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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2017

Future ATM Concepts Evaluation Tool (FACET) Interface Control Document

This Interface Control Document (ICD) documents the airspace adaptation and air traffic inputs of NASA's Future ATM Concepts and Evaluation Tool (FACET). Its intended audience is the project manager, project team, development team, and stakeholders interested in interfacing with the system. FACET equips Air Traffic Management (ATM) researchers and service providers with a way to explore, develop and evaluate advanced air transportation concepts before they are field-tested and eventually deployed. FACET is a flexible software tool that is capable of quickly generating and analyzing thousands of aircraft trajectories. It provides researchers with a simulation environment for preliminary testing of advanced ATM concepts. Using aircraft performance profiles, airspace models, weather data, and flight schedules, the tool models trajectories for the climb, cruise, and descent phases of flight for each type of aircraft. An advanced graphical interface displays traffic patterns in two and three dimensions, under various current and projected conditions for specific airspace regions or over the entire continental United States. The system is able to simulate a full day's dynamic national airspace system (NAS) operations, model system uncertainty, measure the impact of different decision-makers in the NAS, and provide analysis of the results in graphical form, including sector, airport, fix, and airway usage statistics. NASA researchers test and analyze the system-wide impact of new traffic flow management algorithms under anticipated air traffic growth projections on the nation's air traffic system. In addition to modeling the airspace system for NASA research, FACET has also successfully transitioned into a valuable tool for operational use. Federal Aviation Administration (FAA) traffic flow managers and commercial airline dispatchers have used FACET technology for real-time operations planning. FACET integrates live air traffic data from FAA radar systems and weather data from the National Weather Service to summarize NAS performance. This information allows system operators to reroute flights around congested airspace and severe weather to maintain safety and minimize delay. FACET also supports the planning and post-operational evaluation of reroute strategies at the national level to maximize system efficiency. For the commercial airline passenger, strategic planning with FACET can result in fewer flight delays and cancellations. The performance capabilities of FACET are largely due to its architecture, which strikes a balance between flexibility and fidelity. FACET is capable of modeling the airspace operations for the continental United States, processing thousands of aircraft on a single computer. FACET was written in Java and C, enabling the portability of its software to a variety of operating systems. In addition, FACET was designed with a modular software architecture to facilitate rapid prototyping of diverse ATM concepts. Several advanced ATM concepts have already been implemented in FACET, including aircraft self-separation, prediction of aircraft demand and sector congestion, system-wide impact assessment of traffic flow management constraints, and wind-optimal routing.

FACET↗
NASA NTRS1990

Automatic detection of low altitude wind shear due to gust fronts in the terminal Doppler weather radar operational demonstration

A gust front is the leading edge of the cold air outflow from a thunderstorm. Wind shears and turbulence along the gust front may produce potentially hazardous conditions for an aircraft on takeoff or landing such that runway operations are significantly impacted. The Federal Aviation Administration (FAA) has therefore determined that the detection of gust fronts in the terminal environment be an integral part of the Terminal Doppler Weather Radar (TDWR) system. Detection of these shears by the Gust Front Algorithm permits the generation of warnings that can be issued to pilots on approach and departure. In addition to the detection capability, the algorithm provides an estimate of the wind speed and direction following the gust front (termed wind shift) and the forecasted location of the gust front up to 20 minutes before it impacts terminal operations. This has shown utility as a runway management tool, alerting runway supervisors to approaching wind shifts and the possible need to change runway configurations. The formation and characteristics of gust fronts and their signatures in Doppler radar data are discussed. A brief description of the algorithm and its products for use by Air Traffic Control (ATC), along with an assessment of the algorithm's performance during the 1988 Operational Test and Evaluation, is presented.

Klingle-Wilson, Diana↗
NASA NTRS1999

The Component Packaging Problem: A Vehicle for the Development of Multidisciplinary Design and Analysis Methodologies

This report summarizes academic research which has resulted in an increased appreciation for multidisciplinary efforts among our students, colleagues and administrators. It has also generated a number of research ideas that emerged from the interaction between disciplines. Overall, 17 undergraduate students and 16 graduate students benefited directly from the NASA grant: an additional 11 graduate students were impacted and participated without financial support from NASA. The work resulted in 16 theses (with 7 to be completed in the near future), 67 papers or reports mostly published in 8 journals and/or presented at various conferences (a total of 83 papers, presentations and reports published based on NASA inspired or supported work). In addition, the faculty and students presented related work at many meetings, and continuing work has been proposed to NSF, the Army, Industry and other state and federal institutions to continue efforts in the direction of multidisciplinary and recently multi-objective design and analysis. The specific problem addressed is component packing which was solved as a multi-objective problem using iterative genetic algorithms and decomposition. Further testing and refinement of the methodology developed is presently under investigation. Teaming issues research and classes resulted in the publication of a web site, (http://design.eng.clemson.edu/psych4991) which provides pointers and techniques to interested parties. Specific advantages of using iterative genetic algorithms, hurdles faced and resolved, and institutional difficulties associated with multi-discipline teaming are described in some detail.

Fadel, Georges↗
NASA NTRSDate not supplied

Terminal Area Size and Switching Technique Analysis for Unmanned Aircraft Systems Operations

Unmanned Aircraft Systems (UAS) need to be able to comply with the Code of Federal Regulations Part 91 ‘see and avoid’ requirement. Detect and avoid (DAA) is an essential enabler for integrating UAS into the National Airspace System. A DAA system is a suite of sensors, trackers, and alerting and guidance algorithms that assists a remote pilot in maintaining separation from airborne traffic. Previous works have focused on operations transiting to and from Class A or special use airspace. More recent efforts have defined DAA system requirements for operations in and around the airport terminal environment. In continuation of this effort, this paper defines the DAA Terminal Area (DTA) size and switching technique for the DAA Well Clear (DWC) volume while transitioning between en route and the terminal area.

Unmanned Aircraft Systems↗
NASA NTRS2010

Signal Processing Methods Monitor Cranial Pressure

Dr. Norden Huang, of Goddard Space Flight Center, invented a set of algorithms (called the Hilbert-Huang Transform, or HHT) for analyzing nonlinear and nonstationary signals that developed into a user-friendly signal processing technology for analyzing time-varying processes. At an auction managed by Ocean Tomo Federal Services LLC, licenses of 10 U.S. patents and 1 domestic patent application related to HHT were sold to DynaDx Corporation, of Mountain View, California. DynaDx is now using the licensed NASA technology for medical diagnosis and prediction of brain blood flow-related problems, such as stroke, dementia, and traumatic brain injury.

Source record↗
NASA NTRS2001

Towards the Development of a Global Precipitation Measurement (GPM) Mission Concept

The scientific success of the Tropical Rainfall Measuring Mission (TRMM) and additional satellite-focused precipitation retrieval projects have paved the way for a more advanced global precipitation mission. A comprehensive global measuring strategy is currently under study - Global Precipitation Measurement (GPM). The GPM study could ultimately lead to the development of the Global Precipitation Mission. The intent of GPM is to address looming scientific questions arising in the context of global climate-water cycle interactions, hydrometeorology, weather prediction and prediction of freshwater resources, the global carbon cycle, and biogeochemical cycles. This talk overviews the status and scientific agenda of this proposed mission currently planned for launch in the 2007-2008 time frame. GPM is planning to expand the scope of precipitation measurement through the use of a constellation of 6-10 satellites, one of which will be an advanced TRMM-like "core" satellite carry dual-frequency Ku-Ka band radar and a microwave radiometer (e.g. TMI-like). The other constellation members will likely include new lightweight satellites and co-existing operational/research satellites carrying passive microwave radiometers. The goal behind the constellation is to achieve no worse than 3-hour sampling at any spot on the globe. The constellation's orbit architecture will consist of a mix of sun-synchronous and non-su n -synchronous satellites with the "core" satellite providing measurement of cloud-precipitation microphysical processes plus "training calibrating" information to be used with the retrieval algorithms for the constellation satellite measurements. The GPM is organized internationally, currently involving a partnership between NASA in the US, NASDA in Japan, and ESA in Europe (representing the European community). The program is expected to involve additional international partners, other federal agencies, and a diverse collection of scientists from academia, government, and the private sector.

Shepherd, Marshall↗
NASA NTRS2014

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗
NASA NTRSDate not supplied

Demand Capacity Balancing at Vertiports for Initial Strategic Conflict Management of Urban Air Mobility Operations

Urban Air Mobility (UAM) is a new transportation concept that enables highly automated, cooperative, passenger or cargo-carrying air transportation services in and around urban areas. To achieve the high level of operational density and complexity desired by the UAM community, an airspace system that allows UAM operators to readily access and operate safely and efficiently in the airspace is needed. This airspace system will require air traffic management designed to reduce the risk of conflicts and loss of separation between UAM flights. In general, strategic conflict management is considered as the first layer of conflict management for safe flight operations to condition the traffic to reduce the need for airborne separation provision, the second layer of conflict management. Demand Capacity Balancing (DCB) is one of the concept components to achieve strategic conflict management. DCB strategically evaluates traffic demand and resource capacities to allow UAM operators to determine when, where and how they operate, while mitigating conflicting needs for airspace and vertiport capacity. DCB can be applied whenever UAM demand exceeds the capacity in airspace or at vertiports. As the UAM ecosystem evolves with advanced technologies and matured operational procedures, more complicated conflict management will likely be needed. In the current UAM ‘Concept of Operation (ConOps) 1.0’ operational stage defined by FAA, however, it will be meaningful to explore the demand capacity balancing at vertiports only, as an initial strategic conflict management approach for UAM operations because vertiport capacity seems to be a bottleneck of UAM traffic. For this research, we developed a demand-capacity imbalance detection and resolution service for UAM. This DCB service identifies the demand from operators and compares the demand to a given capacity at the shared resources (i.e., vertiports) over the upcoming time horizon which is divided into time bins having a constant interval. When a new flight plan is submitted, the algorithm embedded in the DCB service checks the available time bins based on the desired departure time and estimated arrival time at origin and destination vertiports, respectively. If the time bins for the originally desired times are already occupied by other flights (i.e., demand is at or above capacity), the algorithm finds the next available time bins for takeoff and landing and shifts the conflicting departure time to the earliest time that satisfies the capacity constraints at both origin and destination vertiports. The details of the algorithm will be described in the final manuscript. Figure 1 shows that the proposed DCB algorithm works well for a sample traffic scenario. In this example, a total of 144 flights, split between two operators, are planned over 2 hours, traveling 10 routes between five vertiports. In the heatmaps, the horizontal axis shows 12 time bins where each bin represents a 12-minute interval, and the vertical axis shows five vertiports. The number in each cell shows the number of operations, counting both departures and arrivals, at a specific vertiport in each time bin. For the given capacity of 2 operations/vertiport/bin, Figure 1 shows that the original demand sometimes exceeds the capacity, but the modified demand is reduced to the given capacity after resolving demand-capacity imbalances. When UAM flights are operated, it is expected that many practical issues would arise in the federated system architecture with multiple operators. UAM operators may experience a time synchronization issue due to communication delay between operator and vehicle. UAM vehicles would fly at different flight speeds, depending on vehicle models. Actual departure and arrival times can have large variations, compared to the schedule. The lead time from flight plan submission to desired departure time can vary by service type (e.g., regular shuttle service vs. on-demand service). Using the proposed DCB algorithm, we also investigated how the actual flight schedule and DCB performance are affected by these uncertainties such as unsynchronized times between operators, flight speed differences, lead time differences, and departure time errors. The final manuscript will include the background of this research work, the description of the DCB algorithm and its use cases with traffic scenarios. It will also provide the analytical results about the impact of various uncertainties that can occur in actual UAM operations on the DCB at vertiports, in terms of demand distribution changes, number of simultaneous operations, and delay propagation.

Urban Air Mobility↗
NASA NTRS2017

Unmanned Aircraft Systems Minimum Operations Performance Standards End-to-End Verification and Validation (E2-V2) Simulation

As Unmanned Aircraft Systems (UAS) make their way to mainstream aviation operations within the National Airspace System (NAS), research efforts are underway to develop a safe and effective environment for their integration into the NAS. Detect and Avoid (DAA) systems are required to account for the lack of "eyes in the sky" due to having no human on-board the aircraft. The current NAS relies on pilot's vigilance and judgement to remain Well Clear (CFR 14 91.113) of other aircraft. RTCA SC-228 has defined DAA Well Clear (DAAWC) to provide a quantified Well Clear volume to allow systems to be designed and measured against. Extended research efforts have been conducted to understand and quantify system requirements needed to support a UAS pilot's ability to remain well clear of other aircraft. The efforts have included developing and testing sensor, algorithm, alerting, and display requirements. More recently, sensor uncertainty and uncertainty mitigation strategies have been evaluated. This paper discusses results and lessons learned from an End-to-End Verification and Validation (E2-V2) simulation study of a DAA system representative of RTCA SC-228's proposed Phase I DAA Minimum Operational Performance Standards (MOPS). NASA Langley Research Center (LaRC) was called upon to develop a system that evaluates a specific set of encounters, in a variety of geometries, with end-to-end DAA functionality including the use of sensor and tracker models, a sensor uncertainty mitigation model, DAA algorithmic guidance in both vertical and horizontal maneuvering, and a pilot model which maneuvers the ownship aircraft to remain well clear from intruder aircraft, having received collective input from the previous modules of the system. LaRC developed a functioning batch simulation and added a sensor/tracker model from the Federal Aviation Administration (FAA) William J. Hughes Technical Center, an in-house developed sensor uncertainty mitigation strategy, and implemented a pilot model similar to one from the Massachusetts Institute of Technology's Lincoln Laboratory (MIT/LL). The resulting simulation provides the following key parameters, among others, to evaluate the effectiveness of the MOPS DAA system: severity of loss of well clear (SLoWC), alert scoring, and number of increasing alerts (alert jitter). The technique, results, and lessons learned from a detailed examination of DAA system performance over specific test vectors and encounter cases during the simulation experiment will be presented in this paper.

Ghatas, Rania W.↗
NASA NTRS1999

Survey of Fire Detection Technologies and System Evaluation/Certification Methodologies and Their Suitability for Aircraft Cargo Compartments

As part of the National Aeronautics and Space Administration (NASA) initiated program on global civil aviation, NIST is assisting Federal Aviation Administration in its research to improve fire detection in aircraft cargo compartments. Aircraft cargo compartment detection certification methods have been reviewed. The Fire Emulator-Detector Evaluator (FE/DE) has been designed to evaluate fire detection technologies such as new sensors, multi-element detectors, and detectors that employ complex algorithms. The FE/DE is a flow tunnel that can reproduce velocity, temperature, smoke, and Combustion gas levels to which a detector might be exposed during a fire. A scientific literature survey and patent search have been conducted relating to existing and emerging fire detection technologies, and the potential use of new fire detection strategies in cargo compartment areas has been assessed. In the near term, improved detector signal processing and multi-sensor detectors based on combinations of smoke measurements, combustion gases and temperature are envisioned as significantly impacting detector system performance.

Cleary, T.↗
NASA NTRS2001

Measured Engine Installation Effects of Four Civil Transport Airplanes

The Federal Aviation Administration's Integrated Noise Model (INM) is one of the primary tools for land use planning around airports. The INM currently calculates airplane noise lateral attenuation using the methods contained in the Society of Automotive Engineer's Aerospace Information Report No. 1751 (SAE AIR 1751). Researchers have noted that improved lateral attenuation algorithms may improve airplane noise prediction. The authors of SAE AIR 1751 based existing methods on empirical data collected from flight tests using 1960s-technology airplanes with tail-mounted engines. To determine whether the SAE AIR 1751 methods are applicable for predicting the engine installation component of lateral attenuation for airplanes with wing-mounted engines, the National Aeronautics and Space Administration (NASA) sponsored a series of flight tests during September 2000 at their Wallops Flight Facility. Four airplanes, a Boeing 767-400, a Douglas DC-9, a Dassault Falcon 2000, and a Beech KingAir, were flown through a 20 microphone array. The airplanes were flown through the array at various power settings, flap settings, and altitudes to simulate take-off and arrival configurations. This paper presents the preliminary findings of this study.

Senzig, David A.↗
NASA NTRS2015

Analysis of Aviation Safety Reporting System Incident Data Associated with the Technical Challenges of the System-Wide Safety and Assurance Technologies Project

The Aviation Safety Program (AvSP) System-Wide Safety and Assurance Technologies (SSAT) Project asked the AvSP Systems and Portfolio Analysis Team to identify SSAT-related trends. SSAT had four technical challenges: advance safety assurance to enable deployment of NextGen systems; automated discovery of precursors to aviation safety incidents; increasing safety of human-automation interaction by incorporating human performance, and prognostic algorithm design for safety assurance. This report reviews incident data from the NASA Aviation Safety Reporting System (ASRS) for system-component-failure- or-malfunction- (SCFM-) related and human-factor-related incidents for commercial or cargo air carriers (Part 121), commuter airlines (Part 135), and general aviation (Part 91). The data was analyzed by Federal Aviation Regulations (FAR) part, phase of flight, SCFM category, human factor category, and a variety of anomalies and results. There were 38 894 SCFM-related incidents and 83 478 human-factorrelated incidents analyzed between January 1993 and April 2011.

Withrow, Colleen A.↗
NASA NTRS2018

Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems

Autonomy of aerospace systems requires the ability for flight control systems to be able to adapt to complex uncertain dynamic environment. In spite of the five decades of research in adaptive control, the fact still remains that currently no adaptive control system has ever been deployed on any safety-critical or human-rated production systems such as passenger transport aircraft. The problem lies in the difficulty with the certification of adaptive control systems since existing certification methods cannot readily be used for nonlinear adaptive control systems. Research to address the notion of metrics for adaptive control began to appear in the recent years. These metrics, if accepted, could pave a path towards certification that would potentially lead to the adoption of adaptive control as a future control technology for safety-critical and human-rated production systems. Development of certifiable adaptive control systems represents a major challenge to overcome. Adaptive control systems with learning algorithms will never become part of the future unless it can be proven that they are highly safe and reliable. Rigorous methods for adaptive control software verification and validation must therefore be developed to ensure that adaptive control system software failures will not occur, to verify that the adaptive control system functions as required, to eliminate unintended functionality, and to demonstrate that certification requirements imposed by regulatory bodies such as the Federal Aviation Administration (FAA) can be satisfied. This presentation will discuss some of the technical issues with adaptive flight control and related V&V challenges.

Nguyen, Nhan T.↗
NASA NTRS1994

Neural networks: Application to medical imaging

The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.

Clarke, Laurence P.↗
NASA NTRS2013

An Evaluation of Operational Airspace Sectorization Integrated System (OASIS) Advisory Tool

In January 2013, a human-in-the-loop evaluation of the Operational Airspace Sectorization Integrated System (OASIS) was conducted in the Airspace Operations Laboratory of the Human Systems Integration Division (Code TH) in conjunction with the Aviation Systems Division (Code AF). The development of OASIS is a major activity of the Dynamic Airspace Configuration (DAC) research focus area within the Aeronautics Research Mission Directorate (ARMD) Airspace Systems Program. OASIS is an advisory tool to assist Federal Aviation Administration (FAA) En Route Area Supervisors in their planning of sector combinedecombine operations as well as opening closing of Data-side (D-side) control positions. These advisory solutions are tailored to the predicted traffic demand over the next few hours. During the experiment, eight retired FAA personnel served as participants for a part-task evaluation of OASIS functionality, covering the user interface as well as the underlying algorithm. Participants gave positive feedback on both the user interface and the algorithm solutions for airspace configuration, including an excellent average rating of 94 on the tool usability scales. They also suggested various enhancements to the OASIS tool, which will be incorporated into the next tool development cycle for the full-scale human-in-the-loop evaluation to be conducted later this year.

decision support tools↗
NASA NTRS1997

Propulsion Flight Research at NASA Dryden From 1967 to 1997

From 1967 to 1997, pioneering propulsion flight research activities have been conceived and conducted at the NASA Dryden Flight Research Center. Many of these programs have been flown jointly with the United States Department of Defense, industry, or the Federal Aviation Administration. Propulsion research has been conducted on the XB-70, F-111 A, F-111E, YF-12, JetStar, B-720, MD-11, F-15, F- 104, Highly Maneuverable Aircraft Technology, F-14, F/A-18, SR-71, and the hypersonic X-15 airplanes. Research studies have included inlet dynamics and control, in-flight thrust computation, integrated propulsion controls, inlet and boattail drag, wind tunnel-to-flight comparisons, digital engine controls, advanced engine control optimization algorithms, acoustics, antimisting kerosene, in-flight lift and drag, throttle response criteria, and thrust-vectoring vanes. A computer-controlled thrust system has been developed to land the F-15 and MD-11 airplanes without using any of the normal flight controls. An F-15 airplane has flown tests of axisymmetric thrust-vectoring nozzles. A linear aerospike rocket experiment has been developed and tested on the SR-71 airplane. This paper discusses some of the more unique flight programs, the results, lessons learned, and their impact on current technology.

Burcham, Frank W., Jr.↗
NASA NTRS2023

Oregon Coast Range Ecological Conservation: Mapping Recent Logging Within Drinking Watersheds of Oregon’s Coastal Range to Support Future Resource Management Policies

Logging operations are widespread across the Oregon Coast Range and conventional logging practices pose a risk of contamination to surface water quality. The NASA DEVELOP Oregon Coast Ecological Conservation team partnered with nonprofit Oregon Wild to quantify the extent of clearcutting and commercial thinning in 80 Coast Range drinking watersheds between 2000 and 2022. This project used all available Landsat data from 1997 through June 2023 in Google Earth Engine. Sensors used include Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, and Landsat 9 Operational Land Imager-2. The Continuous Change Detection and Classification (CCDC) algorithm was used with Landsat observations to identify clearcutting patches. Percent change in summer median Landsat Normalized Difference Vegetation Index (NDVI) images were used to identify areas of forest disturbance including commercial thinning. The team concluded that logging, including both clearcutting and commercial thinning, impacted 31% of forested area in drinking watersheds and the intensity of logging remained consistent from year to year. Clearcutting occurred primarily on private land while commercial thinning occurred primarily on state and federal lands. This study showed that CCDC effectively identifies clearcutting, and percent change in NDVI successfully identifies disturbances including commercial thinning. Key constraints included the lack of field validation data and the inability to attribute disturbances to logging with certainty. Ultimately, this study identified the drinking watersheds and communities most likely to be impacted by logging activity. These results can inform legislation aimed at balancing the commercial and environmental benefits of forestlands.

Logging↗
NASA NTRS2018

Tactical Surface Metering Procedures and Information Needs for Charlotte Douglas International Airport

NASA has been working with the FAA and aviation industry partners to develop and demonstrate new concepts and technologies that integrate arrival, departure, and surface traffic management capabilities. In the fall of 2017, NASA began deployment of their technologies in a phased manner to assist with the integrated surface and airspace operations at Charlotte Douglas International Airport (Charlotte, NC). Initial technologies included a tactical surface metering tool and data exchange elements between the airline-controlled ramp and Federal Aviation Administration controlled ATC Tower. In this paper, we focus on the procedures associated with the tactical surface metering tool used in the ramp control tower. This tool was first calibrated in Human-In-the-Loop simulations and was further developed when it was used in the operational world. This paper describes the collaborative procedures that the users exercised in their respective operational worlds to enable surface metering and how several metrics were used to improve the metering algorithm.

Human Factors↗