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NASA NTRS2015

Clays and Carbonates in a Groundwater-Fed 3.8 Ga Martian Lake: Insights to Subsurface Habitability on Mars

On Earth, the deep biosphere remains a largely unexplored, but clearly important carbon reservoir. Results from some uplifted central peaks in craters on Mars indicate that substantial carbon was also present at depth and might have helped sustain a deep biosphere. In fact, many factors relevant to deep biosphere habitability are more favorable on Mars than on Earth (e.g. porosity of the crust, geothermal gradient). Future exploration of Mars should include landing sites where materials have been exhumed from depth by meteor impact or basins where subsurface fluids have emerged, carrying clues to subsurface habitability. One of the most astrobiologically interesting sites on Mars McLaughlin Crater, a 93 km-diameter impact crater that formed approximately 4 b.y. ago. On the floor of the crater is a stratigraphic section of subhorizontal, layered sedimentary rocks with strong spectroscopic evidence for Fe-rich clay minerals and Mg-rich carbonates, which we interpret as ancient lacustrine deposits. The fluids that formed these materials likely originated in the subsurface, based on the paucity of channels leading into the crater basin and the fact that this is one of the deepest basins on Mars - a good candidate to have experienced upwelling of subsurface fluids. Therefore, the deposits within McLaughlin crater provide insight into subsurface processes on Mars. In this presentation, we will discuss the habitability of the martian subsurface as well as the geology of McLaughlin Crater and the possibility to detect biomarkers at that site with a future landed mission.

Michalski, Joseph↗

NASA NTRS2019

Subsurface Cl-bearing salts as potential contributors to recurring slope lineae (RSL) on Mars

We report laboratory experimental results that support a brine-related hypothesis for the recurring slope lineae (RSL) on Mars in which the subsurface Cl-salts, i.e., hydrous chlorides and oxychlorine salts (HyCOS) are the potential source materials. Our experiments revealed that within the observed RSL temperature window TRSL (250–300 K), the deliquescence of HyCOS could occur in relative humidity ranges (RH≥22%–46%) much lower than those for hydrous (Mg, Fe)-sulfates (RH≥75%–96%). In addition, we demonstrated that the RH values kept by common HyCOS and hydrous sulfates in enclosures have a general trend as RH(sulfates) > RH(perchlorates) > RH(chlorides) (with same type of cation) in wide T range. It means that the required RH range for a Cl-bearing salt to deliquescence can be satisfied by a co-existing salt of different type, e.g., in the subsurface layers of mixed salts on Mars. Furthermore, we found a strong temperature dependence of the deliquescence rates for all tested HyCOS, e.g., a duration of 1–5 sols for all HyCOS at the high end (300 K) of TRSL, and of 20–70 sols for all tested HyCOS (except NaClO4·H2O) at the low end (250 K) of TRSL, which is consistent with the observed seasonal behavior of RSL on Mars. From a mass-balance point of view, the currently observed evidences on Mars do not support a fully-brine-wetted track model, thus we suggest a brine-triggered granular-flow model for the most RSL. Considering the recurrence of RSL in consecutive martian years, our experimental results support the rehydration of remnant HyCOS layers during a martian cold season through H2O vapor-to-salt direct interaction. We found that the evidences of HyCOS rehydration under Mars relevant P-T-RH conditions are detectable in a few minutes by in situ Raman spectroscopy. This rehydration would facilitate the recharge of H2O back into subsurface HyCOS, which could serve as the source material to trigger RSL in a subsequent warm season. The major limiting factor for this rehydration is the H2O supply, i.e., the H2O vapor density carried by current Mars atmospheric circulation and the diffusion rate of H2O vapor into the salt-rich subsurface in a cold season. In a worst-case scenario, these H2O supplies can support a maximum increase of hydration degrees of two for totally dehydrated HyCOS, whereas the full rehydration of subsurface HyCOS layers can be easily reached during a>30° obliquity period that has H2O vapor density 10× to 20× times the value of current obliquity. Overall, our results imply the existence of a large amount of Cl-bearing salts in the subsurface at RSL sites.

Alian Wang↗

NASA NTRSDate not supplied

Repurposing Drilling Control Diagnostics for Subsurface Edge Detection and Boundary Advisement During Planetary Drilling

Informed decision-making during lunar drilling and sampling missions will require data monitoring tools and specialized ground data systems. Accurate and updated situational awareness, with ongoing data monitoring, is critical for timely responses by to incoming science data. Traverse plans and scheduled activities may need to be flexibly changed in order to react to unexpected data or situations. Unlike (for example) Mars missions, the relative lightspeed closeness of the Moon allows for near-real-time ground processing of incoming mission and instrument data. An Apollo-class lunar regolith drill will in a sense “travel” a meter or two vertically at a given subsurface characterization site. As the drill penetrates into lunar regolith, it is likely to encounter a range of material densities, orientations, fracture toughness, and (perhaps) ice percentages. Lunar drill telemetry can provide science teams with a valuable first look into the subsurface structure, the regolith bulk properties, and constituents at each drilled site. Real-time AI-based recognition and reaction to downhole situations has been developed for automated deeper drilling on Mars and beyond. We can leverage the same knowledge bases and pattern-matching as areal-time interpreter of the subsurface, a situational awareness tool during drilling operations. We recently (Sept. 2019) demonstrated this AI drilling monitoring and analysis capability, in control of in-situ drilling and sampling operations, mounted on a KREX-2 rover in Chile’s Atacama Desert. Terrestrial automated drilling log analyses in oil exploration have used similar machine learning techniques in classifying and identifying features in drilling logs –but these typically are designed assuming a drilling fluid influencing downhole measurements and data (permeability, resistivity). Drilling models and existing AI software designed to detect and respond to drilling faults and hard materials can be repurposed, for near-real-time (ground-based) interpretation of drilling telemetry –a potentially valuable advisory tool for strata boundaries and changes in drilling parameters. On the Moon, this approach could be used to study the structure and to some extent the composition of lunar regolith vs. borehole depth, based on recognizable variations in fracture hardness, drilling energy and penetration rates while actively drilling. Since the early 2000s, a series of increasingly-capable real-time drilling telemetry interpretation and characterization software tools have been developed. These subsurface models and software tools have monitored the real-time drilling data received, and automatically identified changes in drill behavior (e.g., encountering a harder target layer, bit inclusions, drill choking due to infall downhole, and others) correlating these with subsurface structures and features. We discuss the mappings between drill borehole parameters, faults or events detected, and modeled changes in rock layer boundaries, in examples drawn from field testing at analog sites in an Arctic impact crater, Rio Tinto, and Chile’s Atacama Desert. These demonstrate how subsurface structural boundaries led to fault detections and responses by the software.

drilling advisor↗

DOE OSTI2022

Deep-learning-guided high-resolution subsurface reflectivity imaging with application to ground-penetrating radar data

Subsurface reflectivity imaging is one of the most important geophysical characterization methods for revealing subsurface structures. In many cases, accurate subsurface reflectivity imaging is challenging because of, for example, random or coherent noise in the data and sparse source-receiver observation geometry. Here, we develop a deep-learning-guided iterative imaging method to improve subsurface structure imaging. Specifically, we train a supervised neural network to infer a noise-free, high-resolution image from a noisy, low-resolution image and use this estimated image as guidance to regularize least-squares imaging. We develop a systematic method to generate high-quality synthetic training data (data-label pairs) to train the guidance neural network. The trained neural network can provide high-fidelity predictions even for field-data images that are not in the training data. We validate our new imaging method using one synthetic and two field ground-penetrating radar data examples, and find that our method can produce clean, high-resolution subsurface reflectivity images where existing single-pass and least-squares imaging methods fail due to noise and insufficient data coverage.

58 GEOSCIENCES↗

DOE OSTI2023

Distinct Depth-Discrete Profiles of Microbial Communities and Geochemical Insights in the Subsurface Critical Zone

Microbial assembly and metabolic potential in the subsurface critical zone (SCZ) are substantially impacted by subsurface geochemistry and hydrogeology, selecting for microbes distinct from those in surficial soils. In this study, we integrated metagenomics and geochemistry to elucidate how microbial composition and metabolic potential are shaped and impacted by vertical variations in geochemistry and hydrogeology in terrestrial subsurface sediment. A sediment core from an uncontaminated, pristine well at Oak Ridge Field Research Center in Oak Ridge, Tennessee, including the shallow subsurface, vadose zone, capillary fringe, and saturated zone, was used in this study. Our results showed that subsurface microbes were highly localized and that communities were rarely interconnected. Microbial community composition as well as metabolic potential in carbon and nitrogen cycling varied even over short vertical distances. Further analyses indicated a strong depth-related covariation of community composition with a subset of 12 environmental variables. An analysis of dissolved organic carbon (DOC) quality via ultrahigh resolution mass spectrometry suggested that the SCZ was generally a low-carbon environment, with the relative portion of labile DOC decreasing and that of recalcitrant DOC increasing along the depth, selecting microbes from copiotrophs to oligotrophs and also impacting the microbial metabolic potential in the carbon cycle. Our study demonstrates that sediment geochemistry and hydrogeology are vital in the selection of distinct microbial populations and metabolism in the SCZ.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Characterization and response of three TNT equivalent materials in subsurface explosions

Energetic compositions utilized for inducing seismic responses are often referred to in terms of their TNT equivalent, a metric which is often misused because observations of interest are not often understood with respect to explosive characteristics. Here, in this investigation, we characterize three energetic compositions used to elicit seismic responses in a highly instrumented testbed to further our understanding of subsurface TNT equivalence. Three different energetic sources are prepared and studied for their fidelity to thermochemically predicted detonation behavior. We present effects of subsurface detonation on subsurface rock and seismic emission as a function of energetic source material within the testbed. Field experiments were conducted using a single thermochemical yield of 5 kg using diverse sources consisting of nitromethane, ammonal, and PBXN‐5 (an HMX based plastic bonded explosive) mixtures at the Energetic Materials Research and Testing Center in Socorro, New Mexico. Relative performance of energy density‐related detonation parameters, such as detonation velocity and pressure, affect the observed response in the subsurface. Most notable, equal thermochemical yields described in terms of TNT equivalence do not correlate to equal thermochemical effects in the subsurface.

Blue Canyon Dome↗

DOE OSTI2025

Toward more-robust, AI-enabled subsurface seismic imaging for geotechnical applications

Non-invasive seismic imaging has the potential to cost-effectively evaluate large volumes of subsurface material to inform geotechnical site investigation. However, seismic imaging using full waveform inversion (FWI) requires significant computational time and is dependent on an initial starting model. As a result, FWI has not yet been widely adopted into geotechnical practice. Previous efforts, on relatively simple two-layered models, indicate that data-driven artificial intelligence (AI) models may be as effective as FWI at predicting 2D images of shear wave velocity (V s ). Furthermore, the AI model predictions can be made almost instantaneously after data acquisition and do not require an initial starting model. We examine the generality of these findings by developing a new AI model for subsurface seismic imaging, whereby we make several notable contributions. First, we architect a multimodal AI model that combines time- and frequency-domain representations of the seismic wavefield to predict a 50 m by 20 m subsurface image of V s . Second, we developed a new diverse dataset of 100,000 images with their corresponding seismic wavefields to train the AI model. Third, we propose four physics-informed data augmentations for data-driven seismic imaging. Fourth, we develop two prediction consistency tests to evaluate the model’s performance when the true subsurface is unknown. Our final model, which has been made publicly available, is capable of predicting a subsurface V s image from a single seismic wavefield with an average, mean absolute percent error (MAPE) of 24 %. The predictive model is applied to a field dataset and shown to be consistent with local geology and shear-wave refraction measurements from the same location.

Artificial intelligence↗

DOE OSTI2021

Interfacial and Confinement-Mediated Organization of Gas Hydrates, Water, Organic Fluids, and Nanoparticles for the Utilization of Subsurface Energy and Geological Resources

Harnessing the subsurface geologic environments in an efficient and environmentally sustainable manner is challenged by uncertainties associated with predicting the fate of fluids and sustaining porosity and permeability in subsurface geologic environments. Some of these uncertainties arise from confined and interfacially induced structures of fluids in subsurface geologic environments. The formation of gas hydrates, phase transitions of confined fluids, assembly and deposition of heavy hydrocarbons, and the agglomeration and fate of nanoparticles in confined environments are summarized in this review. Nanoscale confinement contributes to anisotropic structures and dynamics of fluids, which is the basis for anomalous phase transition thermodynamics, reactivity, transport, and geomechanical behavior. In this review, we discuss the structures of confined fluids and deviation in observed properties from bulk fluids. The factors influencing the structures of confined fluids can be generally divided into two groups: (a) pore characteristics including pore size, pore surface chemistry, and pore geometry and (b) confined fluid/solid characteristics such as molecular structure, concentrations, charges, pore filling, and presence of additives. Scientific advancements and knowledge gaps in our understanding of the structures of confined fluids and the associated differences in observed properties compared to bulk fluids are discussed. Here, the phenomena discussed in this review are of particular relevance to our efforts in harnessing the subsurface environments for a low carbon future by increasing the utilization of geothermal energy, using CO 2 as a working fluid, and storing CO 2 in subsurface geologic environments.

42 ENGINEERING↗

DOE OSTI2021

Emergence of Subsurface Oxygen on Rh(111)

Oxygen atoms on transition metal surfaces are highly mobile under the demanding pressures and temperatures typically employed for heterogeneously catalyzed oxidation reactions. This mobility allows for rapid surface diffusion of oxygen atoms, as well as absorption into the subsurface and reemergence to the surface, resulting in variable reactivity. Subsurface oxygen atoms play a unique role in the chemistry of oxidized metal catalysts, yet little is known about how subsurface oxygen is formed or returns to the surface. Furthermore, if oxygen diffusion between the surface and subsurface is mediated by defects, there will be localized changes in the surface chemistry due to the elevated oxygen concentration near the emergence sites. We observed that oxygen atoms emerge preferentially along the boundary between surface phases and that subsurface oxygen is depleted before the surface oxide decomposes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Deep Learning for Subsurface Flow: A Comparative Study of U‐Net, Fourier Neural Operators, and Transformers in Underground Hydrogen Storage

Subsurface flow research is essential for the sustainable management of natural resources and the environment. Deep learning (DL) has significantly advanced this field by developing efficient and accurate surrogate models to replace computationally expensive physics‐based simulations. These surrogate models are commonly used to predict the spatiotemporal evolution of state variables, such as gas saturation and reservoir pressure, in heterogeneous geological formations. Despite the various DL models applied to this task, there is a lack of studies systematically comparing their performance. This absence of comparative analysis leads to somewhat arbitrary DL model selection in subsurface flow research, resulting in suboptimal performance and potentially inaccurate predictions. To bridge this gap, we conduct a systematic comparison study of three popular DL architectures—U‐Net, Fourier Neural Operators (FNO), and Segmentation Transformer (SETR)—in surrogate modeling of underground hydrogen storage (UHS). We focus on UHS due to its promise of enhancing clean energy resilience and its cyclic operational conditions that represent common scenarios in various subsurface applications. We evaluate the models based on accuracy, training cost, and inference speed. The comparison shows that U‐Net achieves the highest accuracy, followed by SETR and FNO. Despite its lower accuracy, FNO has the highest inference speed. SETR offers competitive accuracy with the least training memory usage, demonstrating the potential of transformers in learning subsurface flow. Our results provide guidance for selecting DL models for surrogate modeling in a wide range of subsurface flow problems.

42 ENGINEERING↗

DOE OSTI2020

Hydrogen desorption from the surface and subsurface of cobalt

The influence of coverage on the diffusion of hydrogen into the subsurface of cobalt was studied using density functional theory (DFT) and temperature programmed desorption (TPD). DFT calculations show that as the hydrogen coverage on Co(0001) increases, the barrier for hydrogen diffusion into the bulk decreases by 20%. Additionally, subsurface hydrogen on a hydrogen covered surface was found to be more stable when compared to a clean cobalt surface. To test these theoretical findings experimentally, excited hydrogen was used in an ultra-high vacuum environment to access higher hydrogen coverages. Here, our TPD studies showed that at high hydrogen coverages, a sharp low temperature feature appeared, indicating the stabilization of subsurface hydrogen. Further DFT calculations indicate that this sharp low temperature feature results from associative hydrogen desorption from a hydrogen saturated surface with a population of subsurface hydrogen. Microkinetic modelling was used to model the TPD spectra for hydrogen desporption from cobalt with and without subsurface hydrogen, showing reasonable agreement with experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Effect of surface steps on chemical ordering in the subsurface of Cu(Au) solid solutions

Atomic steps are typically assumed to only influence surface phenomena of solids. In contrast, in this paper we show, using in-situ atomic-resolution electron microscopy observations and atomistic modeling, the pronounced effect from surface stepsin inducing compositional and structural evolution in the subsurface of a Cu(Au) solid solution. We find that Au surface segregation results in a stacked sequence of Cu-Au ordered phases in the subsurface. The presence of a monatomic step at the surface induces the formation of an anti-phase boundary that extends from the surface step to deeper layers by maintaining the same composition profile associated with each terrace. The bunching of surface steps induces chemical disordering of the Cu-Au ordered phases in the subsurface region of the bunched steps. These results demonstrate the instant propagation of surface dynamics of atomic steps into the subsurface region and can find broader applicability in utilizing surface defects to tune the composition and structure in the subsurface of alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Historical Subsurface Cooling in the Tropical Pacific and Its Dynamics

Abstract Understanding how the tropical Pacific responds to rising greenhouse gases in recent decades is of paramount importance given its central role in global climate systems. Extensive research has explored the long-term trends of tropical Pacific sea surface temperatures (SSTs) and the overlying atmosphere, yet the historical change in the upper ocean has received far less attention. Here, we present compelling evidence of a prominent subsurface cooling pattern along the thermocline in the central-to-eastern tropical Pacific since 1958. This subsurface cooling has been argued to be contributing to the observed cooling or lack of warming of the equatorial cold tongue SST. We further demonstrate that different mechanisms are responsible for different parts of the subsurface cooling. In the central-to-eastern equatorial Pacific and the southeastern off-equatorial Pacific, where zonal wind stress strengthens, a pronounced subsurface cooling trend emerges just above the thermocline that is closely tied to increased Ekman pumping. In the eastern equatorial Pacific where zonal wind stress weakens, the westward surface current and eastward Equatorial Undercurrent weaken as well, resulting in reduced vertical current shear and increased ocean stability, which suppresses vertical mixing and leads to local cooling. We conclude that the historical subsurface cooling is primarily linked to dynamical adjustments of ocean currents to tropical surface wind stress changes.

Jiang, Feng↗

DOE OSTI2021

Imaging Complex Subsurface Structures for Geothermal Exploration at Pirouette Mountain and Eleven-Mile Canyon in Nevada

Accurate imaging of subsurface complex structures with faults is crucial for geothermal exploration because faults are generally the primary conduit of hydrothermal flow. It is very challenging to image geothermal exploration areas because of complex geologic structures with various faults and noisy surface seismic data with strong and coherent ground-roll noise. In addition, fracture zones and most geologic formations behave as anisotropic media for seismic-wave propagation. Properly suppressing ground-roll noise and accounting for subsurface anisotropic properties are essential for high-resolution imaging of subsurface structures and faults for geothermal exploration. We develop a novel wavenumber-adaptive bandpass filter to suppress the ground-roll noise without affecting useful seismic signals. This filter adaptively exploits both characteristics of the lower frequency and the smaller velocity of the ground-roll noise than those of the signals. Consequently, this filter can effectively differentiate the ground-roll noise from the signal. We use our novel filter to attenuate the ground-roll noise in seismic data along five survey lines acquired by the U.S. Navy Geothermal Program Office at Pirouette Mountain and Eleven-Mile Canyon in Nevada, United States. We then apply our novel anisotropic least-squares reverse-time migration algorithm to the resulting data for imaging subsurface structures at the Pirouette Mountain and Eleven-Mile Canyon geothermal exploration areas. The migration method employs an efficient implicit wavefield-separation scheme to reduce image artifacts and improve the image quality. Our results demonstrate that our wavenumber-adaptive bandpass filtering method successfully suppresses the strong and coherent ground-roll noise in the land seismic data, and our anisotropic least-squares reverse-time migration produces high-resolution subsurface images of Pirouette Mountain and Eleven-Mile Canyon, facilitating accurate fault interpretation for geothermal exploration.

15 GEOTHERMAL ENERGY↗

NASA NTRS2003

An Examination of Issues Related to a Europa Subsurface Component for the JIMO Mission

The Galileo Europa data set served to revolutionize our view of Europa. In particular the strong evidence of a large, cold, salty Ocean beneath 5-30 km of ice has profoundly altered the significance of Europa in our thinking, especially of context of habitability in the solar system. While much remains to be learned from spacecraft observations of several sorts, there are significant questions answerable only by in-situ techniques; these relate to the formation of Europa, the nature of its ocean, and the prospects for life in its ocean, sediments, and ice. We feel that wide-ranging discussion of an in-situ subsurface mission to Europa, as part of JIMO, should proceed. The science objective of the mission is to characterize the icy shell of Europa to resolve its provenance, estimate the composition of brine of the Europa ocean, and search for evidence of Earth-like life. Probably anyone would agree that an in-situ mission to Europa would be of great value, but he or she would also immediately take the position that such a mission is utterly impractical. We take the position here of defining the least complex mission that can nonetheless justify its cost and to argue that such a mission is realistic enough that it should be seriously considered. Our mission thinking has been: 1) Soft landing. A soft lander is required on a site sufficiently flat to offer a stable platform; no further site selectivity is required. 2) Subsurface exploration. The Europa subsurface must be examined. Surficial processes on Europa arguably have exposed the upper 200 m of shell to chemical effects from the Jovian radiation belts as well as cometary infall, etc; to examine native ice we must descend below that point to, for discussion, 300 m. At that depth we argue that the ice is characteristic of ice at depth and possibly is effectively sea ice. 3) Science data. A few simple measurements at various depths and at 300 m constitute a scientifically successful mission. Measurements would include analysis of meltwater for a few inorganic ions and amino acids and an optical examination of the borehole wall. 4) Communication. Transmission of data to an orbiter is essential, but we will constrain the landed mission to a daily communication over a few days. 5) Subsurface access. Drilling to 300 m is a significant challenge; it can be addressed by several means: Thermal Probe (Cryobot) which permits water to refreeze above the vehicle. This is our tentative choice with plutonium as the fuel to generate thermal energy for drilling and electrical power for operations. Open Hole Drill, a thermal system in which the meltwater is removed for greater thermal efficiency. Meltwater removal on Europa is both a complexity and a risk, but analysis is improved. Mechanical Drilling in which cutting or grinding generates ice chips which are removed. This is too complex at Europa temperatures. The measurement objectives for the mission will be: Obj. 1: Determine the concentration of simple inorganic salts in the Europa Ice Shell and, by extrapolation, of the ocean. These data will also validate spaceborne sensors. Obj. 2: Determine the nature and abundance of amino acids in the ice such that cometary infall material in the upper ice can be compared to material at depth. Obj. 3: Optically examine the ice to resolve inclusion structure, particulate content, and stratification. Access to 300 m depth is a significant if not audacious plan; we are aware that this has not been done on any planetary body. Our approach is the use of a plutonium heat source; to overcome Europa's surface temperature and to melt ice a significant amount of plutonium is needed, and significant shielding and other protective steps will be required. The quantity of plutonium is a key concern. The mission will require subsurface collection and processing of samples for in situ analysis, calling for a miniature, high pressure micro-sampling system designed to meet needs of instruments that require low presses for operation. The inlet system itself collects a micro-sample in the external high pressure environment, then transfers it into a protected low pressure environment for analysis.

Carsey, F. D.↗

NASA NTRS2004

Subsurface Stress Fields in FCC Single Crystal Anisotropic Contacts

Single crystal superalloy turbine blades used in high pressure turbomachinery are subject to conditions of high temperature, triaxial steady and alternating stresses, fretting stresses in the blade attachment and damper contact locations, and exposure to high-pressure hydrogen. The blades are also subjected to extreme variations in temperature during start-up and shutdown transients. The most prevalent high cycle fatigue (HCF) failure modes observed in these blades during operation include crystallographic crack initiation/propagation on octahedral planes, and non-crystallographic initiation with crystallographic growth. Numerous cases of crack initiation and crack propagation at the blade leading edge tip, blade attachment regions, and damper contact locations have been documented. Understanding crack initiation/propagation under mixed-mode loading conditions is critical for establishing a systematic procedure for evaluating HCF life of single crystal turbine blades. This paper presents analytical and numerical techniques for evaluating two and three dimensional subsurface stress fields in anisotropic contacts. The subsurface stress results are required for evaluating contact fatigue life at damper contacts and dovetail attachment regions in single crystal nickel-base superalloy turbine blades. An analytical procedure is presented for evaluating the subsurface stresses in the elastic half-space, based on the adaptation of a stress function method outlined by Lekhnitskii. Numerical results are presented for cylindrical and spherical anisotropic contacts, using finite element analysis (FEA). Effects of crystal orientation on stress response and fatigue life are examined. Obtaining accurate subsurface stress results for anisotropic single crystal contact problems require extremely refined three-dimensional (3-D) finite element grids, especially in the edge of contact region. Obtaining resolved shear stresses (RSS) on the principal slip planes also involves considerable post-processing work. For these reasons it is very advantageous to develop analytical solution schemes for subsurface stresses, whenever possible.

Arakere, Nagaraj K.↗

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↗

NASA NTRS2019

Ocean Subsurface Study from ICESat-2 Mission

NASA has launched the ICESat-2 mission in September 2018 with the primary purpose of monitoring changes in the cryosphere. Fortunately, the measured photons over ocean region provide great opportunity for the ocean subsurface study. We have proposed a novel algorithm to determine ocean subsurface optical properties, such as, diffuse attenuated coefficient, kd (/m), total backscattering coefficients bb (/m), attenuated backscatter coefficient and particulate backscattering coefficients b(sub bp) (/m) from ICESat-2/ATLAS lidar measurements. Our ICESat-2 ocean subsurface results reveal high vertical resolution of these optical properties through the water column that are hidden from the passive ocean color record. Moreover, we can estimate the particulate organic carbon (POC) and phytoplankton carbon biomass based on the ICESat-2 retrieved particulate backscattering coefficients b( sub bp) results. We will present and discuss the first ICESat-2 ocean subsurface profile results, especially in polar region where passive ocean color measurements are difficult to make. We will also present the multiple scattering effects on the ocean subsurface optical properties retrieval.

Xiaomei Lu↗