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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

In-Situ and Remotely-Sensed Observations of Biomass Burning Aerosols at Doi Ang Khang, Thailand During 7-SEAS BASELInE 2015

The spring 2015 deployment of a suite of instrumentation at Doi Ang Khang (DAK) in northwestern Thailand enabled the characterization of air masses containing smoke aerosols from burning predominantly in Myanmar. Aerosol Robotic Network (AERONET) Sun photometer data were used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 "Deep Blue" aerosol optical depth (AOD) retrievals; MODIS Terra and Aqua provided results of similar quality, with correlation coefficients of 0.93-0.94 and similar agreement within expected uncertainties to global-average performance. Scattering and absorption measurements were used to compare surface and total column aerosol single scatter albedo (SSA); while the two were well-correlated, and showed consistent positive relationships with moisture (increasing SSA through the season as surface relative humidity and total columnar water vapor increased), in situ surface-level SSA was nevertheless significantly lower by 0.12-0.17. This could be related to vertical heterogeneity and/or instrumental issues. DAK is at approximately 1,500 meters above sea level in heterogeneous terrain, and the resulting strong diurnal variability in planetary boundary layer depth above the site leads to high temporal variability in both surface and column measurements, and acts as a controlling factor to the ratio between surface particulate matter (PM) levels and column AOD. In contrast, while some hygroscopic effects were observed relating to aerosol particle size and Angstrom exponent, relative humidity variations appear to be less important for this ratio here. As part of the Seven South-East Asian Studies (7-SEAS) project, the Biomass-burning Aerosols & Stratocumulus Environment: Lifecycles and Interactions Experiment (BASELInE) was intended to probe physicochemical processes, interactions, and feedbacks related to biomass burning aerosols and clouds during the spring burning season (February-April) in southeast Asia (SEA).

biomass burning↗
NASA NTRS2018

Toward Long-Term Aquatic Science Products from Heritage Landsat Missions

This paper aims at generating a long-term consistent record of Landsat-derived remote sensing reflectance (Rrs) products, which are central for producing downstream aquatic science products (e.g., concentrations of total suspended solids). The products are derived from Landsat-5 and Landsat-7 observations leading to Landsat-8 era to enable retrospective analyses of inland and nearshore coastal waters. In doing so, the data processing was built into the SeaWiFS Data Analysis System (SeaDAS) followed by vicariously calibrating Landsat-7 and -5 data using reference in situ measurements and near-concurrent ocean color products, respectively. The derived Rrs products are then validated using (a) matchups using the Aerosol Robotic Network (AERONET) data measured by in situ radiometers, i.e., AERONET-OC, and (b) ocean color products at select sites in North America. Following the vicarious calibration adjustments, it is found that the overall biases in Rrs products are significantly reduced. The root-mean-square errors (RMSE), however, indicate noticeable uncertainties due to random and systematic noise. Long-term (since 1984) seasonal Rrs composites over 12 coastal and inland systems are further evaluated to explore the utility of Landsat archive processed via SeaDAS. With all the qualitative and quantitative assessments, it is concluded that with careful algorithm developments, it is possible to discern natural variability in historic water quality conditions using heritage Landsat missions. This requires the changes in Rrs exceed maximum expected uncertainties, i.e., 0.0015 [1/sr], estimated from mean RMSEs associated with the matchups and intercomparison analyses. It is also anticipated that Landsat-5 products will be less susceptible to uncertainties in turbid waters with Rrs(660) > 0.004 [1/sr], which is equivalent of ~1.2% reflectance. Overall, end-users may utilize heritage Rrs products with "fitness-for-purpose" concept in mind, i.e., products could be valuable for one application but may not be viable for another. Further research should be dedicated to enhancing atmospheric correction to account for non-negligible near-infrared reflectance in CDOM-rich and extremely turbid waters.

Pahlevan, Nima↗
NASA NTRS2022

Thermal Hydraulic Disaggregation of SMAP Soil Moisture Over the Continental United States

Thermal Hydraulic disaggregation of Soil Moisture (THySM) algorithm was implemented to downscale NASA’s Soil Moisture Active Passive (SMAP) Enhanced soil moisture (SM) product to 1 km over the continental United States (CONUS). This algorithm was developed by combining thermal inertia theory with a soil hydraulic-based approach that considers fine-scale SM spatial distribution driven by both heat fluxes and hydraulic conductivity in soils. Relative soil wetness values were estimated using land surface temperature and normalized difference vegetation index for the thermal inertia model and using soil properties for the hydraulic model. The relative soil wetness values at 1 km from both models were then combined by using weighting functions whereby the spatial distribution of SM was governed more by thermal fluxes during times of strong heat transport and infiltration during moisture abundant soil conditions. THySM values were evaluated using in situ SM measurements from SMAP Core Validation Sites (CVS), the USDA Soil Climate Analysis Network, and the NOAA Climate Reference Network over CONUS. THySM shows higher accuracy than the SMAP / Sentinel-1 (SPL2SMAP_S) 1 km SM product when compared to in situ measurements. The accuracy of THySM is 0.048 m3/m3 based on unbiased root mean square error (ubRMSE), outperforming SPL2SMAP_S by 0.01-0.02 m3/m3. The ubRMSE of THySM 1km SM over the SMAP grassland/rangeland-dominated CVS sites is better than 0.04 m3/m3, which meets the SMAP mission SM accuracy requirement applied at 9 and 36 km.

SMAP↗
NASA NTRSDate not supplied

Hazardous Meteor Showers and their Fluxes

NASA's meteoroid environment office generates annual forecasts of meteor shower activity. This presentation reviews several recent and current efforts to improve these forecasts by testing the significance of the included showers, validating their mass distributions using observations from independent networks, and examining the relationship between meteoroid mass and peak brightness.

Althea Moorhead↗
NASA NTRS2014

Sao Paulo Lightning Mapping Array (SP-LMA): Network Assessment and Analyses for Intercomparison Studies and GOES-R Proxy Activities

A 12 station Lightning Mapping Array (LMA) network was deployed during October 2011 in the vicinity of Sao Paulo, Brazil (SP-LMA) to contribute total lightning measurements to an international field campaign [CHUVA - Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)]. The SP-LMA was operational from November 2011 through March 2012 during the Vale do Paraiba campaign. Sensor spacing was on the order of 15-30 km, with a network diameter on the order of 40-50km. The SP-LMA provides good 3-D lightning mapping out to 150 km from the network center, with 2-D coverage considerably farther. In addition to supporting CHUVA science/mission objectives, the SP-LMA is supporting the generation of unique proxy data for the Geostationary Lightning Mapper (GLM) and Advanced Baseline Imager (ABI), on NOAA's Geostationary Operational Environmental Satellite-R (GOES-R: scheduled for a 2015 launch). These proxy data will be used to develop and validate operational algorithms so that they will be ready to use on "day1" following the GOES-R launch. As the CHUVA Vale do Paraiba campaign opportunity was formulated, a broad community-based interest developed for a comprehensive Lightning Location System (LLS) intercomparison and assessment study, leading to the participation and/or deployment of eight other ground-based networks and the space-based Lightning Imaging Sensor (LIS). The SP-LMA data is being intercompared with lightning observations from other deployed lightning networks to advance our understanding of the capabilities/contributions of each of these networks toward GLM proxy and validation activities. This paper addresses the network assessment including noise reduction criteria, detection efficiency estimates, and statistical and climatological (both temporal and spatially) analyses for intercomparison studies and GOES-R proxy activities.

Bailey, J. C.↗
NASA NTRS2009

NASA Global Precipitation Mission Ground Validation Implementation

The Global Precipitation Mission (GPM; core-satellite launch 2013) will provide Ka/Ku-band dual-frequency precipitation radar (DPR) and accompanying passive microwave radiometer-diagnosed precipitation estimates over a latitude range of 65 N to 65 S. The extended latitudinal domain of GPM coverage combined with requirements to detect (and in the case of liquid, estimate) liquid and frozen precipitation rates for values ranging from several hundred to just a few tenths of a millimeter per hour present new challenges to the development of physically-based satellite precipitation retrieval algorithms. On regional scales select national and international resources such as existing calibrated radar and rain gauge networks can provide basic datasets that enable direct statistical validation of GPM core-satellite reflectivitys and core/constellation rain rate measurements. Near-term planned field campaign involvements include Finland/Baltic Sea (fall 2010; joint CloudSat,GPM, and European study of precipitation in low-altitude melting layers and snowfall in the vicinity of the Helsinki testbed), central Oklahoma (spring 2011; joint with DOE ARM- precipitation retrievals over a mid-latitude continental land surface), and the Great Lakes region (winter 2011-12, snowfall retrieval).

Petersen, Walter A.↗
NASA NTRS2021

Evaluation of vicarious calibration for airborne sensors using RadCalNet

Vicarious calibration approaches using in-situ measurements are key techniques applied to on-orbit remote sensors. The in-situ measurements have advantages in terms of traceability and quantifiable accuracy that make them ideal for inter-consistency studies of on-orbit sensors. The Committee on Earth Observation Satellites Working Group on Calibration and Validation Infrared Visible Optical Sensors initiated the Radiometric Calibration Network (RadCalNet) to provide automated surface and top-of-atmosphere (TOA) reflectance data from multiple participating ground sites to the worldwide user community. RadCalNet standardizes protocols for collecting data, processes TOA reflectance, and provides International System of Units traceable uncertainty budgets for the five currently operating sites. RadCalNet data from the Railroad Valley Playa, Nevada, site was used to provide an SI-traceable, absolute radiometric calibration of the Enhanced MODIS Airborne Simulator as part of an overflight of opportunity during the FIREX-AQ campaign. The results shown here demonstrate the utility of RadCalNet data for absolute radiometric calibration of airborne imagers making flights of opportunity without the need for coordination with a field validation team.

Sensors↗
NASA NTRS2020

Genetic Algorithm for Optimization of Neural Networks for Bayesian Inference of Model Uncertainty

The objective of this work was to develop a genetic optimization algorithm that can design a neural network capable of producing uncertainty estimates along with predictions. This algorithm is necessary because the inclusion of uncertainty modeling in a neural network greatly complicates the network’s design space, making the development of a converging model extremely difficult and time consuming. The genetic algorithm presented in this work uses a number of value ranges for various configurable neural network parameters to create a randomly generated population of network architectures. The initially generated population is then evolved over the course of several generations, with the best performing models breeding to produce novel network configurations. Mutations are randomly applied to the network designs to facilitate the development of adaptations beneficial to the task being performed. An experiment was conducted to validate the proposed algorithm, in which the genetic optimizer was tasked with producing a neural network capable of predicting the sound pressure level (SPL) resulting from jet-surface interaction (JSI) noise. The data used for this task was generated at the NASA Glenn Research Center in the Aero-Acoustic Propulsion Laboratory. Starting with an initial population size of 35 randomly generated networks, and evolved over the course of 10 generations, the genetic algorithm produced a design able to predict SPL as a result of JSI noise within 0.272 dB, on average.

Genetic algorithm↗
NASA NTRS2010

MACHETE: Environment for Space Networking Evaluation

Space Exploration missions requires the design and implementation of space networking that differs from terrestrial networks. In a space networking architecture, interplanetary communication protocols need to be designed, validated and evaluated carefully to support different mission requirements. As actual systems are expensive to build, it is essential to have a low cost method to validate and verify mission/system designs and operations. This can be accomplished through simulation. Simulation can aid design decisions where alternative solutions are being considered, support trade-studies and enable fast study of what-if scenarios. It can be used to identify risks, verify system performance against requirements, and as an initial test environment as one moves towards emulation and actual hardware implementation of the systems. We describe the development of Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) and its use cases in supporting architecture trade studies, protocol performance and its role in hybrid simulation/emulation. The MACHETE environment contains various tools and interfaces such that users may select the set of tools tailored for the specific simulation end goal. The use cases illustrate tool combinations for simulating space networking in different mission scenarios. This simulation environment is useful in supporting space networking design for planned and future missions as well as evaluating performance of existing networks where non-determinism exist in data traffic and/or link conditions.

Jennings, Esther H.↗
NASA NTRS1995

Infrared algorithm development for ocean observations

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared retrievals. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, and participation in MODIS (project) related activities. Efforts in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, involvement in field studies, production and evaluation of new computer networking strategies, and objective analysis approaches.

Brown, Otis B.↗
NASA NTRS2000

Performance Evaluation of the NASA/KSC Transmission System

NASA-KSC currently uses three bridged 100-Mbps FDDI segments as its backbone for data traffic. The FDDI Transmission System (FTXS) connects the KSC industrial area, KSC launch complex 39 area, and the Cape Canaveral Air Force Station. The report presents a performance modeling study of the FTXS and the proposed ATM Transmission System (ATXS). The focus of the study is on performance of MPEG video transmission on these networks. Commercial modeling tools - the CACI Predictor and Comnet tools - were used. In addition, custom software tools were developed to characterize conversation pairs in Sniffer trace (capture) files to use as input to these tools. A baseline study of both non-launch and launch day data traffic on the FTXS is presented. MPEG-1 and MPEG-2 video traffic was characterized and the shaping of it evaluated. It is shown that the characteristics of a video stream has a direct effect on its performance in a network. It is also shown that shaping of video streams is necessary to prevent overflow losses and resulting poor video quality. The developed models can be used to predict when the existing FTXS will 'run out of room' and for optimizing the parameters of ATM links used for transmission of MPEG video. Future work with these models can provide useful input and validation to set-top box projects within the Advanced Networks Development group in NASA-KSC Development Engineering.

Christensen, Kenneth J.↗
NASA NTRS2016

An Optimal-Estimation-Based Aerosol Retrieval Algorithm Using OMI Near-UV Observations

An optimal-estimation(OE)-based aerosol retrieval algorithm using the OMI (Ozone Monitoring Instrument) near-ultraviolet observation was developed in this study. The OE-based algorithm has the merit of providing useful estimates of errors simultaneously with the inversion products. Furthermore, instead of using the traditional lookup tables for inversion, it performs online radiative transfer calculations with the VLIDORT (linearized pseudo-spherical vector discrete ordinate radiative transfer code) to eliminate interpolation errors and improve stability. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved aerosol optical thickness (AOT) and single scattering albedo (SSA). The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The OEbased estimated error represented the variance of actual biases of AOT at 388 nm between the retrieval and AERONET measurements better than the operational error estimates. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface reflectance at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine-mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for relevant studies. Detailed advantages of using the OE method were described and discussed in this paper.

Air Pollution↗
NASA NTRS1994

Infrared algorithm development for ocean observations with EOS/MODIS

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared retrievals. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, and participation in MODIS (project) related activities. Efforts in this contract period have focused on radiative transfer modeling and evaluation of atmospheric path radiance efforts on SST estimation, exploration of involvement in ongoing field studies, evaluation of new computer networking strategies, and objective analysis approaches.

Brown, Otis B.↗
NASA NTRS1995

Validation of the SINDA/FLUINT code using several analytical solutions

The Systems Improved Numerical Differencing Analyzer and Fluid Integrator (SINDA/FLUINT) code has often been used to determine the transient and steady-state response of various thermal and fluid flow networks. While this code is an often used design and analysis tool, the validation of this program has been limited to a few simple studies. For the current study, the SINDA/FLUINT code was compared to four different analytical solutions. The thermal analyzer portion of the code (conduction and radiative heat transfer, SINDA portion) was first compared to two separate solutions. The first comparison examined a semi-infinite slab with a periodic surface temperature boundary condition. Next, a small, uniform temperature object (lumped capacitance) was allowed to radiate to a fixed temperature sink. The fluid portion of the code (FLUINT) was also compared to two different analytical solutions. The first study examined a tank filling process by an ideal gas in which there is both control volume work and heat transfer. The final comparison considered the flow in a pipe joining two infinite reservoirs of pressure. The results of all these studies showed that for the situations examined here, the SINDA/FLUINT code was able to match the results of the analytical solutions.

Keller, John R.↗
NASA NTRS2003

A Dynamic Optimization Technique for Siting the NASA-Clark Atlanta Urban Rain Gauge Network (NCURN)

NASA satellites and ground instruments have indicated that cities like Atlanta, Georgia may create or alter rainfall. Scientists speculate that the urban heat island caused by man-made surfaces in cities impact the heat and wind patterns that form clouds and rainfall. However, more conclusive evidence is required to substantiate findings from satellites. NASA, along with scientists at Clark Atlanta University, are implementing a dense, urban rain gauge network in the metropolitan Atlanta area to support a satellite validation program called Studies of PRecipitation Anomalies from Widespread Urban Landuse (SPRAWL). SPRAWL will be conducted during the summer of 2003 to further identify and understand the impact of urban Atlanta on precipitation variability. The paper provides an. overview of SPRAWL, which represents one of the more comprehensive efforts in recent years to focus exclusively on urban-impacted rainfall. The paper also introduces a novel technique for deploying rain gauges for SPRAWL. The deployment of the dense Atlanta network is unique because it utilizes Geographic Information Systems (GIS) and Decision Support Systems (DSS) to optimize deployment of the rain gauges. These computer aided systems consider access to roads, drainage systems, tree cover, and other factors in guiding the deployment of the gauge network. GIS and DSS also provide decision-makers with additional resources and flexibility to make informed decisions while considering numerous factors. Also, the new Atlanta network and SPRAWL provide a unique opportunity to merge the high-resolution, urban rain gauge network with satellite-derived rainfall products to understand how cities are changing rainfall patterns, and possibly climate.

Shepherd, J. Marshall↗
NASA NTRS1995

Performance Modeling of Network-Attached Storage Device Based Hierarchical Mass Storage Systems

Network attached storage devices improve I/O performance by separating control and data paths and eliminating host intervention during the data transfer phase. Devices are attached to both a high speed network for data transfer and to a slower network for control messages. Hierarchical mass storage systems use disks to cache the most recently used files and a combination of robotic and manually mounted tapes to store the bulk of the files in the file system. This paper shows how queuing network models can be used to assess the performance of hierarchical mass storage systems that use network attached storage devices as opposed to host attached storage devices. Simulation was used to validate the model. The analytic model presented here can be used, among other things, to evaluate the protocols involved in 1/0 over network attached devices.

Menasce, Daniel A.↗
NASA NTRS2012

Miniaturized Laser Heterodyne Radiometer (LHR) for Measurements of Greenhouse Gases in the Atmospheric Column

This passive laser heterodyne radiometer (LHR) instrument simultaneously measures multiple trace gases in the atmospheric column including carbon dioxide (CO2) and methane (CH4), and resolves their concentrations at different altitudes. This instrument has been designed to operate in tandem with the passive aerosol sensor currently used in AERONET (an established network of more than 450 ground aerosol monitoring instruments worldwide). Because aerosols induce a radiative effect that influences terrestrial carbon exchange, simultaneous detection of aerosols with these key carbon cycle gases offers a uniquely comprehensive measurement approach. Laser heterodyne radiometry is a technique for detecting weak signals that was adapted from radio receiver technology. In a radio receiver, a weak input signal from a radio antenna is mixed with a stronger local oscillator signal. The mixed signal (beat note, or intermediate frequency) has a frequency equal to the difference between the input signal and the local oscillator. The intermediate frequency is amplified and sent to a detector that extracts the audio from the signal. In the LHR instrument described here, sunlight that has undergone absorption by the trace gas is mixed with laser light at a frequency matched to a trace gas absorption feature in the infrared (IR). Mixing results in a beat signal in the RF (radio frequency) region that can be related to the atmospheric concentration. For a one-second integration, the estimated column sensitivities are 0.1 ppmv for CO2, and <1 ppbv for CH4. In addition to producing a standalone ground measurement product, this instrument could be used to calibrate/validate four Earth observing missions: ASCENDS (Active Sensing of CO2 Emissions over Nights, Days, and Seasons), OCO-2 (Orbiting Carbon Observatory), OCO-3, and GOSAT (Greenhouse gases Observational SATellite). The only network that currently measures CO2 and CH4 in the atmospheric column is TCCON (Total Carbon Column Observing Network), and only two of its 16 operational sites are in the United States. TCCON data is used for validation of GOSAT data, and will be used for OCO-2 validation. While these Fourier-transform spectrometers (FTS) can measure the largest range of trace gases, the network is severely limited due to the high cost and extreme size of these instruments (these occupy small buildings and require personnel for operation). The LHR/AERONET instrument offers a significantly smaller (carry-on luggage size) autonomous instrument that can be incorporated into AERONET s much larger (450 instruments) global network.

Steel, Emily↗