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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A 1 km soil moisture dataset over eastern CONUS generated by assimilating SMAP data into the Noah-MP land surface model

An improved fine-scale soil moisture (SM) dataset at 1 km grid spacing, covering much of the eastern continental US, was generated by assimilating 9 km Soil Moisture Active Passive (SMAP) SM data into the v4.0.1 Noah-MP land surface model. With 12 ensemble members, the assimilation was carried out using the ensemble Kalman filter algorithm within NASA's Land Information System. The SM analysis for 2016 was fully validated against in situ observations from four different networks and compared with four other existing datasets. Results indicate that this SM analysis surpasses other datasets in top-layer SM distribution, including a machine-learning-based product, despite all SM estimates being less heterogeneous than observed. The analysis of anomalous errors suggests that large similarity in intrinsic errors is likely due to overlapping data sources among the selected SM datasets. More detailed evaluations were performed over two geographic areas. The observations collected by the Atmospheric Radiation Measurement facility in Oklahoma suggest that soil temperature and surface heat fluxes are concurrently simulated with good accuracy. Investigation into the 2016 southeastern US drought response further indicates drier conditions and higher evapotranspiration estimates compared to GLEAMv4.1. Notably, large errors are associated with grids having clay soil textures, underscoring the need for refined model treatments for specific soil types to further improve SM estimates. The dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.14370563 (Tai et al., 2024).

Tai, Sheng-Lun [Pacific Northwest National Laborat↗
NASA NTRS2001

Correlation Studies of Sea Ice Concentration with Surface Temperature and Meltponding

The spatial and temporal variability of sea ice concentrations derived from passive microwave data is studied in conjunction with co-registered high resolution infrared and visible satellite data. Cloud free infrared and visible data provide surface temperature and large scale surface characteristics, respectively, that can be used to better understand regional and seasonal fluctuations in ice concentrations. Results from correlation analysis of ice concentration versus surface temperature data show the intuitively expected negative relationship but the strength in the relationship is unexpectedly very strong. In the Antarctic, the correlation is consistently very high spatially when yearly anomalies are used, and not so high in some areas when seasonal anomalies are used, especially during spring and summer. In the monthly anomalies, the correlation is also good, especially in dynamically active regions. The expanse in the anomalies in surface temperature are shown to go way beyond the sea ice regions into the open ocean and continental areas, suggesting strong atmospheric forcing. Weak correlations are normally found in highly consolidated areas, where large changes in temperature do not cause large changes in ice concentration on a short term, and in open ocean polynya areas, where the change in ice concentration may be cause by melt from the underside of the ice. In the Arctic, strong correlations between surface temperature and ice concentration are evident for all seasons except during the summer. In the summer, factors such as meltponding, surface wetness, and ice breakup, as detected by high resolution visible data, contributes to larger uncertainties in the determination of ice concentration and the lack of good correlation of the variables.

Comiso, J. C.↗
NASA NTRS2017

Assessment of the Impact of Spatial Heterogeneity on Microwave Satellite Soil Moisture Periodic Error

An accurate temporal and spatial characterization of errors is required for the efficient processing, evaluation, and assimilation of remotely-sensed surface soil moisture retrievals. However, empirical evidence exists that passive microwave soil moisture retrievals are prone to periodic artifacts which may complicate their application in data assimilation systems (which commonly treat observational errors as being temporally white). In this paper, the link between such temporally-periodic errors and spatial land surface heterogeneity is examined. Both the synthetic experiment and site-specified cases reveal that, when combined with strong spatial heterogeneity, temporal periodicity in satellite sampling patterns (associated with exact repeat intervals of the polar-orbiting satellites) can lead to spurious high frequency spectral peaks in soil moisture retrievals. In addition, the global distribution of the most prominent and consistent 8-day spectral peak in the Advanced Microwave Scanning Radiometer - Earth Observing System soil moisture retrievals is revealed via a peak detection method. Three spatial heterogeneity indicators - based on microwave brightness temperature, land cover types, and long-term averaged vegetation index - are proposed to characterize the degree to which the variability of land surface is capable of inducing periodic error into satellite-based soil moisture retrievals. Regions demonstrating 8-day periodic errors are generally consistent with those exhibiting relatively higher heterogeneity indicators. This implies a causal relationship between spatial land surface heterogeneity and temporal periodic error in remotely-sensed surface soil moisture retrievals.

Fangni Lei↗
NASA NTRS2022

Leveraging Pre-storm Soil Moisture Estimates for Enhanced Land Surface Model Calibration in Ungauged Hydrologic Basins

Despite long-standing efforts, hydrologists still lack robust tools for calibrating land surface model (LSM) streamflow estimates within ungauged basins. Using surface soil moisture estimates from the Soil Moisture Active Passive Level 4 Soil Moisture (L4_SM) product, precipitation observations, and streamflow gauge measurements for 617 medium-scale (200-10,000 km2) basins in the contiguous United States, we measure the temporal (Spearman) rank correlation between antecedent (i.e., pre-storm) surface soil moisture (ASM) and the storm-scale runoff coefficient (RC; the fraction of storm-scale precipitation accumulation converted into streamflow). In humid and semi-humid basins, this rank correlation is shown to be sufficiently strong to allow for the substitution of storm-scale RC observations (available only in basins that are both lightly regulated and gauged) with high-quality ASM values (available quasi-globally from L4_SM) in streamflow calibration procedures. Using this principle, we define a new, basin-wise LSM streamflow calibration approach based on L4_SM alone and successfully apply it to identify LSM configurations that produce a high rank correlation with observed RC. However, since the approach cannot detect RC bias, it is less successful in identifying LSM configurations with low mean-absolute error. Plain Text Summary Accurately forecasting the fraction of rainfall that runs off into streams, as opposed to infiltrates into the soil, is critical for flash-flood prediction, water-resource monitoring, and tracking the transport of nutrients from agricultural fields into local waterways. Such forecasting is typically performed by hydrologic models that attempt to represent the physical processes responsible for surface runoff generation. However, to provide accurate streamflow forecasts, these models typically need to be calibrated against actual streamflow observations. This is problematic given the relatively poor, and declining, global availability of stream gauges. This paper presents a novel model calibration strategy that uses soil moisture from remote sensing and numerical modeling in place of streamflow observations during calibration. This transition has significant practical advantages because, unlike streamflow observations, the soil moisture data are continuously available across space. Our results demonstrate that this new approach can significantly improve hydrologic models within humid and semi-humid basins lacking sufficient ground-based instrumentation for traditional streamflow calibration.

hydrologic models↗
NASA NTRS2013

Detection Thresholds of Falling Snow From Satellite-Borne Active and Passive Sensors

There is an increased interest in detecting and estimating the amount of falling snow reaching the Earths surface in order to fully capture the global atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms for current and future missions includes determining the thresholds of detection for various active and passive sensor channel configurations and falling snow events over land surfaces and lakes. In this paper, cloud resolving model simulations of lake effect and synoptic snow events were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W-band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR)Ku- and Ka-bands, and the GPM Microwave Imager. Eleven different nonspherical snowflake shapes were used in the analysis. Notable results include the following: 1) The W-band radar has detection thresholds more than an order of magnitude lower than the future GPM radars; 2) the cloud structure macrophysics influences the thresholds of detection for passive channels (e.g., snow events with larger ice water paths and thicker clouds are easier to detect); 3) the snowflake microphysics (mainly shape and density)plays a large role in the detection threshold for active and passive instruments; 4) with reasonable assumptions, the passive 166-GHz channel has detection threshold values comparable to those of the GPM DPR Ku- and Ka-band radars with approximately 0.05 g *m(exp -3) detected at the surface, or an approximately 0.5-1.0-mm * h(exp -1) melted snow rate. This paper provides information on the light snowfall events missed by the sensors and not captured in global estimates.

remote sensing↗
NASA NTRS2018

Global-scale Evaluation of SMAP, SMOS and ASCAT Soil Moisture Products Using Triple Collocation

Global-scale surface soil moisture products are currently available from multiple remote sensing platforms. Footprint-scale assessments of these products are generally restricted to limited number of densely-instrumented validation sites. However, by taking active and passive soil moisture products together with a third independent soil moisture estimates via land surface modeling, triple collocation (TC) can be applied to estimate the correlation metric of satellite soil moisture products (versus an unknown ground truth) over a quasi-global domain. Here, an assessment of Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity (SMOS) and Advanced SCATterometer (ASCAT) surface soil moisture retrievals via TC is presented. Considering the potential violation of TC error assumptions, the impact of active-passive and satellite-model error cross correlations on the TC-derived inter-comparison results is examined at in situ sites using quadruple collocation analysis. In addition, confidence intervals for the TC-estimated correlation metric are constructed from moving-block bootstrap sampling designed to preserve the temporal persistence of the original (unevenly-sampled) soil moisture time-series. This study is the first to apply TC to obtain a robust global-scale cross-assessment of SMAP, SMOS and ASCAT soil moisture retrieval accuracy in terms of anomaly temporal correlation. Our results confirm the overall advantage of SMAP (with a global average anomaly correlation of 0.76) over SMOS (0.66) and ASCAT (0.63) that has been established in several recent regional, ground-based studies. SMAP is also the best-performing product over the majority of applicable land pixels (52%), although SMOS and ASCAT each shows advantage in distinct geographic regions.

global-scale↗
NASA NTRS2020

Satellite Monitoring of Global Surface Soil Organic Carbon Dynamics Using the SMAP Level 4 Carbon Product

Soil organic carbon (SOC) is an important metric of soil health and the terrestrial carbon balance. Short‐term climate variations affect SOC through changes in temperature and moisture, which control vegetation growth and soil decomposition. We evaluated a satellite data‐driven carbon model, operating under the NASA Soil Moisture Active‐Passive (SMAP) mission, as a means of monitoring global surface SOC dynamics. The SMAP Level 4 Carbon (L4C) product estimates a daily global carbon budget including surface (0‐ to 5‐cm depth) SOC. We found that the L4C mean latitudinal SOC distribution is generally consistent with alternative assessments from static soil inventory records and dynamic global vegetation models (r ≥ 0.89). Within forest systems, based on inventory data, L4C SOC is most similar in magnitude to litterfall but is correlated with coarse woody debris ( urn:x-wiley:jgrg:media:jgrg21790:jgrg21790-math-0001) and total SOC ( urn:x-wiley:jgrg:media:jgrg21790:jgrg21790-math-0002). L4C SOC is sensitive to seasonal and annual climate variability, with mean residence times that range from 1.5 years in the wet tropics to 17 years in the cold tundra. Incorporating soil moisture retrievals from the SMAP L‐band (1.4 GHz) microwave radiometer within the L4C algorithm provides enhanced soil moisture sensitivity under low‐to‐moderate vegetation cover (<5 kg/sq.m vegetation water content). The L‐band soil moisture had the greatest impact on the L4C carbon budget in semiarid regions, which span almost 60% of the globe and account for substantial variability in the terrestrial carbon sink. The L4C operational product enables prognostic investigations into effects of recent climate trends and anomalies (e.g., droughts and pluvials) on shallow soil carbon dynamics.

K. Arthur Endsley↗
DOE OSTI2022

Mechanistic Study of Controlled Zinc Electrodeposition Behaviors Facilitated by Nanoscale Electrolyte Additives at the Electrode Interface

Nanoparticle organic hybrid materials (NOHMs) are liquid-like materials composed of an inorganic core to which a polymeric canopy is ionically tethered. NOHMs have unique properties including negligible vapor pressure, high oxidative thermal stability, and the ability to bind to reactive species of interest due to the tunability of their polymeric canopy. This makes them promising multifunctional materials for a wide range of energy and environmental technologies, including electrolyte additives for electrochemical energy storage (e.g., flow batteries) and the electrochemical conversion of CO 2 to chemicals and fuels. Due to their unique transport behaviors in fluid systems, an understanding of the near-electrode surface behavior of NOHMs in electrolyte solutions and their effect on electrochemical reactions is still lacking. In this work, the complexation of zinc (Zn) by NOHMs with an ionically tethered polyetheramine canopy (HPE) (NOHM-I-HPE) was studied using attenuated total reflectance Fourier transform infrared and Carbon-13 nuclear magnetic resonance spectroscopy. Additionally, various electrochemical techniques were employed to discern the role of NOHM-I-HPE during zinc electrodeposition, and the results were compared to those of the electrochemical system containing untethered HPE polymers. Our findings confirmed that NOHM-I-HPE and HPE reversibly complex zinc in the aqueous electrolyte. NOHM-I-HPE and HPE were found to block some of the electrode active sites, reducing the overall current density during electrodeposition, while facilitating the formation of smooth zinc deposits, as revealed by surface imaging and diffraction techniques. Observed variations in the current density responses and the degree of passivation created by the NOHM-I-HPE and HPE adsorbed on the electrode surface revealed that their different packing behaviors at the electrode–electrolyte interface influence the zinc deposition mechanism. The presence of the nanoparticle and ordering offered by the NOHMs as well as the structured conformation of the polymeric canopy allowed the formation of void spaces and free volumes for enhanced transport behaviors. Furthermore, these findings provided insights into how structured electrolyte additives such as NOHMs can allow for advancements in electrolyte design for controlled deposition of metal species from energy-dense electrolytes or for other electrochemical reactions.

25 ENERGY STORAGE↗
DOE OSTI2021

Evaluation of the Passive Cooling Potential of Thermal Mass Inherent in Medium to Large Commercial Buildings

Typical commercial construction inherently contains large surface areas of relatively thin mass located in the floor slabs. This research asks how effective this mass could be for passive cooling, relative to other mass depths, if it were to be exposed and used as thermal mass. Although much of the rich literature on thermal mass has been conducted with far greater mass depths, a more limited amount of research suggests that because the surface heat transfer rate is limited, the focus should be on the surface area of exposed mass, not its depth. This presents an opportunity for more buildings to behave more thermally massively, if the mass inherent in typical floor slabs contains utility, particularly over diurnal cycles. In all climates analyzed, it was found that there is a pronounced shoulder where energy savings from passive cooling of increasing mass depths was steep until roughly 7.5–10 cm, and beyond this point the achieved energy savings diminished rapidly. When considering the embodied energy of concrete, the incremental benefit of added mass beyond a typical topping slab of 10 cm does not justify the incremental embodied energy cost from a total energy standpoint alone.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2024

Improving the Fire Weather Index System for Peatlands Using Peat-Specific Hydrological Input Data

The Canadian Fire Weather Index (FWI) system, even though originally developed and calibrated for an upland Jack pine forest, is used globally to estimate fire danger for any fire environment. However, for some environments, such as peatlands, the applicability of the FWI in its current form, is often questioned. In this study, we replaced the original moisture codes of the FWI with hydrological estimates resulting from the assimilation of satellite-based L-band passive microwave observations into a peatland-specific land surface model. In a conservative approach that maintains the integrity of the original FWI structure, the distributions of the hydrological estimates were first matched to those of the corresponding original moisture codes before replacement. The resulting adapted FWI, hereafter called FWIpeat, was evaluated using satellite-based information on fire presence over boreal peatlands from 2010 through 2018. Adapting the FWI with model- and satellite-based hydrological information was found to be beneficial in estimating fire danger, especially when replacing the deeper moisture codes of the FWI. For late-season fires, further adaptations of the fine fuel moisture code show even more improvement due to the fact that late-season fires are more hydrologically driven. The proposed FWIpeat should enable improved monitoring of fire risk in boreal peatlands.

Canadian Fire Weather Index↗
NASA NTRS1992

Lunar base thermal management/power system analysis and design

A compilation of several lunar surface thermal management and power system studies completed under contract and IR&D is presented. The work includes analysis and preliminary design of all major components of an integrated thermal management system, including loads determination, active internal acquisition and transport equipment, external transport systems (active and passive), passive insulation, solar shielding, and a range of lunar surface radiator concepts. Several computer codes were utilized in support of this study, including RADSIM to calculate radiation exchange factors and view factors, RADIATOR (developed in-house) for heat rejection system sizing and performance analysis over a lunar day, SURPWER for power system sizing, and CRYSTORE for cryogenic system performance predictions. Although much of the work was performed in support of lunar rover studies, any or all of the results can be applied to a range of surface applications. Output data include thermal loads summaries, subsystem performance data, mass, and volume estimates (where applicable), integrated and worst-case lunar day radiator size/mass and effective sink temperatures for several concepts (shielded and unshielded), and external transport system performance estimates for both single and two-phase (heat pumped) transport loops. Several advanced radiator concepts are presented, along with brief assessments of possible system benefits and potential drawbacks. System point designs are presented for several cases, executed in support of the contract and IR&D studies, although the parametric nature of the analysis is stressed to illustrate applicability of the analysis procedure to a wide variety of lunar surface systems. The reference configuration(s) derived from the various studies will be presented along with supporting criteria. A preliminary design will also be presented for the reference basing scenario, including qualitative data regarding TPS concerns and issues.

Mcghee, Jerry R.↗
NASA NTRS1974

The scientific justification of a radar scatterometer and a passive microwave system on Seasat-A

The purpose of these two systems is to determine the winds over the ocean. The passive system may also provide data on precipitation over the ocean and sea surface temperature through clouds. They complement each other. The radar scatterometer will sense those sea surface properties that define the winds over the ocean through clouds so thick and so wet that the passive microwave system will have detected only the cloud properties. Both wind speed and direction can be found from the combined data to be obtained.

Pierson, W. J.↗
NASA NTRS2021

Impact of Random and Periodic Surface Roughness on P- and L-band Radiometry

L-band passive microwave remote sensing is currently considered a robust technique for global monitoring of soil moisture. However, soil roughness complicates the relationship between brightness temperature and soil moisture, with current soil moisture retrieval algorithms typically assuming a constant roughness parameter globally, leading to a potential degradation in retrieval accuracy. This current investigation established a tower-based experiment site in Victoria, Australia. P-band (~40-cm wavelength/0.75 GHz) was compared with L-band (~21-cm wavelength/1.41 GHz) over random and periodic soil surfaces to determine if there is an improvement in brightness temperature simulation and soil moisture retrieval accuracy for bare soil conditions, due to reduced roughness impact when using a longer wavelength. The results showed that P-band was less impacted by random and periodic roughness than L-band, evidenced by more comparable statistics across different roughness conditions. The roughness effect from smooth surfaces (e.g., 0.8-cm root-mean-square height and 11.1-cm correlation length) could be potentially ignored at both P- and L-band with satisfactory simulation and retrieval performance. However, for rougher soil (e.g., 1.6-cm root-mean-square height and 6.8-cm correlation length), the roughness impact needed to be accounted for at both P- and L-band, with P-band observations showing less impact than L-band. Moreover, a sinusoidal soil surface with 10-cm amplitude and 80-cm period substantially impacted the brightness temperature simulation and soil moisture retrieval at both P- and L-band, which could not be fully accounted for using the SMOS and SMAP default roughness parameters. However, when retrieving roughness parameters along with soil moisture, the ubRMSE at P-band over periodic soil was improved to a similar level (0.01-0.02 m3/m3) as that of smooth flat soil (0.01 m3/m3), while L-band showed higher ubRMSE over the periodic soil (0.03-0.04 m3/m3) than over smooth flat soil (0.01 m3/m3). Accordingly, periodic roughness effects were reduced by using observations at P-band.

Soil roughness↗
NASA NTRS2022

Vulnerability of Passive Microwave Snowfall Retrievals to Physical Properties of Snowpack: A Perspective from Dense Media Radiative Transfer Theory

The uncertainty of passive microwave retrievals of snowfall is notoriously high where the high-frequency surface emissivity is significantly reduced and varies markedly in response to changes of snowpack physical properties. Using the dense media radiative transfer theory, this article studies the potential effects of terrestrial snow-cover depth, density, and6grain size on high-frequency channels 89 and 166 GHz of the radiometer onboard the Global Precipitation Measurement (GPM) core satellite, which are commonly used to capture the snowfall scattering signals. Integrating the inference across all feasible grain sizes, ranges of snowpack density and depth are identified over which the snowfall scattering signatures can be time varying and potentially obscured. Using 10 years of reanalysis data, the seasonal vulnerability of snowfall retrievals to changes of snowpack emissivity in the Northern Hemisphere is mapped in a probabilistic sense and connections are made with uncertainties of the GPM passive microwave snowfall retrievals. It is found that among different snow classes, relatively light Arctic tundra snow in fall, with a density below 260kg m−3, and shallow prairie snow during the winter, with a depth of less than 40cm, can reduce the surface emissivity and obscure the snowfall passive microwave signatures. It is demonstrated that, during the winter, the highly vulnerable areas are over Kazakhstan, and Mongolia with taiga and prairie snow. In the fall, these areas are largely over tundra and taiga snow in north of Russia and the Arctic Archipelagos as well as prairies in Canada and the Great Plains in the United States.

Reyhaneh Rahimi↗
NASA NTRS2010

The SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) Product

The Soil Moisture Active and Passive (SMAP) mission is being developed by NASA for launch in 2013 as one of four first-tier missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space in 2007. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. In this paper we describe the assimilation of SMAP observations for the generation of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product. The SMAP mission makes simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band) from a sun-synchronous low-earth orbit. Measurements will be obtained across a 1000 km wide swath using conical scanning at a constant incidence angle (40 deg). The radar resolution varies from 1-3 km over the outer 70% of the swath to about 30 km near the center of the swath. The radiometer resolution is 40 km across the entire swath. The radiometer measurements will allow high-accuracy but coarse resolution (40 km) measurements. The radar measurements will add significantly higher resolution information. The radar is however very sensitive to surface roughness and vegetation structure. The combination of the two measurements allows optimal blending of the advantages of each instrument. SMAP directly observes only surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (approximately top 1 m of the soil column), which is not directly measured by SMAP. The foremost objective of the SMAP L4_SM product is to fill this gap and provide estimates of root zone soil moisture that are informed by and consistent with SMAP observations. Such estimates are obtained by merging SMAP observations with estimates from a land surface model in a soil moisture data assimilation system. The land surface model component of the assimilation system is driven with observations-based surface meteorological forcing data, including precipitation, which is the most important driver for soil moisture. The model also encapsulates knowledge of key land surface processes, including the vertical transfer of soil moisture between the surface and root zone reservoirs. Finally, the model interpolates and extrapolates SMAP observations in time and in space. The L4_SM product thus provides a comprehensive and consistent picture of land surface hydrological conditions based on SMAP observations and complementary information from a variety of sources. The assimilation algorithm considers the respective uncertainties of each component and yields a product that is superior to satellite or model data alone. Error estimates for the L4_SM product are generated as a by-product of the data assimilation system.

Reichle, Rolf↗
NASA NTRS2014

ADEPT for Secondary Payloads

Deployable entry vehicles provide an enabling capability for large payloads at destinations across the solar system. The primary advantage of such systems derives from the fundamental limitation of available launch vehicle shroads preventing tried-and-true rigid aeroshell technology from being applied. However, little mission-pull exists for deployable entry vehicle technology for missions where the entry vehicle is the primary payload and can fit within available shrouds. The propensity toward applying rigid aeroshell technology is logical given that deployable concepts are higher risk and provide no marginal scientific benefit for missions where a rigid aeroshell is an option. A movement toward flying smaller spacecraft has emerged in recent years and is revealing novel applications for deployable entry vehicles as secondary payloads. Secondary payloads must minimize interference with the primary payload in order to ease accomodation. Advancements in small spacecraft technology have caught the attention of government entities who are now recognizing the high value proposition of small spacecraft for frequent, incremental technology development and science return rather than the traditional high cost and infrequent big-bang approaches. Worldwide, well over 200 small satellites (mass < 180 kg) have launched in recent years for such purposes as eduation, technology development, science, commerce, and defense. The Adaptable Deployable Entry and Placement Technology (ADEPT), a mechanically-deployable entry vehicle technology, has been under development at NASA since 2011. An Ames Center Innovation Fund (CIF) proposal was recently awarded to study ADEPT for EDL of small payloads. The unique capability of ADEPT for small science payloads comes from its ability to stow within a slender volume and deploy passively to achieve a mass-efficient drag surface with a high heat rate capability. The low ballistic coefficient results in entry heating and mechanical loads that can be met by a revolutionary three-dimensionally woven carbon fabric supported with rib structures. This carbon fabric has test-proven capability as both primary structure and payload thermal protection. This presentation will inform the EDL community of the capability of ADEPT for delivery of small secondary payloads as well as provide status of on-going technology development activities. Results of a mission applications study for secondary payloads to Mars and Venus will be presented. A primary goal of these mission design activities is to integrate high-value verification approaches wherever possible. For example, for some mission applications it is possible to test in NASA arc jet facilities at full-scale. This enables endto- end thermostructural requirement verification with a single test. Another important challenge that needs to be solved is the reliability of the decelerator to achieve the desired shape using simple passive mechanical actuators (such as springs) that do not require power from the primary payload for deployment. A configuration of ADEPT is being prototyped and used to evaluate the functionality and reliability of the deployment mechanism through bench-top testing. The prototype will then be tested in a low speed wind tunnel in late 2014 to evaluate aerodynamic load-carrying capability and deflected shape. Results of the deployment testing and status of wind tunnel test plans will be discussed.

Smith, B.↗
DOE OSTI2025

Role of Salt Concentration on Interphase Dynamics and Chemistry of Silicon Anodes during Electrochemical Cycling

We investigated the chemistry and structure of the solid electrolyte interphase (SEI) grown over a silicon anode as a function of the lithium salt concentration. In these experiments, in situ neutron reflectivity measurements were performed to measure the thickness and composition of the SEI formed from 1.0 and 5.5 M lithium bis(trifluoromethane)sulfonimide (LiTFSI) in standard ethylene carbonate:dimethyl carbonate electrolytes. These measurements reveal the formation of a 350+ Å thick SEI layer that is predominantly organic (∼80%) and dimensionally stable when using a 1.0 M salt solution. In contrast, increasing the salt concentration to 5.5 M resulted in an SEI that exhibited thickness changes from 100 to 375 Å and became up to 30% inorganic. In conclusion, these compositional and structural changes point to the role of salt speciation on the resulting passivation of silicon electrodes and indicate the need to form more organic-like passivation layers to promote the calendar life of silicon anodes.

Electrodes↗
NASA NTRS1980

Atmospheric corrections to passive microwave observations of the ocean

Microwave observations of the ocean surface are contaminated to a greater or lesser degree by the overlying atmosphere. The principal components of the atmosphere contributing to this contamination are molecular oxygen, water vapor, and water droplets. By means of measurements at several well-chosen frequencies, these atmospheric parameters may be removed from ocean observations and themselves retrieved as a by-product. This is the basic concept of the Scanning Multifrequency Radiometer (SMMR). These corrections may be made by quasi-linear means to useful accuracies, even in the presence of moderate rain.

Wilheit, T.↗