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At least 811 records · Page 45

Ice in Channels and Ice-Rock Mixtures in Valleys on Mars: Did They Slide on Deformable Rubble Like Antarctic Ice Streams?

Recent studies of ice streams in Antarctica reveal a mechanism of basal motion that may apply to channels and valleys on Mars. The mechanism is sliding of the ice on deformable water-saturated till under high pore pressures. It has been suggested by Lucchitta that ice was present in outflow channels on Mars and gave them their distinctive morphology. This ice may have slid like Antarctic ice streams but on rubbly weathering products rather than till. However, to generate water under high pore pressures, elevated heatflow is needed to melt the base of the ice. Either volcanism or higher heatflow more than 2 b.y. ago could have raised the basal temperature. Regarding valley networks, higher heatflow 3 b.y. ago could have allowed sliding of ice-saturated overburden at a few hundred meters depth. If the original, pristine valleys were somewhat deeper than they are now, they could have formed by the same mechanism. Recent sounding of the seafloor in front of the Ross Ice Shelf in Antarctica reveals large persistent patterns of longitudinal megaflutes and drumlinoid forms, which bear remarkable resemblance to longitudinal grooves and highly elongated streamlined islands found on the floors of martian outflow channels. The flutes are interpreted to have formed at the base of ice streams during the last glacial advance. Additional similarities of Antarctic ice streams with martian outflow channels are apparent. Antarctic ice streams are 30 to 80 km wide and hundreds of kilometers long. Martian outflow channels have similar dimensions. Ice stream beds are below sea level. Carr determined that most common floor elevations of martian outflow channels lie below martian datum, which may have been close to or below past martian sea levels. The Antarctic ice stream bed gradient is flat and locally may go uphill, and surface slopes are exceptionally. Martian channels also have floor gradients that are shallow or go uphill locally and have low surface gradients. The depth to the bed in ice streams is 1 to 1.5 km. At bankful stage, the depth of the fluid in outflow channels was 1 to 2 km, according to the height of bordering scarps. The similarity between Antarctic ice streams and martian outflow channels suggests that ice may have flowed through and shaped the outflow channels, and that perhaps the mechanism of motion of Antarctic ice streams also operated in outflow channels. In addition, sliding on deformable rubble may explain the formation of small valley networks. The large Siple Coast Antarctic ice streams are thought to slide over longitudinally grooved, deforming till, where much of the movement is within the till. The till is saturated with water at high pore pressures that nearly supports all of the weight of the ice. The small differential between overburden pressure and pore pressure at the bed is more important than the volume of water, but water needs to be supplied to the till interface. For pore pressures to remain high, the ice streams have to act as a seal that blocks the flow of water through them, and the rock underneath has to be of low permeability to prevent the water from draining away.

Lucchitta, B. K.↗

Performance Evaluation of Engineered Geothermal Systems Using Discrete Fracture Network Simulations

Electrical power production from geothermal energy has a solid record of success for permeable reservoirs such as The Geysers in northern California and geothermal systems in Iceland and New Zealand, among other places. Such permeable reservoirs, however, represent only a small fraction of the available heat energy in the earth’s shallow crust. Most of the available energy resides in rocks with insufficient permeability and storage to produce commercial volumes of heated fluids.

15 GEOTHERMAL ENERGY↗

Scalable simulation of coupled adsorption and transport of methane in confined complex porous media with density preconditioning

The growing significance of shales and tight formations in the transition to less carbon-intensive and clean energy drives the research endeavor to understand the physics of gas flow within these systems. However, shales are composed of massively heterogeneous physical and chemical features. Most nano-sized pores connect to millimeter-scale fractures, leading to multiscale transport. These nano-scale pore throats demonstrate non-classical flow behavior, such as non-negligible slip velocities and adsorbed gas layers at the boundary. As a result, classical computational fluid dynamics models do not capture the physics. In this work, we develop a coupling scheme for the multiple-relaxation-time (MRT) lattice Boltzmann (LB) method that integrates the Peng-Robinson equation of state into a pseudo-potential interaction model to capture the physics of methane flow in irregular networks of channels that represent nano-scale porous media. We use atomistic simulations to calibrate and validate our model in slit nano-channels. We propose a preconditioning scheme to initialize the coupled transport and adsorption simulation of methane in complex porous media. The results of this implementation of LB agree with Direct Simulation Monte Carlo (DSMC) and Molecular Dynamics (MD) simulations. We then scale up the LB implementation through vectorization and indirect addressing. We parallelize it using Message Passing Interface (MPI) and OpenMP frameworks to simulate transport and adsorption in complex media with a million lattices. Additionally, we analyze the differences between coupled and transport-only simulations in two case studies and show that considering phase behavior, i.e., adsorption, can significantly change the flow behavior. This work constitutes an important step towards bridging the gap between molecular flow and system-scale behavior of complex disordered porous media.

42 ENGINEERING↗

Distributed deep reinforcement learning for simulation control

Abstract Several applications in the scientific simulation of physical systems can be formulated as control/optimization problems. The computational models for such systems generally contain hyperparameters, which control solution fidelity and computational expense. The tuning of these parameters is non-trivial and the general approach is to manually ‘spot-check’ for good combinations. This is because optimal hyperparameter configuration search becomes intractable when the parameter space is large and when they may vary dynamically. To address this issue, we present a framework based on deep reinforcement learning (RL) to train a deep neural network agent that controls a model solve by varying parameters dynamically. First, we validate our RL framework for the problem of controlling chaos in chaotic systems by dynamically changing the parameters of the system. Subsequently, we illustrate the capabilities of our framework for accelerating the convergence of a steady-state computational fluid dynamics solver by automatically adjusting the relaxation factors of the discretized Navier–Stokes equations during run-time. The results indicate that the run-time control of the relaxation factors by the learned policy leads to a significant reduction in the number of iterations for convergence compared to the random selection of the relaxation factors. Our results point to potential benefits for learning adaptive hyperparameter learning strategies across different geometries and boundary conditions with implications for reduced computational campaign expenses 4 4 Data and codes available at https://github.com/Romit-Maulik/PAR-RL . .

42 ENGINEERING↗

Chemical sensing and imaging in microfluidic pore network structures relevant to natural carbon cycling and industrial carbon sequestration

Energy and climate change represent significant factors in global security. Atmospheric carbon dioxide levels, while global in scope, are influenced by pore-scale phenomena in the subsurface. We are developing tools to visualize and investigate processes in pore network microfluidic structures with transparent covers as representations of normally-opaque porous media. In situ fluorescent oxygen sensing methods and fluorescent cellulosic materials are being used to investigate processes related to terrestrial carbon cycling involving cellulytic respiring microorganisms. These structures also enable visualization of water displacement from pore spaces by hydrophobic fluids, including carbon dioxide, in studies related to carbon sequestration.

carbon sequestration↗

Natural Tracers and Multi-Scale Assessment of Caprock Sealing Behavior: A Case Study of the Kirtland Formation, San Juan Basin

The assessment of caprocks for geologic CO{sub 2} storage is a multi-scale endeavor. Investigation of a regional caprock - the Kirtland Formation, San Juan Basin, USA - at the pore-network scale indicates high capillary sealing capacity and low permeabilities. Core and wellscale data, however, indicate a potential seal bypass system as evidenced by multiple mineralized fractures and methane gas saturations within the caprock. Our interpretation of {sup 4}He concentrations, measured at the top and bottom of the caprock, suggests low fluid fluxes through the caprock: (1) Of the total {sup 4}He produced in situ (i.e., at the locations of sampling) by uranium and thorium decay since deposition of the Kirtland Formation, a large portion still resides in the pore fluids. (2) Simple advection-only and advection-diffusion models, using the measured {sup 4}He concentrations, indicate low permeability ({approx}10-20 m{sup 2} or lower) for the thickness of the Kirtland Formation. These findings, however, do not guarantee the lack of a large-scale bypass system. The measured data, located near the boundary conditions of the models (i.e., the overlying and underlying aquifers), limit our testing of conceptual models and the sensitivity of model parameterization. Thus, we suggest approaches for future studies to better assess the presence or lack of a seal bypass system at this particular site and for other sites in general.

03 NATURAL GAS↗

A Complete Machine-Learning-Based Workflow to Illuminate Earthquake Processes

Under this grant we developed, tested, and made available, machine learning models to improve the tasks in the earthquake monitoring workflow (Figure 1). We implemented these models as a part of an end-to-end workflow for seismic network processing and demonstrated, in a variety of settings, that these methods generalize and that they result in dramatically more comprehensive earthquake catalogs. These catalogs illuminate earthquake processes in detail and to an extent that had previously not been possible, and they do so for both tectonic seismicity and seismicity induced by fluid injection related to unconventional hydrocarbon development. This report summarizes the results from the 15 publications that resulted from this grant. Those contributes are divided into: (1) the development of specific tasks related to monitoring (7 publications), (2) the organization of those tasks into workflows for seismic monitoring (2 publications), and (3) applications of those workflows to data (6 publications).

58 GEOSCIENCES↗

Feasibility study for a numerical aerodynamic simulation facility. Volume 2: Hardware specifications/descriptions

An FMP (Flow Model Processor) was designed for use in the Numerical Aerodynamic Simulation Facility (NASF). The NASF was developed to simulate fluid flow over three-dimensional bodies in wind tunnel environments and in free space. The facility is applicable to studying aerodynamic and aircraft body designs. The following general topics are discussed in this volume: (1) FMP functional computer specifications; (2) FMP instruction specification; (3) standard product system components; (4) loosely coupled network (LCN) specifications/description; and (5) three appendices: performance of trunk allocation contention elimination (trace) method, LCN channel protocol and proposed LCN unified second level protocol.

Green, F. M.↗

Visualization of fluid dynamics at NASA Ames

The hardware and software currently used for visualization of fluid dynamics at NASA Ames is described. The software includes programs to create scenes (for example particle traces representing the flow over an aircraft), programs to interactively view the scenes, and programs to control the creation of video tapes and 16mm movies. The hardware includes high performance graphics workstations, a high speed network, digital video equipment, and film recorders.

Watson, Val↗

A Parallel Multigrid Solver for Viscous Flows on Anisotropic Structured Grids

This paper presents an efficient parallel multigrid solver for speeding up the computation of a 3-D model that treats the flow of a viscous fluid over a flat plate. The main interest of this simulation lies in exhibiting some basic difficulties that prevent optimal multigrid efficiencies from being achieved. As the computing platform, we have used Coral, a Beowulf-class system based on Intel Pentium processors and equipped with GigaNet cLAN and switched Fast Ethernet networks. Our study not only examines the scalability of the solver but also includes a performance evaluation of Coral where the investigated solver has been used to compare several of its design choices, namely, the interconnection network (GigaNet versus switched Fast-Ethernet) and the node configuration (dual nodes versus single nodes). As a reference, the performance results have been compared with those obtained with the NAS-MG benchmark.

Prieto, Manuel↗

Nanopore Confinement of C-H-O Mixed-Volatile Fluids Relevant to Subsurface Energy Systems

The overarching goal of OU’s contribution to the project was to use novel computational approaches to quantify the effect of variable nanopore features (pore size, volume, topology, and chemistry) and the presence of water or salt solutions on the sorption and transport of carbon-bearing fluids. To achieve this goal OU collaborators tested test two related hypotheses: • The transport of water and aqueous electrolytes in nanopores is controlled by pore size, pore wall composition, and the type of salt – structure-maker (e.g., CaCl 2 ) versus structure-breaker (e.g., NaCl) that affect the hydrogen-bonding network. • The structure, solubility, and transport of carbon-bearing molecules in water or aqueous electrolyte-filled nanopores are controlled by the substrate type including degree of hydration, and pore features, and regulated by the hydration structure of the guest molecules.

58 GEOSCIENCES↗

CFD-trained ANN Model for Approximating Near-occupant Condition in Real-time Simulations

The main drawback of Computational Fluid Dynamics (CFD) simulations has been the time and resource consuming nature which is not suitable for real-time applications. In this work, we first generated numerous CFD models of a given indoor space to obtain airspeed, temperature, and mean radiant temperature near an occupant as training data. Several artificial neural networks (ANN) models were trained using this CFD simulated data to approximate near real-time environmental conditions for a given occupant. This trained ANN model approach is a part of a real-time simulation of building operations using a combination of software and real hardware (HVAC equipment) approaches. The preliminary results suggest that the CFD- generated training data and the trained ANN model can accurately approximate such conditions in a real-time application, a method that has great potential in building simulation and building digital twin areas of research.

Zhang, Yun↗

Combined Structural Analysis of Core and Image Log of TGH 76-31 South East of Mt Baker, Washington State

Despite active volcanism, few geothermal energy resources have been developed in the Cascades Range. Temperature Gradient Hole 76-31 was drilled to ~440 m measured depth to probe for zones where fractures provide fluid conduits that transport deep volcanic heat to shallow depths that could support baseload, carbon neutral electrical generation. These zones were predicted by a Play Fairway assessment (PFA) of resource potential along a zone 11 km west-southwest of the summit of Mount Baker Volcano. Rock core, temperature logs, and an acoustic image log were obtained. By comparison to outcrops, the core has been initially interpreted as the Chilliwack group comprised of partially metamorphosed basaltic to andesitic volcanics. Core mapping reveals complex, steeply dipping networks of fractures and brecciation along slickensided strike slip faults; clay alteration is common in many of these structures. The majority of fractures are thoroughly healed by layers of chlorite and calcite; preservation of pyrite indicates anoxic conditions. The majority of fracture porosity resides in very dense fractures a few centimeters or less in length. The image log provides good insights into attitude of fractures that fully transect the core, but generally underestimates fracture density. The combination of complex, non-planar fracture zones containing many short fractures and healing promote misinterpretation of natural fracture attitude and density in the image log. The healing and anoxic minerals are consistent with the conductive temperature gradient measured in the well below a shallow isothermal zone, although, several fractures are open or only partially healed and resulted in fluid entries into the well. Here, the equilibrated measured temperature gradient of 64ºC/km and calculated heat flow of 145 mW/m2 is more than twice the regional average, indicating local influence of the Mt Baker magmatic system at the Little Park Creek TGH site.

Cascades↗

Parallel and Distributed Computational Fluid Dynamics: Experimental Results and Challenges

This paper describes several results of parallel and distributed computing using a large scale production flow solver program. A coarse grained parallelization based on clustering of discretization grids combined with partitioning of large grids for load balancing is presented. An assessment is given of its performance on distributed and distributed-shared memory platforms using large scale scientific problems. An experiment with this solver, adapted to a Wide Area Network execution environment is presented. We also give a comparative performance assessment of computation and communication times on both the tightly and loosely-coupled machines.

Djomehri, Mohammad Jahed↗

Analysis of the Monitoring Network at the Salmon, Mississippi, Site

The Salmon site in southern Mississippi was the location of two underground nuclear tests and two methane-oxygen gas explosion tests conducted in the Tatum Salt Dome at a depth of 2,715 feet below ground surface. The U.S. Atomic Energy Commission (a predecessor agency of the U.S. Department of Energy [DOE]) and the U.S. Department of Defense jointly conducted the tests between 1964 and 1970. The testing operations resulted in surface contamination at multiple locations on the site and contamination of shallow aquifers. No radionuclides from the nuclear tests were released to the surface or to groundwater, although radionuclide-contaminated drill cuttings were brought to the surface during re-entry drilling. Drilling operations generated the largest single volume of waste materials, including radionuclide-contaminated drill cuttings and drilling fluids. Nonradioactive wastes were also generated as part of the testing operations. Site cleanup and decommissioning began in 1971 and officially ended in 1972. DOE conducted additional site characterization between 1992 and 1999. The historical investigations have provided a reasonable understanding of current surface and shallow subsurface conditions at the site, although some additional investigation is desirable. For example, additional hydrologic data would improve confidence in assigning groundwater gradients and flow directions in the aquifers. The U.S. Environmental Protection Agency monitored groundwater at the site as part of its Long-Term Hydrologic Monitoring Program from 1972 through 2007, when DOE's Office of Legacy Management (LM) assumed responsibility for site monitoring. The current monitoring network consists of 28 monitoring wells and 11 surface water locations. Multiple aquifers which underlie the site are monitored. The current analyte list includes metals, radionuclides, and volatile organic compounds (VOCs).

54 ENVIRONMENTAL SCIENCES↗

Glass–water interaction: Effect of high-valence cations on glass structure and chemical durability

Borosilicate glass is a durable solid, but it dissolves when in contact with aqueous fluids. The dissolution mechanism, which involves a variety of sequential reactions that occur at the solid-fluid interface, has important implications for the corrosion resistance of industrial and nuclear waste glasses. In this study, spectroscopic measurements, dissolution experiments, and Monte Carlo simulations were performed to investigate the effect of high–valence cations (HVC) on the mechanisms of glass dissolution under dilute and near-saturated conditions. Raman and NMR spectroscopy were used to determine the structural changes that occur in glass, specifically network formers (e.g., Al, Si, and B), with the addition of the HVC element hafnium in the Na2O–Al2O3–B2O3–HfO2–SiO2 system (e.g., Na/[Al+B] = 1.0 and HfO2/SiO2 from 0.0 to 0.42). Spectroscopic measurements revealed that increasing hafnium content decreases N4 (tetrahedral boron/total boron) and increases the amount of Si—O—Hf moieties in the glass. Results from flow–through experiments conducted under dilute and near–saturated conditions show a decrease of approximately 100× or more in the dissolution rate over the series from 0 to 20 mol% HfO2. Comparing the average steady-state rates obtained under dilute conditions to the rates obtained for near-saturated conditions reveals a divergence in the magnitude between the average steady state rates measured in these different conditions. The reason for this divergence was investigated more thoroughly using Monte Carlo simulations. Simulations indicate that the divergence in glass dissolution behavior under dilute and near-saturated conditions result from the stronger binding of Si sites that deposit on the surface from the influent when Hf is present in the glass. As a result, the residence time at the glass surface of these newly-formed Si sites is longer in the presence of Hf, which increases the density of anchor sites from which altered layers with higher Si densities can form. These results illustrate the importance of understanding solid–water/solid-fluid interactions by linking macroscopic reaction kinetics to nanometer scale interfacial processes.

Environmental Molecular Sciences Laboratory↗

Learning intermolecular forces at liquid–vapor interfaces

By adopting a perspective informed by contemporary liquid-state theory, we consider how to train an artificial neural network potential to describe inhomogeneous, disordered systems. Here, we find that neural network potentials based on local representations of atomic environments are capable of describing some properties of liquid-vapor interfaces but typically fail for properties that depend on unbalanced long-ranged interactions that build up in the presence of broken translation symmetry. These same interactions cancel in the translationally invariant bulk, allowing local neural network potentials to describe bulk properties correctly. By incorporating explicit models of the slowly varying long-ranged interactions and training neural networks only on the short-ranged components, we can arrive at potentials that robustly recover interfacial properties. We find that local neural network models can sometimes approximate a local molecular field potential to correct for the truncated interactions, but this behavior is variable and hard to learn. Generally, we find that models with explicit electrostatics are easier to train and have higher accuracy. We demonstrate this perspective in a simple model of an asymmetric dipolar fluid, where the exact long-ranged interaction is known, and in an ab initio water model, where it is approximated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗