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At least 829 records · Page 46

Saline pulse test monitoring with the self‐potential method to nonintrusively determine the velocity of the pore water in leaking areas of earth dams and embankments

A method is proposed to localize preferential fluid flow pathways in porous media on the basis of time‐lapse self‐potential measurements associated with salt tracer injection upstream. This method is first tested using laboratory data. A network of nonpolarizing electrodes located is connected to a highly sensitive voltmeter used to record the resulting electrical field fluctuations occurring over time at the surface of the tank. The transport of the conductive salt plume through the permeable porous materials changes the localized streaming potential coupling coefficient associated with the advective drag of the excess charge of the pore water and is also responsible for a diffusion current associated with the salinity gradient. Monitoring of the electrical potential distribution at the ground surface can be used to localize the pulse of saline water over time and to determine its velocity. This method applies in real time and can be used to track highly localized flow pathways characterized by high permeability. Our sandbox experiment demonstrates the applicability of this new method under well‐controlled conditions with a coarse‐sand channel embedded between fine‐sand banks. A finite element model allows us to reproduce the time‐lapse electrical potential distribution over the channel, but some discrepancies were observed on the banks. Finally, we performed a numerical simulation for a synthetic case study inspired by a recently published field case study. A Markov chain Monte Carlo sampler is used to determine the permeability and the porosity of the preferential fluid flow pathway of this synthetic case study.

54 ENVIRONMENTAL SCIENCES↗

Assessing mechanical response of CO 2 storage into a depleted carbonate reef using a site-scale geomechanical model calibrated with field tests and InSAR monitoring data

Geomechanical risks of injection have raised concerns regarding secure CO 2 storage. In this work, a combined monitoring and modeling approach is used to assess the stress changes and surface uplift associated with CO 2 injection into a depleted carbonate reef of the Michigan basin. A site-scale geomechanical model is built by assigning mechanical properties of formations using well-log and experimental data. Gravity load is applied to the model to estimate the vertical component of stress as well as different lateral boundary displacement scenarios to estimate horizontal stresses. We used a poroelastic pressure-dependent model (instead of a linear elastic mechanical earth model) to calibrate initial stresses using hydraulic fracture test data measured at depleted reservoir status. Multi-phase fluid flow-geomechanical simulations are performed to estimate the poroelastic response during (1) primary depletion (2) field-scale CO 2 injection phase (3) a hypothetical forecast scenario in which well bottom hole pressure (BHP) reach 45000 KPa. The predicted surface uplift is less than 1 mm at the end of the field-scale CO 2 injection phase which is in good agreement with Interferometric Synthetic Aperture Radar (InSAR) uplift measurement. Although the InSAR data shows an insignificant uplift, hydromechanical modeling of injection shows that CO 2 injection still causes reservoir deformation emphasizing the role of carbonate overburden and reservoir formation mechanical properties and limited size of reef on diminishing the surface deformation. Modeling indicates poroelastic response of caprock matters to estimate uplift. The lower permeability of the top two layers provides additional barrier to large uplift. Also, history of subsidence due to production should be accounted to predict uplift due to a follow up injection correctly. This report shows the significance of combining a calibrated geomechanical model with field measured stresses and monitoring data to be used as a tool to ensure the safety of CO 2 storage.

42 ENGINEERING↗

Predicting the potential for mineral scale precipitation in unconventional reservoirs due to fluid-rock and fluid mixing geochemical reactions

Mineral precipitation within hydraulically fractured shale may affect fluid flow pathways and impact longterm hydrocarbon production. The ability to predict geochemical reactions that lead to problematic mineral precipitation will lead to active reservoir management strategies to improve overall production. Using the Marcellus Shale as a case study, a combination of laboratory experiments and reaction path modeling was applied to determine which reactions are likely to occur upon introduction of hydraulic fracturing fluid into the shale reservoir. Experimental results indicate that contact between fracturing fluid and shale will result in dissolution of primary minerals (quartz, feldspars, kaolinite, chlorite, pyrite) and secondary mineral precipitation over time periods of less than one week. Precipitation of barite, Fe-oxides, feldspars, amorphous silica and clay is likely to occur within the reservoir during shut in and early flowback due to mixing between fracturing fluid and reservoir brine as based on modeling saturation indices using experimental fluid data. Reaction path modeling of the experimental scenarios corroborates the specific dissolution and precipitation reactions observed experimentally. Comparison of the results to injected and produced waters from a Marcellus Shale well pad in Greene County, PA, USA, shows that the mineral reactions occur during the hydraulic fracturing, shut in, and early flowback periods. The results presented in this paper demonstrate the value in applying experimental approaches to identify mineral precipitation/dissolution reactions that may significantly impact reservoir performance. The good agreement between geochemical models and experimental results provides confidence that numerical models can be applied to screen the potential fluid-mineral and fluid-mixing reactions in unconventional reservoirs that result in undesired mineral scale precipitation.

58 GEOSCIENCES↗

Model fusion with physics-guided machine learning: Projection-based reduced-order modeling

The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range of spatiotemporal scales has enabled the rapid advancement of data-driven and especially deep learning models in the field of fluid mechanics. Although these methods are proven successful for many applications, there is a grand challenge of improving their generalizability. This is particularly essential when data-driven models are employed within outer-loop applications like optimization. In this work, we put forth a physics-guided machine learning (PGML) framework that leverages the interpretable physics-based model with a deep learning model. Leveraging a concatenated neural network design from multi-modal data sources, the PGML framework is capable of enhancing the generalizability of data-driven models and effectively protects against or inform about the inaccurate predictions resulting from extrapolation. We apply the PGML framework as a novel model fusion approach combining the physics-based Galerkin projection model and long- to short-term memory (LSTM) network for parametric model order reduction of fluid flows. We demonstrate the improved generalizability of the PGML framework against a purely data-driven approach through the injection of physics features into intermediate LSTM layers. Our quantitative analysis shows that the overall model uncertainty can be reduced through the PGML approach, especially for test data coming from a distribution different than the training data. Moreover, we demonstrate that our approach can be used as an inverse diagnostic tool providing a confidence score associated with models and observations. The proposed framework also allows for multi-fidelity computing by making use of low-fidelity models in the online deployment of quantified data-driven models.

42 ENGINEERING↗

Evaluation of stochastic particle dispersion modeling in turbulent round jets

ODT (one-dimensional turbulence) simulations of particle-carrier gas interactions are performed in the jet flow configuration. Particles with different diameters are injected onto the centerline of a turbulent air jet. The particles are passive and do not impact the fluid phase. Their radial dispersion and axial velocities are obtained as functions of axial position. The time and length scales of the jet are varied through control of the jet exit velocity and nozzle diameter. Dispersion data at long times of flight for the nozzle diameter (7 mm), particle diameters (60 and 90 µm), and Reynolds numbers (10, 000–30, 000) are analyzed to obtain the Lagrangian particle dispersivity. Flow statistics of the ODT particle model are compared to experimental measurements. It is shown that the particle tracking method is capable of yielding Lagrangian prediction of the dispersive transport of particles in a round jet. In this study, three particle-eddy interaction models (Type-I, -C, and -IC) are presented to examine the details of particle dispersion and particle-eddy interaction in jet flow.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Numerical investigation of plasma edge transport and limiter heat fluxes in Wendelstein 7-X startup plasmas with EMC3-EIRENE

Here the results of a first systematic assessment of plasma edge transport processes for the limiter startup configuration at Wendelstein 7-X are presented. This includes an investigation of transport from intrinsic and externally injected impurities and their impact on the power balance and limiter heat fluxes. The fully 3D coupled plasma fluid and kinetic neutral transport Monte Carlo code EMC3-EIRENE is used. The analysis of the magnetic topology shows that the poloidally and toroidally localized limiters cause a 3D helical scrape-off layer (SOL) consisting of magnetic flux tubes of three different connection lengths L C . The transport in the helical SOL is governed by L C as topological scale length for the parallel plasma loss channel to the limiters. A clear modulation of the plasma pressure with L C is seen. The helical flux tube topology results in counter streaming sonic plasma flows. The heterogeneous SOL plasma structure yields an uneven limiter heat load distribution with localized peaking. Assuming spatially constant anomalous transport coefficients, increasing plasma density yields a reduction of the maximum peak heat loads from 12 MWm -2 to 7.5 MWm -2 and a broadening of the deposited heat fluxes. The impact of impurities on the limiter heat loads is studied by assuming intrinsic carbon impurities eroded from the limiter surfaces with a gross chemical sputtering yield of 2 . The resulting radiative losses account for less than 10% of the input power in the power balance with marginal impact on the limiter heat loads. It is shown that a significant mitigation of peak heat loads, 40–50%, can be achieved with controlled impurity seeding with nitrogen and neon, which is a method of particular interest for the later island divertor phase.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NUMERICAL INVESTIGATION OF FUEL PROPERTY EFFECTS ON MIXED-MODE COMBUSTION IN A SPARK-IGNITION ENGINE

In the present study, mixed-mode combustion of an E30 fuel in a direct-injection spark-ignition engine is numerically investigated at a fuel-lean operating condition using multidimensional computational fluid dynamics (CFD). A fuel surrogate matching Research Octane Number (RON) and Motor Octane Number (MON) of E30 is first developed using neural network based non-linear regression model. To enable efficient 3D engine simulations, a 164-species skeletal reaction mechanism incorporating NO, chemistry is reducedfrom a detailed chemical kinetic model. A hybrid approach that incorporates the G-equation model for tracking turbulentflame front, and the multi-zone well-stirred reactor model for predicting auto-ignition in the end gas, is employed to account for turbulent combustion interactions in the engine cylinder. Predicted in-cylinder pressure and heat release rate traces agree well with experimental measurements. The proposed modelling approach also captures moderated cyclic variability. Two different types of combustion cycles, corresponding to purely deflagrative and mixed-mode combustion, are observed. In contrast to the purely deflagrative cycles, mixed-mode combustion cycles feature early flame propagation followed by end-gas auto-ignition, leading to two distinctive peaks in heat release rate traces. The positive correlation between mixed-mode combustion cycles and early flame propagation is well captured by simulations. With the validated numerical setup, effects of NOx chemistry on mixed-mode combustion predictions are investigated. NOx chemistry is found to promote auto-ignition through residual gas recirculation, while the deflagrative flame propagation phase remains largely unaffected. Local sensitivity analysis is then performed to understand effects of physical and chemical properties of the fuel, i.e., heat of evaporation (HoV) and laminar flame speed (S-L). An increased HoV tends to suppress end-gas auto-ignition due to increased vaporization cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased SL is found to significantly promote both flame propagation and auto-ignition. The promoting effect of SL on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end gas.

detailed chemical kinetics↗

Development of a Hydrogasification Process for Co-Production of Substitute Natural Gas (SNG) and Electric Power from Western Coals

This report presents the results of the research and development conducted on an Advanced Hydrogasification Process (AHP) conceived and developed by Arizona Public Service Company (APS) under U.S. Department of Energy (DOE) contract: DE-FC26-06NT42759 for Substitute Natural Gas (SNG) production from western coal. A double-wall (i.e., a hydrogasification contained within a pressure shell) down-flow hydrogasification reactor was designed, engineered, constructed, commissioned and operated by APS, Phoenix, AZ. The reactor is ASME-certified under Section VIII with a rating of 1150 pounds per square inch gage (psig) maximum allowable working pressure at 1950 degrees Fahrenheit (°F). The reaction zone had a 1.75 inch inner diameter and 13 feet length. The initial testing of a sub-bituminous coal demonstrated ~ 50% carbon conversion and ~10% methane yield in the product gas under 1625°F, 1000 psig pressure, with a 11 seconds (s) residence time, and 0.4 hydrogen-to-coal mass ratio. Liquid by-products mainly contained Benzene, Toluene, Xylene (BTX) and tar. Char collected from the bottom of the reactor had 9000-British thermal units per pound (Btu/lb) heating value. A three-dimensional (3D) computational fluid dynamic model simulation of the hydrodynamics around the reactor head was utilized to design the nozzles for injecting the hydrogen into the gasifier to optimize gas-solid mixing to achieve improved carbon conversion. The report also presents the evaluation of using algae for carbon dioxide (CO 2 ) management and biofuel production. Nannochloropsis, Selenastrum and Scenedesmus were determined to be the best algae strains for the project purpose and were studied in an outdoor system which included a 6-meter (6M) radius cultivator with a total surface area of 113 square meters (m 2 ) and a total culture volume between 10,000 to 15,000 liters (L); a CO 2 on-demand feeding system; an on-line data collection system for temperature, pH, Photosynthetically Activate Radiation (PAR) and dissolved oxygen (DO); and a ~2 gallons per minute (gpm) algae culture dewatering system. Among the three algae strains, Scenedesmus showed the most tolerance to temperature and irradiance conditions in Phoenix and the best self-settling characteristics. Experimental findings and operational strategies determined through these tests guided the operation of the algae cultivation system for the scale-up study. Effect of power plant flue gas, especially heavy metals, on algae growth and biomass adsorption were evaluated as well.

01 COAL, LIGNITE, AND PEAT↗

Evaporation Submodel Development for Volume of Fluid (eVOF) Method Applicable to Spray-Wall Interaction Including Film Characteristics with Validation at High Pressure and Temperature Conditions

Internal combustion engines have seen a great evolution over the last several decades through application of high pressure direct injection, multiple injections, and other technologies to reduced fuel consumption, NOx, and PM. Although combustion systems with advanced injection strategies have been studied extensively, there exists a significant fundamental knowledge gap on the fuel-spray interactions with the piston surface and chamber walls. Advanced computational codes validated with experimental techniques have to be developed for accurate representation of the drop impingement, fuel film formation, and vaporization. Current engine CFD (Computational Fluid Dynamics) spray models utilize a Lagrangian framework for modeling which lacks critical considerations of the physics pertaining to these interactions and thus requiring extensive parameterization, tuning and validation. The team from Michigan Technological University, University of Massachusetts Dartmouth, and Argonne National Laboratory is composed of experts in sprays, combustion, engines and CFD with a wide spectrum of knowledge including specific expertise in the area under consideration. In the proposed work, a VOF (Volume of Fluid) modeling approach has been adopted for the spray-wall interaction, film formation and spreading, and vaporization. With the inclusion of a vaporization submodel, a more predictive and accurate simulation of the spray-film was performed without extensive need of parameterization and tuning. Extensive experimentation of the spray-wall interaction under the range of conditions matching the thermodynamic and surface temperatures that occur in diesel and gasoline engines were conducted to validate the SWI submodels and for development of the evaporation submodel, which has been implemented in the flow solver.

42 ENGINEERING↗

Simulations of Multi-Mode Combustion Regimes Realizable In a Gasoline Direct Injection Engine

Lean and dilute gasoline compression ignition (GCI) operation in spark ignition (SI) engines are an attractive strategy to attain high fuel efficiency and low NOx levels. However, this combustion mode is often limited to low-load engine conditions due to the challenges associated with autoignition controllability. In order to overcome this constrain, multi-mode (MM) operating strategies, consisting of advanced compression ignition (ACI) at low load and conventional SI at high load, have been proposed. In this three-dimensional computational fluid dynamics study, the concept of multi-mode combustion using two RON98 gasoline fuel blends (Co-Optima Alkylate and E30) in a gasoline direct injection (GDI) engine were explored. To this end, a new reduced mechanism for simulating the kinetics of E30 fuel blend is introduced in this study. To cover the varying engine load demands for multi-mode engines, primary combustion dynamics observed in ACI and SI combustion modes was characterized and validated against experimental measurements. In order to implement part-load conditions, a strategy of mode transition between SI and ACI combustion (i.e., mixed-mode combustion) was then explored numerically by creating a virtual test condition. The results obtained from the mixed-mode simulations highlight an important feature that deflagrative flame propagation regime coexists with ignition-assisted end-gas autoignition. This study also identifies a role of turbulent flow property adjacent to premixed flame front in characterizing the mixed-mode combustion. The employed hybrid combustion model was verified to perform simulations aiming at suitable range of multi-mode engine operations.

Kim, Sayop↗

MULTIDIMENSIONAL NUMERICAL SIMULATIONS OF REACTING FLOW IN A NON-PREMIXED ROTATING DETONATION ENGINE

Over the last two decades, detonation based propulsion has received a great deal of attention as a potential means to achieve significant improvement in the performance of air-breathing and rocket engines. Detonative combustion mode is particularly interesting due to the resulting pressure gain from reactants to products, faster heat release, decreased entropy generation, more available work and higher thrust compared to conventional deflagrative combustion. Rotating detonation engine (RDE) is one such novel combustor concept. Realistic RDE configurations utilize separate fuel and air injection schemes, hence are not perfectly premixed. Moreover, RDE performance is governed by a large number of design parameters and operating conditions. In this context, computational fluid dynamics (CFD) has the potential to enhance the understanding of RDE combustion and aid future development/optimization of this technology. In the present work, a CFD model was developed to simulate a representative non-premixed RDE combustor. Unsteady Reynolds-Averaged Navier-Stokes (RANS) simulations were performed for the full combustor geometry (including the separate fuel and air injection ports), with hydrogen as fuel and air as the oxidizer. Adaptive mesh refinement (AMR) was incorporated to achieve a trade-off between model accuracy and computational expense. A finite-rate chemistry model along with a 10-species detailed kinetic mechanism was employed to describe the H2-Air combustion chemistry. Two operating conditions were simulated, corresponding to the same global equivalence ratio of unity but different fuel and air mass flow rates. For both conditions, the capability of the model to capture the essential detonation wave dynamics was assessed. A validation study was performed against experimental data available on detonation wave frequency/height, reactant fill height, oblique shock angle, axial pressure distribution in the channel, and fuel/air plenum pressure. The CFD model predicted the sensitivity of these wave characteristics to the operating conditions with good accuracy, both qualitatively and quantitatively. The present CFD model offers a potential capability to perform rapid design space exploration and/or performance optimization studies for realistic full-scale RDE configurations.

Pal, Pinaki↗

Baseline Monitoring of CO 2 Fluids

The Southeast Carbon Sequestration Partnership Phase III Anthropogenic Test at Citronelle Field is one of the United States’ largest demonstrations of CO 2 capture, transportation, injection, storage and monitoring using CO 2 derived from a coal-fired electric generating unit. This report summarizes the background and initial injection phase groundwater and soil flux monitoring results.

01 COAL, LIGNITE, AND PEAT↗

Shape optimization and fluid control of near isothermal compressor for transcritical carbon dioxide cycle

The compressor holds great promise for enhanced energy efficiency over a wide range of vapor compression systems (VCS). However, the majority of them focused on liquid refrigerant injection or inter-stage cooling technologies to improve heat transfer. Increasing the heat transfer area provides another perspective to promote heat dissipation, which commonly involves shape optimization whilst bringing some limitations, mainly from the manufacturing side. To fill the research gap, this paper compares the performance of isothermal compressors under different compression chamber shapes and chamber connection configurations. Additionally, the fluid control of the liquid piston was combined with shape optimization to explore the potential for further heat transfer enhancement. The simulation results have demonstrated that the COP improvements can reach up to 9% compared with the baseline case by optimizing the chamber shape and properly controlling the liquid piston speed, which provides a guideline for designing and customizing the isothermal compression chamber.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Mechanical Response of Castlegate Sandstone under Hydrostatic Cyclic Loading

The stress history of rocks in the subsurface affects their mechanical and petrophysical properties. Rocks can often experience repeated cycles of loading and unloading due to fluid pressure fluctuations, which will lead to different mechanical behavior from static conditions. This is of importance for several geophysical and industrial applications, for example, wastewater injection and reservoir storage wells, which generate repeated stress perturbations. Laboratory experiments were conducted with Castlegate sandstone to observe the effects of different cyclic pressure loading conditions on a common reservoir analogue. Each sample was hydrostatically loaded in a triaxial cell to a low effective confining pressure, and either pore pressure or confining pressure was cycled at different rates over the course of a few weeks. Fluid permeability was measured during initial loading and periodically between stress cycles. Samples that undergo cyclic loading experience significantly more inelastic (nonrecoverable) strain compared to samples tested without cyclic hydrostatic loading. Permeability decreases rapidly for all tests during the first few days of testing, but the decrease and variability of permeability after this depend upon the loading conditions of each test. Cycling conditions do affect the mechanical behavior; the elastic moduli decrease with the increasing loading rate and stress cycling. The degree of volumetric strain induced by stress cycles is the major control on permeability change in the sandstones, with less compaction leading to more variation from measurement to measurement. The data indicate that cyclic loading degrades permeability and porosity more than static conditions over a similar period, but the petrophysical properties are dictated more by the hydrostatic loading rate rather than the total length of time stress cycling is imposed.

58 GEOSCIENCES↗

Breakup dynamics in a pressure-swirl injector for urea-water solution applications: A computational study

The co-optimization of in-cylinder combustion and after-treatment technology has become a major aspect in engine design and development, with the goal of meeting the increasingly restrictive emission regulations in the transportation industry. Selective Catalytic Reduction is a robust technology to control the emission of NO x , and the injection of urea in water solution is the exhaust tailpipe is a key aspect of its operation. The proposed work uses high-fidelity Computational Fluid Dynamics to characterize the atomization dynamics of the liquid jet in relevant cross-flow conditions. The study focuses on a commercial low-pressure (9 bar) pressure-swirl injector which is characterized in its internal geometry through high-resolution X-ray micro-computational tomography. The internal two-phase flow has been modeled according to the volume-of-fluid approach in a large eddy simulation framework and validated against near-nozzle X-ray radiography measurement. Moreover, characterizing the breakup dynamics for the swirling hollow cone formation, and assessing the influence of the cross-flow in the breakup dynamics was completed. The results have been reported proposing Re-Oh maps and probability density functions of the spray kinematics. Higher cross-flow momentum generates an increase in the jet intact length and a reduction of the liquid droplet diameters. The axial momentum of the jet is affected by the cross-flow already in the near-nozzle region, determining a relevant deviation of the spray velocities. In conclusion, this work aims to inform the initialization of Eulerian-Lagrangian spray models through the assignment of droplet kinematics and static one-way coupling between volume-of-fluid results and Lagrangian spray parcels, to be used for system-size domain simulations.

33 ADVANCED PROPULSION SYSTEMS↗

The U.S. Gas Flooding Experience: CO2 Injection Strategies and Impact on Ultimate Recovery

The Permian Basin in West Texas and southwestern New Mexico has seen 45 years of oil reserve growth through CO2 enhanced oil recovery (CO2 EOR). More than 60 CO2 EOR projects are currently active in the region’s limestone, sandstone and dolomite reservoirs. Water alternating gas (WAG) has been the development strategy of choice in the Permian for several technical and economic reasons. More recently, the technology started to get implemented in the much more porous and permeable clastic depositional systems of the onshore U.S. Gulf Coast. Continued CO2 injection (CGI), as opposed to WAG, was selected as the injection strategy to develop Gulf Coast oil fields, where CO2 injection volumes are significantly larger (up to 6 times larger) than those of the Permian. We conducted a compositional simulation based study with the objective of comparing the CO2 utilization ratios (volume of CO2 injected to produce a barrel of oil) of 4 conventional and novel CO2 injection strategies: (1) continuous gas injection (CGI), (2) water alternating gas (WAG), (3) water curtain injection (WCI), and (4) WAG and WCI combination. These injection scenarios were simulated using the GEM module from the Computer Modeling Group (CMG). GEM is an advanced general equation-of-state compositional simulator, which includes equation of state, CO2 miscible flood, CO2/brine interactions, and complex phase behavior. The simulator is set up to model three fluid phases including water, oil, and gas. Our study demonstrates how the selected field development strategy has a significant impact on the ultimate recovery of CO2-EOR projects, with GCI injection providing maximum oil recovery in absolute volume terms, but with WAG offering a more balanced technical-economical approach.

02 PETROLEUM↗