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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Radioactive Cleaning Robot

Here at Fermi National Accelerator Laboratory, particle accelerators are constantly running, giving off excess radioactive dust. This dust can be extremely harmful to people and the environment, posing numerous issues. The goal of this project is to conceptualize an automated cleaning solution. With this main goal in mind, the project started with a brainstorming session. The main concept relied on the use of a powder distributing system paired with a vacuum to easily attract and trap the dust. From this main concept, multiple sketches were produced, showing a robot with pieced-together systems. With the initial idea down, each subsystem could be brought further with the inner workings being sketched out. After sketches and proof of concept were polished, the next step was to begin 3D modeling, using NX, to bring life into the sketches. With every day came new ideas, modifying the previous sketches and models as necessary. Soon after the bigger structures were fleshed out, the focus could be shifted onto the less pressing subsystems. Adding a conveyor belt and spinning brush attachment to the powder hopper allowed for more even powder distribution. Along with that, the addition of spring-loaded brushes on the vacuum nozzle ensures constant dust agitation, improving overall functionality. A few other quality of life improvements, such as a removable dust reservoir with a ramp gave a push towards real life functionality. After considering the logistics of this robot functioning in real-life, pressure plates were provided to stop the robot from crashing into its surroundings. Having all of the individual models lead to an overall assembly. Making this robot programmable allowed for this project to meet the design requirements, providing a solution to the previous dilemma.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Multilevel Spectral Coarsening for Graph Laplacian Problems with Application to Reservoir Simulation

We extend previously developed two-level coarsening procedures for graph Laplacian problems written in a mixed saddle point form to the fully recursive multilevel case. The resulting hierarchy of discretizations gives rise to a hierarchy of upscaled models, in the sense that they provide approximation in the natural norms (in the mixed setting). This property enables us to utilize them in three applications: (i) as an accurate reduced model, (ii) as a tool in multilevel Monte Carlo simulations (in application to finite volume discretizations), and (iii) for providing a sequence of nonlinear operators in a full approximation scheme for solving nonlinear pressure equations discretized by the conservative two-point flux approximation. Finally, we illustrate the potential of the proposed multilevel technique in all three applications on a number of popular benchmark problems used in reservoir simulation.

multilevel Monte Carlo↗
DOE OSTI2024

Pore-scale visualization of natural hydrate-bearing sediments

Accurate modeling of gas hydrate reservoir productivity and geomechanical risks associated with subsurface dissociation of natural gas hydrates (NGH) requires the determination of model parameters through physical testing on natural hydrate-bearing sediments (HBS). This involves investigating the hydro-mechanical behavior of undisturbed hydrate samples from nature under in situ conditions using pressure core characterization and analysis, which provides a unique opportunity for research. By employing state-of-the-art micro computed tomography imagery on cryogenically preserved, hydrate-bearing sediment samples, we can determine hydrate saturation as well as permeability with and without the presence of hydrates in the sediment. Furthermore, utilizing a machine learning based image segmentation technique, it is possible to extract pore space and grain information. Subsections of the entire image volume were used to determine anisotropic permeabilities using a finite-difference method Stokes solver (FDMSS). Additionally, permeability measurements on whole pressure and temperature preserved hydrate-bearing core were analyzed by utilizing the National Energy Technology Laboratory’s (NETL) Pressure Core Characterization and X-ray CT Visualization Tool (PCXT) to manipulate, cut, and analyze pressure preserved sediment. Permeabilities were measured under a broad range of vertical stress states to simulate expected pressure changes during production scenarios, and the results show that permeabilities derived from images are in agreement with those from traditional core derived experiments. The collected stress-dependent permeability, permeability anisotropy, and corresponding gas hydrate saturations provide valuable input into numerical simulations of reservoir productivity. These properties have been proven to be key parameters determining a long-term reservoir response under depressurization.

Liu, Mengwei [Oak Ridge Institute for Science and ↗
DOE OSTI2021

Operation of Natural Gas Pipeline Networks With Storage Under Transient Flow Conditions

Here, we formulate a nonlinear optimal control problem for intraday operation of a natural gas pipeline network that includes storage reservoirs. The dynamics of compressible gas flow through pipes, compressors, reservoirs, and wells are considered. In particular, a reservoir is modeled as a rigid, hollow container that stores gas under isothermal conditions and uniform density, and a well is modeled as a vertical pipe. For each pipe, flow dynamics are described by a coupled partial differential equation (PDE) system in density and mass flux variables, with momentum dissipation modeled using the Darcy–Wiesbach friction approximation. Compressors are modeled as scaling up the pressure of gas between the inlet and outlet. The governing equations for all network components are spatially discretized and assembled into a nonlinear differential-algebraic equation (DAE) system, which synthesizes above-ground pipeline and subsurface reservoir dynamics into a single reduced-order model. We seek to maximize an objective function that quantifies economic profit and network efficiency subject to the flow equations and inequalities that represent operating limitations. The problem is solved using a primal–dual interior point solver, and the solutions are validated in computational experiments and simulations on several pipeline test networks to demonstrate the effectiveness of the proposed methodology.

03 NATURAL GAS↗
DOE OSTI2024

Active Reservoir Management Engineering and Evaluation Summary – Brine Extraction and Storage Test Phase II Final Report – Volumes 1-3

The Energy & Environmental Research Center (EERC) conducted a multiyear program over two phases to perform a field study of the potential efficacy of formation water extraction during carbon dioxide (CO 2 ) injection for CO 2 storage as a means of improving efficiency and/or effectiveness. Phase I was a 2-year study on potential methodologies for a field study of pressure management, culminating in site selection and experimental and site design. Phase II was a 7-year effort that involved constructing site facilities, conducting experiments, and evaluating collected field data. The experimental portion was split into two collaborative components, one for the active reservoir management (ARM) experiment and a second component to host and demonstrate potential water treatment technologies appropriate for high-saline brine at the project site. The results of the overall project are expected to benefit future saline storage projects through validation of techniques that may reduce stress on sealing formations, increase storage capacity, and reduce area of review. The following report focuses on the Phase II ARM experimental implementation and results. A second companion report summarizes the results of the high-saline brine demonstrations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Coupled Investigation of Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior (Final Technical Report)

Enhanced Geothermal Systems (EGS) produce clean energy by circulating fluid through hot rock deep underground and bringing that heat to the surface to generate electricity. For this process to work reliably, fluids must be able to move efficiently through networks of natural or engineered fractures in the rock. Enhancing and maintaining subsurface permeability over time is essential for sustainable energy production. However, fluid injection changes the underground temperature, pressure, rock stress, and chemistry, which can alter permeability and sometimes trigger earthquakes. Predicting these interconnected processes remains a key challenge. To address this, we combined high-temperature laboratory experiments with high-fidelity simulations to better understand how fractures in geothermal reservoirs evolve over time. Our experiments measured how fractures respond to stress, slip, slip rate, and chemical reactions under geothermal conditions. These data were integrated into coupled thermal-hydrological-mechanical-chemical and earthquake (THMC+E) models tailored to the Utah FORGE site. The validated modeling framework improves predictions of reservoir performance and seismic response and helps guide operational decisions. This work reduces technical risk and strengthens the scientific foundation needed to make geothermal energy a reliable and scalable clean energy resource.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Optimal carbon storage reservoir management through deep reinforcement learning

Model-based optimization plays a central role in energy system design and management. The complexity and high-dimensionality of many process-level models, especially those used for geosystem energy exploration and utilization, often lead to formidable computational costs when the dimension of decision space is also large. This work adopts elements of recently advanced deep learning techniques to solve a sequential decision-making problem in applied geosystem management. Specifically, a deep reinforcement learning framework was formed for optimal multiperiod planning, in which a deep Q-learning network (DQN) agent was trained to maximize rewards by learning from high-dimensional inputs and from exploitation of its past experiences. To expedite computation, deep multitask learning was used to approximate high-dimensional, multistate transition functions. Both DQN and deep multitask learning are pattern based. As a demonstration, the framework was applied to optimal carbon sequestration reservoir planning using two different types of management strategies: monitoring only and brine extraction. Both strategies are designed to mitigate potential risks due to pressure buildup. Results show that the DQN agent can identify the optimal policies to maximize the reward for given risk and cost constraints. Finally, experiments also show that knowledge the agent gained from interacting with one environment is largely preserved when deploying the same agent in other similar environments.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Microseismic Monitoring Study to Assess the Potential for Induced Seismicity in a Depleted Oil Field in Northern Michigan

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. Microseismic monitoring is the passive recording of very small-scale seismic energy events occurring underground. Microseismic monitoring has been proposed as a monitoring technology for CCUS sites to monitor fracturing before it becomes sufficiently extensive to cause leakage. This study aimed to determine if CO 2 injection into the Niagaran pinnacle reefs in northern Michigan is likely to generate microseismic events. The Niagaran reefs are relatively small, closed features making it possible to observe a large pressure increase by injecting a relatively small volume of CO 2 . In this study, two microseismic monitoring events were conducted 39 months apart during re-pressurization of the Dover 33 reef to evaluate the potential for CO 2 -injection induced seismicity in Silurian-age carbonate reef depleted oil reservoirs.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

A quantitative risk assessment framework for fault reactivation in underground hydrogen storage: Coupled simulation and deep learning approach

Underground hydrogen storage (UHS) is emerging as a critical solution for large-scale energy storage. However, like all subsurface fluid injection activities, UHS poses the risk of injection-induced fault reactivation. Accurate risk assessment is essential to ensuring the safety and efficiency of UHS operations. This study presents the development of deep-learning surrogate models for fault reactivation prediction in UHS, trained on a comprehensive database of fully coupled fluid flow-geomechanics simulations. Our findings reveal that analytical models often yield unreliable estimates, with errors up to 54% in the allowable injection pressure, potentially leading to a 40% reduction in UHS operational capacity. The developed surrogate models were incorporated into a quantitative risk assessment (QRA) framework, enabling probabilistic evaluation of fault reactivation risk while accounting for uncertainties in the input variables. Site-specific features, such as horizontal stress gradients, fault’s dip and strike angles, and operational parameters like bottom-hole injection pressure and well-fault distance, were identified as the primary drivers of fault reactivation across various stress regimes. Whereas other hydraulic, geological, and poroelastic reservoir properties were found to have a secondary impact. Notably, we observed that the risk of fault reactivation for a critically oriented fault with a static friction coefficient greater than 0.55 remains below 10% in a normal faulting stress regime. However, the risk significantly increases as the stress regime transitions from normal to strike-slip and ultimately to reverse faulting conditions. These findings underscore the importance of rigorous site characterization and comprehensive QRA evaluations to optimize UHS performance and minimize geomechanical risks.

25 ENERGY STORAGE↗
DOE OSTI2020

Numerical Simulations of Gas Production from Gas Hydrate Reservoirs at the Prudhoe Bay Unit 7-11-12 Pad on Alaska North Slope

In December 2018, a partnership between the U.S. Department of Energy National Energy Technology Laboratory (DOE NETL), the Japan Oil, Gas and Metals National Corporation (JOGMEC), and the U.S. Geological Survey (USGS) successfully drilled and logged the Hydrate-01 Stratigraphic Test Well (STW) in the greater Prudhoe Bay oil field on Alaska North Slope. The logging-while-drilling (LWD) data confirmed the presence of gas hydrate-bearing reservoirs within two sand reservoirs (Unit B and Unit D) that are suitable targets for future testing. The interpreted log data and core sample measurements were used to create reservoir models for the Prudhoe Bay Unit (PBU) Kuparuk 7-11-12 Site. The models combine both gas hydrate-bearing sections in Unit B and Unit D together with the intermediate Unit C and over- and underburden sands and shales. The vertical heterogeneity in porosity, gas hydrate saturation, and permeability distributions for reservoir and non-reservoir units was implemented using fine mesh discretization. The depressurization method was applied to Unit B to induce gas hydrate destabilization at constant bottom hole pressure (BHP) values. The results of the numerical simulations support the development of production scenarios, well design, surface facilities, and field test procedures with the main goal to perform efficient and safe scientific production testing. Project results contribute to the knowledge base of permafrost-associated gas hydrate accumulations as a future energy source.

Myshakin, Evgeniy↗
DOE OSTI2022

Simulation of 15% and 50% Thermal Power Dispatch to an Industrial Facility Using a Flexible Generic Full-Scope Pressurized Water Reactor Plant Simulator

Nuclear power plants in the United States are increasingly challenged to compete in wholesale electricity markets due to the low electricity costs and increasingly dynamic grid conditions from competing generation sources. An alternative market for nuclear power is industrial facilities that can use the thermal and/or electrical power generated by a nuclear power plant to offset the economic losses incurred by electricity market challenges. A generic pressurized water reactor (PWR) simulator was used to show the results of a basic design for a generic thermal power extraction system and tests were run using a set of procedures to show what happens when a nuclear power plant transitions from full electrical power dispatch to 15% and 50% thermal power dispatch. This type of operation leads to losses in turbine performance efficiency due to the deviation from the design operating point, but because the thermal power is also used by the industry load without conversion losses, the combined thermal efficiency of the PWR increases. For the 15% case, the thermal efficiency increased from 32% to 41.9%, while for the 50% case, the efficiency increased up to 60.1%. In addition, for 50% thermal power dispatch, the power dissipated by the condenser decreased from approximately 2000 to approximately 1300 MW (thermal), indicating a substantially diminished impact on the environment in terms of releasing heat into the cooling water reservoir.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Modeling Study of Reduced Tubing Size Effects on Flow in Depleted Reservoir Natural Gas Storage Wells

This report explores the effects of tubing size reductions on natural gas flow from representative depleted reservoir underground storage wells and fields using basic models for coupled reservoir and pipe flow. This work was motivated by interest at the U.S. Department of Transportation, Pipeline and Hazardous Materials Safety Administration, in evaluating the effects of tubing and packer as a potential safety upgrade to implement double-barrier systems to existing underground natural gas storage wells. Reservoir and well flow models were developed from widely accepted industry equations, verified against a commercial process simulator model, and validated against field data. The study utilized U.S. operator survey data to provide context and assure that modeling parameters including aver age deliverability rates for wells and fields, operating pressures, well depths, and storage capacities were all carefully considered to keep the modeling relevant to the known range of U.S. operations. The models generally found that wells and fields with inherently low deliverability were relatively insensitive to reductions in tubing diameter, primarily because the hydraulics in those cases were controlled by reservoir properties. For the high-producing wells and fields, the models found that reducing tubing diameter could produce significant reductions in deliverability, both at the field- and well-level. When put into context with occurrence data regarding average deliverability of fields and wells, it appears that most wells and most fields across the U.S. would experience deliverability reductions on the low end of what was simulated here, generally below 20%. For fields with moderate to high deliverability, reductions were generally larger, and could reach as high as 60% for the highest-producing wells and fields.

03 NATURAL GAS↗
DOE OSTI2021

A Type–Curve Approach for Evaluating Aquifer Properties by Interpreting Shallow Strain Measured During Well Tests

Strains occur at shallow depths in response to pressure changes during well tests in an underlying aquifer, and recent developments in instrumentation have made it feasible to measure essentially the full strain tensor. Simulations using poroelastic analyses indicate that shallow normal strains are approximately proportional to the logarithm of time when a well is injecting into or pumping from a deep aquifer or reservoir. The drawdown is also a linear function of log time, as shown by the classic Cooper-Jacob type-curve analysis. The time when the semilog straight line intercepts the zero-strain axis is similar to the time determined from the Cooper-Jacob pressure analysis, and it can be used to estimate hydraulic diffusivity, suggesting that horizontal strain data can be used directly to estimate aquifer properties. This approach was validated using measurements from shallow (30-m deep) borehole strainmeters during an injection test at a 530-m-deep sandstone aquifer/reservoir in Oklahoma. The results show intercept times for the shallow normal strain data are essentially the same as for deep pressure data from an equivalent radial distance. The slopes of the semilog plots of the pressure and the strain increase at the same time, suggesting that they both respond to a lateral aquifer boundary. Significantly, though, strain was measured at shallow depths while the pressure data were measured at 530-m depth. This suggests that strain data from shallow depths could be an effective way to improve the characterization of an underlying aquifer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Mantle–melt partitioning of the highly siderophile elements: New results and application to Mars

Trace elements and extant and extinct isotopic attributes in Martian meteorites have been used to argue that Mars accreted quickly, differentiated into core and mantle, and established several mantle reservoirs, possibly within 10 Ma of T0. The partitioning of trace elements in the deep mantle has been relatively unstudied, despite the need for such knowledge in understanding magma ocean crystallization and the origin of depleted and enriched mantle reservoirs. The siderophile element composition of the Martian mantle and lithophile isotopic systems such as Sr, Hf, and Nd are thought to record evidence for early metal–silicate equilibrium and deep magma ocean at an intermediate depth and pressure of 800 km or 14 GPa. We have carried out experiments across this pressure range to better understand the mineral/melt partitioning of a wide range of elements. These new data are used to evaluate differentiation models for Mars and to help interpret the available isotopic data. The relatively incompatible nature of Re compared to mildly compatible Os means that the crystallization of a deep magma ocean will lead to residual liquids with superchondritic Re/Os, and solids with subchondritic Re/Os. Such material available in the mantle could be the source of enriched isotopic reservoir that produced shergottites with +γOs values. Slightly subchondritic Re/Os ratios in the crystallizing solids would provide a reservoir that could produce -γOs values. Finally, melting of mixtures of these two enriched and depleted endmembers could explain the Nd-Os isotopic correlations and systematics of shergottites.

58 GEOSCIENCES↗
DOE OSTI2026

Innovations in underground hydrogen storage with multiphysics simulations, optimization, and monitoring: A review

Underground Hydrogen Storage (UHS) is a promising solution for large-scale energy storage and a critical component in advancing low-carbon energy system. Ensuring the safety and efficiency of UHS necessitates a comprehensive understanding of multiphysical interactions driven by cyclic pore fluid pressure fluctuations and coupled physicochemical processes. Here, this review examines the key geomechanical responses in UHS, including rock property variations under cyclic loading, fracture evolution and propagation, reservoir stress sensitivity, and fault stability. It also explores the impact of geochemical and microbial reactions on geomechanical characteristics. We provide an in-depth analysis of Thermal-Hydraulic-Mechanical-Chemical (THMC) coupled numerical simulations, highlighting their potential for future multi-scale modeling. Limitations of current machine learning (ML) approaches in addressing UHS challenges are highlighted, emphasizing the need for innovative ML-based methodologies. Operational strategies for hydrogen injection and production are reviewed, focusing on safety, efficiency, and economic viability. The necessity for multi-objective optimization (MOO) to balance storage efficiency, risk mitigation, and cost-effectiveness is also discussed. Current monitoring technologies are evaluated to ensure safe and efficient UHS operations. Finally, this review identifies critical knowledge gaps and underscores the importance of advancing geomechanical understanding under multiphysics-coupling. We highlight the need for ML-driven multiphysics theories, enhanced modeling techniques, and robust optimization strategies to improve UHS performance. This study serves as a comprehensive reference for future research and the large-scale implementation of UHS systems.

25 ENERGY STORAGE↗
DOE OSTI2023

Assessing reservoir performance for geologic carbon sequestration in offshore saline reservoirs

Carbon capture and storage (CCS) is a technological strategy to reduce CO 2 emissions from hydrocarbon-based energy production and non-energy industrial emitters, like fertilizer and cement production. To expand the geographic opportunities for CCS, offshore geologic settings are increasingly considered for saline CO 2 storage, particularly where legacy oil and gas infrastructure may be repurposed for CO 2 transport and injection. In this context, the Gulf of Mexico (GoM), United States (U.S.), may offer tremendous opportunity for CCS because the surrounding states are among the largest CO 2 producers in the U.S. and there has been extensive oil and gas development over the last half century. Nevertheless, there remains significant uncertainty in how GoM reservoir/seal systems will respond to industrial-scale CO 2 injections, particularly in the context of meso-scale (1–10s of meters) permeability variations that are difficult to identify prior to injection. Such permeability variations can have significant impacts on CO 2 migration and fluid pressure propagation, both of which govern the overall effectiveness of the CCS project. This research uses ensemble simulation methods to quantify the influence of spatially variable and a priori unknown permeability fields on CO 2 plume development and fluid pressure propagation when CO 2 is injected at 1 MMt per year for ten years. Results show a number of characteristic patterns that reveal the substantial influence of both near- and far-field permeability on reservoir performance. By focusing on basin characteristics that are common among offshore basins worldwide, results from this study suggest that offshore CCS may be a feasible carbon management strategy in regions where offshore basins are proximal to industrial CO 2 sources.

42 ENGINEERING↗
DOE OSTI2022

Assessment of chemo-mechanical impacts of CO 2 sequestration on the caprock formation in Farnsworth oil field, Texas

This study evaluates the chemo-mechanical influence of injected CO 2 on the Morrow B sandstone reservoir and the upper Morrow shale caprock utilizing data from the inverted 5-spot pattern centered on Well 13-10A within the Farnsworth unit (FWU). This study also seeks to evaluate the integrity of the caprock and the long-term CO 2 storage capability of the FWU. The inverted 5-spot pattern was extracted from the field-scale model and tuned with the available field observed data before the modeling work. Two coupled numerical simulation models were utilized to continue the study. First, a coupled hydro-geochemical model was constructed to simulate the dissolution and precipitation of formation minerals by modeling three intra-aqueous and six mineral reactions. In addition, a coupled hydro-geomechanical model was constructed and employed to study the effects of stress changes on the caprock’s porosity, permeability, and ground displacement. The Mohr–Coulomb circle and failure envelope were used to determine caprock failure. In this work, the CO 2 -WAG injection is followed by the historical field-observed strategy. During the forecasting period, a Water Alternating Gas (WAG) injection ratio of 1:3 was utilized with a baseline bottom-hole pressure constraint of 5500 psi for 20 years. A post-injection period of 1000 years was simulated to monitor the CO 2 plume and its effects on the CO 2 storage reservoir and caprock integrity. The simulation results indicated that the impacts of the geochemical reactions on the porosity of the caprock were insignificant as it experienced a decrease of about 0.0003% at the end of the 1000-year post-injection monitoring. On the other hand, the maximum stress-induced porosity change was about a 1.4% increase, resulting in about 4% in permeability change. It was estimated that about 3.3% of the sequestered CO 2 in the formation interacted with the caprock. Despite these petrophysical property alterations and CO 2 interactions in the caprock, the caprock still maintained its elastic properties and was determined to be far from its failure.

04 OIL SHALES AND TAR SANDS↗