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Contents include the following: NASA's Missions and Aeronautics Research. Today's Air Traffic Control System. Development of Decision-Support Tools. The Center-TRACON Automation System (CTAS). The Traffic Management Advisor (TMA). The Multi-Center Traffic Management Advisor (McTMA). The Surface Management System (SMS). Future Directions: The Joint Planning and Development Office.
Continuing advances in airport surface management and improvements in airport surface safety are required to enable future growth in air traffic throughout the airspace, as airport arrival and departure delays create a major system bottleneck. These airport management and safety advances will be built upon improved communications, navigation, surveillance, and weather sensing, creating an information environment supporting system automation. The efficient movement of the digital data generated from these systems requires an underlying communications network infrastructure to connect data sources with the intended users with the required quality of service. Current airport surface communications consists primarily of buried copper or fiber cable. Safety related communications with mobile airport surface assets occurs over 25 kHz VHF voice and data channels. The available VHF spectrum, already congested in many areas, will be insufficient to support future data traffic requirements. Therefore, a broadband wireless airport surface communications network is considered a requirement for the future airport component of the air transportation system. Progress has been made on defining the technology and frequency spectrum for the airport surface wireless communications network. The development of a test and demonstration facility and the definition of required testing and standards development are now underway. This paper will review the progress and planned future work.
The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been collaborating to conduct joint research addressing future surface traffic management challenges. The surface management tool from DLR, called Taxi Routing for Aircraft: Creation and Controlling (TRACC), was adapted to be integrated in NASA's fast-time simulation environment called Surface Operations Simulator and Scheduler (SOSS). The research described in this paper 1) applied TRACC to trajectory-based ramp traffic management, where TRACC generates conflict-free aircraft trajectories in a congested ramp area, 2) investigated the feasibility of the concept through the integrated TRACC-SOSS fast-time simulation, and 3) evaluated the performance of the integrated system. For this activity, TRACC was adapted for ramp operations at Charlotte Douglas International Airport, called TRACC_PB (TRACC for pushback optimization). TRACC_PB provides four-dimensional taxi trajectories with a command speed profile for each aircraft following standard taxi routes within the ramp area. In this study, departures are given the Target Movement Area entry Times (TMATs) provided by the baseline surface metering scheduler based on NASA's Spot and Runway Departure Advisor (SARDA). TRACC_PB also calculates optimal pushback times for departures, as well as the times when arrivals shall enter the ramp, the Target Movement area Exit Times (TMETs). The initial results showed that the TRACC_PB successfully generated conflict-free trajectories for the ramp area taxi operations and improved taxiing efficiency compared to the baseline results. TRACC_PB aimed to provide conflict-free taxi routes avoiding any stops while taxiing. This resulted in longer gate hold times for departures and postponed throughput values compared to the baseline simulation without trajectory optimization. Having conflict-free routes without stoppage also created shorter taxi times but required renegotiation of the given TMATs. TRACC_PB also achieved reductions in both fuel consumption and engine emissions (17% for departures and 10% for arrivals), which correlate with the ramp taxi time reduction.
The authors describe and illustrate an integrated trio of software programs for carrying out surface-based analyses of cerebral cortex. The first component of this trio, SureFit (Surface Reconstruction by Filtering and Intensity Transformations), is used primarily for cortical segmentation, volume visualization, surface generation, and the mapping of functional neuroimaging data onto surfaces. The second component, Caret (Computerized Anatomical Reconstruction and Editing Tool Kit), provides a wide range of surface visualization and analysis options as well as capabilities for surface flattening, surface-based deformation, and other surface manipulations. The third component, SuMS (Surface Management System), is a database and associated user interface for surface-related data. It provides for efficient insertion, searching, and extraction of surface and volume data from the database.
The runway configuration used by an airport has significant implications with respect to its capacity and ability to effectively manage surface and airborne traffic. Aircraft operators rely on runway configuration information because it can significantly affect an airline's operations and planning of their resources. Current practices in runway management are limited by a relatively short time horizon for reliable weather information and little assistance from automation. Wind velocity is the primary consideration when selecting a runway configuration; however when winds are below a defined threshold, discretion may be used to determine the configuration. Other considerations relevant to runway configuration selection include airport operator constraints, weather conditions (other than winds) traffic demand, user preferences, surface congestion, and navigational system outages. The future offers an increasingly complex landscape for the runway management process. Concepts and technologies that hold the potential for capacity and efficiency increases for both operations on the airport surface and in terminal and enroute airspace are currently under investigation. Complementary advances in runway management are required if capacity and efficiency increases in those areas are to be realized. The System Oriented Runway Management (SORM) concept has been developed to address this critical part of the traffic flow process. The SORM concept was developed to address all aspects of runway management for airports of varying sizes and to accommodate a myriad of traffic mixes. SORM, to date, addresses the single airport environment; however, the longer term vision is to incorporate capabilities for multiple airport (Metroplex) operations as well as to accommodate advances in capabilities resulting from ongoing research. This paper provides an update of research supporting the SORM concept including the following: a concept of overview, results of a TRCM simulation, single airport and Metroplex modeling effort and a benefits assessment.
This paper describes past and present air-traffic-management research at NASA Ames Research Center. The descriptions emerge from the perspective of a technical manager who supervised the majority of this research for the last four years. Past research contributions built a foundation for calculating accurate flight trajectories to enable efficient airspace management in time. That foundation led to two predominant research activities that continue to this day - one in automatically separating aircraft and the other in optimizing traffic flows. Today s national airspace uses many of the applications resulting from research at Ames. These applications include the nationwide deployment of the Traffic Management Advisor, new procedures enabling continuous descent arrivals, cooperation with industry to permit more direct flights to downstream way-points, a surface management system in use by two cargo carriers, and software to evaluate how well flights conform to national traffic management initiatives. The paper concludes with suggestions for prioritized research in the upcoming years. These priorities include: enabling more first-look operational evaluations, improving conflict detection and resolution for climbing or descending aircraft, and focusing additional attention on the underpinning safety critical items such as a reliable datalink.
As the amount of air traffic increases over the years, most airports simply do not have the means of expanding to handle the intensified traffic on the surface that will ensue. Precise surveillance equipment and automation concepts, as well as advanced surface traffic algorithms are being developed to improve airport efficiency. These surface algorithms require inputs unique to each airport to ensure maximum efficiency, and minimal taxi delay. This study analyzes surface traffic at Dallas-Fort Worth International Airport (DFW) to determine the effect of the number of aircraft on the surface and the amount of stop and go situations they experience to the amount of additional taxi time encountered. If the surface capacity of an airport is known, minimal delay can be accomplished by limiting the number of taxiing aircraft to that capacity. This concept is related to highways, where traffic flow drastically decreases as more cars occupy the road. An attempt to minimize this effect on highways is seen with the use of metering lights at freeway on-ramps. Since the surface traffic at airports is highly regulated, and aircraft are less mobile on the ground, limiting the surface count to a certain number can greatly reduce the amount of additional taxi time encountered, as well as reduce hazardous emissions. This study will also find the regions of an airport that encounter the most additional taxi time when the number of aircraft in that area is increased. This could help surface traffic algorithms avoid congesting that area, or re-route aircraft to different runways when that area reaches its capacity. The relationship between the amount of stop and go situations an aircraft encounters and their effect on the taxi time of that aircraft will also be investigated. This will help to determine the effect of holding an aircraft on the taxiway as opposed to re-routing it. The lesser of the two should be used when developing surface traffic algorithms to further minimize the delay encountered. The fields investigated in this study include taxi time, the number of aircraft on the surface, the number of stop and go situations, and the time stopped for each aircraft. Taxi time is defined as spot to runway for departures, and runway to spot for arrivals. It does not include ramp area taxi time because the ramp area is controlled differently, and surface traffic schedulers do not currently incorporate them. Taxi time is found by finding the difference between take-off time (OFF) and spot crossing time for departures, and spot crossing time and landing time (ON) for arrivals. All surface data was either found directly using the Surface Operations Data Analysis and Adaptation (SODAA), a tool to analyze the Surface Management System (SMS) generated log files, or indirectly from SODAA using Matlab to derive values from SODAA data. The number of aircraft on the surface is found by looping through the ON times, OFF times, and spot times for each aircraft during a particular day. For each departure aircraft, surface counts are taken at its spot crossing and OFF time. The average of these two is used as the surface count for that aircraft. For arrivals, surface counts are taken at its ON time and its spot crossing time. The average of these two is used.
NASA's Airspace Technical Demonstration-2 (ATD-2) Integrated Arrival, Departure, and Surface (IADS) traffic management system integrates strategic and tactical scheduling tools for traffic sequencing from the gate to the overhead stream and back again for multi-airport, metroplex environments. The system is expected to increase airport efficiency, predictability, and throughout while improving information sharing among all airport operators. A series of knowledge elicitation sessions were conducted with commercial airline pilots and general aviation pilots to characterize airport operations and procedures. This presentation describes ATD-2 IADS-enabled Information Sharing impacts on the Flight Deck, benefits of that Information Sharing, pilot procedural changes, our pilot engagement/outreach efforts, use of a Mobile App to faciliate information flow in GA operations, and future IADS efforts at other airports/metroplexes.
The current lack of unsettled mass gauging is a key roadblock for many space activities, such as orbital refueling, missions to the Moon and Mars, and nuclear thermal and nuclear electric propulsion technologies. Liquid can form any one of an infinite number of configurations in microgravity, such as floating in globs or accumulating on tank surfaces in discontiguous volumes, or both. Capacitive sensing requires no moving parts and dissipates close to zero heat, making it an ideal candidate for cryogenic fluid mass gauging in settled and unsettled configurations. Capacitive sensing has a history of proven use in space propellant tanks, including tanks on the space shuttle, Saturn V, and the Apollo Lunar Excursion Module. Modern capacitive sensor technology allows using the entire tank as the capacitor volume by placing electrodes on the tank walls and propellant management surfaces. Capacitance is directly related to density, and therefore to mass for fixed volumes. In this presentation, we discuss the concepts behind whole-tank capacitance mass gauging and associated engineering challenges. We describe recent efforts to develop a micro-g unsettled cryogenic mass gauge using whole-tank capacitance sensing, including the development of test beds, electronics, and algorithms. We describe several mathematical processing techniques, including empirical-based averaging, electrical capacitance volume tomography, and spatial regularization. A modeling study, performed using settled configurations in gravity and no gravity, and with a set of 100 random fluid configurations, has indicated that spatial regularization, in which capacitance measurements are weighted to account for non-uniform electric fields, yields a mass fraction accuracy of 8% for any fluid configuration. Such a sensor is expected to operate in real time with a sampling frequency of at least 1 kHz.
PSSEARCH provides predictive sea state estimation, coupled with closed-loop feedback control for automated ride control. It enables a manned or unmanned watercraft to determine the 3D map and sea state conditions in its vicinity in real time. Adaptive path-planning/ replanning software and a control surface management system will then use this information to choose the best settings and heading relative to the seas for the watercraft. PSSEARCH looks ahead and anticipates potential impact of waves on the boat and is used in a tight control loop to adjust trim tabs, course, and throttle settings. The software uses sensory inputs including IMU (Inertial Measurement Unit), stereo, radar, etc. to determine the sea state and wave conditions (wave height, frequency, wave direction) in the vicinity of a rapidly moving boat. This information can then be used to plot a safe path through the oncoming waves. The main issues in determining a safe path for sea surface navigation are: (1) deriving a 3D map of the surrounding environment, (2) extracting hazards and sea state surface state from the imaging sensors/map, and (3) planning a path and control surface settings that avoid the hazards, accomplish the mission navigation goals, and mitigate crew injuries from excessive heave, pitch, and roll accelerations while taking into account the dynamics of the sea surface state. The first part is solved using a wide baseline stereo system, where 3D structure is determined from two calibrated pairs of visual imagers. Once the 3D map is derived, anything above the sea surface is classified as a potential hazard and a surface analysis gives a static snapshot of the waves. Dynamics of the wave features are obtained from a frequency analysis of motion vectors derived from the orientation of the waves during a sequence of inputs. Fusion of the dynamic wave patterns with the 3D maps and the IMU outputs is used for efficient safe path planning.
The high-latitude ionosphere is considered as a convenient 'viewing screen' for deducing magnetospheric convection, since the footprints of the immense volume of the magnetospheric flux tubes map to a considerably more manageable surface area. This area is, however, still very large, and an instantaneous measurement of the flow pattern over the entire high latitude region is presently not feasible. Therefore, much effort has been made in synthesizing many passes of polar orbiting spacecraft into convection patterns. The present investigation follows the development of a description of the global convection pattern and its dependence on the interplanetary magnetic field (IMF). The convection pattern is described in terms of the plasma flow speed and direction. Attention is given to the southward interplanetary magnetic field and the northward interplanetary magnetic field.
Future needs of the National Airspace System require decision support tools to adopt a service-oriented architecture in alignment with the FAA’s vision for an Info-Centric NAS. To achieve this, many existing systems will need to undergo a digital transformation from a monolithic decision support tool to a service-oriented architecture where individual services are exposed through well defined Application Programming Interfaces (APIs). To enable this transformation, NASA has developed the Digital Information Platform as a cloud based foundation for development of aviation services with a special focus towards Artificial Intelligence and Machine Learning (ML) services. This paper describes the work required for the transformation of NASA’s legacy surface management system to a real-time ML based decision support system deployed in the cloud. Details of the Machine Learning Operations (MLOps) infrastructure and best practices are described which enabled the end-toend lifecycle management of ML within an integrated software system. Validation results are provided from an operational field evaluation where performance was benchmarked against the legacy approach.
Discussion of the propellant management system requirements derived for the Viking 75 mission, and review of a series of surface tension propellant management system design concepts. The chosen concept is identified and its mission operation described. The ullage bubble and bulk liquid positioning characteristics are presented, along with propellant dynamic considerations entailed by thrust initiation/termination. Pressurization design considerations, required to assure minimum disturbance to the bulk propellant, are introduced as well as those of the tank ullage vent. Design provisions to assure liquid communication between tank ends are discussed. Results of a preliminary design study are presented, including mechanical testing requirements to assure structural integrity, propellant compatibility, and proper installation.
The BLiSS: Cargo Management and Retrieval project is a submission to the NASA X-Hab challenge for an autonomous system of cargo storage and retrieval for use on the Lunar Gateway system. The system is designed to stow 5 tonnes of cargo within a capsule that has an internal diameter of 3.2 meters and height of 6 meters for cargo that will be up to 0.8 meters in any one dimension. The system will inventory all cargo items placed in each cargo container and then track the containers using RFID chips for autonomous stowage and retrieval upon request by on-station crew.
The Surface Currents Database Management System (SCDBMS) provides access to the Surface Currents Data Base (SCDB) which is maintained by the Naval Oceanographic Office (NAVOCEANO). The SCDBMS incorporates database technology in providing seamless access to surface current data. The SCDBMS is an interactive software application with a graphical user interface (GUI) that supports user control of SCDBMS functional capabilities. The purpose of this document is to define and describe the structural framework and logistical design of the software components/units which are integrated into the major computer software configuration item (CSCI) identified as the SCDBMS, Version 1.0. The preliminary design is based on functional specifications and requirements identified in the governing Statement of Work prepared by the Naval Oceanographic Office (NAVOCEANO) and distributed as a request for proposal by the National Aeronautics and Space Administration (NASA).
This book chapter describes the issues surrounding managing planetary dust during surface operations. It summarizes the effects of dust on surface operations, the effects of planetary surface environments on dust transport, and a snapshot of current dust mitigation technologies.
The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted; one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft: Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.
The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted: one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft58; Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.