Erratum: Towards storage rings as quantum computers [Phys. Rev. Accel. Beams 23 , 054701 (2020)]
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43 PARTICLE ACCELERATORS↗
SEARCH · Engineering Papers
Results for “information storage”
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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Contamination control handbook
Contamination Control Handbook provides technical information on avoiding contamination of physical, chemical or biological systems or products. The book includes control methods for product design, gases and liquids, airborne and surface contamination, radiation, packaging handling, storage and personnel.
Source record↗
The problem of regime summaries of the data from radar observations
Peculiarities of the radar information about clouds are examined in comparison with visual data. An objective radar classification is presented and the relation of it to the meteorological classification is shown. The advisability of storage and summarization of the primary radar data for regime purposes is substantiated.
Divinskaya, B. S.↗
Lossless compression of image data products on th e FIFE CD-ROM series
How do you store enough of the key data sets, from a total of 120 gigabytes of data collected for a scientific experiment, on a collection of CD-ROM's, small enough to distribute to a broad scientific community? In such an application where information loss in unacceptable, lossless compression algorithms are the only choice. Although lossy compression algorithms can provide an order of magnitude improvement in compression ratios over lossless algorithms the information that is lost is often part of the key scientific precision of the data. Therefore, lossless compression algorithms are and will continue to be extremely important in minimizing archiving storage requirements and distribution of large earth and space (ESS) data sets while preserving the essential scientific precision of the data.
Newcomer, Jeffrey A.↗
Development and Testing of the CRYOTSU Flight Experiment
This paper describes the development and ground testing of the CRYOTSU thermal management flight experiment. CRYOTSU incorporates three cryogenic temperature experiments and one ambient temperature experiment into a Hitchhiker (HH) Get Away Special (GAS) Canister that is currently scheduled to fly on STS-95 in October 1998. The cryogenic experiments consist of a nitrogen triple-point cryogenic thermal storage unit (CTSU), a nitrogen cryogenic capillary pumped loop (CCPL), and a hydrogen gas-gap cryogenic thermal switch (CTSW). The ambient experiment is a carbon-fiber core, paraffin-filled thermal storage unit. Test results of integrated flight canister testing are provided herein for the CTSU and CCPL experiments. Pre-integration laboratory test results are provided for the CTSW. Design information and test results for the ambient experiment are not included.
Bugby, David C.↗
Development and Testing of the CRYOTSU Flight Experiment
This paper describes the development and ground testing of the CRYOTSU thermal management flight experiment. CRYOTSU incorporates three cryogenic temperature experiments and one ambient temperature experiment into a Hitchhiker (HH) Get Away Special (GAS) Canister that is currently scheduled to fly on STS-95 in October 1998. The cryogenic experiments consist of a nitrogen triple-point cryogenic thermal storage unit (CTSU), a nitrogen cryogenic capillary pumped loop (CCPL) and a hydrogen gas-gap cryogenic thermal switch (CTSW). The ambient experiment is a carbon-fiber core, paraffin-filled thermal storage unit. Test results of integrated flight canister testing are provided herein for the CTSU and CCPL experiments. Pre-integration laboratory test results are provided for the CTSW. Design information and test results for the ambient experiment are not included.
Bugby, David C.↗
Physics Simulation Software for Autonomous Propellant Loading and Gas House Autonomous System Monitoring
1. Kennedy Space Center (KSC) is developing a mobile launching system with autonomous propellant loading capabilities for liquid-fueled rockets. An autonomous system will be responsible for monitoring and controlling the storage, loading and transferring of cryogenic propellants. The Physics Simulation Software will reproduce the sensor data seen during the delivery of cryogenic fluids including valve positions, pressures, temperatures and flow rates. The simulator will provide insight into the functionality of the propellant systems and demonstrate the effects of potential faults. This will provide verification of the communications protocols and the autonomous system control. 2. The High Pressure Gas Facility (HPGF) stores and distributes hydrogen, nitrogen, helium and high pressure air. The hydrogen and nitrogen are stored in cryogenic liquid state. The cryogenic fluids pose several hazards to operators and the storage and transfer equipment. Constant monitoring of pressures, temperatures and flow rates are required in order to maintain the safety of personnel and equipment during the handling and storage of these commodities. The Gas House Autonomous System Monitoring software will be responsible for constantly observing and recording sensor data, identifying and predicting faults and relaying hazard and operational information to the operators.
Regalado Reyes, Bjorn Constant↗
(ODIN): An Open Source, Low-Latency Data Integration & Visualization Framework for the NASA System Wide Safety Project's Disaster Response Safety Demonstration Series
The Open Data Integration Framework (ODIN) is an open source, low latency data integration and visualization framework (https://github.com/NASARace/race-odin) developed under NASA’s System WideSafety Program to demonstrate new safety capabilities designed to improve US airspace operations. Safety demonstrations are a set of increasingly complex (from public safety perspective) disaster response scenarios under which air systems must operate with increased capacity and include: 1) Wildland fire response, 2) Hurricane relief and recovery, 4) Emergency medical delivery via UAS and 4) Urban disaster relief. To accommodate disaster response, ODIN is field deployable and can scale on one or more multi-core, commodity laptops operating with full to limited or intermittent internet connectivity, conditions likely encountered during operations. ODIN runs as webserver with local, persistent data storage to serve either public or a secured, ad hoc network (e.g., an incident command post). The current released ODIN, ODIN-Fire is tailored for wildland fire management incorporating information on satellite overpasses with links to the near real-time data and imagery from the respective agencies. Included are winds data, an important variable for emergency responders and airspace operations, and high-resolution wind forecasts generated by super-computing resources and ingested into ODIN. As an open-source project, ODIN has attracted interest from multiple entities. We will show how 1) a commercial field instrument and data provider uses ODIN to help users visualize, publish and integrate their in-situ sensor network data and 2) ODIN’s capabilities to ingest, integrate and display near-real time satellite data with air traffic and a USFS winds forecast model used in fire response and post-fire assessment. Within NASA ODIN demonstrated novel, near terminal airspace safety capabilities for a project close-out event and previously it monitored the national airspace in real-time to meet an agency milestone. ODIN is presently under development for the anticipated hurricane relief and response demonstration notionally scheduled for the 2025-27 time frame and is available from NASA's github at the above link.
Aeronautics↗
All Hazards Approach to Grid Modernization
Resilience hazards for electric power systems are on the rise, exacerbated by both a rise in extreme weather events and manmade physical and cyber attacks. At the same time, grid modernization challenges plague the United States, covering everything from increased electrification and ambitious renewable energy targets to aging infrastructure and regulation that lags behind today’s challenges. This talk will cover an all-hazards risk based approach that addresses both rising resilience and grid modernization challenges. Examples of this approach taken for national laboratory research projects will be discussed, including a deep dive into a project that addressed black start, resynchronization, distributed control, and cybersecurity challenges for an operational microgrid up to sub-transmission voltages. As takeaways from this project are translated from demonstration scale to real-world exercises, key lessons are noted on the translation from research into practice and how this can inform risk-based research moving forward
17 WIND ENERGY↗
HYBRID Modeling Validation and Verification Status Matrix
The HYBRID modeling repository is a premier resource for integrated energy systems modeling. HYBRID models have been developed since 2015 to describe the physical operation of tightly coupled thermal systems including power generators, thermal transport systems, thermal storage, thermal-to-electric conversion systems, and other thermal applications. Due to the increased size of the repository, a concise summary matrix of available models is desired. This matrix will consolidate not only the list of available models but also indicate original information sources, publications that have model examples, and level of validation and verification that exists for the models. Validation and verification (V&V) levels begin from simplified algebraic relationship and advance to dynamic data validation. Moving forward, as new models are contributed to HYBRID, their V&V level will be included, updating this matrix.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Data retrieval system provides unlimited hardware design information
Data is input to magnetic tape on a single format card that specifies the system, location, and component, the test point identification number, the operators initial, the date, a data code, and the data itself. This method is efficient for large volume data storage and retrieval, and permits output variations without continuous program modifications.
Rawson, R. D.↗
The anomaly data base of screwworm information
Standard statistical processing of anomaly data in the screwworm eradication data system is possible from data compiled on magnetic tapes with the Univac 1108 computer. The format and organization of the data in the data base, which is also available on dedicated disc storage, are described.
Giddings, L. E.↗
System Analysis Support of Consent-Based Siting Efforts - 23400
To better enable informed decision-making regarding the back end of the nuclear fuel cycle, the Integrated Waste Management (IWM) program within the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) has been sponsoring the development and application of system analysis tools capable of analyzing various system options for the management of spent nuclear fuel (SNF) and high-level radioactive waste. With these tools, integrated waste management system (IWMS) architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). System analyses and assessments typically use these modeling and simulation tools to investigate things like the implications of changes in various assumptions and parameters such as acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, and different assumed system operation start dates. Some example system analysis results have been published previously. With the passage of the consolidated appropriations acts for fiscal years 2021 and 2022, Congress provided funding and direction for the DOE to move forward with interim storage to support near-term action in managing the nation’s SNF as an important component of an IWMS. Consent-based siting is a phased, adaptive, and collaborative approach to siting facilities that focuses on the needs and concerns of people and communities. Communities participate in the siting process by working carefully through a series of phases and steps with the DOE (as the implementing organization). Each step and phase helps a community determine whether and how hosting a facility to manage SNF is aligned to the community’s goals. By its nature, a consent-based siting process must be transparent, flexible, adaptive, and responsive to community concerns. Thus, the phases and steps are intended to serve as a guide, not a prescriptive set of instructions. System analysis research analysts interface with DOE’s consent-based siting for a federal interim storage program and can perform preliminary system analyses as requested to support various aspects of the consent-based siting team’s work. This paper provides an overview of IWM program’s system analysis activities that support the ongoing consent-based siting process. The questions that decision-makers, planners, communities, and stakeholders might have during the consent-based siting process are similar to questions that have been explored by system analysts previously. Specifically, this paper discusses work that will inform consent-based siting efforts in the areas of community impacts, cost estimates, various SNF acceptance rates by potential facilities, potential consolidated interim storage facility (CISF) capacities and configurations, and the implications of a CISF on the overall waste management system. It is expected that system analysis will continue to be performed to support the consent-based siting process in the future.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage
Integrating monitoring data to efficiently update reservoir pressure and CO 2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. Here we applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO 2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.
58 GEOSCIENCES↗
Designing a GIS-based supply chain for producing carinata-based sustainable aviation fuel in Georgia, USA
Carinata is a potential crop for sustainable aviation fuel (SAF) production in the southern USA. However, as a novel crop, the cost-effectiveness and environmental feasibility of carinata feedstock are unknown, and there are questions about the optimal supply chain configuration for carinata-based SAF production. This study aims to design a supply chain model for carinata-based SAF production by optimizing the location of farms and facilities (e.g. storage units, crushing mills, biorefineries) for a minimum transportation cost under a set of supply and demand conditions. An integrated mixed-integer linear programming (MILP) model was combined with geographical information system (GIS) analysis to design a spatially explicit supply chain configuration. The GIS-based network analysis considered all of the counties in Georgia to set the candidate locations of carinata farms and facilities, and determined minimum cost and emission routes between those counties and the airport using existing transportation networks and modes (e.g. road, rail and pipeline). The MILP model determined the final selection of the farms and the number of facilities and their locations over those minimum-cost routes. With this supply chain configuration, the minimum price of SAF was $\$$0.92 L –1 , which is $\$$0.44 higher than conventional aviation fuel (CAF). The associated carbon intensity of SAF was estimated at 940.7 g CO 2 e L –1 , a reduction of 66% relative to the carbon intensity of equivalent CAF. The study found that a carbon tax (or subsidy) of $\$$230.48 t CO 2 e –1 would be needed to overcome the cost differential with CAF and promote carinata-based SAF in Georgia.
09 BIOMASS FUELS↗
Low-Income Energy Affordability: Conclusions From A Literature Review
This paper examines the persistent problem of high energy burdens among low-income households, based on a review of more than 180 publications that pointed to several promising opportunities to address energy affordability including inclusive solar programs, leveraged health care benefits, and behavioral economics. using an equity and affordability lens. Even after decades of weatherization and bill-payment programs, low-income households, on average, continue to spend a higher share of their income on electricity and natural gas bills than any other income group. Energy burden for low-income households is not declining, and it remains persistently high, particularly in the South, in rural America, among minority households, and those with children and elderly residents. On a per household basis, utility companies spend less on energy-efficiency programs for low-income households than for other income groups. In addition, government and utility programs that promote rooftop solar power, electric vehicles, and home energy storage are largely inaccessible to low-income households. Our review identifies promising opportunities to address energy affordability including inclusive solar programs, leveraged health care benefits, behavioral economics, data analytics, advanced information and communication technologies, and grid resiliency. Scalable approaches require linking implementing agencies, programs and policies to tackle the complex web of causes and impacts on low-income households with high energy burdens.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
A Review of International Field Experience with Well Integrity at Carbon Utilization and Storage Sites
This report details findings from a survey of well integrity experiences elicited from operators of geologic carbon storage (GCS) and carbon dioxide enhanced oil recovery (CO2-EOR) sites around the world. The survey consisted of 41 questions organized in four sections and its goal was to obtain information about site characteristics and operator experiences with well integrity, monitoring methods, and risk assessment of legacy wells. Current literature relevant to the survey questions was also reviewed and summarized to provide context for survey responses and identify areas where field experiences with well integrity do and do not align with the current state of research.
54 ENVIRONMENTAL SCIENCES↗
Uncertainty in Thermal Modeling of Spent Nuclear Fuel Casks
Uncertainty is a key metric in computational modeling that must be evaluated for results to have wide ranging applicability. A well characterized uncertainty range is ideal with clear error bars on results that can be presented to stakeholders. In the field of spent fuel cask modeling, this ideal has been historically difficult to achieve in practice because of the computationally intensive nature of the models used and the difficulty assigning reasonable uncertainties to quantities in as-built systems. The work in this report has been conducted to evaluate the overall state of uncertainty and sensitivity in spent fuel cask models and develop methodologies for evaluating these uncertainties. These methodologies must be practical for engineering applications. They should not require excessive computational resources or calendar time to achieve results. In engineering, the model must be on a scale such that it can be changed and adapted throughout a project as new information is discovered and project goals evolve. This report covers three major modeling task areas that provide an overview of the types of sensitivity and uncertainty present in a spent fuel storage and transportation system. Section 3 discusses sensitivity and uncertainty analysis in the effective thermal conductivity model for the fuel region and applies these results to a single assembly model. Section 4 shows sensitivity analysis of a full cask model in the TN-32B and Section 5 demonstrates the overall uncertainty workflow using Coolant Boiling in Rod Arrays – Spent Fuel Storage and STAR-CCM+ developed from the sensitivity work in the preceding sections.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗