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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Landform Degradation and Slope Processes on Io: The Galileo View

The Galileo mission has revealed remarkable evidence of mass movement and landform degradation on Io. We recognize four major slope types observed on a number of intermediate resolution (250 m/pixel) images and several additional textures on very high resolution (10 m/pixel) images. Slopes and scarps on Io often show evidence of erosion, seen in the simplest form as alcove-carving slumps and slides at all scales. Many of the mass movement deposits on Io are probably mostly the consequence of block release and brittle slope failure. Sputtering plays no significant role. Sapping as envisioned by McCauley et al. remains viable. We speculate that alcove-lined canyons seen in one observation and lobed deposits seen along the bases of scarps in several locations may reflect the plastic deformation and 'glacial' flow of interstitial volatiles (e.g., SO2) heated by locally high geothermal energy to mobilize the volatile. The appearance of some slopes and near-slope surface textures seen in very high resolution images is consistent with erosion from sublimation-degradation. However, a suitable volatile (e.g., H2S) that can sublimate fast enough to alter Io's youthful surface has not been identified. Disaggregation from chemical decomposition of solid S2O and other polysulfur oxides may conceivably operate on Io. This mechanism could degrade landforms in a manner that resembles degradation from sublimation, and at a rate that can compete with resurfacing.

Moore, Jeffrey M.↗
NASA NTRSDate not supplied

Retrospective Observations of the Solar System Planets with Interstellar Probe

Retrospective Observations of the Solar System Planets with Interstellar Probe The Interstellar Probe (ISP) mission concept could simultaneously explore a number of long-standing solar system and exoplanetary science objectives. ISP’s long mission lifetime, in combination with the large separations from the solar system objects it could observe (Fig. 1), affords a truly unique dataset. This data could be leveraged to validate models of solar system and extrasolar planets and would be directly analogous to observations we can expect to make for exoplanets. Taken together, these opportunities suggest that ISP’s mission is a critical and necessary component for future planetary science endeavors. This abstract aims to address some of the clear synergies between ISP’s mission profile and the gaps in solar system science that are necessarily gaps in our ability to wholly bound our expectations for exoplanet observations (partly discussed in several white papers, including Zemcov et al., 2019; Harman et al., 2020). Notably, no single platform has yet returned near-complete phase curves for the majority of solar system planets. This is partly due to observational constraints (e.g., ground-based observatories can observe a maximum phase angle of Jupiter, Saturn, Uranus, and Neptune of 12º, 6º, 3º, and 2º, respectively; Mallama and Hilton, 2018), but also because of the sparse nature of observations captured by spacecraft over the last 40 years (e.g., Pollack et al., 1986). Additionally, these observations come from disparate instruments that have their own biases and limitations, whereas observations by ISP’s instrumentation would provide almost uniform measurements of nearly every solar system object, removing much of the uncertainty when it comes to data intercomparisons. The biggest hurdles for making these measurements from ISP are likely to be the tight mass and energy limitations, as well as the technical challenge of looking as close as possible to the Sun without peering directly at it. This is potentially complicated by the nature of the larger astrophysical mission requirements, including whether the spacecraft is spinning, but integrating observations on board before returning them to Earth serves to both partly mitigate both the possibility of a spinning spacecraft and the downlink volumes for lookback data (although it may make data disaggregation more technically challenging). Ultimately, ISP could return truly innovative observational data of our solar system, in furtherance of a number of planetary and solar system science goals.

Sonny Harman↗
NASA NTRS1998

Carbon-Water-Energy Relations for Selected River Basins

A biophysical process-based model was run using satellite, assimilated and ancillary data for four years (1987-1990) to calculate components of total evaporation (transpiration, interception, soil and snow evaporation), net radiation, absorbed photosynthetically active radiation and net primary productivity over the global land surface. Satellite observations provided fractional vegetation cover, solar and photosynthetically active radiation incident of the surface, surface albedo, fractional cloud cover, air temperature and vapor pressure. The friction velocity and surface air pressure are obtained from a four dimensional data assimilation results, while precipitation is either only surface observations or a blended product of surface and satellite observations. All surface and satellite data are monthly mean values; precipitation has been disaggregated into daily values. All biophysical parameters of the model are prescribed according to published records. From these global land surface calculations results for river basins are derived using digital templates of basin boundaries. Comparisons with field observations (micrometeorologic, catchment water balance, biomass production) and atmospheric water budget analysis for monthly evaporation from six river basins have been done to assess errors in the calculations. Comparisons are also made with previous estimates of zonal variations of evaporation and net primary productivity. Efficiencies of transpiration, total evaporation and radiation use, and evaporative fraction for selected river basins will be presented.

Choudhury, B. J.↗
NASA NTRS1992

Resources for a lunar base: Rocks, minerals, and soil of the Moon

The rocks and minerals of the Moon will be included among the raw materials used to construct a lunar base. The lunar regolith, the fragmental material present on the surface of the Moon, is composed mostly of disaggregated rocks and minerals, but also includes glassy fragments fused together by meteorite impacts. The finer fraction of the regolith (i.e., less than 1 cm) is informally referred to as soil. The soil is probably the most important portion of the regolith for use at a lunar base. For example, soil can be used as insulation against cosmic rays, for lunar ceramics and abodes, or for growing plants. The soil contains abundant solar-wind-implanted elements as well as various minerals, particularly oxide phases, that are of potential economic importance. For example, these components of the soil are sources of oxygen and hydrogen for rocket fuel, helium for nuclear energy, and metals such as Fe, Al, Si, and Ti.

Taylor, Lawrence A.↗
NASA NTRS1976

Missile impact craters (White Sands Missile Range, New Mexico) and applications to lunar research: Contributions to astrogeology

Craters in natural materials at White Sands Missile Range, N. Mex., were produced by the impact of high-velocity to hypervelocity missiles traveling along oblique trajectories with kinetic energies between 2.1 and 81 × 1014 ergs. The oblique impacts produce craters 2 to 10 m across with morphologies and ejecta that are bilaterally symmetrical with respect to the plane of the missile trajectory. Rims are high and the amount of ejecta large in down-trajectory and lateral directions, whereas rims are low to nonexistent and ejecta thin to absent up-trajectory. Symmetry development and modifications of the symmetry are a function of target material, local topography, and angle of impact. Seven mappable units can be recognized in and around the craters. Three of these are ejecta: thick ejecta near the crater, thin to discontinuous ejecta at greater distances, and scattered ejecta at the greatest distances to the limit of throwout. These ejecta units may be absent on the up-trajectory side; if present, they are rarely as thick or continuous as on other sides of the crater. Three units are target materials: undeformed target material exposed in local patches through thin to discontinuous ejecta and everywhere between the fragments of scattered ejecta, tilted and broken target material exposed in upper crater walls, and shattered and fractured target material exposed on the up-trajectory crater wall. The seventh unit is slope material composed of talus and fallback within the crater. Development, character, and exposure of these units varies chiefly with the target material. Ejecta from the craters is chiefly broken but relatively undeformed target material that may range in size from very fine grained debris to large blocks. Where the target is porous, significant amounts of the ejecta are composed of sheared and compressed fragments, some coated with dark layers of mixed projectile pieces, powder, and fused metal mixed with crushed target material. For layered targets, the original stratigraphic sequence is crudely preserved and in inverted order in thick ejecta. Secondary impact craters are produced by the impact of ejected fragments when the surrounding surface materials are sufficiently weak. A wide variety of secondary impact crater relations may result. Secondary craters nearest the primary crater have blocks in them that are larger than or the same size as the crater they produced. Farther from the primary crater, the fragments are generally smaller than the secondary crater and are ejected from it. Excavation of four craters revealed a mixed breccia beneath the crater floor composed of missile pieces, sheared and compressed target material, and crushed debris. Banded, disaggregated target material and nonmixed breccia surrounded the mixed breccia, and these breccias were surrounded by a zone of conjugate fractures. Beneath the ejecta on the lateral and down-trajectory crater flanks, the target materials were tilted upward and broken. Up-trajectory, open fractures and downward displacement occurred in two of the craters. No displacement was observed for the other two. Beneath the down-trajectory rims of craters with distinct layering, overturned synclines were observed. Missile breakup and behavior during cratering are a function of target and missile properties. Missile breakup depends on missile velocity and is most extensive at high velocities, where the missile is fragmented, powdered, and partly fused. Burial of missile or its fragmented, powdered, and fused remains is greatest for porous targets and least for dense cohesive targets. For very porous targets, camouflet structures containing the fragmented missile may form. Least squares fit to the data on craters in dry to moist targets indicate V(a) = 10^(-11.433)E(p)^(1.205) where V(a) is the volume of the apparent crater and E(p) is the kinetic energy of the missile. This equation is consistent with expectations of the equations relating apparent depth and radius to kinetic energy. Extrapolation of displaced masses and kinetic energies for laboratory impacts with sand and rock converge near 10^(15) to 10^(16) ergs, where the extrapolations are near the data on missile impact craters, corrected for impact angle. Displaced masses of craters produced by missile impacts and by chemical explosives with small scaled depths of burial are about the same when the kinetic energies of the missiles (corrected for angle of impact) are equal to the TNT equivalent energy of the explosive. The problem of equivalent scaled depth of burst for an impact crater is complicated and not entirely resolved, however. Both missile impact craters and chemical explosive craters in water-saturated targets are larger than their counterparts in dry to moist materials. Data collected during the study of missile impact craters have helped resolve a number of problems in lunar research: (1) the soillike nature of lunar surface materials was predicted, (2) sizes of craters produced by artificial impacts were correctly predicted, (3) certain features imaged by Surveyor were found to be analogous to features associated with missile impact craters, {4) missile impacts were used in support of the Apollo passive seismic experiment, (5) craters seen in Apollo orbital photographs were found to be similar to some missile impact craters, (6) missile impact craters supplied data on sample collection and crater phenomenology used in training astronauts, and (7) some returned lunar samples are similar to coated, sheared, and compressed fragments ejected from missile impact craters.

H. J. Moore↗
NASA NTRS1998

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗
NASA NTRS1999

Three Paradigms of Lunar Regolith Evolution

Integration of diverse datasets on the Moon may render some paradigms of lunar science either better-defended or vulnerable. We will consider three paradigms commonly used for understanding the processes of lunar regolith evolution in light of new and accumulated data. Our premise is that all data-sets should converge to a single interpretation if a concept or model is to be accepted as a paradigm. If a convergence is lacking, the paradigm needs fresh scrutiny. SteadyState: Lunar regolith evolution is currently understood in terms of comminution, agglutination, and replenishment as described by McKay and coworkers). Briefly, the model envisages continued micrometeoritic bombardment to comminute exposed soil particles to finer sizes while continued agglutination consumes finer sizes to produce larger constructional particles. Eventually, a balance between these two opposing processes achieves a steady state; soils at steady state maintain their mean grain size (M(sub z)). Episodic higher-energy impacts excavate fresh coarse material from below the soil cover, disturb the steady state, and restart the process to achieve a new steady state. It follows that the thickness of the regolith at any site would control the frequency of replenishment; indeed, the thickness of the regolith at Apollo landing sites was predicted by McKay et al. from the average M(sub z) of local soils. However, replenishment may come also from disintegrating boulders and cobbles at the lunar surface, and rates of comminution and agglutination may depend on the properties of target material. Regression between M(sub z) and I(sub s)/Fe(sup 0) (a measure of maturity or total surface exposure) of Apollo soils at different sites shows the following relations and estimated M(sub z) at a high maturity of I(sub s)/Fe(sup 0)= 100. It is possible that Apollo 12 and 15 sites have the thickest regolith and the Apollo 16 site has the thinnest. It is also possible that Apollo 12 and 15 basalts are comminuted faster than Apollo 16 highland rocks and Apollo 14 and 17 soils are products of mixed parentage. If a soil becomes continually finer as it matures until agglutination catches up, and if comminution is differential-dependent on the physical properties of the constituents, then the composition of the bulk soil has to match the composition of some "fulcrum" grain size fraction, say X Grain size fractions >X and <X will complement each other; their mass balance is the bulk soil. It appears that the 10-20-micron size fraction may be the fulcrum. In general, trace-element chemistry and IR reflectance spectra of this size fraction are closest to that of the bulk soil, regardless of maturity that is surprising. Disaggregated products of regolith breccias may also show similar relationships. If the 10-20 gm is the fulcrum (i.e., X as above) for many soil properties (e.g., major element composition, FMR, solar-wind-implanted elements), then this may be the ultimate mean grain size of lunar soils at steady state. However, different properties of soils may find steady states at different grain size fractions. The steady state of solar-wind-implanted elements, on the other hand, will climb up the grain-size scale as agglutinates transfer surface-correlated components into volume correlated components until a saturation level is reached or the rates of replenishment and implantation become equal. The same will be the case with vapor-deposited reduced metals as they too are incorporated inside constructional particles. Properties that are directly affected by soil-maturation processes will thus have different pathways of achieving steady states. Maturity, i.e., cumulative surface exposure, of lunar soils is best quantified by the amount of nanophase superparamagnetic Fe(sup 0) (np-Fe(sup 0)) normalized to Fe content (=I(sub s)/Fe(sup 0). The majority consensus (paradigm?) for the production of np-Fe(sup 0) is associated with the production of agglutinates. Because large doses of solar-wind H are implanted in all lunar soils upon exposure, any melting (e.g., during agglutinate production) triggers a chemical reduction of Fe-bearing minerals resulting in np-Fe(sup 0) production. The quantity of np-Fe(sup 0) is thus dependent on melting events, (i.e., exposure), and limited by the Fe content of the soil. All freshly produced np-Fe(sup 0) resides in agglutinitic glass, as new TEM images show. Apparently, the correction procedure developed by Lucey et al. to estimate the Fe content of the lunar surface from IR-reflectance spectra depends on accepting the above. However, the process of producing np-Fe(sup 0) may be physical rather than chemical. All np-Fe(sup 0) could be deposits from a vapor produced by micrometeoritic impact on lunar soils. If metal-O bonds in target phases are broken, O being "most volatile" will escape leaving an O-deficient vapor to facilitate the production of np-Fe(sup 0). If so, the quantity of np-Fe(sup 0) is dependent on the vaporizing events, (i.e., exposure), and limited by the efficiency of breaking metal-O bonds and the escape of 0. To the extent that strengths of metal-O bonds are dependent on the local crystal field, production of np-Fe(sup 0) may be limited by the mineral composition of target soils and not by their total Fe content. According to this model, vapor-deposited np-Fe(sup 0) should be found at any retentive sites on lunar soil grains. Indeed, TEM images show np-Fe(sup 0) on plagioclase and ilmenite. Incorporation of such pre-irradiated np-Fe(sup 0)-bearing grains into agglutinates may account for eventual increased emplacement of np-Fe(sup 0) in agglutinates. Such a paradigm shift in understanding the origin of np-Fe(sup 0) will raise questions ranging from the unquestionable use of Is/FeO as the universal maturity parameter of lunar soils to global elemental maps of the Moon from remote-sensing data. Additional information is contained in the original.

Basu, A.↗