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At least 271 records · Page 15

Applying Graph Theory to Problems in Air Traffic Management

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it is shown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

precision arrival scheduling↗

The Role of Design-of-Experiments in Managing Flow in Compact Air Vehicle Inlets

It is the purpose of this study to demonstrate the viability and economy of Design-of-Experiments methodologies to arrive at microscale secondary flow control array designs that maintain optimal inlet performance over a wide range of the mission variables and to explore how these statistical methods provide a better understanding of the management of flow in compact air vehicle inlets. These statistical design concepts were used to investigate the robustness properties of low unit strength micro-effector arrays. Low unit strength micro-effectors are micro-vanes set at very low angles-of-incidence with very long chord lengths. They were designed to influence the near wall inlet flow over an extended streamwise distance, and their advantage lies in low total pressure loss and high effectiveness in managing engine face distortion. The term robustness is used in this paper in the same sense as it is used in the industrial problem solving community. It refers to minimizing the effects of the hard-to-control factors that influence the development of a product or process. In Robustness Engineering, the effects of the hard-to-control factors are often called noise , and the hard-to-control factors themselves are referred to as the environmental variables or sometimes as the Taguchi noise variables. Hence Robust Optimization refers to minimizing the effects of the environmental or noise variables on the development (design) of a product or process. In the management of flow in compact inlets, the environmental or noise variables can be identified with the mission variables. Therefore this paper formulates a statistical design methodology that minimizes the impact of variations in the mission variables on inlet performance and demonstrates that these statistical design concepts can lead to simpler inlet flow management systems.

Anderson, Bernhard H.↗

Development of a Safety Hazards Risk Assessment Tool for Uncrewed Aircraft System Traffic Management during Preflight Planning

Tremendous growth in the uncrewed and remotely piloted vehicle market is expected in low-altitude, uncontrolled airspace, resulting in potential decreases in safety without systems that support monitoring, assessing, and mitigating risk. At NASA, the System-Wide Safety (SWS) project has been developing a suite of data-driven tools to predict hazards so that the potential risks that these hazards pose can be mitigated. Services to predict various hazards have been developed, including battery capacity, proximity to static obstacles, population risks, global positioning system signal strength, radio frequency spectrum interference risk, and vertiport congestion. These services can monitor hazards along a flight path and if any risks posed by these hazards exceed a threshold, the uncrewed aircraft system (UAS) fleet manager can be alerted to mitigate the risk by modifying the flight path, changing the scheduled departure or arrival times, and/or diverting the vehicle to an alternate vertiport. These services were originally developed to monitor and assess risks during flight, but they have been adapted to assess hazard risks prior to departure so that a fleet manager can evaluate the potential risks for a fleet of UAS along their planned flight paths. These services have been integrated into a prototype tool called the Supplemental Data Service Provider-Consolidated Dashboard (SDSP-CD), developed at NASA Ames Research Center. The tool consists of a dashboard which provides a comprehensive overview for a number of risks and a map display that shows the details of the hazards along each flight’s path. Based on the findings from three previous studies, the SDSP-CD has been updated with new design elements and functions. In this paper, we describe lessons learned from the previous studies, changes made to the interface, and the feedback received during a follow-up usability study. Overall, participants reported that there is a substantial benefit of having a fleet manager use a consolidated dashboard to assess hazards for the vehicles in their fleet and to provide situational awareness to potential risks so that they can be mitigated prior to flight. Once the SDSP-CD matures, it will need to be integrated into flight and mission planning tools. Some initial thoughts on how this integration should be accomplished are shared in this paper. Finally, the functional differences between preflight vs. in-flight risk assessment and the differences in fleet manager vs. UAS pilot roles that may require different information and user interactions are discussed.

preflight↗

Airborne Precision Spacing: A Trajectory-based Approach to Improve Terminal Area Operations

Airborne Precision Spacing has been developed by the National Aeronautics and Space Administration (NASA) over the past seven years as an attempt to benefit from the capabilities of the flight deck to precisely space their aircraft relative to another aircraft. This development has leveraged decades of work on improving terminal area operations, especially the arrival phase. With APS operations, the air traffic controller instructs the participating aircraft to achieve an assigned inter-arrival spacing interval at the runway threshold, relative to another aircraft. The flight crew then uses airborne automation to manage the aircraft s speed to achieve the goal. The spacing tool is designed to keep the speed within acceptable operational limits, promote system-wide stability, and meet the assigned goal. This reallocation of tasks with the controller issuing strategic goals and the flight crew managing the tactical achievement of those goals has been shown to be feasible through simulation and flight test. A precision of plus or minus 2-3 seconds is generally achievable. Simulations of long strings of arriving traffic show no signs of instabilities or compression waves. Subject pilots have rated the workload to be similar to current-day operations and eye-tracking data substantiate this result. This paper will present a high-level review of research results over the past seven years from a variety of tests and experiments. The results will focus on the precision and accuracy achievable, flow stability and some major sources of uncertainty. The paper also includes a summary of the flight crew s procedures and interface and a brief concept overview.

Barmore, Bryan↗

An analysis of landing rates and separations at the Dallas/Fort Worth International Airport

Advanced air traffic management systems such as the Center/TRACON Automation System (CTAS) should yield a wide range of benefits, including reduced aircraft delays and controller workload. To determine the traffic-flow benefits achievable from future terminal airspace automation, live radar information was used to perform an analysis of current aircraft landing rates and separations at the Dallas/Fort Worth International Airport. Separation statistics that result when controllers balance complex control procedural constraints in order to maintain high landing rates are presented. In addition, the analysis estimates the potential for airport capacity improvements by determining the unused landing opportunities that occur during rush traffic periods. Results suggest a large potential for improving the accuracy and consistency of spacing between arrivals on final approach, and they support earlier simulation findings that improved air traffic management would increase capacity and reduce delays.

Ballin, Mark G.↗

Dual-Use Aspects of System Health Management

System Health Management functionality is an essential part of any space launch system. Health management functionality is an integral part of mission reliability, since it is needed to verify the reliability before the mission starts. Health Management is also a key factor in life cycle cost reduction and in increasing system availability. The degree of coverage needed by the system and the degree of coverage made available at a reasonable cost are critical parameters of a successful design. These problems are not unique to the launch vehicle world. In particular, the Intelligent Vehicle Highway System, commercial aircraft systems, train systems, and many types of industrial production facilities require various degrees of system health management. In all of these applications, too, the designers must balance the benefits and costs of health management in order to optimize costs. The importance of an integrated system is emphasized. That is, we present the case for considering health management as an integral part of system design, rather than functionality to be added on at the end of the design process. The importance of maintaining the system viewpoint is discussed in making hardware and software tradeoffs and in arriving at design decisions. We describe an approach to determine the parameters to be monitored in any system health management application. This approach is based on Design of Experiments (DOE), prototyping, failure modes and effects analyses, cost modeling and discrete event simulation. The various computer-based tools that facilitate the approach are discussed. The approach described originally was used to develop a fault tolerant avionics architecture for launch vehicles that incorporated health management as an integral part of the system. Finally, we discuss generalizing the technique to apply it to other domains. Several illustrations are presented.

Owens, P. R.↗

Long-term, large-scale experiment reveals the effects of seed limitation, climate, and anthropogenic disturbance on restoration of plant communities in a biodiversity hotspot

Ecological restoration is essential for maintaining biodiversity in the face of dynamic, global changes in climate, human land use, and disturbance regimes. Effective restoration requires understanding bottlenecks in plant community recovery that exist today, while recognizing that these bottlenecks may relate to complex histories of environmental change. Such understanding has been a challenge because few long-term, well-replicated experiments exist to decipher the demographic processes influencing recovery for numerous species against the backdrop of multiyear variation in climate and management. Here we address this challenge through a long-term and geographically expansive experiment in longleaf pine savannas, an imperiled ecosystem and biodiversity hotspot in the southeastern United States. Using 48 sites at three locations spanning 480 km, the 8-y experiment manipulated initial seed arrival for 24 herbaceous plant species and presence of competitors to evaluate the impacts of climate variability and management actions (e.g., prescribed burning) on plant establishment and persistence. Adding seeds increased plant establishment of many species. Cool and wet climatic conditions, low tree density, and reduced litter depth also promoted establishment. Once established, most species persisted for the duration of the 8-y experiment. Plant traits were most predictive when tightly coupled to the process of establishment. Our results illustrate how seed additions can restore plant diversity and how interannual climatic variation affects the dynamics of plant communities across a large region. The significant effects of temperature and precipitation inform how future climate may affect restoration and conservation via large-scale changes in the fundamental processes of establishment and persistence.

60 APPLIED LIFE SCIENCES↗

Online Learning and Pricing for Service Systems with Reusable Resources

We consider a price-based revenue management problem with finite reusable resources over a finite time horizon T. Customers arrive following a price-dependent Poisson process, and each customer requests one unit of c homogeneous reusable resources. If there is an available unit, the customer gets served within a price-dependent exponentially distributed service time; otherwise, the customer waits in a queue until the next available unit. In this paper, we assume that the firm does not know how the arrival and service rates depend on posted prices, and thus it makes adaptive pricing decisions in each period based only on past observations to maximize the cumulative revenue. Given a discrete price set with cardinality P, we propose two online learning algorithms, termed batch upper confidence bound (BUCB) and batch Thompson sampling (BTS), and prove that the cumulative regret upper bound is O˜(√PT) , which matches the regret lower bound. In establishing the regret, we bound the transient system performance upon price changes via a novel coupling argument, and also generalize bandits to accommodate subexponential rewards. Here, we also extend our approach to models with balking and reneging customers and discuss a continuous price setting. Our numerical experiments demonstrate the efficacy of the proposed BUCB and BTS algorithms.

97 MATHEMATICS AND COMPUTING↗

The Dynamic Planner: The Sequencer, Scheduler, and Runway Allocator for Air Traffic Control Automation

The Dynamic Planner (DP) has been designed, implemented, and integrated into the Center-TRACON Automation System (CTAS) to assist Traffic Management Coordinators (TMCs), in real time, with the task of planning and scheduling arrival traffic approximately 35 to 200 nautical miles from the destination airport. The TMC may input to the DP a series of current and future scheduling constraints that reflect the operation and environmental conditions of the airspace. Under these constraints, the DP uses flight plans, track updates, and Estimated Time of Arrival (ETA) predictions to calculate optimal runway assignments and arrival schedules that help ensure an orderly, efficient, and conflict-free flow of traffic into the terminal area. These runway assignments and schedules can be shown directly to controllers or they can be used by other CTAS tools to generate advisories to the controllers. Additionally, the TMC and controllers may override the decisions made by the DP for tactical considerations. The DP will adapt to computations to accommodate these manual inputs.

Wong, Gregory L.↗

Delay Banking for Managing Air Traffic

Delay banking has been invented to enhance air-traffic management in a way that would increase the degree of fairness in assigning arrival, departure, and en-route delays and trajectory deviations to aircraft impacted by congestion in the national airspace system. In delay banking, an aircraft operator (airline, military, general aviation, etc.) would be assigned a numerical credit when any of their flights are delayed because of an air-traffic flow restriction. The operator could subsequently bid against other operators competing for access to congested airspace to utilize part or all of its accumulated credit. Operators utilize credits to obtain higher priority for the same flight, or other flights operating at the same time, or later, in the same airspace, or elsewhere. Operators could also trade delay credits, according to market rules that would be determined by stakeholders in the national airspace system. Delay banking would be administered by an independent third party who would use delay banking automation to continually monitor flights, allocate delay credits, maintain accounts of delay credits for participating airlines, mediate bidding and the consumption of credits of winning bidders, analyze potential transfers of credits within and between operators, implement accepted transfers, and ensure fair treatment of all participating operators. A flow restriction can manifest itself in the form of a delay in assigned takeoff time, a reduction in assigned airspeed, a change in the position for the aircraft in a queue of all aircraft in a common stream of traffic (e.g., similar route), a change in the planned altitude profile for an aircraft, or change in the planned route for the aircraft. Flow restrictions are typically imposed to mitigate traffic congestion at an airport or in a region of airspace, particularly congestion due to inclement weather, or the unavailability of a runway or region of airspace. A delay credit would be allocated to an operator of a flight that has accepted, or upon which was imposed, a flow restriction. The amount of the credit would increase with the amount of delay caused by the flow restriction, the exact amount depending on which of several candidate formulas is eventually chosen. For example, according to one formula, there would be no credit for a delay smaller than some threshold value (e.g., 30 seconds) and the amount of the credit for a longer delay would be set at the amount of the delay minus the threshold value. Optionally, the value of a delay credit could be made to decay with time according to a suitable formula (e.g., an exponential decay). Also, optionally, a transaction charge could be assessed against the value of a delay credit that an operator used on a flight different from the one for which the delay originated or that was traded with a different operator. The delay credits accumulated by a given airline could be utilized in various ways. For example, an operator could enter a bid for priority handling in a new flow restriction that impacts one or more of the operator s flights; if the bid were unsuccessful, all or a portion of the credit would be returned to the bidder. If the bid pertained to a single aircraft that was in a queue, delay credits could be consumed in moving the aircraft to an earlier position within the queue. In the case of a flow restriction involving a choice of alternate routes, planned altitude profile, aircraft spacing, or other non-queue flow restrictions, delay credits could be used to bid for an alternative assignment.

Green, Steve↗

Initial Analysis of Digitally Enabled Cooperative Operations in Class D Terminal Airspace

The primary contribution of this paper is an initial analysis of integrating digitally enabled cooperative operations (or digital operations for short) with Visual Flight Rules (VFR) and Instrument Flight Rules (IFR) operations in the terminal airspace around a Class D airport, specifically around Fort Worth Alliance airport (KAFW). Enabled by connected digital technologies and automated information exchange, digital operations as envisioned would utilize cooperative practices and operator-responsible separation to ensure safety. In the present study, three conflict management configurations for digital operations were analyzed: 1) centralized with a single instance of a conflict management service to model a scenario with only one fleet operator conducting digital operations or all fleet operators utilizing the same service, 2) federated with two different instances to model a scenario with two different fleet operators conducting digital operations, and 3) fully distributed with a different instance for each digital operation. In simulations in which recorded tracks for VFR and IFR operations were played back and digital operations were modeled that would nominally arrive at KAFW once every 20 minutes (given no conflict resolution maneuvers), there were one or fewer losses of separation (LOS) across the three conflict management configurations. The same result was seen in simulations in which digital operations would nominally arrive at KAFW once every 10 minutes. However, in simulations in which digital operations would nominally arrive at KAFW once every 5 minutes, the number of LOS ranged between six and ten. This highlights the need for follow-on research to investigate the extent to which additional capabilities for digital operations, such as complexity management and/or flow organization, may be needed.

digitally enabled cooperative operations, digital ↗

Initial Analysis of Digitally Enabled Cooperative Operations in Class D Terminal Airspace

The primary contribution of this paper is an initial analysis of integrating digitally enabled cooperative operations (or digital operations for short) with Visual Flight Rules (VFR) and Instrument Flight Rules (IFR) operations in the terminal airspace around a Class D airport, specifically around Fort Worth Alliance airport (KAFW). Enabled by connected digital technologies and automated information exchange, digital operations as envisioned would utilize cooperative practices and operator-responsible separation to ensure safety. In the present study, three conflict management configurations for digital operations were analyzed: 1) centralized with a single instance of a conflict management service to model a scenario with only one fleet operator conducting digital operations or all fleet operators utilizing the same service, 2) federated with two different instances to model a scenario with two different fleet operators conducting digital operations, and 3) fully distributed with a different instance for each digital operation. In simulations in which recorded tracks for VFR and IFR operations were played back and digital operations were modeled that would nominally arrive at KAFW once every 20 minutes (given no conflict resolution maneuvers), there were one or fewer losses of separation (LOS) across the three conflict management configurations. The same result was seen in simulations in which digital operations would nominally arrive at KAFW once every 10 minutes. However, in simulations in which digital operations would nominally arrive at KAFW once every 5 minutes, the number of LOS ranged between six and ten. This highlights the need for follow-on research to investigate the extent to which additional capabilities for digital operations, such as complexity management and/or flow organization, may be needed.

digitally enabled cooperative operations↗

Application of Computational Fluid Dynamics to the Study of Vortex Flow Control for the Management of Inlet Distortion

The present study demonstrates that the Reduced Navier-Stokes code RNS3D can be used very effectively to develop a vortex generator installation for the purpose of minimizing the engine face circumferential distortion by controlling the development of secondary flow. The computing times required are small enough that studies such as this are feasible within an analysis-design environment with all its constraints of time and costs. This research study also established the nature of the performance improvements that can be realized with vortex flow control, and suggests a set of aerodynamic properties (called observations) that can be used to arrive at a successful vortex generator installation design. The ultimate aim of this research is to manage inlet distortion by controlling secondary flow through an arrangements of vortex generators configurations tailored to the specific aerodynamic characteristics of the inlet duct. This study also indicated that scaling between flight and typical wind tunnel test conditions is possible only within a very narrow range of generator configurations close to an optimum installation. This paper also suggests a possible law that can be used to scale generator blade height for experimental testing, but further research in this area is needed before it can be effectively applied to practical problems. Lastly, this study indicated that vortex generator installation design for inlet ducts is more complex than simply satisfying the requirement of attached flow, it must satisfy the requirement of minimum engine face distortion.

Anderson, Bernhard H.↗

Predicting Airport Runway Configuration for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.

air traffic management↗

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.

air traffic management↗

Research Progress and Accomplishments on ISS

The first research payloads reached the International Space Station (ISS) more than two years ago, with research operating continuously since March 2001. Seven research racks are currently on-orbit, with three more arriving soon to expand science capabilities. Through the first five expeditions, 60 unique NASA-managed investigations from 11 nations have been supported, many continuing into later missions. More than 90,000 experiment hours have been completed, and more than 1,000 hours of crew time have been dedicated to research, numbers that grow daily. The multidisciplinary program includes research in life sciences, physical sciences, biotechnology, Earth sciences, technology demonstrations as well as commercial endeavors and educational activities. The Payload Operations and Integration Center monitors the onboard activities around the clock, working with numerous Principal Investigators and Payload Developers at their remote sites. Future years will see expansion of the station with research modules provided by the European Space Agency and Japan, which will be outfitted with additional research racks. The first research payloads arrived at ISS more than two years ago, and continuous science has been ongoing for more than one and a half years. During this time, the research capabilities have been tremendously increased, even as assembly of the overall platform continues. Despite significant challenges along the way, ISS continues to successfully support a large number of investigations in a variety of research disciplines. The results of some of the early investigations are reaching the publication stage. The near future looms with new challenges, but experience to date and dedicated efforts give reason to be optimistic that the challenges will be overcome and that new and greater successes will be added to past ones.

Roe, Lesa B.↗

Leveraging the Cloud for Robust and Efficient Lunar Image Processing

The Lunar Mapping and Modeling Project (LMMP) is tasked to aggregate lunar data, from the Apollo era to the latest instruments on the LRO spacecraft, into a central repository accessible by scientists and the general public. A critical function of this task is to provide users with the best solution for browsing the vast amounts of imagery available. The image files LMMP manages range from a few gigabytes to hundreds of gigabytes in size with new data arriving every day. Despite this ever-increasing amount of data, LMMP must make the data readily available in a timely manner for users to view and analyze. This is accomplished by tiling large images into smaller images using Hadoop, a distributed computing software platform implementation of the MapReduce framework, running on a small cluster of machines locally. Additionally, the software is implemented to use Amazon's Elastic Compute Cloud (EC2) facility. We also developed a hybrid solution to serve images to users by leveraging cloud storage using Amazon's Simple Storage Service (S3) for public data while keeping private information on our own data servers. By using Cloud Computing, we improve upon our local solution by reducing the need to manage our own hardware and computing infrastructure, thereby reducing costs. Further, by using a hybrid of local and cloud storage, we are able to provide data to our users more efficiently and securely. 12 This paper examines the use of a distributed approach with Hadoop to tile images, an approach that provides significant improvements in image processing time, from hours to minutes. This paper describes the constraints imposed on the solution and the resulting techniques developed for the hybrid solution of a customized Hadoop infrastructure over local and cloud resources in managing this ever-growing data set. It examines the performance trade-offs of using the more plentiful resources of the cloud, such as those provided by S3, against the bandwidth limitations such use encounters with remote resources. As part of this discussion this paper will outline some of the technologies employed, the reasons for their selection, the resulting performance metrics and the direction the project is headed based upon the demonstrated capabilities thus far.

Cloud Computing↗