Improvements of NSLS-II X-ray Diagnostic Beamlines
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Pore network characterization is an important aspect in unconventional reservoir evaluation. While application of the technique of scanning electron microscope (SEM) brings substantial advances in pore characterization in shale, understanding the connected pore network that dominates flow in shale samples is limited by using SEM alone because of small fields of view and lack of views of connectivity in 3D. In this research, a technique integrating tracer imbibition, micro-computed tomography (CT) imaging, and SEM imaging was developed to provide a solution for multiscale imaging in shale. Tracer imbibition indicates pore connectivity; micro-CT imaging after tracer imbibition thus provides an overview of the connected pore network at the millimeter scale. With guidance from micro-CT images after tracer imbibition, a more accurate and detailed characterization of pore systems and related mineralogy can be conducted using higher-resolution SEM. The method was applied to five samples from Wolfcamp and Eagle Ford Formations. Results reveal the effectiveness of the integrated method by showing different patterns of distribution of the dominant pore network and different controlling mineralogy. Dominant porosity, estimated from grayscale analyses, displays a good correlation with permeability. This result indicates that dominant porosity is more relevant to permeability than is total porosity. Results from imbibition tests are also compared with that from contact angle measurement, and important implications on wettability can be obtained. The integrated method thus has the capacity to link the dominant pore network and wettability with microscale to submicroscale mineralogy, which can help better understand the pore systems and fluid flow in shale. Plain Language Summary Pore network characterization and wettability are two important aspects in unconventional reservoir evaluation and are crucial to understanding the nature of shale oil or gas storage and production. Here, a new technique integrating tracer imbibition, micro-computed tomography imaging, and scanning electron microscope imaging was developed for a more representative and effective pore characterization in shale. This integrated technique can provide a direct visualization of the dominant pore network in a millimeter-scale sample and, at the same time, can provide a guided pore network characterization under nanoscale resolution. This method thus can generate results that are more representative and more accurate in a more efficient way compared with the traditional scanning electron microscope method. The new technique can also reveal the local wettability in microscale. High-resolution analysis on the tracer imbibition or fluid displacement and mineralogy can shed light on the local wettability and the controlling mineralogy in shale.
An emerging scientific computing environment in which computers are used not only to solve large-scale models, but are also integrated into the daily activities of scientists and engineers, is discussed. The requirements of the scientific user in this environment are reviewed, and the hardware environment is described, including supercomputers, work stations, mass storage, and communications. Significant increases in memory capacity to keep pace with performance increases, the introduction of powerful graphics displays into the work station, and networking to integrate many computers are stressed. The emerging system software environment is considered, including the operating systems, communications software, and languages. New scientific user tools and utilities that will become available are described.
The shift from synchronous generators to inverter-based resources has caused power system inertia to be unevenly distributed across power grids. As a result, certain grid regions are more vulnerable to high rate-of-change of frequency (RoCoF) during disturbances. This paper presents a measurement-based framework for estimating grid inertia in CAISO (California Independent System Operator) region using real disturbance-driven frequency data from the Frequency Monitoring Network (FNET/GridEye). By analyzing confirmed disturbances from 2013 to 2024, we identify trends in regional inertia and frequency dynamics, highlighting their relationship with renewable generation and the evolving duck curve. Regional RoCoF values were up to six times higher than interconnection-wide values, coinciding with declining inertia. Recent recovery in inertia is attributed to the increased deployment of battery energy storage systems with synthetic inertia capabilities. These findings underscore the importance of regional inertia monitoring, strategic resource planning, and adaptive operational practices to ensure grid reliability amid growing renewable integration.
The online computing environment at STAR has generated demand for high availability of services (HAS) and a resilient uptime guarantee. Such services include databases, webservers, and storage systems that user and sub-systems tend to rely on for their critical workflows. Standard deployment of services on bare metal creates a problem if the fundamental hardware fails or loses connectivity. Additionally, the configuration of redundant failover nodes (a secondary Web service for example) requires constant syncing of configuration and content and sometimes manual interaction for switching hardware (DNS name comes to mind). For this project, we will focus on two tools: oVirt and Ceph. oVirt is an OpenSource virtualization management application that enables central management of hardware nodes, storage, and network resources used to deploy and monitor virtual machines. oVirt supports the deployment of a virtual environment for your data center leveraging automatic provisioning, live migration, and the ability to easily scale the number of hypervisors. oVirt enables the use of multiple storage technologies where you can store virtual machines, images, and templates within one or multiple storage systems. STAR's recent efforts focused on deploying a CephFS POSIX compliant distributed storage system, we would enable the ability to couple our Ceph storage with the oVirt virtualization management system. When designing an intricate system for hosting critical services, it is a requirement to circumvent single points of failure. This work will involve the testing and viability of such an approach along with test cases for high availability, live migration, and service on demand.
Future scientific discoveries will rely on flexible ecosystems that incorporate modern scientific instruments, high performance computing resources, parallel distributed data storage, and performant networks across multiple, independent facilities. In addition to connecting physical resources, such an ecosystem presents many challenges in logistics and accessibility, especially in orchestrating computations and experiments that span across leadership computing systems and experimental instruments. Past efforts have typically been application-specific or limited to interfaces for computing resources. This paper proposes a general framework for integrating computation resources and instrument operations, addressing challenges in code development/execution, data staging and collection, software stack, control mechanisms, resource authorization and governance, and hardware integration. We also describe a demonstration use case wherein a Bayesian optimization algorithm running on an edge computing resource guides a scanning probe microscope to autonomously and intelligently characterize a material sample. This science edge ecosystem framework will provide a blueprint for federating multi-institutional, disparate resources and orchestrating scientific workflows across them to enable next-generation discoveries.
We present an experimental evaluation of a burst buffer for a real-time DAQ streaming system designed to transmit instrument data to remote data centers. The system is based on EJ-FAT, a load balancing system capable of Nx 100Gbps streams, distributing data from event sources to processing nodes. We explore applying the DAOS system as a burst buffer to serve a number of purposes: improve resiliency, elasticity and add new functions into the processing pipeline. In the evaluation a sender transmits events over a 100Gbps network to a receiver integrated with DAOS to store the reassembled events using DAOS APIs. We evaluate the system for possible bottlenecks and provide end-to-end evaluation with a burst buffer using DAOS storage abstractions. We show that a receiver node can support 38.1 Gbps. This proves the viability of our approach and allows us to extend this work to investigate scale-out properties and new streaming optimizations.
NASA computer program automatically analyzes power-system networks under faulted conditions. Program is general enough to calculate single-line to ground faults and three-phase-to-ground faults. Several novel programing techniques automate analysis while reducing computing time and storage requirements. Program is written in FORTRAN IV for batch execution.
The current cache of S/X-band geodetic/astrometric VLBI data accumulated since 1979 is approx.4.2 million observations and is increasing by approx.300,000 observations per year. The long time interval and access to all such VLBI data for re-analysis have contributed to their usefulness for the terrestrial and celestial reference frames, Earth orientation parameters, tidal and nontidal loading, and troposphere. While data access and integrity have been maintained through the Mark III data base system as storage devices and media have evolved, past transitions have been major projects. A new format and retention concept to ensure eternal archiving and access should make use of self-documentation, generalized media, network connectivity and multiple redundancy. Similarly permanent organizations or sequences of organizations are also necessary.
The current cache of S/X-band geodetic/astrometric VLBI data accumulated since 1979 is approx. 5 million observations and is increasing by approx. 300,000 observations per year. The long time interval and access to all such VLBI data for re-analysis have contributed to their usefulness for the terrestrial and celestial reference frames, Earth orientation parameters, tidal and non-tidal loading, and troposphere. While data access and integrity have been maintained through the Mark III data base system as storage devices and media have evolved, past transitions have been major projects. A new format and retention concept to ensure eternal archiving and access should make use of self-documentation, generalized media, network connectivity and multiple redundancy. Similarly permanent organizations or sequences of organizations are also necessary.
A DC bus collection system for a wind farm reduces the overall required number of converters and minimizes the energy storage system requirements. The DC bus collection system implements a power phasing control method between wind turbines that filters the variations and improves power quality. The phasing control method takes advantage of a novel power packet network concept with nonlinear power flow control design techniques that guarantees both stable and enhanced dynamic performance.
One of NASA's key goals is to increase the safety and reduce the cost of space transportation. Thus, a key element of NASA's new Integrated Space Transportation Plan is to develop new propulsion, structures, and operations for future generations of reusable launch vehicles (RLVs). As part of this effort to develop the next RLV, the ClCT Program's Computing, Networking, and Information Systems (CNIS) Project is developing and demonstrating collaborative software technologies that use the collective power of the NASA Grid to accelerate spacecraft design. One of these technologies, called AeroDB, automates the execution and monitoring of computational fluid dynamics (CFD) parameter studies on the NASA Grid. About the NASA Grid The NASA Grid, or Information Power Grid,. is being developed to leverage the distributed resources of NASA's many computers. instruments, simulators, and data storage systems. The goal is to use these combined resources to sdve difficult NASA challenges, such as iimulating the entire flight of a space vehicle from ascent to descent.To realize the vision of the NASA Grid, the CNIS Project is developing the software framework and protocols for building domain-specific environments and interfaces, new Grid services based on emerging industry standards, and advanced networking and computing testbeds to support new Grid-based applications such as AeroDB.
Carbon, natural gas, and hydrogen gas storage is an emerging solution to safeguard us against pollution, support goals of negative carbon emission, and protect sources of renewable energy. Properly constructed storage wells provide a virtually impervious barrier to any unintended subsurface transmission. The ability to ensure the long-term integrity of such wells is vital to the success of any storage operation and be successful in the public eyes. Therefore, robust monitoring of any gas migration into the subsurface is highly sought. A fiber-optic distributed chemical sensor (DCS) enables monitoring of long-term well integrity along its depth, ensuring the success of any storage operation and bolsters public acceptance of the safety of the reservoir via leak early detection. The same technique can be applied to gas monitoring in pipeline networks and nuclear stockpile monitoring applications. Fiber based Raman spectroscopy enables DCS, as optical fibers can be deployed in virtually any environment and relay spectroscopic information over long distances back to the user. Hollow core fibers (HCF) make excellent DCSs as the air core of the fiber allows gas from the environment to diffuse into the core, which interacts with the laser signal that is carried in the air core. This work builds upon the previous LDRD project, Fiber Optic System for Direct Detection of Carbon Dioxide Leakage in Carbon Storage Wells (21-FS-003), in which the feasibility of Raman spectroscopy detection of Carbon Dioxide (CO2) in HCF detection was demonstrated. We mitigated the risk of this DCS technology by establishing and completing five objectives. The first objective was to model and optically characterize HCF uptake of CO2, establishing the relationship between HCF length, gas diffusion time, detectable gas concentration, and measured Raman intensity. In objective two, we developed a fiber core drilling recipe to enable additional diffusion ports in the fiber core and established a method for maintaining fiber strength and integrity post drilling. Objective three characterized the drilled fibers against the undrilled fibers, establishing the differences in the gas mechanics and optical properties and provided parameters to iterate the drilling process. In objective four, a fusion splicing technique was developed to join the HCF to conventional single-mode fibers, localizing the gas detection point at the drilled HCF hole, emulating a DCS. Lastly, objective five was the testing of the sensor in Edgar Mines at Colorado School of Mines on a CO2 pipeline with a simulated leak, to showcase the ability to detect CO2 leaks. This capstone result showed CO2 leak detection in < 10 minutes, raising the technology readiness level of HCF segments as deployable DCS.
Abstract The Intergovernmental Panel on Climate Change concludes that CO 2 capture and storage (CCS) is critical for climate‐stabilizing energy transitions. In CCS, captured CO 2 is sequestered in saline aquifers within sedimentary basins. The CO 2 storage capacity and the rate of injection are functions of the geology of the saline aquifer, which is uncertain. To minimize impacts of this uncertainty, CCS projects could include backup plans, such as co‐locating geologic CO 2 storage (GCS) sites with or near existing CO 2 ‐enhanced oil recovery (CO 2 ‐EOR) operations. These “stacked storage” projects could hedge against uncertainty in the saline formation performance because captured CO 2 could be injected into either location in the event of unexpected events (e.g., the injectivity decreases). Here, we investigate the possibility and ramifications of developing CCS networks in Oklahoma that are amendable to stacked storage. We find that stacked storage is possible in Oklahoma but the counties with the lowest‐cost saline storage resources do not have existing CO 2 ‐EOR operations. At the systems level, we find it is slightly more expensive (e.g., $1/tCO 2 to $5/tCO 2 ) to site GCS in counties with CO 2 ‐EOR projects. This increased expense is largely due to increased CO 2 transportation costs because hundreds of km of additional pipeline is required to capture CO 2 from the lowest‐cost sources. Overall, our results suggest that it is optimal to build more pipelines and avoid injecting CO 2 in some of the lowest‐cost saline storage resources, to enable capturing CO 2 from the least‐cost sources. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.
The U.S. military has been exploring pathways to reduce the logistical burden of fuel on virtually all their missions globally. Energy harvesting of local resources such as wind and solar can help increase the resilience and operational effectiveness of military units, especially at the most forward operating bases where the fuel logistics are most challenging. This report considers the potential benefits of wind energy provided by deployable wind turbines as measured by a reduction in fuel consumption and supply convoys to a hypothetical network of Army Infantry Brigade Combat Team bases. Two modeling and simulation tools are used to represent the bases and their operations and quantify the impacts of system design variables that include wind turbine technologies, battery storage, number of turbines, and wind resource quality. The System of Systems Analysis Toolkit Joint Operational Energy Model serves as a baseline scenario for comparison. The Hybrid Optimization of Multiple Energy Resources simulation tool is used to optimize a single base within the larger Joint Operational Energy Model. The results of both tools show that wind turbines can provide significant benefits to contingency bases in terms of reduced fuel use and number of convoy trips to resupply the base. The match between the turbine design and wind resource, which is statistically low across most of the global land area, is a critical design consideration. The addition of battery storage can enhance the benefits of wind turbines, especially in systems with more wind turbines and higher wind resources. Wind turbines may also provide additional benefits to other metrics such as resilience that may be important but not fully considered in the current analysis. ACKNOWLEDGEMENTS The authors would like to thank the following individuals for their helpful support, feedback and review to improve this report: U.S. Department of Energy Wind Energy Technologies Office, Patrick Gilman and Bret Barker; Idaho National Laboratory, Jake Gentle and Bradley Whipple; The National Renewable Energy Laboratory, Robert Preus and Tony Jimenez; Sandia National Laboratories, Alan Nanco, Dennis Anderson, and Hai Le. In addition, numerous discussions with military and industry stakeholders over the year were invaluable in focusing the efforts represented in this report.
Optimal power management (OPM) is critical for large-scale battery energy storage systems. Today’s methods often require formidable computational effort due to the design based on centralized numerical optimization. Thus, this paper investigates computationally distributed OPM where the agents based on the cells communicate over a network to cooperatively solve the OPM problem. We propose an accelerated tracking alternating direction method of multipliers (ADMM) algorithm to solve the distributed OPM. The proposed algorithm embeds dynamic average consensus and Nesterov’s acceleration technique in the ADMM algorithm. Not only is the proposed algorithm fully distributed without a need for fusion or aggregating nodes, but it also accelerates convergence. The paper formulates the OPM in a model predictive control framework where it seeks to regulate the charging/discharging power of each battery cell to minimize the total power losses and promote balanced use of the constituent cells while complying with the safety constraints. The paper provides ample simulation results to demonstrate the effectiveness and advantages of the proposed distributed OPM in terms of computation and convergence.
Rapid efficient access to Earth sciences data is fundamental to the Nation's efforts to understand the effects of global environmental changes and their implications for public policy. It becomes a bigger challenge in the future when data volumes increase further and missions with constellations of satellites start to appear. Demands on data storage, data access, network throughput, processing power, and database and information management are increased by orders of magnitude, while budgets remain constant and even shrink. The Global Change Data Center's (GCDC) mission is to provide systems, data products, and information management services to maximize the availability and utility of NASA's Earth science data. The specific objectives are (1) support Earth science missions be developing and operating systems to generate, archive, and distribute data products and information; (2) develop innovative information systems for processing, archiving, accessing, visualizing, and communicating Earth science data; and (3) develop value-added products and services to promote broader utilization of NASA Earth Sciences Enterprise (ESE) data and information. The ultimate product of GCDC activities is access to data and information to support research, education, and public policy.
Each summer, large volumes of surface meltwater drain off the Greenland ice sheet (GrIS) surface through moulins to the bed, impacting subglacial hydrology and ice flow dynamics. Supraglacial surface routing delays may propagate to englacial and subglacial hydrologic systems, requiring accurate assessment to correctly estimate subglacial effective pressures. We compare hourly supraglacial moulin discharge simulations from three surface meltwater routing models – the synthetic unit hydrograph (SUH), the bare-ice component of surface routing and lake filling (SRLF), and the rescaled width function (RWF) – for four internally drained catchments on the southwestern Greenland ice sheet surface. The routing models are forced identically using surface runoff from the Modèle Atmosphérique Régionale regional climate model (RCM). For each catchment, simulated moulin hydrographs are input to the SHAKTI subglacial hydrologic model to simulate diurnally varying subglacial effective-pressure variations in the vicinity of a single moulin. Overall, all three routing models produce more realistic moulin discharges than simply using RCM runoff outputs without surface routing but produce significant differences in peak moulin discharge and time to peak. In particular, the RWF yields later, smaller peak moulin discharges than the SUH or SRLF due to its representation of slow interfluve flow between supraglacial meltwater channels, and it can readily accommodate the seasonal evolution of supraglacial stream and river networks. Differences among the three routing models are reflected in a series of simple idealized subglacial hydrology simulations that yield different diurnal effective-pressure amplitudes; however, the supraglacial hydrologic system acts as short-term storage for surface meltwater, and the temporal mean effective pressure is relatively consistent across routing models.