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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Combining Satellite Data and Spatial Analysis to Assess the UHI Amplitude and Structure within Urban Areas: The Case of Moroccan Cities

Landsat-8 surface temperature and the European Space Agency land cover are used to assess the impact of land cover on the Urban Heat Island (UHI) and Urban Heat Sink (UHS). We analyzed five Moroccan cities selected for their different local climate, size, and typology during summer at three different spatial scales. The results show multiple causes defining the different forms and amplitudes of the UHI, namely: the ambient climate, the proximity to the sea, the presence of landscaped areas, and the color of building roofs and walls. Contrary to what was expected, the vegetation was not systematically an island of coolness, either because of its typology or its irrigation status. In the coastal cities of Tangier and Casablanca, UHIs around 20°C are observed on the seaside, whereas a UHS of up to 11°C is observed between the city center and the southern periphery of Casablanca. A moderate amplitude UHI of 7°C is formed in the mountainous city of Ifrane. For cities built in desert-like environments, well-defined UHSs between 9°C and 12°C are observed in Smara and Marrakech, respectively. At a finer scale, towns recorded lower temperatures than their immediate surroundings, which are attributed to evaporation from irrigated plants.

Laila El Ghazouani↗
NASA NTRSDate not supplied

Integrated Handling Qualities Safety Analysis For Conceptual Design of Urban Air Mobility Vehicles

The recent emergence of distributed electric propulsion Vertical Takeoff and Landing (VTOL) aircraft has created a rapid introduction of new design concepts with unique stability and control characteristics. A challenge to realizing the full potential of these vehicles for urban transportation is to gain public acceptance which is largely driven by flight safety. This paper describes ongoing research to address the feasibility of integrating flying qualities safety metrics into conceptual design of VTOL Urban Air Mobility (UAM) vehicles. The discussion is composed of the approach and progress toward a toolbox that integrates with existing NASA rotorcraft design software and processes. Several key challenges are highlighted including modeling requirements for failures, identification of critical failures, and capturing critical failures, with robustness to model uncertainty. A discussion of requirements for safety metrics, specific to UAM vehicles, as well as the effects of the control system design is also included. Results to date have demonstrated the degradation in flying qualities metrics due to propulsion failures.

George Altamirano↗
NASA NTRS2023

High-Fidelity Simulations of a Tiltwing Vehicle for Urban Air Mobility

NASA is playing an important role in the development of the urban air mobility ecosystem by identifying key research areas and establishing a fleet of conceptual reference vehicles for urban air mobility applications. This paper delves deeper into the study of NASA’s six-passenger tiltwing air taxi aerodynamics using high-fidelity computational fluid dynamics simulations. NASA’s OVERFLOW flow solver has been loosely-coupled with the rotorcraft comprehensive analysis code CAMRAD II. Dual-time stepping, high-order accurate schemes, and the delayed detached-eddy simulation are employed. The tiltwing configuration is analyzed in airplane and helicopter mode, with flight conditions representative of an air taxi mission. Airloads, wake geometry, and performance are studied to identify the unique flow features of this configuration. NASA’s tiltwing vehicle is one of the conceptual designs intended to focus and guide NASA’s research activities in support of aircraft development for vertical take-off and landing air taxi operations.

RVLT↗
NASA NTRSDate not supplied

Accuracy Assessment of Two Gps Fidelity Prediction Services in Urban Terrain

Low altitude flight in urban areas is susceptible to degraded GNSS-based navigation system performance due to terrain interference with radio signals from orbital positioning satellites. Predictive navigation performance fidelity tools are needed a) in preflight planning to assist in the creation of safe flight paths and b) in-flight to provide contingency management agents with the navigation risk of proximal flight corridors. Two navigation fidelity prediction services are validated by comparison with over 6000 readings from GNSS sensors collected along a five-mile path through urban areas of Corpus Christi, Texas, on three dates in 2022. Predictions are based on satellite line of sight through 3D terrain data collected in 2018. Each service predicts a set of navigation fidelity metrics over a user-specified time period. One metric estimated by both is the number of visible satellites. A direct comparison of the number of predicted visible satellites with the number sensed by the receiver is used to validate the prediction services. Results show an exact match in the number of predicted satellites for 60% of the measurements, and a match within +/- 4 satellites for 95% of the measurements. As expected, agreement improves away from vertical blocking terrain. Most cases of mismatch are due a lower predicted count than measured (false negatives), and can be accounted for by receiver pickup of stray signals caused by multipath propagation. About 10% of mismatches are false positives and are mostly accounted for by foliage effects. The two services predict visibility of the same set of satellites 80% of the time, differ by two or less satellites 95% of the time, and can compute predictions for one hour of observations in one minute or less. Validation is analyzed statistically and in detailed case studies of selected observation times. The prediction services validated in this study run fast enough for preflight safety planning. The more stringent challenge of inflight navigation fidelity prediction for contingency management requires both a speedup of the current level of modeling and equally fast stray signal modeling.

Andrew Moore↗
NASA NTRSDate not supplied

Accuracy Assessment of Two GPS Fidelity Prediction Services in Urban Terrain

Low altitude flight in urban areas is susceptible to degraded GNSS-based navigation system performance due to terrain interference with radio signals from orbital positioning satellites. Predictive navigation performance fidelity tools are needed a) in preflight planning to assist in the creation of safe flight paths and b) in-flight to provide contingency management agents with the navigation risk of proximal flight corridors. Two navigation fidelity prediction services are validated by comparison with over 6000 readings from GNSS sensors collected along a five-mile path through urban areas of Corpus Christi, Texas, on three dates in 2022. Predictions are based on satellite line of sight through 3D terrain data collected in 2018. Each service predicts a set of navigation fidelity metrics over a user-specified time period. One metric estimated by both is the number of visible satellites. A direct comparison of the number of predicted visible satellites with the number sensed by the receiver is used to validate the prediction services. Results show an exact match in the number of predicted satellites for 60% of the measurements, and a match within +/- 4 satellites for 95% of the measurements. As expected, agreement improves away from vertical blocking terrain. Most cases of mismatch are due a lower predicted count than measured (false negatives), and can be accounted for by receiver pickup of stray signals caused by multipath propagation. About 10% of mismatches are false positives and are mostly accounted for by foliage effects. The two services predict visibility of the same set of satellites 80% of the time, differ by two or less satellites 95% of the time, and can compute predictions for one hour of observations in one minute or less. Validation is analyzed statistically and in detailed case studies of selected observation times. The prediction services validated in this study run fast enough for preflight safety planning. The more stringent challenge of inflight navigation fidelity prediction for contingency management requires both a speedup of the current level of modeling and equally fast stray signal modeling.

Andrew J. Moore↗
NASA NTRSDate not supplied

Joint Communication Resource Allocation and Velocity Selection in Urban Air Mobility via Multi-agent Reinforcement Learning

With traffic congestion problems becoming more severe in urban areas, the National Aeronautics and Space Administration promotes the Urban Air Mobility (UAM) concept, which envisages a safe and efficient air transportation system. However, the increased communication demands in UAM can exacerbate the spectrum scarcity. Therefore, a new communication resource allocation solution is necessary. In this paper, we focus on uplink UAM communications, where multiple aerial vehicles (AV) perform cargo/passenger delivery tasks. With predefined flight paths, AVs make decisions on communication resource allocation and velocity selection to complete their missions under safety constraints. Accordingly, we formulate a joint optimization problem to minimize the weighted sum of the total travel time and communication outage time. We first model the optimization problem as a Markov game and propose a multi-agent reinforcement learning based solution. Simulation results corroborate the effectiveness of the proposed solution.

Ruixuan Han↗
NASA NTRSDate not supplied

Ground-Based Vision Tracker for Advanced Air Mobility and Urban Air Mobility

Advanced Air Mobility (AAM) Air Mobility and Urban Air Mobility (UAM) require aircraft surveillance and monitoring for safety and security. Persistent tracking of flying objects provides Air Traffic Control (ATC) and Air Traffic Management (ATM) continuous coverage and knowledge of the national airspace (NAS). Since there are numerous more AAM and UAM aircraft than commercial aircraft, it will be challenging to utilize the same ATC/ATM architectures. A first step in creating a similar ATC/ATM architecture for AAM/UAM will require ground-based and airborne-based sensors to provide monitoring, which will be difficult in urban environments due to GPS degradation. This paper proposes a vision-based tracking method with static cameras by utilizing image subtraction and blob detection, which avoids adding additional electromagnetic interferences in the environment with sensors such as radar. The ground-based vision tracker (GBVT) outputs the detected objects' azimuth and elevation angles from unmanned aerial system (UAS) flight tests. Future and ongoing work includes sending the detected objects' azimuth and elevation angles as inputs for an extended Kalman filter (EKF) to estimate the position and velocity of the detected object.

distributed sensing↗
NASA NTRSDate not supplied

Advancing Electric Propulsion Aircraft Evaluation for Urban Air Mobility: Insights from NASA-Ames

This presentation delves into a recent evaluation conducted at NASA-Ames on the Vertical Motion Simulator, focusing on the handling qualities of Distributed Electric Propulsion VTOL (eVTOL) aircraft, specifically tailored for Urban Air Mobility (UAM) applications. The presentation will focus on the recent effort to adapt and refine use of the Aeronautical Design Standard -33 (ADS-33) rotorcraft handling qualities developed by the U.S. Army and NASA to meet the diverse needs of civilian (eVTOL) concept evaluation. A brief discussion of the author’s personal test pilot insights in the early development of military Fly-By-Wire evaluation methods will also be provided. The emergence of innovative eVTOL designs with unique lift capabilities and flight control systems, present both opportunities and challenges, particularly in ensuring safety amidst technological complexity. To navigate these challenges, our investigation examined evaluation criteria designed to accommodate the varied configurations and advanced automation systems inherent in modern eVTOL aircraft. By establishing a standardized approach to evaluation, our research not only fosters innovation but also upholds safety standards in the dynamic landscape of urban air mobility. Through this endeavor, we help to facilitate the seamless integration of novel aircraft capabilities into new operations, contributing to a new era of safe and efficient aerial transportation.

Loran Allen Haworth↗
NASA NTRSDate not supplied

Advancing Electric Propulsion Aircraft Evaluation for Urban Air Mobility: Insights from NASA Ames

This presentation delves into a recent evaluation conducted at NASA-Ames on the Vertical Motion Simulator, focusing on the handling qualities of Distributed Electric Propulsion VTOL (eVTOL) aircraft, specifically tailored for Urban Air Mobility (UAM) applications. The presentation will focus on the recent effort to adapt and refine use of the Aeronautical Design Standard -33 (ADS-33) rotorcraft handling qualities developed by the U.S. Army and NASA to meet the diverse needs of civilian (eVTOL) concept evaluation. A brief discussion of the author’s personal test pilot insights in the early development of military Fly-By-Wire evaluation methods will also be provided. The emergence of innovative eVTOL designs with unique lift capabilities and flight control systems, present both opportunities and challenges, particularly in ensuring safety amidst technological complexity. To navigate these challenges, our investigation examined evaluation criteria designed to accommodate the varied configurations and advanced automation systems inherent in modern eVTOL aircraft. By establishing a standardized approach to evaluation, our research not only fosters innovation but also upholds safety standards in the dynamic landscape of urban air mobility. Through this endeavor, we help to facilitate the seamless integration of novel aircraft capabilities into new operations, contributing to a new era of safe and efficient aerial transportation.

eVTOL↗
NASA NTRSDate not supplied

Assistive Detect and Avoid Technology in Urban Air Mobility Environments

The use of Assistive Detect and Avoid (Assistive DAA or ADAA) technology in Urban Air Mobility (UAM) environments poses potential benefits as well as challenges. Assistive DAA refers to the leveraged use of DAA technology, originally developed to replace see-and-avoid capabilities for remotely piloted aircraft, in onboard-piloted aircraft to augment (rather than replace) pilots’ see-and-avoid abilities and thus enhance the safety and efficiency of visual flight operations. ADAA is anticipated to be especially safety-enhancing in airspace where traffic density is high or traditional air traffic services are limited, such as in future UAM environments. ADAA may also enable higher-tempo UAM operations than with only see-and-avoid capabilities, while still maintaining acceptable levels of safety. UAM concepts under development by the FAA, NASA, and industry focus on operations moving people and cargo in urban and suburban areas using innovative technologies, operations, and aircraft, including electric vertical takeoff and landing (eVTOL) aircraft. Researchers at NASA Langley Research Center, in collaboration with FAA researchers at the William J. Hughes Technical Center in Atlantic City, NJ, have conducted a series of medium-fidelity, human-in-the-loop research simulations of potential future UAM operations and concepts in both Class C and Class B airspace environments. These simulations have included use of a Langley-developed ADAA research tool called DANTi, which enables configurable ADAA displays to be presented to pilots of simulated eVTOL aircraft participating in higher-density and higher-tempo UAM operations. Experience and observations made during testing of the NASA-developed DANTi ADAA capability in the UAM NFLITE simulation environment will be reported in this paper together with a discussion of airspace integration and regulatory topics.

Detect and Avoid↗
NASA NTRS2024

Synergy of Urban Heat, Pollution, and Social 1 Vulnerability in One of America’s Most Rapidly 2 Growing Cities: Houston, We Have a Problem

During the first two decades of the twenty-first century, we analyze the expansion of 23urban land cover, urban heat island (UHI), and urban pollution island (UPI) in the Houston 24Metropolitan Area (HMA) using land cover classifications derived from Landsat and land/aerosol 25products from NASA's Moderate Resolution Imaging Spectroradiometer. Our approach involves 26both direct utilization and fusion with in situobservations for a comprehensive characterization.27We also examined how social vulnerability within the HMA changed during the study period and 28whether the synergy of UHI, UPI,and social vulnerability enhances environmental inequalities.

Andrew Blackford↗
NASA NTRSDate not supplied

Assistive Detect and Avoid Technology in Urban Air Mobility Environments

The use of Assistive Detect and Avoid (Assistive DAA or ADAA) technology in Urban Air Mobility (UAM) environments poses potential benefits as well as challenges. Assistive DAA refers to the leveraged use of DAA technology, originally developed to replace see-and-avoid capabilities for remotely piloted aircraft, in onboard-piloted aircraft to augment (rather than replace) pilots’ see-and-avoid abilities and thus enhance the safety and efficiency of visual flight operations. ADAA is anticipated to be especially safety-enhancing in airspace where traffic density is high or traditional air traffic services are limited, such as in future UAM environments. ADAA may also enable higher-tempo UAM operations than with only see-and-avoid capabilities, while still maintaining acceptable levels of safety. UAM concepts under development by the FAA, NASA, and industry focus on operations moving people and cargo in urban and suburban areas using innovative technologies, operations, and aircraft, including electric vertical takeoff and landing (eVTOL) aircraft. Researchers at NASA Langley Research Center, in collaboration with FAA researchers at the William J. Hughes Technical Center in Atlantic City, NJ, have conducted a series of medium-fidelity, human-in-the-loop research simulations of potential future UAM operations and concepts in both Class C and Class B airspace environments. These simulations have included use of a Langley-developed ADAA research tool called DANTi, which enables configurable ADAA displays to be presented to pilots of simulated eVTOL aircraft participating in higher-density and higher-tempo UAM operations. Experience and observations made during testing of the NASA-developed DANTi ADAA capability in the UAM NFLITE simulation environment will be reported in this paper together with a discussion of airspace integration and regulatory topics.

Detect and Avoid↗
NASA NTRSDate not supplied

Vision-Based Distributed Sensing at Vertiports for Advanced Air Mobility and Urban Air Mobility Approach and Landing

Advanced Air Mobility (AAM) encompasses a broad vision for air transportation, including Urban Air Mobility (UAM) as a subset. AAM aims to create a more connected and efficient transportation network across various geographical settings. However, navigating AAM aircraft in GPS-denied or degraded environments during approach and landing is challenging. Traditional vision aids like glideslopes and localizers are limited in vertiport environments due to narrow beam constraints and reduced landing angle options. This paper addresses the need for accurate navigation solutions at vertiports by proposing a vision-based distributed sensing (VIDIS) system utilizing cameras with bundle adjustment to assist incoming AAM aircraft during approach and landing while monitoring surface movements to enhance safety and efficiency. Key focus areas for current and future vertiport developers include identifying suitable sensor types and infrastructure standards to support AAM operations and including vertiport markings as vision-based navigation aids. The proposed system offers a novel approach to overcoming navigation challenges in AAM operations, particularly in urban settings where traditional aids may be insufficient. Preliminary simulation results with distributed cameras demonstrate promising outcomes for implementing bundle adjustment techniques to enhance vision-based navigation solutions at vertiports. Generating waypoint-based trajectories via waypoint integration using explicit guidance synthesis (WINGS) creates smooth AAM trajectories for landing at vertiports by using the current waypoint's terminal conditions as the initial conditions for the next waypoint. Combining bundle adjustment's ground-based solution of vertiport features with WINGS, Coplanar Pose from Orthography and Scaling with Iterations (COPOSIT), and an extended Kalman filter (EKF) estimates the state of an incoming aircraft during approach and landing at vertiports. Future work includes testing VIDIS in a high-fidelity simulation and with real-world data.

Distributed sensing↗
NASA NTRSDate not supplied

Vision-Based Distributed Sensing at Vertiports for Advanced Air Mobility and Urban Air Mobility Approach and Landing

Advanced Air Mobility (AAM) encompasses a broad vision for air transportation, including Urban Air Mobility (UAM) as a subset. AAM aims to create a more connected and efficient transportation network across various geographical settings. However, navigating AAM aircraft in GPS-denied or degraded environments during approach and landing is challenging. Traditional vision aids like glideslopes and localizers are limited in vertiport environments due to narrow beam constraints and reduced landing angle options. This paper addresses the need for accurate navigation solutions at vertiports by proposing a vision-based distributed sensing (VIDIS) system utilizing cameras with bundle adjustment to assist incoming AAM aircraft during approach and landing while monitoring surface movements to enhance safety and efficiency. Key focus areas for current and future vertiport developers include identifying suitable sensor types and infrastructure standards to support AAM operations and including vertiport markings as vision-based navigation aids. The proposed system offers a novel approach to overcoming navigation challenges in AAM operations, particularly in urban settings where traditional aids may be insufficient. Preliminary simulation results with distributed cameras demonstrate promising outcomes for implementing bundle adjustment techniques to enhance vision-based navigation solutions at vertiports. Generating waypoint-based trajectories via waypoint integration using explicit guidance synthesis (WINGS) creates smooth AAM trajectories for landing at vertiports by using the current waypoint's terminal conditions as the initial conditions for the next waypoint. Combining bundle adjustment's ground-based solution of vertiport features with WINGS, Coplanar Pose from Orthography and Scaling with Iterations (COPOSIT), and an extended Kalman filter (EKF) estimates the state of an incoming aircraft during approach and landing at vertiports. Future work includes testing VIDIS in a high-fidelity simulation and with real-world data.

Distributed sensing↗
DOE OSTI2026

Urban wash-off of tire wear particles

Tire wear particles (TWPs) are an important class of microplastics due to their toxicity and abundance. Because most TWPs are generated on impervious road surfaces, urban wash-off is the critical first phase of waterborne transport from their zone of production to stormwater drainage. However, little is known about the driving factors behind their mobilization. In this study, we use a rainfall simulator to investigate how surface roughness, rainfall intensity, and surface slope affect wash-off behaviors of TWPs. We also analyze how the size and shape of mobilized TWPs change over the course of simulated storm events. We found that low surface roughness, high rainfall intensity (most significant factor), and low slope result in the most rapid conveyance of TWP load. On average, large particles (>1000 µm) travelled faster than small particles (<125 µm). Particle shape explained a very small amount of variance in TWP wash-off velocity but was found to be more important under higher surface roughness conditions. In addition to wash-off velocity, we found similar conditions controlled the percent mobilization of TWPs. Low surface roughness and high rainfall intensity resulting in higher TWP wash-off rates is consistent with mineral sediment wash-off behavior. Conversely, low surface slope and large particle size leading to faster conveyance is directly opposed to mineral sediment wash-off. Our findings suggest drag-dominated flow and that sufficient runoff depth is the most important parameter governing TWP wash-off. These findings are important first steps to understanding wash-off behaviors of TWPs and informing future modeling efforts and mitigation strategies.

13 HYDRO ENERGY↗
DOE OSTI2020

Urban building energy modeling (UBEM) tools: A state-of-the-art review of bottom-up physics-based approaches

Regulations corroborate the importance of retrofitting existing building stocks or constructing new energy-efficient districts. There is, thus, a need for modeling tools to evaluate energy scenarios to better manage and design cities, and numerous methodologies and tools have been developed. Among them, Urban Building Energy Modelling (UBEM) tools allow the energy simulation of buildings at large scales. Choosing an appropriate UBEM tool, balancing the level of complexity, accuracy, usability, and computing needs, remains a challenge for users. The review focuses on the main bottom-up physics-based UBEM tools, comparing them from a user-oriented perspective. Five categories are used: (i) the required inputs, (ii) the reported outputs, (iii) the exploited workflow, (iv) the applicability of each tool, and (v) the potential users. Moreover, a critical discussion is proposed, focusing on interests and trends in research and development. The results highlighted major differences between UBEM tools that must be considered to choose the proper one for an application. Finally, barriers of adoption of UBEM tools include the needs of a standardized ontology, a common three-dimensional city model, a standard procedure to collect data, and a standard set of test cases. This feeds into future development of UBEM tools to support cities’ sustainability goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

AI-Driven Frameworks for Characterizing Urban Energy Systems

We develop AI-driven frameworks to characterize urban energy systems with the goal of transforming planning by reducing the labor of model generation, scaling scenario exploration, and improving accuracy for localized analysis. The approach integrates top-down and bottom-up data to train different AI models that predict missing information and generate inputs and targeted scenarios for district-scale models. The result is a scalable framework that provides actionable insights for reliable and efficient planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRSDate not supplied

Generic Urban Air Mobility Simulation

This research presents a simulation framework for autonomous research for a UAM vehicle using the NASA Revolutionary Vertical Lift Technology Lift+Cruise concept vehicle. Our research results were produced using the open-source, six degree of freedom, rigid-body, nonlinear generic urban air mobility (GUAM) simulation. The intent of this paper is to demonstrate the GUAM simulation and a series of Challenge Problems that our researchers have posed to the broader autonomous vehicle research community. Our team has developed the GUAM simulation for the express purpose of providing a high-fidelity transition vehicle dynamics model to foster collaboration and algorithm performance comparison across research teams. In this paper, we demonstrate some of the autonomous flight research challenges and some of our current approaches to tackling basic autonomous flight tasks (e.g., trajectory following, stationary and moving obstacle avoidance). Additionally, we propose some flight metrics to assess autonomous algorithm performance while accomplishing these basic autonomous tasks.

autonomous flight↗