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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Simulating Secure Data Exchange and Storage for Urban Air Mobility Environments

Urban Air Mobility (UAM) defines an environment for managing operations of vertical takeoff and landing (VTOL) and short takeoff and landing (STOL) vehicles in an urban environment. Within a UAM environment, UAM operators manage fleets of vehicles, relying on Providers of Services for UAM (PSUs) for managing flights in a region of airspace. Flight plan deconfliction is primarily performed by the Discovery and Synchronization Service (DSS), and the Federal Aviation Administration (FAA) maintains control over the UAM space via the FAA-Industry Exchange Protocol (FIDXP). UAM is a federated environment with many different entities owning and operating vehicles, PSUs, and other services. These entities often need to interoperate or access data generated by other organizations. This paper demonstrates the feasibility of using blockchain to facilitate a secure data exchange and storage for this flight information in a UAM environment. In particular, this paper is focused on flight plans and telemetry data. A blockchain network was developed with a set of smart contracts for managing relevant flight data. Hyperledger Fabric was chosen as it is performent, scalable, and allows organizations to reuse existing public key infrastructure (PKI) for identity management. A set of simulated UAM services were also developed. These services propose flight plans and negotiate with other UAM services for airspace access. All interactions between UAM services, as well as vehicle telemetry data, is recorded onto the blockchain. Vehicle telemetry data is generated by a vehicle flight simulation service. This paper successfully demonstrates the feasibility of using blockchain as a secure data exchange and storage mechanism in a UAM environment.

UAM↗
NASA NTRSDate not supplied

Immutable Secure Data Exchange and Storage for Urban Air Mobility Environments

Urban air mobility (UAM) is a concept that proposes to develop short-range aerial vehicles to overcome increasing surface congestion. Within the UAM environment, UAM operators work collaboratively to manage aerial vehicles in the urban environment. Providers of Services for UAM (PSU), UAM operators, and Supplemental Data Service Providers (SDSP) provide services to support flight operations within the UAM environment. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. To address these challenges, this research focuses on the secure data exchange and storage of this decentralized UAM environment. The intent of this research is to leverage a permissioned blockchain approach to address cybersecurity threats that may impact a UAM environment.

Urban Air Mobility↗
NASA NTRSDate not supplied

Immutable Secure Data Exchange and Storage for Urban Air Mobility Environments

Urban air mobility (UAM) is a concept that proposes to develop short-range aerial vehicles to overcome increasing surface congestion. Within the UAM environment, UAM operators work collaboratively to manage aerial vehicles in the urban environment. Providers of Services for UAM (PSU), UAM operators, and Supplemental Data Service Providers (SDSP) provide services to support flight operations within the UAM environment. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. To address these challenges, this research focuses on the secure data exchange and storage of this decentralized UAM environment. The intent of this research is to leverage a permissioned blockchain approach to address cybersecurity threats that may impact a UAM environment.

Urban Air Mobility↗
NASA NTRS1994

A GIS approach to urban heat island research: The case of Huntsville, Alabama

The urban heat island represents a case of inadvertent human modification of climate in an urban environment. Urbanization changes the nature of the surface and atmospheric properties of a region. As a result, radiation balance in the urban areas is altered and sensible heat is added to the point that urban areas are warmer than surrounding rural areas. At the boundary between the rural and urban area, a sharp rise in temperature occurs, culminating to a peak temperature at the central business district of the city, hence the name 'urban heat island'. The extent and intensity of the urban heat island are a function of population size, land use, and topography. Because the urban heat island exhibits spatial variations of temperatures, the use of Geographic Information System (GIS) is appropriate. The research on the urban heat island focuses on the acquisition of 15 bands of visible and thermal infrared data (ranging from 0.45 to 12.2 microns) from an aerial platform using NASA's ATLAS (Airborne Thermal/Visible Land Application Sensor) over Huntsville, Alabama. The research reported in this paper is an analysis of the impact of population, land use, and topography on the shape of the urban heat island that could be developed in Huntsville using the GIS approach. The outcome of this analysis can then be verified using the acquired remotely sensed data.

Lo, Chor Pong↗
NASA NTRSDate not supplied

Immutable Secure Data Exchange and Storage for Urban Air Mobility Environments

The Urban Air Mobility (UAM) environment is derived from the Unmanned Traffic Management (UTM) concept of operations. Within the environment, UAM operators work independently to manage aerial vehicles in the urban environment. Providers of Services (PSU), UAM operators, and Supplemental Data Service Providers provide services to support flight operations within the UAM environment. The intent of this work is to leverage a permissioned blockchain approach, to, simulate secure data exchange and storage for UAM environments. Blockchain technologies can be used for identity management of vehicles, people, and systems.

Blockchain↗
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↗
DOE OSTI2022

Urban working groups in the IAEA’s model testing programmes: overview from the MODARIA I and MODARIA II programmes

The IAEA’s model testing programmes have included a series of Working Groups concerned with modelling radioactive contamination in urban environments. These have included the Urban Working Group of Validation of Environmental Model Predictions (1988–1994), the Urban Remediation Working Group of Environmental Modelling for Radiation Safety (EMRAS) (2003–2007), the Urban Areas Working Group of EMRAS II (2009–2011), the Urban Environments Working Group of (Modelling and Data for Radiological Impact Assessments) MODARIA I (2013–2015), and most recently, the Urban Exposures Working Group of MODARIA II (2016–2019). The overarching objective of these Working Groups has been to test and improve the capabilities of computer models used to assess radioactive contamination in urban environments, including dispersion and deposition processes, short-term and long-term redistribution of contaminants following deposition events, and the effectiveness of various countermeasures and other protective actions, including remedial actions, in reducing contamination levels, human exposures, and doses to humans. This paper describes the exercises conducted during the MODARIA I and MODARIA II programmes. These exercises have included short-range and mid-range atmospheric dispersion exercises based on data from field tests or tracer studies, hypothetical urban dispersion exercises, and an exercise based on data collected after the Fukushima Daiichi accident. We report improvement of model capabilities will lead to improvements in assessing various contamination scenarios (real or hypothetical), and in turn, to improved decision-making and communication with the public following a nuclear or radiological emergency.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRSDate not supplied

Immutable Secure Data Exchange and Storage for UAM Environments

Urban Air Mobility (UAM) has become a focus for the next generation of aerial passenger transportation. UAM operations will be leveraging a service-based architecture for airspace solutions. The UAM environment will leverage diverse communications and system access approaches. These approaches include independent Providers of Services for UAM and supplemental data service providers that exchange data between themselves and UAM operators. This research focuses on the secure data exchange and storage of this decentralized UAM environment to address these challenges. This research intends to leverage a permissioned blockchain approach to address cybersecurity threats that may impact a UAM environment.

Urban Air Mobility↗
DOE OSTI2020

Mobility Data and Models Informing Smart Cities

This presentation explores the interactions of Emerging Technology, Changing Urban Environments, and Urban Travel Behavior on Mobility and Energy Impacts. Key findings include quantifying impacts of emerging mobility, access and infrastructure associated with new mobility choices and services in urban areas. The results demonstrate new data collection methods and capabilities to understand and identify key levers to improve energy productivity of future mobility systems and of quickly evolving MaaS and COVID-19 contexts to monitor rapidly shifting urban mobility patterns. Under development are mode choice models for new modes versus traditional modes. Initial estimates are developed on the potential of workforce mobility strategies in shaping future energy-efficient mobility system impacts. For mode replacement and workforce mobility, this presentation offers observability into the changes in number of transactions per mode, after ride-hailing/TNC/MaaS introduction and in origins of workforce to enable user need-driven reimagining of efficient mobility systems: Seattle (SEA-TAC) airport: for every 100 new TNC transactions for ground transportation, ~27% replaced transit, 35% replaced parking, 17% replaced car rentals, and 21% replaced taxis. Similarly, at Denver International (DEN), ride-hailing transactions replaced transit, parking, car rental and taxis at a rate of 34.7%, 39.0%, 16.6%, and 9.7%, respectively. A workforce mobility tool, analysis/visualization techniques, and capabilities to understand and identify key job commute needs, new choices in access to job opportunities, and affordability aspects as levers to improve energy productivity of future integrated urban mobility systems.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2022

Evaluation of Turbulence and Dispersion in Multiscale Atmospheric Simulations over Complex Urban Terrain during the Joint Urban 2003 Field Campaign

Abstract This paper evaluates the representation of turbulence and its effect on transport and dispersion within multiscale and microscale-only simulations in an urban environment. These simulations, run using the Weather Research and Forecasting Model with the addition of an immersed boundary method, predict transport and mixing during a controlled tracer release from the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma. This work extends the results of a recent study through analysis of turbulence kinetic energy and turbulence spectra and their role in accurately simulating wind speed, direction, and tracer concentration. The significance and role of surface heat fluxes and use of the cell perturbation method in the numerical simulation setup are also examined. Our previous study detailed the model development necessary for our multiscale simulations, examined model skill at predicting wind speeds and tracer concentrations, and demonstrated that dynamic downscaling from mesoscale to microscale through a sequence of nested simulations can improve predictions of transport and dispersion relative to a microscale-only simulation forced by idealized meteorology. Here, predictions are compared with observations to assess qualitative agreement and statistical model skill at predicting wind speed, wind direction, tracer concentration, and turbulent kinetic energy at locations throughout the city. We also investigate the scale distribution of turbulence and the associated impact on model skill, particularly for predictions of transport and dispersion. Our results show that downscaled large-scale turbulence, which is unique to the multiscale simulations, significantly improves predictions of tracer concentrations in this complex urban environment. Significance Statement Simulations of atmospheric transport and mixing in urban environments have many applications, including pollution modeling for urban planning or informing emergency response following a hazardous release. These applications include phenomena with spatial scales spanning from millimeters to kilometers. Most simulations resolve flow only within the urban area of interest, omitting larger scales of turbulence and regional influences. This study examines a method that resolves both the small and large-scale flow features. We evaluate simulation accuracy by comparing predictions with observations from an experiment involving the release of a tracer gas in Oklahoma City, Oklahoma, with emphasis on correctly modeling turbulent fluctuations. Our results demonstrate the importance of resolving large-scale flow features when predicting transport and dispersion in urban environments.

42 ENGINEERING↗