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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

The Development of the Multi-Center Traffic Management Advisor (MCTMA): Traffic Flow Management Research in a Multi-Facility Environment

The Traffic Management Advisor (TMA) is a decision-support tool for traffic managers and air traffic controllers that provides traffic flow visualization and other flow management tools. TMA creates an efficiently sequenced and safely spaced schedule for arrival traffic that meets but does not exceed specified airspace system constraints. TMA is being deployed at selected facilities throughout the National Airspace System in the US as part of the FAA's Free Flight Phase 1 program. TMA development and testing, and its current deployment, focuses on managing the arrival capacity for single major airports within single terminal areas and single en route centers. The next phase of development for this technology is the expansion of the TMA capability to complex facilities in which a terminal area or airport is fed by multiple en route centers, thus creating a multicenter TMA functionality. The focus of the multi-center TMA (McTMA) development is on the busy facilities in the Northeast comdor of the US. This paper describes the planning and development of McTMA and the challenges associated with adapting a successful traffic flow management tool for a very complex airspace.

Lee, Katharine K.↗
NASA NTRS2003

En Route Descent Advisor Multi-Sector Planning Using Active and Provisional Controller Plans

As decision support tools are developed to support controllers in complex air traffic control environments, new approaches to maintaining situation awareness and managing traffic planning must be developed to handle the ever-increasing amounts of alerting and advisory data. Within high-density metering and other environments where flight path changes are the rule, not the exception, and where interactions between these changes are required, current trial planning approaches are limited by potential increases in workload. The Enroute Descent Advisor (EDA) is a set of decision support tool capabilities for managing high-density en route traffic subject to metering restrictions. The EDA system s novel approach builds aircraft plans from combinations of user intent data and builds controller plans from combinations of aircraft plans to effectively maintain situation awareness during traffic planning. By maintaining both active (current) and provisional (proposed) controller plans, EDA supports controllers in coordinated traffic planning both within and between sectors. Ultimately, EDA s multi-sector planning approach will facilitate a transition from current sector-oriented operations to a new trajectory-oriented paradigm, enabling new levels of efficiency and collaboration in air traffic control.

Vivona, Robert↗
NASA NTRS2005

Multi-Center Traffic Management Advisor Operational Field Test Results

The Multi-Center Traffic Management Advisor (McTMA) is a research prototype system which seeks to bring time-based metering into the mainstream of air traffic control (ATC) operations. Time-based metering is an efficient alternative to traditional air traffic management techniques such as distance-based spacing (miles-in-trail spacing) and managed arrival reservoirs (airborne holding). While time-based metering has demonstrated significant benefit in terms of arrival throughput and arrival delay, its use to date has been limited to arrival operations at just nine airports nationally. Wide-scale adoption of time-based metering has been hampered, in part, by the limited scalability of metering automation. In order to realize the full spectrum of efficiency benefits possible with time-based metering, a much more modular, scalable time-based metering capability is required. With its distributed metering architecture, multi-center TMA offers such a capability.

Farley, Todd↗
NASA NTRS2005

The Effects of the Uncertainty of Departures on Multi-Center Traffic Management Advisor (TMA) Scheduling

The Multi-center Traffic Management Advisor (McTMA) provides a platform for regional or national traffic flow management, by allowing long-range cooperative time-based metering to constrained resources, such as airports or air traffic control center boundaries. Part of the demand for resources is made up of proposed departures, whose actual departure time is difficult to predict. For this reason, McTMA does not schedule the departures in advance, but rather relies on traffic managers to input their requested departure time. Because this happens only a short while before the aircraft's actual departure, McTMA is unable to accurately predict the amount of delay airborne aircraft will need to take in order to accommodate the departures. The proportion of demand which is made up by such proposed departures increases as the horizon over which metering occurs gets larger. This study provides an initial analysis of the severity of this problem in a 400-500 nautical mile metering horizon and discusses potential solutions to accommodate these departures. The challenge is to smoothly incorporate departures with the airborne stream while not excessively delaying the departures.' In particular, three solutions are reviewed: (1) scheduling the departures at their proposed departure time; (2) not scheduling the departures in advance; and (3) scheduling the departures at some time in the future based on an estimated error in their proposed time. The first solution is to have McTMA to automatically schedule the departures at their proposed departure times. Since the proposed departure times are indicated in their flight times in advance, this method is the simplest, but studies have shown that these proposed times are often incorrect2 The second option is the current practice, which avoids these inaccuracies by only scheduling aircraft when a confirmed prediction of departure time is obtained from the tower of the departure airport. Lastly, McTMA can schedule the departures at a predicted departure time based on statistical data of past departure time performance. It has been found that departures usually have a wheels-up time after their indicated proposed departure time, as shown in Figure 1. Hence, the departures were scheduled at a time in the future based on the mean error in proposed departure times for their airport.

Thipphavong, Jane↗
NASA NTRS2006

Pilot Weather Advisor System

The Pilot Weather Advisor (PWA) system is an automated satellite radio-broadcasting system that provides nearly real-time weather data to pilots of aircraft in flight anywhere in the continental United States. The system was designed to enhance safety in two distinct ways: First, the automated receipt of information would relieve the pilot of the time-consuming and distracting task of obtaining weather information via voice communication with ground stations. Second, the presentation of the information would be centered around a map format, thereby making the spatial and temporal relationships in the surrounding weather situation much easier to understand

Lindamood, Glenn↗
NASA NTRS2013

Research Traffic Management Advisor (rTMA) Up-level Final Report

The FAA Time Based Flow Management (TBFM) Program provides for operational use and continued development of the Traffic Management Advisor (TMA) technology that NASA demonstrated in 1996. Although NASA's Center-TRACON Automation System (CTAS) software baseline includes advanced versions of TMA, some research activities are better served by a version of TMA that more closely matches the FAA's TBFM software. Beginning in 2009, NASA created Research TMA (rTMA) to enable researchers to work with FAA TBFM software in a research environment. The original rTMA was derived from TBFM v3.10 and later up-leveled to TBFM v3.12. This report documents the most recent up-level effort in which rTMA was re-derived from TBFM v4.00.07.

traffic management↗
NASA NTRS2013

Spot and Runway Departure Advisor

The Spot and Runway Departure Advisor (SARDA) is a research prototype of a decision support tool for ATC tower controllers to assist in manging and controlling traffic on the surface of an airport. SARDA employs a scheduler to generate an optimal runway schedule and gate push-back - spot release sequence and schedule that improves efficiency of surface operations. The advisories for ATC tower controllers are displayed on an Electronic Flight Strip (EFS) system. The human-in-the-loop simulation of the SARDA tool was conducted for east operations of Dallas-Ft. Worth International Airport (DFW) to evaluate performance of the SARDA tool and human factors, such as situational awareness and workload. The results indicates noticeable taxi delay reduction and fuel savings by using the SARDA tool. Reduction in controller workload were also observed throughout the scenario runs. The future plan includes modeling and simulation of the ramp operations of the Charlotte International Airport, and develop a decision support tool for the ramp controllers.

decision support tool↗
NASA NTRS2016

Spot and Runway Departure Advisor (SARDA)

Spot and Runway Departure Advisor (SARDA) is a decision support tool to assist airline ramp controllers and ATC tower controllers to manage traffic on the airport surface to significantly improve efficiency and predictability in surface operations. The core function of the tool is the runway scheduler which generates an optimal solution for runway sequence and schedule of departure aircraft, which would minimize system delay and maximize runway throughput. The presentation also discusses the latest status of NASA's current surface research through a collaboration with an airline partner, where a tool is developed for airline ramp operators to assist departure pushback operations. The presentation describes the concept of the SARDA tool and results from human-in-the-loop simulations conducted in 2012 for Dallas-Ft. Worth International Airport and 2014 for Charlotte airport ramp tower.

surface management↗
NASA NTRS2017

The Generic Resolution Advisor and Conflict Evaluator (GRACE) for Detect-And-Avoid (DAA) Systems

The paper describes the Generic Resolution Advisor and Conflict Evaluator (GRACE), a novel alerting and guidance algorithm that combines flexibility, robustness, and computational efficiency. GRACE is "generic" in that it makes no assumptions regarding temporal or spatial scales, aircraft performance, or its sensor and communication systems. Accordingly, GRACE is well suited to research applications where alerting and guidance is a central feature and requirements are fluid involving a wide range of aviation technologies. GRACE has been used at NASA in a number of real-time and fast-time experiments supporting evolving requirements of DAA research, including parametric studies, NAS-wide simulations, human-in-the-loop experiments, and live flight tests.

Unmanned Aircraft↗
NASA NTRS2017

The Generic Resolution Advisor and Conflict Evaluator (GRACE) for Detect-And-Avoid Systems

Java Architecture for Detect-And-Avoid (DAA) Extensibility and Modeling (JADEM) was developed at NASA Ames Research Center as a research and modeling tool for Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS). UAS will be required to have DAA systems in order to fulfill the regulatory requirement to remain well clear'' of other traffic. JADEM supports research on technological requirements and Minimum Operational Performance Standards (MOPS) for UAS DAA systems by providing a flexible and extensible software platform that includes models and algorithms for all major DAA functions. This paper describes one of these algorithms, the Generic Resolution Advisor and Conflict Evaluator (GRACE). GRACE supports two core DAA functions: threat evaluation and guidance. GRACE is generic in the sense that it is designed to work with any aircraft or sensor type (both cooperative and non-cooperative), and to be used in various applications and DAA guidance concepts, thus supporting evolving MOPS requirements and research. GRACE combines flexibility, robustness, and computational efficiency. It has modest memory requirements and can handle multiple cooperative and noncooperative intruders. GRACE has been used as a core JADEM component in several real-time and fast-time experiments, including human-in-the-loop simulations and live flight tests.

detect and avoid↗
NASA NTRS2017

The Generic Resolution Advisor and Conflict Evaluator (GRACE) for Unmanned Aircraft Detect-And-Avoid Systems

The paper describes the Generic Resolution Advisor and Conflict Evaluator (GRACE), a novel alerting and guidance algorithm that combines flexibility, robustness, and computational efficiency. GRACE is generic since it was designed without any assumptions regarding temporal or spatial scales, aircraft performance, or its sensor and communication systems. Therefore, GRACE was adopted as a core component of the Java Architecture for Detect-And-Avoid (DAA) Extensibility and Modeling, developed by NASA as a research and modeling tool for Unmanned Aerial Systems Integration in the National Airspace System (NAS). GRACE has been used in a number of real-time and fast-time experiments supporting evolving requirements of DAA research, including parametric studies, NAS-wide simulations, human-in-the-loop experiments, and live flight tests.

Unmanned Aircraft↗
NASA NTRS2014

Overview: Spot and Runway Departure Advisor (SARDA)

Spot and Runway Departure Advisor (SARDA) is a decision support tool to assist airline ramp controllers and ATC tower controllers to manage traffic on the airport surface to significantly improve efficiency and predictability in surface operations. The core function of the tool is the runway scheduler which generates an optimal solution for runway sequence and schedule of departure aircraft, which would minimize system delay and maximize runway throughput. The presentation describes the concept of the SARDA tool and results from human-in-the-loop simulations conducted in 2012 for DallasFt. Worth International Airport. The presentation also explains the latest status of NASA's current surface research through a collaboration with an airline partner. The presentation concludes with a discussion on other on-going as well as future surface research.

decision support tool↗
NASA NTRS2015

Enhancing the Traffic Management Advisor's Schedule by Time Advance

A time advance algorithm associated with the scheduling functionalities of the Traffic Management Advisor (TMA) for arrival flights is presented and evaluated. The algorithm enhances TMA's meter fix schedule by advancing the flights' Scheduled Time of Arrival (STA) by an amount that minimizes their systemic operating cost. The systemic operating cost leverages the inherent trade-off of time and fuel efficiency resident in the cost index of modern flight management systems. The resulting STAs are achievable by speeding up the leading flights from their desired nominal speed profiles. A key advantage of this approach is that it reduces systemic delay to tight groupings of arriving aircraft as well as increases sustained throughput of the operation. A fast-time, Monte Carlo simulation that emulates TMA's scheduling functionalities is performed for arrival flights to the Phoenix Airport to quantify the benefit of the time advance algorithm. Results show consistent time saving benefits, ranging from 3 to 50 minutes for 112 flights with varying levels of traffic congestion.

arrival traffic management↗
NASA NTRS2019

Spot and Runway Departure Advisor (SARDA) Technical Overview

This presentation provides a technical overview of the Spot and Runway Departure Advisor (SARDA), including concept, technical approach, recent research results, and next step. This presentation was prepared for the kickoff meeting with KAIA (Korea Agency for Infrastructure Technology Advancement).

Surface management↗