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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Numerical simulation of the environmental impact of hydraulic fracturing of tight/shale gas reservoirs on near‐surface groundwater: Background, base cases, shallow reservoirs, short‐term gas, and water transport

Abstract Hydrocarbon production from unconventional resources and the use of reservoir stimulation techniques, such as hydraulic fracturing, has grown explosively over the last decade. However, concerns have arisen that reservoir stimulation creates significant environmental threats through the creation of permeable pathways connecting the stimulated reservoir with shallower freshwater aquifers, thus resulting in the contamination of potable groundwater by escaping hydrocarbons or other reservoir fluids. This study investigates, by numerical simulation, gas and water transport between a shallow tight‐gas reservoir and a shallower overlying freshwater aquifer following hydraulic fracturing operations, if such a connecting pathway has been created. We focus on two general failure scenarios: (1) communication between the reservoir and aquifer via a connecting fracture or fault and (2) communication via a deteriorated, preexisting nearby well. We conclude that the key factors driving short‐term transport of gas include high permeability for the connecting pathway and the overall volume of the connecting feature. Production from the reservoir is likely to mitigate release through reduction of available free gas and lowering of reservoir pressure, and not producing may increase the potential for release. We also find that hydrostatic tight‐gas reservoirs are unlikely to act as a continuing source of migrating gas, as gas contained within the newly formed hydraulic fracture is the primary source for potential contamination. Such incidents of gas escape are likely to be limited in duration and scope for hydrostatic reservoirs. Reliable field and laboratory data must be acquired to constrain the factors and determine the likelihood of these outcomes.

03 NATURAL GAS↗
DOE OSTI2015

Deep and shallow sources for the Lusi mud eruption revealed by surface deformation

The Lusi mud eruption, in East Java, Indonesia, began in May 2006 and continues to the present. Previous analyses of surface deformation data suggested an exponential decay of the pressure in the mud source but did not constrain the location, geometry, and evolution of the possible source(s) of the erupting mud and fluids. To map the surface deformation, we employ multitemporal interferometric synthetic aperture radar and analyze a well-populated L-band data set acquired by the Advanced Land Observing Satellite (ALOS) between May 2006 and April 2011. We then apply a time-dependent inverse modeling scheme. Volume changes occur in two regions beneath Lusi, at 0.3-2.0km and 3.5-4.75km depth. The cumulative volume change within the shallow source is ~2-3 times larger than that of the deep source. The observation and model suggest that a shallow source plays a key role by supplying the erupting mud, but that additional fluids do ascend from depths >4km on eruptive timescales. Key Points Spatiotemporal map of the surface deformation associated with Lusi mud eruption Time-dependent source model of the Lusi and nearby gas field Revealing the deep and shallow sources of the Lusi and characterizing their relationship.

58 GEOSCIENCES↗
DOE OSTI2016

Radar imaging of shallow water bathymetry: A case study in the Yangtze Estuary

This study focuses on 2-dimensional (2-D) radar imaging of bathymetric features in the shallow water of the Yangtze Estuary using synthetic aperture radar (SAR) observations and model simulations. A validated 2-D shallow water numerical model simulates the barotropic current velocity, and the simulated current fields together with the relevant parameters of radar observations are then invoked in the radar imaging model as the input. The results show that variations in the simulated image intensity are mainly dominated by distinct radar backscatter anomalies caused by wave-current interactions in the vicinity of rapidly changing underwater topographies. The comparison between the simulated and observed SAR images shows a reasonable agreement, demonstrating that our approach may be implemented to monitor changes in the shallow water bathymetry of the Yangtze Estuary in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Modeling the potential impacts of CO 2 sequestration on shallow groundwater: The fate of trace metals and organic compounds before and after leakage stops

Large-scale deployment of CO 2 geological sequestration requires understanding and assessing the risks of such an operation. One of these risks is the potential contamination of groundwater by CO 2 /brine leakage into shallow aquifers. Although our understanding of this issue has improved significantly over the last decade, several questions still need to be better addressed, including the fate of organic constituents, the dominant source of trace metals (are they mainly coming from aquifer sediments, or leaking brine), and whether the trace metals released during the leakage phase recover to background levels if the leakage were to be detected and stopped. In this paper, reactive transport simulations that model the behavior of trace metals and organic compounds in response to the leakage of CO 2 and brine into a shallow aquifer are presented to address these questions. Model results show that the metals and organic compounds brought by the leaking brine form a plume at the bottom of the aquifer because the density of the brine is higher than that of groundwater. In contrast, metals are mobilized by CO 2 over a larger vertical extent because of the spreading of gaseous CO 2 by buoyancy. The concentration of organic contaminants is strongly attenuated by adsorption and degradation, with degradation playing the major role in the modeled scenarios. Although the leaking brine is assumed to contain elevated concentrations of As, Pb, Cd, and Ba, it does not contribute significantly to the contamination of the modeled shallow aquifer by these elements. Once the leakage stops, mobilized organic compounds that undergo degradation vanish, while less degradable compounds linger for a longer time; the dissolved concentrations of trace metals decrease significantly, as a result of re-sorption and reversal of processes leading to Ca-driven cation exchange.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Numerical studies of CO 2 and brine leakage into a shallow aquifer through an open wellbore

Industrial-scale geological storage of CO 2 in saline aquifers may cause CO 2 and brine leakage from abandoned wells into shallow fresh aquifers. This leakage problem involves the flow dynamics in both the wellbore and the storage reservoir. T2Well/ECO2N, a coupled wellbore-reservoir flow simulator, was used to analyze CO 2 and brine leakage under different conditions with a hypothetical simulation model in water-CO 2 -brine systems. Parametric studies on CO 2 and brine leakage, including the salinity, excess pore pressure (EPP) and initially dissolved CO 2 mass fraction, are conducted to understand the mechanism of CO 2 migration. The results show that brine leakage rates increase proportionally with EPP and inversely with the salinity when EPP varies from 0.5 to 1.5 MPa; however, there is no CO 2 leakage into the shallow freshwater aquifer if EPP is less than 0.5 MPa. The dissolved CO 2 mass fraction shows an important influence on the CO 2 plume, as part of the dissolved CO 2 becomes a free phase. Scenario simulation shows that the gas lifting effect will significantly increase the brine leakage rate into the shallow freshwater aquifer under the scenario of 3.89% dissolved CO 2 mass fraction. The equivalent porous media (EPM) approach used to model the wellbore flow has been evaluated and results show that the EPM approach could either under- or over-estimate brine leakage rates under most scenarios. The discrepancies become more significant if a free CO 2 phase evolves. Therefore, a model that can correctly describe the complex flow dynamics in the wellbore is necessary for investigating the leakage problems.

58 GEOSCIENCES↗
DOE OSTI2020

Building thermal load prediction through shallow machine learning and deep learning

Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the model and input complexity. In this study, we developed 12 data-driven models (7 shallow learning, 2 deep learning, and 3 heuristic methods) to predict building thermal load and compared shallow machine learning and deep learning. The 12 prediction models were compared with the measured cooling demand. It was found XGBoost (Extreme Gradient Boost) and LSTM (Long Short Term Memory) provided the most accurate load prediction in the shallow and deep learning category, and both outperformed the best baseline model, which uses the previous day's data for prediction. Then, we discussed how the prediction horizon and input uncertainty would influence the load prediction accuracy. Major conclusions are twofold: first, LSTM performs well in short-term prediction (1 h ahead) but not in long term prediction (24 h ahead), because the sequential information becomes less relevant and accordingly not so useful when the prediction horizon is long. Second, the presence of weather forecast uncertainty deteriorates XGBoost's accuracy and favors LSTM, because the sequential information makes the model more robust to input uncertainty. Training the model with the uncertain rather than accurate weather data could enhance the model's robustness. Finally, our findings have two implications for practice. First, LSTM is recommended for short-term load prediction given that weather forecast uncertainty is unavoidable. Second, XGBoost is recommended for long term prediction, and the model should be trained with the presence of input uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Efficient shallow Ritz method for 1D diffusion problems

This paper studies the shallow Ritz method for solving the one-dimensional diffusion problem. It is shown that the shallow Ritz method improves the order of approximation dramatically for non-smooth problems. To realize this optimal or nearly optimal order of the shallow Ritz approximation, we develop a damped block Newton (dBN) method that alternates between updates of the linear and non-linear parameters. Per each iteration, the linear and the non-linear parameters are updated by exact inversion and one step of a modified, damped Newton method applied to a reduced non-linear system, respectively. The computational cost of each dBN iteration is $\mathcal{O}$(n). Starting with the non-linear parameters as a uniform partition of the interval, numerical experiments show that the dBN is capable of efficiently moving mesh points to nearly optimal locations. In conclusion, to improve the efficiency of the dBN further, we propose an adaptive damped block Newton (AdBN) method by combining the dBN with the adaptive neuron enhancement (ANE) method [28].

Diffusion problems↗
DOE OSTI2021

Background Concentrations of Argon-39 in Shallow Soil Gas

While radioisotopes of noble gases are known to be indicators of underground nuclear explosions (UNE), McIntyre et al. (2017) was the first to report the presence of 39Ar in shallow soil gas in association with a decades old UNE. While this finding hinted at the potential application of 39Ar to be used as an indicator of an UNE, doing so would also require an understanding of the natural concentrations of 39Ar present in soil gas. Without knowing the expected range and variability of naturally occurring concentrations of 39Ar, it is difficult to determine what measured concentrations would be indicative of an elevated concentration. This paper presents results from 16 soil gas samples and three atmospheric air samples collected from various locations across the western United States. Shallow soil gas samples were collected into self-contained underwater breathing apparatus (SCUBA) tanks using a custom-built soil gas sampling system and then processed and analyzed for 39Ar. The measured concentrations of 39Ar varied from atmospheric air concentrations to about 3.5 times atmospheric air concentrations. The variation in concentration was primarily attributed to the latitude the sample was collected at, which was consistent with previous work (Johnson et al. 2015). The results presented here represent the first measurements of natural background 39Ar concentrations in shallow soil gas. This data will be necessary if 39Ar is to be used as an indicator of UNE.

Fritz, Brad G.↗
DOE OSTI2022

Spectroscopic Investigation of Shallow Hole Traps in Ga- and B-doped Czochralski Silicon: Insight into Light-Induced Degradation

We report the minority carrier lifetime in B-doped Czochralski (Cz) Si declines upon carrier injection due to light-induced degradation (LID), which is attributed to the formation of a recombination-active boron-oxygen complex. Ga-doped Cz Si does not undergo LID. Previously, we showed that B-doped Cz Si undergoes a transition from paramagnetic to diamagnetic due to LID. Herein, we show that Ga-doped Cz Si remains paramagnetic upon carrier injection. This suggests that either the shallow hole traps that are formed in B-doped Cz Si are absent in Ga-doped Cz Si, or the negative-U centers in Ga-doped Cz Si do not transform into a recombination-active configuration, because the shallow acceptor trap state is shallower than the Ga acceptor level in the forbidden gap. In contrast to B-doped Cz Si, the defect signatures in Ga-doped Cz Si do not change upon light exposure, as detected by both electron paramagnetic resonance and deep-level transient spectroscopy.

14 SOLAR ENERGY↗
DOE OSTI2020

Characterizing Subsiding Shells in Shallow Cumulus Using Doppler Lidar and Large‐Eddy Simulation

Abstract The existence of subsiding shells on the periphery of shallow cumulus clouds has major implications concerning the parameterization of shallow convection, with the mass exchange between the shell and cloudy air representing a significant deviation from the commonly used bulk‐plume parameterization. We examine the structure and frequency of subsiding shells in shallow cumulus convection using Doppler lidars at the Atmospheric Radiation Measurement Southern Great Plains facility in the central United States and at the Jülich ObservatorY for Cloud Evolution in western Germany. Doppler lidar indicates that the vertical subsiding shell extent is asymmetric, while shell width is typically ~100 m. Large‐eddy simulation can reasonably simulate the observed shell structure using a grid spacing of 10 m and suggests that much of the observed asymmetry is not a result of transient cloud evolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model

Continental shallow cumulus (ShCu) clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign are simulated by using an observation-constrained cloud-system resolving model. On this day, ShCu forms over Oklahoma and southern Kansas and some of these clouds transition to deeper, precipitating convection during the afternoon. We apply a four-dimensional ensemble-variational (4DEnVar) hybrid technique in the Community Gridpoint Statistical Interpolation (GSI) system to assimilate operational data sets and unique boundary layer measurements including a Raman lidar, radar wind profilers, radiosondes, and surface stations collected by the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory into the Weather Research and Forecasting (WRF) model to ascertain how improved environmental conditions can influence forecasts of ShCu populations and the transition to deeper convection. Independent observations from aircraft, satellite, as well as ARM's remote sensors are used to evaluate model performance in different aspects. Several model experiments are conducted to identify the impact of data assimilation (DA) on the prediction of clouds evolution. The analyses indicate that ShCu populations are more accurately reproduced after DA in terms of cloud initiation time and cloud base height, which can be attributed to an improved representation of the ambient meteorological conditions and the convective boundary layer. Extending the assimilation to 18 UTC (local noon) also improved the simulation of shallow-to-deep transitions of convective clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Linking Deep and Shallow Convective Mass Fluxes via an Assumed Entrainment Distribution in CAM5‐CLUBB: Parameterization and Simulated Precipitation Variability

Abstract We modify the Zhang‐McFarlane (ZM) deep convection scheme in the Community Atmosphere Model version 5 to couple it with a unified parameterization for boundary‐layer turbulence and shallow convection, that is, Cloud Layers Unified by Binormals (CLUBB). By assuming a lognormal distribution of entrainment rate across the entire moist convective regimes, we link mass fluxes between shallow and deep convection, which are partitioned by the entrainment rate of the shallowest deep convective plume. Hence, a new deep convective closure is established which is coupled to the sub‐grid vertical motion variability in CLUBB. The convection feedback (or memory) effects are also considered to decrease the entrainment spectrum width and enhance the vertical velocity variability that further affect deep convection. Results show that the revised scheme improves the precipitation simulations in terms of the mean state and variability at various timescales, such as the alleviated double‐intertropical convergence zone and more realistic simulations of the seasonal variation of monsoon precipitation over East Asia, Madden‐Julian Oscillation, and precipitation diurnal phase propagations downstream of large terrains. The improvements are still seen in many aspects such as the mean‐state precipitation when turning off the convection feedback impacts in the revised scheme, emphasizing the benefits of using the modified mass‐flux closure. However, the convection feedbacks have considerable effects on the precipitation diurnal cycle simulations over regions with late‐afternoon precipitation peaks. Overall, the revised scheme provides a unified treatment for sub‐grid vertical motions across regimes of boundary‐layer turbulence, shallow convection, and deep convection, leading to better‐simulated precipitation at various timescales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Factors Governing Cloud Growth and Entrainment Rates in Shallow Cumulus and Cumulus Congestus During GoAmazon2014/5

Shallow cumulus and cumulus congestus clouds play an important role in the large-scale tropical circulation by mixing heat and moisture vertically and preconditioning the environment for deeper convection. Different representations of these shallow clouds account for much of the spread in General Circulation Model (GCMs) climate sensitivity, potentially because of how entrainment is represented in GCM parameterizations. This study uses observations from the Department of Energy's Atmospheric Radiation Measurement (ARM) mobile facility deployed at Manacapuru, Brazil, during the Green Ocean Amazon (GoAmazon2014/5) Campaign. Environmental thermodynamic profiles and observations of cloud top height (CTH) are used to constrain an entraining plume model to estimate bulk entrainment rates (ERs). Estimates of CTH are obtained from a combination of vertically pointing W-band ARM cloud radar and 1,290 MHz Radar Wind Profiler observations. A combination of radiosonde, microwave radiometer profiler, and microwave radiometer observations provides new best estimates of the environmental thermodynamic state. We quantify uncertainty in ERs considering uncertainties in estimated CTH, environmental thermodynamic properties, and assumed initial parcel characteristics. We find ERs ranging from 0.16 to 2.8 km -1 with an average of 0.58 ± 0.10 km -1 over a selected population of 469 shallow cumulus and cumulus congestus clouds. Using the retrieved estimates of ER, we evaluate several entrainment closures that are currently used in atmospheric models or have been proposed based on theory or large eddy simulation. Finally, entrainment rates in cumulus clouds are weakly correlated with low-level buoyancy, cloud depth, and cloud size.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Large-Scale Forcing Impact on the Development of Shallow Convective Clouds Revealed From LASSO Large-Eddy Simulations

Real-world large-eddy simulations (LES) are driven by time-varying large-scale forcings (LSF) - e.g., temperature advection, moisture advection, and subsidence - derived from large-scale weather models. This study investigates the impact of the uncertainty in LSF on real-world LES in terms of the development of shallow convection at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory for the 11 June 2016 case using LES provided by the U.S. Department of Energy's LES ARM Symbiotic Simulation and Observation (LASSO) activity. The LASSO dataset provides an ensemble of LES for the selected case, which consists of LES runs that were driven by different LSF. The two contrasting LES runs investigated here generate different types of convective clouds, i.e., nonprecipitating shallow clouds and precipitating cumulus congestus, mainly due to the difference of LSF in temperature advection in the free troposphere. The temperature advection modulates the strength of the capping inversion and therefore the buoyancy of the air parcels rising from the atmospheric boundary layer (ABL). The inversion, together with large-scale updrafts, controls the penetration of the ABL thermals into the free troposphere, leading to cumulus congestus in the case of a weaker inversion. In contrast, clouds remain shallow in the case of a strong inversion. Differences between the two simulations are amplified over time, as mixed-phase clouds are formed near the top of the congestus in the weaker inversion case. Furthermore, this high dependency of LES results to LSF stresses the importance of accurate LSF by large-scale models to real-world LES simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluating Shallow Convection Parameterization Assumptions With a q t – w Quadrant Analysis

Abstract Uncertainties associated with the response of shallow clouds to global warming remain a great challenge for climate projection. Due to the small size of these clouds, parameterizations are required to represent them in both current‐ and next‐generation climate models. We present a quantitative evaluation of several important assumptions used in both mass‐flux and Assumed‐PDF Higher‐Order Closure parameterizations of shallow convection. We use large‐eddy simulations (LESs) of four different shallow convection regimes as benchmarks and apply a q t (total moisture)– w (vertical velocity) quadrant analysis technique to identify the “coherent structures” of moist and dry up/down‐drafts. The statistics of these coherent structures and the environment are then used to evaluate commonly used assumptions in mass‐flux parameterizations related to (a) the convective downdrafts and (b) the subplume variability of convective updrafts. For quantitative evaluation of the PDF closure used in AP‐HOCs, we perform offline calculations with the PDF closure used in the Cloud Layers Unified By Bi‐normals and the Simplified Higher‐Order Closure schemes by supplying the closure with statistical quantities directly calculated from the LESs. Then, the impact of parameterization assumptions embedded in the PDF closure in the same two categories is analyzed and understood through comparisons of the output from the closure with the statistics of the moist and dry up/down‐drafts from the LESs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Probabilistic evaluation of shallow groundwater resources at a hypothetical carbon sequestration site

Carbon sequestration in geologic reservoirs is an important approach for mitigating greenhouse gases emissions to the atmosphere. This study first develops an integrated Monte Carlo method for simulating CO 2 and brine leakage from carbon sequestration and subsequent geochemical interactions in shallow aquifers. Then, we estimate probability distributions of five risk proxies related to the likelihood and volume of changes in pH, total dissolved solids, and trace concentrations of lead, arsenic, and cadmium for two possible consequence thresholds. The results indicate that shallow groundwater resources may degrade locally around leakage points by reduced pH and increased total dissolved solids (TDS). The volumes of pH and TDS plumes are most sensitive to aquifer porosity, permeability, and CO 2 and brine leakage rates. The estimated plume size of pH change is the largest, while that of cadmium is the smallest among the risk proxies. Plume volume distributions of arsenic and lead are similar to those of TDS. The scientific results from this study provide substantial insight for understanding risks of deep fluids leaking into shallow aquifers, determining the area of review, and designing monitoring networks at carbon sequestration sites.

58 GEOSCIENCES↗
DOE OSTI2015

Muon background studies for shallow depth Double - Chooz near detector

Muon events are one of the main concerns regarding background in neutrino experiments. The placement of experimental set-ups in deep underground facilities reduce considerably their impact on the research of the expected signals. But in the cases where the detector is installed on surface or at shallow depth, muon flux remains high, being necessary their precise identification for further rejection. Total flux, mean energy or angular distributions are some of the parameters that can help to characterize the muons. Empirically, the muon rate can be measured in an experiment by a number of methods. Nevertheless, the capability to determine the muons angular distribution strongly depends on the detector features, while the measurement of the muon energy is quite difficult. Also considering that on-site measurements can not be extrapolated to other sites due to the difference on the overburden and its profile, it is necessary to find an adequate solution to perform the muon characterization. The method described in this work to obtain the main features of the muons reaching the experimental set-up, is based on the muon transport simulation by the MUSIC software, combined with a dedicated sampling algorithm for shallow depth installations based on a modified Gaisser parametrization. This method provides all the required information about the muons for any shallow depth installation if the corresponding overburden profile is implemented. In this work, the method has been applied for the recently commissioned Double - Chooz near detector, which will allow the cross-check between the simulation and the experimental data, as it has been done for the far detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Dynamics of electrified liquid metal surface using shallow water model

A shallow water model that incorporates surface tension and electric field effects is developed to investigate the dynamics of an electrified liquid surface. The computational model is verified against the Zakharov–Kuznetsov equation and is applied to study the growth and damping of the electrified liquid surface. A linear wave analysis is performed under a shallow water theory assuming an analytic solution of the electric field, similar to the Tonks–Frenkel instability. The electrified liquid surface grows or dampens based on the balance of the electric field, surface tension, and gravitational forces. As a result, the numerical results obtained from the electrified shallow water solver are in good agreement with the theoretical analysis.

Computational models↗