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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Unlocking the Potential of Marine Energy Using Hydrogen Generation Technologies

Marine energy, including ocean waves, ocean currents, ocean thermal gradients, tides, and river currents, is a vast and untapped resource that can be harnessed to help enable the transition to renewable energy. Marine energy is an attractive renewable resource because of its energy density, predictability, and persistence. Further, marine energy has the potential to provide energy for utility-scale applications, remote and distributed applications, and rapidly expanding maritime industries, such as aquaculture and shipping. Marine energy technologies are, however, at a nascent stage of development, and a significant amount of the resource is located far from population centers and transmission infrastructure. Accordingly, to unlock the full potential of marine energy, efficient methods of storing and transporting captured marine energy are needed so that the energy can be used when and where it is needed. A promising solution to these energy storage and transportation challenges is to combine marine energy and hydrogen generation technologies. Herein, we provide a high-level analysis of the unique value proposition and technical challenges of combining marine energy and hydrogen technologies. First, we review marine energy technologies, electrolysis technologies, and hydrogen storage methods. Next, we consider specific applications and opportunities for combining the two technologies. Finally, we identify critical R&D challenges that must be overcome to successfully combine marine energy and hydrogen generation technologies. As part of our fact-finding effort in this area, we held a workshop attended by marine energy and hydrogen technology experts from industry, academia, national labs, and government entities to explore the technical challenges and opportunities for combined marine energy and hydrogen generation systems. Our intent is that this document and the report from the workshop can be used in conjunction to help identify and direct research and development that is needed to realize the potential of marine energy-hydrogen systems.

08 HYDROGEN↗
DOE OSTI2023

Community Resilience Options: A Menu for Enhancing Local Energy Resilience

This document highlights areas of potential community resilience improvements, especially those that relate to clean energy deployment for communities and municipalities. The National Renewable Energy Laboratory (NREL) defines resilience as "a system's ability to anticipate, prepare for, and adapt to changing conditions and withstand, respond to, and recover rapidly from disruptions through sustainable, adaptable, and holistic planning and technical solutions." This document introduces 10 categories of resilience-enhancing projects at a high level, intended for community members and decision-makers new to the topic to build their understanding of which solutions fit their community best. These categories focus primarily on community-scale measures and different options may be available at larger scales. Full implementation of the measures described here requires in-depth, site-specific considerations that go beyond the scope of this document.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Connected and Learning Based Optimal Freight Management for Efficiency

The management of the future heterogenous fleet is a complex decision-making problem. The heterogenous fleet is emerging as decarbonization technologies are deployed by fleets toward lowering the freight operation emissions in Medium and Heavy-duty vehicles. Traditionally, in fleets characterized by a homogeneous Diesel Internal Combustion Engine (ICE) powertrain, the process of fleet planning and operational optimization unfolds sequentially without the necessity to account for powertrain and vehicle-specific characteristics during dispatch decisions. Fleets with trucks less than 5 years old tend to maintain stable vehicle efficiency with minimal operational reliability risks for fleet managers. However, the landscape changes with the incorporation of emerging powertrain technologies, which lack extensive operational data and service experiences. This includes technologies like hybrid, Electric, Fuel Cell, or alternative fuel ICE. Operational decisions for fleets featuring heterogeneous powertrain technologies and facing limited access to alternative fueling and charging stations become intricate, requiring careful consideration and optimization at each dispatch. The difference in efficiency characteristics of emerging technologies, their range limitations, and the restricted availability of charging/alternative fueling infrastructure, coupled with sensitivity to driving conditions (e.g., EV range reduction in low temperatures) and their impact on component aging (such as batteries), become pivotal factors influencing the reliable and efficient freight transportation. To make the path toward low emission freight transportation efficient and reliable, an AI-assisted fleet management software is developed in this project to help fleet managers in optimizing both adoption of emerging powertrain decarbonization, connected and automated technologies and also operating the fleet after such technologies are deployed as schematically. Freight transportation requirements are different depending on the cargos to be shipped, customer requirements and regions of operations. This further highlights the need for software and digital solutions to tailor deployment and operation of emerging powertrain, connectivity, and automation technologies toward the specific fleet operation requirements. The fleet management optimizer was also integrated with a model of the fleet to simulate the operation of the fleet over 1 year of the baseline fleet operation (250,000+ shipments) indicating the significance of day-to-day variations on emissions and energy consumption of a freight transportation fleet. The results demonstrate ≥20% improvement in freight efficiency in terms of WTW CO2 per ton-mile of cargo shipments while all fleet operation constraints are enforced, and the cost (CapEx and OpEx) is minimized.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Interconnected Risks in Electricity Systems: Understanding Research Challenges, Needs, and Partnerships

The U.S. federal government has a potential role in mitigating the most poorly addressed risks across electricity markets and interdependent systems. Electricity system risks stem from extreme acute shocks (e.g., cyberattacks, extreme weather, and supply chain disruptions) and chronic stressors (e.g., global economic competition, uncertainties surrounding emerging technologies, climate change, and related conflicts). These acute shocks and chronic stressors can result in dire consequences for society, underscoring the need for better information for decision makers in both public and private sectors. Best practices and a shared understanding of risk management and risk quantification must be rapidly developed and disseminated. Informed by a quantitative treatment of risk to electrical infrastructure and interdependent systems, decision makers can more prudently and efficiently prioritize mitigation initiatives to maximize benefits to government, businesses, and the public.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1993

Modernization of the NASA scientific and technical information program

The NASA Scientific and Technical Information Program utilizes a technology infrastructure assembled in the mid 1960s to late 1970s to process and disseminate its information products. When this infrastructure was developed it placed NASA as a leader in processing STI. The retrieval engine for the STI database was the first of its kind and was used as the basis for developing commercial, other U.S., and foreign government agency retrieval systems. Due to the combination of changes in user requirements and the tremendous increase in technological capabilities readily available in the marketplace, this infrastructure is no longer the most cost-effective or efficient methodology available. Consequently, the NASA STI Program is pursuing a modernization effort that applies new technology to current processes to provide near-term benefits to the user. In conjunction with this activity, we are developing a long-term modernization strategy designed to transition the Program to a multimedia, global 'library without walls.' Critical pieces of the long-term strategy include streamlining access to sources of STI by using advances in computer networking and graphical user interfaces; creating and disseminating technical information in various electronic media including optical disks, video, and full text; and establishing a Technology Focus Group to maintain a current awareness of emerging technology and to plan for the future.

Cotter, Gladys A.↗
NASA NTRS2003

DSMS investment in support of satellite constellations and formation flying

Over the years, NASA has supported unmanned space missions, beyond earth orbit, through a Deep Space Mission System (DSMS) that is developed and operated by the Jet Propulsion Laboratory (JPL) and subcontractors. The DSMS capabilities have been incrementally upgraded since its establishment in the late '50s and are delivered primarily through three Deep Space Communications Complexes (DSCC 's) near Goldstone, California, Madrid, Spain, and Canberra, Australia and from facilities at JPL. Traditionally, mission support (tracking, command, telemetry, etc) is assigned on an individual-mission basis, between each mission and a ground-based asset, independent of other missions. As NASA, and its international partners, move toward flying fullconstellations and precision formations, the DSMS is developing plans and technologies to provide the requisite support. The key activities under way are: (1) integrated communications architecture for Mars exploration, including relays on science orbiters and dedicated relay satellites to provide continuous coverage for orbiters, landers and rovers. JPL is developing an architecture, as well as protocols and equipment, required for the cost-effective operations of such an infrastructure. (2) Internet-type protocols that will allow for efficient operations across the deep-space distances, accounting for and accommodating the long round-trip-light-time. JPL is working with the CCSDS to convert these protocols to an international standard and will deploy such protocol, the CCSDS File Delivery Protocol (CFDP), on the Mars Reconnaissance Orbiter (MRO) and on the Deep Impact (01) missions. (3) Techniques to perform cross-navigation between spacecrafi that fly in a loose formation. Typical cases are cross-navigation between missions that approach Mars and missionsthat are at Mars, or the determination of a baseline for missions that fly in an earth-lead- lag configuration. (4) Techniques and devices that allow the precise metrology and controllability of tightformations for precision constellation missions. In this paper we discuss the four classes of constellatiodformation support with emphasis of DSMS current status (technology and implementation) and plans in the first three areas.

space operations↗
NASA NTRS2008

NASA Langley's AirSTAR Testbed: A Subscale Flight Test Capability for Flight Dynamics and Control System Experiments

As part of the Airborne Subscale Transport Aircraft Research (AirSTAR) project, NASA Langley Research Center (LaRC) has developed a subscaled flying testbed in order to conduct research experiments in support of the goals of NASA s Aviation Safety Program. This research capability consists of three distinct components. The first of these is the research aircraft, of which there are several in the AirSTAR stable. These aircraft range from a dynamically-scaled, twin turbine vehicle to a propeller driven, off-the-shelf airframe. Each of these airframes carves out its own niche in the research test program. All of the airplanes have sophisticated on-board data acquisition and actuation systems, recording, telemetering, processing, and/or receiving data from research control systems. The second piece of the testbed is the ground facilities, which encompass the hardware and software infrastructure necessary to provide comprehensive support services for conducting flight research using the subscale aircraft, including: subsystem development, integrated testing, remote piloting of the subscale aircraft, telemetry processing, experimental flight control law implementation and evaluation, flight simulation, data recording/archiving, and communications. The ground facilities are comprised of two major components: (1) The Base Research Station (BRS), a LaRC laboratory facility for system development, testing and data analysis, and (2) The Mobile Operations Station (MOS), a self-contained, motorized vehicle serving as a mobile research command/operations center, functionally equivalent to the BRS, capable of deployment to remote sites for supporting flight tests. The third piece of the testbed is the test facility itself. Research flights carried out by the AirSTAR team are conducted at NASA Wallops Flight Facility (WFF) on the Eastern Shore of Virginia. The UAV Island runway is a 50 x 1500 paved runway that lies within restricted airspace at Wallops Flight Facility. The facility provides all the necessary infrastructure to conduct the research flights in a safe and efficient manner. This paper gives a comprehensive overview of the development of the AirSTAR testbed.

Jordan, Thomas L.↗
NASA NTRS2016

Evolution of Flexible Multibody Dynamics for Simulation Applications Supporting Human Spaceflight

During the course of transition from the Space Shuttle and International Space Station programs to the Orion and Journey to Mars exploration programs, a generic flexible multibody dynamics formulation and associated software implementation has evolved to meet an ever changing set of requirements at the NASA Johnson Space Center (JSC). Challenging problems related to large transitional topologies and robotic free-flyer vehicle capture/ release, contact dynamics, and exploration missions concept evaluation through simulation (e.g., asteroid surface operations) have driven this continued development. Coupled with this need is the requirement to oftentimes support human spaceflight operations in real-time. Moreover, it has been desirable to allow even more rapid prototyping of on-orbit manipulator and spacecraft systems, to support less complex infrastructure software for massively integrated simulations, to yield further computational efficiencies, and to take advantage of recent advances and availability of multi-core computing platforms. Since engineering analysis, procedures development, and crew familiarity/training for human spaceflight is fundamental to JSC's charter, there is also a strong desire to share and reuse models in both the non-realtime and real-time domains, with the goal of retaining as much multibody dynamics fidelity as possible. Three specific enhancements are reviewed here: (1) linked list organization to address large transitional topologies, (2) body level model order reduction, and (3) parallel formulation/implementation. This paper provides a detailed overview of these primary updates to JSC's flexible multibody dynamics algorithms as well as a comparison of numerical results to previous formulations and associated software.

Multibody dynamics↗
NASA NTRS2019

Cognitive Communications and Networking Technology Infusion Study Report

As the envisioned next-generation SCaN Network transitions into an end-to-end “system of systems” with new enabling capabilities, it is anticipated that the introduction of machine learning, artificial intelligence, and other cognitive strategies into the network infrastructure will result in increased mission science return, improved resource efficiencies, and increased autonomy and reliability. This enhanced set of cognitive capabilities will be implemented via a “space cloud” concept to achieve a service-oriented architecture with distributed cognition, de-centralized routing, and shared, on-orbit data processing. The enabling cognitive communications and networking capabilities that may facilitate the desired network enhancements are identified in this document, and the associated enablers of these capabilities, such as technologies and standards, are described in detail.

Knoblock, Eric J.↗
NASA NTRS2020

Urban Air Mobility System Testbed Using CAVE Virtual Reality Environment

Urban Air Mobility (UAM) refers to a system of air passenger and small cargo transportation within an urban area. The UAM framework also includes other urban Unmanned Aerial Systems (UAS) services that will be supported by a mix of onboard, ground, piloted, and autonomous operations. Over the past few years UAM research has gained wide interest from companies and federal agencies as an on-demand innovative transportation option that can help reduce traffic congestion and pollution as well as increase mobility in metropolitan areas. The concepts of UAM/UAS operation in the National Airspace System (NAS) remains an active area of research to ensure safe and efficient operations. With new developments in smart vehicle design and infrastructure for air traffic management, there is a need for methods to integrate and test various components of the UAM framework. In this work, we report on the development of a virtual reality (VR) testbed using the Cave Automatic Virtual Environment (CAVE) technology for human-automation teaming and airspace operation research of UAM. Using a four-wall projection system with motion capture, the CAVE provides an immersive virtual environment with real-time full body tracking capability. We created a virtual environment consisting of San Francisco city and a vertical take-off-and-landing passenger aircraft that can fly between a downtown location and the San Francisco International Airport. The aircraft can be operated autonomously or manually by a single pilot who maneuvers the aircraft using a flight control joystick. The interior of the aircraft includes a virtual cockpit display with vehicle heading, location, and speed information. The system can record simulation events and flight data for post-processing. The system parameters are customizable for different flight scenarios; hence, the CAVE VR testbed provides a flexible method for development and evaluation of UAM framework.

Marayong, Panadda↗
NASA NTRSDate not supplied

Historical Domestic Flights from 2016-2020 with Estimations of Greenhouse Gas Emissions by Aircraft Type

Data and analyses are presented on the utilization of aircraft fuel in the U.S. and the greenhouse gas emissions that they create. Aggregated commercial passenger and freight aviation flight data from 2016-2020 is captured from the Bureau of Transportation Statistics website is used to augment flight data from the Sherlock data warehouse at NASA Ames is used to determine the miles flown by major aircraft models. The corresponding fuel burn is estimated using the International Civilian Aviation Organization fuel burn tables and carbon dioxide emissions are calculated using a fuel-burn multiplicative factor. One key conclusion of this analysis is that long haul flights (i.e. >2485 statute miles) create a disproportionately large amount of carbon dioxide emissions in the U.S while short flights (i.e. < 311 statute miles) contribute less than five percent of the U.S. aviation-related carbon dioxide emission. Although these short-haul flights may not have a large impact on overall carbon dioxide emissions, they will be a critical entry point for the adoption of future, larger fuel-efficient novel vehicles and the impact to future airport and infrastructure requirements. The final paper will present some estimates of the impact of advanced technologies on fuel burn and CO₂ emissions in various scenarios.

Susie Go↗
NASA NTRSDate not supplied

NASA and Advanced Air Mobility (AAM) National Campaign (NC) Tech Talk: Integrated Data Product

NASA Advanced Air Mobility (AAM) National Campaign has hosted multiple flight tests in a effort to promote public confidence and accelerate the realization of emerging aviation markets for passenger and cargo transportation in urban, suburban, rural, and regional environments. The goals and objectives for each flight test are intended to assess the performance of the vehicle’s capacity to operate safely, efficiently, and sustainably in urban areas. The Airspace Test and Infrastructure (ATI) team processes the flight data to evaluate the effectiveness of air vehicle and airspace management integration, while its analysis capabilities support the assessment of the efficacy of proposed vehicles and ground systems required to enable the vehicles’ operations. The ATI data services team creates many products from the data, first by transforming and merging the data into a single Integrated Data Product (IDP). This aligns data from many sources by time, so that, for example, the winds that impacted a flight can be aligned with its ground track and speed. A detailed IDP enables many types of statistical computation and visualizations that help researchers understand what transpired during the flight and how it can be explained. This Tech Talk will give an overview of the IDP process, including examples of the resulting products created by the data services team. It will also share an application that will allow participants to perform their own data analysis.

National Campaign, Advanced Air Mobility, Integrat↗
NASA NTRSDate not supplied

NASA Space Communications and Navigation: One Network Evolution

The NASA Space Communications and Navigation (SCaN) Program is responsible for providing the essential connectivity to robotic and human space explorers. The missions relying on SCaN range from suborbital and balloon missions to those traveling beyond the edge of the solar system. The demands for communications and navigation services enabled by SCaN (and its affiliated partners) are projected to increase and outpace the current network capacity. At the same time, the Agency finds itself surrounded by a burgeoning commercial space marketplace, technological advancement, and other government agencies that share common interests in space resiliency, robustness, and performance. As a result, SCaN has begun pivoting toward commercial services and collaborating with partners to close capacity and capability gaps. Given these growing demands of the Agency there is increasing need for multi-network solutions. Future mission concepts will rely on both government and commercial capabilities, both Near Space Network capacity and Deep Space Network capacity. Integrating these diverse support services together from a technical, programmatic and implementation standpoint will be key to meet the growing needs of the future. To accomplish this, a more substantive shift is required, and SCaN is reshaping itself to be a customer-centric, service-oriented, high-performance leader in the space communications community. This paper outlines the SCaN One Team, One Mission, One Network approach, and provides a vision for future mission community experience that includes streamlined mission commitment interfaces and clear processes, dynamic network scheduling and load balancing, and higher efficiency data transport and delivery through the integration of cloud infrastructure and services.

Near Space Network↗
NASA NTRSDate not supplied

Materials Informatics at NASA GRC: Machine Learning Surrogate Modeling, Data Management, and Integrated Toolsets for Establishing/Maintaining the Digital Thread

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which heavily depend on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results that is findable and usable, along with integrated, efficient toolsets for effectively passing information across various length and time scales across such models. At the NASA Glenn Research Center under the Transformational Tools and Technologies Project, significant recent efforts have been directed towards establishing the required cyberinfrastructure to enable optimized ICME processes and the design of “fit-for-purpose” materials to achieve the goals outlined in the NASA Vision 2040 report. Such efforts include development of multiscale physics-based material models, which can be used to train highly efficient surrogate machine learning models, development of best practices and infrastructure for effective, traceable materials information management, and development of toolsets that integrate with physics-based codes, machine learning models, and an information management system to enable high throughput of materials data collection and analysis, establishment of digital twins and the digital thread, and automation of the ICME design process for material optimization.

Machine Learning↗
DOE OSTI2020

A Community Energy Operations and Planning System: Concept, Use cases, Metrics, and Benefits

Community and city leaders are interested in achieving sustainability goals, providing resilient energy infrastructure, and improving economic competitiveness. Community-level data acquisition and analysis can provide energy and associated benefits that are not possible at the single building level. However, there is a lack of organizational structure, common semantic data models, interoperable systems, and methods to support data-driven decision-making for community-scale energy supply and demand systems. We explored the need and opportunity for a Community Energy Operations and Planning System (Community EOPS), a potential data exchange platform. We conducted “customer discovery” interviews, and reviewed literature, public tools, and technology platforms to identify key energy data “users” and use cases in communities. The key users of the Community EOPS could be developers of mixed-use districts, corporate, defense and university campus energy managers, and city managers of cities that own their energy utility. The value could be for community planning and reporting (for energy data-integrated land use planning and community infrastructure investments in microgrids, storage, district heating and cooling), energy efficiency (leveraging optimizations for community scale energy supply and demand), flexible load management (grid-edge load management to offset, shift, and flatten loads for multiple buildings and EV fleets), cost savings and revenue generation (participating in grid services), and social benefits such as energy resilience, equity, and awareness. We developed a conceptual Community EOPS architecture with recommendations for streamlined and prioritized data acquisition, sharing, and integration driven by prioritized use cases, common metrics, and actionable visualizations that can provide value to a community’s users.

Singh, Reshma↗
DOE OSTI2024

Summary of Federal and State Funding Sources for the Solid Waste and Wastewater Sectors

This quick-reference sheet provides a list of funding programs for the solid waste and wastewater sectors available at the national state levels. These funding programs are related to existing infrastructure improvements, as well as the development of new energy efficiency and renewable energy systems (including waste-to-energy).

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Optimization of distributed compute resources utilization in the CMS Global Pool

The CMS Submission Infrastructure is the primary system for managing computing resources for CMS workflows, including data processing, simulation, and analysis. It integrates geographically distributed resources from Grid, HPC, and cloud providers into federated pools managed by HTCondor and Glidein- WMS, for a total of around 500k CPU cores. This system dynamically manages workloads based on priorities defined by the collaboration. Additionally, CMS scheduling strategies must be flexible to handle multiple concurrent workloads while considering changing processing demands and resource availability from various providers.Efficient utilization of vast amounts of distributed compute resources is a key element for the success of the scientific programs of the LHC experiments. Optimizing the system is essential to maximize resource efficiency and fully utilize the distributed computing power. The CMS Submission Infrastructure team thus systematically investigates sources of inefficiency in workload scheduling to reduce their impact. In addition, a strategy of pilot overloading has been introduced to compensate for other inefficiency sources, thereby optimizing resource utilization and enhancing computational throughput.

Mascheroni, Marco [UC, San Diego (main)]↗
DOE OSTI2023

ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud Continuum

Modern scientific workflows require hybrid infrastructures combining numerous decentralized resources on the IoT/Edge interconnected to Cloud/HPC systems (aka the Computing Continuum) to enable their optimized execution. Understanding and optimizing the performance of such complex Edge-to-Cloud workflows is challenging. Capturing the provenance of key performance indicators, with their related data and processes, may assist in understanding and optimizing workflow executions. However, the capture overhead can be prohibitive, particularly in resource-constrained devices, such as the ones on the IoT/Edge.To address this challenge, based on a performance analysis of existing systems, we propose ProvLight, a tool to enable efficient provenance capture on the IoT/Edge. We leverage simplified data models, data compression and grouping, and lightweight transmission protocols to reduce overheads. We further integrate ProvLight into the E2Clab framework to enable workflow provenance capture across the Edge-to-Cloud Continuum. This integration makes E2Clab a promising platform for the performance optimization of applications through reproducible experiments.We validate ProvLight at a large scale with synthetic workloads on 64 real-life IoT/Edge devices in the FIT IoT LAB testbed. Evaluations show that ProvLight outperforms state-of-the-art systems like ProvLake and DfAnalyzer in resource-constrained devices. ProvLight is 26—37x faster to capture and transmit provenance data; uses 5—7x less CPU; 2x less memory; transmits 2x less data; and consumes 2—2.5x less energy. ProvLight [1] and E2Clab [2] are available as open-source tools.

Rosendo, Daniel↗