An Overview of Aeropropulsion Wind Tunnel Productivity Improvements at the NASA Lewis Research Center

Enhancing wind tunnel test productivity in terms of increased efficiency, reduced cost, and expanded flexibility is a high-priofity goal of the NASA Lewis Research Center's Aeropropulsion Facilities and Experiments Division. Over the past several years, several significant productivity improvements were implemented: test times were shortened by using facility and test article automation; additional flexibility was provided to the research customer by using the remote-access control room and by expanding facility operating envelopes; facility throughput was greatly increased and electric power cost for facility operation reduced by using the three-shift operation. One method being used to reduce electric power costs and expand the facility operating envelop in the 8- by 6-Foot Supersonic Wind Tunnel is operating the drive system with only one of the three drive motors. Metrics are being used to document several categories of facility utilization, which in turn allows tracking of test productivity. This paper provides an overview of the productivity improvements already in place in the large wind tunnels at NASA Lewis and presents plans for future improvements

Quantifying Desirable Air Route Attributes for a Reroute Generation Capability

When airspace is partially or completely blocked by severe weather, a major challenge for airspace managers and users is the creation and selection of viable alternate routing for air traffic. Research is underway for an automate d capability to help to meet this challenge. An important component of such a capability is the quantification of the attributes of operationally-acceptable routes. In this paper we describe two such quantifications, for route lateral deviation, and for flow preference

Assessing Schedule Delay Propagation in the National Airspace System

Flight delay propagation or “ripple” is a well-known phenomenon in the National Airspace System (NAS). It is when delay on one flight leg carries forward to a future flight leg for the same aircraft due to the practice of airlines scheduling multiple flight legs per aircraft. The research investigates where delay propagation is occurring in the NAS by analyzing historical data. A backtracking algorithm is proposed to tally delay that is experienced on the ground and in the air for each flight leg, which later becomes observable schedule delay at downstream airports. Results are shown across different time periods, carriers, weather conditions, and airports

Simulation Modeling in Support of a European Airspace Study

Abstract: To address some questions of usage of European airspace by United States Air Force aircraft, two simulation models are employed. The first model offers a wide array of functions to represent aircraft movement and management of aggregates or "flows " of aircraft. The second model uses a Petri net approach to represent the complexity of a flight planning/replanning operation, in order to estimate staffing requirements. Key-words: Simulation model, Petri net, air traffic management, airspace congestion.

State inspection program evaluation and data analysis. Volume I - summary report. Final report.

National Highway Traffic Safety Administration, Crash Avoidance Division, Washington, D.C.Mode of access: Internet.Author corporate affiliation: Automated Sciences Group, Inc., Silver Spring, Md.Report covers the period June 1975-Sept 1976Subject code: DZN*NOOSubject code: RCGB*DESubject code: WW

State inspection program evaluation and data analysis. Volume II. Technical report. Final report.

National Highway Traffic Safety Administration, Crash Avoidance Division, Washington, D.C.Mode of access: Internet.Author corporate affiliation: Automated Sciences Group, Inc., Silver Spring Md.Report covers the period June 1975-Sept 1976Subject code: DZN*NOOSubject code: RCGB*DESubject code: WW

Do Flight Times Change Year to Year? A Comparison of 2001 and 2002

For a system to be managed, it must be measured. The National Airspace System (NAS), the collection of airspace and airport resources in and under the control of the United States (U.S.), is a very complex system which presents great challenges of measurement and management. One key measure of en route airspace efficiency is flying time, i.e., the amount of time it takes for an aircraft to travel through en route airspace on its flight from origin to destination airport. A number of factors influence flying time, the most obvious being the winds. Other important factors are: traffic congestion, air traffic management (ATM) interventions, route structure, industry strategies, and weather. In this paper, we calculate en route flying time in the aggregate and compare a subset of data for the years 2001 and 2002. We account for aircraft equipment type and adjusted flying time for wind effects. In addition, we have selected for analysis a sample of only good weather days (15 in each of the 2 years). The results show that 2002 has slightly shorter flying times than 2001, on the order of 20–25 seconds shorter. Although we did not investigate the causes for the change, we conjecture that the lower levels of traffic after the Fall of 2001 are causing less congestion and less delay. New automation and procedural initiatives may also be contributing to the improvement. Introduction The Federal Aviation Administration (FAA) is charged with the safe, efficient movement of air traffic in U.S. airspace. In recent years, the FAA has begun initiatives to measure efficiency of airspace usage. The measurements are useful for determining the impact of automation and procedural enhancements. Such measurements are also useful for identifying problem areas in the NAS, which can be targeted for remediation. Changes in efficiency may be examined as a function of time. This study assessed system efficiency using en route flying times, comparing 2001 versus 2002. Although several studies have been performed in the past calculating changes in en route flying distance, the authors are familiar with one time-based analysis in the open literature. Bolczak, et al. used Estimated Time of Arrival (ETA) data to analyze a trend in flying time, and discover some year-to-year changes. Other studies of flight times are in the literature, though they have not compared actual or modeled values across years. An early simulation of Free Flight, Ball, et al. analyzed flying times for flights without the constraints of route structuring. Efficiency may be defined as the level of utilization of a resource, with consideration of the cost or effort undertaken to achieve that level. † Free Flight is an industry/government initiative which provides greater freedom for pilots and airlines to select planned and flown routes and take-off times. Free Flight supports collaboration between airspace managers and airspace users. 1 American Institute of Aeronautics and Astronautics Willemain examined sources of variability in flying times for certain city pairs. The Bureau of Transportation Statistics has collected flight time statistics and hosts a web site which allows the public to access this information. In this study, results are presented in aggregated form, with some detail with respect to city pairs. Differences were found in the flying time metrics: 2002 has slightly lower flying times than 2001. The causes for this difference are not discussed

BENEFITS ANALYSIS OF AN AIR TRAFFIC FLOW MANAGEMENT CAPABILITY

Air Traffic Management in the U.S. can logically be divided into two major components: (1) air traffic control (ATC) ensures pairwise separation of proximate aircraft, and (2) traffic flow management (TFM) seeks a general balance between demand and capacity for airspace and airport resources. A set of new capabilities for TFM is in the process of being developed, for deployment in the 2009-2014 timeframe. In this paper, we describe an analysis of the benefits of one capability – a capability called Automated Airborne Congestion Resolution (AACR). AACR is a capability that allows TFM staff to model, and then implement, alternatives for flight rerouting and take-off time delays when there are airspace constraints, i.e., reduced airspace sector capacity, typically because of severe weather. Our benefits analysis compares today’s approach with the proposed 2015 approach in which AACR provides automation support to augment and enhance human decision-making. Today’s approach is mostly manual – TFM staff plan and coordinate alternate routing as possible under conditions of the disorder and pressure-to-act associated with severe weather impacting airspace. The future approach relies more on a computed solution – AACR generates 1 DeArmon/Stalnaker Katkin/McKinney scores of reroutes, each with a spectrum of plausible take-off delays. The AACR approach can exploit scarce airspace resources when they are at a premium. In the paper, we present a comparative analysis of the current vs. future scenarios, with quantitative results