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At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
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 OSTI2020

Multiscale formulation of frictional contact mechanics at the pore scale

Direct numerical simulation (DNS) yields the highest fidelity predictions of mechanical deformation at the pore scale, but is prohibitively expensive for analyzing large or many samples. Discrete element methods (DEM) are an efficient alternative, but are limited to granular media and incapable of estimating or controlling prediction errors. We present a pore-level multiscale method (PLMM) that approximates DNS efficiently and with controllable accuracy. We focus on the linear elastic response of a consolidated geologic porous medium with arbitrary microstructure, heterogeneous mineralogy, containing cracks or defects. PLMM decomposes the solid phase into non-overlapping subdomains, on which local basis functions are constructed. The bases are then coupled with a global interface problem that accounts for slip or stick contact conditions between the subdomains. PLMM produces an initial, but accurate, approximation to DNS that can be iteratively improved. It is amenable to parallelism and allows for different mesh, models, and physics in each subdomain. An algebraic interpretation of PLMM as a preconditioner is also presented to allow non-intrusive implementation into existing solvers. Lastly, this work extends previous developments of PLMM in fluid dynamics to solid mechanics and enables future extensions towards modeling coupled flow and mechanics problems.

42 ENGINEERING↗
DOE OSTI2025

Sustainable recovery of Rare Earth Elements (REEs) from coal and coal ash through urban mining: A Nature Based Solution (NBS) for circular economy

The demand for rare earth elements (REEs) has surged in recent years, driven by their crucial role in various industrial applications and their uneven geological distribution. As a result, urban mining from secondary resources, particularly coal and coal ash, has gained traction as a sustainable solution within a circular economy framework. This study highlights the significant presence of REEs in coal and coal ash, revealing that certain samples contain REE concentrations that rival traditional ores. Notably, coal ash has the potential to yield approximately 312,000 tons of REEs annually, far exceeding global demand. The research delves into advanced techniques for analyzing REEs, including elemental, isotopic, and mineralogical studies. Additionally, it explores innovative extraction methods such as the use of green solvents, nature-based solutions, and bioleaching and biosorption. By leveraging coal and its byproducts as secondary resources, this study underscores the opportunity to reduce dependence on conventional mining, enhancing the sustainability of REE recovery. Here, a comprehensive literature review was conducted to highlight technological advancements and emerging opportunities that can address current challenges in this field.

Circular economy↗
DOE OSTI2025

Manganese in drinking-water reservoirs: a multi-disciplinary review of current issues, biogeochemical controls, and oxygenation-based management

Decreased water quality and increased treatment costs due to excess manganese (Mn) in drinking-water supplies are critical issues globally. To combat on-going and emerging taste and odour issues with Mn and other contaminants (e.g., algal toxins), many utilities are using engineered oxygenation or aeration (EOA) systems to improve water quality in lakes and reservoirs. Resultant shifts in key biogeochemical and physical processes are still poorly understood, often leading to inefficiently managed systems. Paired with knowledge gaps regarding environmental drivers of Mn and the complexity of Mn redox kinetics, Mn problems persist. This review presents the state of current research in areas critical to optimisation of EOA mitigation of Mn, with focus on i) Mn biogeochemical cycling within drinking-water reservoirs; ii) influences of local catchment geology, hydrology, and land use on Mn dynamics; and iii) Mn management using different EOA approaches. The importance of considering the combined implications of these factors for successful Mn management in reservoirs is highlighted by an evaluation of relevant field-based studies; a wide range in EOA performance is observed, from a 97 % decrease in soluble Mn up to a ∼400 % increase in total Mn. Despite the breadth of studies that consider Mn in water-supply systems, there are still several areas of research which warrant further investigation, including: the influence of natural sources and anthropogenic activities on Mn within a given catchment, Mn speciation and transport in stratified and destratified lakes and reservoirs, and optimal site-specific EOA strategies for Mn mitigation.

Aeration↗
DOE OSTI2022

Noble gas adsorption to tuff

For this report a method was developed to measure trace noble gas element adsorption to the surfaces of geologic materials in the presence of a background gas that could potentially compete for surface adsorption sites. Adsorption of four noble gas elements (Ne, Ar, Kr, and Xe) at a concentration of 100 ppm in helium and nitrogen were measured on a sample of crushed tuff at 0, 15, 30, and 45°C. In addition, Ne, Ar, Kr, and Xe at 250 ppm and 500 ppm in nitrogen at 15°C were measured. Noble gas adsorption was found to increase with increasing atomic mass and decreasing temperature. It was also observed that the relative increase in noble gas element adsorption with decreasing temperature tends to increase with increasing atomic mass. Noble gas adsorption from nitrogen was approximately an order of magnitude greater than for the noble gases in helium. As the noble gas concentrations in nitrogen increased, adsorption increased in a slightly non-linear fashion which could be modeled using a Freundlich isotherm. For noble gas concentrations that were ≤100 ppm Henry's Law constant were calculated.

58 GEOSCIENCES↗
DOE OSTI2022

Patterns of indoor radon concentrations, radon-hazard potential, and radon testing on a small geographic scale in Utah

Currently, there are no publicly-available estimates of indoor radon concentration at scales smaller than the county. Radon-hazard potential soil maps that reflect underlying geologic factors can be created at small geographic scale and linked to residential and census data. We determined the association between residential radon tests and high radon-hazard potential soil at the residential and block group levels using a large Utah-based dataset. We also identified characteristics of block groups with limited tests in the dataset.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

Nuclear waste Educator's workshop: What and how do we teach about nuclear waste?

A workshop was held at the Massachusetts Institute of Technology (MIT) on July 25th and 26th, 2022. The objective was to develop a blueprint for educating next-generation engineers and scientists about nuclear waste management and disposal, which requires knowledge from diverse disciplines, including nuclear, chemical, civil, environmental, and geological science and engineering. The 49 participants included university professors, researchers, industry experts, and government officials from different areas. First, we have developed a list of key fundamental knowledge on waste management and disposal across the nuclear fuel cycle. In addition, we discussed strategies on how to teach students with diverse backgrounds through innovative teaching strategies as well as how to attract students into this area. Through the workshop, we identified the critical needs to (1) develop community resources for nuclear waste education; (2) synthesize historical perspectives, including past contamination and the management of general hazardous waste; (3) emphasize a complete life-cycle perspective, including proper waste management as the key component for energy sustainability; (4) teach students how to communicate about the key facts and risks to technical and non-technical audiences; and (5) accelerate the use of the state-of-art-technologies to attract and retain a young workforce. Furthermore, we aim to build a diverse, inclusive community that supports students in developing their own narratives about nuclear waste, particularly in recognizing that antagonistic views have been important to improving safety and protecting public health and the environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Geographic source attribution of honey by strontium isotope analyses: Latvia and India measurements compared to model predictions in a feasibility study

Strontium isotope ratios ( 87 Sr/ 86 Sr) can be used to determine the geographic origin of agricultural products. Here, in this study, we measured the 87 Sr/ 86 Sr of honey samples from Richland, WA, USA, Latvia, and India, and compared the results to published 87 Sr/ 86 Sr from surrounding areas and values predicted based upon a random forest isoscape model (Bataille et al., 2020). While the 87 Sr/ 86 Sr of the honey samples compared well with previously published data, the model did not accurately predict the 87 Sr/ 86 Sr of the honey samples, demonstrating that further refinement of the model would be beneficial. Because Sr cycling in terrestrial ecosystems is complex, the 87 Sr/ 86 Sr of honey is likely to reflect several sources (e.g., nectar, surface water, dust) and may change over time. In order to accurately predict the 87 Sr/ 86 Sr of honey, models must consider local geology, ecology, and bee behavior. Additional research examining how Sr is incorporated into honey is needed to inform models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Experimental investigation into coal wettability changes caused by reactions with scCO 2 -H 2 O

Geological CO 2 sequestration (GCS) can help mitigate global warming and enhance methane recovery from coal beds. However, few studies have linked the effects of CO 2 to surface chemistry changes controlling wetting behavior in deep coal beds. Contact angles (CAs) of CO 2 /N 2 -high volatile bituminous coal-water systems were measured under different temperatures and pressures. The surface chemistry and physical structure of coals were characterized to investigate changes in physicochemical properties and their relations with wettability after reactions. For N 2 treatment, the time-dependence of static and dynamic CAs were insignificant, ranging within 4°. For gaseous CO 2 treatment, the static CAs and the average advancing angles increased slightly. With supercritical (sc) CO 2 , both the static and dynamic CAs increased significantly, and θ adv changed to intermediate-wet (92°). Reactions with minerals exposed to scCO 2 resulted in greater surface roughness and heterogeneity, greater contact angle hysteresis and more surface sites occupied by scCO 2 rather than H 2 O. Increases in hydrophobic functional groups and decreases in hydrophilicity were shown by FTIR spectra, reflecting the shedding of polar oxygen-containing functional groups, reduction of hydrogen bonds, and increasing percentage of hydrocarbons. XRD patterns obtained following scCO 2 -treatment showed that crystallite growth and molecular polymerization were higher toward graphite-like. The calculated structural parameters of functional groups and crystallites both showed elevated coal rank. Changes in crystallite structure, notably higher carbon content and decreased negative surface charge, are unfavorable for water-wetting. Finally, this study contributes to understanding surface chemistry changes responsible for decreased wettability during CO 2 -enhanced coal bed methane recovery and GCS in coal reservoirs.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Comparison of four learning-based methods for predicting groundwater redox status

Knowing the location where groundwater denitrification occurs, or by proxy the groundwater redox status (oxic, mixed, and anoxic), is valuable information for assessing and managing potential agricultural land-use impacts on freshwater quality. We compare the efficacy of supervised (Linear Discriminant Analysis LDA; Boosted Regression Trees, BRT; and Random Forest, RF) and unsupervised (Modified Self-Organizing Map, MSOM) learning-based methods to predict groundwater redox status in the agriculturally dominated Tasman, Waikato, and Wellington regions of New Zealand. Thresholds applied to regional groundwater-quality samples provide redox status variables and learn heuristics constrained by these variables and applied to spatial factors (climate, elevation, geologic, hydrology soils, and well depth) identify optimal sets of regional predictor variables. A split-sample approach is used to train and test the learning methods ability to predict redox status using the optimal predictor variables. Overall, the supervised methods demonstrate a prediction bias toward oxic conditions and inability to perform statistically well when using independent regional data; for example, consider kappa statistics for BRT (Tasman: 0.42, Waikato: 0.38, Wellington: 0.17), RF (Tasman: 0.42, Waikato: 0.47, Wellington: 0.17 and LDA (Tasman: 0.46, Waikato: 0.32, Wellington: 0.17). By contrast, the unsupervised method performs statistically well when predicting oxic, mixed, and anoxic conditions and corresponding depths when using independent regional data; for example, consider MSOM kappa statistics for Tasman: 0.78, Waikato: 0.80, Wellington: 0.76. The unsupervised learning method provides the added benefits of being (1) able to combine predictions into 3D regional anoxic probability plots for interpreting the spatial influence of paleosols and groundwater flowpaths on redox status, and (2) readily extended to map 3D redox status across New Zealand and other countries despite data bias and sparsity.

machine learning algorithms, Random Forest, booste↗
DOE OSTI2020

Characterization of flow and transport in a fracture network at the EGS Collab field experiment through stochastic modeling of tracer recovery

Energy extraction from subsurface reservoirs is important for addressing the increasing energy demand and environmental concerns such as global warming. However, the characterization of subsurface reservoirs, particularly reservoirs dominated by fracture networks remains a challenge due to the lack of means to directly observe subsurface processes. This study explores the feasibility and efficacy of characterizing fracture flow and transport processes in an enhanced geothermal system (EGS) testbed through stochastic tracer modeling. There are two enabling factors that allow application of stochastic modeling to characterize a subsurface reservoir. First, an abundance of geological and geophysical measurements enables the development of a high-fidelity and well-constrained fracture network model. Second, high-performance computing (HPC) allows running massive realizations efficiently. Six conservative tracer tests were stochastically modeled and produced satisfactory realizations that successfully reproduce field tracer recovery data from each tracer test. The evolution of flow and transport processes in the fracture network was then analyzed from these satisfactory realizations. This work demonstrates that stochastic tracer modeling on a high-fidelity fracture network model is feasible and can provide important insights regarding flow and transport characteristics in subsurface fractured reservoirs.

58 GEOSCIENCES↗
DOE OSTI2022

Large-scale paleo water-table rise in a deep desert aquifer recorded by dissolved noble gases

Illuminating past hydrological and climatological conditions in arid regions may provide insights into future trends in groundwater availability. The main objective of this study is to explore paleorecharge processes in the deep regional Nubian Sandstone Aquifer (NSA), which stretches below the hyperarid deserts of the Sinai Peninsula (Egypt) and the Negev (Israel), using dissolved noble gas data. Extremely high amounts of dissolved excess air (Ne concentrations up to 4 × solubility equilibrium) were observed in the ancient ( 81 Kr-depleted) groundwater that was recharged during past pluvial epochs in the basin. Here, the observed unique excess air signal and the clear spatiotemporal structure of the noble gas compositions in the aquifer are hypothesized to reflect two major characteristics of the groundwater system: (a) large-scale, long-term rises in the water table that facilitate the entrapment and dissolution of air bubbles under increased hydrostatic pressure, and (b) the geological settings in the southern recharge area in Sinai, including an almost horizontal position of the layers and intercalation of low-permeability rock formations within the aquifer, which inefficiently reject air bubbles from groundwater, thereby allowing for substantial entrapment of bubbles that dissolve as the water table rises. Enhanced dissolution of entrapped air was also observed in other paleo-groundwater-containing regional sandstone aquifers across North Africa, which, together with the recent findings from the NSA, suggest that largescale water table fluctuations have likely extensively occurred during past pluvial periods over these (and possibly other) arid regions. A preliminary assessment of noble gas recharge temperatures (NGTs) indicates an apparent decoupling of surface and water table temperatures in the case of deep aquifers with a thick (hundreds of m) unsaturated zone. This observed decoupling calls for a re-evaluation of previously obtained NGT records and a need for future work to consider the modification of NGTs due to soil air fractionation and geothermal heating of the underlying deep unsaturated zones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High resolution identification and quantification of diffuse deep groundwater discharge in mountain rivers using continuous boat-mounted helium measurements

Discharge of deeply sourced groundwater to streams is difficult to locate and quantify, particularly where both discrete and diffuse discharge points exist, but diffuse discharge is one of the primary controls on solute budgets in mountainous watersheds. The noble gas helium is a unique identifier of deep groundwater discharge because groundwater with long residence times is commonly enriched in helium. In this study, a portable mass spectrometer was used to measure longitudinal variation in dissolved helium concentrations in two mountainous rivers at high spatial resolution not feasible with traditional sampling techniques. Helium profiles were then simulated using a mass-balance model to quantify longitudinal variation in groundwater discharge to the receiving rivers. Results indicate helium concentrations were enriched by multiple orders of magnitude above atmospheric equilibrium in both rivers and that this persisted for up to 18 km below observed pulse inputs in the Colorado River. Helium mass-balance models match observed longitudinal patterns with the exception of sharp initial increases in helium observed in the rivers. Increased longitudinal groundwater discharge rates correspond to mapped geologic structures in both watersheds that likely transport deep geothermal water. Models show variable sensitivity to spatial assignment of input variables representing the groundwater source, illustrating the importance of collecting data from discrete groundwater discharges where possible. The methodology shows promise for field experiments designed to assess air–water exchange rates and to quantify total groundwater discharge from a combination of discrete and diffuse sources.

Deep groundwater↗
DOE OSTI2024

Identifying recharge sources and their impacts on a North Central New Mexico shallow aquifer using unsupervised machine learning

In this article, shallow aquifers are important but highly variable resources in arid to semi-arid regions. Limited shallow aquifer volume results in high sensitivity to recharge fluctuations, which can impact the local fauna and flora, and transport of contaminants in the aquifer or vadose zone. Aquifer response to external forcing (e.g., precipitation) is usually solved by estimating aquifer parameters and running physics-based models to match known fluctuations of hydraulic head. However, this technique is time and computationally expensive. Furthermore, high aquifer complexity decreases precision in physics-based models. Alternatively supervised machine learning is used to predict aquifer dynamics. However, these techniques rely on input data and struggle to interpret aquifer response for missing sources (i.e., snowpack data). To counter these problems, we propose an unsupervised machine learning technique (NMFk) to estimate the impact of different sources on aquifer recharge. NMFk is used to understand the influence of external forcing on shallow aquifer recharge in the Pajarito Plateau (Los Alamos, NM, USA). The results show how NMFk can be used to reduce the data dimension in a complex field dataset to three recharge signals that cause fluctuations within the field data. Here, the source signals are interpreted as rainfall, snowmelt, and a delayed aquifer response to the previous two signals. These results evidence how heterogeneous aquifers delimited by canyons incised into the Pajarito Plateau respond in similar ways to the source signals identified by NMFk. Furthermore, results show the importance of the local geology where faults act as sinks, and anthropogenic disturbances can facilitate infiltration amplifying the interpreted signal.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Enhancing 2D hydrodynamic flood models through machine learning and urban drainage integration

Two-dimensional hydrodynamic flood models are commonly employed for simulating flood extent and inundation depth. However, the influence of urban drainage network (UDN) is frequently overlooked in these models, potentially compromising their accuracy. Furthermore, the expensive computational costs and longer processing times make them challenging for large-scale hydrodynamic simulation. To address these challenges, this paper develops a machine learning (ML)-driven emulator for an open-source flood model, the Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON). A TRITON-ML Emulator (TR-Emulator) that utilizes Convolutional Long Short-Term Memory is developed to capture the spatiotemporal features of flood events based on the outputs from TRITON. We further enhance the emulator by integrating UDN parameters (TR-UDN), such as the flow capacity of drainage pipes, pipe size, and pipe length, via an ML stacking technique to improve the water surface elevation (WSE) simulation. Hurricane Harvey 2017 in Houston, TX is used as the case study. We compare WSE results from TRITON, TR-Emulator, TR-UDN, and the United States Geological Survey (USGS) observations to evaluate the performance of these models. The results indicate that the TR-Emulator effectively replicates the WSE simulated by TRITON. Additionally, TR-UDN performs well in capturing WSE patterns and peak flows, aligning more closely with USGS observations, except in areas with milder slopes where conveyance discrepancies are observed. We further test the generalizability of our ML-based models using another smaller event. This paper shows that the TR-Emulator is effective for users and engineers to emulate a 2D hydrodynamic model, and the enhanced version of the TR-Emulator, TR-UDN, can be an efficient tool for predicting WSEs during urban flooding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

α-U and ω-UZr 2 in neutron irradiated U-10Zr annular metallic fuel

Here, to develop metallic fuel with ultra-high burnup of 30%-40%, an annular U-10Zr fuel with 55% smear density was fabricated through a casting route and irradiated at the Advanced Test Reactor at Idaho National Laboratory. The annular fuel design also serves as a demonstration of the feasibility to replace sodium bond with a helium bond to benefit the geological disposal of irradiated fuel, cut the cost of fuel fabrication, and boost the overall metallic fuel economy. This paper reports the results from transmission electron microscopy (TEM) based post-irradiation examination of this fuel type irradiated to a burnup of 3.3% fissions per initial heave metal atoms for initial screening purpose. After irradiation, the initial U-10Zr separated into an a-U annular region and an UZr 2+x center region with nanoscale spinodal decomposed microstructure. Because of the provided large amount of coherent interface areas, the fission gas atoms and vacancies generated in UZr 2+x phase are possibly pinned at the interface areas, leading to 20 times smaller fission gas bubbles than those in the neighboring a-U. The large bubbles in a-U become connected and merged into large pores that provide fast release paths for fission gas which prevents further fuel swelling. The fuel center still has open space to accommodate further fuel swelling from solid fission products at higher burnup. Other neutron irradiation induced phase and microstructure change are also characterized and compared with traditional solid fuel designs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Metallographic examinations and hydrogen measurements of high-burnup spent nuclear fuel cladding

In the US, commercial spent nuclear fuel (SNF) is transferred to interim dry storage casks where it will be stored for decades awaiting transport to a consolidated interim storage facility or a geologic repository. Because the fuel rod cladding is the first barrier against any radioactive material release, understanding the behavior of SNF cladding, particularly at high burnup (HBU), in dry storage conditions is crucial to safely store and transport the spent fuel. In this study, a series of metallographic examinations and cladding hydrogen measurements were conducted on HBU SNF cladding at Oak Ridge National Laboratory as a part of the High Burnup Spent Fuel Data Project, which is sponsored by the US Department of Energy (DOE) Office of Nuclear Energy (NE). Here, t o investigate the effect of simulated drying conditions on the cladding, three as-received fuel rods with different cladding materials—M5, ZIRLO, and Zircaloy-4—were heated to 400°C and then slow-cooled to room temperature. The pellet and cladding were then qualitatively and quantitatively analyzed and compared in terms of pellet crack morphology, HBU rim, waterside oxide, cladding H, and cladding hydride morphologies. This paper presents and discusses the results of these analyses in detail.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗