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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

UNESE Data Analysis-Disko Elm Gas Transport Characteristics (NA-22 Quarterly Report)

Recently published papers have demonstrated the impact of sorption mechanisms on gas transport in the subsurface following an underground nuclear explosion. To include sorption processes in the multi-physics models of noble gas production and transport, researchers have conducted experiments of gas sorption in geologic materials and calibrated a linear (Henry’s law) sorption model for all gases in various geologic materials. As a part of Task #4, we requested the experimental data from Sandia Laboratories and derived a dual-mode (Henry’s absorption and Langmuir adsorption) sorption model. The derived model better describes the nonlinear sorption mechanism with much higher fitness with the experimental data. When gas concentrations are relatively low (in the conditions of field experiments or underground nuclear explosions) compared to those used sorption experiments, the nonlinear sorption model can be approximated as a linear sorption model. The equivalent Henry’s constant, which equals the product of Langmuir capacity and affinity, is systematically higher than the literature values. Further analyses and comparison of sorption models are planned in FY2020 Q4 and the sorption model will be coupled in models of nonisothermal multiphase transport for studying noble gas detectability.

58 GEOSCIENCES↗
NASA NTRS2013

Challenges in Quantifying Pliocene Terrestrial Warming Revealed by Data-Model Discord

Comparing simulations of key warm periods in Earth history with contemporaneous geological proxy data is a useful approach for evaluating the ability of climate models to simulate warm, high-CO2 climates that are unprecedented in the more recent past. Here we use a global data set of confidence-assessed, proxy-based temperature estimates and biome reconstructions to assess the ability of eight models to simulate warm terrestrial climates of the Pliocene epoch. The Late Pliocene, 3.6-2.6 million years ago, is an accessible geological interval to understand climate processes of a warmer world4. We show that model-predicted surface air temperatures reveal a substantial cold bias in the Northern Hemisphere. Particularly strong data-model mismatches in mean annual temperatures (up to 18 C) exist in northern Russia. Our model sensitivity tests identify insufficient temporal constraints hampering the accurate configuration of model boundary conditions as an important factor impacting on data- model discrepancies. We conclude that to allow a more robust evaluation of the ability of present climate models to predict warm climates, future Pliocene data-model comparison studies should focus on orbitally defined time slices.

Salzmann, Ulrich↗
NASA NTRS1987

Wind ripples in low density atmospheres

The effect of varying fluid density (rho) on particle transport was examined by conducting tests at atmospheric pressures between 1 and 0.004 bar in the Martian Surface Wind Tunnel (MARSWIT). This study specifically concerns the effect of varying rho on the character of wind ripples, and elicits information concerning generalized ripple models as well as specific geological circumstances for ripple formation such as those prevailing on Mars. Tests were conducted primarily with 95 micron quartz sand, and for each atmospheric pressure chosen, tests were conducted at two freestream wind speeds: 1.1 U*(t) and 1.5 U*(t), where U*(t) is saltation threshold. Preliminary analysis of the data suggests: (1) ballistic ripple wavelength is not at variance with model predictions; (2) an atmospheric pressure of approximately 0.2 bar could represent a discontinuity in ripple behavior; and (4) ripple formation on Mars may not be readily predicted by extrapolation of terrestrial observations.

Miller, J. S.↗
NASA NTRS2004

Numerical Modeling of Glaciers in Martian Paleoclimates

Numerous geologic features suggest the presence of ice flow on the surface of mars. These features include lobate debris aprons, concentric crater fill, and lineated valley fill. The lateral extent of these features can range from 100 meters to over 20 km. Previous work has demonstrated that these features could not have formed in current Martian conditions. It has long been speculated that changes in Mars orbital properties, namely its obliquity, eccentricity, and argument of perihelion, can result in dramatic changes to climate. Recent climate model studies have shown that at periods of increased obliquity north polar water ice is mobilized southward and deposited at low ad mid latitudes. Mid latitude accumulation of ice would provide the necessary conditions for rock glaciers to form. A time-marching, finite element glacier model is used to demonstrate the ability of ice and ice-rock mixtures to flow under Martian paleoclimate conditions. Input to this model is constrained by the NASA Ames Mars General Circulation Model (MGCM).

Colaprete, A.↗
DOE OSTI2020

Multi-Model and Multi-Scale Global Sensitivity Analysis for Identifying Controlling Processes of Complex Systems

An environmental model consists of multiple process level sub-models, and each sub-model represents a process that is key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this project develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods with variance-based global sensitivity analysis to address uncertainty in process models and parameters. The new method yields three process sensitivity indices. The first one is called first-order process sensitivity index, and it is derived as a single summary measure of relative process importance. Evaluating the index is computationally expensive, because it relies in a Monte Carlo scheme that requires thousands and even millions of model executions. To reduce computational cost, this project develops a computationally efficient, quasi Monte Carlo method, and this method is presented in Chapter 2 of this report with and a numerical example for demonstration. The numerical example shows that the results of the quasi Monte Carlo method are substantially close to those of the full Monte Carlo method, but the computational cost of the quasi Monte Carlo method is only 0.7% of that of the full Monte Carlo method. The second index is called total-effect process sensitivity index, and it measures interactions between different processes. Therefore, this sensitivity index includes the first-order process sensitivity index, and can be used to identify influential processes. On the other hand, the total-effect process sensitivity index can also be used to screen non-influential processes. This is demonstrated by two numerical examples using the Sobol-G* functions and groundwater flow models that consider recharge process, geological process, and snowmelt process. The numerical examples shows that the total-effect process sensitivity index is more informative than the first-order process sensitivity. The derivation of the process sensitivity index and the numerical examples are discussed in Chapter 3. Chapter 4 presents two computationally efficient methods for screening non-influential processes to exclude them from further investigation. The two methods are the multi-model difference-based sensitivity (MMDS) analysis method, which can be implemented using the Latin Hypercube Sampling. The second one is the implementation of MMDS method using a binning method. The numerical example for the Sobol-G* function indicates the two methods are capable of identifying non-influential models, and the numerical examples for the groundwater flow and reactive transport show that the two methods are effective for groundwater problems. However, it should be noted that the two methods are numerical approximations, and they can only be used for screening non-influential processes, not for ranking importance of system processes. All the sensitivity analysis methods are implemented by developing python codes, and the codes are in a software called SAMMPY: a python package for process sensitivity analysis under multiple models. The SAMMPY design and structure are discussed in Chapter 5, and the package is released to the public for free download.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Physics-informed semantic inpainting: Application to geostatistical modeling

A fundamental problem in geostatistical modeling is to infer the heterogeneous geological field based on limited measurements and some prior spatial statistics. Semantic inpainting, a technique for image processing using deep generative models, has been recently applied for this purpose, demonstrating its effectiveness in dealing with complex spatial patterns. However, the original semantic inpainting framework incorporates only information from direct measurements, while in geostatistics indirect measurements are often plentiful. In this work, to overcome this limitation, we propose a physics-informed semantic inpainting framework, employing the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) and jointly incorporating the direct and indirect measurements by exploiting the underlying physical laws. Our simulation results for a high-dimensional problem with 512 dimensions show that in the new method, the physical conservation laws are satisfied and contribute in enhancing the inpainting performance compared to using only the direct measurements.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2025

Carbon Utilization and Storage Partnership of the Western United States

This technical report documents research conducted under DOE Award No. DE-FE0031837 focused on evaluating the feasibility of carbon capture, utilization, and storage (CCUS) systems in the central and western United States. The project integrated geologic characterization, reservoir simulation, infrastructure modeling, and economic analysis to assess CO₂ storage potential near industrial sources and develop strategies for transport and sequestration. The work included subsurface modeling, risk assessment, monitoring and verification (MRV) planning, and evaluation of regulatory pathways such as EPA Underground Injection Control (UIC) Class VI permitting and IRS 45Q tax credit eligibility. Results demonstrate the viability of multiple storage approaches, including saline formations, enhanced coalbed methane recovery, and basalt mineralization, supported by data-driven workflows and regional analyses. The project also produced permitting templates, technology transfer activities, and stakeholder engagement efforts to support deployment readiness. These findings contribute to the development of scalable, economically viable CCUS systems and provide a repeatable framework for future carbon management projects.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2019

Multiscale Modeling of CO 2 Migration and Trapping in Fractured Reservoirs with Validation by Model Comparison and Real-Site Applications (Final Technical Report)

This report documents the accomplishments achieved during the project titled “Multiscale Modeling of CO 2 Migration and Trapping in Fractured Reservoirs with Validation by Model Comparison and Real-Site Applications” funded by the US Department of Energy, Office of Fossil Energy. The objectives of the project were to develop modeling capabilities for predicting CO 2 and brine migration in fractured reservoirs during geologic carbon storage and to investigate the feasibility of carbon storage in fractured reservoirs using the newly developed modeling capabilities. To achieve these objectives new mass transfer functions were developed to adapt existing dual-continuum approaches – a commonly used approach in hydrocarbon reservoir modeling – to the CO 2 -brine system. In the dual-continuum approach the undisturbed rock matrix and the fractures are modeled as two separate continua, which are coupled through mass exchange of CO 2 and brine between the two continua. Mass transfer functions represent the mass exchange between fractures and the rock matrix, without requiring highly resolved numerical grids of individual fractures, thus allowing large modeling domains relevant to geologic carbon storage questions (tens of meters to hundreds of kilometers). Mass transfer functions for the exchange of both free-phase CO 2 and brine between fractures and rock matrix were developed for both the injection phase and the post-injection phase. During the injection phase the fractures are filled with CO 2 , while the rock matrix is initially filled with brine. Therefore, a mass transfer function was developed that is based on vertical displacement of brine by CO 2 in the rock matrix due to gravitational forces. Once CO 2 injection ceases and CO 2 migrates away from the direct vicinity of the injection site, the fractures will begin to re-fill with brine, while the rock matrix will have high CO 2 saturations. For these conditions a mass transfer functions was developed that is based on spontaneous imbibition, as the pore spaces in the rock matrix are much smaller than in the fractures. For formations with low permeability or high capillary entry pressure of the rock matrix, free-phase CO 2 may not be able to enter the rock matrix. However, free-phase CO 2 at the interface between fractures and rock matrix can dissolve into brine resident in the rock matrix. Therefore, additional mass transfer functions were developed based on aqueous-phase diffusion of CO 2 through the rock matrix. These mass transfer functions are based on existing solutions for diffusion and were expanded to be applicable to a variety of block shapes relevant to dual-continuum modeling. Implementations of the newly developed mass transfer functions showed that they give accurate results when compared to highly resolved models. In addition to developing new transfer functions, a new vertically-integrated dual-continuum modeling framework was developed. This development takes advantage of fast vertical segregation of CO 2 and brine in the fractures due to the density difference between CO 2 and brine and the high permeability of the fractures. Therefore, a vertically-integrated vertical equilibrium model for the fractures is coupled with a vertically-distributed model for the rock matrix. The newly developed approach significantly reduces the computational effort, but is only accurate for fracture permeabilities of 100 mD or higher. Finally, the newly developed models were applied to real and hypothetical geologic carbon storage sites to investigate the feasibility of using fractured reservoirs for carbon storage. The general results were, that storage of CO 2 – both as free-phase and dissolved – is feasible, but that storage capacities are likely lower than in unfractured systems. While the high permeability of the fractures reduces the injection pressure (or permits higher injection rates), fast migration of CO 2 may limit the overall storage volume, because CO 2 may escape laterally with not enough of the rock matrix being swept for effective storage.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Process Interactions Can Change Process Ranking in a Coupled Complex System Under Process Model and Parametric Uncertainty

For a complex hydrologic system with multiple processes and process interactions, global sensitivity analysis is often used to identify important or influential parameters for model development and improvement. The identification is complicated by process model uncertainty, when a system process can be represented by multiple process models. This study develops a new total-effect process sensitivity index to identify influential processes under model uncertainty. This is done by extending Sobol's total-effect parameter sensitivity index for one system model to total-effect process sensitivity index for multiple system models to account for uncertainty in process models and model parameters. The total-effect process sensitivity index includes not only the first-order process sensitivity index for measuring the importance of individual processes but also higher-order indices that account for process interactions. The total-effect process sensitivity index can identify an influential process that itself and its interactions with other processes influence a model output. Here, the total-effect process sensitivity index is applied to two numerical examples: (a) Sobol's G*-functions with analytical solutions of first-order and total-effect process sensitivity indices, and (b) groundwater flow models with interactions between recharge, geology, and snowmelt processes. The second evaluation shows that, due to second-order and higher-order process interactions, the first-order and total-effect process sensitivity indices give different process ranking. It is thus necessary to estimate both first-order and total-effect process sensitivity indices to appreciate the difference between the first-order impact of a process alone and the overall total-effect impact of the process itself and its interactions with other processes on a model output.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Robust Ceramic Coaxial Cable Down-Hole Sensors for Long-Term In Situ Monitoring of Geologic CO 2 Injection and Storage

Energy generation by use of fossil fuels produces large volumes of CO 2 and other greenhouse gases, whose accumulation in the atmosphere is widely seen as undesirable. CO 2 Capture followed by sequestration has been identified as the solution. Subsurface geologic formations offer a potential location for long-term storage of CO 2 because of their requisite size. Unfortunately, the inaccessibility and complexity of the subsurface, the wide range of scales of variability, and the coupled nonlinear processes, impose tremendous challenges to determine the transport and predict the fate of the stored CO 2 . Among the various monitoring approaches, in situ down-hole monitoring of the various state parameters provides critical and direct data points that can be used to validate the models, optimize the injection, detect leakage and track the CO 2 plume. However, down-hole sensors that can withstand the harsh conditions and operate over decades of the project lifecycle remain unavailable. Given that the widespread of carbon capture and storage will be the necessity and reality in the future, fundamental and applied research is required to address the significant challenges and technological gaps in lack of long-term reliable down-hole sensors This project focused on the development and demonstration of a novel, low-cost, distributed, robust ceramic coaxial cable sensor platform for in situ down-hole monitoring of geologic CO 2 injection and storage with high spatial and temporal resolutions. The coaxial cable Fabry-Perot interferometer (CCFPI) has been studied as a general sensor platform for in situ, long-term, measurement of temperature, pressure and strain, which are critical to CO 2 injection and storage. A novel signal processing scheme has been developed and demonstrated for dense multiplexing of the sensors for low-cost distributed sensing with high spatial resolution. The developed temperature, pressure and strain sensors have been extensively tested under laboratory conditions that are similar to the downhole CO 2 storage environment, showing excellent capability for in situ monitoring the various parameters that are important to model, optimize the injection, detect leakage and track the CO 2 plume. In addition, the interactions between the sensor datum and the geological models have been investigated in details for the purposes of model validation, guiding sensor installation/placement, enhancement of model prediction capability and optimization of the injection processes. This project has resulted in the successful development of new ceramic coaxial cable based sensor systems that can monitor directly the changes in pressure, temperature, and strain caused by increased reservoir pressure and reduced reservoir temperature due to the supercritical CO 2 injection. Integrated with geological models, the sensors and measurement data can improve the possibility to identify plume movement and leakage in the cap rock and wells with higher precision and more accuracy. The low cost, ease of deployment, small size and dense multiplexing features of the new sensing technology will allow a large number of sensors to be deployed to address the objective to demonstrate that 99% of the CO 2 remains in the injection zone.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

Numerical Study of Critical Role of Rock Heterogeneity in Hydraulic Fracture Propagation

Log and seismic data indicate that most shale formations have strong heterogeneity. Conventional analytical and semi-analytical fracture models are not enough to simulate the complex fracture propagation in these highly heterogeneous formation. Without considering the intrinsic heterogeneity, predicted morphology of hydraulic fracture may be biased and misleading in optimizing the completion strategy. In this paper, a fully coupling fluid flow and geomechanics hydraulic fracture simulator based on dual-lattice Discrete Element Method (DEM) is used to predict the hydraulic fracture propagation in heterogeneous reservoir. The heterogeneity of rock is simulated by assigning different material force constant and critical strain to different particles and is adjusted by conditioning to the measured data and observed geological features. Based on proposed model, the effects of heterogeneity at different scale on micromechanical behavior and induced macroscopic fractures are examined. From the numerical results, the microcrack will be more inclined to form at the grain weaker interface. The conventional simulator with homogeneous assumption is not applicable for highly heterogeneous shale formation.

Dual Lattice Discrete Element Method↗
DOE OSTI2017

Improved image of intrusive bodies at Newberry Volcano, Oregon, based on 3D gravity modelling

Beneath Newberry Volcano is one of the largest geothermal heat reservoirs in the western United States and it has been extensively studied for the last 40 years. Several magmatic intrusions have been recognized at depths between 2.5 and 8 km and some of them identified as suitable targets for enhanced geothermal energy and tested during two previous EGS campaigns. These subsurface structures have been intersected by three deep wells and imaged by various geophysical methods including seismic tomography and magnetotellurics. Although three high quality gravity surveys were completed between 2006 and 2010 as part of various projects, a complete synthesis and interpretation of the gravity data has not yet been performed. Regional gravity data also exist in the vicinity of the Newberry volcano and have been added to these surveys to constitute a dataset with a total of 1418 gravity measurements. When coupled with existing geologic and geophysical data and models, this new gravity dataset provides important constraints on the depth and contours of the magmatic bodies previously identified by other methods and thus greatly contributing to facilitate any future drilling and stimulation works. Using the initial structures discovered by seismic tomography, inversion of gravity data has been performed. Shape, density values and depths of various bodies were allowed to vary and three main bodies have been identified. Densities of the middle and lower intrusive bodies (~2.6-2.7 g/cm3) are consistent with rhyolite, basalt or granites. Modeled density of the near-surface caldera body match that of a low density tephra material and the density of the shallow ring structures contained in the upper kilometer correspond to that of welded tuff or low-density rhyolites. Modeled bodies are in reality a composite of thin layers; however, average densities of the modeled gravity bodies are in good agreement with the density log obtained in one well located on the western flank (well 55-29). Final gravity data residuals show that most of the observed gravity anomalies at the surface can be explained by the modeled gravity bodies and are consistent with other site characterization information.

Cascade Range↗
NASA NTRS1993

Yana ring structure, North-Eastern Siberia: A possible counterpart of coronae on Venus

An arch of Verkhoyansky Range in NE Siberia, Russia is considered as W and S parts of the rim of the large ring structure, referred hereafter as Yana Ring Structure (YRS). It has general appearance similar to coronae on Venus and could be considered as the terrestrial counter part of coronae. The structure is located between 63 and 70 deg N, 125 and 140 deg E. The outer diameter of YRS (between the rim feet) is 680-700 km. The rim crest diameter is 500-520 km. The inner diameters (between the inner feet of the rim) is 320-350 km. The rim of YRS consist of the following topographic features: W segment is Orulgan Range (N part of Verkhoyansky Range), SW and S segments consist of S part of Verkhoyansky Range, SE segment is Elginskoye Ploskogorye (Tableland), E segment is Chersky Range (its part W of Indigirka River), NE segment is Selennyakhsky Range, and NW segment is Kular Range. Inside this ring of mountains Yanskoye Ploskogorye (Tableland) is located. The circular outlines of YRS are marked with the large river valleys located outside: Lena River (lower of Aldan River mouth) is located W from YRS, Aldan River (lower of Amga River mouth) is from S, Indigirka River (between 64 and 67 deg N lat) is from E, and Selennyakh River (the part running N to S) is from NE. The ring patterns inside the mountaineous rim of YRS are marked with the tributaries of Yana River. The largest ring here, 300 km in diameter, consists of Bytangay (with Bellyakh) River at W, Nelgese and Derbeke Rivers at S/SE, and Tuostakh River at E. The typical altitudes of YRS mountain rim are 1000-2000 m. The maximal ones are: 2400 m in W part of the rim, 2300 m in S, 1600 m in SE, 2200-2500 m in E, and 1300-1500 m in N. The central part of YRS have typical altitudes of 400-600 m. There are lowlands with altitudes 50-200 m to the S, W, N, and NW outside YRS Oymyakonskoye Nagorye (Highland) is located SE of YRS at 500-1500 m altitudes. It should be recognized from this description YRS have a general appearance of circular highland with its central plateau located 1000-2000 m lower than surrounding mountain rim, but 300-400 m higher than plains of lowlands located outside the rim. Such topographic patterns are typical for coronae on Venus. The diameter of YRS is equal to the largest coronae on Venus. There are only 3 or 4 structures of such or larger size on the whole Venus. This calls to compare morphology and geologic evolution of YRS with morphology and models of coronae evolutions especially the largest ones, to search the similarities and/or differences in geologic histories of the structures on the Earth and Venus.

Burba, G. A.↗
DOE OSTI2016

Development of an Integrated Hydrological Model for Simulation of Surface Runoff and Stream Flow in Tims Branch Watershed, Savannah River Site, South Carolina - 16203

This research is part of continued efforts to develop an integrated transport model to predict the distribution of tin within the overland flow in Tims Branch Watershed (TBW) at Savannah River Site (SRS), South Carolina. Tin was introduced into TBW during the application of an innovative mercury remediation technology implemented by the U.S. Department of Energy's Office of Environmental Management, which involved the injection of stannous (tin) chloride into mercury contaminated groundwater. Understanding the fate and transport of tin and its compounds is of primary importance due to their potential impact on the environment. In this study, we developed an overland hydrology model (MIKE SHE) capable of simulating surface hydrology throughout the TBW. The modeling application used historical precipitation, groundwater levels, geological data, and river discharges that were retrieved from government databases and input to the model. The model was developed to simulate spatio-temporal distribution of flow discharges, flow duration, and water levels in the TBW. The preliminary simulation results indicated that the model was capable of predicting flow depth and velocity within the study area during extreme climate events. The developed hydrology model will later on be coupled with transport model to simulate tin distribution within Tims Branch stream during seasonal storm events. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2020

The formation of Enceladus' Tiger Stripe Fractures from eccentricity tides

Enceladus has a young, tectonically active south polar region, which is erupting material from a prominent set of fractures called Tiger Stripes. No comparable activity is observed at the north pole, which is heavily cratered with limited tectonism. Given the many lines of evidence supporting a global ocean under Enceladus' icy shell, the reason for the dichotomy in geologic activity is unclear. We model the formation of the Tiger Stripes as tidally-driven fractures and examine the magnitudes of tidal stresses with different ice shell structures in order to explore whether and how tidal stress might explain Enceladus' distribution of tectonic activity. We find that eccentricity-driven tidal stresses would produce fractures of nearly identical orientations to the observed Tiger Stripe Fractures and that a 10-km difference in ice shell thickness between the north and south poles can result in substantially different tidal stress magnitudes, providing a natural explanation for the hemispheric dichotomy in tectonic activity on Enceladus. Finally, we synthesize these results with Enceladus' global geologic record to offer insight into the evolution of this enigmatic moon.

Alyssa RoseRhoden↗