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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

QUIC-URB and QUIC-fire extension to complex terrain: Development of a terrain-following coordinate system

Ensemble-based approaches to prescribed fire planning cannot be supported by CFD-based models like FIRETEC and WFDS because they are too computationally expensive and cannot leverage LES approaches like CAWFE and WRF-SFIRE because too coarse of resolution. QUIC-Fire was developed to fill this gap but it cannot currently address complex terrain, typical for instance of the Western United States. In this paper, we describe the extension of the diagnostic wind model QUIC-URB, the wind engine of QUIC-Fire, to a terrain-following coordinate system. In particular, the paper presents the mathematical derivation of the wind solver leading to a linear system of equations that are solved through the successive over-relaxation method. The model is validated against a standard test used in previous works (the Askervein Hill) and against a new dataset from measurements in the Socorro Mountains, New Mexico. The terrain-following implementation captured the correct phenomenology for the isolated Askervein Hill, with a wind speed up at the top of the hill. We report the model agreed well with measurements on the upwind side of the peak, but overestimated speed-up on the downwind side of the hill. This is due to the inability of the model to generate flow separation and wake-eddy dynamics. On a common laptop, the divergence-free wind field was obtained in 6 s, making the solver appealing for coupled fire–atmosphere simulations. The Socorro Mountain was highly complex, with many cliff faces, peaks, and valleys. Although the model captures the magnitude and direction of inlet and outlet areas of the domain, it performs rather poorly in the valley region and in the regions near the steep cliffs. Hence, the model shows good agreement with data in areas of open sloped terrain but lacks in areas where flow separation and thermally driven effects may be present (neither effect was addressed in this work). Results highlight that future work should focus on the implementation of parameterizations of wake-eddies, similar to QUIC-URB’s building parameterizations, and on thermodynamic-driven flow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The evolution of seafloor venting from hydrate-sealed gas reservoirs

Here we use 3D seismic data to show that three rows of seafloor gas mounds can be traced downward to leak points that lie at the hydrate-gas contact within three individual dipping coarse-grained sand bodies in the Terrebonne Basin, Walker Ridge block 313, northern Gulf of Mexico. We predict the overpressure within the sand bodies by assuming that the gas pressure at the vent points equal the least principal stress. We interpret that free gas accumulates at the base of the hydrate stability zone, trapped by the overlying sand which has a high methane hydrate saturation. The free gas accumulates until the gas pressure at the base of the hydrate stability zone reaches the least principal stress in the overlying mudrock, whereupon hydraulic fractures form and fluids are vented to the surface. The warm rising fluids and perhaps localized exothermic formation of hydrate raise the local salinity and temperature. This process progressively shifts the base of the hydrate stability zone to shallower depths and dissociates the hydrate seal within the sand, which creates new leak points and results in the observed migration of the seafloor vents. Within the southwest corner of the Terrebonne Basin, this process has repeated multiple times within the Blue, Orange, and Green sands. Here this study shows how the hydrate stability zone can influence the location of fluid expulsion and in turn be affected by the warm, rising, saline fluids sealed by hydrate.

58 GEOSCIENCES↗
DOE OSTI2022

Discovering hidden geothermal signatures using non-negative matrix factorization with customized k-means clustering

Discovery of hidden geothermal resources is challenging. It requires the mining of large datasets with diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used play fairway analysis approach typically incorporates subject-matter expertise to analyze regional data to estimate geothermal characteristics and favorability. We demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset from southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. Several of these systems are not well characterized because of insufficient existing data and limited past explorative work. This study discovers hidden patterns and relations in the SWNM geothermal dataset to improve our understanding of the regional hydrothermal conditions and energy-production favorability. This understanding is obtained by applying an unsupervised ML algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden signatures characterizing analyzed datasets, (2) the optimal number of these signatures, (3) the dominant data attributes associated with each signature, and (4) the spatial distribution of the extracted signatures. Here, in this study, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, and geothermal attributes at 44 locations in SWNM. Using NMFk, we find data patterns and identify the spatial associations of hydrothermal signatures within two physiographic provinces (Colorado Plateau and Basin and Range) and two sub-regions of these provinces (the Mogollon-Datil volcanic field and the Rio Grande rift) in SWNM. The ML algorithm extracted five hydrothermal signatures in the SWNM datasets that differentiate between low (<90°C) and medium (90-150°C)-temperature hydrothermal systems. The algorithm also suggests that the Rio Grande rift and northern Mogollon-Datil volcanic field are the most favorable regions for future geothermal resource discovery. NMFk also identified critical attributes to identify medium-temperature hydrothermal systems in the study area. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored regions. The code to execute the performed analyses as well as the corresponding data can be found at https://github.com/SmartTensors/GeoThermalCloud.jl.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Fetch-trap Pairs: Exploring definition of carbon storage prospects to increase capacity and flexibility in areas with competing uses

As CCS grows beyond isolated first-mover projects, the question of how to identify potential storage sites (prospects) is key to siting projects amidst the constraints of neighboring storage projects, hydrocarbon fields and other considerations. To date, prospects have been defined either by the extent of a buoyant trap or by the predicted maximum extent of the CO 2 or pressure plume. Both approaches have worked, but they may struggle in places like the Gulf of Mexico where complex geologic structure can invalidate simple assumptions of radial plume spread and buoyant traps are commonly unattractive due to numerous legacy well penetrations. Here, we propose identifying prospective storage sites by fetch area (drainage cell) rather than by buoyant closure alone. Doing so offers 1) greater freedom in siting injectors to avoid surface and subsurface constraints, including legacy wells that tend to cluster on structural high; and 2) a coherent flow regime in which buoyancy drives all injected CO 2 toward a common high. This strategy gives space to dissipate injection pressure and minimize the number of legacy wells needing review. It may also offer 1) better injectivity by bringing synclines and associated channel axes into play; and 2) potentially improved capacity by tapping a larger rock volume and taking advantage of migration losses.

58 GEOSCIENCES↗
DOE OSTI2022

Impacts of climate change on future hurricane induced rainfall and flooding in a coastal watershed: A case study on Hurricane Harvey

The warming climate is likely to increase hurricane-associated extreme rainfall and lead to sea-level rise (SLR). Thus, how the floods induced by intense hurricanes respond to these potential changes is of great concern. This study investigates the future warmer climate impacts on hurricane-induced extreme rainfall, and—more importantly—the subsequent compound flooding at the watershed scale (from an event-based analysis perspective). To this goal, a modeling framework is designed based on the Distributed Hydrology Soil Vegetation Model (DHSVM), the Two-Dimensional fvand the Regional Community Earth System Model (R-CESM). The framework was applied to Hurricane Harvey (2017) at the Clear Creek watershed (a coastal watershed in the southern Houston) as a case study. The results show that the projected maximum rainfall totals over the watershed would be exacerbated by 17.7 % and 49.7 % in the 2050s and 2090s (respectively) under Representative Concentration Pathway 8.5 (RCP 8.5). This means a 16.1 % increase in Harvey rainfall over the watershed per degree Celsius increase in Mean Surface Temperature over the Gulf of Mexico region (18°~31° N, 77°~98° W). Meanwhile, the increases in maximum inundation extent would be 11.0 % (2050s) and 19.5 % (2090s). Furthermore, considerable increases in maximum inundation depth and duration in regions along the middle and downstream of Clear Creek (and also those around Clear Lake) are expected. The projected SLR will have little effect on the maximum inundation depth and extent if storm surge changes are not taken into account; meanwhile, it will influence the inundation duration at downstream locations. In conclusion, this modeling framework can be also applied at other coastal watersheds to evaluate the projected climate change impacts on the compound flooding induced by extreme climate events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.

3D reconstruction model↗
DOE OSTI2020

Thermo-hydrologic processes in maar eruptions: The role of vapor transport and condensation

Phreatomagmatic eruptions occur when magma interacts directly with water or slurries, commonly from groundwater in the shallow crust, resulting in rapid conversion of thermal energy to mechanical energy in a set of processes known as molten fuel-coolant interaction (MFCI). The efficiency of MFCI is controlled by properties of the magma and coolant, contact surface geometry, and system conditions, such as pressure and temperature; phreatomagmatic behavior can range from passive thermal granulation to violent thermohydraulic explosions (Zimanowski et al., 2015). Maar-diatreme eruptions, characterized by repetitive phreatomagmatic explosions, can form in a wide range of near-surface environments, from soft sediment substrate (e.g., Tecuitlapa, Mexico, Ort and Carrasco-Núñez, 2009; Hopi Buttes, AZ, Lefebvre et al., 2013) to hard, fractured country rock (e.g., West Eifel volcanic field, Germany and Massif Central, France, Lorenz, 2003). Country-rock structure, including faults and joints, rock type, and shallow crustal hydrologic properties, can influence an eruption’s behavior by controlling how much and at what rate water can be supplied to the magma (hydraulic flow rate), and determining the sediment: water ratio in the case of soft-sediment substrate eruptions. In a “soft” substrate environment, volcanic tremor can lead to liquefaction of saturated sediment, producing a slurry that may then interact with magma in unique ways (White, 1996; Auer, et al., 2006).

58 GEOSCIENCES↗
DOE OSTI2024

A knowledge gap analysis for transient CHF prediction within RELAP5-3D

Here we compare several experimental pool and flow boiling critical heat flux experiments with corresponding computational models developed with RELAP5-3D. Encompassed within this paper are several sensitivity analyses for the boiling heat transfer correlations, critical heat flux (CHF) prediction within RELAP5-3D and the thermal properties of the cladding for experiments in the Transient Reactor Test Loop (TRTL) and Transient Reactor Test (TREAT) facilities. The sensitivity analyses were consistent in determining that there is a large contribution from the critical heat flux multiplier which in this application, accounts for the effects of power transient critical heat flux. Comparison to experimental results of both the TREAT CHF-SERTTA experimental campaign and a University of New Mexico (UNM) pool boiling experimental campaign demonstrate both the under-prediction of transient CHF and nucleate boiling heat transfer. To address the gaps in knowledge regarding the transient heating effect for both boiling heat transfer and CHF prediction, we present an experimental test matrix for the TRTL facility that will isolate the power transient effect under PWR relevant operational conditions. The test matrix will incorporate 6 power pulses with a constant energy deposition and a timescale that spans over several orders of magnitude, including a steady state test with an exponential period of 10 s.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Total Water Level Prediction at Continental Scale: Coastal Ocean

We demonstrate recent progress made in the simulation of total water level (TWL) at continental scale, using the coastal ocean of US East Coast/Gulf of Mexico coast as an example. A key difference between the continental-scale and small-scale modeling is that the former requires a more accurate vertical datum. Using a geoid-based datum (xGEOID20b), a satellite altimetry product, and a state-of-the-art 3D unstructured-grid model, we significantly improve the accuracy for TWL both near- and off-shore. The average root-mean-square error at all NOAA stations is 14 cm. The non-tidal signals are found to be sensitive to the representation of a large-scale current system near the boundary and extending the domain extent to accommodate this system improves these signals.

Cui, Linlin↗
DOE OSTI2023

A scalable wave resource assessment methodology: Application to U.S. waters

Waves deliver large quantities of energy to populated coastlines around the world, and wave energy technology research and development has accelerated over the last two decades. Throughout this time national and regional resource assessments have utilized disparate methodologies, which can cause confusion and skepticism. Here, in this work, we describe a theoretical wave resource assessment methodology that addresses many of the major areas of inconsistency and debate. Applying this revised methodology to U.S. waters, we find the theoretical U.S. wave energy resource to be 3300 TWh/yr, with region totals of 2000 TWh/yr in Alaska, 510 TWh/yr along the U.S. west coast, 380 TWh/yr in Hawaii, 290 TWh/yr along the east coast, 69 TWh/yr in the Gulf of Mexico, and 17 TWh/yr in Puerto Rico and the U.S. Virgin Islands. We also find significant uncertainty in these estimates associated with the underlying model dataset, which emphasizes the importance of thorough model validation and calibration as well as quantifying uncertainty.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

U-Pu and Ba-Cs isotopic measurements on Trinitite by laser ablation sampling on the Neoma MC-ICP-MS

In this study we present the results of combined U-Pu and Ba-Cs isotope measurements obtained by laser ablation (LA) sampling of two glassy debris fragments (‘Trinitite’) from the world's first atomic bomb detonation conducted in New Mexico on July 16, 1945. Our primary goal in conducting these measurements was to understand whether examination of the U-Pu and Ba-Cs systematics by direct sampling (e.g. without any chemical separation or purification prior to isotope ratio measurement) could yield meaningful information that would differentiate the Trinitite fragments from glassy material lacking a nuclear fission signature. These measurements were conducted on a ThermoFisher Scientific Neoma multi collector – inductively coupled plasma – mass spectrometer (MC-ICP-MS), which is a relatively new MC-ICP-MS platform, so we also examine the behavior of these isotope systems in standards sampled in solution and via LA. Unsurprisingly, the measurements made on purified solutions of the U, Pu, and Ba isotopic standards produce high precision isotope ratios. Furthermore, this extends to the U-Pu measurements made by LA sampling, with the expected degradation in precision and accuracy related to matrix effects and signal intensity fluctuation. However, the Ba-Cs data acquired by LA is of low precision across all of the matrices examined and bears evidence of complex mass fractionation that will require further investigation to resolve. In total, our results indicate that the observed U-Pu isotope data are of sufficient quality to accurately constrain the U and Pu isotopic composition of glass containing sub-ppm levels of these elements which in turn could be used to differentiate glass containing anthropogenic fission products from natural glass whereas the Ba-Cs LA data cannot be used for this purpose until further methodological refinement is performed.

Ba-Cs↗
DOE OSTI2023

Plant versus local soil inorganic ionic composition: The relationship to biomass smoke

Here, we examine the relationship between soil and plant inorganic chemical composition as a precursor to biomass smoke aerosol particle (PM 2.5 ) properties in desert landscapes of the Southwestern United States. Past work underscored the importance of plant species and in particular the dependence of smoke PM 2.5 water uptake on the water-soluble inorganics important in select plant species (e.g., halophytes) versus absent in other species (e.g., conifers). This study extends this work by looking at a range of soil types and salinity in examining native and invasive species in the Desert Southwest US region. Eighteen plant samples and surrounding soils were taken from four ecosystems in New Mexico, USA. Results here support the conclusion that plant species are the primary controller over the inorganic plant composition that is relevant to biomass smoke and controls its hygroscopicity. The role of soil type is secondary to plant inorganic composition but is found to be important on the ecosystem level in determining what plant species are viable in a given ecosystem. This ultimately affects the smoke properties, including PM 2.5 hygroscopicity (water uptake), produced in landscape fires. Knowledge of ecosystem features including plant species distribution and soil salinity may be combined as a first-order predictor of PM 2.5 hygroscopicity of the primary smoke emissions. This can be particularly useful when combined with knowledge of burn characteristics such as flame temperature, which also plays a key role in determining PM 2.5 water uptake response.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An assessment of tropical cyclones in North American $\mathrm{CORDEX}$ $\mathrm{WRF}$ simulations

This work presents an assessment of tropical cyclones (TCs) in the 25 km and 50 km resolution reanalysis-forced and baseline and future (RCP8.5) global climate model (GCM) forced simulations produced for the North American branch of the international Coordinated Regional climate Downscaling Experiment (NA-CORDEX) using the Weather Research and Forecasting (WRF) model. A set of complementary 12 km resolution simulations produced as a part of a different project is also included in this assessment. Before examining the projections from the GCM-driven simulations, the ability of the simulations to minimally produce a realistic spatial distribution of historical TC occurrence was assessed in simulations forced by reanalysis and the three different GCMs used herein. Then, projections for occurrence, TC related mean precipitation and precipitation intensity, storm duration, the intensity measured by minimum pressure and maximum wind speed, storm size, and translation speed were examined. Several of these characteristics show little to no change in the future in trend or in distribution across the ensemble. However, many simulations suggest a westward shift or increase in TC occurrence over the East Pacific basin and a decrease in occurrence over the Caribbean and Gulf of Mexico. Increases (decreases) in total storm-related precipitation are projected where TC occurrence increases (decreases). TC precipitation intensity is found to increase in all simulations over the East Pacific, but projections are mixed over the North Atlantic. Finally, the ensemble projects a distribution shift towards more intense TC over the East Pacific, and a shift toward faster translation speeds over the North Atlantic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Water Quality Effects of Economically Viable Land Use Change in the Mississippi River Basin under the Renewable Fuel Standard

Demand for biofuel production driven by the Renewable Fuel Standard (RFS2) has coincided with increased land in corn production and increasing nitrogen (N) loss to the Gulf of Mexico. Diversifying cropland with perennial energy crops (miscanthus and switchgrass) may reduce N loss and improve water quality. However, the extent of these benefits depends on the mix of biomass feedstocks (corn stover, perennials) incentivized by the RFS2 and the extent to which energy crops displace N-intensive row crops. We developed an integrated economic-biophysical model to quantify the water quality impacts of three potential policy scenarios that provided corn ethanol at levels before the RFS2 (RFS1 baseline); 15 billion gallons of corn ethanol (corn ethanol only); or 16 billion gallons of cellulosic ethanol in addition to corn ethanol (corn + cellulosic ethanol). Our results showed that economically optimal locations for perennial energy crop production were distributed across idle cropland with lower intrinsic N loss than active cropland. We found stover removal incentivized by the RFS2 offset N loss benefits of perennial energy crops. Furthermore, this finding suggests that targeted incentives for N loss reduction are needed to supplement the RFS2 to induce displacement of N-intensive row crops with energy crops to reduce N losses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Seasonality and Declining Intensity of Methane Emissions from the Permian and Nearby US Oil and Gas Basins

We quantify weekly methane emissions and trends from oil and gas production in the US Permian Basin for 2019-2023, and in nearby basins for 2022-2023, by analytical inversion of Tropospheric Monitoring Instrument (TROPOMI) satellite observations with the Integrated Methane Inversion (IMI) at 25 km resolution. Permian oil and gas emissions averaged 4.0 ± 1.1 Tg a-1 over 2019-2023, with large seasonal variation but little interannual variability. Methane intensity fell from 5.2 to 3.2% as production surged. Intensity in the New Mexico Permian fell from 4.5 to 2.1%, approaching the state's 2026 target of <2%. Emissions were on average 50 ± 10% higher in winter than summer, which we corroborate with Permian Basin Tower Network measurements, Insight M aircraft data, and GHGSat satellite observations. This seasonality may be driven in part by higher winter emissions from liquid storage tanks due to decreased separator efficiency in cold conditions. Similar but weaker seasonality along with decreasing emissions and intensities is found in weekly inversions for the Anadarko, Barnett, Eagle Ford, and Haynesville basins in 2022-2023. Our work suggests that better weatherization of oil and gas facilities could significantly reduce methane emissions.

Permian↗
DOE OSTI2020

Spatiotemporal Variability in Transport and Reactive Processes Across a First- to Fifth-Order Fluvial Network

Fluvial networks integrate and transport constituents from terrestrial and aquatic ecosystems. To date, most research on water quality dynamics has focused on process understanding at individual streams and, as a result, there is a lack of studies analyzing how small-scale, physical and biogeochemical drivers scale across fluvial networks. We performed tracer tests in five stream orders of the Jemez River continuum in New Mexico, USA, to quantify reach-scale hyporheic exchange during two different seasonal periods to address: how do hyporheic zone contributions to riverine processing change with space and time? And does the spatiotemporal variability of hyporheic exchange scale across fluvial networks? Combining conservative (i.e., bromide) and reactive (i.e., resazurin) tracer analyses with solute transport modeling, we found a dominance of reaction-limited transport conditions in space (for all stream orders) and time (two contrasting flow regimes). Moreover, we found a trend toward more reaction-limited conditions with increasing discharge across all stream orders. While our studied fluvial network did not consistently follow the expectations of decreasing hyporheic exchange contributions with increasing stream order, as it has been previously suggested from modeling studies, we found that processing rate coefficients and Damköhler numbers consistently decreased along the continuum with increasing discharge. Our findings suggest that knowledge transferability of hyporheic zone processing along fluvial networks may be possible if the scaling patterns that we found hold true in other catchments. Thus, more research on scaling patterns along fluvial networks is highly needed.

Gootman, Kaylyn S.↗
DOE OSTI2020

Dynamics of Gas Bubbles From a Submarine Hydrocarbon Seep Within the Hydrate Stability Zone

We validate a new model for mass transfer and bubble transport for natural seeps on the continental margins using an integrated observation of a seep at 883 m in the Northern Gulf of Mexico. In the model, mass transfer is assumed to transition from clean to dirty bubble mass transfer rates following a characteristic hydrate formation time that depends on the initial bubble surface area and the hydrate subcooling. We show that buoyancy-induced upwelling is negligible for the bubble stream. We initialize the model using precise data observed at the seafloor and validate the model results to optical and acoustic measurements within the bubble stream. The model accurately predicts the acoustic attenuation of the bubble flare by lateral spreading and bubble shrinkage throughout the water column. In conclusion, the model shows that up to 99.4% by mass of the released gases from this seep dissolves into the ocean within the hydrate stability zone.

03 NATURAL GAS↗