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At least 865 records · Page 48

Intelligent Contingency Management for Urban Air Mobility

The third aviation revolution is seeking to enable transportation where users have access to immediate and flexible air travel; the users dictate trip origin, destination and timing. One of the major components of this vision is urban air mobility (UAM) for the masses. UAM means a safe and efficient system for vehicles to move passengers and cargo within a city. In order to reach UAM’s full market potential the vehicle will have to be autonomous. One of the primary challenges of autonomous flight is dealing with off-nominal events, both common and unforeseen; thus, intelligent contingency management (ICM) is one of the enabling technologies. This paper proposes an ICM architecture with associated tools that would help enable the UAM vision.

UAM↗

Intelligent Contingency Management for Urban Air Mobility

The third aviation revolution is seeking to enable transportation where users have access to immediate and flexible air travel; the users dictate trip origin, destination and timing. One of the major components of this vision is urban air mobility (UAM) for the masses. UAM means a safe and efficient system for vehicles to move passengers and cargo within a city. In order to reach UAM’s full market potential the vehicle will have to be autonomous. One of the primary challenges of autonomous flight is dealing with off-nominal events, both common and unforeseen; thus, intelligent contingency management (ICM) is one of the enabling technologies. This paper proposes an ICM architecture with associated tools that would help enable the UAM vision.

UAM;↗

Towards Resilient Autonomous Navigation of Drones

Robots and particularly drones are especially useful in exploring extreme environments that pose hazards to humans. To ensure safe operations in these situations, usually perceptually degraded and without good GNSS, it is critical to have a reliable and robust state estimation solution. The main body of literature in robot state estimation focuses on developing complex algorithms favoring accuracy. Typically, these approaches rely on a strong underlying assumption: the main estimation engine will not fail during operation. In contrast, we propose an architecture that pursues robustness in state estimation by considering redundancy and heterogeneity in both sensing and estimation algorithms. The architecture is designed to expect and detect failures and adapt the behavior of the system to ensure safety. To this end, we present HeRO (Heterogeneous Redundant Odometry): a stack of estimation algorithms running in parallel supervised by a resiliency logic. This logic carries out three main functions: a) perform confidence tests both in data quality and algorithm health; b) re-initialize those algorithms that might be malfunctioning; c) generate a smooth state estimate by multiplexing the inputs based on their quality. The state and quality estimates are used by the guidance and control modules to adapt the mobility behaviors of the system. The validation and utility of the approach are shown with real experiments on a ying robot for the use case of autonomous exploration of subterranean environments, with particular results from the STIX event of the DARPA Subterranean Challenge.

Agha-mohammadi, Ali-akbar↗

Current Trends in the Detection of Sociocultural Signatures: Data-Driven Models

The harvesting of behavioral data and their analysis through evidence-based reasoning enable the detection of sociocultural signatures in their context to support situation awareness and decision making. Harvested data are used as training materials from which to infer computational models of sociocultural behaviors or calibrate parameters for such models. Harvested data also serve as evidence input that the models use to provide insights about observed and future behaviors for targets of interest. The harvested data is often the result of assembling diverse data types and aggregating them into a form suitable for analysis. Data need to be analyzed to bring out the categories of content that are relevant to the domain being addressed in order to train or run a model. If, for example, we are modeling the intent of a group to engage in violent behavior using messages that the group has broadcasted, then these messages need to be processed to extract and measure indicators of violent intent. The extracted indicators and the associated measurements (e.g. rates or counts of occurrence) can then be used to train/calibrate and run computational models that assess the propensity for violence expressed in the source message. Ubiquitous access to the Internet, mobile telephony and technologies such as digital photography and digital video have enabled social media application platforms such as Facebook, YouTube, and Twitter that are altering the nature of human social interaction. The fast increasing pace of online social interaction introduces new challenges and opportunities for gathering sociocultural data. Challenges include the development of harvesting and processing techniques tailored to new data environments and formats (e.g. Twitter, Facebook), the integration of social media content with traditional media content, and the protection of personal privacy. As these and other challenges are addressed, a new wealth of behavioral data and data analysis methods becomes available that are shaping social computing as a strongly data-driven experimental discipline with an increasingly stronger impact on the decision-making process of groups and individuals alike. In this chapter, we review current advances and trends in the detection of sociocultural signatures. Specific embodiments of the issues discussed are provided with respect to the assessment of violent intent and sociopolitical contention. We begin by reviewing current approaches to the detection of sociocultural signatures in these domains. Next, we turn to the review of novel data harvesting methods for social media content. Finally, we discuss the application of sociocultural models to social media content, and conclude by commenting on current challenges and future developments.

Sanfilippo, Antonio P.↗

Subjective Assessment of Initial and Mid-Term UAM Operations and the Impact on Air Traffic Controllers' Workload

The emergence of Urban Air Mobility (UAM) marks a new era of aviation that will be characterized by a shift in transportation dynamics marked by safe, efficient, and sustainable air travel within urban areas. Although UAM will provide significant advantages, increased air travel demand has the potential to impact air traffic controllers (ATCo) workload. Therefore, industry, government, and academia in the UAM ecosystem are actively working to overcome potential implementation challenges that include airspace integration and air traffic management. As part of this effort, researchers from the National Aeronautics and Space Administration (NASA) are studying the challenges associated with UAM operations’ interactions with air traffic control (ATC). The present research paper presents an analysis of subjective assessments to determine the usability and acceptability of airspace procedures under two different operating conditions – Initial and Mid-Term – and two different levels of UAM traffic. The completion of these investigations will be a steppingstone in supporting the successful implementation of UAM operations into the National Airspace System.

Urban Air Mobility, Air Traffic Control, Workload↗

Subjective Assessment of Initial and Mid-Term UAM Operations and the Impact on Air Traffic Controllers' Workload

The emergence of Urban Air Mobility (UAM) marks a new era of aviation that will be characterized by a shift in transportation dynamics marked by safe, efficient, and sustainable air travel within urban areas. Although UAM will provide significant advantages, increased air travel demand has the potential to impact air traffic controllers (ATCo) workload. Therefore, industry, government, and academia in the UAM ecosystem are actively working to overcome potential implementation challenges that include airspace integration and air traffic management. As part of this effort, researchers from the National Aeronautics and Space Administration (NASA) are studying the challenges associated with UAM operations’ interactions with air traffic control (ATC). The present research paper presents an analysis of subjective assessments to determine the usability and acceptability of airspace procedures under two different operating conditions – Initial and Mid-Term – and two different levels of UAM traffic. The completion of these investigations will be a steppingstone in supporting the successful implementation of UAM operations into the National Airspace System.

Urban Air Mobility↗

Countercations Control Local Specific Bonding Interactions and Nucleation Mechanisms in Concentrated Water-in-Salt Solutions

One of the continuing challenges presented in aqueous salt solutions is to understand ion association reactions driving dynamic demixing from solvation, complexation and solute clustering. The problems understanding this phenomenon are exacerbated in the highly-concentrated water-in-salt electrolytes, where the deficiency of water leads to a dramatic retardation of solvating water and formation of extended solvent-solute clustering networks. By probing microscopic dynamics of water and prenucleation clusters using quasi-elastic neutron scattering and proton nuclear magnetic resonance spectroscopy, we observed contrasting mechanistic specifics of ion-water mobilities in highly-concentrated Na+- vs. K+-based aluminate solutions (diffusion coefficients of 0.2 vs. 2.6?10-10m2s-1 at 293 K, respectively). The magnitude of the differences is far beyond the kosmotropic (Na+) and chaotropic (K+) effects typically understood at low ionic concentrations. The distinct crystallization mechanisms observed in analogous deuterated systems further imply that different prenucleation cluster dynamics and network packing morphologies can either frustrate or promote crystallization, as described by non-classical nucleation theory.

Wang, Hsiu-Wen↗

π Berry phase and Zeeman splitting of Weyl semimetal TaP

Here, the recent breakthrough in the discovery of Weyl fermions in monopnictide semimetals provides opportunities to explore the exotic properties of relativistic fermions in condensed matter. The chiral anomaly-induced negative magnetoresistance and π Berry phase are two fundamental transport properties associated with the topological characteristics of Weyl semimetals. Since monopnictide semimetals are multiple-band systems, resolving clear Berry phase for each Fermi pocket remains a challenge. Here we report the determination of Berry phases of multiple Fermi pockets of Weyl semimetal TaP through high field quantum transport measurements. We show our TaP single crystal has the signatures of a Weyl state, including light effective quasiparticle masses, ultrahigh carrier mobility, as well as negative longitudinal magnetoresistance. Furthermore, we have generalized the Lifshitz-Kosevich formula for multiple-band Shubnikov-de Haas (SdH) oscillations and extracted the Berry phases of π for multiple Fermi pockets in TaP through the direct fits of the modified LK formula to the SdH oscillations. In high fields, we also probed signatures of Zeeman splitting, from which the Landé g-factor is extracted.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

New value of old knowledge: sulphur-based GaAs surface passivation and potential GaAs application in molecular electronics and spintronics

GaAs is well known for its extremely high electron mobility and direct band gap. Owing to the technological advances in silicon-based technology, GaAs has been limited to niche areas. This paper discusses the application of GaAs in molecular electronics and spintronics as a potential field for considering this amazing but challenging material. GaAs is challenging because its surface is characterized by a high density of surface states, which precludes the utilization of this semiconducting material in mainstream devices. Sulfur(S)-based passivation has been found to be significantly useful for reducing the effect of dangling bonds and was researched thoroughly. GaAs applications in molecular spintronics and electronics can benefit significantly from prior knowledge of GaAs and S interactions because S is a popular functional group for bonding molecular device elements with different semiconductors and metals. In this article, the problem associated with the GaAs surface is discussed in a tutorial form. A wide variety of surface passivation methods has been briefly introduced. We attempted to highlight the significant differences in the S-GaAs interactions for different S passivation methods. We also elaborate on the mechanisms and atomic-scale understanding of the variation in surface chemistry and reconstruction due to various S passivation methods. It is envisioned that GaAs and thiol-terminated molecule-based novel devices can exhibit innovative device characteristics and bring the added advantage of S-based passivation.

36 MATERIALS SCIENCE↗

Investigation of a Tandem Tilt-wing VTOL Aircraft in the NASA Langley 12-Foot Low-Speed Tunnel

The emerging Urban Air Mobility market imposes new design requirements on aircraft, including the ability to have vertical take-off and landing (VTOL) capabilities with the ability to transition into fast and efficient forward flight. Industry has proposed many different vehicle configurations, which have many different challenges. A primary challenge facing many of these concepts is flight through the transition corridor from vertical to horizontal flight and back. In an effort to better understand and help improve vehicle safety in the complex transition corridors, NASA Langley Research Center has proposed to characterize the transition corridor with wind tunnel and flight tests for a variety of unmanned aircraft system sized VTOL configurations. The first vehicle of this series is the Langley Aerodrome 8 (LA-8). LA-8 is a high-risk/high-reward tandem tilt-wing vehicle with distributed electric propulsion and a partially deflected slipstream aircraft. The LA-8 vehicle has gone through a preliminary wind tunnel test in NASA Langley's 12-Foot Low-Speed Wind Tunnel. The results of the aerodynamic data collected, including the longitudinal, lateral, and directional force and moment aerodynamic coefficients, from these tests during different phases of flight are presented.

VTOL↗

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↗

Benchmark Problem for Autonomous Urban Air Mobility

This paper introduces a Community Benchmark Problem (CBP) for Intelligent Contingency Management (ICM) for Urban Air Mobility (UAM) aircraft. The CBP aims to provide a common framework for measuring and comparing the progress of autonomy solutions for UAM aircraft in handling emergency situations. The paper proposes a methodology for defining and quantifying five measures of complexity that capture the challenges and requirements of ICM for UAM: Mission, Environmental, Autonomy, Decision-Making, and Mission Fault. In addition, it proposes a methodology for defining and quantifying mission risk acceptability with the same goals: Contingency Management, Mission Success, Operational, Mission Redefinition, and Environmental. We describe how to use these measures to track progress of the development of ICM capability, as well as to create scenarios and evaluate the performance of different autonomy solutions.

autonomy↗

Community Benchmark Problem for Intelligent Contingency Management

This paper introduces a Community Benchmark Problem (CBP) for Intelligent Contingency Management (ICM) for Urban Air Mobility (UAM) aircraft. The CBP aims to provide a common framework for measuring and comparing the progress of autonomy solutions for UAM aircraft in handling emergency situations. The paper proposes a methodology for defining and quantifying five measures of complexity that capture the challenges and requirements of ICM for UAM: Mission, Environmental, Autonomy, Decision-Making, and Mission Fault. In addition, it proposes a methodology for defining and quantifying mission risk acceptability with the same goals: Contingency Management, Mission Success, Operational, Mission Redefinition, and Environmental. We describe how to use these measures to track progress of the development of ICM capability, as well as to create scenarios and evaluate the performance of different autonomy solutions.

autonomy↗

Preventive Power Outage Estimation Based on A Novel Scenario Clustering Strategy: Preprint

The increasing occurrence of extreme weather events is challenging the power grid operation. In front of the extreme weather, the system operator is responsible for estimating the power outage and scheduling the restoration resources. This paper proposes an outage evaluation framework to identify the possible unserved load profiles, vulnerable areas, and mobile energy adequacy. The predicted vulnerable lines of an outage prediction model tool are utilized to generate numerous faulted line scenarios. Next, each scenario's nodal unserved load profile is obtained by solving a three-phase restoration model that considers the schedule of repair crews and mobile energy resources. Then, a novel scenario clustering strategy is developed to cluster the unserved load profiles into multiple representative ones for straightforward analysis. Finally, case studies on a distribution system evaluate the damage level brought by extreme weather and verify the effectiveness of the proposed scenario clustering strategy.

mobile energy resources↗

Deploying Mobility-On-Demand for All by Optimizing Paratransit Services

While on-demand ride-sharing services have become popular in recent years, traditional on-demand transit services cannot be used by everyone, e.g., people who use wheelchairs. Paratransit services, operated by public transit agencies, are a critical infrastructure that offers door-to-door transportation assistance for individuals who face challenges in using standard transit routes. However, with declining ridership and mounting financial pressure, public transit agencies in the USA struggle to operate existing services. We collaborate with a public transit agency from the southern USA, highlight the specific nuances of paratransit optimization, and present a vehicle routing problem formulation for optimizing paratransit. We validate our approach using real-world data from the transit agency, present results from an actual pilot deployment of the proposed approach in the city, and show how the proposed approach comprehensively outperforms existing approaches used by the transit agency. To the best of our knowledge, this work presents one of the first examples of using open-source algorithmic approaches for paratransit optimization.

Pavia, Sophie↗

AAM Project: High Density Vertiplex (HDV) Research and Capabilities

NASA is currently engaged in dedicated research into vertiports through its Advanced Air Mobility Project, housed within the Airspace Operations Safety Program (AOSP), through a Sub-Project referred to as High Density Vertiplex, or simply HDV. This effort’s mission is to develop a reference automation architecture for vertiports that will enable operations to scale to the density levels envisioned for future environments. Through the development of the HDV Concept of Operations and accompanying architecture documents a research roadmap was developed as part of the effort's formulation process that laid the foundations for the work and schedule to be completed as part of the HDV scope and technical challenge. This presentation provides the background of the HDV Sub-Project and outlines the concept and capabilities as it has developed to date. Summaries of the completed work package and status of current work package will be provided with details on specific capabilities and supporting integration developments.

vertiport↗

The Shortwave Spectral Radiometer for Atmospheric Science: Capabilities and Applications from the ARM User Facility

Industry advances have greatly reduced the cost and size of ground-based shortwave (SW) sensors for the ultraviolet, visible, and near-infrared spectral ranges that make up the solar spectrum, while simultaneously increasing their ruggedness, reliability, and calibration accuracy needed for outdoor operation. These sensors and collocated meteorological equipment are an important part of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility, which has supported parallel integrated measurements of atmospheric and surface properties for more than two decades at fixed and mobile sites around the world. The versatile capability of these ground-based measurements includes 1) rich spectral information required for retrieving cloud and aerosol microphysical properties, such as cloud phase, cloud particle size, and aerosol size distributions, and 2) high temporal resolution needed for capturing fast evolution of cloud microphysical properties in response to rapid changes in meteorological conditions. Here we describe examples of how ARM's spectral radiation measurements are being used to improve understanding of the complex processes governing microphysical, optical, and radiative properties of clouds and aerosol.

54 ENVIRONMENTAL SCIENCES↗

Precise Motion Control of Hybrid Hydraulic Electric Architecture (HHEA)

Off-highway heavy-duty vehicles have been long-standing users of hydraulic systems for power transmission and control. However, traditional hydraulic systems suffer from significant energy losses which lead to increased operating costs and a larger carbon footprint due to higher CO2 emissions. Improving the efficiency of these mobile machines is crucial not only for reducing their environmental impact but also for saving billions of dollars in operating costs. Currently, the state-of-the-art Load Sensing Architecture uses throttling valves for control, which significantly reduces its efficiency and does not recuperate energy from over-running loads. Researchers have developed several architectures such as Common Pressure Rail systems, Displacement Control, STEAM, and Electrohydraulic Architecture to improve the efficiency of off-road mobile machines. However, each of these architectures has its drawbacks. To increase system efficiency and take advantage of electrification benefits, our research group has developed a novel Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA can significantly improve efficiency, decrease the size of electrical components, and maintain control performance. This new architecture has the potential to revolutionize the off-highway mobile machine industry and lead to a more sustainable future. The HHEA uses a set of common pressure rails to provide the majority of power to the actuators via power-dense hydraulics and uses electric motors for precise control and power modulation. In the context of off-road mobile machines, energy savings are undoubtedly important but it is equally important to consider the machines’ ability to perform tasks with precision and accuracy according to given commands. Therefore, precise motion control is of utmost importance to maintain the utility of Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA presents a unique challenge to motion control due to the discrete pressure changes that occur when the system switches between selected pressure rails. These changes are made to minimize system inefficiencies or to keep the system within the torque capability of the electric motor. Hence, it is important to solve the motion control challenges for HHEA. This thesis aims at developing an effective motion control strategy for HHEA. The dissertation presents a two-tiered control strategy for HHEA, comprising a high-level and a low-level controller. The primary responsibility of the high- level controller is to optimize energy efficiency by making informed pressure rail selections. On the other hand, the low-level controller is focused on achieving precise motion control of the HHEA, which is crucial for realizing the desired reference trajectories. To achieve this, the low-level controller utilizes a passivity-based backstepping integral controller as the nominal control, which handles the motion control between two pressure rail switches. Additionally, a separate least norm controller is utilized as a transition controller to manage motion control during pressure rail transitions. The effectiveness of the combined control strategy is demonstrated through experiments conducted on two hardware-in-the-loop testbeds. Furthermore, the HHEA is installed on the boom and stick actuators of a backhoe arm to build a Human-in-the-Loop system that a human operator can control. A real-time rail switching algorithm is developed to determine pressure rail switching based on present duty cycle information from the operator. Modifications have been made to the human-machine interface to achieve more intuitive control. Modifications include performing control in the task-oriented coordinates, incorporating pressure feedback to enhance control with physical interaction, and using velocity field control to simplify multi-degree-of-freedom tasks and to enable novice operators to perform them with reduced risk, improved efficiency, and productivity. The research in this dissertation makes significant contributions to the field of off-road mobile machine control, providing a novel and effective control strategy for the HHEA, and demonstrating the potential for simplified machine operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗