Lunar surface roughness - Shadowing and thermal emission.
Model for lunar surface roughness effect on emission of thermal IR radiation and casting of shadows in sunlight
SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Model for lunar surface roughness effect on emission of thermal IR radiation and casting of shadows in sunlight
A theoretical analysis on the performance of hydrodynamic oil bearings is made considering surface roughness effect. The hydrodynamic as well as asperity contact load is found. The contact pressure was calculated with the assumption that the surface height distribution was Gaussian. The average Reynolds equation of partially lubricated surface was used to calculate hydrodynamic load. An analytical expression for average gap was found and was introduced to modify the average Reynolds equation. The resulting boundary value problem was then solved numerically by finite difference methods using the method of successive over relaxation. The pressure distribution and hydrodynamic load capacity of plane slider and journal bearings were calculated for various design data. The effects of attitude and roughness of surface on the bearing performance were shown. The results are compared with similar available solution of rough surface bearings. It is shown that: (1) the contribution of contact load is not significant; and (2) the hydrodynamic and contact load increase with surface roughness.
Statistical model of lunar surface roughness for shadow and infrared emission characteristics
The effect on airfoil characteristics of surface roughness of varying degrees and types at different locations on an airfoil was investigated at high values of the Reynolds number in a variable density wind tunnel. Tests were made on a number of National Advisory Committee for Aeronautics (NACA) 0012 airfoil models on which the nature of the surface was varied from a rough to a very smooth finish. The effect on the airfoil characteristics of varying the location of a rough area in the region of the leading edge was also investigated. Airfoils with surfaces simulating lap joints were also tested. Measurable adverse effects were found to be caused by small irregularities in airfoil surfaces which might ordinarily be overlooked. The flow is sensitive to small irregularities of approximately 0.0002c in depth near the leading edge. The tests made on the surfaces simulating lap joints indicated that such surfaces cause small adverse effects. Additional data from earlier tests of another symmetrical airfoil are also included to indicate the variation of the maximum lift coefficient with the Reynolds number for an airfoil with a polished surface and with a very rough one.
We use repeat high-resolution airborne geophysical data consisting of laser altimetry, snow, and Ku-band radar and optical imagery acquired in 2014, 2016, and 2017 to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88° S, an elevation bias validation site for ICESat-2 and potential validation site for CryoSat-2. We find significant small-scale variability (<10 km) in snow accumulation based on the snow radar subsurface stratigraphy, indicating areas of strong wind redistribution are prevalent at 88° S. In general, highs in snow accumulation rate correspond with topographic lows, resulting in a negative correlation coefficient of r(exp 2)=−0.32 between accumulation rate and MSWD (mean slope in the mean wind direction). This relationship is strongest in areas where the dominant wind direction is parallel to the survey profile, which is expected as the geophysical surveys only capture a two-dimensional cross section of snow redistribution. Variability in snow accumulation appears to correlate with variability in MSWD. The correlation coefficient between the standard deviations of accumulation rate and MSWD is r(exp 2)=0.48, indicating a stronger link between the standard deviations than the actual parameters. Our analysis shows that there is no simple relationship between surface slope, wind direction, and snow accumulation rates for the overall survey area. We find high variability in surface roughness derived from laser altimetry measurements on length scales smaller than 10 km, sometimes with very distinct and sharp transitions. Some areas also show significant temporal variability over the course of the 3 survey years. Ultimately, there is no statistically significant slope-independent relationship between surface roughness and accumulation rates within our survey area. The observed correspondence between the small-scale temporal and spatial variability in surface roughness and backscatter, as evidenced by Ku-band radar signal strength retrievals, will make it difficult to develop elevation bias corrections for radar altimeter retrieval algorithms.
No abstract available
The effect of surface roughness on the brightness temperature of a moist terrain was studied through the modification of Fresnel reflection coefficient and using the radiative transfer equation. The modification involves introduction of a single parameter to characterize the roughness. It is shown that this parameter depends on both the surface height variance and the horizontal scale of the roughness. Model calculations are in good quantitative agreement with the observed dependence of the brightness temperature on the moisture content in the surface layer. Data from truck mounted and airborne radiometers are presented for comparison. The results indicate that the roughness effects are greatest for wet soils where the difference between smooth and rough surfaces can be as great as 50K.
The effect of surface roughness on the brightness temperature of a moist terrain has been studied through the modification of Fresnel reflection coefficient and using the radiative transfer equation. The modification involves introduction of a single parameter to characterize the roughness. It is shown that this parameter depends on both the surface height variance and the horizontal scale of the roughness. Model calculations are in good quantitative agreement with the observed dependence of the brightness temperature on the moisture content in the surface layer. Data from truck mounted and airborne radiometers are presented for comparison. The results indicate that the roughness effects are great for wet soils where the difference between smooth and rough surfaces can be as great as 50 K.
Results from the radar cross section of rough surfaces calculated from a conventional definition and from a direct solution of the radar equation are compared. The purpose is to define conditions under which the conventional solution produces the same cross-section as the radar equation. A randomly rough conduction surface is considered for line sources and corrugated surfaces. Two problems are analyzed: first, a plane wave is assumed to be incident on the surface and the observed scattered fields are computed, and second, the scattered fields received by an antenna colocated with the emitting antenna are used to compute the available power. The fields are assumed to scatter incoherently and the stationary points are assumed to be homogeneously distributed over the surface. The cross sections are found to be equal if the observer is far from the surface compared to the radii of the surface at the specular points.
Rough surface scattering on communication link using isotropic antennas, noting fading characteristics
Statistical model of lunar surface roughness, shadow, and thermal emission
Theoretical model for scattering from rough surfaces with moon and sea applications
Radar scatter from rough surfaces with application to lunar radar backscatter
Omnidirectional characteristics of scattering of acoustic waves from statistically rough surfaces, measuring scattering cross section as function of incidence and observation angles
Additive Manufacturing (AM) has offered many new design and manufacturing opportunities for components across various industries. As AM evolves there is a need to better understand outputs of the process including geometric limitations and surface roughness based on specific application requirements. One possible application area of AM are components using thin-wall (<2 mm) microchannel heat exchangers for subsystems across aerospace, and industrial applications. AM offers the opportunity to significantly reduce the cost and lead time associated with fabricating these complex parts with internal features such as an array of cooling channels. Laser Powder Bed Fusion (L-PBF) has been continuously demonstrated as a technique to fabricate heat exchangers with internal geometric complexities. However, L-PBF is limited in the scale at which parts can be fabricated. Laser Powder Directed Energy Deposition (LP-DED) has been demonstrated as an AM technology to significantly increase the scale of which thin-wall microchannel heat exchangers could be manufactured. Successful deployment of the LP-DED technology requires critical understanding of the resulting features from the build process. Surface roughness is one of the critical areas that effects the friction factor and pressure drop within a heat exchanger and must be well understood. This presentation will provide an overview of the characterization work completed to understand the LP-DED process for thin-walls representative of hydrogen resistant alloy NASA HR-1 that would be used in a Hydrogen-environment application. An overview of the experiments conducted with varying LP-DED parameters, evaluation of various geometric channel and geometric build features and resulting surface finish will be provided along with a summary of conclusions from these experiments. Results indicate that powder size is a major contributor and surface roughness varies between closed channel shapes and external surfaces.
Two predawn ascending data-takes by the Shuttle Imaging Radar-B (SIR-B) were used to evaluate the effects of surface roughness, crop canopy, and soil moisture on radar backscatter. The two images, separated by three days, were both obtained at 30-deg local angle of incidence, but with opposite azimuth viewing directions. The imagery was externally calibrated with respect to the radar backscattering coefficient sigma(0) via response to arrays of point and area-extended targets of known radar cross section. Three land-cover classes: (1) corn, (2) corn stubble and plowed bare soil, and (3) disked bare soil, soybeans, soybean stubble, alfalfa, and clover could be readily separated for either observation date on the basis of image tone alone. The dependence of sigma(0) on the surface roughness and canopy brightness inhibits the capability of SIR to globally estimate the near-surface soil moisture from the value of sigma(0) for single date observations, unless the surface roughness or canopy cover conditions are accounted for. However, within given ranges of these conditions, the sigma(0) was found to be highly correlated with the soil moisture.
Ever since Crombie used the Doppler spectrum of RF signals scattered from the ocean surface to provide conclusive evidence for Bragg resonant scattering, scattering from the ocean surface has served as a testing ground for the identification of governing scattering mechanisms in rough surface scattering. The moving ocean surface has the advantage for rough surface scattering that, being a dispersive medium, features with different spatial scales the tendency to travel at different speeds. Thus, by looking at the temporal signature of the scattered field, one can try to isolate the scattering mechanism. This feature has been exploited by various authors. To give a recent example, we cite the work of Plant, who examined the Doppler spectrum of the return signal to infer the presence of two-scale scattering in scattering at medium incidence angles. The problem with restricting oneself to the examination of the Doppler spectrum, as has been done traditionally, is that one restricts the phenomena under investigation to temporally homogeneous phenomena: transient phenomena, which are localized in time, are not localized in frequency space. There is increasing evidence that this type of phenomena, due to specular scattering or breaking waves, may also play an important role in determining the scattering mechanism in ocean-like surfaces. To overcome this problem, we introduce the use of the Wavelet Transform to study the frequency-temporal signatures of the scattered field from moving ocean waves. We calculate this signature using various analytic scattering theories and show that the Wavelet Transform provides a useful tool for separating the different scattering mechanisms operating in scattering in ocean-like surfaces. Next we simulate realistic nonlinear moving ocean waves and calculate the temporal scattered field signature by using the method of moments and the stop-start approximation: the surface is assumed stationary during a scattering event, but moves between incident EM pulses. We compute and compare the Doppler frequency spectrum and the Wavelet Transform of the resulting signal for various types of surfaces and show how different scattering mechanisms may be isolated by this technique. Finally, we compare these numerical results against the analytical predictions in order to obtain the domain of applicability of various scattering theories for moving ocean surfaces which may include wave breaking and specular glints.
Monitoring spatial and temporal changes of soil moisture are of importance to hydrology, meteorology, and agriculture. This paper reports a result on study of using L-band SAR imagery to estimate soil moisture and surface roughness for bare fields. Due to limitations of the Small Perturbation Model, it is difficult to apply this model on estimation of soil moisture and surface roughness directly. In this study, we show a simplified model derived from the Integral Equation Model for estimation of soil moisture and surface roughness. We show a test of this model using JPL L-band AIRSAR data.