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Results for “Urban Air Mobility Vehicles”

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
NASA NTRSDate not supplied

AEGIS: Autonomous Entity Global Intelligence System for Urban Air Mobility

This paper presents a global intelligence system that synthesizes aerial vehicles’ real-time physical data, planned actions, and historical behavior into engineered data frames representing the collective state of the airspace and suitable for efficient machine learning consumption. These data frames are then learnt by a deep neural net to build a prediction model that estimates the expected evolution path of the current state, thereby identifying potential future conflicts. This approach lends itself to an automated early warning system that the aerial vehicles can implement onboard with a suitable edge computing module more efficiently and effectively than non-AI methods, and eventually take preventive or corrective measures towards self/collaborative resolution of the issues. Contrary to a centralized early warning system where all vehicles’ task-space eventually converges to a global optimum state, the presented distributed global intelligence system brings in a balance between local utility functions of each vehicle and the global operating framework. This contributes to effectively handle the potential massive scaling in urban air mobility in the near future.

Artificial Intelligence↗
NASA NTRSDate not supplied

Visualizing Corridors in Terminal Airspace using Trajectory Clustering

Context: Advances in battery and automation technology have made routine air taxi and cargo transport in urban areas a business model that can be attained by emerging aviation innovators. The community vision and work to enable these novel operations is discussed using the term ‘Urban Air Mobility’ or UAM. Small, piloted, airspace vehicles that fly with a few passengers do operate in urban areas today, and these vehicles can be studied as an early proxy for this future UAM traffic. Aim: We seek to identify corridors already in daily operation and their properties. Method: We applied DBSCAN and HDBSCAN to Dallas Forth-Worth TRACON flight data to identify corridors in use, their density, and devised a method to annotate landing sites used in these corridors with site metadata. Results: While DBSCAN was unable to group similar trajectories, we we were able to successfully identify corridors using HDBSCAN, measure their density and annotate them. Conclusion: The applied method can successfully identify corridors in daily operation with additional metadata to help domain expert understand the intent of UAM corridors.

UAM, Trajectory, TRACON, Clustering, DBSCAN, HDBSC↗
NASA NTRSDate not supplied

Visualizing Corridors in Terminal Airspace Using Trajectory Clustering

Context: Advances in battery and automation technology have made routine air taxi and cargo transport in urban areas a business model that can be attained by emerging aviation innovators. The community vision and work to enable these novel operations is discussed using the term ‘Urban Air Mobility’ or UAM. Small, piloted, airspace vehicles that fly with a few passengers do operate in urban areas today, and these vehicles can be studied as an early proxy for this future UAM traffic. Aim: We seek to identify corridors already in daily operation and their properties. Method: We applied DBSCAN and HDBSCAN to Dallas Forth-Worth TRACON flight data to identify corridors in use, their density, and devised a method to annotate landing sites used in these corridors with site metadata. Results: While DBSCAN was unable to group similar trajectories, we we were able to successfully identify corridors using HDBSCAN, measure their density and annotate them. Conclusion: The applied method can successfully identify corridors in daily operation with additional metadata to help domain expert understand the intent of UAM corridors.

UAM Trajectory, TRACON, Clustering, DBSCAN, HDBSCA↗
NASA NTRS2018

Observations from Exploration of VTOL Urban Air Mobility Designs

This presentation will be displayed on the Aeromechanics Branch website. It outlines: NASA Exploration of Urban Air Mobility, Reduced-Emission Rotorcraft Concepts, Concept Vehicles for Air Taxi Operations, Vehicles for UAM Mission and Market and Observations.

Urban Air Mobility Designs↗
NASA NTRSDate not supplied

A Comprehensive eVTOL Performance Evaluation Framework in Urban Air Mobility

In this paper, we developed an open-source simulation framework for the evaluation of electric vertical takeoff and landing vehicles (eVTOLs) in the context of Unmanned Traffic Management (UTM) and under the concept of Urban Air Mobility (UAM). Unlike most existing studies, the proposed framework combines the utilization of UTM and eVTOLs to develop a realistic UAM testing platform. For this purpose, we first develop an UTM simulator to simulate the real-world UAM environment. Then, instead of using a simplified eVOTL model, a high-fidelity eVTOL design tool, namely SUAVE, is employed and an dilation sub-module is introduced to bridge the gap between the UTM simulator and SUAVE eVTOL performance evaluation tool to elaborate the complete mission profile. Based on the developed simulation framework, experiments are conducted and the results are presented to analyze the performance of eVTOLs in the UAM environment.

Mrinmoy Sarkar↗
NASA NTRSDate not supplied

Experiments for Securing Air Traffic Against Cyber-Physical System Attacks

This presentation describes experiments conducted with single board computers to investigate methods for creating trust for enabling the development of cyber-resilient air transportation systems. Methods included secure communication to prevent unauthorized access to data, consistency of data obtained via sensors and by processing, and built-in safeguards to prevent mission failure. The motivation for this work are the following. The future air transportation system needs to ensure availability, integrity, confidentiality and safety of operations. Safety of vehicles and operations is paramount for successful integration of Urban Air Mobility (UAM), Unmanned Aerial Systems (UAS), supersonic aircraft and launch vehicles with conventional aviation operations in the National Airspace System. Security is becoming critical because the sensors, networks and computers are far more vulnerable to bad actors than their mechanical or human predecessors. The goal therefore is to design and develop cyber-resilient systems that continue to function even in degraded states. The main findings are (1) off-the-shelf hardware can support development of cyber-resilient onboard flight computers and (2) trust in system design and implementation can be accomplished by integrating layers in depth (detail) and in breadth (scope).

cyber-resilient autonomy, trust, secure communicat↗
NASA NTRSDate not supplied

Analysis of the Electrical Grid for UAM

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 presentation is on 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 over time. Under the best-case assumption that electricity can be transmitted and distributed as needed within each interconnection (i.e., electrical grid), it is estimated that the maximum number of UAM aircraft that can charge simultaneously in the continental United States will decrease by 20% from about 595 thousand in the year 2021 to about 475 thousand in the year 2050 due to the projected increase in ground electric vehicles.

electrical grid; urban air mobility; electric vehi↗
NASA NTRSDate not supplied

Fault Detection and Performance Monitoring of Propellers in Electric UAV

Unmanned aerial vehicles (UAVs) are used in various industries such as agriculture and logistics, to name but a few, where their applications are beyond basic mapping, surveillance, and photography. In near future, UAVs are expected to be used in package delivery service and larger electric vertical takeoff and landing vehicles will be employed for urban air mobility applications (air taxi). Thus, several electric propulsion systems will enter the low-altitude airspace with frequent take offs and landings. To achieve state-of-the-art safety standards under such high traffic density, UAVs will require in-time fault detection and performance monitoring of critical powertrain components. This work focuses on propeller blade performance and damage detection in electric UAVs. Propellers are the fastest moving component in an UAV; even a minor defect in the propeller blades could cause performance deterioration, with consequent challenges in flying through the planned trajectory or adhere to the safety requirements of the operation. Monitoring and updating aerodynamic efficiency of each rotor would therefore enable the detection of off-nominal propeller conditions thus magnifying the state-awareness of powertrain monitoring systems based on the acquired electrical signals. We use an extended Kalman filter-based parameter estimation algorithm that incorporates time history responses from UAV powertrain in conjunction with a full powertrain system model. Propeller fault detection is achieved by incorporating the aerodynamic parameters of propeller into the powertrain model. The proposed technique is successfully validated with numerical simulations.

Unmanned aerial vehicles↗
NASA NTRS2020

March of the Interns

Summer 2019 brought 70 interns — from Puerto Rico, 44 continental US states, Sweden, and the Republic of Trinidad and Tobago — into the NASA Ames Aeromechanics Branch. Some were high school students learning engineering for the first time, while most were mechanical and aerospace engineering students, though two physics majors and a math major jumped into the mix to provide balance. This year’s interns completed work on 30 different projects with a collective of 30,000 dedicated hours of work. The projects this year were on urban air mobility (UAM), search and rescue vehicle design, all things Mars, Titan exploration concept designs, 3D modeling (i.e. computer aided design, CAD), computational fluid dynamics (CFD), and much more. Last year we addressed the question of what to do with an army of interns. This year, we are following its path to change the world.

Dromiack, Hannah↗
NASA NTRS2023

Simulation of a Single Rotor and a Quadrotor Hovering in Full and Partial Ground Effect

With the development of urban air mobility, the safety of multirotor vehicle operations in proximity to vertiports must be assessed. This paper examines high-fidelity blade-resolved OVERFLOW simulations and medium-fidelity vortex particle–mesh simulations that capture the aerodynamics of a rotorcraft in full and partial ground effect. Results obtained with each CFD method are compared to verify the consistency of the models introduced in the latter, which include an immersed lifting line for the blade aerodynamics and various boundary conditions to account for solid surfaces such as ground and walls. Satisfactory agreement is obtained for the blade loads and rotorwash velocity profiles in the case of a single rotor, except for small discrepancies at the blade tip. Finally, a quadrotor air taxi is simulated to quantify the load imbalance when the vehicle hovers above a rooftop edge. The combined use of high- and medium-fidelity methods is envisioned to accelerate the workflow when a large number of configurations need to be tested.

HEC↗
NASA NTRS2023

Distributed Sensing and Reasoning for Advanced Air Mobility Health Management and Mission Assurance

As envisioned, Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) will introduce new vehicles and operations within the national airspace, moving people and cargo safely and efficiently at a much larger scale than today. Driven by transformative technology and revolutionary aircraft, this movement must still manage technical, regulatory, operational, and policy challenges. NASA’s work in support of AAM and UAM includes, but is not limited to tools, technologies, and architectures for distributed sensing of aircraft, data & reasoning services exchange, Human-Autonomy Teaming (HAT), contingency management, and vehicle health management. This paper builds upon these concepts and evaluates the use of distributed sensing and infrastructure assistance towards health management and mission assurance of UAM vehicles in specific operational scenarios. Through analysis of these example missions, aided by the data produced by the conceptual distributed sensing and reasoning infrastructure, we define opportunities for state estimation, diagnosis, and key decision points affecting the health state of the vehicle and the airspace volume. As a result, we define a number of measurable health state parameters providing relevant information to drive decision-making in contingency situations or feed automation tools in support of operators and managers.

Safety↗
NASA NTRS2024

Revolutionary Vertical Lift Technology Lift + Cruise Concept Vehicle Powertrain Dynamic Model

The Lift + Cruise (L+C) is one of several Revolutionary Vertical Lift Technology (RVLT) concept aircraft identified by NASA to investigate Urban Air Mobility (UAM) requirements. This six-passenger vehicle has a conventional tube-and-wing configuration, but with eight lift rotors (four on each wing) and a pusher rotor on the tail. This arrangement allows it to take off and land vertically as well as fly like an airplane. This report presents a novel dynamic model of the L+C powertrain built using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) and the Electrical Modeling and Thermal Analysis Toolbox (EMTAT), both of which are NASA-developed toolboxes, and together are capable of modeling hybrid-electric powertrain architectures. This research effort models the complex behavior of the powertrain at the mechanical timescale (15 to 20 ms). The model consists of a turboshaft engine, generator, direct current bus, energy storage management system, gearboxes, and electric propulsor systems coupled together to create a dynamic model that mimics the operation of the multidomain powertrain. Two control algorithms, designed to equalize the power consumed to the power produced, are compared to assess their practicality: (1) independent proportional-integral (PI) control and (2) linear quadratic integral regulator (LQIR) control. Simulation results highlight the key features present in the model and demonstrate its operation under the two control schemes.

revolutionary vertical lift technology↗
NASA NTRS2019

Hazards Analysis and Failure Modes and Effects Criticality Analysis (FMECA) of Four Concept Vehicle Propulsion Systems

The primary objective of this research effort is to identify failure modes and hazards associated with the concept vehicles and to perform functional hazard analyses (FHA) and failure modes and effects criticality analyses (FMECA) for each. Boeing also created a Fault Tree Analysis (FTA) for each of the concept vehicles, as the FTA contains the connectivity between systems and is an accepted, top-down method to analyze the safety of an air-vehicle. Conceptual design of notional powertrain configuration for each of four (4) NASA RVLT (Revolutionary Vertical Lift Technology) Concept Vehicles were developed in as much detail as was necessary to support the reliability and safety analysis for this project. Functional block diagrams from each of the conceptual powertrain configurations were created and used to order the FHA, FMECA, and FTA. Hazards were identified and the severity of each were categorized in the FHA for use in a follow-up FMECA. The FTA took inputs from the FMECA and the functional block diagrams to develop the connectivity and develop a quantitative architecture that could be used to perform sensitivity studies, as related to vehicle safety.Guidelines for reliability targets for both the air vehicle and the operation in the UAM (Urban Air Mobility) mission are discussed. An industry literature search was performed in order to assess gaps in existing government regulations and industry specifications. The industry literature search led to air-vehicle and operational reliability discussions, as related to Distributed Electric/Hybrid-Electric Propulsion (DE/HEP) system operating in the UAM role. A discussion of results and recommendations for future work is also provided.

Hazards Analysis↗
NASA NTRSDate not supplied

Hierarchical Mixture of Experts for Advanced Air Mobility Flight Phase Classification

Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) operations will have numerous vehicles and aircraft flying in the airspace, which poses safety and security concerns. Commercial airlines utilize Air Traffic Management (ATM) and Air Traffic Control (ATC) for real-time monitoring, surveillance, traffic coordination, and rerouting to maintain safe and efficient flight patterns. Transferring ATM and ATC architectures to AAM/UAM will be challenging to implement since AAM/UAM aircraft fly at lower altitudes, have more static and dynamic obstacles, operate in highly dense environments, and have several more aircraft to monitor for a given volume of the national airspace (NAS). Aircraft typically have the following flight phases: takeoff, climb, cruise, descent, and landing. Classifying these flight phases provides insight into ensuring safe operations, providing situational awareness of the NAS, and monitoring flights in emergencies. Automatic flight phase classification will enhance the efficiencies of ATM/ATC-like architectures for AAM/UAM, especially since numerous aircraft will be flying in highly dense urban environments. Typical flight phase classification methods are all-or-nothing, which will not capture or accurately classify the transitions between flight phases. Utilizing hierarchical mixture of experts (HME) provides a flight phase classification solution that includes transitions between the flight phases by assigning weights based on ground-based distributed sensor readings from cameras and radar. Adding the transitions between flight phases increases the fidelity of flight phase classification and provides deeper insight into flight phase classification by leveraging distributed sensing concepts. Simulation results and post-processed flight test results demonstrate the utility of HME for automatic and robust flight phase classification for real-time AAM operations.

distributed sensing↗
NASA NTRSDate not supplied

Practical Conceptual Design of Quieter Urban VTOL Aircraft

A toolchain and process for conceptual design of VTOL rotorcraft, employing low- and mid-fidelity tools is presented. The approach is capable of providing more quantitatively-credible trades between noise, size, and cost metrics than the methods commonly used for conceptual design. In addition to a general conceptual design tool, the approach employs comprehensive analysis for trim, blade motion, and airloads; these are then used by acoustic analysis software to develop source sound, propagate it, and calculate noise metrics. A key aspect of the approach is flexibility to assess varied aircraft types and different technologies and design features. Vehicles are sized using a representative Urban Air Mobility design mission. Demonstration cases are presented for a single main rotor helicopter, quadrotor, side-by-side helicopter, and lift+cruise aircraft. Noise metrics used for demonstration are the FAA/EASA certification Effective Perceived Noise Levels for takeoff, flyover, and approach. The concept aircraft in this study are shown to achieve reductions in noise relative the initial design points, with changes in mission performance and cost as a consequence. Many of the designs are predicted to be tens of EPNdB quieter in the certification metrics than existing helicopters.

Conceptual Design↗
NASA NTRSDate not supplied

Hierarchical Mixture of Experts for Advanced Air Mobility Flight Phase Classification

Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) operations will have numerous vehicles and aircraft flying in the airspace, which poses safety and security concerns. Commercial airlines utilize Air Traffic Management (ATM) and Air Traffic Control (ATC) for real-time monitoring, surveillance, traffic coordination, and rerouting to maintain safe and efficient flight patterns. Transferring ATM and ATC architectures to AAM/UAM will be difficult to implement since AAM/UAM aircraft fly at lower altitudes, have more static and dynamic obstacles, operate in highly dense environments, and have several more aircraft to monitor for a given volume of the national airspace (NAS). Automatic flight phase classification will enhance efficiencies of ATM/ATC-like architectures for AAM/UAM. Classifying the main flight phases (takeoff, climb, cruise, descent, and landing) provides insight to ensure safe operations, provide situational awareness of the NAS, and monitor flights in case there are any emergencies. Typical flight phase classification methods are all-or-nothing, which will not capture or accurately classify the transitions between flight phases. Utilizing hierarchical mixture of experts (HME) provides a flight phase classification solution that includes transitions between the flight phases by assigning weights based on ground-based distributed sensor readings from cameras and radar. Adding the transitions between flight phases increases the fidelity of flight phase classification and provides deeper insight for flight phase classification by leveraging distributed sensing concepts.

distributed sensing↗
NASA NTRSDate not supplied

Simplified Vehicle Control Concept for a Lift Plus Cruise eVTOL Vehicle

Electric Vertical Takeoff and Landing (eVTOL) vehicles have the potential to enable cost effective Urban Air Mobility (UAM) applications. These concepts may also pose several challenging handling and control problems, which must be addressed prior to safe and reliable urban operations. This paper investigates a simplified vehicle control concept that is designed to address some of these challenges for a conceptual Lift Plus Cruise vehicle designed by NASA’s Revolutionary Vertical Lift Technology (RVLT) project. The command and control architecture for this concept is presented along with preliminary findings. Initial results explore the vehicle performance in an approach to hover transition scenario, designed to explore the challenge of dissipating energy across all flight regimes. Operational concepts with varying aggressiveness are evaluated through changing glideslope and deceleration rates. Preliminary results show that the simplified control concept is effective over these operational conditions, with control strategies and envelope protection limits able to maintain control though aggressive operations despite saturation at steeper slopes with higher deceleration rates. Final results will show piloted simulation evaluations in the the Aerospace Cognitive Engineering Lab – Rapid Automation Test Environment (ACEL-RATE) laboratory at NASA Ames Research Center. The planned tests will build on these operations with additional test cases exploring variations in wind conditions as well as transition-to-hover automation strategies and display information.

simplified vehicle control↗
NASA NTRSDate not supplied

Simplified Vehicle Control Concept for a Lift Plus Cruise eVTOL Vehicle

Electric Vertical Takeoff and Landing (eVTOL) vehicles have the potential to enable cost effective Urban Air Mobility (UAM) applications. These concepts may also pose several challenging handling and control problems, which must be addressed prior to safe and efficient urban operations. This paper investigates a simplified vehicle control concept that is designed to address some of these challenges for a conceptual Lift Plus Cruise vehicle. This concept also includes several variations of a transition-to-hover function, designed to assist pilots in capturing and maintaining a stabilized hover prior to landing. The different simplified control architectures for this concept are presented along with preliminary findings. Preliminary results show that the simplified control concept can be effective in assisting pilots to achieve safe and reliable hover landings, and that transition-to-hover functions have the potential of reducing workload while increasing accuracy. A follow on evaluation will be performed in the Vertical Motion Simulator (VMS) at NASA Ames Research Center. The planned tests will focus on more operationally representative scenarios, while building upon these operations with additional test cases exploring variations in glidepath angles and wind conditions.

simplified vehicle control↗