to a professional (public) conference or a journal publisher.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1994

Aircraft ground vibration testing at the NASA Dryden Flight Research Facility, 1993

The NASA Dryden Flight Research Facility performs ground vibration testing to assess the structural characteristics of new and modified research vehicles. This paper updates the research activities, techniques used, and experiences in applying this technology to aircraft since 1987. Test equipment, data analysis methods, and test procedures used for typical test programs are discussed. The data presented illustrate the use of modal test and analysis in flight research programs for a variety of aircraft. This includes a technique to acquire control surface free-play measurements on the X-31 airplane more efficiently, and to assess the effects of structural modifications on the modal characteristics of an F-18 aircraft. In addition, the status and results from current research activities are presented. These data show the effectiveness of the discrete modal filter as a preprocessor to uncouple response measurements into simple single-degree-of-freedom responses, a database for the comparison of different excitation methods on a JetStar airplane, and the effect of heating on modal frequency and damping.

Kehoe, Michael W.↗
NASA NTRS1981

Exploitation of SAR data for measurement of ocean currents and wave velocities

Methods of extracting information on ocean currents and wave orbital velocities from SAR data by an analysis of the Doppler frequency content of the data are discussed. The theory and data analysis methods are discussed, and results are presented for both aircraft and satellite (SEASAT) data sets. A method of measuring the phase velocity of a gravity wave field is also described. This method uses the shift in position of the wave crests on two images generated from the same data set using two separate Doppler bands. Results of the current measurements are pesented for 11 aircraft data sets and 4 SEASAT data sets.

Shuchman, R. A.↗
NASA NTRS2010

Acoustic Measurements for Small Solid Rocket Motors

Models have been developed to predict large solid rocket motor acoustic loads based on the scaling of small solid rocket motors. MSFC has measured several small solid rocket motors in horizontal and launch configurations to anchor these models. Solid Rocket Test Motor (SRTM) has ballistics similar to the Reusable Solid Rocket Motor (RSRM) therefore a good choice for acoustic scaling. Acoustic measurements were collected during the test firing of the Insulation Configuration Extended Length (ICXL) 7,6, and 8 (in firing order) in order to compare to RSRM horizontal firing data. The scope of this presentation includes: Acoustic test procedures and instrumentation implemented during the three SRTM firings and Data analysis method and general trends observed in the data.

Vargas, Magda B.↗
NASA NTRS1999

X-Ray Diffraction Techniques for a Field Instrument: Patterns of Lithologic Provences

Future exploration of Mars will attempt to shed light on the mineralogy of surface materials. Instruments deployed from remote platforms should have the capability to conduct both intensive analyses as well as rapid, reconnaissance surveys while they function in the martian environment as surrogate geologists. In order to accommodate the reconnaissance mode of analysis and to compensate for analytical limitations imposed by the space-flight conditions, data analysis methods are being developed that will permit interpretation of data by recognition of signatures or "fingerprints". Specifically, we are developing a technique which will allow interpretation of diffraction patterns by recognition of characteristic signatures of different lithologic provences. This technique allows a remote vehicle to function in a rapid-scan mode using the lithologic signature to determine where a more thorough analysis is needed. An x-ray diffraction pattern is characterized by the angular positions of diffracted x-rays, x-ray intensity levels and background radiation levels. These elements may be used to identify a generalized x-ray signature. Lithologic signatures are being developed in two ways. A signature is composed using the ideal powder diffraction indices from the mineral assembledge common to a specific lithologic provence. This is then confirmed using a laboratory diffraction pattern of a whole rock powder. Preliminary results comparing the diffraction signatures of the major mineral assembledges common to basalt, carbonate, and evaporite basin deposits indicate that lithologies are differentiable as a "fingerprint". Statistical analyses are being performed to establish the confidence levels of this technique.

Marshall, J.↗
NASA NTRSDate not supplied

Leveraging the 2024 Solar Eclipse to Enhance Science Learning through Citizen Science

The solar eclipse on April 8, 2024, provided a rare and compelling opportunity for educators and students to engage in hands-on citizen science. Two NASA Science Activation projects GLOBE Mission Earth (GME) and NASA Earth Science Education Collaborative (NESEC) partnered together to provide a unique professional development experience for educators interested in the eclipse. They invited educators to participate in a specialized 5-week online workshop designed to engage the educators in Global Learning and Observations to Benefit the Environment (GLOBE) citizen science about the eclipse. The workshop was designed to support their certification as GLOBE educators and develop their knowledge, skills, and confidence in conducting a GLOBE investigation. Over 60 educators from across the United States took part in this workshop, which focused on investigating the eclipse by collecting and analyzing atmospheric data. The GLOBE Program promotes environmental and scientific literacy by enabling participants to collect Earth science data and contribute it to a global database accessible for research. The 2024 GLOBE Eclipse workshop trained educators in specific GLOBE protocols—Clouds, Air Temperature, and Surface Temperature—using the GLOBE Eclipse tool integrated into the GLOBE Observer app. This training was supplemented with guidance on engaging students in authentic scientific research and creating research posters to present their findings. The workshop aimed to enhance educators’ skills and confidence in integrating GLOBE protocols into their teaching practices. It addressed several key areas outlined in the National Academies' report on Learning through Citizen Science, including scientific context, nature of participation, and project infrastructure. Educators learned about the atmospheric effects of solar eclipses and were trained to use scientific tools and data analysis methods relevant to their research. They also engaged in live sessions and asynchronous activities, practicing data collection and analysis with real-time feedback. Survey results from the workshop highlighted that participants were primarily motivated by the desire to better use data in their classrooms and improve their proficiency with the GLOBE Observer app. Post-workshop evaluations showed significant increases in educators' confidence regarding their ability to conduct and guide scientific research. Participants reported feeling well-prepared to use the GLOBE Observer app for data collection and were successful in integrating their eclipse observations into classroom activities. Participants also valued the opportunity to contribute to authentic science through GLOBE, which involved observing atmospheric changes such as air temperature fluctuations and cloud cover alterations during the eclipse. The success of the workshop is evident in the increased confidence and skill levels of educators, as well as the publication of research posters on the GLOBE Mission Earth Student Research webpage.This session will discuss how the GLOBE Eclipse workshop series effectively utilized the unique context of the solar eclipse to enhance science education through citizen science. By adhering to the principles outlined in the Learning through Citizen Science framework, the workshop successfully engaged educators and students in meaningful scientific practices, demonstrating the potential of citizen science to enrich science education and foster a deeper understanding of Earth systems.

Jessica Taylor↗
NASA NTRS1978

The Earth Radiation Budget Satellite System

The scientific objectives of an Earth Radiation Budget Satellite System (ERBSS) are discussed along with the associated data analysis methods, mission analysis, and the instrument systems. High resolution data on the scale of about 250 km over the entire globe are essential to gain insight into such features as the development of sea-surface temperature anomalies, radiation effects of ice and snow cover on the atmospheric circulation, albedo variation in the desert-vegetation boundaries, and major long-period circulation phenomena. The ERBSS experiment is also viewed as a precursor of an operational satellite system for monitoring the earth's radiation budget. Various numbers of satellites and orbit inclinations have been analyzed to define the satellite combination which provides sufficient coverage of the earth for spatial and temporal radiation sampling.

Woerner, C. V.↗
NASA NTRS1994

The Global Oscillation Network Group site survey. 1: Data collection and analysis methods

The Global Oscillation Network Group (GONG) Project is planning to place a set of instruments around the world to observe solar oscillations as continuously as possible for at least three years. The Project has now chosen the sites that will comprise the network. This paper describes the methods of data collection and analysis that were used to make this decision. Solar irradiance data were collected with a one-minute cadence at fifteen sites around the world and analyzed to produce statistics of cloud cover, atmospheric extinction, and transparency power spectra at the individual sites. Nearly 200 reasonable six-site networks were assembled from the individual stations, and a set of statistical measures of the performance of the networks was analyzed using a principal component analysis. An accompanying paper presents the results of the survey.

Hill, Frank↗
DOE OSTI2021

Small-angle X-ray and neutron scattering

Small-angle scattering (SAS) is a technique that is able to probe the structural organization of matter and quantify its response to changes in external conditions. X-ray and neutron scattering profiles measured from bulk materials or materials deposited at surfaces arise from nanostructural inhomogeneities of electron or nuclear density. Furthermore, the analysis of SAS data from coherent scattering events provides information about the length scale distributions of material components. Samples for SAS studies may be prepared in situ or under near-native conditions and the measurements performed at various temperatures, pressures, flows, shears or stresses, and in a time-resolved fashion. In this Primer, we provide an overview of SAS, summarizing the types of instrument used, approaches for data collection and calibration, available data analysis methods, structural information that can be obtained using the method, and data depositories, standards and formats. Recent applications of SAS in structural biology and the soft-matter and hard-matter sciences are also discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗