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En route noise annoyance laboratory test: Preliminary results

Until recently concerns about the impact of aircraft noise on people have centered around the takeoff and landing operations of aircraft in the vicinity of airport terminals. The development of the advanced turboprop (propfan) engine, modifications to air corridors, and the desire to maintain a natural environment in national parks and recreation areas have now focused attention on the impact at ground level of the en route noise produced by aircraft at cruise conditions and altitudes. Compared to terminal area noise, en route noise is characterized by relatively low noise levels, lack of high frequency spectral content, and long durations. Much research has been directed towards understanding and quantifying the annoyance caused by terminal area aircraft noise, but relatively little research has been conducted for en route noise. To address this need, a laboratory experiment was conducted to quantify the annoyance of people on the ground to en route noise generated by aircraft at cruise conditions. The objectives of the experiment are to determine the annoyance prediction ability of noise measurement procedures and corrections when applied to en route noise; to determine differences in annoyance response to en route noise and takeoff/landing noise; and to determine differences in annoyance response to advanced turboprop en route noise and conventional jet en route noise.

Mccurdy, David A.

Adaptive fault-tolerant routing in hypercube multicomputers

A connected hypercube with faulty links and/or nodes is called an injured hypercube. To enable any non-faulty node to communicate with any other non-faulty node in an injured hypercube, the information on component failures has to be made available to non-faulty nodes so as to route messages around the faulty components. A distributed adaptive fault tolerant routing scheme is proposed for an injured hypercube in which each node is required to know only the condition of its own links. Despite its simplicity, this scheme is shown to be capable of routing messages successfully in an injured hypercube as long as the number of faulty components is less than n. Moreover, it is proved that this scheme routes messages via shortest paths with a rather high probabiltiy and the expected length of a resulting path is very close to that of a shortest path. Since the assumption that the number of faulty components is less than n in an n-dimensional hypercube might limit the usefulness of the above scheme, a routing scheme is introduced based on depth-first search which works in the presence of an arbitrary number of faulty components. Due to the insufficient information on faulty components, the paths chosen by the above scheme may not always be the shortest. To guarantee that all messages be routed via shortest paths, it is proposed that every mode be equipped with more information than that on its own links. The effects of this additional information on routing efficiency are analyzed, and the additional information to be kept at each node for the shortest path routing is determined. Several examples and remarks are also given to illustrate the results.

Chen, Ming-Syan

Dynamic Weather Routes: A Weather Avoidance Concept for Trajectory-Based Operations

The integration of convective weather modeling with trajectory automation for conflict detection, trial planning, direct routing, and auto resolution has uncovered a concept that could help controllers, dispatchers, and pilots identify improved weather routes that result in significant savings in flying time and fuel burn. Trajectory automation continuously and automatically monitors aircraft in flight to find those that could potentially benefit from improved weather reroutes. Controllers, dispatchers, and pilots then evaluate reroute options to assess their suitability given current weather and traffic. In today's operations aircraft fly convective weather avoidance routes that were implemented often hours before aircraft approach the weather and automation does not exist to automatically monitor traffic to find improved weather routes that open up due to changing weather conditions. The automation concept runs in real-time and employs two keysteps. First, a direct routing algorithm automatically identifies flights with large dog legs in their routes and therefore potentially large savings in flying time. These are common - and usually necessary - during convective weather operations and analysis of Fort Worth Center traffic shows many aircraft with short cuts that indicate savings on the order of 10 flying minutes. The second and most critical step is to apply trajectory automation with weather modeling to determine what savings could be achieved by modifying the direct route such that it avoids weather and traffic and is acceptable to controllers and flight crews. Initial analysis of Fort Worth Center traffic suggests a savings of roughly 50% of the direct route savings could be achievable.The core concept is to apply trajectory automation with convective weather modeling in real time to identify a reroute that is free of weather and traffic conflicts and indicates enough time and fuel savings to be considered. The concept is interoperable with today's integrated FMS/datalink. Auxiliary(lat/long) waypoints define a minimum delay reroute between current position and a downstream capture fix beyond the weather. These auxiliary waypoints can be uplinked to equipped aircraft and auto-loaded into the FMS. Alternatively, for unequipped aircraft, auxiliary waypoints can be replaced by nearby named fixes, but this could reduce potential savings. The presentation includes an overview of the automation approach and focuses on several cases in terms of potential savings, reroute complexity, best auxiliary waypoint solution vs. named fix solution, and other metrics.

McNally, B. David

Benefits Analysis of Multi-Center Dynamic Weather Routes

Dynamic weather routes are flight plan corrections that can provide airborne flights more than user-specified minutes of flying-time savings, compared to their current flight plan. These routes are computed from the aircraft's current location to a flight plan fix downstream (within a predefined limit region), while avoiding forecasted convective weather regions. The Dynamic Weather Routes automation has been continuously running with live air traffic data for a field evaluation at the American Airlines Integrated Operations Center in Fort Worth, TX since July 31, 2012, where flights within the Fort Worth Air Route Traffic Control Center are evaluated for time savings. This paper extends the methodology to all Centers in United States and presents benefits analysis of Dynamic Weather Routes automation, if it was implemented in multiple airspace Centers individually and concurrently. The current computation of dynamic weather routes requires a limit rectangle so that a downstream capture fix can be selected, preventing very large route changes spanning several Centers. In this paper, first, a method of computing a limit polygon (as opposed to a rectangle used for Fort Worth Center) is described for each of the 20 Centers in the National Airspace System. The Future ATM Concepts Evaluation Tool, a nationwide simulation and analysis tool, is used for this purpose. After a comparison of results with the Center-based Dynamic Weather Routes automation in Fort Worth Center, results are presented for 11 Centers in the contiguous United States. These Centers are generally most impacted by convective weather. A breakdown of individual Center and airline savings is presented and the results indicate an overall average savings of about 10 minutes of flying time are obtained per flight.

NAS based Benefits Analysis

Operational Evaluatioin of Dynamic Weather Routes at American Airlines

Dynamic Weather Routes (DWR) is a search engine that continuously and automatically analyzes inflight aircraft in en route airspace and proposes simple route amendments for more efficient routes around convective weather while considering sector congestion, traffic conflicts, and active Special Use Airspace. NASA and American Airlines (AA) are conducting an operational trial of DWR at the AA System Operations Center in Fort Worth, TX. The trial includes only AA flights in Fort Worth Center airspace. Over the period from July 31, 2012 through August 31, 2012, 45% of routes proposed by DWR and evaluated by AA users - air traffic control coordinators and flight dispatchers - were rated as acceptable as proposed or with some modifications. The wind-corrected potential flying time savings for these acceptable routes totals 470 flying min, and results suggest another 1,500 min of potential savings for flights not evaluated due to staffing limitations. A sector congestion analysis shows that in only two out of 83 DWR routes rated acceptable by AA staff were the flights predicted to fly through a congested sector inside of 30 min downstream of present position. This shows that users considered sector congestion data provided by DWR automation and in nearly all cases did not accept routes through over-capacity sectors. It is estimated that 12 AA flights were given reroute clearances as a direct result of DWR for a total savings of 67 flying min.

air traffic trajectory automation

The Effectiveness of a Route Crossing Tool in a Simulated New York Airspace

Congested airspace is the cause of many delays in the terminal area and these delays can have a ripple effect on the rest of a nation's airspace. The New York terminal area is an example of where this happens in the U. S. An important goal, therefore, is to increase the efficiency of operations in congested terminal airspace where possible. Modeling studies of arrival and departure flows have shown that sharing of arrival and departure airspace increases efficiency in terminal operations. One source of inefficiency in terminal operations is that departure aircraft are frequently held level under arrival flows when it would be more efficient to climb the departure aircraft earlier. A Route Crossing Tool was developed to help controllers climb Newark (EWR) departures to the south earlier by temporarily sharing airspace with arrivals coming into LaGuardia (LGA) from the south. Instead of flying under the arrivals, a departure to the south could climb earlier by flying through the arrival airspace if there was a suitable gap between arrivals. A Human-in-the-Loop (HITL) simulation was conducted in this environment which compared three tool conditions: Baseline (no tool), a Single Route Crossing tool in which one route through the arrival flow was evaluated for crossing, and a Multi-Route Crossing tool in which five parallel routes were evaluated. In all conditions, the departures could be held level under the arrival flow. The results showed that controllers climbed a higher proportion of departures in the Multi-Route tool condition than in the other two conditions, with a higher proportion of departures climbed in smaller gaps and in front of trailing arrivals. The controllers indicated that the Multi-Route and Single Route tools helped them estimate distances more accurately and rated safety, workload, and coordination in the simulation as acceptable.

terminal airspace

Human-in-the-Loop Evaluation of Dynamic Multi-Flight Common Route Advisories

Flights often experience large delays when they are routed around weather. Multi-flight common route advisories provide delay recovery by suggesting time-saving re-routes for groups of flights whose current weather-avoidance routes have become outdated because the weather has dissipated and/or moved away. A laboratory evaluation of these advisories was conducted by four subject matter experts having extensive experience in traffic flow management operations. These experts provided a total of 120 data points in the airspace of Houston Center. The multi-flight common route tool provides time-saving route change advisories taking into account flight plans, wind fields, and the spatio-temporal evolution of predicted convective weather. It is not designed to account for complex operational factors such as non-standard sector traversal and interactions with local traffic management initiatives; hence a relatively low percentage (37%) of advisories generated by the tool were rated as acceptable. However, a high percentage (81%) of advisories were rated as acceptable after the subject matter experts used the tool's user interface to make route modifications that accounted for relevant operational factors not considered by the tool. The workload associated with using the tool, as measured by the NASA Task Load Index, was quite low (1.1 on a scale of 0 to 10). The results of this evaluation make a good case for human-automation teaming to design operationally valid weather re-routes for delay recovery.

Traffic Flow Management

Human-in-the-Loop Evaluation of Dynamic Multi-Flight Common Route Advisories

Flights often experience large delays when they are routed around weather. Multi-flight common route advisories provide delay recovery by suggesting time-saving re-routes for groups of flights whose current weather-avoidance routes have become outdated because the weather has dissipated and/or moved away. A laboratory evaluation of these advisories was conducted by four subject matter experts having extensive experience in traffic flow management operations. These experts provided a total of 120 data points in the airspace of Houston Center. The multi-flight common route tool provides time-saving route change advisories taking into account flight plans, wind fields, and the spatio-temporal evolution of predicted convective weather. It is not designed to account for complex operational factors such as non-standard sector traversal and interactions with local traffic management initiatives; hence a relatively low percentage (37%) of advisories generated by the tool were rated as acceptable. However, a high percentage (81%) of advisories were rated as acceptable after the subject matter experts used the tool's user interface to make route modifications that accounted for relevant operational factors not considered by the tool. The workload associated with using the tool, as measured by the NASA Task Load Index, was quite low (1.1 on a scale of 0 to 10). The results of this evaluation make a good case for human-automation teaming to design operationally valid weather re-routes for delay recovery.

Traffic Flow Management

Intercomparison of surface meltwater routing models for the Greenland ice sheet and influence on subglacial effective pressures

Each summer, large volumes of surface meltwater drain off the Greenland ice sheet (GrIS) surface through moulins to the bed, impacting subglacial hydrology and ice flow dynamics. Supraglacial surface routing delays may propagate to englacial and subglacial hydrologic systems, requiring accurate assessment to correctly estimate subglacial effective pressures. We compare hourly supraglacial moulin discharge simulations from three surface meltwater routing models – the synthetic unit hydrograph (SUH), the bare-ice component of surface routing and lake filling (SRLF), and the rescaled width function (RWF) – for four internally drained catchments on the southwestern Greenland ice sheet surface. The routing models are forced identically using surface runoff from the Modèle Atmosphérique Régionale regional climate model (RCM). For each catchment, simulated moulin hydrographs are input to the SHAKTI subglacial hydrologic model to simulate diurnally varying subglacial effective-pressure variations in the vicinity of a single moulin. Overall, all three routing models produce more realistic moulin discharges than simply using RCM runoff outputs without surface routing but produce significant differences in peak moulin discharge and time to peak. In particular, the RWF yields later, smaller peak moulin discharges than the SUH or SRLF due to its representation of slow interfluve flow between supraglacial meltwater channels, and it can readily accommodate the seasonal evolution of supraglacial stream and river networks. Differences among the three routing models are reflected in a series of simple idealized subglacial hydrology simulations that yield different diurnal effective-pressure amplitudes; however, the supraglacial hydrologic system acts as short-term storage for surface meltwater, and the temporal mean effective pressure is relatively consistent across routing models.

Kang Yang

Dynamic Weather Routes: Two Years of Operational Testing at American Airlines

The Dynamic Weather Routes (DWR) tool continuously analyzes active flights in en-route airspace and finds simple route corrections to achieve more time- and fuel-efficient routes around convective weather. A strong partnership between NASA, American Airlines (AA), and the Federal Aviation Administration has enabled testing of DWR in real-world air traffic operations. NASA and AA have been conducting a trial of DWR at AA’s Integrated Operations Center in Fort Worth, Texas since July 2012. This paper describes test results based on AA’s use of DWR for their flights in and around Fort Worth Center (ZFW). Results indicate an actual savings of 3,290 flying minutes for 526 AA revenue flights from January 2013 through September 2014. Of these, 48 flights each indicate a savings of 15 minutes or more. Potential savings for all flights in ZFW airspace, corrected for savings flights achieve today through normal pilot requests and controller clearances, is about 100,000 flying minutes for 15,000 flights in 2013. Results indicate that AA flights with DWR in use realize about 20 percent more savings than non-AA flights. A weather forecast analysis examines the extent to which DWR routes rated acceptable by AA users remain clear of downstream weather. A sector congestion analysis indicates congestion could be reduced 19-38 percent if all flights fly DWR routes rather than nominal weather-avoidance routes.

Trajectory Automation

Predicting the Operational Acceptability of Route Advisories

NASA envisions a future Air Traffic Management system that allows safe, efficient growth in global operations, enabled by increasing levels of automation and autonomy. In a safety-critical system, the introduction of increasing automation and autonomy has to be done in stages, making human-system integrated concepts critical in the foreseeable future. One example where this is relevant is for tools that generate more efficient flight routings or reroute advisories. If these routes are not operationally acceptable, they will be rejected by human operators, and the associated benefits will not be realized. Operational acceptance is therefore required to enable the increased efficiency and reduced workload benefits associated with these tools. In this paper, the authors develop a predictor of operational acceptability for reroute advisories. Such a capability has applications in tools that identify more efficient routings around weather and congestion and that better meet airline preferences. The capability is based on applying data mining techniques to flight plan amendment data reported by the Federal Aviation Administration and data on requested reroutes collected from a field trial of the NASA developed Dynamic Weather Routes tool, which advised efficient route changes to American Airlines dispatchers in 2014. 10-Fold cross validation was used for feature, model and parameter selection, while nested cross validation was used to validate the model. The model performed well in predicting controller acceptance or rejection of a route change as indicated by chosen performance metrics. Features identified as relevant to controller acceptance included the historical usage of the advised route, the location of the maneuver start point relative to the boundaries of the airspace sector containing the maneuver start (the maneuver start sector), the reroute deviation from the original flight plan, and the demand level in the maneuver start sector. A random forest with forty trees was the best performing of the five models evaluated in this paper.

route advisories

Predicting the Operational Acceptability of Route Advisories

NASA envisions a future Air Traffic Management system that allows safe, efficient growth in global operations, enabled by increasing levels of automation and autonomy. In a safety-critical system, the introduction of increasing automation and autonomy has to be done in stages, making human-system integrated concepts critical in the foreseeable future. One example where this is relevant is for tools that generate more efficient flight routings or reroute advisories. If these routes are not operationally acceptable, they will be rejected by human operators, and the associated benefits will not be realized. Operational acceptance is therefore required to enable the increased efficiency and reduced workload benefits associated with these tools. In this paper, the authors develop a predictor of operational acceptability for reroute advisories. Such a capability has applications in tools that identify more efficient routings around weather and congestion and that better meet airline preferences. The capability is based on applying data mining techniques to flight plan amendment data reported by the Federal Aviation Administration and data on requested reroutes collected from a field trial of the NASA developed Dynamic Weather Routes tool, which advised efficient route changes to American Airlines dispatchers in 2014. 10-Fold cross validation was used for feature, model and parameter selection, while nested cross validation was used to validate the model. The model performed well in predicting controller acceptance or rejection of a route change as indicated by chosen performance metrics. Features identified as relevant to controller acceptance included the historical usage of the advised route, the location of the maneuver start point relative to the boundaries of the airspace sector containing the maneuver start (the maneuver start sector), the reroute deviation from the original flight plan, and the demand level in the maneuver start sector. A random forest with forty trees was the best performing of the five models evaluated in this paper.

operational acceptability

Analysis of Multi-Flight Common Routes for Traffic Flow Management

When severe convective weather requires rerouting aircraft, FAA traffic managers employ severe weather avoidance plans (e.g., Playbook routes, Coded Departure Routes, etc.) These routes provide pilots with safe paths around weather-affected regions, and provide controllers with predictable, and often well-established flight plans. However, they often introduce large deviations to the nominal flight plans, which may not be necessary as weather conditions change. If and when the imposed traffic management initiatives (TMIs) become stale, updated shorter path flight trajectories may be found en route, providing significant time-savings to the affected flights. Multiple Flight Common Routes (MFCR) is a concept that allows multiple flights that are within a specified proximity or region, to receive updated shorter flight plans in an operationally efficient manner. MFCR is believed to provide benefits to the National Airspace System (NAS) by allowing traffic managers to update several flight plans of en route aircraft simultaneously, reducing operational workload within the TMUs of all affected ARTCCs. This paper will explore some aspects of the MFCR concept by analyzing multiple flights that have been selected for rerouting by the NAS Constraint Evaluation and Notification Tool (NASCENT). Various methods of grouping aircraft with common or similar routes will be presented, along with a comparison of the efficacy of these methods.

dynamic weather routes

Parallel algorithms for placement and routing in VLSI design

The computational requirements for high quality synthesis, analysis, and verification of very large scale integration (VLSI) designs have rapidly increased with the fast growing complexity of these designs. Research in the past has focused on the development of heuristic algorithms, special purpose hardware accelerators, or parallel algorithms for the numerous design tasks to decrease the time required for solution. Two new parallel algorithms are proposed for two VLSI synthesis tasks, standard cell placement and global routing. The first algorithm, a parallel algorithm for global routing, uses hierarchical techniques to decompose the routing problem into independent routing subproblems that are solved in parallel. Results are then presented which compare the routing quality to the results of other published global routers and which evaluate the speedups attained. The second algorithm, a parallel algorithm for cell placement and global routing, hierarchically integrates a quadrisection placement algorithm, a bisection placement algorithm, and the previous global routing algorithm. Unique partitioning techniques are used to decompose the various stages of the algorithm into independent tasks which can be evaluated in parallel. Finally, results are presented which evaluate the various algorithm alternatives and compare the algorithm performance to other placement programs. Measurements are presented on the parallel speedups available.

Brouwer, Randall Jay

A workstation-based evaluation of a far-field route planner for helicopters

Helicopter flight missions at very low, nap of the Earth, altitudes place a heavy workload on the pilot. To aid in reducing this workload, Ames Research Center has been investigating various types of automated route planners. As part of an automated preflight mission planner, a route planner algorithm aids in selecting the overall (far-field) route to be flown. During the mission, the route planner can be used to replan a new route in case of unexpected threats or change in mission requirements. An evaluation of a candidate route planning algorithm, based on dynamic programming techniques is described. This algorithm meets most of the requirements for route planning, both preflight and during the mission. In general, the requirements are to minimize the distance and/or fuel and the deviation from a flight time schedule, and must be flyable within the constraints of available fuel and time.

Warner, David N., Jr.

Weather Avoidance Using Route Optimization as a Decision Aid: An AWIN Topical Study

The aviation community is faced with reducing the fatal aircraft accident rate by 80 percent within 10 years. This must be achieved even with ever increasing, traffic and a changing National Airspace System. This is not just an altruistic goal, but a real necessity, if our growing level of commerce is to continue. Honeywell Technology Center's topical study, "Weather Avoidance Using Route Optimization as a Decision Aid", addresses these pressing needs. The goal of this program is to use route optimization and user interface technologies to develop a prototype decision aid for dispatchers and pilots. This decision aid will suggest possible diversions through single or multiple weather hazards and present weather information with a human-centered design. At the conclusion of the program, we will have a laptop prototype decision aid that will be used to demonstrate concepts to industry for integration into commercialized products for dispatchers and/or pilots. With weather a factor in 30% of aircraft accidents, our program will prevent accidents by strategically avoiding weather hazards in flight. By supplying more relevant weather information in a human-centered format along with the tools to generate flight plans around weather, aircraft exposure to weather hazards can be reduced. Our program directly addresses the NASA's five year investment areas of Strategic Weather Information and Weather Operations (simulation/hazard characterization and crew/dispatch/ATChazard monitoring, display, and decision support) (NASA Aeronautics Safety Investment Strategy: Weather Investment Recommendations, April 15, 1997). This program is comprised of two phases, Phase I concluded December 31, 1998. This first phase defined weather data requirements, lateral routing algorithms, an conceptual displays for a user-centered design. Phase II runs from January 1999 through September 1999. The second phase integrates vertical routing into the lateral optimizer and combines the user interface into a prototype software testbed. Phase II concludes with a dispatcher and pilot evaluation of the route optimizer decision aid. This document describes work completed in Phase I in contract with NASA Langley August 1998 - December 1998. This report includes: (1) Discuss how weather hazards were identified in partnership with experts, and how weather hazards were prioritized; (2) Static representations of display layouts for integrated planning function (3) Cost function for the 2D route optimizer; (4) Discussion of the method for obtaining, access to raw data of, and the results of the flight deck user information requirements definition; (5) Itemized display format requirements identified for representing weather hazards in a route planning aid.

Source record

Defining Dynamic Route Structure

This poster describes a method for defining route structure from flight tracks. Dynamically generated route structures could be useful in guiding dynamic airspace configuration and helping controllers retain situational awareness under dynamically changing traffic conditions. Individual merge and diverge intersections between pairs of flights are identified, clustered, and grouped into nodes of a route structure network. Links are placed between nodes to represent major traffic flows. A parametric analysis determined the algorithm input parameters producing route structures of current day flight plans that are closest to todays airway structure. These parameters are then used to define and analyze the dynamic route structure over the course of a day for current day flight paths. Route structures are also compared between current day flight paths and more user preferred paths such as great circle and weather avoidance routing.

Zelinski, Shannon

Airspace Technology Demonstration 3 (ATD-3): Multi-Flight Common Route (MFCR) Technology Transfer Document Summary Version 1.0

This summary document and accompanying technology artifacts satisfy the second of three Research Transition Products (RTPs) defined in the ATD-3 Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. This transfer consists of NASA's Multi-Flight Common Route (MFCR) research for efficient route corrections for en-route weather avoidance. The MFCR concept builds on the experience of the legacy Dynamic Weather Routes (DWR) and focuses on a better balance of potential savings with ATC acceptability, common route corrections options for multiple flights on similar routings, and better use of existing and/or modern automation for communication and coordination of route change options. All of these capabilities are expected to improve system performance significantly in terms of actual delay-reducing clearances issued to flights compared to that of the DWR tool and operating concept.

tech transfer