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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

How deep to dig: effects of web-scraping search depth on hyperlink network analysis of environmental stewardship organizations

Abstract Social network analysis (SNA) tools and concepts are essential for addressing many environmental management and sustainability issues. One method to gather SNA data is to scrape them from environmental organizations’ websites. Web-based research can provide important opportunities to understand environmental governance and policy networks while potentially reducing costs and time when compared to traditional survey and interview methods. A key parameter is ‘search depth,’ i.e., how many connected pages within a website to search for information. Existing research uses a variety of depths and no best practices exist, undermining research quality and case study comparability. We therefore analyze how search depth affects SNA data collection among environmental organizations, if results vary when organizations have different objectives, and how search depth affects social network structure. We find that scraping to a depth of three captures the majority of relevant network data regardless of an organization’s focus. Stakeholder identification (i.e., who is in the network) may require less scraping, but this might under-represent network structure (i.e., who is connected). We also discuss how scraping web-pages of local programs of larger organizations may lead to uncertain results and how our work can combine with mixed methods approaches.

Sayles, Jesse S. (ORCID:0000000218378920)↗
NASA NTRS2012

The Morphology of Craters on Mercury: Results from MESSENGER Flybys

Topographic data measured from the Mercury Laser Altimeter (MLA) and the Mercury Dual Imaging System (MDIS) aboard the MESSENGER spacecraft were used for investigations of the relationship between depth and diameter for impact craters on Mercury. Results using data from the MESSENGER flybys of the innermost planet indicate that most of the craters measured with MLA are shallower than those previously measured by using Mariner 10 images. MDIS images of these same MLA-measured craters show that they have been modified. The use of shadow measurement techniques, which were found to be accurate relative to the MLA results, indicate that both small bowl-shaped and large complex craters that are fresh possess depth-to-diameter ratios that are in good agreement with those measured from Mariner 10 images. The preliminary data also show that the depths of modified craters are shallower relative to fresh ones, and might provide quantitative estimates of crater in-filling by subsequent volcanic or impact processes. The diameter that defines the transition from simple to complex craters on Mercury based on MESSENGER data is consistent with that reported from Mariner 10 data.

Barnouin, Oliver S.↗
NASA NTRS1985

A cool anomaly off northern California - An investigation using IR imagery and in situ data

The OPTOMA (Ocean Prediction Through Observation, Modeling and Analysis) program is developing an ocean descriptive-predictive system for four-dimensional data assimilation. It is presently concerned with the mesoscale variability in the California Current System (CCS). The present paper has the objective to assess the relationship of surface temperature structure to subsurface temperature structure and flow fields. Surface temperature anomalies are related to the mesoscale horizontal advective and subsurface mass fields. The cool anomaly off northern California in summer 1982 is discussed, taking into account the temperature structure along transects, T-S variations and inferred water masses, variation of horizontal temperature patterns with depth, and synoptic information from IR data.

Rienecker, M. M.↗
NASA NTRS2012

Ground and Airborne Methane Measurements using Optical Parametric Amplifiers

We report on an initial airborne demonstration of atmospheric methane column measurements at 1.65 micrometers using a widely tunable, seeded optical parametric amplifier (OPA) lidar and a photon counting detector. Methane is an important greenhouse gas and accurate knowledge of its sources and sinks is needed for climate modeling. Our lidar system uses 20 pulses at increasing wavelengths and integrated path differential absorption (IPDA) to map a methane line at 1650.9 nanometers. The wavelengths are generated by using a Nd:YAG pump laser at 1064.5 nanometers and distributed feedback diode laser at 1650.9 nanometers and a periodically-poled lithium niobate (PPLN) crystal. The pulse width was 3 nanoseconds and the pulse repetition rate was 6.28 KHz. The outgoing energy was approximately 13 microJoules/pulse. A commercial 20 nanometer diameter fiber-coupled telescope with a photon counting detector operated in analog mode with a 0.8 nanometer bandpass filter was used as the lidar receiver. The lidar system was integrated on NASA's DC-8 flying laboratory, based at Dryden Airborne operations Facility (DAOF) in Palmdale CA. Three flights were performed in the central valley of California. Each flight lasted about 2.5 hours and it consisted of several flight segments at constant altitudes at approximately 3, 4.5, 6, 7.6, 9.1, 10.6 km (l0, 15, 20, 25, 30, 35 kft). An in-situ cavity ring down spectrometer made by Picarro Inc. was flown along with the lidar instrument provided us with the "truth" i.e. the local CH4, CO2 and H2O concentrations at the constant flight altitude segments. Using the aircraft's altitude, GPS, and meteorological data we calculated the theoretical differential optical depth of the methane absorption at increasing altitudes. Our results showed good agreement between the experimentally derived optical depth measurements from the lidar instrument and theoretical calculations as the flight altitude was increased from 3 to 10.6 kilometers, assuming a constant methane mixing ratio of 1.8 parts per million. The in-situ spectrometer did not show any significant deviations from the ambient concentrations. Further analysis using meteorological data from the Global Modeling and Assimilation Office (http://gmao.gsfc.nasa.gov/) to derive the theoretical optical depth also showed good agreement with the experimentally derived values. The OPA lidar system with slight modifications has also been used to measure CO2, water vapor, and CO in the near and mid-infrared spectral regions on the ground.

Riris, Haris↗
NASA NTRS2006

Review of Orbiter Flight Boundary Layer Transition Data

In support of the Shuttle Return to Flight program, a tool was developed to predict when boundary layer transition would occur on the lower surface of the orbiter during reentry due to the presence of protuberances and cavities in the thermal protection system. This predictive tool was developed based on extensive wind tunnel tests conducted after the loss of the Space Shuttle Columbia. Recognizing that wind tunnels cannot simulate the exact conditions an orbiter encounters as it re-enters the atmosphere, a preliminary attempt was made to use the documented flight related damage and the orbiter transition times, as deduced from flight instrumentation, to calibrate the predictive tool. After flight STS-114, the Boundary Layer Transition Team decided that a more in-depth analysis of the historical flight data was needed to better determine the root causes of the occasional early transition times of some of the past shuttle flights. In this paper we discuss our methodology for the analysis, the various sources of shuttle damage information, the analysis of the flight thermocouple data, and how the results compare to the Boundary Layer Transition prediction tool designed for Return to Flight.

Mcginley, Catherine B.↗
NASA NTRS2007

Antarctic Sea Ice Thickness and Snow-to-Ice Conversion from Atmospheric Reanalysis and Passive Microwave Snow Depth

Passive microwave snow depth, ice concentration, and ice motion estimates are combined with snowfall from the European Centre for Medium Range Weather Forecasting (ECMWF) reanalysis (ERA-40) from 1979-200 1 to estimate the prevalence of snow-to-ice conversion (snow-ice formation) on level sea ice in the Antarctic for April-October. Snow ice is ubiquitous in all regions throughout the growth season. Calculated snow- ice thicknesses fall within the range of estimates from ice core analysis for most regions. However, uncertainties in both this analysis and in situ data limit the usefulness of snow depth and snow-ice production to evaluate the accuracy of ERA-40 snowfall. The East Antarctic is an exception, where calculated snow-ice production exceeds observed ice thickness over wide areas, suggesting that ERA-40 precipitation is too high there. Snow-ice thickness variability is strongly controlled not just by snow accumulation rates, but also by ice divergence. Surprisingly, snow-ice production is largely independent of snow depth, indicating that the latter may be a poor indicator of total snow accumulation. Using the presence of snow-ice formation as a proxy indicator for near-zero freeboard, we examine the possibility of estimating level ice thickness from satellite snow depths. A best estimate for the mean level ice thickness in September is 53 cm, comparing well with 51 cm from ship-based observations. The error is estimated to be 10-20 cm, which is similar to the observed interannual and regional variability. Nevertheless, this is comparable to expected errors for ice thickness determined by satellite altimeters. Improvement in satellite snow depth retrievals would benefit both of these methods.

Markus, Thorsten↗
NASA NTRS2012

Derivation of a New Smoke Emissions Inventory using Remote Sensing, and Its Implications for Near Real-Time Air Quality Applications

A new emissions inventory of particulate matter (PM) is being derived mainly from remote sensing data using fire radiative power (FRP) and aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, as well as wind data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis dataset, which spans the satellite era. This product is generated using a coefficient of emission, C(sub e), that has been produced on a 1x1 degree global grid such that, when it is multiplied with satellite measurements of FRP or its time-integrated equivalent fire radiative energy (FRE) retrieved over a given area and time period, the corresponding PM emissions are estimated. This methodology of using C(sub e) to derive PM emissions is relatively new and advantageous for near real-time air quality applications compared to current methods based on post-fire burned area that may not provide emissions in a timely manner. Furthermore, by using FRP to characterize a fire s output, it will represent better accuracy than the use of raw fire pixel counts, since fires in individual pixels can differ in size and strength by orders of magnitude, resulting in similar differences in emission rates. Here we will show examples of this effect and how this new emission inventory can properly account for the differing emission rates from fires of varying strengths. We also describe the characteristics of the new emissions inventory, and propose the process chain of incorporating it into models for air quality applications.

Ellison, Luke↗
DOE OSTI2020

Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning

Big data transfer in next-generation scientific ap- plications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Net- works (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate band- widths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer perfor- mance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application- level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher pre- diction accuracy in up to 90% of the cases with very noisy real-life performance measurements.

Yun, Daqing↗
NASA NTRS2011

Mars Exploration Rover Heatshield Observation Campaign

For the first time ever, engineers were able to observe a heatshield on the surface of another planet after a successful entry through the atmosphere. A three-week heatshield observation campaign was conducted in December 2004 after the Mars Exploration Rover Opportunity exited "Endurance Crater." By utilizing the rover's scientific instruments, data was collected to make a qualitative assessment of the performance of the heatshield. This data was gathered to gain a better understanding of how the heatshield performed during entry through the Martian atmosphere. In addition, this unprecedented look at the heatshield offered engineers the opportunity to assess if any unexpected anomalies occurred. Once a survey of the heatshield debris was completed, multiple targets of interest were chosen for the collection of imaging data. This data was then used to assess the char depth of the thermal protection material, which compared well with design and post-flight computational predictions. Extensive imaging data was collected and showed the main seal in pristine conditions, and no observable indications of structure overheating. Additionally, unexpected vehicle dynamics during the atmospheric entry were explained by the observation of thermal blanket remnants attached to the heatshield.

Thermal Protection System (TPS)↗
NASA NTRS2011

Mars Exploration Rover Heatshield Observation Campaign

For the first time ever, engineers were able to observe a heatshield on the surface of another planet after a successful entry through the atmosphere. A three-week heatshield observation campaign was conducted in December 2004 after the Mars Exploration Rover Opportunity exited "Endurance Crater." By utilizing the rover's scientific instruments, data was collected to make a qualitative assessment of the performance of the heatshield. This data was gathered to gain a better understanding of how the heatshield performed during entry through the Martian atmosphere. In addition, this unprecedented look at the heatshield offered engineers the opportunity to assess if any unexpected anomalies occurred. Once a survey of the heatshield debris was completed, multiple targets of interest were chosen for the collection of imaging data. This data was then used to assess the char depth of the thermal protection material, which compared well with design and post-flight computational predictions. Extensive imaging data was collected and showed the main seal in pristine conditions, and no observable indications of structure overheating. Additionally, unexpected vehicle dynamics during the atmospheric entry were explained by the observation of thermal blanket remnants attached to the heatshield.

Mars Exploration Rovers↗
NASA NTRS2008

The Mid-infrared Spectrum of the Transiting Exoplanet HD 209458b

We report the spectroscopic detection of mid-infrared emission from the transiting exoplanet HD 209458b. Using archive data taken with the Spitzer IRS instrument, we have determined the spectrum of HD 209458b between 7.46 and 15.25 micrometers. We have used two independent methods to determine the planet spectrum, one differential in wavelength and one absolute, and find the results are in good agreement. Over much of this spectral range, the planet spectrum is consistent with featureless thermal emission. Between 7.5 and 8.5 m, we find evidence for an unidentified spectral feature. If this spectral modulation is due to absorption, it implies that the dayside vertical temperature profile of the planetary atmosphere is not entirely isothermal. Using the IRS data, we have determined the broadband eclipse depth to be 0:00315 +/- 0:000315, implying significant redistribution of heat from the dayside to the nightside. This work required the development of improved methods for Spitzer IRS data calibration that increase the achievable absolute calibration precision and dynamic range for observations of bright point sources.

data analysis↗
NASA NTRS2012

Flexible Ablators Char Depths LHMEL Test Results

Char and pyrolysis zone depths give physical evidence of peak temperature reached in depth: The pyrolyzing material acts as a temperature indicator within its characteristic thermal decomposition range. A matrix of novel flexible ablators were laser tested in one component of material screening for NASA Entry, Descent and Landing research for future Mars missions. LHMEL tests were run both on virgin materials, and on previously charred materials for a dual pulse simulation of the heating due to aerocapture followed by atmospheric entry. The test models were machined to expose the cross-sections. Char measurements were made at three locations near the center of the exposed area. Data are presented showing the char depths developed in these flexible materials, grouped by reinforcing fiber and pyrolyzing material type.

White, Susan↗
DOE OSTI2021

Hurricanes alter 10 Be concentrations in tropical river sediment but do not change regional erosion rate estimates

Tropical islands, including many in island arcs, are subjected to recurring disturbances from extreme storms such as tropical cyclones. To test whether such storms influence cosmogenic nuclide concentrations such that they do not reflect long-term rates of erosion, we measured meteoric and in situ 10Be in river sediment samples from Dominica, an andesitic island in the Caribbean, before and after category five Hurricane Maria (2017). Populations of before- and after-storm concentrations are statistically indistinguishable (n=7 pairs for in situ 10 Be, n=11 pairs for meteoric 10 Be). 10 Be concentrations vary from -138% to +73% within before-after sample pairs relative to the mean of the pair. These new data suggest that the effects of extreme storms on the depth and amount of near-surface erosion on Dominica vary spatially. Our data support calculations of Niemi, et al. (2005) and Yanites, et al. (2009) suggesting that basin-by-basin comparisons of erosion rates based on cosmogenic nuclides should be approached with caution in small (<~100 km 2 ) watersheds affected by mass movements and extreme storms. Erosion rates determined from in situ 10Be in Dominica (geometric mean=0.102 mm y-1, n=12) are low compared to similarly steep and wet areas globally and correlate positively with the spatial density of mass movements.

58 GEOSCIENCES↗
DOE OSTI2023

Automated fault detection and diagnosis of airflow and refrigerant charge faults in residential HVAC systems using IoT-enabled measurements

While automated fault detection and diagnosis (AFDD) in residential heating, ventilation, and air-conditioning (HVAC) using smart thermostat data is gaining increasing attention in recent times, it still requires in-depth investigation for market adoption, especially with real-life data. Furthermore, this paper proposes an Internet of Things (IoT) - based approach that adds a smart sensor to the smart thermostat data to carry out AFDD. The approach uses a model which predicts enthalpy change across the evaporator and compares the prediction to the measured enthalpy change. Deviations which exceed analytically determined thresholds then signal faults in the HVAC system. The faults detected are either installation related or degradation related. Experimental tests were carried out in four homes located in Norman, Oklahoma. From the tests, installation issues like indoor/outdoor mismatch were detected in two homes, while a 30% low charge and low indoor airflow rate were detected in one home. The results show that the proposed AFDD algorithm was able to successfully detect two prevalent faults, namely low indoor airflow and low refrigerant charge. Unlike most of the smart thermostat-based approaches, the proposed IoT-based approach can detect and diagnose both faults but only require one additional sensor which is provided by smart thermostat manufacturers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1973

Reflectance measurements for the detection and mapping of soil limitations

During 1971 and 1972 research was conducted on two fallow fields in the proposed Oahe Irrigation Project to investigate the relationship between the tonal variations observed on aerial photographs and the principal soil limitations of the area. A grid sampling procedure was used to collected detailed field data during the 1972 growing season. The field data was compared to imagery collected on May 14, 1971 at 3050 meters altitude. The imagery and field data were initially evaluated by a visual analysis. Correlation and regression analysis revealed a highly significant correlation and regression analysis revealed a highly significant correlation between the digitized color infrared film data and soil properties such as organic matter content, color, depth to carbonates, bulk density and reflectivity. Computer classification of the multiemulsion film data resulted in maps delineating the areas containing claypan and erosion limitations. Reflectance data from the red spectral band provided the best results.

Benson, L. A.↗
DOE OSTI2022

Depth-resolved Laue microdiffraction with coded apertures

A rapid data acquisition and reconstruction method is introduced to image the crystalline structure of materials and the associated strain and orientations at micrometre resolution using Laue diffraction. The method relies on scanning a coded aperture across the diffracted X-ray beam from broadband illumination and a reconstruction algorithm to resolve Laue microdiffraction patterns as a function of depth along the incident illumination path. It provides rapid access to full diffraction information for sub-micrometre volume elements in bulk materials. Both the theory and the experimental validation of this imaging approach are presented in this report.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Improvement of Aerosol Optical Depth Retrieval from MODIS Spectral Reflectance over the Global Ocean Using New Aerosol Models Archived from AERONET Inversion Data and Tri-axial Ellipsoidal Dust Database

New over-ocean aerosol models are developed by integrating the inversion data from the Aerosol Robotic Network (AERONET) sun/sky radiometers with a database for the optical properties of tri-axial ellipsoid particles. The new aerosol models allow more accurate retrieval of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) in the case of high AOD (AOD greater than 0.3). The aerosol models are categorized by using the fine-mode fraction (FMF) at 550 nm and the singlescattering albedo (SSA) at 440 nm from the AERONET inversion data to include a variety of aerosol types found around the globe. For each aerosol model, the changes in the aerosol optical properties (AOPs) as functions of AOD are considered to better represent aerosol characteristics. Comparisons of AODs between AERONET and MODIS for the period from 2003 to 2010 show that the use of the new aerosol models enhances the AOD accuracy with a Pearson coefficient of 0.93 and a regression slope of 0.99 compared to 0.92 and 0.85 calculated using the MODIS Collection 5 data. Moreover, the percentage of data within an expected error of +/-(0.03 + 0.05xAOD) is increased from 62 percent to 64 percent for overall data and from 39 percent to 51 percent for AOD greater than 0.3. Errors in the retrieved AOD are further characterized with respect to the Angstrom exponent (AE), scattering angle, SSA, and air mass factor (AMF). Due to more realistic AOPs assumptions, the new algorithm generally reduces systematic errors in the retrieved AODs compared with the current operational algorithm. In particular, the underestimation of fine-dominated AOD and the scattering angle dependence of dust-dominated AOD are significantly mitigated as results of the new algorithm's improved treatment of aerosol size distribution and dust particle nonsphericity.

aerosol optical depth↗