SEARCH · Search NASA

Results for “Scheduled arrival operations”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

NASA NTRS2014

Interval Management Display Design Study

In 2012, the Federal Aviation Administration (FAA) estimated that U.S. commercial air carriers moved 736.7 million passengers over 822.3 billion revenue-passenger miles. The FAA also forecasts, in that same report, an average annual increase in passenger traffic of 2.2 percent per year for the next 20 years, which approximates to one-and-a-half times the number of today's aircraft operations and passengers by the year 2033. If airspace capacity and throughput remain unchanged, then flight delays will increase, particularly at those airports already operating near or at capacity. Therefore it is critical to create new and improved technologies, communications, and procedures to be used by air traffic controllers and pilots. National Aeronautics and Space Administration (NASA), the FAA, and the aviation industry are working together to improve the efficiency of the National Airspace System and the cost to operate in it in several ways, one of which is through the creation of the Next Generation Air Transportation System (NextGen). NextGen is intended to provide airspace users with more precise information about traffic, routing, and weather, as well as improve the control mechanisms within the air traffic system. NASA's Air Traffic Management Technology Demonstration-1 (ATD-1) Project is designed to contribute to the goals of NextGen, and accomplishes this by integrating three NASA technologies to enable fuel-efficient arrival operations into high-density airports. The three NASA technologies and procedures combined in the ATD-1 concept are advanced arrival scheduling, controller decision support tools, and aircraft avionics to enable multiple time deconflicted and fuel efficient arrival streams in high-density terminal airspace.

Baxley, Brian T.↗

NASA NTRS2018

Simulation Evaluations of an Autonomous Urban Air Mobility Network Management and Separation Service

This paper presents an initial implementation of an autonomous Urban Air Mobility network management and aircraft separation service for urban airspace that does 1) departure and arrival scheduling across the network, 2) continuous trajectory management to ensure safe separation between aircraft, and 3) seamless integration with traditional operations. The highly-autonomous AutoResolver algorithm developed for traditional aviation was extended to provide these capabilities. An evaluation of this initial implementation was conducted in fast-time simulations using a dense, two-hour traffic scenario with Urban Air Mobility aircraft flying between a network of 20 vertiports in the Dallas-Fort Worth metroplex. When the spatial separation was reduced from 0:3nmi to 0:1nmi, the total de- lay decreased by 7:3%; when the temporal separation was reduced from 60s to 45s, the total delay decreased by 28:4%. The total number of conflict resolutions decreased by 26% and 17%, respectively. Furthermore, when a scheduling horizon greater than the duration of UAM flights was used (50min), most conflicts were resolved pre-departure producing ground delay. By comparison, when a shorter scheduling horizon was used (8min), most conflicts were resolved post-departure generating airborne delay. For all scheduling and separation constraints tested, AutoResolver prevented loss of separation from occurring. Urban Air Mobility operations have the ability to revolutionize how people and goods are transported and this paper presents initial research focusing on the high levels of autonomy required for an airspace system capable of scaling to handle significantly higher densities of aircraft.

Bosson, Christabelle S.↗

NASA NTRS2018

Simulation Evaluations of an Autonomous Urban Air Mobility Network Management and Separation Service

This presents an initial implementation of an autonomous Urban Air Mobility network management and aircraft separation service for urban airspace that does 1) departure and arrival scheduling across the network, 2) continuous trajectory management to ensure safe separation between aircraft, and 3) seamless integration with traditional operations. The highly-autonomous AutoResolver algorithm developed for traditional aviation was extended to provide these capabilities. An evaluation of this initial implementation was conducted in fast-time simulations using a dense, two-hour traffic scenario with Urban Air Mobility aircraft flying between a network of 20 vertiports in the Dallas-Fort Worth metroplex. When the spatial separation was reduced from 0:3 nmi (nautical miles) to 0:1nmi, the total delay decreased by 7:3 percent...

Bosson, Christabelle S.↗

NASA NTRS2016

In-Flight Operation of the Dawn Ion Propulsion System Through the Low Altitude Mapping Orbit at Ceres

The Dawn mission, part of NASA’s Discovery Program, has as its goal the scientific exploration of the two most massive main-belt objects, Vesta and Ceres. The Dawn spacecraft was launched from the Cape Canaveral Air Force Station on September 27, 2007 on a Delta-II 7925H- 9.5 (Delta-II Heavy) rocket that placed the 1218-kg spacecraft onto an Earth-escape trajectory. On-board the spacecraft is an ion propulsion system (IPS) developed at the Jet Propulsion Laboratory for the heliocentric transfer to Vesta, orbit capture at Vesta, transfer between Vesta science orbits, departure and escape from Vesta, heliocentric transfer to Ceres, orbit capture at Ceres, transfer between Ceres science orbits, and orbit maintenance maneuvers. Full-power thrusting from December 2007 through October 2008 was used to successfully target a Mars gravity assist flyby in February 2009 that provided an additional ΔV of 2.6 km/s. Deterministic thrusting for the heliocentric transfer to Vesta resumed in June 2009 and concluded with orbit capture at Vesta on July 16, 2011. From July 2011 through September 2012 the IPS was used to transfer to all the different science orbits at Vesta and to escape from Vesta orbit. Cruise for a rendezvous with Ceres began in August 2012 and completed in late December 2014. From December 2014 through June 2016 the IPS was used for transiting the spacecraft to the Approach phase, survey orbit, the high altitude mapping orbit (HAMO), and the low altitude mapping orbit (LAMO) with arrival to LAMO on December 13, 2015, almost eight years after the start of deterministic thrusting to Vesta. The LAMO orbit, at a mean altitude above Ceres of approximately 385 km, is the spacecraft’s final destination and there are no plans to move the spacecraft from LAMO once science operations there are completed. Since arrival at LAMO Dawn’s IPS has been used for occasional orbit maintenance maneuvers while the spacecraft performs scientific investigations. Dawn has successfully completed its science goals and Dawn’s primary mission is scheduled to end June 30, 2016. To date the IPS has been operated for approximately 48,458 hours, consumed approximately 401 kg of xenon, and provided a delta-V of over 11.0 km/s, a record for an on-board propulsion system. The IPS performance characteristics are close to the expected performance based on analysis and testing performed pre-launch. Dawn’s IPS continues to be fully operational as of June 2016. This paper provides an overview of Dawn’s mission objectives and the results of Dawn IPS mission operations from Survey orbit through the completion of Dawn’s primary mission.

Garner, Charles E.↗

NASA NTRSDate not supplied

A Notional Artemis Lunar Surface Exploration Package (ArLSEP) based on the Gandalf Staff Platform

Introduction: The Artemis program is planning to deliver crew and cargo to the lunar surface, but there is no current package for supporting lunar in-struments and experiments similar to the Apollo Lunar Surface Exploration Package (ALSEP). This abstract provides a possible concept for such a package using the Gandalf Staff Platform as a common core. Gandalf Staff: The Gandalf Staff is an early prototype system developed over FY’21/FY’22 using NASA Science Technology Mission Directorate (STMD) Center Information Fund (CIF) grants to de-sign, build and test “proof-of-concept” components. These components include a 24v battery powered monopole that powers a suite of subsystems, including a Graphical User Interface (GUI) for crew, surface voice and data communications, Lunar Search and Rescue (LunaSAR) navigation and communications, LiDAR, field site external lighting, 360-degree camera, and a geothermal instrument for measuring sub-surface temperature gradient. The staff can be carried independently by an Extra-Vehicular Activity (EVA) astronaut, or can be mounted into a tripod for “hands free” support at a surface site being investigated. The staff can be attached to an external solar array and power storage system for long-duration operations. [1,2] ALSEP: An ASLEP flew on each mission Apollo 12 to Apollo 17. For Apollo 11, a simplified packaged called the Early Apollo Scientific Experiments Pack-age (EASEP) was flown. Each package included a “Central Station” that provided the power and communications connected to a variety of instruments and sensors. The power was provided by a Radioisotope Thermoelectric Generator (RTG) fueled by Plutoni-um-238 generating 70 watts of power (initially, decayed over time) [3]. The communications system provide for direct to Earth data transfer from the lunar surface. Each pack-age was stowed externally in the Lunar Module (LM) Scientific Equipment (SEQ) bay with a mass up to 163 kg (Apollo 17). The crew unloaded the ALSEP from the LM and deployed the instruments on the lunar surface. Although designed to operate for only 1 year, many sites operated for up to 8 years successfully [4]. The Active Seismic Experiment (ASE) included 3 geophones for detecting seismic waves created by mortars and thumpers deployed by the crew. Other active experiments measured the lunar atmosphere, the heat flow in the subsurface, the lunar gravity and potential gravity waves, the lunar magnetic field, the solar wind and plasma interactions in cislunar space. Passive experiments included collectors for dust and cosmic rays, and retroreflectors for precise measurements of distance using a laser from Earth. The ALSEP program continues to generate insights into lunar formation and evolution. ArLSEP Concepts: The lunar surface science package for the Artemis program will hopefully exceed the capability of the ALSEP. There are multiple issues for discussion leading to the design of a new ArLSEP, needing requirements definition from the science community, NASA mission architecture, and NASA budget planners. 1. Delivery Mechanism Two possible projects currently provide capability to deliver scientific cargo to the lunar surface: 1) the Commercial Lunar Payload Services (CLPS) [5] and the Human Landing System (HLS) [6, 7]. Each project is controlled by a different organization within NASA and budgeted with different criteria although both support lunar exploration. The HLS system delivers crew (and potentially cargo) to human landing sites. If an ArLSEP is “predeployed” to such a site, the design must include power (either from the vehicle or independently) to keep the electronics functioning until deployed by the crew. If an ArLSEP is delivered on a vehicle after the crew is present on the lunar surface, safety protocols require adequate distance from the humans for impact from descent propelled sur-face regolith ejecta. This distance can not exceed the capability of the crew to walk (if no rover) to the vehicle for ArLSEP deployment. 2. Overall Guidelines The general design of ArLSEP will likely follow the ALSEP with a common system for communications and power; however, significant architecture differences between Apollo and Artemis exist. Power: The RTG will not be available for early Artemis missions nor likely follow-on Lunar Exploration Transportation Services (LETS) missions [8]. Thus, ArLSEP power must be supplied by solar arrays with sufficient battery capability to “keep alive” necessary electronics during any lunar surface eclipse period. Communication: The Artemis program is developing a series of communications satellites for lunar orbit to provide surface transmission of data and voice to Earth. Called “LunaNET”, this network is component useful for ArLSEP since south polar locations may not always have direct “line-of-sight” to Earth [9]. 3. Concept of Operations (ConOps) The general ConOps for ArLSEP is to deliver the package to lunar surface before the crew arrives, and then have the crew deploy the package after some period of time. This requires coordinated design (for power systems) and launch window (for schedule) on both the cargo and crew missions. Once the ArLSEP is deployed, it will operate autonomously for a number of years. It should be designed to be EVA compatible for crew maintenance and upgrade. 4. Notional Design (for discussion purpose only) The landing site near the South Pole is expected to have no eclipse cycle exceeding 5 days, so the “keep alive” power is 144 hours (6 days to include margin). A 12v ArLSEP will use rechargeable LiFePO4 cells, which are common in the Electric Vehicle (EV) industry. With a current of 5 amps and a 125 watt system, the mass is about 90kg. The comm. system and structure adds another 10kg, thus the “Central Station” is approximately 100kg. The solar power is collected on four arrays (each 2m above the surface), and the entire ArLSEP is designed to stow in a 2m x 1m x 1m volume. The experiment and instrument design will vary for each installation and add mass to the total (although they are expected to fit within the 2m3 volume). Seismic wave generation will likely not be provided with mortars, thus an electric “thumper” will be required. Active instruments such as imaging systems and sensing instruments will benefit from the additional power and communication capability provided by ArLSEP. Passive systems such as retroreflectors, witness plates, and cosmic dust collectors can be added to either the landing vehicle and/or the ArLSEP. With repeated HLS missions to the same human site, the ArLSEP can be expanded and easily maintained for long duration science collection on the lunar surface.

ALSEP↗

NASA NTRS2016

In-flight Operation of the Dawn Ion Propulsion System Through the Low Altitude Mapping Orbit at Ceres

The Dawn mission, part of NASA’s Discovery Program, has as its goal the scientific exploration of the two most massive main-belt objects, Vesta and Ceres. The Dawn spacecraft was launched from the Cape Canaveral Air Force Station on September 27, 2007 on a Delta-II 7925H- 9.5 (Delta-II Heavy) rocket that placed the 1218-kg spacecraft onto an Earth-escape trajectory. On-board the spacecraft is an ion propulsion system (IPS) developed at the Jet Propulsion Laboratory for the heliocentric transfer to Vesta, orbit capture at Vesta, transfer between Vesta science orbits, departure and escape from Vesta, heliocentric transfer to Ceres, orbit capture at Ceres, transfer between Ceres science orbits, and orbit maintenance maneuvers. Full-power thrusting from December 2007 through October 2008 was used to successfully target a Mars gravity assist flyby in February 2009 that provided an additional ΔV of 2.6 km/s. Deterministic thrusting for the heliocentric transfer to Vesta resumed in June 2009 and concluded with orbit capture at Vesta on July 16, 2011. From July 2011 through September 2012 the IPS was used to transfer to all the different science orbits at Vesta and to escape from Vesta orbit. Cruise for a rendezvous with Ceres began in August 2012 and completed in late December 2014. From December 2014 through June 2016 the IPS was used for transiting the spacecraft to the Approach phase, survey orbit, the high altitude mapping orbit (HAMO), and the low altitude mapping orbit )LAMO) with arrival to LAMO on December 13, 2015, almost eight years after the start of deterministic thrusting to Vesta. The LAMO orbit, at a mean altitude above Ceres of approximately 385 km, is the spacecraft’s final destination and there are no plans to move the spacecraft from LAMO once science operations there are completed. Since arrival at LAMO Dawn’s IPS has been used for occasional orbit maintenance maneuvers while the spacecraft performs scientific investigations. Dawn has successfully completed its science goals and Dawn’s primary mission is scheduled to end in the summer of 2016. To date the IPS has been operated for over 48,454 hours, consumed approximately 401 kg of xenon, and provided a delta-V of over 11.0 km/s, a record for an on-board propulsion system. The IPS performance characteristics are close to the expected performance based on analysis and testing performed pre-launch. Dawn’s IPS continues to be fully operational as of June 2016. This paper provides an overview of Dawn’s mission objectives and the results of Dawn IPS mission operations from Survey orbit through June 2016.

Garner, Charles E.↗

NASA NTRSDate not supplied

Impact of General Aviation Operations on Airport Performance Through Fast-Time Simulations at Charlotte Douglas International Airport

NASA, in partnership with the Federal Aviation Administration and commercial airlines, deployed the Integrated Arrival, Departure, and Surface (IADS) traffic management system at Charlotte Douglas International Airport (CLT) in 2017 for field evaluation. The system features new capabilities of data exchange and integration, collaborative surface metering and scheduling, which has demonstrated operational benefits of reducing delay time and fuel consumption. General Aviation flights, however, are not currently included in the surface metering programs because of their different operational procedures and lack of reliable predictability in departure time. Thus, their impact on the system performance is not well understood. This paper presents a study of the impact of General Aviation traffic at CLT using fast-time simulations.

General Aviation↗

NASA NTRS2005

An Initial Study of Airport Arrival Heinz Capacity Benefits Due to Improved Scheduling Accuracy

The long-term growth rate in air-traffic demand leads to future air-traffic densities that are unmanageable by today's air-traffic control system. I n order to accommodate such growth, new technology and operational methods will be needed in the next generation air-traffic control system. One proposal for such a system is the Automated Airspace Concept (AAC). One of the precepts of AAC is to direct aircraft using trajectories that are sent via an air-ground data link. This greatly improves the accuracy in directing aircraft to specific waypoints at specific times. Studies of the Center-TRACON Automation System (CTAS) have shown that increased scheduling accuracy enables increased arrival capacity at CTAS equipped airports.

Meyn, Larry↗

NASA NTRS2019

ATD-3 Dynamic Routes for Arrivals in Weather (DRAW) Operational Concept, V2.0

NASA's Airspace Technology Demonstration-3 (ATD-3) is the applied traffic flow management activity, and third in the series of ATD projects. ATD-3 provides a suite of en route automation tools, both ground and flight-deck based, that focus on improving the efficiency of en route operation from initial cruise to arrival into the Terminal Radar Approach Control (TRACON). Dynamic Routes for Arrivals in Weather (DRAW) is a technology in the ATD-3 suite that is designed to provide Traffic Managers with a capability to efficiently manage arrival traffic flow and help sustain metering operations when weather is impacting arrivals into major airports. DRAW mitigates convective weather impact on arrival metering operations by providing tools to Traffic Managers that enable efficient reroutes free of convective weather conflicts, and integrated with the arrival metering schedule(s).

terminal airspace↗

NASA NTRS2016

Wind Information Uplink to Aircraft Performing Interval Management Operations

Interval Management (IM) is an ADS-B-enabled suite of applications that use ground and flight deck capabilities and procedures designed to support the relative spacing of aircraft (Barmore et al., 2004, Murdoch et al. 2009, Barmore 2009, Swieringa et al. 2011; Weitz et al. 2012). Relative spacing refers to managing the position of one aircraft to a time or distance relative to another aircraft, as opposed to a static reference point such as a point over the ground or clock time. This results in improved inter-aircraft spacing precision and is expected to allow aircraft to be spaced closer to the applicable separation standard than current operations. Consequently, if the reduced spacing is used in scheduling, IM can reduce the time interval between the first and last aircraft in an overall arrival flow, resulting in increased throughput. Because IM relies on speed changes to achieve precise spacing, it can reduce costly, low-altitude, vectoring, which increases both efficiency and throughput in capacity-constrained airspace without negatively impacting controller workload and task complexity. This is expected to increase overall system efficiency. The Flight Deck Interval Management (FIM) equipment provides speeds to the flight crew that will deliver them to the achieve-by point at the controller-specified time, i.e., assigned spacing goal, after the target aircraft crosses the achieve-by point (Figure 1.1). Since the IM and target aircraft may not be on the same arrival procedure, the FIM equipment predicts the estimated times of arrival (ETA) for both the IM and target aircraft to the achieve-by point. This involves generating an approximate four-dimensional trajectory for each aircraft. The accuracy of the wind data used to generate those trajectories is critical to the success of the IM operation. There are two main forms of uncertainty in the wind information used by the FIM equipment. The first is the accuracy of the forecast modeling done by the weather provider. This is generally a global environmental prediction obtained from a weather model such as the Rapid Refresh (RAP) from the National Centers for Environmental Prediction (NCEP). The weather forecast data will have errors relative to the actual, or truth, winds that the aircraft will encounter. The second source of uncertainty is that only a small subset of the forecast data can be uplinked to the aircraft for use by the FIM equipment. This results in loss of additional information. The Federal Aviation Administration (FAA) and RTCA are currently developing standards for the communication of wind and atmospheric data to the aircraft for use in NextGen operations. This study examines the impact of various wind forecast sampling methods on IM performance metrics to inform the standards development.

Ahmad, Nashat N.↗

NASA NTRS2012

Optimal Integration of Departure and Arrivals in Terminal Airspace

Coordination of operations with spatially and temporally shared resources such as route segments, fixes, and runways improves the efficiency of terminal airspace management. Problems in this category include scheduling and routing, thus they are normally difficult to solve compared with pure scheduling problems. In order to reduce the computational time, a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSGA) was introduced in this work and applied to a test case based on existing literature. The experiment showed that new method can solve the whole problem in fast time instead of solving sub-problems sequentially with a window technique. The results showed a 60% or 406 second delay reduction was achieved by sharing departure fixes (more details on the comparison with MILP results will be presented in the final paper). Furthermore, the NSGA algorithm was applied to a problem in LAX terminal airspace, where interactions between 28% of LAX arrivals and 10% of LAX departures are resolved by spatial segregation, which may introduce unnecessary delays. In this work, spatial segregation, temporal segregation, and hybrid segregation were formulated using the new algorithm. Results showed that spatial and temporal segregation approaches achieved similar delay. Hybrid segregation introduced much less delay than the other two approaches. For a total of 9 interacting departures and arrivals, delay reduction varied from 4 minutes to 6.4 minutes corresponding flight time uncertainty from 0 to 60 seconds. Considering the amount of flights that could be affected, total annual savings with hybrid segregation would be significant.

high density terminal↗

NASA NTRS1996

An Aircraft Vortex Spacing System (AVOSS) for Dynamical Wake Vortex Spacing Criteria

A concept is presented for the development and implementation of a prototype Aircraft Vortex Spacing System (AVOSS). The purpose of the AVOSS is to use current and short-term predictions of the atmospheric state in approach and departure corridors to provide, to ATC facilities, dynamical weather dependent separation criteria with adequate stability and lead time for use in establishing arrival scheduling. The AVOSS will accomplish this task through a combination of wake vortex transport and decay predictions, weather state knowledge, defined aircraft operational procedures and corridors, and wake vortex safety sensors. Work is currently underway to address the critical disciplines and knowledge needs so as to implement and demonstrate a prototype AVOSS in the 1999/2000 time frame.

Hinton, D. A.↗

NASA NTRS2004

Future Air Traffic Growth and Schedule Model User's Guide

The Future Air Traffic Growth and Schedule Model was developed as an implementation of the Fratar algorithm to project future traffic flow between airports in a system and of then scheduling the additional flights to reflect current passenger time-of-travel preferences. The methodology produces an unconstrained future schedule from a current (or baseline) schedule and the airport operations growth rates. As an example of the use of the model, future schedules are projected for 2010 and 2022 for all flights arriving at, departing from, or flying between all continental United States airports that had commercial scheduled service for May 17, 2002. Inter-continental US traffic and airports are included and the traffic is also grown with the Fratar methodology to account for their arrivals and departures to the continental US airports. Input data sets derived from the Official Airline Guide (OAG) data and FAA Terminal Area Forecast (TAF) are included in the examples of the computer code execution.

Kimmel, William M.↗

NASA NTRS2004

Future Air Traffic Growth and Schedule Model, Supplement

Kimmel, William M.↗

NASA NTRS2019

Airspace Technology Demonstration 2 (ATD-2): Integrated Arrival/ Departure/Surface (IADS) System Demonstration Technology Transfer Document Summary (ReadMe) Version 2 - Phase 2 Fused IADS

Airspace Technology Demonstration 2 (ATD-2) is part of NASA's Airspace Technology Demonstrations (ATD) Project under its Airspace Operations and Safety Program (AOSP). ATD-2 is a multi-year research and development effort to improve the predictability and operational efficiency of the air traffic system in metroplex environments while maintaining or improving throughput by enhancing and integrating arrival, departure, and surface prediction, scheduling, and management systems. In order to ensure that the products of this knowledge and technology transfer are relevant and useful, NASA has created strong partnerships with the FAA and industry stakeholders. This summary document and accompanying artifacts satisfy the second of three research transition products (RTPs) defined in the IADS research transition team (RTT) plan. This transfer consists of NASA's ATD-2 Phase 1 Baseline IADS and Phase 2 Fused IADS system capabilities

Capps, Alan↗

NASA NTRS2020

Airspace Technology Demonstration 2 (ATD-2): Integrated Arrival/Departure/Surface (IADS) System Demonstration - Technology Transfer Document Summary (ReadMe) (Version 2.5 - Initial Phase 3 Metroplex IADS)

Airspace Technology Demonstration – 2 (ATD-2) is part of NASA’s Airspace Technology Demonstrations (ATD) Project under its Airspace Operations and Safety Program (AOSP). ATD-2 is a multi-year research and development effort to improve the predictability and operational efficiency of the air traffic system in metroplex environments while maintaining or improving throughput by enhancing and integrating arrival, departure, and surface prediction, scheduling, and management systems. In order to ensure that the products of this knowledge and technology transfer are relevant and useful, NASA has created strong partnerships with the FAA and industry stakeholders. This summary document and accompanying artifacts satisfy the next delivery of research transition products (RTPs) defined in the IADS research transition team (RTT) plan. With the ATD-2 project extended for another year, this Tech Transfer 2.5 constitutes an interim delivery of artifacts from the Phase 3 field demonstration. The final Phase 3 tech transfer delivery is planned for August 2021.

ATD-2, IADS, Phase 3, tech transfer↗

NASA NTRS2021

Airspace Technology Demonstration 2 (ATD-2): Integrated Arrival/ Departure/Surface (IADS) System Demonstration - Technology Transfer Document Summary (ReadMe)Version 3 (Final Phase 3 Metroplex IADS)

Airspace Technology Demonstration – 2 (ATD-2) is part of NASA’s Airspace Technology Demonstrations (ATD) Project under its Airspace Operations and Safety Program (AOSP). ATD-2 is a multi-year research and development effort to improve the predictability and operational efficiency of the air traffic system in metroplex environments while maintaining or improving throughput by enhancing and integrating arrival, departure, and surface prediction, scheduling, and management systems. In order to ensure that the products of this knowledge and technology transfer are relevant and useful, NASA has created strong partnerships with the FAA and industry stakeholders. This summary document and accompanying artifacts satisfy the final delivery of research transition products (RTPs) defined in the IADS research transition team (RTT) plan.

ATD-2↗

NASA NTRS2014

An Evaluation of a Flight Deck Interval Management Algorithm Including Delayed Target Trajectories

NASA's first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature air traffic management technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise timebased scheduling in the terminal airspace; Controller Managed Spacing (CMS), which provides controllers with decision support tools enabling precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain precise in-trail spacing. During high demand operations, TMA-TM may produce a schedule and corresponding aircraft trajectories that include delay to ensure that a particular aircraft will be properly spaced from other aircraft at each schedule waypoint. These delayed trajectories are not communicated to the automation onboard the aircraft, forcing the IM aircraft to use the published speeds to estimate the target aircraft's estimated time of arrival. As a result, the aircraft performing IM operations may follow an aircraft whose TMA-TM generated trajectories have substantial speed deviations from the speeds expected by the spacing algorithm. Previous spacing algorithms were not designed to handle this magnitude of uncertainty. A simulation was conducted to examine a modified spacing algorithm with the ability to follow aircraft flying delayed trajectories. The simulation investigated the use of the new spacing algorithm with various delayed speed profiles and wind conditions, as well as several other variables designed to simulate real-life variability. The results and conclusions of this study indicate that the new spacing algorithm generally exhibits good performance; however, some types of target aircraft speed profiles can cause the spacing algorithm to command less than optimal speed control behavior.

Swieringa, Kurt A.↗