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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Real-Time Atomic-Scale Structural Analysis Resolves the Amorphous to Crystalline CaCO 3 Mechanism Controversy

Amorphous calcium carbonate (ACC) occurs as a precursor to geological and biogenic calcium carbonate (CaCO 3 ), yet its transformation pathways and reaction mechanisms remain inconsistent and controversial. In this study, we investigated the transformation of ACC to calcite under both solution and dry conditions, in the presence and absence of impurity ions, utilizing operando time-resolved synchrotron X-ray diffraction (TRXRD) and reactive transport modeling. Results demonstrate that TRXRD techniques allow us to differentiate dissolution-reprecipitation versus solid-state transformation mechanisms for amorphous to crystalline phase transitions. Specifically, we observe that in environments with abundant water, ACC transforms to calcite through a dissolution-reprecipitation mechanism. This features an activation energy of 63 ± 2 kJ/mol and unit cell volume contraction during calcite crystal growth. Conversely, under water-limited conditions, ACC to calcite transformation proceeds via a solid-state transformation mechanism, with an activation energy of 210 ± 2 kJ/mol, three times greater than the dissolution-reprecipitation route, and a unit cell expansion during crystalline calcite growth. Further, to illustrate the magnitude of these effects, the rates of calcite growth were similar during dissolution-reprecipitation at 3 °C [0.00207(35) s –1 ] and solid-state transformation at 280 °C [0.00134(11) s –1 ]. Moreover, the incorporation of an impurity, strontium, significantly retards the rate of calcite growth while expanding its unit cell but whose incorporation is history dependent. Reactive transport modeling of the dissolution–precipitation kinetics suggests that ACC must be dissolving as compact aggregates. These various transformation mechanisms drive diverse geological and biological carbonate formations, impacting their use as paleoenvironmental markers and functional materials synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Physical properties, internal structure, and the three‐dimensional petrography of CI chondrites

physical properties and the nature of their breccation, we investigated nine samples of the Ivuna and Orgueil CI chondrites ranging in size from 1 mm to 4 cm in approximate diameter. The combined mass of unique material investigated in this work is 113 g. For our investigations, we use ideal gas pycnometry, 3-D laser scanning, x-ray computed microtomography (μCT), and accompanying digital data extraction techniques. We found that the bulk density of the samples ranged from 1.61 to 2.10 g cm −3 . Larger samples tend to have a lower bulk density. Grain density (ranging from 2.44 to 2.55 g cm −3 ) is significantly less variable than the bulk density in our samples and the quantity of porosity (ranging from 14.6% to 33.8%) is the dominant factor in determining the bulk density of CI chondrite material. Our μCT results show that the visible porosity across all sizes of our CI chondrite samples is in the form of cracks, but these cracks can account for less than two-thirds of the porosity in the CI chondrites. Other porosity is not visible, even at μCT resolutions of 2.7 μm voxel edge −1 and we conclude that it is sub-micron in nature. It is not clear if the cracks seen in our samples are indigenous to the chondrites or are a result of terrestrial processes. We also find that the CI chondrites are excellent examples of the fractal-like nature of brecciation, where clasts can be observed at all scales we imaged. The breccias are composed of sub-equant-shaped and sub-rounded-textured clasts like melt-free impact breccias on other solar system bodies. From our μCT volume and digital data extraction, we determine that the Ivuna CI chondrite breccia is organized: the mostly sub-equant clasts within our ~2 cm chunk of Ivuna have a mean diameter of 1.33 mm and their aligned longest axes define a lineation structure. We speculate that the lineation was imparted after fragmentation of the clasts by slight shear on the parent asteroid which could be the result of seismic-related granular flow or mild non-axial impact-related compaction. These data will help to place returned asteroidal material from asteroids 162173 Ryugu and 101955 Bennu and the CI chondrites into a mutual geological context.

CI chondrite↗
DOE OSTI2023

Otolith 87 Sr / 86 Sr identifies natal origin, movement and life history of Burbot Lota lota in the Kootenai River following 45 years of impoundment

Abstract Hydropower has long been an effective form of renewable energy, but the development of the resource has negatively impacted fishes throughout the world. Formulating recovery plans to mitigate these effects requires a firm understanding of species‐specific provenance, life history and life stage habitat requirements. However, the importance of this information is often only recognised after a substantial population decline, when obtaining it becomes demographically challenging. We provide a case study for this scenario and present a post hoc approach to gain insight into these critical data gaps for Burbot Lota lota in the upper Kootenai River in Montana and British Columbia. The population once supported a robust tribal and recreational harvest but declined following impoundment and these fisheries have remained closed or curtailed for nearly 20 years. The reasons for the decline are unknown and actions to assist recovery have been constrained by limited information regarding natal origin, life history and habitat use. We addressed this issue using strontium isotope ratios ( 87 Sr/ 86 Sr) in otoliths collected over four decades in Lake Koocanusa, the reservoir on the Kootenai River above Libby Dam. Due to the geologic heterogeneity of the basin and resulting variation in water 87 Sr/ 86 Sr, the assignment probability for Burbot to their region of natal origin approached unity. Otolith 87 Sr/ 86 Sr also indicated the population was comprised of mainstem‐ and tributary‐origin forms and their relative abundance changed over time. Mainstem Burbot was most abundant during the 1970s and 2000s, whereas tributary forms dominated between these periods. We suggest ecosystem changes following impoundment contributed to this shift in life history forms and the overall decline of the population. Our findings underscore the need for additional investigations of these impacts to guide restoration efforts.

Dunnigan, James L.↗
DOE OSTI2021

Estimating Watershed Subsurface Permeability From Stream Discharge Data Using Deep Neural Networks

Subsurface permeability is a key parameter in watershed models that controls the contribution from the subsurface flow to stream flows. Since the permeability is difficult and expensive to measure directly at the spatial extent and resolution required by fully distributed watershed models, estimation through inverse modeling has had a long history in subsurface hydrology. The wide availability of stream surface flow data, compared to groundwater monitoring data, provides a new data source to infer soil and geologic properties using integrated surface and subsurface hydrologic models. As most of the existing methods have shown difficulty in dealing with highly nonlinear inverse problems, we explore the use of deep neural networks for inversion owing to their successes in mapping complex, highly nonlinear relationships. We train various deep neural network (DNN) models with different architectures to predict subsurface permeability from stream discharge hydrograph at the watershed outlet. The training data are obtained from ensemble simulations of hydrographs corresponding to an permeability ensemble using a fully-distributed, integrated surface-subsurface hydrologic model. The trained model is then applied to estimate the permeability of the real watershed using its observed hydrograph at the outlet. Our study demonstrates that the permeabilities of the soil and geologic facies that make significant contributions to the outlet discharge can be more accurately estimated from the discharge data. Their estimations are also more robust with observation errors. Compared to the traditional ensemble smoother method, DNNs show stronger performance in capturing the nonlinear relationship between permeability and stream hydrograph to accurately estimate permeability. Our study sheds new light on the value of the emerging deep learning methods in assisting integrated watershed modeling by improving parameter estimation, which will eventually reduce the uncertainty in predictive watershed models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effects of Model Uncertainties in Underground Chemical Explosions on Far-field Results

We used the CTH shock physics code to simulate the explosion of an 18-t chemical explosive at a depth of 250 m. We used the CTH in the two-dimensional axisymmetric (cylindrical) geometry (2DC) and most simulations included fully tamped explosions in wet tuff. Our study focused on parametric studies of three of the traditional strength models available in CTH, namely, geologic-yield, elastic perfectly-plastic von Mises, and Johnson-Cook strength (flow stress) models. We processed CTH results through a code that generates Reduced Displacement Potential (RDP) histories for each simulation. Since RDP is the solution of the linear wave equation in spherical coordinates, it is mainly valid at far-enough distance from the explosion the elastic radius. Among various parameters examined, we found the yield strength to have the greatest effect on the resulting RDP, where the peak RDP reduces almost linearly in log-log space as the yield strength increases. Moreover, an underground chemical explosion results in a cavity whose final diameter is inversely proportional to the material yield strength, i.e., as the material's yield strength increases the resulting final cavity radius decreases. Additionally, we found the choice of explosive material (COMP-C4 versus COMP-B) has minor effects on the peak RDP, where denser COMP-C4 shows higher peak RDP than the less dense COMP-B by a factor of ~1.1. In addition to wet tuff, we studied explosions in dry tuff, salt, and basalt, for a single strength model and yield strength value. We found wet tuff has the highest peak RDP value, followed by dry tuff, salt, and basalt. 2DC simulations of explosions in 11 m radius spherical, hemispherical, and cylindrical cavities showed the RDP signals have much lower magnitude than tamped explosions, where the cavity explosions mimicked nearly decoupled explosions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Geological study of an outburst flood event in the upper Yangtze River and risk of similar extreme events

Here, outburst flood sediments are studied on the upper course of the Yangtze River (known as the Jinsha River) where is a key region for the development of hydroelectric power. As the history and magnitude of outburst flooding in this stretch of the Jinsha River during historic times has remained largely undocumented, we have endeavored as part of this study to conduct field investigations into, and provide numerical dating (using OSL and 14 C dating techniques) of outburst flood evidence found in the First Bend area of the Yangtze River. Carbonized nutshells and charcoal from the ancient settlement yielded 14 C ages that precisely pinpointed an outburst flood event ~1200–1300 cal yr BP, during China's Tang Dynasty (618–907 CE). However, OSL ages using the minimum age model for all outburst flood samples ranged from 9.1 to 1.8 ka, which was ~0.5–7.8 ka older than the 14 C-dated outburst flood. This discrepancy suggests a potential overestimation of quartz age when dating outburst flood sediments from the Holocene period. Furthermore, using 2D hydraulic modeling, we estimated the magnitude of the aforementioned outburst flood, revealing a reconstructed peak flow discharge of 51,000–55,300 m 3 /s. This discharge was three times greater than the 10,000-year flood for the hydroelectric power station nearest to the study area. Our study underscores the significant role of combining archaeological and geological evidence in enhancing paleoflood hydrology research. Through a multidisciplinary approach, our findings emphasize the importance of paleoflood hydrology studies in comprehending both the latent and catastrophic flood risks in alpine mountain areas amid the context of global warming.

14C dating↗
DOE OSTI2021

Using femtosecond pump-probe spectroscopy to shed new light on complex materials

We know a lot about events that have occurred during the earth’s history, on timescales of millions of years. We are much less familiar with events that occur on “ultra”-short timescales of less than a billionth of a second. Unlike in geology, we can actually do experiments at ultrashort timescales, so we should be able to understand the “ultrafast” world much better! Ultrafast optical spectroscopy is the only technique capable of measuring processes at the fundamental time scales of electron, lattice and nuclear motion.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A deep learning-based direct forecasting of CO 2 plume migration

Accurate and timely forecasts of CO 2 plume evolution in geological reservoirs are crucial for CO 2 migration detection, leakage risk assessment, and operation decision support. Conventional forecasting usually adopts a two-step strategy, first calibrating reservoir model parameters against observations using iterative inverse modeling (or history matching) and then applying the calibrated model for predictions. This method impedes real-time forecasts due to the heavy computational demand in inverse modeling and may suffer from poor prediction accuracy because of the limited observation data. In this work, we propose a deep learning-based latent space mapping framework to forecast CO 2 plume migration directly by avoiding the inverse modeling. We first use the convolutional autoencoder to map the high-dimensional complex plume extents onto low-dimensional latent space. Next, we use neural networks to learn the relationship between the observation variables and the prediction latent variables. And then for given observation data, we infer the prediction values directly. This one-step direct forecasting is computationally efficient which requires a few number of parallelizable reservoir simulations and it can provide accurate predictions with limited observations by learning the observation-prediction relationship in the reduced dimension. Therefore, our proposed method enables an in-time forecast of dynamic CO 2 plume distributions. In this work, we demonstrate the effectiveness and accuracy of our method in predicting the CO 2 plume migration using four metrics such as plume area, centroid movement distance, and plume spreading in the primary and secondary directions. And the spatio-temporal evolution patterns of plume migration under diverse geological complexities are also accurately quantified.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Alteration history of aluminum-rich rocks at Jezero crater, Mars

Aluminum-rich clay minerals are detected across the ancient surface of Mars and record intervals of intense alteration by liquid water. On Earth, these clay minerals can form from hydrothermal alteration or rainfall-driven chemical weathering over thousands to millions of years, but how they formed on Mars remains a mystery. The Perseverance rover discovered light-toned, cobble-sized, aluminum-rich (30-45 wt% Al 2 O 3 ) “float” rocks (rock fragments), with some exhibiting spectral signatures of kaolinite, an aluminum-rich clay mineral. These rocks now enable an investigation into the ancient kaolinite-bearing terrains of Mars. To interpret their formation, we use data from the SuperCam and Mastcam-Z instruments onboard the rover to compare the chemistry and reflectance spectra of the float rocks with deeply weathered paleosols and hydrothermal kaolin deposits from Earth’s geological record. Aluminum and titanium enrichments coupled with depletion of iron and magnesium are unlike hydrothermal deposits and instead comparable to bleached horizons of paleosols that formed under high rainfall during past greenhouse climates on Earth. These rocks therefore likely represent some of the wettest intervals of Mars’ history.

58 GEOSCIENCES↗
DOE OSTI2022

Improving deep learning performance for predicting large-scale geological ${{CO}_{2}}$ sequestration modeling through feature coarsening

Physics-based reservoir simulation for fluid flow in porous media is a numerical simulation method to predict the temporal-spatial patterns of state variables (e.g. pressure p) in porous media, and usually requires prohibitively high computational expense due to its non-linearity and the large number of degrees of freedom (DoF). This work describes a deep learning (DL) workflow to predict the pressure evolution as fluid flows in large-scale 3-dimensional(3D) heterogeneous porous media. In particular, we develop an efficient feature coarsening technique to extract the most representative information and perform the training and prediction of DL at the coarse scale, and further recover the resolution at the fine scale by spatial interpolation. We validate the DL approach to predict pressure field against physics-based simulation data for a field-scale 3D geologic CO 2 sequestration reservoir model. We evaluate the impact of feature coarsening on DL performance, and observe that the feature coarsening not only decreases the training time by >74% and reduces the memory consumption by >75%, but also maintains temporal error 0.63% on average. Besides, the DL workflow provides predictive efficiency with 1406 times speedup compared to physics-based numerical simulation. The key findings from this research significantly improve the training and prediction efficiency of deep learning model to deal with large-scale heterogeneous reservoir models, and thus it can also be further applied to accelerate workflows of history matching and reservoir optimization for close-loop reservoir management.

58 GEOSCIENCES↗
DOE OSTI2021

River sinuosity describes a continuum between randomness and ordered growth

River channels are among the most common landscape features on Earth. An essential characteristic of channels is sinuosity: their tendency to take a circuitous path, which is quantified as along-stream length divided by straight-line length. River sinuosity is interpreted as a characteristic that either forms randomly at channel inception or develops over time as meander bends migrate. Studies tend to assume the latter and thus have used river sinuosity as a proxy for both modern and ancient environmental factors including climate, tectonics, vegetation, and geologic structure. But no quantitative criterion for planform expression has distinguished between random, initial sinuosity and that developed by ordered growth through channel migration. This ambiguity calls into question the utility of river sinuosity for understanding Earth’s history. We propose a quantitative framework to reconcile these competing explanations for river sinuosity. Using a coupled analysis of modeled and natural channels, we show that while a majority of observed sinuosity is consistent with randomness and limited channel migration, rivers with sinuosity ≥1.5 likely formed their geometry through sustained, ordered growth due to channel migration. This criterion frames a null hypothesis for river sinuosity that can be applied to evaluate the significance of environmental interpretations in landscapes shaped by rivers. The quantitative link between sinuosity and channel migration further informs strategies for preservation and restoration of riparian habitat and guides predictions of fluvial deposits in the rock record and in remotely sensed environments from the seafloor to planetary surfaces.

58 GEOSCIENCES↗
DOE OSTI2024

Stochastic Modeling Workflow to Generate Representative Geologic Variability in Training Dataset for SMART Initiative

The poster discusses the modeling workflow to generate ensemble of geologic realizations of the Illinois Basin Decatur Project (IBDP) site, based on available site characterization data and inherent uncertainty of those data, for use by project collaborators in DOE SMART Initiative (Phase 2) to build their forward modeling, history matching, and optimization workflows. This poster is summarized from the technical report for the SMART project submitted to U.S. DOE earlier this year.

Ganesh, Priya Ravi↗
DOE OSTI2020

A History of Molecular Level Analysis of Natural Organic Matter by FTICR Mass Spectrometry and The Paradigm Shift in Organic Geochemistry

Natural organic matter (NOM) is a complex mixture of biogenic molecules resulting from the deposition and transformation of plant and animal matter. It has long been recognized that NOM plays an important role in many geological, geochemical, and environmental processes. Of particular concern is the fate of NOM in response to a warming climate in environments that have historically sequestered carbon (e.g., peatlands and swamps) but may transition to net carbon emitters. In this review, we will highlight developments in the application of high-field Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) in identifying the individual components of complex NOM mixtures, focusing primarily on the fraction that is dissolved in natural waters (dissolved organic matter or DOM). We will first provide some historical perspective on developments in FTICR technology that made molecular-level characterizations of DOM possible. In conclusion, a variety of applications of the technique will then be described, followed by our view of the future of high-field FTICR MS in carbon cycling research, including a particularly exciting metabolomic approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Real Time 3D Observations of Portland Cement Carbonation at CO2 Storage Conditions

Depleted oil reservoirs are considered a viable solution to the global challenge of CO 2 storage. A key concern is whether the wells can be suitably sealed with cement to hinder the escape of CO 2 . Under reservoir conditions, CO 2 is in its supercritical state, and the high pressures and temperatures involved make real-time microscopic observations of cement degradation experimentally challenging. Here, we present an in situ 3D dynamic X-ray micro computed tomography (μ-CT) study of well cement carbonation at realistic reservoir stress, pore-pressure, and temperature conditions. The high-resolution time-lapse 3D images allow monitoring the progress of reaction fronts in Portland cement, including density changes, sample deformation, and mineral precipitation and dissolution. By switching between flow and nonflow conditions of CO 2 -saturated water through cement, we were able to delineate regimes dominated by calcium carbonate precipitation and dissolution. For the first time, we demonstrate experimentally the impact of the flow history on CO 2 leakage risk for cement plugging. In-situ μ-CT experiments combined with geochemical modeling provide unique insight into the interactions between CO 2 and cement, potentially helping in assessing the risks of CO 2 storage in geological reservoirs.

58 GEOSCIENCES↗
DOE OSTI2025

Building confidence in models for complex barrier systems for radionuclides

The modeling and simulation of the Cement-clay Interaction-Diffusion field (CI-D) experiment at the Mont Terri site in Switzerland presented here demonstrates that it is possible to capture the multiscale physical and chemical features of natural and engineered barrier systems for radionuclides. The simulations are successfully carried out with the newly developed CrunchODiTi high-performance computing software that accounts for multiple continua, including a continuum representing the electrical double layer (EDL) developed along negatively charged clay particles in clay rock. The simulation also accounts for both the complex three-dimensional (3D) geometry, expected as the norm in a geological waste repository, and the anisotropy of the geological formation. In addition, the high resolution of the model makes it possible to include "skin effects" developed at the interface between highly reactive materials, in this case between the high pH cement and the circumneutral but electrostatic Opalinus Clay. The successful history matching with the field experiment demonstrates that the distinct geochemical and physical properties of the cement and the Opalinus Clay in the CI-D experiment can be accounted for. Such analyses are essential for developing a defensible safety case for the underground storage of radioactive waste.

Sarsenbayev, Dauren↗