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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

System Dynamic Analysis of a Wind Tunnel Model with Applications to Improve Aerodynamic Data Quality

The research investigates the effect of wind tunnel model system dynamics on measured aerodynamic data. During wind tunnel tests designed to obtain lift and drag data, the required aerodynamic measurements are the steady-state balance forces and moments, pressures, and model attitude. However, the wind tunnel model system can be subjected to unsteady aerodynamic and inertial loads which result in oscillatory translations and angular rotations. The steady-state force balance and inertial model attitude measurements are obtained by filtering and averaging data taken during conditions of high model vibrations. The main goals of this research are to characterize the effects of model system dynamics on the measured steady-state aerodynamic data and develop a correction technique to compensate for dynamically induced errors. Equations of motion are formulated for the dynamic response of the model system subjected to arbitrary aerodynamic and inertial inputs. The resulting modal model is examined to study the effects of the model system dynamic response on the aerodynamic data. In particular, the equations of motion are used to describe the effect of dynamics on the inertial model attitude, or angle of attack, measurement system that is used routinely at the NASA Langley Research Center and other wind tunnel facilities throughout the world. This activity was prompted by the inertial model attitude sensor response observed during high levels of model vibration while testing in the National Transonic Facility at the NASA Langley Research Center. The inertial attitude sensor cannot distinguish between the gravitational acceleration and centrifugal accelerations associated with wind tunnel model system vibration, which results in a model attitude measurement bias error. Bias errors over an order of magnitude greater than the required device accuracy were found in the inertial model attitude measurements during dynamic testing of two model systems. Based on a theoretical modal approach, a method using measured vibration amplitudes and measured or calculated modal characteristics of the model system is developed to correct for dynamic bias errors in the model attitude measurements. The correction method is verified through dynamic response tests on two model systems and actual wind tunnel test data.

Buehrle, Ralph David↗
NASA NTRS1978

Process air quality data

Air quality sampling was conducted. Data for air quality parameters, recorded on written forms, punched cards or magnetic tape, are available for 1972 through 1975. Computer software was developed to (1) calculate several daily statistical measures of location, (2) plot time histories of data or the calculated daily statistics, (3) calculate simple correlation coefficients, and (4) plot scatter diagrams. Computer software was developed for processing air quality data to include time series analysis and goodness of fit tests. Computer software was developed to (1) calculate a larger number of daily statistical measures of location, and a number of daily monthly and yearly measures of location, dispersion, skewness and kurtosis, (2) decompose the extended time series model and (3) perform some goodness of fit tests. The computer program is described, documented and illustrated by examples. Recommendations are made for continuation of the development of research on processing air quality data.

Butler, C. M.↗
NASA NTRSDate not supplied

In-Depth Analysis of Subject Functional Performance and Subjective Feedback Data for Evaluating Argos Simulation Quality

Mechanical offloading systems such as the Active Response Gravity Offload System (ARGOS) at NASA Johnson Space Center (JSC) are used to simulate various partial gravity environments. ARGOS offloads pressurized suited subjects through a gimbaling pivot point system attached to a volumetric Portable Life Support System (PLSS). The pivot point can be configured to multiple locations with respect to the human-suit system center of gravity (CG). Previous work has tested and documented the interaction between different pivot point locations and measured CG. Observations indicated that small changes in pivot point location substantially affect the stability and functional performance (simulation quality) of a subject. This led to the development of a standardized gimbal assessment protocol to assess the functional performance of a pressurized suited subject as a function of the pivot point location, using the data obtained from a variety of planetary suit mobility tasks. As a result, an expansive repository of CG-related task metrics was generated from numerous ARGOS spacesuit test events, for different gimbal configurations and different test subjects. Based on the evaluation metrics and observed trends, several pivot point locations were iteratively identified to determine an “appropriate/optimal” configuration. This study thus describes the in-depth analysis of the CG evaluation metrics to better quantify trends and determine if specific factors are strongly associated with appropriate/optimal configurations. Quantitative and qualitative variables relating to subject task performance, subjective feedback, and anthropometry will be evaluated via probabilistic methods. The results from this study are expected to improve our understanding of optimal ARGOS gimbal settings, which will better inform the gimbal configuration identification process and improve simulation quality for extravehicular activity (EVA) training.

Joseph Yao↗
DOE OSTI2025

A Performant, Scalable Processing Pipeline for High‐Quality and FAIR Environmental Sensor Data

High-resolution environmental monitoring is necessary to record, understand, and predict biogeochemical and ecological changes particularly in coastal systems but brings significant challenges in processing and making rapidly available the resulting data. The COMPASS-FME project established a network of coastal observational sites across the Chesapeake Bay and western Lake Erie regions extensively instrumented with soil, vegetation, and weather sensors logging data every 15 min. Our data processing framework, written in R and completely open source, prioritizes rapid model-experiment iteration and makes biogeochemical data rapidly available for quality assurance/quality control, analysis, and model ingestion. This pipeline is distinguished by a standardized and modular approach to data curation, extensive metadata and documentation, and its high performance. These attributes combine to make biogeochemical data rapidly accessible across COMPASS-FME and the broader community. Flexible, powerful, and reproducible approaches to handling high-volume environmental data are crucial for accelerating biogeosciences research.

Pennington, Stephanie C. [Pacific Northwest Nation↗
NASA NTRS1982

Criteria for the use of regression analysis for remote sensing of sediment and pollutants

Data analysis procedures for quantification of water quality parameters that are already identified and are known to exist within the water body are considered. The liner multiple-regression technique was examined as a procedure for defining and calibrating data analysis algorithms for such instruments as spectrometers and multispectral scanners.

Whitlock, C. H.↗
DOE OSTI2024

Probing New Physics with Tau Leptons using the CMS Detector

The Standard Model (SM) of particle physics is a thoroughly well-tested theory of all electroweak scale phenomena to date—the most recent test being the discovery of the long-predicted Higgs boson. However, there is much evidence to suggest that it is incomplete. On the formal side, the mass of the Higgs particle itself is perplexingly small, while the largest theoretical energy scale of the SM is 17 orders of magnitude larger, a puzzle known as the hierarchy problem. On the experimental side, among other things, the SM lacks a candidate for dark matter, which is now known to play an indispensable role in astrophysical large scale structure formation. Many theories that address the fundamental puzzles of the SM predict the existence of multiple Higgs bosons, including a very light boson that couples preferentially to third-generation fermions. Observation of this new light boson, either directly produced or in the decay of the recently discovered SM Higgs, would provide an unmistakable sign of new dynamics in nature. The research supported by this award used data collected by the Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) to explore boosted di-tau signatures of a new light boson as a tool in the quest to understand the shortcomings of the SM. With a proton-proton collision energy of 13 trillion electron-volts (TeV) and peak instantaneous proton luminosity of over 10^34 collisions per square centimeter per second (cm –2 s –1 ), the LHC is the only facility in the world that could enable this line of research. The research sought to address the hierarchy problem and other shortcomings of the SM through a mixture of LHC data analysis, maintenance of the CMS detector to ensure high quality data, and contributions to the Phase 2 upgrade detector for the upcoming High Luminosity phase of the LHC (HL-LHC).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2020

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles Using Python

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗
NASA NTRS1989

Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series

Two dimensions of a dynamical system given by experimental time series are distinguished. Statistical dimension gives a theoretical upper bound for the minimal number of degrees of freedom required to describe the attractor up to the accuracy of the data, taking into account sampling and noise problems. The dynamical dimension is the intrinsic dimension of the attractor and does not depend on the quality of the data. Singular Spectrum Analysis (SSA) provides estimates of the statistical dimension. SSA also describes the main physical phenomena reflected by the data. It gives adaptive spectral filters associated with the dominant oscillations of the system and clarifies the noise characteristics of the data. SSA is applied to four paleoclimatic records. The principal climatic oscillations and the regime changes in their amplitude are detected. About 10 degrees of freedom are statistically significant in the data. Large noise and insufficient sample length do not allow reliable estimates of the dynamical dimension.

Vautard, R.↗
NASA NTRS1986

Studies of radiative transfer in planetary atmospheres

Schloerb and Claussen continued their analysis of the very high quality data set obtained on the 18 centimeter OH line from the Comet P/Halley with the NRAO 43 meter antenna. The high spectral resolution (0.22 km/sec) and high signal-to-noise of the OH spectra make them ideal for the study of kinematics in the coma. Synthetic profiles were initiated for comparison with the data. A vectorial model was developed using the Monte Carlo techniques originated by Combi and Delsemme. Analysis of the millimeter wavelength observations of HCN emission from P/Halley obtained throughout much of the recent apparition were continued using the University of Massachusetts 14 millimeter-wavelength (FCRAO) antenna. A detailed analysis of the HCN lineshpaes was performed over the last six months. The excitation of HCN in the coma was studied to obtain a detailed match to the observed spectra. The passive millimeter wave radiometer was used to probe the physical and chemical nature of comets from spacecraft. Work was continued on an improved theory of radiative transfer for rough and porous surfaces, such as the regoliths of satellites, asteroids, and comets.

Irvine, W. M.↗
DOE OSTI2021

Moab Desert Crust - Sample 4E

Uncultivated Bacteria and Archaea comprise the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only recently become possible. To realize the hope of capturing Earth’s microbial genetic complement, technologies that accelerate recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform (http://www.kbase.us/). In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAG genomes, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq, and others. While portions of such capabilities are individually available from other resources, the combination of the intuitive usability, data interoperability, and integration of tools in a freely available compute resource makes KBase a uniquely powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended, with additional MAG recovery and analysis tools, via the KBase SDK (Software Development Kit).

Chivian, Dylan↗
NASA NTRSDate not supplied

Invited: uPSP Launch Vehicle Demonstration Test at NASA Ames Research Center

The Unsteady Pressure-Sensitive Paint (uPSP) Development Team outof NASA Ames Research Center (ARC) has spent the past five yearsimproving the systems and processes to advance the uPSP technology for production-level wind tunnel testing. Already considered turnkey for small-scale and research applications, development in acquisition, calibration, data transfer, and data processing were needed to be useful to customers testing at NASA wind tunnels. This development focused at ARC at the Unitary Plan Wind Tunnel (UPWT) 11-by 11-ft Transonic Wind Tunnel due to the large optical access of the test section and the NASA Advanced Supercomputer(NAS), also located at ARC. A Launch Vehicle Demonstration Test (LVDT) at the UPWT represents a milestone of this initial phase of development where several new improvements were demonstrated in a production wind tunnel environment for the first time. LVDT was conducted in April 2024 and used a 4% forebody Space Launch System (SLS) Block 1B model as the test article. Both a crew and cargo configuration were tested, with varying Mach numbers, pressures, model positions, and camera magnifications. This paper summarizes the details of the test and is part of a collection with four additional papers that provide greater detail on: high-speed lifetime methodology, spectral proper orthogonal decomposition analysis, quality of high-resolution data compared to Corcos model, and data quality, calibration, and uncertainty.

SLS↗
NASA NTRS2017

Daily Ambient Air Pollution Metrics for Five Cities: Evaluation of Data Fusion-Based Estimates and Uncertainties

Spatiotemporal characterization of ambient air pollutant concentrations is increasingly relying on the combination of observations and air quality models to provide well-constrained, spatially and temporally complete pollutant concentration fields. Air quality models, in particular, are attractive, as they characterize the emissions, meteorological, and physiochemical process linkages explicitly while providing continuous spatial structure. However, such modeling is computationally intensive and has biases. The limitations of spatially sparse and temporally incomplete observations can be overcome by blending the data with estimates from a physically and chemically coherent model, driven by emissions and meteorological inputs. We recently developed a data fusion method that blends ambient ground observations and chemical transport-modeled (CTM) data to estimate daily, spatially resolved pollutant concentrations and associatedcorrelations. In this study, we assess the ability of the data fusion method to produce daily metrics (i.e., 1-hr max, 8-hr max, and 24-hr average) of ambient air pollution that capture spatiotemporal air pollution trends for 12 pollutants (CO, NO2, NOx, O3, SO2, PM (sub10), PM (sub 2.5), and five PM (sub 2.5) components) across five metropolitan areas (Atlanta, Birmingham, Dallas, Pittsburgh, and St. Louis), from 2002 to 2008. Three sets of comparisons are performed: (1) the CTM concentrations are evaluated for each pollutant and metropolitan domain, (2) the data fusion concentrations are compared with the monitor data, (3) a comprehensive cross-validation analysis against observed data evaluates the quality of the data fusion model simulations across multiple metropolitan domains. The resulting daily spatial field estimates of air pollutant concentrations and uncertainties are not only consistent with observations, emissions, andmeteorology, but substantially improve CTM-derived results for nearly all pollutants and all cities, with the exception of NO2 for Birmingham. The greatest improvements occur for O3 and PM (sub 2.5). Squared spatiotemporal correlation coefficients range between simulations and observations determined using cross-validation across all cities for air pollutants of secondary and mixed origins are R-squared equal to 0.88-0.93 (O3), 0.81-0.89 (SO4), 0.67-0.83 (PM (sub 2.5)), 0.52-0.72 (NO3), 0.43-0.80 (NH4), 0.32-0.51 (OC), and 0.14-0.71 (PM (sub 10)). Results for relatively homogeneous pollutants of secondary origin, tend to be better than those for more spatially heterogeneous (larger spatial gradients) pollutants of primary origin (NOx, CO, SO2 and EC). Generally, background concentrations and spatial concentration gradients reflect interurban airshed complexity and the effects of regional transport, whereas daily spatial pattern variability shows intra urban consistency in the fused data. With sufficiently high CTM spatial resolution, traffic-related pollutants exhibit gradual concentration gradients that peak toward the urban centers. Ambient pollutant concentration uncertainty estimates for the fused data are both more accurate and smaller than those for either the observations or the model simulations alone.

spatiotemporal fusion↗
DOE OSTI2022

Source scaling comparison and validation in Central Italy: data intensive direct S waves versus the sparse data coda envelope methodology

SUMMARY Robustness of source parameter estimates is a fundamental issue in understanding the relationships between small and large events; however, it is difficult to assess how much of the variability of the source parameters can be attributed to the physical source characteristics or to the uncertainties of the methods and data used to estimate the values. In this study, we apply the coda method by Mayeda et al. using the coda calibration tool (CCT), a freely available Java-based code (https://github.com/LLNL/coda-calibration-tool) to obtain a regional calibration for Central Italy for estimating stable source parameters. We demonstrate the power of the coda technique in this region and show that it provides the same robustness in source parameter estimation as a data-driven methodology [generalized inversion technique (GIT)], but with much fewer calibration events and stations. The Central Italy region is ideal for both GIT and coda approaches as it is characterized by high-quality data, including recent well-recorded seismic sequences such as L'Aquila (2009) and Amatrice–Norcia–Visso (2016–2017). This allows us to apply data-driven methods such as GIT and coda-based methods that require few, but high-quality data. The data set for GIT analysis includes ∼5000 earthquakes and more than 600 stations, while for coda analysis we used a small subset of 39 events spanning 3.5 < Mw < 6.33 and 14 well-distributed broad-band stations. For the common calibration events, as well as an additional 247 events (∼1.7 < Mw < ∼5.0) not used in either calibration, we find excellent agreement between GIT-derived and CCT-derived source spectra. This confirms the ability of the coda approach to obtain stable source parameters even with few calibration events and stations. Even reducing the coda calibration data set by 75 per cent, we found no appreciable degradation in performance. This validation of the coda calibration approach over a broad range of event size demonstrates that this procedure, once extended to other regions, represents a powerful tool for future routine applications to homogeneously evaluate robust source parameters on a national scale. Furthermore, the coda calibration procedure can homogenize the Mw estimates for small and large events without the necessity of introducing any conversion scale between narrow-band measures such as local magnitude (ML) and Mw, which has been shown to introduce significant bias.

Morasca, Paola (ORCID:0000000265254867)↗
DOE OSTI2021

Wind Plant Performance Prediction Benchmark Phase 1 (Technical Report)

Financial risk resulting from the uncertainty associated with developing, owning, and operating wind power plants remains a barrier to reducing the levelized cost of energy (LCOE). On average, modern wind power plants in the U.S. underperform their expected annual energy output by 3.5-4.5% , with many underperforming by over 10%. To compensate for this uncertainty, investors require a larger return on investment (ROI) and apply "knock-down" factors that mask much of the underlying sources of uncertainty. Wind energy projects thus have reduced access to low-cost capital. Furthermore, operating wind plants often take a simple approach to estimating operations & maintenance (O&M) costs (e.g. straight-line estimates based on similar plants), which can eat into profits. To overcome these issues, the wind industry must improve the models they use for estimating wind plant performance and operations. An industry consortium (IC) requested that the National Renewable Energy Laboratory (NREL) lead a Department of Energy (DOE) working group to benchmark the accuracy of wind power plant energy predictions against real operational data. The IC was also motivated by DOE and NREL's potential to characterize systematic energy underperformance, identify sources of uncertainty, and explore root causes. The Wind Plant Performance Prediction (WP3) project was created out of this request, and this report represents the successful completion of Phase 1 of the WP3 project. During the project, wind plant owners provided both pre-construction and operational data to NREL. The pre-construction data was provided to wind resource assessment (WRA) consultants so they could conduct energy yield assessments (EYA). NREL took all of the completed EYAs, along with the operational data, and conducted an operational assessment to benchmark the EYA results against actual operational data. Given the large amounts of sensitive data required for this effort, as well as historical opposition to sharing data within industry, successful completion of Phase 1 represents an unprecedented milestone for industry data sharing. To improve the accuracy and confidence of pre-construction EYAs, wind plant owners and investors need better, more certain, energy yield predictions. The WP3 Benchmark Project is an industry-driven response to this reality. For the first time, industry has taken the important step of working together at scale, sharing valuable operational data with DOE and NREL in order to investigate the sources of bias and uncertainty in these energy estimates. This IC provides wind plant preconstruction and operational data to NREL in an organized and documented fashion and provides guidance and feedback as needed. The IC also provides introspection of the design of experiment, key metrics of success, data challenges, analysis best practices, and quality of results.

17 WIND ENERGY↗
NASA NTRS1980

The 1979 Southeastern Virginia Urban Plume Study (SEV-UPS): Surface and airborne studies

The operation of two surface monitoring stations (one in downtown Norfolk, Virginia, one south of the city near the Great Dismal Swamp) and the collection of 40 hours of airborne measurements is described. Surface site measurements of ozone, oxides of nitrogen, sulfur dioxide, temperature, dew point, b sub seat, and condensation nuclei were made. Instrument calibrations, quality assurance audits, and preliminary data analysis in support of the Urban Plume Study were also made. The air pollution problems that were addressed are discussed. Data handling procedures followed for the surface stations are presented. The operation of the aircraft sampling platform is described. Aircraft sampling procedures are discussed. A preliminary descriptive analysis of the aircraft data is given along with data or plots for surface sites, airborne studies, hydrocarbon species, and instrument performance audits. Several of the aircraft flights clearly show the presence of an urban ozone plume downwind of Norfolk in the direction of the mean wind flow.

White, J. H.↗
NASA NTRS1988

Radiative transfer in planetary atmospheres

Rheoretical techniques and observations at millimeter wavelengths are combined to study the atmosphere of planets and comets, planetary and satellite regoliths, and planetary rings. Analysis of the very high quality data on the 18 cm OH line observed in recent comets continued. The high spectral resolution and high signal-to-noise make these lines ideal for study of the kinematics in cometary comae. A model of the collisional quenching of the inversion of the lambda doublet responsible for the OH radio emission has been developed by P. Schloerb. For conditions appropriate to Halley's Comet, collisional quenching should lead radio observers to systematically underestimate the OH parent production rate by a factor of approximately 3 relative to its actual value, which is very consistent with differences observed between radio and ultraviolet-derived production rates. Modeling is likewise continuing for the profiles observed in the lowest rotational transition of HCN in Comet Halley in order to better estimate the excitation and hence the abundance of HCN, as well as the kinematics of parent molecules in the coma. A collaborative program to combine data from the 14 m antenna with interferometric data abtained at the Hat Creek Radio Observatory is allowing aperture synthesis mapping of Venus in the CO J=1-0 line.

Irvine, William M.↗
NASA NTRS1997

Gamma-Ray Burst Arrival Time Localizations: Simultaneous Observations by Mars Observer, Compton Gamma Ray Observatory and Ulysses

Between 1992 October 4 and 1993 August 1, concurrent coverage by the Compton Gamma Ray Observatory (CGRO), Mars Observer (MO), and Ulysses spacecraft was obtained for 78 gamma-ray bursts (GRBs). Although most of these were below the MO and Ulysses thresholds, nine were positively detected by all three spacecraft, with data quality adequate for quantitative localization analysis. All were localized independently to approximately 2 deg accuracy by the CGRO Burst and Transient Source Experiment (BATSE). We computed arrival-time error boxes with larger dimensions ranging from a few arcminutes to the diameters of the BATSE-only boxes and with smaller dimensions in the arcminute range. Three events are of particular interest: GB 930704 (BATSE 2428) has been described as a possible repeater. The arrival-time information is consistent with that hypothesis, but only just so. The GB 930706 (2431) box, at approximately 1 min x 4 min, is the only one this small obtained since Pioneer Venus Orbiter (PVO) entered the Venusian atmosphere in 1992 October. Sensitive radio and optical observations of this location were made within 8 and 9 days of the burst, but no counterpart candidates were identified. GB 930801 (2477) is the first GRB that had its localization improved by taking into account BATSE Earth occultation.

Laros, J. G.↗
NASA NTRS1978

Smooth Passage For The Jetfoil

The Flying Princess is a Boeing Jetfoil, one of a family of commercial waterjets built by Boeing Marine Systems, a division of The Boeing Company, Seattle, Washington. The new Jetfoil offers a number of advantages over earlier hydrofoils, a major one being a smooth ride in rough waters. NASA technology contributed to jolt-free passenger comfort. Hydrofoils skim the surface at speeds considerably greater than those of conventional ships because there is little friction between hull and water. Hulls are raised above the water by the lift of the foils, which resemble and function like an airplane wing. The foils are attached to the hull by rigid struts, which ordinarily cause a vessel operating in coastal seas to follow the contour of the waves. In wind-whipped waters, this makes for a rough ride. Seeking to increase passenger acceptance, Boeing Marine System engineers looked for ways to improve rough-water ride quality. Langley Research Center conducts continuing ride quality research. Initially, it was aimed at improving aircraft ride; it was later expanded to include all modes of transportation. Research includes studies of vibration, acceleration, temperature, humidity, passenger seats and posture, and the psychological aspects of passenger reaction to vehicle ride. As part of the program, Langley developed instrumentation, ride quality models and methods of data analysis.

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