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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 127 records · Page 7

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NASA NTRS1998

On-Board Switching and Routing Advanced Technology Study

Future satellite communications is expected to be fully integrated into National and Global Information Infrastructures (NII/GII). These infrastructures will carry multi gigabit-per-second data rates, with integral switching and routing of constituent data elements. The satellite portion of these infrastructures must, therefore, be more than pipes through the sky. The satellite portion will also be required to perform very high speed routing and switching of these data elements to enable efficient broad area coverage to many home and corporate users. The technology to achieve the on-board switching and routing must be selected and developed specifically for satellite application within the next few years. This report presents evaluation of potential technologies for on-board switching and routing applications.

Yegenoglu, F.↗

NASA NTRS2005

Conflict Resolution Performance in an Experimental Study of En Route Free Maneuvering Operations

NASA has developed a far-term air traffic management concept, termed Distributed Air/Ground Traffic Management (DAG-TM). One component of DAG-TM, En Route Free Maneuvering, allows properly trained flight crews of equipped autonomous aircraft to assume responsibility for separation from other autonomous aircraft and from Instrument Flight Rules (IFR) aircraft. Ground-based air traffic controllers continue to separate IFR traffic and issue flow management constraints to all aircraft. To examine En Route Free Maneuvering operations, a joint human-in-the-loop experiment was conducted in summer 2004 at the NASA Ames and Langley Research Centers. Test subject pilots used desktop flight simulators to resolve traffic conflicts and adhere to air traffic flow constraints issued by subject controllers. The experimental airspace integrated both autonomous and IFR aircraft at varying traffic densities. This paper presents a subset of the En Route Free Maneuvering experimental results, focusing on airborne and ground-based conflict resolution, and the effects of increased traffic levels on the ability of pilots and air traffic controllers to perform this task. The results show that, in general, increases in autonomous traffic do not significantly impact conflict resolution performance. In addition, pilot acceptability of autonomous operations remains high throughout the range of traffic densities studied. Together with previously reported findings, these results continue to support the feasibility of the En Route Free Maneuvering component of DAG-TM.

Doble, Nathan A.↗

NASA NTRS2001

Method and System For an Automated Tool for En Route Traffic Controllers

A method and system for a new automation tool for en route air traffic controllers first finds all aircraft flying on inefficient routes, then determines whether it is possible to save time by bypassing some route segments, and finally whether the improved route is free of conflicts with other aircraft. The method displays all direct-to eligible aircraft to an air traffic controller in a list sorted by highest time savings. By allowing the air traffic controller to easily identify and work with the highest pay-off aircraft, the method of the present invention contributes to a significant increase in both air traffic controller and aircraft productivity. A graphical computer interface (GUI) is used to enable the air traffic controller to send the aircraft direct to a waypoint or fix closer to the destination airport by a simple point and click action.

Heinz Erzberger↗

NASA NTRS2001

Method and system for an automated tool for en route traffic controllers

Erzberger, Heinz↗

NASA NTRS2010

Automated Flight Routing Using Stochastic Dynamic Programming

Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.

Ng, Hok K.↗

NASA NTRS2010

En Route Air Traffic Control Input Devices for the Next Generation

The purpose of this study was to investigate the usefulness of different input device configurations when trial planning new routes for aircraft in an advanced simulation of the en route workstation. The task of trial planning is one of the futuristic tools that is performed by the graphical manipulation of an aircraft's trajectory to reroute the aircraft without voice communication. In this study with two input devices, the FAA's current trackball and a basic optical computer mouse were evaluated with "pick" button in a click-and-hold state and a click-and-release state while the participant dragged the trial plan line. The trial plan was used for three different conflict types: Aircraft Conflicts, Weather Conflicts, and Aircraft + Weather Conflicts. Speed and accuracy were the primary dependent variables. Results indicate that the mouse conditions were significantly faster than the trackball conditions overall with no significant loss of accuracy. Several performance ratings and preference ratings were analyzed from post-run and post-simulation questionnaires. The release conditions were significantly more useful and likable than the hold conditions. The results suggest that the mouse in the release button state was the fastest and most well liked device configuration for trial planning in the en route workstation. Keywords-input devices, en route, controller, workstation, mouse, trackball, NextGen

Mainini, Matthew J.↗

NASA NTRS2010

A Computer Simulation of the System-Wide Effects of Parallel-Offset Route Maneuvers

Most aircraft managed by air-traffic controllers in the National Airspace System are capable of flying parallel-offset routes. This paper presents the results of two related studies on the effects of increased use of offset routes as a conflict resolution maneuver. The first study analyzes offset routes in the context of all standard resolution types which air-traffic controllers currently use. This study shows that by utilizing parallel-offset route maneuvers, significant system-wide savings in delay due to conflict resolution of up to 30% are possible. It also shows that most offset resolutions replace horizontal-vectoring resolutions. The second study builds on the results of the first and directly compares offset resolutions and standard horizontal-vectoring maneuvers to determine that in-trail conflicts are often more efficiently resolved by offset maneuvers.

Lauderdale, Todd A.↗

NASA NTRS2013

Contact Graph Routing Enhancements Developed in ION for DTN

The Interplanetary Overlay Network (ION) software suite is an open-source, flight-ready implementation of networking protocols including the Delay/Disruption Tolerant Networking (DTN) Bundle Protocol (BP), the CCSDS (Consultative Committee for Space Data Systems) File Delivery Protocol (CFDP), and many others including the Contact Graph Routing (CGR) DTN routing system. While DTN offers the capability to tolerate disruption and long signal propagation delays in transmission, without an appropriate routing protocol, no data can be delivered. CGR was built for space exploration networks with scheduled communication opportunities (typically based on trajectories and orbits), represented as a contact graph. Since CGR uses knowledge of future connectivity, the contact graph can grow rather large, and so efficient processing is desired. These enhancements allow CGR to scale to predicted NASA space network complexities and beyond. This software improves upon CGR by adopting an earliest-arrival-time cost metric and using the Dijkstra path selection algorithm. Moving to Dijkstra path selection also enables construction of an earliest- arrival-time tree for multicast routing. The enhancements have been rolled into ION 3.0 available on sourceforge.net.

Segui, John S.↗

NASA NTRS2017

A Machine Learning Concept for DTN Routing

This paper discusses the concept and architecture of a machine learning based router for delay tolerant space networks. The techniques of reinforcement learning and Bayesian learning are used to supplement the routing decisions of the popular Contact Graph Routing algorithm. An introduction to the concepts of Contact Graph Routing, Q-routing and Naive Bayes classification are given. The development of an architecture for a cross-layer feedback framework for DTN (Delay-Tolerant Networking) protocols is discussed. Finally, initial simulation setup and results are given.

Delay Tolerant Networks↗

NASA NTRS2018

Air Traffic Management Technology Demonstration - 3 (ATD-3) Multi-Flight Common Route (MFCR) Concept of Operations Version 1.0

NASA's Multi Flight Common Route (MFCR) automation represents one element of those technologies focusing primarily on delay recovery in the en route phase of flight. Delay recovery is an attenuation of flight-time delay, accomplished by periodically revising weather-avoidance routing as the convective weather system evolves. MFCR is intended for use by Traffic Management Coordinators (TMCs) in Air Route Traffic Control Centers (ARTCCs, or Centers) and traffic management specialists (TMSs) in the Air Traffic Control System Command Center (ATCSCC). MFCR leverages existing weather, airspace, and traffic data, as well as improvements in navigation, surveillance, communication, and digital information technologies, to build on existing ATM automation and address some of the shortcomings associated with strategic traffic flow management initiatives and weather forecasting uncertainties. These capabilities provide significant potential benefits in the form of time, fuel, and cost savings. The concept of operations described in this document describes MFCR functionality as delivered by NASA to the FAA in December 2017, including a list of potential enhancements that may be realized when the system is fielded.

conops↗

NASA NTRS2014

Development of a Route Crossing Tool for Shared Airspace Environments

In current-day Terminal Radar Approach Control (TRACON) operations, departure and arrival controllers maintain separate and dedicated airspace for their respective traffic flows. Although this practice has obvious safety features, it also leads to inefficiencies; for example, departure aircraft may be routinely capped beneath arrival airspace. With the right decision-support and coordination tools, departures could continue to climb through arrival airspace when sufficient gaps exist. Previous studies of ‘shared airspace’ have examined pre-arranged coordination procedures, as well as tools that gave feedback to the controllers on where gaps between arrivals were located and whether the departure aircraft could be scheduled to fly through those gaps [1, 2, 3, 4]. Since then, the Route Crossing Tool (RCT) has been developed to allow controllers to assess multiple pre-defined route options at points where the arrivals and departures cross, thereby increasing the possibility of climbing a departure through an arrival gap.The RCT aids in ensuring lateral separation between departure and arrival aircraft that pass through the same altitude. Since the RCT can be applied tactically, it can enable aircraft to fly through arrival flows even if these aircraft depart outside scheduled times. The RCT makes use of a set of predefined parallel departure routes crossing the arrival flow at equidistant intersecting points on the arrival route. The RCT uses the Estimated Time of Arrival (ETA) of the departure aircraft at each intersecting point to calculate the lateral separation with the neighboring arrivals when it crosses that point; this information is graphically displayed to the controller. Additionally, the RCT incorporates forecast winds in its ETA predictions.Multiple prototypes of the RCT have been iteratively developed with feedback from Subject Matter Experts (SMEs). This paper presents the final design, the design process, and lessons learned. Initial results from a simulation suggest that the tool was successful in helping controllers to safely climb more aircraft. Controller feedback on the tool was also positive.

shared airspace↗

NASA NTRS2019

Application of Machine Learning Techniques to Delay Tolerant Network Routing

This dissertation discusses several machine learning techniques to improve routing in delay tolerant networks (DTNs). These are networks in which there may be long one-way trip times, asymmetric links, high error rates, and deterministic as well as non-deterministic loss of contact between network nodes, such as interplanetary satellite networks, mobile ad hoc networks and wireless sensor networks. This work uses historical network statistics to train a multi-label classifier to predict reliable paths through the network. In addition, a clustering technique is used to predict future mobile node locations. Both of these techniques are used to reduce the consumption of resources such as network bandwidth, memory and data storage that is required by replication routing methods often used in opportunistic DTN environments. Thesis contributions include: an emulation tool chain developed to create a DTN test bed for machine learning, the network and software architecture for a machine learning based routing method, the development and implementation of classification and clustering techniques and performance evaluation in terms of machine learning and routing metrics.

Dudukovich, Rachel M.↗

NASA NTRS2015

Simple Tool for Aircraft Noise-Reduction Route Design

The design of arrival and departure routes from an airport has to balance the conflicting requirements of fuel efficiency, airport capacity utilization and community emission and noise considerations. The commonly used tools for aircraft noise assessment are the FAA’s Integrated Noise Model (INM) and Aviation Environmental Design Tool (AEDT). These tools are suitable to generate precise noise contours. However, they are harder to use with other tools for route design optimization involving evaluation of a large number of aircraft trajectories. A simplified aircraft noise computation tool, named AIRNOISE, is developed for preliminary aircraft noise-reduction route design in this paper. AIRNOISE computes aircraft noise based on the same SAE-AIR-1845 procedures used by INM and AEDT. AIRNOISE does not consider components related to terrain and atmosphere adjustments. As a result, it is not only computationally efficient but also flexible to use for customized aircraft profiles. The aircraft noise results are compared with the FAA’s AEDT2b and show that the level of accuracy achieved by AIRNOISE can be used to reduce the number of route design options to a small number from a large pool for subsequent accurate analysis by INM.

Li, Jinhua↗

NASA NTRS2015

Dynamic Arrival Routes: A Trajectory-Based Weather Avoidance System for Merging Arrivals and Metering

Convective weather can cause arrival traffic to fly less efficient weather avoidance routes and is the primary cause for time-based metering to be discontinued. Dynamic Arrival Routes (DAR) is a trajectory-based weather avoidance system that is designed to help improve arrival traffic flow when weather is present. The DAR system continuously analyzes airborne arrival flights for opportunities to reroute them to more efficient arrival routes or around weather that is predicted to be on their current flight plan early enough to allow the arrival time-based metering system to adjust its times of arrival for the presence of weather. Analysis of 93 hours of actual traffic over 12 different days from Fort Worth Center showed DAR proposed more efficient arrival reroutes for 352 arrival flights for an average time savings of 12.3 minutes per flight at a look-ahead time of 60 minutes from the meter fix. DAR also identified 642 arrival flights with a need to deviate around weather and proposed weather avoidance routes that were analytically shown to remain weather-free 83 percent of the time for a look-ahead time of 30 minutes from the meter fix.

Arrivals↗

NASA NTRS2008

Dynamic Routing for Delay-Tolerant Networking in Space Flight Operations

Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology composed of scheduled, bounded communication contacts in a network built on the Delay-Tolerant Networking (DTN) architecture. It is designed to support operations in a space network based on DTN, but it also could be used in terrestrial applications where operation according to a predefined schedule is preferable to opportunistic communication, as in a low-power sensor network. This paper will describe the operation of the CGR system and explain how it can enable data delivery over scheduled transmission opportunities, fully utilizing the available transmission capacity, without knowing the current state of any bundle protocol node (other than the local node itself) and without exhausting processing resources at any bundle router.

CGR↗

NASA NTRS2016

A Mathematical Model and Algorithm for Routing Air Traffic Under Weather Uncertainty

A central challenge in managing today's commercial en route air traffic is the task of routing the aircraft in the presence of adverse weather. Such weather can make regions of the airspace unusable, so all affected flights must be re-routed. Today this task is carried out by conference and negotiation between human air traffic controllers (ATC) responsible for the involved sectors of the airspace. One can argue that, in so doing, ATC try to solve an optimization problem without giving it a precise quantitative formulation. Such a formulation gives the mathematical machinery for constructing and verifying algorithms that are aimed at solving the problem. This paper contributes one such formulation and a corresponding algorithm. The algorithm addresses weather uncertainty and has closed form, which allows transparent analysis of correctness, realism, and computational costs.

uncertainty↗

NASA NTRS2018

TCAS Alerts from Simulated Urban Air Mobility Flights Along FAA Helicopter Routes in Dallas-Fort Worth

This is a presentation of the current state of a TCAS study being conducted by the ATM-X project. This study examines the rate at which an urban air mobility vehicle flying along existing helicopter routes near DFW will trigger alerts on the TCAS II systems equipped on commercial airliners flying in the D10 TRACON of DFW airspace. The presentation will cover initial results, as well as next steps on the path towards producing a full paper. These initial results show that some aircraft could fly along published helicopter routes, while obeying published restrictions, and fly into and out of DFW airport without triggering any TCAS RAs, so long as the airport is operating in South Flow and the UAM vehicles approach and depart; the airport in the same direction as commercial traffic. Attempting to take off opposite the direction of commercial traffic produces a large number of TCAS RAs. Future work will examine North Flow, check sensitivity to aircraft performance, and examine alternative routes.

helicopter routes↗

DOE OSTI2024

Reducing AI RAG Hallucination by Optimizing Routing Techniques

Large Language Models (LLMs), such as ChatGPT, tend to “hallucinate”, meaning they confidently generate false information. Retrieval Augmented Generation (RAG) attempts to diminish hallucination by providing context to the LLM from data stores (indexes) containing relevant information. The LLM uses this context to formulate its response. RAG systems can still suffer from hallucination because of bad embeddings or ineffective routing. For example, a router will often return context from an irrelevant index, resulting in a hallucinated answer. In this study, we aim to minimize the frequency of routing hallucinations by optimizing Index Summary Routing.

97 MATHEMATICS AND COMPUTING↗