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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Passive Thermal Compensation of the Optical Bench of the Galaxy Evolution Explorer

The Galaxy Evolution Explorer is an orbiting space telescope that will collect information on star formation by observing galaxies and stars in ultraviolet wavelengths. The optical bench supporting detectors and related optical components used an interesting and unusual passive thermal compensation technique to accommodate thermally-induced focal length changes in the optical system. The proposed paper will describe the optical bench thermal compensation design including concept, analysis, assembly and testing results.

optomechanical design↗
NASA NTRS2012

Cost-Effective Telemetry and Command Ground Systems Automation Strategy for the Soil Moisture Active Passive (SMAP) Mission

Soil Moisture Active Passive (SMAP) is an Earth-orbiting, remote-sensing NASA mission slated for launch in 2014.[double dagger] The ground data system (GDS) being developed for SMAP is composed of many heterogeneous subsystems, ranging from those that support planning and sequencing to those used for real-time operations, and even further to those that enable science data exchange. A full end-to-end automation of the GDS may result in cost savings during mission operations, but it would require a significant upfront investment to develop such comprehensive automation. As demonstrated by the Jason-1 and Wide-field Infrared Survey Explorer (WISE) missions, a measure of "lights-out" automation for routine, orbital pass ground operations can still reduce mission cost through smaller staffing of operators and limited work hours. The challenge, then, for the SMAP GDS engineering team is to formulate an automated operations strategy--and corresponding system architecture--to minimize operator intervention during operations, while balancing the development cost associated with the scope and complexity of automation. This paper discusses the automated operations approach being developed for the SMAP GDS. The focus is on automating the activities involved in routine passes, which limits the scope to real-time operations. A key subsystem of the SMAP GDS--NASA's AMMOS Mission Data Processing and Control System (AMPCS)--provides a set of capabilities that enable such automation. Also discussed are the lights-out pass automations of the Jason-1 and WISE missions and how they informed the automation strategy for SMAP. The paper aims to provide insights into what is necessary in automating the GDS operations for Earth satellite missions.

remote-sensing↗
NASA NTRS2012

Evaluation of Precipitation Detection over Various Surfaces from Passive Microwave Imagers and Sounders

During the middle part of this decade a wide variety of passive microwave imagers and sounders will be unified in the Global Precipitation Measurement (GPM) mission to provide a common basis for frequent (3 hr), global precipitation monitoring. The ability of these sensors to detect precipitation by discerning it from non-precipitating background depends upon the channels available and characteristics of the surface and atmosphere. This study quantifies the minimum detectable precipitation rate and fraction of precipitation detected for four representative instruments (TMI, GMI, AMSU-A, and AMSU-B) that will be part of the GPM constellation. Observations for these instruments were constructed from equivalent channels on the SSMIS instrument on DMSP satellites F16 and F17 and matched to precipitation data from NOAA's National Mosaic and QPE (NMQ) during 2009 over the continuous United States. A variational optimal estimation retrieval of non-precipitation surface and atmosphere parameters was used to determine the consistency between the observed brightness temperatures and these parameters, with high cost function values shown to be related to precipitation. The minimum detectable precipitation rate, defined as the lowest rate for which probability of detection exceeds 50%, and the detected fraction of precipitation, are reported for each sensor, surface type (ocean, coast, bare land, snow cover) and precipitation type (rain, mix, snow). The best sensors over ocean and bare land were GMI (0.22 mm/hr minimum threshold and 90% of precipitation detected) and AMSU (0.26 mm/hr minimum threshold and 81% of precipitation detected), respectively. Over coasts (0.74 mm/hr threshold and 12% detected) and snow-covered surfaces (0.44 mm/hr threshold and 23% detected), AMSU again performed best but with much lower detection skill, whereas TMI had no skill over these surfaces. The sounders (particularly over water) benefited from the use of re-analysis data (vs. climatology) to set the a-priori atmospheric state and all instruments benefit from the use of a conditional snow cover emissivity database over land. It is recommended that real-time sources of these data be used in the operational GPM precipitation algorithms.

GPM↗
NASA NTRS2015

An Overview of Production and Validation of the SMAP Passive Soil Moisture Product

The Soil Moisture Active Passive (SMAP) mission is an L-band mission scheduled for launch in Jan. 2015. The SMAP instruments consist of a radar and a radiometer to obtain complementary information from space for soil moisture and freeze/thaw state research and applications. By utilizing novel designs in antenna construction, retrieval algorithms, and acquisition hardware, SMAP provides a capability for global mapping of soil moisture and freeze/thaw state with unprecedented accuracy, resolution, and coverage. This improvement in hydrosphere state measurement is expected to advance our understanding of the processes that link the terrestrial water, energy and carbon cycles, improve our capability in flood prediction and drought monitoring, and enhance our skills in weather and climate forecast. For swath-based soil moisture measurement, SMAP generates three operational geophysical data products: (1) the radiometer-only soil moisture product (L2_SM_P) posted at 36-kilometer resolution, (2) the radar-only soil moisture product (L2_SM_A) posted at 3-kilometers resolution, and (3) the radar-radiometer combined soil moisture product (L2_SM_AP) posted at 9-kilometers resolution. Each product draws on the strengths of the underlying sensor(s) and plays a unique role in hydroclimatological and hydrometeorological applications. A full suite of SMAP data products is given in Table 1.

passive microwave↗
NASA NTRS2015

Alternative to Nitric Acid Passivation

The Ground Systems Development and Operations (GSDO) Program at NASA John F. Kennedy Space Center (KSC), Florida, has the primary objective of modernizing and transforming the launch and range complex at KSC to benefit current and future NASA programs along with other emerging users. Described as the launch support and infrastructure modernization program in the NASA Authorization Act of 2010, the GSDO Program will develop and implement shared infrastructure and process improvements to provide more flexible, affordable, and responsive capabilities to a multi-user community. In support of NASA and the GSDO Program, the objective of this project is to qualify citric acid as an environmentally-preferable alternative to nitric acid for passivation of stainless steel alloys. This project is a direct follow-on to United Space Alliance (USA) work at KSC to optimize the parameters for the use of citric acid and verify effectiveness. This project will build off of the USA study to further evaluate citric acids effectiveness and suitability for corrosion protection of a number of stainless steels alloys used by NASA, the Department of Defense (DoD), and the European Space Agency (ESA).

stainless steel↗
NASA NTRS2016

NASA Soil Moisture Active Passive Mission Status and Science Performance

The Soil Moisture Active Passive (SMAP) observatory was launched January 31, 2015, and its L-band radiometer and radar instruments became operational since mid-April 2015. The SMAP radiometer has been operating flawlessly, but the radar transmitter ceased operation on July 7. This paper provides a status summary of the calibration and validation of the SMAP instruments and the quality assessment of its soil moisture and freeze/thaw products. Since the loss of the radar in July, the SMAP project has been conducting two parallel activities to enhance the resolution of soil moisture products. One of them explores the Backus Gilbert optimum interpolation and de-convolution techniques based on the oversampling characteristics of the SMAP radiometer. The other investigates the disaggregation of the SMAP radiometer data using the European Space Agency's Sentinel-1 C-band synthetic radar data to obtain soil moisture products at about 1 to 3 kilometers resolution. In addition, SMAP's L-band data have found many new applications, including vegetation opacity, ocean surface salinity and hurricane ocean surface wind mapping. Highlights of these new applications will be provided.

hydroclimatology↗
NASA NTRS2017

Radio Frequency Interference Detection for Passive Remote Sensing Using Eigenvalue Analysis

Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels. Simulated tests show that the proposed detector outperforms conventional kurtosis-based RFI detectors in the low-to-medium interference-to-noise-power-ratio (INR) regime under continuous wave (CW) and quadrature phase shift keying (QPSK) RFIs.

kurtosis↗
NASA NTRS2017

Radio Frequency Interference Detection for Passive Remote Sensing Using Eigenvalue Analysis

Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels. Simulated tests show that the proposed detector outperforms conventional kurtosis-based RFI detectors in the low-to-medium interferece-to-noise-power-ratio (INR) regime under continuous wave (CW) and quadrature phase shift keying (QPSK) RFIs.

Passive remote sensing↗
NASA NTRS2017

Assessment of Version 4 of the SMAP Passive Soil Moisture Standard Product

NASAs Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2-3 days. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAPs radiometer-derived standard soil moisture product (L2SMP) provides soil moisture estimates posted on a 36-km fixed Earth grid using brightness temperature observations and ancillary data. A beta quality version of L2SMP was released to the public in October, 2015, Version 3 validated L2SMP soil moisture data were released in May, 2016, and Version 4 L2SMP data were released in December, 2016. Version 4 data are processed using the same soil moisture retrieval algorithms as previous versions, but now include retrieved soil moisture from both the 6 am descending orbits and the 6 pm ascending orbits. Validation of 19 months of the standard L2SMP product was done for both AM and PM retrievals using in situ measurements from global core calval sites. Accuracy of the soil moisture retrievals averaged over the core sites showed that SMAP accuracy requirements are being met.

SMAP↗
NASA NTRS2017

Skillful Spring Forecasts of September Arctic Sea Ice Extent Using Passive Microwave Data

In this study, we demonstrate skillful spring forecasts of detrended September Arctic sea ice extent using passive microwave observations of sea ice concentration (SIC) and melt onset (MO). We compare these to forecasts produced using data from a sophisticated melt pond model, and find similar to higher skill values, where the forecast skill is calculated relative to linear trend persistence. The MO forecasts shows the highest skill in March-May, while the SIC forecasts produce the highest skill in June-August, especially when the forecasts are evaluated over recent years (since 2008). The high MO forecast skill in early spring appears to be driven primarily by the presence and timing of open water anomalies, while the high SIC forecast skill appears to be driven by both open water and surface melt processes. Spatial maps of detrended anomalies highlight the drivers of the different forecasts, and enable us to understand regions of predictive importance. Correctly capturing sea ice state anomalies, along with changes in open water coverage appear to be key processes in skillfully forecasting summer Arctic sea ice.

melt onset↗
NASA NTRSDate not supplied

Delamination Depth Imaging for Quasi-Static and Fatigue Load Testing Using Passive Thermography

Passive thermography is used to monitor small increases in temperature resulting from delamination damage formation in composite hat-stiffened panels during both quasi-static and fatigue loading. It has been observed that rapid damage formation produces heating. This is composed of two heat generation components. The first component is an instantaneous response due to an irreversible thermoelastic strain release. The second component is mechanical heating, at the interface of failure, due to fracture damage. This produces a transient rise in temperature as the heat diffuses to the surface. The first component defines the thermal start time for the transient response. A one-dimensional thermal model is fitted to the data pixel by pixel, to produce imagery of the damage depth. The results are compared to ultrasonic and X-ray CT data.

Passive thermography↗
NASA NTRSDate not supplied

Characterization of Composite Damage Using Passive Thermography

Passive thermography is used to monitor small increases in temperature on a composite structure during loading. A rise in temperature can be attributed to damage formation due to matrix cracking and fiber breaks. An infrared camera allows for imaging the damage location, size, and shape. Recently, a technique has been developed to estimate the depth of the damage in a composite hat-stiffened panel during quasi-static loading. This technique is based on two heat generation components. The first component is an instantaneous thermoelastic response due to a strain release. The second component is mechanical heating, at the interface of failure, due to fracture damage. This second component produces a transient rise in temperature that is a function of the damage depth and thermal diffusivity. The first component defines the thermal start time for the transient response. A one-dimensional thermal model is used to determine the damage depth for a known thermal diffusivity. The results are compared to ultrasonic and X-ray CT data and show good agreement for damage depth.

Thermal nondestructive evaluation↗
NASA NTRS2021

Surface Melting Over the Greenland Ice Sheet Derived From Enhanced Resolution Passive Microwave Brightness Temperatures (1979–2019)

Surface melting is a major component of the Greenland ice sheet surface mass balance, and it affects sea level rise through direct runoff and the modulation of ice dynamics and hydrological processes, supraglacially, englacially and subglacially. Passive microwave (PMW) brightness temperature observations are of paramount importance in studying the spatial and temporal evolution of surface melting due to their long temporal coverage (1979–present) and high temporal resolution (daily). However, a major limitation of PMW datasets has been the relatively coarse spatial resolution, which has historically been of the order of tens of kilometers. Here, we use a newly released PMW dataset (37 GHz, horizontal polarization) made available through a NASA “Making Earth System Data Records for Use in Research Environments” (MeASUREs) program to study the spatiotemporal evolution of surface melting over the Greenland ice sheet at an enhanced spatial resolution of 3.125 km. We assess the outputs of different detection algorithms using data collected by automatic weather stations (AWSs) and the outputs of the Modèle Atmosphérique Régional (MAR) regional climate model. We found that sporadic melting is well captured using a dynamic algorithm based on the outputs of the Microwave Emission Model of Layered Snowpack (MEMLS), whereas a fixed threshold of 245 K is capable of detecting persistent melt. Our results indicate that, during the reference period from 1979 to 2019 (from 1988 to 2019), surface melting over the ice sheet increased in terms of both duration, up to 4.5 (2.9) d per decade, and extension, up to 6.9 % (3.6 %) of the entire ice sheet surface extent per decade, according to the MEMLS algorithm. Furthermore, the melting season started up to 4.0 (2.5) d earlier and ended 7.0 (3.9) d later per decade. We also explored the information content of the enhanced-resolution dataset with respect to the one at 25 km and MAR outputs using a semi-variogram approach. We found that the enhanced product is more sensitive to local-scale processes, thereby confirming the potential of this new enhanced product for monitoring surface melting over Greenland at a higher spatial resolution than the historical products and for monitoring its impact on sea level rise. This offers the opportunity to improve our understanding of the processes driving melting, to validate modeled melt extent at high resolution and, potentially, to assimilate these data in climate models.

Surface melting↗
NASA NTRS2022

Mapping Firn Saturation over Greenland using NASA’s Soil Moisture Active Passive Satellite

Mapping the spatial extent of recently identified englacial hydrological features (i.e., ice slabs and perennial firn aquifers) formed by meters-thick water-saturated firn layers over the percolation facies of the Greenland Ice Sheet using L-band microwave radiometry has recently been demonstrated. However, these initial maps are binary, and do not provide a parameter to estimate the spatial variability in the thickness and volumetric fraction of meltwater stored within the firn pore space. Here, we exploit enhanced-resolution vertical-polarization L-band brightness temperature (T^(B)_(V)) imagery (2015–2019) generated using observations collected over Greenland by NASA’s Soil Moisture Active Passive (SMAP) satellite and a simple two-layer L-band brightness temperature model. We map water-saturated firn layers via a “firn saturation” parameter, and interpret our results together with ice slab and perennial firn aquifer spatial extents, estimates of snow accumulation simulated via the Regional Atmospheric Climate Model (RACMOp2.3), and airborne radar surveys collected via NASA’s Operation IceBridge (OIB) campaigns. We find that variable firn saturation parameter values are mapped in lower snow accumulation ice slab areas in western, northern, and northeastern Greenland, where firn is colder and water-saturated firn layers seasonally refreeze as solid-ice. Higher firn saturation parameter values are mapped in higher snow accumulation perennial firn aquifer areas in southeastern, southern, and northwestern Greenland, where firn is near the melting point, and meters-thick water-saturated firn layers exist. Our results have implications for identifying expansive englacial reservoirs that store significant volumes of meltwater in locations that are vulnerable to meltwater-induced hydrofracturing and accelerated outlet glacier flow year-round.

Greenland ice sheet↗
NASA NTRS2022

The Fourth Stokes Parameter for Geolocation in Passive Microwave Remote Sensing from Space

Polarimetric microwave radiometers such as SMAP are capable of measuring the fourth Stokes parameter in brightness temperature over the Earth surface. The value of this parameter is normally small but exhibits sharp spikes when the scene includes large differences in emission from the surface, such occur at land/water boundaries. In this manuscript, it is shown that these spikes can be used to accurately locate coastlines with potential application to geolocation in passive microwave remote sensing from space. Examples are presented using the L-band radiometer on SMAP, first with theory using calculations with the SMAP antenna pattern and orbit and then with SMAP measurements of the fourth Stokes parameter over Madagascar. Using the SMAP data, the coastline is located with a standard deviation less than 2 km. The results are consistent with the conventional approach used for geolocation of the SMAP radiometer footprint.

Passive Microwave Remote Sensing↗