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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Range and Endurance Tradeoffs on Personal Rotorcraft Design

Rotorcraft design has always been a challenging tradeoff among overall size, capabilities, complexity, and other factors based on available technology and customer requirements. Advancements in propulsion, energy systems and other technologies have enabled new vehicles and missions; complementary advances in analysis methods and tools enable exploration of these enhanced vehicles and the evolving mission design space. A system study was performed to better understand the interdependency between vehicle design and propulsion system capabilities versus hover / loiter requirements and range capability. Three representative vertical lift vehicles were developed to explore the tradeoff in capability between hover efficiency versus range and endurance capability. The vehicles were a single-main rotor helicopter, a tilt rotor, and a vertical take-off and landing (VTOL) aircraft. Vehicle capability was limited to two or three people (including pilot or crew) and maximum range within one hour of flight (100-200 miles, depending on vehicle). Two types of propulsion and energy storage systems were used in this study. First was traditional hydrocarbon-fueled cycles (such as Otto, diesel or gas turbine cycles). Second was an all-electric system using electric motors, power management and distribution, assuming batteries for energy storage, with the possibility of hydrocarbon-fueled range extenders. The high power requirements for hover significantly reduced mission radius capability. Loiter was less power intensive, resulting in about 1/2 the equivalent mission radius penalty. With so many design variables, the VTOL aircraft has the potential to perform well for a variety of missions. This vehicle is a good candidate for additional study; component model development is also required to adequately assess performance over the design space of interest.

systems analysis↗
NASA NTRS2016

Range and Endurance Tradeoffs on Personal Rotorcraft Design

Rotorcraft design has always been a challenging tradeoff among overall size, capabilities, complexity, and other factors based on available technology and customer requirements. Advancements in propulsion, energy systems and other technologies have enabled new vehicles and missions; complementary advances in analysis methods and tools enable exploration of these enhanced vehicles and the evolving mission design space. A system study was performed to better understand the interdependency between vehicle design and propulsion system capabilities versus hover loiter requirements and range capability. Three representative vertical lift vehicles were developed to explore the tradeoff in capability between hover efficiency versus range and endurance capability. The vehicles were a single-main rotor helicopter, a tilt rotor, and a vertical take-off and landing (VTOL) aircraft. Vehicle capability was limited to two or three people (including pilot or crew) and maximum range within one hour of flight (100-200 miles, depending on vehicle). Two types of propulsion and energy storage systems were used in this study. First was traditional hydrocarbon-fueled cycles (such as Otto, diesel or gas turbine cycles). Second was an all-electric system using electric motors, power management and distribution, assuming batteries for energy storage, with the possibility of hydrocarbon-fueled range extenders. The high power requirements for hover significantly reduced mission radius capability. Loiter was less power intensive, resulting in about 12 the equivalent mission radius penalty. With so many design variables, the VTOL aircraft has the potential to perform well for a variety of missions. This vehicle is a good candidate for additional study; component model development is also required to adequately assess performance over the design space of interest.

systems analysis↗
NASA NTRS2017

Applications of Satellite Data to Support Improvements in Irrigation and Groundwater Management in California

In agricultural regions around the world, threats to water supplies from drought and groundwater depletion are driving increased demand for tools to advance agricultural water use efficiency and support sustainable groundwater management. Satellite mapping of evapotranspiration (ET) from irrigated agricultural lands can provide agricultural producers and water resource managers with information that can be used to both optimize ag water use and improve estimates of groundwater withdrawals for irrigation. We describe the development of two remote sensing-based tools for ET mapping in California, including important lessons in terms of system design, partnership development, and transition to operations. For irrigation management, the integration of satellite data and surface sensor networks to provide timely delivery of information on crop water requirements can make irrigation scheduling more practical, convenient, and accurate.Developed through a partnership between NASA and the CA Department of Water Resources, the Satellite Irrigation Management Support (SIMS) framework integrates satellite data with information from agricultural weather networks to map crop canopy development and crop water requirements at the scale of individual fields. Information is distributed to agricultural producers and water managers via a web-based interface and web data services. SIMS also provides an API that facilitates integration with other irrigation decision support tools, such as CropManage and IrriQuest. Field trials using these integrated tools have shown that they can be used to sustain yields while improving water use efficiency and nutrient management. For sustainable groundwater management, the combination of satellite-derived estimates of ET and data on surface water deliveries for irrigation can increase the accuracy of estimates of groundwater pumping. We are developing an OpenET platform to facilitate access to ET data from multiple models and accelerate operational use of ET data in support of a range of water management applications, including implementation of the Sustainable Groundwater Management Act in CA. By providing a shared basis for decision making, we anticipate that the OpenET platform will accelerate implementation of solutions for sustainable groundwater management.

Satellite↗
DOE OSTI2020

The Plant Microbiome: From Ecology to Reductionism and Beyond

Methodological advances over the past two decades have propelled plant microbiome research, allowing the field to comprehensively test ideas proposed over a century ago and generate many new hypotheses. Studying the distribution of microbial taxa and genes across plant habitats has revealed the importance of various ecological and evolutionary forces shaping plant microbiota. In particular, selection imposed by plant habitats strongly shapes the diversity and composition of microbiota and leads to microbial adaptation associated with navigating the plant immune system and utilizing plant-derived resources. Reductionist approaches have demonstrated that the interaction between plant immunity and the plant microbiome is, in fact, bidirectional and that plants, microbiota, and the environment shape a complex chemical dialogue that collectively orchestrates the plantmicrobiome. Finally, the next stage in plant microbiome research will require the integration of ecological and reductionist approaches to establish a general understanding of the assembly and function in both natural and managed environments.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2023

Propellant Mass Gauging in Microgravity with Electrical Capacitance Tomography

Advancements in microgravity propellant mass gauging will result in improvements to many areas of propellant management, which influences space vehicle performance and mission assurance. Propellant mass gauging technologies designed to work in an accelerated environment, where the propellant remains settled at one end of the propellant tank, do not always work well in a microgravity environment because the propellant is not necessarily settled. While some microgravity mass gauging technologies exist at various stages of development, most of them have major disadvantages. Electrical Capacitance Tomography (ECT) is a sensing technology that is able to reconstruct the liquid distribution inside of a tank, which can then be integrated to obtain mass. While ECT mass gauging will theoretically work during all phases of flight, it had not yet been tested in microgravity. The NASA Kennedy Space Center Launch Services Program, with support from the Flight Opportunities Program, successfully tested an ECT liquid mass gauging system experiment on a parabolic flight aircraft in May 2022. Basics of ECT measurement theory, details of the experiment setup, data processing, ground test results, and the flight test result will be discussed. The results suggest that ECT sensor systems will be useful as a propellant mass gauging technology in both accelerated and microgravity environments.

electrical capacitance tomography↗
NASA NTRS1998

Validation of the Version 1 NOAA/NASA Pathfinder Sea Surface Temperature Data Set

A high-resolution, global satellite-derived sea surface temperature (SST) data set called Pathfinder, from the Advanced Very High Resolution Radiometer (AVHRR) aboard the NOAA Polar Orbiters, is available from the Jet Propulsion Laboratory Physical Oceanography Distributed Active Archive Center (JPL PO.DAAC). Suitable for research as well as education, the Pathfinder SST data set is a result of a collaboration between the National Oceanographic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA) and investigators at several universities. NOAA and NASA are the sponsors of the Pathfinder Program, which takes advantage of currently archived Earth science data from satellites. Where necessary, satellite sensors have been intercalibrated, algorithms improved and processing procedures revised, in order to produce long time-series, global measurements of ocean, land and atmospheric properties necessary for climate research. Many Pathfinder data sets are available to researchers now, nearly a decade before the first launch of NASA's Earth Observing System (EOS). The lessons learned from the Pathfinder programs will facilitate the processing and management of terabytes of data from EOS. The Oceans component of Pathfinder has undertaken to reprocess all Global Area Coverage (GAC) data acquired by the 5-channel AVHRRs since 1981. The resultant data products are consistent and stably calibrated [Rao, 1993a, Rao, 1993b, Brown et al., 1993], Earth-gridded SST fields at a variety of spatial and temporal resolutions.

Smith, Elizabeth A.↗
NASA NTRSDate not supplied

Controls for Electrified Aircraft Propulsion

Advanced electrified aircraft propulsion (EAP) concepts with integrated power, propulsion, and thermal systems require the development of equally sophisticated controllers to fly safe and efficient missions. Hybrid electric aircraft utilize electric machines mechanically coupled to the engine shafts to extract and insert power for a variety of purposes. Additionally, electric machines may drive propulsive fans pulling from a combination of on-board energy storage devices and engine extracted power. NASA’s investment in hybrid electric aircraft hardware-in-the-loop testing enables controls research on representative engine models using a novel emulation and scaling methodology. High-voltage, high-power electrical powertrain presents several technical risks at altitude. High-power requires high efficiency to minimize losses. Superconducting electric machines and power distribution research at NASA has identified key challenges with potential controls solutions. These risks necessitate the development of controllers robust to model uncertainty, disturbances, and fault conditions. System health management and fault detection schemes play an important role in a multi-layer controls approach that utilizes a supervisor which oversees inner loops for the highly coupled power, propulsion, and thermal systems. Such a supervisory controller enables coordinates energy transfer between engines, energy storage devices, electric machines, propulsors, and heat exchangers. Existing methods have shown an improvement in engine operability using the hybrid electric powertrain.

Halle E Buescher↗
DOE OSTI2023

Improving snow albedo modeling in the E3SM land model (version 2.0) and assessing its impacts on snow and surface fluxes over the Tibetan Plateau

With the highest albedo of the land surface, snow plays a vital role in Earth's surface energy budget and water cycle. Snow albedo is primarily controlled by snow grain properties (e.g., size and shape) and light-absorbing particles (LAPs) such as black carbon (BC) and dust. The mixing state of LAPs in snow also has impacts on LAP-induced snow albedo reduction and surface radiative forcing (RF). However, most land surface models assume that snow grain shape is spherical and LAPs are externally mixed with the snow grains. This study improves the snow radiative transfer model in the Energy Exascale Earth System Model version 2.0 (E3SM v2.0) Land Model (ELM v2.0) by considering non-spherical snow grain shapes (i.e., spheroid, hexagonal plate, and Koch snowflake) and internal mixing of dust–snow, and it systematically evaluates the impacts on the surface energy budget and water cycle over the Tibetan Plateau (TP). A series of ELM simulations with different treatments of snow grain shape, mixing state of BC–snow and dust–snow, and sub-grid topographic effects (TOP) on solar radiation are performed. Compared with two remote sensing snow products derived from the Moderate Resolution Imaging Spectroradiometer, the control ELM simulation (ELM_Control) with the default configurations of spherical snow grain shape, internal mixing of BC–snow, external mixing of dust–snow, and without TOP as well as the ELM simulation with new model features (ELM_New) can both capture the overall snow distribution reasonably. Additionally, ELM_New overall shows smaller biases in snow cover fraction than ELM_Control in spring when snowmelt is important for water management. The estimated LAP-induced RF in ELM_New ranges from 0 to 19.3 W m -2 with the area-weighted average value of 1.5 W m -2 that is comparable to the reported values in existing studies. The Koch snowflake shape, among other non-spherical shapes, shows the largest difference from the spherical shape in spring when snow processes related to the surface energy budget and water cycle have high importance. The impacts of the mixing state of LAP in snow are smaller than the shape effects and depend on snow grain shape. Compared to external mixing, internal mixing of LAP–snow can lead to larger snow albedo reduction and snowmelt, which further affect the surface energy budget and water cycle. The individual contributions of non-spherical snow shape, mixing state of LAP–snow, and local topography impacts on the snow and surface fluxes have different signs and magnitudes, and their combined effects may be negative or positive due to complex and nonlinear interactions among the factors. Overall, the changes in net solar radiation in spring due to individual and combined effects range from -28.6 to 16.9 W m -2 and -29.7 to 12.2 W m -2 , respectively. This study advances understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offers guidance for improving snow simulations and RF estimates in Earth system models under climate change.

58 GEOSCIENCES↗
DOE OSTI2023

PipeSight: A High-Performance Computing Platform for Pipeline Integrity Management

The Phase I feasibility study completed as part of this project has led to a number of innovative technologies being developed and has laid the foundation for a successful Phase II effort to commercialize a platform for managing the integrity of pipelines for the damage mechanisms of the new, hybrid-energy based economy. To ground the development efforts and direction of the project, an extensive market research and customer discovery effort was undertaken early in Phase I. Through this effort, a number of pipeline owners and operators were interviewed, and the following key findings were discovered about the pipeline industry: • Small pipeline operators do not have the central engineering groups necessary to perform their own independent analysis of inspection data, but instead rely on summarized tally sheets provided to them by inspection service providers. • The time it takes to go from an inspection to a completed engineering assessment, even for small segments of pipeline, can take anywhere from 30-120 days. During this delay, critical threats can (and have been known to) cause failures. • Uncertainty is often not accounted for in the assessment of pipeline integrity. The tally sheets provided by third-party service providers are almost always deterministic in nature, identifying threats that present a concern only to the current (not the future) integrity of the pipeline. • It is uncommon to apply the latest technologies to perform advanced assessments of damaged pipelines. There is a desire to use more advanced analysis capabilities to assess threats. Many pipeline operators indicated that they would often excavate a pipeline to perform an inspection and find that the damage was not as bad as they anticipated, thus using limited resources unnecessarily. Companies are not consistent in their use of inspection data to determine corrosion rates, and those that do only calculate deterministic corrosion rates. • The industry has prominently relied on time-based inspections but has recently started to transition to risk-based inspections. However, there appears to be no uniform guidance on how to do so while properly accounting for all sources of uncertainty. • Companies are not storing inspection data in a manner that allows for the ready determination of temporal trends. • Predictive maintenance principles and practices are beginning to be used by early adopters • Some pipelines are being re-purposed to transport different process fluids than they were designed for, e.g., H 2 and CO 2 rich process streams to serve the new hybrid-energy based economy, which are presenting new integrity concerns for the existing pipeline network that crisscrosses the United States. As a result of these discoveries, we were able to target the development efforts in Phase I to best serve the needs of the industry. In Phase I, we developed a way to correlate multiple large-scale scans of the pipeline to determine a probabilistic corrosion rate that accounts for all sources of error and uncertainty in the inspection process. This probabilistic corrosion rate can be used to predict the future thickness distribution of the pipe wall. We demonstrate how this analysis may be performed in an analytical fashion and has been implemented in such a manner that it can be readily distributed using GPU computing through integration of the Kokkos programming model. We also make a very novel extension of the analytical corrosion rate model to Bayesian Networks (an explainable AI technique) that can account for non-parametric distributions of corrosion rates. With the predictions made above for the probabilistic corrosion rate and corresponding future distribution of the pipe wall thickness, we can assess the integrity of the pipeline through the use of a probabilistic engineering assessment. We developed a novel screening data analysis approach that can rapidly identify ‘hotspots’ (local thin areas) where the integrity of the pipeline is a concern. Once more, we implemented this screening approach in C++ to leverage GPU computing via the Kokkos programming model. After the critical hotspots are identified, we developed a program that can automatically generate an advanced finite element model of the damaged regions. Since the number of damaged regions that require advanced analysis can number in the thousands, we integrated an open-source container-native workflow engine for orchestrating parallel jobs on the cloud. Initially, these advanced numerical models were only designed to account for loading due to internal pressure. However, in a slight pivot from the initial Phase I proposal, we developed a complete pipe stress analysis program (called Simflex) which can simulate the complete pipeline and its response to thermal expansion, pressure, thermal bowing, weight, wind, earthquake, support displacement, support friction and external forces. This pipe stress analysis program was written generically, to handle any piping system, but contains the features needed to model long pipelines (i.e., it incorporates a model for soil mechanics and can account for the nonlinear boundary conditions necessary to simulate long underground pipelines). This pipe stress analysis program can simulate any segment of the pipeline (simple or complex) under any set of conditions and loads, to determine the supplemental loads (axial forces and bending moments) at the location of damage. This enables the most accurate state of stress to be accounted for in the pipeline, which can prove critical when evaluating the integrity of a damaged region. In the process of developing the technologies to perform the integrity assessment of the pipeline, we also extended one of the industry standard approaches for performing the assessment of local thin areas that extend more in the circumferential direction than the longitudinal direction of the pipeline. This approach was presented to the API 579-1/AS ME FFS-1 steering committee in November 2021 for consideration in the next edition of the industry standard for Fitness-For-Service (expected to be released in 2023). To help pipeline operators make decisions with the results on any integrity assessment, we developed a new approach to the life-cycle management of pipelines which uses a Bayesian Decision Network. The network is designed to help pipeline operators plan and prioritize inspection activities and ultimately make smarter, more cost-effective decisions. The Bayesian approach accounts for all sources of uncertainty and carries them through to the final optimal decisions, providing a probabilistic framework for optimizing inspection intervals. The proof-of-concept networks developed in the feasibility study are complete, verified, and are focused on a subset of the pipeline. To expand this novel approach to the scale necessary for an entire network of pipelines in Phase II, we will leverage the DOE-funded Bengi solver for industrial-scale decision making with Bayesian Networks [22]. Once implemented, we will be able to provide the pipeline industry with a much-needed tool for optimal inspection planning using truly explainable artificial intelligence (XAI). To handle all of these advanced capabilities into a cloud-based platform, the architecture of the Equity Engineering Cloud (EEC) was extended to include Argo Workflows, a framework capable of distributing and managing a massive number of jobs that consume their own resources, such that thousands of serial finite element simulations can be run in parallel. As part of this substantial undertaking, we also integrated Argo Continuous Delivery (CD) into the EEC, to aid with the rapid prototyping and iterations that will be imperative to the success of the PipeSight platform’s Agile development process in Phase II. As part of the pipe stress analysis program, we also developed a custom visualizer that leverages the DOE-funded VTK visualization library. We added custom contouring capabilities and a means for interacting visually with both the inputs and outputs of the pipe stress analysis program. We also developed routines for automating the post-processing of the finite element simulations to determine if any failure criteria are met and to visualize the deformations, stresses and strains in ParaView using the exodus II file format (a subset of netCDF).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Guest Editorial: Special Section on Sustainable Energy for Enhancing Grid Resiliency

Extreme weather threatens lives, disables communities, and devastates energy generation, transmission, and distribution systems. These extreme events are likely to become more frequent or more intense due to climate change. Energy networks have shown significant vulnerability during record hurricanes, deadly heat waves, destructive wildfires, and winter storms in the past few years. Because of the energy transition process, modern power grids will feature a high penetration level of the use of renewable resources. The adoption of renewable energy and the rise of omnidirectional power delivery mean that our energy network is more decentralized than ever. In this new environment, grid operation becomes more complex, and achieving resiliency is more difficult than in the past. Many utilities are seeking the latest technologies to improve energy security and responsiveness to severe events. On the one hand, sustainable energy resources can provide emergency power and assist grid restoration in disastrous events. On the other hand, their volatility, susceptibility, interdependency, and other unique features must be carefully considered when being used for grid resilience enhancement. This special section brings together 22 papers that range from innovative research advances tackling fundamental challenges of achieving more resilient grids to real-world demonstrations of leveraging sustainable energy resources to enhance grid resiliency. These papers can be categorized into three groups.

climate change↗
DOE OSTI2024

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗
DOE OSTI2025

Bridging the Gap on Data and Analysis for Distribution System Planning: Information That Utilities Can Provide Regulators, State Energy Offices and Other Stakeholders

Electric utilities conduct planning annually to ensure their distribution system meets technical standards, policies, and regulations; addresses forecasted grid conditions; satisfies customer needs; and advances utility priorities. The plan identifies grid deficiencies, analyzes potential solutions, and prioritizes capital investments and other expenditures. About 20 U.S. states and jurisdictions require regulated utilities to file some type of distribution system plan with the public utility commission for review. Requirements for sharing distribution system data and analyses vary widely, from few specific requirements to a detailed list of information that must be provided. While utilities conduct extensive analysis to develop distribution system plans, in most jurisdictions regulators and stakeholders do not know what data are available and how the utility uses the data in planning and investing. This report aims to bridge the gap by increasing understanding of the types of data and analyses utilities employ to develop distribution system plans and how the information affects their decision-making. The report describes information that states and stakeholders can ask for related to 11 data categories: -Forecasting loads and distributed energy resources (DERs) -Scenario analysis -Worst-performing circuits -Asset management strategy -Hosting capacity analysis -Value of DERs -Grid needs assessment -Cost-effectiveness framework for investments -Distribution system investment strategy and implementation -Geotargeted programs -Non-wires alternatives procurements.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2001

Aeronautical-Satellite-Assisted Process Being Developed for Information Exchange Through Network Technologies (Aero-SAPIENT)

Communications technologies are being developed to address safety issues during aviation travel. Some of these technologies enable the aircraft to be in constant bidirectional communications with necessary systems, people, and other aircraft that are not currently in place today. Networking technologies, wireless datalinks, and advanced avionics techniques are areas of particular importance that the NASA Glenn Research Center has contributed. Glenn, in conjunction with the NASA Ames Research Center, NASA Dryden Flight Research Center, and NASA Langley Research Center, is investigating methods and applications that would utilize these communications technologies. In mid-June 2000, the flight readiness of the network and communications technologies were demonstrated via a simulated aircraft. A van simulating an aircraft was equipped with advanced phased-array antennas (Advanced Communications/Air Traffic Management (AC/ATM) Advanced Air Transportation Technologies (AATT) project) that used commercial Ku-band satellite communications to connect Glenn, Dryden, and Ames in a combined system ground test. This test simulated air-ground bidirectional transport of real-time digital audio, text, and video data via a hybrid network configuration that demonstrated the flight readiness of the network and communications technologies. Specifically, a Controller Pilot Data Link Communications application was used with other applications to demonstrate a multiprotocol capability via Internet-protocol encapsulated ATN (Aeronautical Telecommunications Network) data packets. The significance of this combined ground test is its contribution to the Aero Information Technology Base Program Level I milestone (Software Technology investment area) of a real-time data link for the National Airspace System. The objective of this milestone was to address multiprotocol technology applicable for real-time data links between aircraft, a satellite, and the ground as well as the ability to distribute flight data with multilevel priorities among several sites.

Zernic, Michael J.↗
NASA NTRS1994

The design of a petabyte archive and distribution system for the NASA ECS project

The NASA EOS Data and Information System (EOSDIS) Core System (ECS) will contain one of the largest data management systems ever built - the ECS Science and Data Processing System (SDPS). SDPS is designed to support long term Global Change Research by acquiring, producing, and storing earth science data, and by providing efficient means for accessing and manipulating that data. The first two releases of SDPS, Release A and Release B, will be operational in 1997 and 1998, respectively. Release B will be deployed at eight Distributed Active Archiving Centers (DAAC's). Individual DAAC's will archive different collections of earth science data, and will vary in archive capacity. The storage and management of these data collections is the responsibility of the SDPS Data Server subsystem. It is anticipated that by the year 2001, the Data Server subsystem at the Goddard DAAC must support a near-line data storage capacity of one petabyte. The development of SDPS is a system integration effort in which COTS products will be used in favor of custom components in very possible way. Some software and hardware capabilities required to meet ECS data volume and storage management requirements beyond 1999 are not yet supported by available COTS products. The ECS project will not undertake major custom development efforts to provide these capabilities. Instead, SDPS and its Data Server subsystem are designed to support initial implementations with current products, and provide an evolutionary framework that facilitates the introduction of advanced COTS products as they become available. This paper provides a high-level description of the Data Server subsystem design from a COTS integration standpoint, and discussed some of the major issues driving the design. The paper focuses on features of the design that will make the system scalable and adaptable to changing technologies.

Caulk, Parris M.↗
NASA NTRS2011

Power Management and Distribution (PMAD) Model Development: Final Report

Power management and distribution (PMAD) models were developed in the early 1990's to model candidate architectures for various Space Exploration Initiative (SEI) missions. They were used to generate "ballpark" component mass estimates to support conceptual PMAD system design studies. The initial set of models was provided to NASA Lewis Research Center (since renamed Glenn Research Center) in 1992. They were developed to estimate the characteristics of power conditioning components predicted to be available in the 2005 timeframe. Early 90's component and device designs and material technologies were projected forward to the 2005 timeframe, and algorithms reflecting those design and material improvements were incorporated into the models to generate mass, volume, and efficiency estimates for circa 2005 components. The models are about ten years old now and NASA GRC requested a review of them to determine if they should be updated to bring them into agreement with current performance projections or to incorporate unforeseen design or technology advances. This report documents the results of this review and the updated power conditioning models and new transmission line models generated to estimate post 2005 PMAD system masses and sizes. This effort continues the expansion and enhancement of a library of PMAD models developed to allow system designers to assess future power system architectures and distribution techniques quickly and consistently.

Metcalf, Kenneth J.↗
DOE OSTI2025

Advancing Grid Resilience through Smart Charge Management: Findings from Maryland’s Pilot

This report presents research findings from a four-year Smart Charge Management (SCM) pilot program conducted by Maryland’s largest electric utilities—Baltimore Gas and Electric (BGE), Potomac Electric Power Company (Pepco), and Delmarva Power & Light (DPL)—to evaluate strategies for optimizing electric vehicle (EV) charging loads and enhancing grid stability. Supported by the U.S. Department of Energy (DOE), Argonne National Laboratory collaborated with all project partners and examined the effectiveness of Time-of-Use (TOU) and Load Balancing (LB) strategies in managing peak demand, deferring costly infrastructure upgrades, and reducing grid constraints at the feeder level.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids with Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Optimizing green infrastructure placement under precipitation uncertainty

Increased urbanization, infrastructure degradation, and climate change threaten to overwhelm stormwater systems across the nation, rendering them ineffective. Green Infrastructure (GI) practices are low cost, low regret strategies that can contribute to urban runoff management. However, questions remain as to how to best distribute GI practices through urban watersheds given precipitation uncertainty and the variable hydrological responses to them. We develop stochastic programming models to determine the optimal placement of GI practices across a set of candidate locations in a watershed to minimize the total expected runoff under medium-term precipitation uncertainties. Specifically, we first develop a two-stage stochastic programming model. Next, we reformulate this model using perturbed parameters to reduce the requisite computational time and extend it to multi-stage. In addition, we introduce constraints that allow for incorporating sub-catchment-level runoff reduction considerations. Furthermore, we account for hydrological connectivity in the watershed using an underlying acyclic connectivity graph of sub-catchments and incorporate various practical considerations into the models. In addition, we develop a systemic approach to downscale the existing daily precipitation projections into hourly units and efficiently estimate the corresponding hydrological responses. These advancements are brought together in a case study for an urban watershed in a mid-sized city in the U.S., where we perform sensitivity analyses, evaluate the importance of the considered constraints, and provide insights.

54 ENVIRONMENTAL SCIENCES↗