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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 163 records · Page 9

Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties

Machine learning-based data-driven modeling can allow computationally efficient time-dependent solutions of PDEs, such as those that describe subsurface multiphysical problems. In this work, our previous approach (Kadeethum et al., 2021d) of conditional generative adversarial networks (cGAN) developed for the solution of steady-state problems involving highly heterogeneous material properties is extended to time-dependent problems by adopting the concept of continuous cGAN (CcGAN). The CcGAN that can condition continuous variables is developed to incorporate the time domain through either element-wise addition or conditional batch normalization. Moreover, this framework can handle training data that contain different timestamps and then predict timestamps that do not exist in the training data. As a numerical example, the transient response of the coupled poroelastic process is studied in two different permeability fields: Zinn & Harvey transformation and a bimodal transformation. The proposed CcGAN uses heterogeneous permeability fields as input parameters while pressure and displacement fields over time are model output. Our results show that the model provides sufficient accuracy with computational speed-up. This robust framework will enable us to perform real-time reservoir management and robust uncertainty quantification in poroelastic problems.

97 MATHEMATICS AND COMPUTING↗

Quadri-joint inversion: Method and application to the Big Sky 9C 3D data set in northern Montana

The Kevin Dome [Formula: see text] storage project, located in northern Montana, attempted to characterize the Duperow Formation as a potential long-term storage zone for injected [Formula: see text]. A multicomponent (9C) seismic survey was acquired for the Big Sky Carbon Sequestration Partnership over a portion of the Kevin Dome using P- and S-wave sources. Prestack migrated PP, PS, SH, and SV data sets were generated. We then applied several stratigraphic inversion workflows using one or several kinds of seismic wavefield at the same time resulting in joint inversions of each data set. The aim of our study is to demonstrate the benefits of doing quadri-joint inversion of PP-, PS-, SH-, and SV-wavefields for the recovery of the elastic earth parameters, especially the S-wave impedance and density. These are crucial parameters because they can help determine lithology and porefill in the reservoir characterization workflow. Because the inversion workflow always uses the original seismic data recorded in its own time domain, it is necessary to compute registration laws between PP-PS-, PP-SH-, and PP-SV-wavefields using a time shift computation procedure (warping) based on inverted S-wave impedances from inversion of a single wavefield. This generated a significant improvement over methods that rely on attempting to match trace waveforms that may have a different phase, frequency content, and polarity. Finally, we wanted to investigate the reliability of the quadri-joint inversion results in the Bakken/Banff Formations, which have less lateral geologic variation than the underlying Duperow target. This interval shares many of the geophysical characterization challenges common to shale reservoirs in other North American basins. We computed geomechanical parameters, such as Poisson’s ratio and Young’s modulus, which are a proxy for brittleness. Comparison of these results with independent laboratory measurements in the Bakken interval demonstrates the superiority of the quadri-joint inversion method to the traditional inversion using P-wave data only.

Geochemistry & Geophysics↗

Tundra SGS – Critical Importance of Site-Specific Injectivity Testing for Carbon Dioxide Injection Well Simulation Calibration

Paper presented at 16th International Conference on Greenhouse Gas Control Technologies (GHGT-16), October 23–27, 2022, Lyon, France. Brine injectivity tests were conducted on both the Broom Creek (BC) and Deadwood (DW) storage formations in one of the cored stratigraphic test wells prior to finalized simulations. The injectivity tests entailed injection of brine into the formations, followed by shutting in the wells. The shut-in duration represents the fall-off period which was used to carry out pressure transient analyses of the tests. The analysis of injectivity tests indicated that core-indicated and modeled permeability distributions should be conservatively multiplied by 2.5× and 5× in the BC and DW geologic models, respectively, prior to numerical simulations of CO 2 injection using Computer Modelling Group’s (CMG’s) GEM equation-of-state reservoir simulator. The scaler permeability multipliers allowed the fluid flow simulations to fully represent well test-measured injection well rates in the respective formations.

20 FOSSIL-FUELED POWER PLANTS↗

The NASA Ames 16-Inch Shock Tunnel Nozzle Simulations and Experimental Comparison

The 16-Inch Shock Tunnel at NASA Ames Research Center is a unique test facility used for hypersonic propulsion testing. To provide information necessary to understand the hypersonic testing of the combustor model, computational simulations of the facility nozzle were performed and results are compared with available experimental data, namely static pressure along the nozzle walls and pitot pressure at the exit of the nozzle section. Both quasi-one-dimensional and axisymmetric approaches were used to study the numerous modeling issues involved. The facility nozzle flow was examined for three hypersonic test conditions, and the computational results are presented in detail. The effects of variations in reservoir conditions, boundary layer growth, and parameters of numerical modeling are explored.

TokarcikPolsky, S.↗

A Novel Workflow for Coupled Simulation of Hydraulic Stimulation with Simultaneous Injection of Proppant

Enhanced Geothermal Systems (EGS) are located in impermeable host rock. Therefore, to achieve promising circulation, hydraulic stimulation is a key factor. Stimulation involves injecting a combination of fluids and proppant particles into existing fractures under high pressure. The effectiveness of stimulation depends on a variety of different factors, including the pressurization scheme and the optimal choice of carrying fluid and proppant particles to be used. For example, high-density particles can settle out of the injected slurry quickly, whereas lighter particles as well as a dense carrying fluid allow for a long transport into the reservoir. A numerical tool is therefore essential to take all these factors into account and to make robust predictions about the performance of the hydraulic stimulation. We present a novel computational application for coupled numerical simulation of hydraulic stimulation with concurrent injection of proppant in a fractured geothermal reservoir. This application is based on the open-source MOOSE framework that has been enriched with a set of equations to account for the circulation of proppant-laden slurries. It accounts for both the fluid and proppant components of the mixture, as well as particle-driven processes that include gravity settling, particle-particle interactions, and strong density and viscosity contrasts. A particular challenge is the mutual coupling with fracture mechanical processes in a propagating fracture using the FE code Defmod. Aperture and fluid pressure on one side and slurry density and viscosity changes on the other side interact and affect each other. Their basic understanding is therefore essential for the success of the stimulation. We compare our application to common numerical benchmark problems for both slurry flow and hydraulic stimulation.

15 GEOTHERMAL ENERGY↗

The transient performance of a two-phase fluid reservoir

Thermal control of future large, high power spacecraft will require a two-phase fluid central bus. The two-phase fluid reservoir is a critical component in the two-phase fluid bus. It both controls the saturation temperature and provides a space for volumetric changes. A dynamic reservoir simulation model does not currently exist, but it is needed to expedite efforts and reduce risk. During 1989 an effort was made to develop a simulation model of the transient performance of a two-phase fluid reservoir. As a beginning, a preliminary model was developed. It is based upon component mathematical models in lumped parametric form and build upon five component mathematical models for calculating dynamic responses of two-phase fluid reservoirs, primary feedback elements, controller commands, heater actuators, and reservoir heaters. As much as possible, the model took advantage of the available SINDA'85/FLUINT thermal/fluid integrator. Additional calculation logic and computer subroutines were developed to complete implementation of the model. The model is capable of simulating dynamic response of an equilibrium two-phase fluid reservoir. Modification of the model to include the liquid/vapor nonequilibrium is required for applications of the model to simulate performance of reservoir in which the liquid and vapor phases of the reservoir fluid are not in equilibrium. In addition, the model in its present form, needs to be refined in several respects. More empirical data are needed to guide the model development. The model may then be used to conduct a full parametric study of two-phase fluid reservoirs. More complexities in two-phaes flow regions in laboratory and flight conditions may have to be considered eventually if empirical data cannot be simulated satisfactorily. System with other components arrangement also need to be simulated if optimization is ever to be attained. The present model does, however, preliminarily demonstrates that such analyses are quite possible and offers a far less expensive method to understand the transient of a two-phase fluid reservoir system than a totally headware approach.

Chi, Joseph↗

Uncertainty Quantification in CO2 Trapping Mechanisms: A Case Study of PUNQ-S3 Reservoir Model Using Representative Geological Realizations and Unsupervised Machine Learning

Evaluating uncertainty in CO2 injection projections often requires numerous high-resolution geological realizations (GRs) which, although effective, are computationally demanding. This study proposes the use of representative geological realizations (RGRs) as an efficient approach to capture the uncertainty range of the full set while reducing computational costs. A predetermined number of RGRs is selected using an integrated unsupervised machine learning (UML) framework, which includes Euclidean distance measurement, multidimensional scaling (MDS), and a deterministic K-means (DK-means) clustering algorithm. In the context of the intricate 3D aquifer CO2 storage model, PUNQ-S3, these algorithms are utilized. The UML methodology selects five RGRs from a pool of 25 possibilities (20% of the total), taking into account the reservoir quality index (RQI) as a static parameter of the reservoir. To determine the credibility of these RGRs, their simulation results are scrutinized through the application of the Kolmogorov–Smirnov (KS) test, which analyzes the distribution of the output. In this assessment, 40 CO2 injection wells cover the entire reservoir alongside the full set. The end-point simulation results indicate that the CO2 structural, residual, and solubility trapping within the RGRs and full set follow the same distribution. Simulating five RGRs alongside the full set of 25 GRs over 200 years, involving 10 years of CO2 injection, reveals consistently similar trapping distribution patterns, with an average value of Dmax of 0.21 remaining lower than Dcritical (0.66). Using this methodology, computational expenses related to scenario testing and development planning for CO2 storage reservoirs in the presence of geological uncertainties can be substantially reduced.

Mahjour, Seyed Kourosh↗

Design and Modeling of a Prototype Floating Membrane Reservoir System Application for Pumped Storage Hydropower

Design and modeling were performed for a prototype floating membrane reservoir system for closed-loop pumped storage hydropower (PSH) application. Typically, new construction of PSH requires high up-front development costs and long investment return periods. The proposed floating membrane reservoir system innovative technology would eliminate the need for highly disruptive and costly reservoir construction. Such modular systems may ultimately provide reliable, flexible power generation and can be replicated multiple times to increase energy storage capacity. This paper documents the modeling response analysis completed to refine and validate the design prior to the testing of the prototype. Computational fluid dynamics modeling efforts were completed to assess hydrostatic and hydrodynamic forces acting on the reservoir for several deployment and alignment arrangements. The system stability was evaluated using material stress and frequency response analysis. The conclusions, based on hydrodynamic and structural response modeling, support a decision to move forward with construction, deployment, and testing of the innovative prototype floating reservoir system.

Hadjerioua, Boualem↗

Newton trust-region methods with primary variable switching for simulating high temperature multiphase porous media flow

Coupling multiphase flow with energy transport due to high temperature heat sources introduces significant new challenges since boiling and condensation processes can lead to dry-out conditions with subsequent re-wetting. The transition between two-phase and single-phase behavior can require changes to the primary dependent variables adding discontinuities as well as extending constitutive nonlinear relations to extreme physical conditions. Practical simulations of large-scale engineered domains lead to Jacobian systems with a very large number of unknowns that must be solved efficiently using iterative methods in parallel on high-performance computers. Performance assessment of potential nuclear repositories, carbon sequestration sites and geothermal reservoirs can require numerous Monte-Carlo simulations to explore uncertainty in material properties, boundary conditions, and failure scenarios. Due to the numerical challenges, standard NR iteration may not converge over the range of required simulations and require more sophisticated optimization method like trust-region. In this study, we use the open-source simulator PFLOTRAN for the important practical problem of the safety assessment of future nuclear waste repositories in the U.S. DOE geologic disposal safety assessment Framework. The simulator applies the PETSc parallel framework and a backward Euler, finite volume discretization. We demonstrate failure of the conventional NR method and the success of trust-region modifications to Newton’s method for a series of test problems of increasing complexity. Trust-region methods essentially modify the Newton step size and direction under some circumstances where the standard NR iteration can cause the solution to diverge or oscillate. Furthermore, we show how the Newton Trust-Region method can be adapted for Primary Variable Switching (PVS) when the multiphase state changes due to boiling or condensation. The simulations with high-temperature heat sources which led to extreme nonlinear processes with many state changes in the domain did not converge with NR, but they do complete successfully with the trust-region methods modified for PVS. This implementation effectively decreased weeks of simulation time needing manual adjustments to complete a simulation down to a day. Finally, we show the strong scalability of the methods on a single node and multiple nodes in an HPC cluster.

54 ENVIRONMENTAL SCIENCES↗

Hydropower flexibility valuation tool for flow requirement evaluation

Timing of generation is becoming more and more valuable. This creates greater potential tension between environmental and power system objectives since both systems require their own flow patterns. Identifying win–win outcomes in this context requires being able to discuss the value of flexibility across stakeholder groups. This research proposes a two-stage optimization method to understand hydropower flexibility to meet both environmental and power system requirements. The tool simulates the two-settlement market process in the U.S. by maximizing revenues from both the day-ahead and real-time markets, subject to plant operational limits, regulatory flow and ramping requirements, and uncertainties associated with water availability and market prices. The model is formulated as linear programming problems and solved using IBM ILOG CPLEX optimizer. By examining a range of flow requirements, ramping constraints, and storage capacities, the proposed tool shows how to make more informed decisions to weigh the cost of specific flow requirements in the context of the overall license requirements. Results from the case study show that revenue is more sensitive to the ramping constraints than the minimum flow constraints. We also demonstrate that removing flow constraints in a dry month increases monthly revenue by up to 118%, as opposed to only 1% in a wet month. In addition, our results suggest that using a learning-based water flow forecast results in an increase of monthly revenue up to 6.4% compared with persistence forecast.

13 HYDRO ENERGY↗

Play fairway analysis of geothermal resources across the state of Hawaii: 2. Resource probability mapping

We develop a new geostatistical method to combine evidence provided by diverse geological data sets and produce maps of geothermal resource probability. The application is to the State of Hawaii, and the data sets include the locations and ages of mapped volcanic centers, gravity and magnetotelluric measurements, groundwater temperature and geochemistry, ground surface deformation, seismicity, water table elevation, and groundwater recharge. Using the basic principles of Bayesian statistics, these data and expert knowledge about the effects and importance of the data are used to compute the probabilities of the primary resource qualities of elevated subsurface heat, reservoir permeability, and reservoir fluid content. The product of these marginal probabilities estimates the joint probability of all three qualities and hence the probability of a successful geothermal prospect at each map point. An analogous set of algorithms is used to quantify the confidence in the probability at each point. Not surprisingly, we find that successful geothermal prospects are most probable on the active volcanoes of Hawaii Island, including the area of Hawaii’s single geothermal energy plant. Probability decreases primarily with shield volcano age, being relatively moderate in select locations on Maui and Lanai, relatively low on Oahu, and minimal on Kauai. Future exploration efforts should consider these results as well as the practical, societal, and economic conditions that influence development viability. Here, the difficulties of interisland power transmission mean that even areas with moderate to low probabilities are worth investigating on islands with population centers.

15 GEOTHERMAL ENERGY↗

Multiple-compartment venting program

Computer program solves time-dependent energy and state equations for gas reservoirs, using the solutions of conductor conservation equations as mass and energy rate changes to reservoirs.

Leblanc, L. P.↗

The formation of stable pH gradients with weak monovalent buffers for isoelectric focusing in free solution

Two methods which utilize simple buffers for the generation of stable pH gradients (useful for preparative isoelectric focusing) are compared and contrasted. The first employs preformed gradients comprised of two simple buffers in density-stabilized free solution. The second method utilizes neutral membranes to isolate electrolyte reservoirs of constant composition from the separation column. It is shown by computer simulation that steady-state gradients can be formed at any pH range with any number of components in such a system.

Mosher, Richard A.↗

CELSS simulations for a lunar outpost

The paper describes a five-year simulation of two mission scenarios consisting of 14 different 'events' that could take place at a lunar outpost. The time-dependent status of the life support consumables was calculated in response to the two selected mission scenarios. This application demonstrates that complex sequences of events are reproducible for understanding of integrated mission operations. A Controlled Ecological Life Support System (CELSS) can regenerate air, water, and food from the wastes generated in the habitat and do so with safety and reliability. The CELSS Emulator is under development at the NASA's Johnson Space Center with a purpose of investigating computer simulations of integrated CELSS operations involving humans, plants, process machinery, and reservoirs. The Emulator Version 2.0 has been implemented to provide a mission-scenario-analysis capability. Thus, the future space exploration missions, lunar or Mars, can be analyzed by using 'events' to build mission timelines.

Cullingford, H. S.↗

Delta L: An Apparatus for Measuring Macromolecule Crystal Growth Rates in Microgravity

Strongly diffracting high quality macromolecule crystals of suitable volume are keenly sought for X-ray diffraction analysis so that high-resolution molecular structure data can be obtained. Such data is of tremendous value to medical research, agriculture and commercial biotechnology. In previous studies by many investigators microgravity has been reported in some instances to improve biological macromolecule X-ray crystal quality while little or no improvement was observed in other cases. A better understanding of processes effecting crystal quality improvement in microgravity will therefore be of great benefit in optimizing crystallization success in microgravity. In ground based research with the protein lysozyme we have previously shown that a population of crystals grown under the same solution conditions, exhibit a variation in X-ray diffraction properties (Judge et al., 1999). We have also observed that under the same solution conditions, individual crystals will grow at slightly different growth rates. This phenomenon is called growth rate dispersion. For small molecule materials growth rate dispersion has been directly related to crystal quality (Cunningham et al., 1991; Ristic et al., 1991). We therefore postulate that microgravity may act to improve crystal quality by reducing growth rate dispersion. If this is the case then as different, Materials exhibit different degrees of growth rate dispersion on the ground then growth rate dispersion could be used to screen which materials may benefit the most from microgravity crystallization. In order to assess this theory the Delta L hardware is being developed so that macromolecule crystal growth rates can be measured in microgravity. Crystal growth rate is defined as the change or delta in crystal size (defined as a characteristic length, L) over time; hence the name of the hardware. Delta L will consist of an optics, a fluids, and a data acquisition sub-assemblies. The optics assembly will consist of a video microscope camera mounted on three axis computer controlled translation stages. The fluids assembly consists of macromolecule and precipitant reservoirs, a temperature controlled growth cell and waste container, The data acquisition is achieved by using a frame-gabber, with images being stored on a hard drive. In operation, macromolecule and precipitant solution will be injected into the temperature controlled growth cell. As macromolecule crystals grow, the video microscope camera controlled by the translation stages, will be used to locate and record images of individual crystals, returning to the same crystals at specific time intervals. The images will be stored on the hard drive and used to calculate the crystal growth rate. To prevent vibrations interfering in the crystal growth rate measurements (Snell et al., 1997) Delta L will be used in connection with the Glovebox Integrated Microgravity Isolation Technology (g-LIMIT) inside the Microgravity Science Glovebox (MSG), onboard the International Space Station (ISS).

Judge, Russell A.↗

Bayesian Inversion of Seismic and Electromagnetic Data for Marine Gas Reservoir Characterization Using Multi-chain Markov Chain Monte Carlo Sampling

In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic amplitude versus angle (AVA) and controlled source electromagnetic (CSEM) data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo (MCMC) sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis (DREAM) and Adaptive Metropolis (AM) samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and CSEM data. The multi-chain MCMC is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic AVA and CSEM joint inversion provides better estimation of reservoir saturations than the seismic AVA-only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated – reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.

Ren, Huiying↗

Computed Tomography Scanning to Understand Micro-to-Macro Controls on Multiphase Flow during Geologic Carbon Storage; NETL-TRS-3-2017; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2017; p 24.

Evaluation of the fate and transport of carbon dioxide (CO 2 ) in deep reservoirs is crucial to the development of long-term geologic carbon sequestration (GCS) technologies. In this report, various studies using computed tomography (CT) scanning are utilized in conjunction with traditional flow tests to observe the multi-scale phenomena associated with CO 2 injection in geologic media. Pore scale analyses were performed to determine the infiltration characteristics of CO 2 into a brine saturated reservoir rock. Multiphase floods were performed to evaluate the saturation of CO 2 into a brine-saturated reservoir rock and determine how structural changes within the lithology affect such interactions. Additionally, CO 2 induced swelling of unconventional reservoir rock was evaluated with respect to reductions in fracture transmissivity due to matrix swelling. These studies are just a few examples of the benefits of multi-scale CT imaging in conjunction with traditional laboratory methodology to gain a better understanding of the interactions between CO 2 and the lithologies it interacts with during GCS.

58 GEOSCIENCES↗