Lunar surface mechanical properties
Lunar surface mechanical properties determined by landing impacts, telemetry data from Surveyor III, and comparison of data collected by Surveyor I and Surveyor III
LUNAR SURFACE↗
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Lunar surface mechanical properties
Lunar surface mechanical properties derived from Surveyor 5 photographs
Batterson, S. A.↗
Lunar surface mechanical properties.
Lunar surface mechanical properties at Surveyor 5 site
Batterson, S. A.↗
Learning interpretable surface elasticity properties from bulk properties via neural network equation learners
Surface elasticity is central to understanding the mechanics and stability of surfaces and interfaces. It is characterized by quantities such as surface tension, residual surface stress, and surface stiffness. However their analytical expressions are typically difficult to derive from atomistic data, and depend strongly on modeling choices. This work presents a neural network-based equation learner which combines customized activation functions and connection-based pruning to discover parsimonious, closed-form equations for surface elasticity from atomistic simulations. Applying the method to seven face-centered cubic (FCC) metals, our equation learner uncovers interpretable equations that describe both low-Miller index and high-Miller index surface properties, capturing long-tail property distributions accurately. The discovered expressions are decoupled into two components: a universal, geometry-driven orientation function, and material-specific baseline coefficients. We find that lower-order properties such as surface tension are fundamentally geometry dependent, while higher-order properties such as surface stress and elasticity show more complex geometry and material dependence. We also relate material dependent coefficients to bulk properties, forming a clear map from bulk material properties to surface elasticity. Overall, this approach demonstrates that interpretable neurosymbolic machine learning can bridge the gap between atomistic simulations and physical laws, enabling the discovery of generalizable structure–property relationships for materials science phenomena such as surface elasticity.
Equation learning↗
Dependence of the spectral surface irradiance on aerosol properties and surface reflectivity
A reduction in global surface irradiance occurs with increasing aerosol loadings when the aerosols are absorbing. For scattering aerosols, a reduction is pronounced for isotropic scattering (characteristic of small particles) but reduction is not as significant for scattering with a high anisotropy of a large forward peak (characteristic of large particles). This distinction between isotropic and anisotropic scattering becomes small or null over highly reflecting terrain; and for reflectivities higher than 0.5 and solar elevation angles close to the zenith, the global irradiance can be slightly higher for isotropic scattering than in the case of an anisotropy of a forward peak. Under such conditions, which can be encountered in reflective infrared bands over dense vegetation or over sandy deserts (close to noon, in low latitudes) the surface irradiance becomes nearly independent of the aerosol optical thickness.
Otterman, J.↗
Investigation of Arctic Cloud Properties and Surface Radiation Based on MOSAiC Shipborne Observations
The Arctic is rapidly changing due to changes of the Earth system. This study investigates cloud fraction, phase partition, cloud type, and their relationships with surface radiation based on yearlong shipborne observations in the Arctic regions. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign provided lidar and radar observations of cloud microphysical properties and surface shortwave (SW) and longwave (LW) radiation. Cloud and radiative properties were examined at daily and monthly resolutions in four seasons. Low clouds were found to be most prevalent throughout the year, followed by deep clouds. The ice phase is the dominant phase except for summer (June–August). Liquid and mixed phases show more significant monthly and annual mean radiative effects in SW and LW than the ice phase. The clouds show net warming effects due to LW heating in most months, while the SW cooling effects of clouds become more dominant for July and August. The cloud and radiation observations from MOSAiC were used to evaluate simulations of the atmospheric component of the Energy Exascale Earth System Model version 2. The simulations show large overestimations of the liquid and mixed phases in the Arctic regions from February to September. The simulations also underestimate the percentages of low clouds and overestimate the percentages of deep clouds throughout the year. Altogether, this work provides a unique analysis of cloud and radiation properties based on high-resolution shipborne observations, which can be used to assist future model evaluation and development.
58 GEOSCIENCES↗
Surface electrical properties experiment
The Surface Electrical Properties Experiment (SEP) was flown to the moon in December 1972 on Apollo 17 and used to explore a portion of the Taurus-Littrow region. SEP used a relatively new technique, termed radio frequency interferometry (RFI). Electromagnetic waves were radiated from two orthogonal, horizontal electric dipole antennas on the surface of the moon at frequencies of 1, 2, 4, 8, 16, and 32 Mhz. The field strength of the EM waves was measured as a function of distance with a receiver mounted on the Lunar Roving Vehicle and using three orthogonal, electrically small, loops. The interference pattern produced by the waves that travelled above the moon's surface and those that travelled below the surface was recorded on magnetic tape. The tape was returned to earth for analysis and interpretation. Several reprints, preprints, and an initial draft of the first publication of the SEP results are included. These documents provide a rather complete account of the details of the theory of the RFI technique, of the terrestrial tests of the technique, and of the present state of our interpretation of the Apollo 17 data.
Simmons, G.↗
Surface electrical properties experiment
The surface electrical properties (SEP) experiment was used to explore the subsurface material of the Apollo 17 landing site by means of electromagnetic radiation. The experiment was designed to detect electrical layering, discrete scattering bodies, and the possible presence of water. From the analysis of the data, it was expected that values of the electrical properties (dielectric constant and loss tangent) of lunar material in situ would be obtained. The basic principle of the SEP experiment is interferometry. This principle involves only the interference of two or more waves to produce an interference pattern. The inversion of the interference pattern in terms of the spatial distribution of the electrical properties is the basic aim of the experiment (fig. 15-1). The experiment is most easily understood in terms of a single dipole antenna for radiating electromagnetic energy and a loop receiver for measuring the magnitudes of the fields.
Simmons, G.↗
Effect of polymer properties and adherend surfaces on adhesion
The surface properties associated with good adhesive joints were evaluated in terms of application of adhesive bonding in aerospace technology. The physical and chemical nature was determined of Ti and Al adherend surfaces after various surface treatments, and the effects on fracture surfaces of high temperature aging, and variations in amide, anhydride, and solvent during polymer synthesis. The effects were characterized of (1) high temperature during shear strength testing, (2) fiber-reinforced composites as adherends, (3) acid/base nature of adherends, (4) aluminum powder adhesive filler, and (5) bonding pressure.
Dwight, D. W.↗
Invariant surface elastic properties in FCC metals and their correlation to bulk properties revealed by machine learning methods
In this work, we present a combination of machine-learned models that predicts the surface elastic properties of general free surfaces in face-centered cubic (FCC) metals. These models are built by combining a semi-analytical method based on atomistic simulations to calculate surface properties with the artificial neural network (ANN) method or the boosted regression tree (BRT) method. The latter is also used to link bulk properties and surface orientation to surface properties. The surface elastic properties are represented by their invariants considering plane elasticity within a polar method. The resulting models are shown to accurately predict the surface elastic properties of seven pure FCC metals (Cu, Ni, Ag, Au, Al, Pd, Pt). The BRT model reveals the correlations between bulk and corresponding surface properties in terms of invariants, which can be used to guide the design of complex nano-sized particles, wires and films. Finally, by expressing the surface excess energy density as a function of surface elastic invariants, fast predictions of surface energy as a function of in-plane deformations can be made from these model constructs.
36 MATERIALS SCIENCE↗
Ab-initio predictions of phase stability, electronic structure, and optical properties of (0001)-MAX surfaces in M 2 AC (M = Cr, Zr, Hf; A = Al, Ga)
In this work, we report MAX phases' surface properties, which are essential for thin-film technology due to their excellent resistance to high-temperature oxidation, corrosion, and wear. The surface stability, electronic, and optical properties of 0001-surfaces in M 2 AC (M = Zr, Hf, Cr; A = Al, Ga) are investigated and compared with their bulk counterparts. The interplay between chemical bonding and charge distribution is discussed from electronic structure, including the Fermi surfaces. Four possible (0001)-terminated surfaces are considered by breaking M - C and M-A bonds in which cleavage energy of M - C is higher than M-A. The Cr–Al bond in Cr 2 AlC is stronger than other M-A bonds. The charge density of valance A-p electrons redistributes in the surface area, distinct from that of the bulk. The A- and M(C)-terminated (0001)-surfaces are the most stable and energetically favorable terminations due to lower surface energies. The optical properties of the most stable (0001)-surfaces were also investigated to understand the dielectric and photoconductive behavior in the (0001)-terminated surfaces of M 2 AC.
36 MATERIALS SCIENCE↗
How well can regional fluxes be derived from smaller-scale estimates?
Regional surface fluxes are essential lower boundary conditions for large scale numerical weather and climate models and are the elements of global budgets of important trace gases. Surface properties affecting the exchange of heat, moisture, momentum and trace gases vary with length scales from one meter to hundreds of km. A classical difficulty is that fluxes have been measured directly only at points or along lines. The process of scaling up observations limited in space and/or time to represent larger areas was done by assigning properties to surface classes and combining estimated or calculated fluxes using an area weighted average. It is not clear that a simple area weighted average is sufficient to produce the large scale from the small scale, chiefly due to the effect of internal boundary layers, nor is it known how important the uncertainty is to large scale model outcomes. Simultaneous aircraft and tower data obtained in the relatively simple terrain of the western Alaska tundra were used to determine the extent to which surface type variation can be related to fluxes of heat, moisture, and other properties. Surface type was classified as lake or land with aircraft borne infrared thermometer, and flight level heat and moisture fluxes were related to surface type. The magnitude and variety of sampling errors inherent in eddy correlation flux estimation place limits on how well any flux can be known even in simple geometries.
Moore, Kathleen E.↗
How well can regional fluxes be derived from smaller-scale estimates?
Regional surface fluxes are essential lower boundary conditions for large scale numerical weather and climate models and are the elements of global budgets of important trace gases. Surface properties affecting the exchange of heat, moisture, momentum and trace gases vary with length scales from one meter to hundreds of km. A classical difficulty is that fluxes have been measured directly only at points or along lines. The process of scaling up observations limited in space and/or time to represent larger areas was done by assigning properties to surface classes and combining estimated or calculated fluxes using an area weighted average. It is not clear that a simple area weighted average is sufficient to produce the large scale from the small scale, chiefly due to the effect of internal boundary layers, nor is it known how important the uncertainty is to large scale model outcomes. Simultaneous aircraft and tower data obtained in the relatively simple terrain of the western Alaska tundra were used to determine the extent to which surface type variation can be related to fluxes of heat, moisture, and other properties. Surface type was classified as lake or land with aircraft borne infrared thermometer, and flight level heat and moisture fluxes were related to surface type. The magnitude and variety of sampling errors inherent in eddy correlation flux estimation place limits on how well any flux can be known even in simple geometries.
Moore, Kathleen E.↗
Contactless Measurement of Physical Properties
Surface tension and other properties determined from measurement of resonant frequency. Surface tension and other physical properties of molten and liquid samples excited at resonance measured by observing photographic or TV image and noting resonant frequency and rate of change. Technique used in normal gravity and low gravity in either vacuum or gaseous environment, where sample is positioned by electrostatic, acoustic, or magnetic forces.
Elleman, D. D.↗
Using Remote Sensing Platforms to Estimate Near-Surface Soil Properties
Evaluation of near-surface soil properties via remote sensing (RS) could facilitate soil survey mapping, erosion prediction, fertilization regimes, and allocation of agrochemicals. The objective of this study was to evaluate the relationship between soil spectral signature and near surface soil properties in conventionally managed row crop systems. High resolution RS data were acquired over bare fields in the Coastal Plain, Appalachian Plateau, and Ridge and Valley provinces of Alabama using the Airborne Terrestrial Applications Sensor (ATLAS) multispectral scanner. Soils ranged from sandy Kandiudults to fine textured Rhodudults. Surface soil samples (0-1 cm) were collected from 163 sampling points for soil water content, soil organic carbon (SOC), particle size distribution (PSD), and citrate dithionite extractable iron (Fed) content. Surface roughness, soil water content, and crusting were also measured at sampling. Results showed RS data acquired from lands with less than 4 % surface soil water content best approximated near-surface soil properties at the Coastal Plain site where loamy sand textured surfaces were predominant. Utilizing a combination of band ratios in stepwise regression, Fed (r2 = 0.61), SOC (r2 = 0.36), sand (r2 = 0.52), and clay (r2 = 0.76) were related to RS data at the Coastal Plain site. In contrast, the more clayey Ridge and Valley soils had r-squares of 0.50, 0.36, 0.17, and 0.57. for Fed, SOC, sand and clay, respectively. Use of estimated eEmissivity did not generally improve estimates of near-surface soil attributes.
Sullivan, D. G.↗
Lunar surface mechanical properties - Surveyor results
Lunar surface mechanical properties from Surveyor spacecraft interactions with soil /exclusive of surface sampler/
Christensen, E. M.↗
Dependence of adsorption properties on surface structure for body-centered-cubic substrates
Dependence on surface structure for adsorption energy by single atom on body centered cubic substrate
BODY CENTERED CUBIC /BCC/ CRYSTAL↗
Lunar surface mechanical properties - Surveyor 1.
Lunar surface mechanical properties at Surveyor landing site according to telemetry data and photographs
LUNAR LANDING SITE↗