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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Detection of Subsurface Material Separation in Shuttle Orbiter Slip-Side Joggle Region of the Wing Leading Edge using Infrared Imaging Data from Arc Jet Tests

The objective of the present study was to determine whether infrared imaging (IR) surface temperature data obtained during arc-jet tests of Space Shuttle Orbiter s reinforced carbon-carbon (RCC) wing leading edge panel slip-side joggle region could be used to detect presence of subsurface material separation, and if so, to determine when separation occurs during the simulated entry profile. Recent thermostructural studies have indicated thermally induced interlaminar normal stress concentrations at the substrate/coating interface in the curved joggle region can result in local subsurface material separation, with the separation predicted to occur during approach to peak heating during reentry. The present study was an attempt to determine experimentally when subsurface material separations occur. A simplified thermal model of a flat RCC panel with subsurface material separation was developed and used to infer general surface temperature trends due to the presence of subsurface material separation. IR data from previously conducted arc-jet tests on three test specimens were analyzed: one without subsurface material separation either pre or post test, one with pre test separation, and one with separation developing during test. The simplified thermal model trend predictions along with comparison of experimental IR data of the three test specimens were used to successfully infer material separation from the arc-jet test data. Furthermore, for the test specimen that had developed subsurface material separation during the arc-jet tests, the initiation of separation appeared to occur during the ramp up to the peak heating condition, where test specimen temperature went from 2500 to 2800 F.

Daryabeigi, Kamran↗
DOE OSTI2024

Electrical Resistivity Tomography Monitoring of In Situ Soil Flushing at the Hanford 100-K East Area: 100KE Soil Flushing Monitoring

Former operations in the 100-KE Area at the Hanford Site resulted in vadose zone hexavalent chromium that provides a source of groundwater contamination. Previous efforts to remediate vadose zone chromium involved excavation and offsite treatment of contaminated soils. Although much of the chromium was removed, contamination still exists in native soil between the water table and the bottom of the pit, which has since been backfilled. In-situ soil flushing was tested at the 100-KE Area to accelerate the removal of the remaining hexavalent chromium in the vadose zone. Soil flushing works by applying clean flush water at the surface, which mobilizes and transports chromium as it migrates downward to the water table. Once the chromium reaches the water table, it is hydraulically contained, extracted, and treated through pump and treat operations. The efficacy of soil flushing is directly related to the volume of clean water that infiltrates through contaminated soils. Therefore, performance monitoring requires and understanding of flush water migration through the vadose zone. It is challenging to comprehensively assess soil flushing performance via borehole access due to the limited volume of investigation afforded by a given wellbore. As an alternative, 3D time-lapse electrical resistivity tomography (ERT) was tested as a method of monitoring the distribution of flush water over time within the vadose zone. ERT is a method of imaging the bulk electrical conductivity of the subsurface, which is highly dependent on water saturation levels in unconsolidated and unsaturated sediments. Thus, the timing and location of changes in bulk conductivity caused by soil flushing can be used to infer flush water migration pathways. In this report we present results of 3D time-lapse ERT imaging during two separate soil flushing campaigns conducted during the spring and summer months of 2022 and 2023. Results show generally that: 1) Pit backfill materials appear to nominally have larger permeability than native soils. Consequently, the boundary between pit backfill and native soil had a significant impact on flush water migration, causing some flush water to migrate along the pit boundary to the bottom of the pit. 2) Non-uniform flows, likely caused by variations in hydrogeologic properties, developed in the pit backfill materials, resulting in uneven flush water distribution on the southern margin of the soil flushing zone. 3) Redistribution of water at the interface between backfill materials and Hanford formation materials likely facilitated elevated and uniform distribution of flush water within native soils beneath the deeper parts of the pit boundary beneath the center of the flush zone, which presumably overlie soils with elevated chromium contamination. These areas appear to have been infiltrated by higher volumes of flush water than the northern and southern margins of the flush zone. 4) In comparison to 2022, high flush water application rates significantly improved flush water distribution throughout the target flushing zone. 5) Imaging resolution was limited to a depth of approximate 20 meters below the land surface, due primarily to limitations on the lateral extent of the surface ERT array. The ~10 m region of the vadose zone between approximately 130 meters elevation and the water table at approximately 120 meters elevation was unresolved.

100 Area↗
DOE OSTI2020

Hidden Subsurface Reconstruction and Its Atomic Origins in Layered Oxide Cathodes

Structural transformations near surfaces of solid-state materials underpin functional mechanisms of a broad range of applications including catalysis, memory, and energy storage. It has been a long-standing notion that the outmost free surfaces, accompanied by broken translational symmetry and altered atomic configurations, are usually the birthplace for structural transformations. Here, in a layered oxide cathode for Li-ion batteries, we for the first time observe the incipient state of the well documented layered-to-spinel-like structural transformation, which is surprisingly initiated from subsurface layer, rather than the very surface. Coupling atomic level scanning transmission electron microscopy imaging with electron energy loss spectroscopy, we discover that the reconstructed subsurfaces, featuring a mix of discrete patches of layered and spinel-like structures, are associated with selective atomic species partition and consequent nanoscale non-uniform composition gradient distribution at the subsurface. In conclusion, our findings provide fundamental insights on atomic-scale mechanisms of structural transformation in layered cathodes.

25 ENERGY STORAGE↗
DOE OSTI2021

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components. Third Annual Progress Report

Additive manufacturing (AM) of high-strength corrosion resistance alloys for nuclear energy applications, such as stainless steel and Inconel, is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Probability of crack initiation at the pore depends on size, shape, and orientation of the defect. Pulsed Infrared Thermography Imaging (PIT) provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PIT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PIT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PIT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PIT capabilities in detecting microscopic subsurface defects in metals, and classifying shapes and orientation of pores in thermal images. For detection of microscopic defects in PIT imaging data, we have developed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) image processing algorithm. We show that flat bottom hole (FBH) defects as small as 200µm in SS316 and IN718 specimens, can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature. For classification of defects shapes, we have previously developed thermal tomography (TT) algorithm to obtain depth reconstructions of material defects from data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Imaging Science Requirements for a Uranus Flagship Mission

Introduction: Our presentation will summarize the requirements for UV/Visible/Near-IR remote-sensing imaging science instruments (including mapping spectrometers) envisioned for the Uranus Orbiter and Probe (UOP) mission recommended by the recent planetary decadal survey. The Uranus system offers many targets for imaging investigations. Imaging science investigations are crucial to answering fundamental questions about various physical processes that shape the Uranian system and drive its evolution. Each science objective addressed through imaging has requirements for observation and illumination geometries as well as coverage and resolution in the spatial, spectral and temporal dimensions. By combining the requirements for the diverse science targets in the Uranian system, we present a set of overarching imaging science requirements for UOP. Atmospheric Science: The study of Uranus’ atmosphere is crucial in understanding the planet's energy balance and interior heat flux. Imaging observations map how the atmosphere scatters incident solar radiation. Imaging is key to characterizing planetary-scale energy/material transport though global atmospheric dynamics and local meteorology. Hyperspectral mapping combined with radiative transfer analysis reveals the vertical distribution of clouds and hazes. Chronicling temporal variabilities of atmospheric features is key to understanding the various processes that operate within the dynamic Uranian atmosphere. A comprehensive understanding of Uranus' atmosphere is essential in deciphering the planet's origins and evolution as well as providing insight into the broader field of planetary and exoplanetary science. Magnetospheric Interactions: Imaging science is critical to understand the elusive Uranian aurorae. Mapping the aurorae and their temporal dynamics will reveal the interaction of Uranus’ complex magnetosphere with the solar wind. The apparent decades-long cooling of Uranus’ upper atmosphere is thought to be due to changes in energy input from the overlying magnetosphere, and so mapping and quantifying the auroral evidence for this energy flux is particularly relevant for upper atmospheric science In addition, Uranus’ large moons may generate auroral footprints, which can be used to constrain the planet’s unusual magnetic field structure. Satellite Interiors: Imaging science can address the potential habitability of the larger moons of Uranus by measuring their shapes and rotational states (including librations), which combined with gravity data are crucial to understanding their internal density structure. Satellite Origins: Origin markers such as organics and volatiles may be preserved on the satellite surfaces, which may be sensed by UV/IR mapping. Imaging combined with the moons’ densities may reveal whether the moons formed in Uranus’ circumplanetary disk, rings, or from ejecta of a giant impact on Uranus. Satellite Geology: Imaging investigations, including stereo imaging to obtain topography, will enable constraining each satellite’s geologic history by investigating the distributions and morphologies of impact craters, tectonic and potential cryovolcanic features, and regolith and mass wasting deposits. These records will help unravel the past complex history of orbital resonances that occurred between Uranian satellites, which may have driven geologic activity. Analyses of these features will also point to resurfacing styles and modification processes important for understanding each moon’s thermal evolution, and any present-day geological activity, including potential subsurface deep oceans or possible current activity. Additionally, hyperspectral imaging will enable mapping the surface composition and identifying the potential presence of material that may point to a subsurface ocean, such as ammonia-bearing species. Rings and Small Moons: Imaging observations elucidate the physical processes that contribute to the complex ring-moon system’s inferred unstable state. Imaging surveys will seek smaller moons and other debris that could provide evidence of past collisions, while precise astrometric data of moons will determine the current dynamical state of the system. Many of Uranus' rings are exceptionally narrow, and images of the rings covering a broad range of longitudes, and high-resolution images of features within the rings will reveal how these rings are confined and maintained, as well as illustrating the rings' internal structure and dynamics. Images of the rings and moons obtained at a variety of wavelengths and lighting conditions are also needed to quantify the composition and the size distribution of the small satellites and ring particles.

K M Sayanagi↗
DOE OSTI2020

Three-dimensional seismic characterization and imaging of the Soda Lake geothermal field

Accurate characterization of subsurface geophysical properties and detection of the fault system are essential for geothermal energy exploration and production. The Soda Lake geothermal field is in western Nevada with a complex fault system. Previous seismic characterization only produced a low-resolution, smooth velocity model along with a simple, conceptual fault model. Using optimized correlation-based full-waveform inversion, wavefield-separation-based reverse-time migration, and automatic fault detection techniques, we present 3D seismic characterization for the Soda Lake geothermal field using 3D surface seismic data acquired with Vibroseis sources. Here, we obtain 3D high-resolution velocity, density, and acoustic impedance models, 3D seismic images with different grid spacings, and a high-resolution fault system. Consistency check between the constructed faults and currently active injection and production geothermal wells verifies that our seismic inversion and imaging results and detected faults are reliable. These results can provide valuable information for optimizing well placement and geothermal energy production at the Soda Lake geothermal field.

15 GEOTHERMAL ENERGY↗
NASA NTRS2016

Determining the 3D Subsurface Density Structure of Taurus Littrow Valley Using Apollo 17 Gravity Data

Surface gravity surveys can detect subsurface density variations that can reveal subsurface geologic features. In 1972, the Apollo 17 (A17) mission conducted the Traverse Gravimeter Experiment (TGE) using a gravimeter that measured the local gravity field near Taurus Littrow Valley (TLV), located on the south-eastern rim of the Serenitatis basin. TLV is hypothesized to be a basaltfilled radial graben resulting from the impact that formed Mare Serenitatis. It is bounded by both the North and South Massifs (NM and SM) as well as other smaller mountains to the East that are thought to be mainly composed of brecciated highland material. The TGE is the first and only successful gravity survey on the surface of the Moon. Other more recent satellite surveys, such as NASA's Gravity Recovery and Interior Laboratory (GRAIL) mission (2011- 2012), have produced the best global gravity field to date (approx. 13km resolution). However, these satellite surveys are not sensitive enough to detect fine-scale (<1km) lunar subsurface structures. This underscores the value of the data collected at the surface by A17. In the original analysis of the data a 2D forward-modelling approach was used to derive a thickness of the subsurface basalt layer of 1.0 km by assuming a simple flat-faced rectangular geometry and using densities derived from Apollo lunar samples. We are investigating whether modern 3D modelling techniques in combination with high-resolution topographical and image datasets can reveal additional fine-scale subsurface structure in TLV.

TGE↗
DOE OSTI2022

Classification of computed thermal tomography images with deep learning convolutional neural network

Thermal tomography (TT) is a computational method for the reconstruction of depth profile of the internal material defects from Pulsed Infrared Thermography (PIT) nondestructive evaluation. Here, the PIT method consists of recording material surface temperature transients with a fast frame infrared camera, following thermal pulse deposition on the material surface with a flashlamp and heat diffusion into material bulk. TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of the subsurface internal defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to the heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify the size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. The performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shapes imported from scanning electron microscopy images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on the TT images of elliptical defects is capable of classifying the shape and orientation of irregular defects.

42 ENGINEERING↗
NASA NTRS2001

Seismoball: A Small Europa Orbiter Drop-Off Probe for Early Exploration of the Europan Surface

Recent magnetometry data received from Galileo indicate that the most likely explanation for the magnetic signature there is indeed a global conducting layer below the surface. This conducting layer is well matched by a salty, mineral rich strata beneath the Europan ice crust or a salt water ocean. Galileo imaging results show a variety of terrain types thought to contain young material; for example, lineaments, chaotic terrain, and eruption features. Additionally, Galileo images have shown indications of areas of up-welling where subsurface material periodically gets pushed to the surface due to the forces of fracturing, butting, and refreezing of the ice sheet. While Europa Orbiter will provide close-flyby high resolution images, as well as magnetometry, spectroscopy and other remote sensing data of the surface, it will not be able to provide essential engineering data like surface hardness and surface ice structure needed to support eventual landed missions. Additionally, ice chemical composition at microscopic scales can only be studied in detail through in situ instrumentation. Seismoball is a small probe designed to be injected into a surface intersect orbit around Europa. Using small reverse thrusters, the probe will be capable of nulling the high horizontal injection velocity as it approaches the 2 km surface injection altitude, thus allowing it to fall to the surface at an impact velocity of < 100m/sec (much less than the DS-2 impact velocities). The external breakaway thruster structure and crushable exterior shell absorb the impact energy while allowing the science instrument suite to remain intact. JPL has already started analyzing the entry dynamics and designing/building a small, low mass probe which will withstand the impact g-forces and fit as a 'carry-on' on board the Europa Orbiter. The probe will carry a suite of 5-6 micro-instruments for imaging the surface (both microscopic and far-field), surface and shallow subsurface ice temperatures, surface hardness, crustal dynamics and periodicity, and compositional chemistry. If selected, this flight development activity will provide a unique science opportunity and adjunct to the primary Orbiter science mission. The final flight system will be designed to accommodate orbiter mass, volume, and power interface constraints, as well as entry dynamics, g-load mitigation, and arbitrary landing orientation.

Tamppari, L.↗
DOE OSTI2020

Magnetotelluric Data from Mountain Home, ID

This dataset includes magnetotelluric transfer functions in the form of EDI files for 16 stations collected by the USGS and 40 stations collected by Quantec Geoscience for Lawerence Berkeley National Lab around the Mountain Home area in Idaho. A 3D electrical resistivity model is included that images resistive and conductive bodies in the subsurface that maybe important for geothermal characterization. The model was created using ModEM using the high performance computer Yeti at the USGS.

15 GEOTHERMAL ENERGY↗
NASA NTRS1974

Fabrication of an extreme ultraviolet glancing incidence telescope

A technique is described for use in the fabrication of glancing incidence telescopes which operate at large grazing angles (i.e., 8 to 15 degrees). Precision conic section plunge laps are used in a controlled grinding procedure to initially generate imaging surfaces which have a minimum of subsurface damage. A numerically controlled Moore Number 3 Measuring Machine is used throughout the fabrication procedure. Surface geometry accuracies on the order of one-tenth micron have been achieved.

Fleetwood, C. M.↗
NASA NTRS2004

On the Dielectric Properties of the Martian-like Surface Sediments

We have undertaken laboratory electromagnetic characterization of the total set of minerals identified by TES on the Martian surface in order to investigate experimentally the dielectric properties of the sediments covering it in the frequency range from 1 to 30 MHz. Volcanic Rocks with a well defined mineralogy and petrology from potential terrestrial analogues sites have also been included in the study. Our primary objective is to evaluate the range of electrical and magnetic losses that may be encountered by the various Radar sounding and imaging experiments dedicated to map the Martian subsurface searching for underground water. The electromagnetic properties of these Mars-like materials will be presented as a function of various geophysical parameters, such as porosity, bulk density and temperature. The secondary objective, is to locate regions were surface dielectric conditions are suitable for subsurface sounding.

Heggy, E.↗
NASA NTRS2010

Resonant difference-frequency atomic force ultrasonic microscope

A scanning probe microscope and methodology called resonant difference-frequency atomic force ultrasonic microscopy (RDF-AFUM), employs an ultrasonic wave launched from the bottom of a sample while the cantilever of an atomic force microscope, driven at a frequency differing from the ultrasonic frequency by one of the contact resonance frequencies of the cantilever, engages the sample top surface. The nonlinear mixing of the oscillating cantilever and the ultrasonic wave in the region defined by the cantilever tip-sample surface interaction force generates difference-frequency oscillations at the cantilever contact resonance. The resonance-enhanced difference-frequency signals are used to create images of nanoscale near-surface and subsurface features.

Cantrell, John H.↗
DOE OSTI2022

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Lytic archaeal viruses infect abundant primary producers in Earth’s crust

The continental subsurface houses a major portion of life’s abundance and diversity, yet little is known about viruses infecting microbes that reside there. Here, we use a combination of metagenomics and virus-targeted direct-geneFISH (virusFISH) to show that highly abundant carbon-fixing organisms of the uncultivated genus Candidatus Altiarchaeum are frequent targets of previously unrecognized viruses in the deep subsurface. Analysis of CRISPR spacer matches display resistances of Ca. Altiarchaea against eight predicted viral clades, which show genomic relatedness across continents but little similarity to previously identified viruses. Based on metagenomic information, we tag and image a putatively viral genome rich in protospacers using fluorescence microscopy. VirusFISH reveals a lytic lifestyle of the respective virus and challenges previous predictions that lysogeny prevails as the dominant viral lifestyle in the subsurface. CRISPR development over time and imaging of 18 samples from one subsurface ecosystem suggest a sophisticated interplay of viral diversification and adapting CRISPR-mediated resistances of Ca. Altiarchaeum. We conclude that infections of primary producers with lytic viruses followed by cell lysis potentially jump-start heterotrophic carbon cycling in these subsurface ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1990

Helioseismic imaging of sunspots at their antipodes

Recent work by Braun et al. (1988) has shown that sunspots absorb helioseismic waves. It is proposed that sunspot absorption causes a seismic deficit that should be imaged at the antipode of the sunspot. If these images are observable, it should be possible to produce seismic maps of magnetic regions on the far side of the sun. Diagnostic applications would include lifetimes of higher-frequency modes, and possibly rotation of the solar interior and detection of subsurface magnetic structure. Elements of the theory of seismic imaging are outlined. The extention of acoustic holography to solar interior diagnostics in the context of antipodal imaging is proposed.

Lindsey, Charles↗
NASA NTRS2024

Dielectric Permittivity Measurements of Geologic Samples at Venus Surface Temperatures

Synthetic-aperture radar (SAR) and radar sounding are two powerful remote sensing techniques used to examine the surface and subsurface of planets. Their value is critical in the case of Venus due to this planet’s global and visually opaque cloud layer. The recently selected VERITAS and EnVision orbital missions, slated to study the planet in the early 2030’s, employ radar instruments to image the surface (VERITAS and EnVision) and probe the subsurface (EnVision). For both techniques, the complex dielectric permittivity of the surface and subsurface materials control radar backscatter intensity and penetration depth. Since the 1970’s, many studies have characterized the dielectric permittivity of geologic materials collected both on Earth and on the Moon to constrain the radar reflectivity and transparency at a variety of radar frequencies [e.g., 1]. Two consistent findings from those studies are that complex permittivity depends on both the density (or porosity) and the composition of the material. Denser materials and more metal-rich compositions tend to have higher permittivity values and to incur greater propagation path loss. Water content also elevates permittivity of otherwise dry rocks/soils/regolith [e.g., 2]. However, permittivity is independent of frequency for the 0.5-18 GHz range, within which SAR imaging commonly lies. The one aspect poorly explored thus far is the effect of elevated temperatures on dielectric permittivity. Previous work suggests that increased lattice vibrations and flow of free electrons associated with an increase in temperature elevate both the real (reflectivity) and imaginary (path loss) parts of the complex permittivity. We are currently conducting a 3-year campaign to measure the complex dielectric permittivity of Venusrelevant geologic materials at Venus surface temperatures (380°C - 460°C) and with frequencies relevant to VERITAS, EnVision, and Magellan imaging synthetic aperture radars.

M Barmatz↗
NASA NTRS2004

Surface Penetrating Radar Simulations for Europa

The space environment above the icy surface of Europa is a source of radio noise in this frequency range from natural sources in the Jovian magnetosphere. The ionospheric and magnetospheric plasma environment of Europa affects propagation of transmitted and return signals between the spacecraft and the solid surface in a frequency-dependent manner. The ultimate resolution of the subsurface sounding measurements will be determined, in part, by a capability to mitigate these effects. We discuss an integrated multi-frequency approach to active radio sounding of the Europa ionospheric and local magnetospheric environments, based on operational experience from the Radio Plasma Imaging @PI) experiment on the IMAGE spacecraft in Earth orbit, in support of the subsurface measurement objectives.

Markus, T.↗