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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 271 records · Page 15

Deposition of Nanostructured Thin Film from Size-Classified Nanoparticles

Materials comprising nanometer-sized grains (approximately 1_50 nm) exhibit properties dramatically different from those of their homogeneous and uniform counterparts. These properties vary with size, shape, and composition of nanoscale grains. Thus, nanoparticles may be used as building blocks to engineer tailor-made artificial materials with desired properties, such as non-linear optical absorption, tunable light emission, charge-storage behavior, selective catalytic activity, and countless other characteristics. This bottom-up engineering approach requires exquisite control over nanoparticle size, shape, and composition. We describe the design and characterization of an aerosol system conceived for the deposition of size classified nanoparticles whose performance is consistent with these strict demands. A nanoparticle aerosol is generated by laser ablation and sorted according to size using a differential mobility analyzer. Nanoparticles within a chosen window of sizes (e.g., (8.0 plus or minus 0.6) nm) are deposited electrostatically on a surface forming a film of the desired material. The system allows the assembly and engineering of thin films using size-classified nanoparticles as building blocks.

Camata, Renato P.↗

A Data-Driven Reduced Order Model of an Isolated Rotor

There are numerous conceptual design stage rotorcraft analysis tasks which demand a high-fidelity and low cost method for rotor load distribution predictions. Considering Urban Air Mobility (UAM) vehicles aim to operate in close proximity to buildings and with unique rotor configurations, there is a significant challenge in quickly and accurately modeling rotors operating in complex, turbulent flow fields. One potential path for deriving a high-fidelity, low cost rotor model is with data-driven surrogate modeling. In this study, an initial investigation is taken to apply a proper orthogonal decomposition (POD) based reduced order model (ROM) for the purpose of pressure distribution prediction. In this study, a POD ROM was derived to produce distributed pressure predictions on rotor blades subjected to topology change due to variation in twist and taper ratio. Rotor twist was varied between 0◦, 10◦, 20◦, and 30◦ while taper ratio was varied between 1.0, 0.9, 0.8, and 0.7. All rotors consisted of a single blade. The POD ROM was validated for three demonstration cases; a high thrust rotor in hover, a low thrust rotor in hover, and a rotor in forward flight with a flight speed of M = 0.1. Results showed highly accurate distributed load predictions could be achieved at minimal computational cost. Computational cost for hovering blade surface pressure modeling was reduced from 12 hours on 440 cores to 10−5 seconds on a single core. For blade in forward flight cost was reduced from 20 hours on 440 cores to 0.6 seconds on a single core. For cases of high thrust and low thrust rotors, POD ROM was used to undergo a design optimization of the rotor such that figure of merit was maximized. Total optimization time for each case was 1 minute.

Data-Driven↗

Mobile radio alternative systems study satellite/terrestrial (hybrid) systems concepts

The use of satellites for mobile radio service in non-urban areas of the United States in the years from 1985 to 2000 was investigated. Several satellite concepts are considered: a system with single-beam coverage of the fifty United States and Puerto Rico, and multi-beam satellites with greater capacity. All of the needed functions and services identified in the market study are provided by the satellite systems, including nationwide radio access to vehicles without knowledge of vehicle location wideband data transmission from remote sites, two way exchange of short data and control messages between vehicles and dispatch or control centers, and automatic vehicle location (surveillance). The costs of providing the services are within acceptable limits, and the desired returns to the system investors are attractive. The criteria by which the Federal Communication judges the competing demands for public radio spectrum are reviewed with comments on how the criteria might apply to the consideration of land mobile satellites. Institutional arrangements for operating a mobile satellite system are based on the present institutional arrangements in which the services are offered to the end users through wireline and radio common carriers, with direct access by large private and government users.

Kiesling, J. D.↗

Analysis of Electrical Grid Capacity in Major U.S. Metropolitan Areas for Urban Air Mobility

A wide range of challenges must be overcome to conduct Urban Air Mobility (UAM) operations at scale with electric vertical takeoff and landing aircraft as envisioned. This paper documents an analysis of one potential infrastructure challenge for UAM: available electrical grid power capacity. The success of UAM depends on the availability of electricity, which will be increasingly impacted by the proliferation of ground electric vehicles (EVs) over time. Under the worst-case assumption that each U.S. Metropolitan Statistical Area (MSA) can only access and utilize the electricity generated by power plants within its boundaries, it is estimated that the maximum number of UAM aircraft that can charge simultaneously in the 25 most populous MSAs will decrease by about 61% from about 129,000 in the year 2021 to about 51,000 in the year 2050, due to the projected increase in ground EVs. Also, it is estimated that the number of these MSAs that may lack any available electrical grid power capacity for UAM operations will increase from zero MSAs in 2021 to eleven MSAs in 2050—including three MSAs that prospective UAM operators have announced as target markets (Los Angeles, Miami, and Orlando)—unless electricity demand for other purposes is reduced.

electrical grid↗

Unlocking the value of recycling scrap from Li-ion battery manufacturing: Challenges and outlook

The growing global trend toward mobile electrification is primarily driven by the rising popularity of electric vehicles, leading to an unprecedented surge in demand for lithium-ion batteries. As a result, the importance of battery recycling has become increasingly apparent. Battery recycling aims to recover valuable materials from both spent batteries and battery manufacturing scraps. By recycling these resources, the reliance on raw material extraction is reduced, which benefits resource conservation and minimizes the need for new mining operations. While significant attention has been given to the recycling of spent batteries, less emphasis has been placed on the recycling and recovery of battery scraps. However, it is important to recognize that many gigafactories are still taking steps to improve their manufacturing processes, and end-of-life batteries take approximately 10 years to become suitable for recycling, the manufacturing scraps will serve as the primary sources for recycling in this decade. This review delves into the progress in recycling technologies associated with battery manufacturing scraps, shedding light on the challenges, opportunities, and evolving perspectives surrounding battery manufacturing scrap recycling. In conclusion, we aim to contribute to the knowledge base of battery manufacturing scrap recycling and promote a more comprehensive understanding of the subject.

25 ENERGY STORAGE↗

USAID Colombia Young Leaders Workforce Training Program Action Plans: Planning for Electric Vehicle Charging Infrastructure in Bogotá

As part of the U.S. Agency for International Development (USAID)-National Renewable Energy Laboratory (NREL) Young Leaders Workforce Training Program in Colombia, the Grupo Energía Bogotá (GEB) participants leveraged their training and professional experience to develop an action plan for modeling and evaluating Bogotá's projected electric vehicle (EV) charging needs to meet future demand. This case study summarizes the collaboration between USAID-NREL, GEB, and the Bogotá Department of Transportation Mobility Secretariat (SDM) to estimate EV charging station needs to meet projected future EV sales in the city of Bogotá and determine high-priority locations within the greater Bogotá metropolitan area for planning and applying EVSE investment and installation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Communication Requirements in 5G-Enabled Healthcare Applications: Review and Considerations

Fifth generation (5G) mobile communication technology can enable novel healthcare applications and augment existing ones. However, 5G-enabled healthcare applications demand diverse technical requirements for radio communication. Knowledge of these requirements is important for developers, network providers, and regulatory authorities in the healthcare sector to facilitate safe and effective healthcare. In this paper, we review, identify, describe, and compare the requirements for communication key performance indicators in relevant healthcare use cases, including remote robotic-assisted surgery, connected ambulance, wearable and implantable devices, and service robotics for assisted living, with a focus on quantitative requirements. We also compare 5G-healthcare requirements with the current state of 5G capabilities. Finally, we identify gaps in the existing literature and highlight considerations for this space.

5G networks↗

Space Station Freedom accommodation of the Human Exploration Initiative

The design requirements of the Space Station Freedom (SSF) are proposed based on the requirements and assumptions of the Human Exploration Initiative. In this summary of a NASA study consideration is given to the mission-supporting capabilities needed to sustain support of a continuous human presence in earth orbit for scientific activities. The initial SSF configuration (called Assembly Complete) is found to be insufficient in terms of the optimal provisions for crew size, power, pressurized volume, and truss structure. Specific design requirements are also given for the Lunar Transfer Vehicle, and the checkout of this vehicle creates additional demands on the SSF facilities. General specifications are given for the SSF modules, vehicle processing, remote manipulator, and mobile transporter within the context of a continuous human presence in orbit.

Meredith, Barry D.↗

Corridor Design and Analysis for UAM Operations

The Urban Air Mobility (UAM) concept is a part of Advanced Air Mobility (AAM), a joint initiative between the Federal Aviation Administration (FAA), NASA, and industry to develop an air transportation system that uses new electric (i.e., green) air vehicles in geographical areas previously underserved by traditional aviation. Market forecast studies predict that there will be demand for alternate modes of air transportation using electric Vertical Take-off and Landing aircraft. UAM expands transportation networks by introducing short flights to move people and goods around metropolitan areas​. UAM is expected to improve mobility for the public, decongest road traffic, reduce trip time, and decrease strain on existing public transportation networks. Various challenges exist to make the introduction of UAM operations successful in the U.S. National Airspace System (NAS). These include but are not limited to integration with existing airports and airspace, provision of air traffic services (e.g., separation), vehicle design and certification, and community acceptance. The focus of this paper is on integration of UAM operations into the NAS via introduction of new airspace structures. UAM will operate within a regulatory, operational, and technical environment that is incorporated into the NAS​. As per the UAM Concept of Operations (ConOps), the FAA retains regulatory authority and is responsible for establishing operational parameters and maintaining oversight. The FAA’s UAM ConOps describes flights at low altitudes (below 5,000 ft) with minimal disruption to established conventional aircraft traffic and limited voice interactions with the Air Traffic Control (ATC). Early stages of UAM may use existing procedures to safely integrate UAM with conventional flights. This would involve flying under Part 91 Visual Flight Rules (VFR) and using voice for communications. The initial UAM ecosystem will utilize the current infrastructure such as routes, helipads, and ATC services, where practicable. ​A NASA study explored the use of existing helicopter routes in Dallas Fort Worth (DFW) airspace for initial UAM operations with a Letter of Agreement (LOA) that included procedures to request a Class B (controlled airspace) clearance. The research showed that the chosen approach was feasible for near-term, low-demand UAM traffic, but was not scalable. The growth of operations in today’s aviation system has resulted in airspace reorganization and procedures to ensure safety and efficiency as traffic rates increase. One proposed operating innovation that can help with the scalability of UAM is establishing routes and corridors. This may look similar to the Area Navigation (RNAV) procedures used today to streamline operations into busy airports. However, instead of FAA automation systems and ATC managing the flow of traffic, some UAM concepts envision a third-party service provider performing this role as part of the Provider of Services for UAM (PSU) network. The FAA’s UAM ConOps posits that new airspace structures such as UAM corridors include the following design criteria: 1) Minimal impact on existing NAS operations, 2) no or minimal additional ATC services, 3) public interest considerations such as noise, safety, and security, and 4) customer needs. The airspace available in urban environments is limited by the height of buildings, the effect of weather including wind gusts, privacy needs, and a clearance envelope. The new airspace structure would need to be designed around large airports and urban areas where the initial market demand is likely to exist. NASA has started evaluating airspace in the Dallas Fort Worth area to design new airspace structures, keeping the first two design criteria in mind. It is assumed that there will be an on-board pilot-in-command, and the flights will operate under VFR in Visual Meteorological Conditions. Corridors will be required in controlled airspace, whereas UAM operations can fly in uncontrolled Class G and E airspace using current day rules. Keeler et. al identified factors and heuristics for development of routes for UAM operations for integration with airspace close to large airports such as Dallas Fort Worth and Dallas Love Field. This paper describes the heuristics applied to define the corridors, analyzes them with respect to legacy traffic and presents key results.

Urban Air Mobility↗

Estimation of the demand for public services communications

Market analyses and economic studies are presented to support NASA planning for a communications satellite system to provide public services in health, education, mobile communications, data transfer, and teleconferencing.

Source record↗

COMBLE Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility recently concluded its Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE), with its campaign emphasis on marine boundary-layer clouds and mixed-phase clouds during cold-air outbreaks. The COMBLE campaign featured the deployment of the first ARM Mobile Facility (AMF1) to northern Scandinavia (Andenes, Norway), including its standard complement of ARM cloud radars. In keeping with user demands stemming from the previous AMF Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina, a post-campaign radar mentor effort was initiated for COMBLE. This activity was intended to improve the usability of the ARM cloud radar data sets in response to overall demands for calibrated, corrected data sets for downstream studies and retrieval applications. In addition to the terrain complexities previously important to CACTI data sets (e.g., clutter designation and/or removal), COMBLE presented new challenges to existing ARM radar mentor capabilities. These included the extension of existing methodologies (e.g., relative calibration adjustment [RCA] target techniques) to frozen environments and the potential issues with their applicability when considering mixed-phase precipitation conditions. As in the previous CACTI documentation (Hardin et al. 2020), the overall calibration and conditioning process in ARM nomenclature is referred to as generating a “b1” datastream. For the radars, these “b1” standards refer to a datastream that has been calibrated (and cross-calibrated), with effort to deliver the highest-quality (well-characterized) data possible. The “b1” radar mentor reporting (this current document) is intended to detail (i) the status/quality of the original “a1” (raw) data sets during the COMBLE AMF campaign, (ii) the corrections and calibrations that are applied to generate the b1 datastreams available on ARM’s Data Discovery, and (iii) the details of the applied methods, e.g., how radar offset/calibration numbers were determined.

54 ENVIRONMENTAL SCIENCES↗

Emerging Trends in Freight [Slides]

Freight transportation accounts for only 5% of the vehicles on U.S. roads, but 10% of vehicle miles of travel and 27% of on-road energy use. With rail and water, freight accounts for 28% of U.S. transportation energy and emissions. Trucking is the primary mode for transporting goods, but rail is a significant mode for longer shipments. Economic, technological, and operational trends pose both challenges and opportunities to meet U.S. demand for goods movement as well as national decarbonization goals. This presentation provides a systems perspective for energy efficiency freight mobility and an overview of available NREL analytical tools to address these challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.

GNSS↗

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.

GNSS↗

Process design and techno-economic analysis for bio-based graphite and liquid hydrocarbons production from lignocellulosic biomass

The worldwide demand for graphite, as the main anode material for Li-ion batteries, is expected to double by 2028 since it supports the use of electricity, including transient renewable sources, for energy storage, sustainable mobility, and automation. However, the dependence on non-renewable and external resources jeopardizes the world supply chain. This study explores the technical and economic performance of transforming lignocellulosic biomass into biographite and fuel-grade hydrocarbons through pyrolysis bio-oil upgrading. According to simulation results, the total power demand for the biorefinery reached 10,784 kWh per tonne of biographite, of which 36 % can be supplied by the heat integration network and power plant. Sensitivity and risk analyses were conducted to evaluate the economics, with process yields identified as the most relevant indicators to the minimum selling price (MSP). The analysis revealed a promising cost-competitive range for biographite MSP against fossil-based graphite (medium quality synthetic graphite Chinese market price ~$\$$4.2/kg). Case D, which includes biofuels as a byproduct, presents the best metrics, reaching a MSP of $\$$3.3/kg of anode-grade biographite with a profit margin of 27 %. While including biofuels in the product slate provides the best economic performance, the uncertainty associated with the big capital investment makes its risk 13 % higher to attain an IRR >20 % than the case in which biographite is produced as a standalone product. Overall, this study demonstrates that integrated biorefineries can produce a cost-competitive bio-based anode material for Li-ion batteries.

09 BIOMASS FUELS↗

Aeronautical mobile TDMA/MCTDMA system

A multiple carrier Time Division Multiple Access (TDMA) system capable of supporting voice, stream data, and packet data traffic between aircraft and ground terminals is presented. Demand assignment permits efficient resource sharing for voice and stream data. The bandwidth efficiency of uncoded A Quadrature Phase Shift Keying (AQPSK) is 1 bps/Hz. High time efficiency (approximately equals 83 percent) is achieved through the use of symbol synchronous TDMA. Demodulation is achieved without loop hang-up while requiring only a 16 symbol preamble each burst. A concatenated coding system provides reliable transmission under multipath conditions.

Magill, Thomas↗

Street context of various demographic groups in their daily mobility

Abstract We present an urban science framework to characterize phone users’ exposure to different street context types based on network science, geographical information systems (GIS), daily individual trajectories, and street imagery. We consider street context as the inferred usage of the street, based on its buildings and construction, categorized in nine possible labels. The labels define whether the street is residential, commercial or downtown, throughway or not, and other special categories. We apply the analysis to the City of Boston, considering daily trajectories synthetically generated with a model based on call detail records (CDR) and images from Google Street View. Images are categorized both manually and using artificial intelligence (AI). We focus on the city’s four main racial/ethnic demographic groups (White, Black, Hispanic and Asian), aiming to characterize the differences in what these groups of people see during their daily activities. Based on daily trajectories, we reconstruct most common paths over the street network. We use street demand (number of times a street is included in a trajectory) to detect each group’s most relevant streets and regions. Based on their street demand, we measure the street context distribution for each group. The inclusion of images allows us to quantitatively measure the prevalence of each context and points to qualitative differences on where that context takes place. Other AI methodologies can further exploit these differences. This approach presents the building blocks to further studies that relate mobile devices’ dynamic records with the differences in urban exposure by demographic groups. The addition of AI-based image analysis to street demand can power up the capabilities of urban planning methodologies, compare multiple cities under a unified framework, and reduce the crudeness of GIS-only mobility analysis. Shortening the gap between big data-driven analysis and traditional human classification analysis can help build smarter and more equal cities while reducing the efforts necessary to study a city’s characteristics.

Salgado, Ariel (ORCID:0000000177015372)↗

Exploring urban typologies using comprehensive analysis of transportation dynamics

Abstract As urban areas continue to expand and develop, categorizing cities into typologies offers a valuable framework for understanding metropolitan dynamics and fostering inter-city collaboration. However, existing typologies related to urban mobility have limitations, failing to consider cities within a single large urban region and often overlooking crucial dimensions such as trip demand and traffic flow. In this paper, we introduce a transportation-focused characterization for cities within a large urban region, specifically the San Francisco Bay Area, California. We incorporate over 40 metrics across five transportation dimensions: trip demand, road network, multi-modal network, traffic flow, and land use. Specifically, for the trip demand dimension, we include metrics capturing residents’ trip characteristics, such as mode share, intra-city trips, and inter-city trips. Additionally, we analyze the purpose of trips entering the city to gain a deeper understanding of incoming trip patterns. In the traffic flow dimension, we examine metrics like vehicle miles traveled, delay, and congestion to assess the traffic conditions on the street network. These, combined with other dimensions, provide a comprehensive view of a city’s transportation dynamics. Using unsupervised machine learning clustering methods, we identified eight distinct typologies for the Bay Area: Live Work Cities; Job and Activity Magnet Cities; Anchor Cities; Multi-modal Cities; Hyper-connected Cities; Low-density Residential Cities; Medium-density Residential Cities; and Mixed-use Residential Cities. Our findings show that many clusters are strongly influenced by trip demand and traffic flow metrics. Finally, we examine the practicality of this typology and its potential to guide collaborative transportation management strategies. The typologies provide a foundation for dialogue among Bay Area cities, focusing on evaluating shared characteristics and leveraging successes or challenges to develop unified strategies for transportation management.

Kuncheria, Anu↗