Advisory Algorithm for Scheduling Open Sectors, Operating Positions, and Workstations

Air traffic controller supervisors configure available sector, operating position, and work-station resources to safely and efficiently control air traffic in a region of airspace. In this paper, an algorithm for assisting supervisors with this task is described and demonstrated on two sample problem instances. The algorithm produces configuration schedule advisories that minimize a cost. The cost is a weighted sum of two competing costs: one penalizing mismatches between configurations and predicted air traffic demand and another penalizing the effort associated with changing configurations. The problem considered by the algorithm is a shortest path problem that is solved with a dynamic programming value iteration algorithm. The cost function contains numerous parameters. Default values for most of these are suggested based on descriptions of air traffic control procedures and subject-matter expert feedback. The parameter determining the relative importance of the two competing costs is tuned by comparing historical configurations with corresponding algorithm advisories. Two sample problem instances for which appropriate configuration advisories are obvious were designed to illustrate characteristics of the algorithm. Results demonstrate how the algorithm suggests advisories that appropriately utilize changes in airspace configurations and changes in the number of operating positions allocated to each open sector. The results also demonstrate how the advisories suggest appropriate times for configuration changes

Flight to Grandmother\u27s

https://digitalcommons.cwu.edu/government_posters/1170/thumbnail.jp

Pilot\u27s Handbook of Aeronautical Knowledge, 2016

The Pilot’s Handbook of Aeronautical Knowledge provides basic knowledge that is essential for pilots. This handbook introduces pilots to the broad spectrum of knowledge that will be needed as they progress in their pilot training. Except for the Code of Federal Regulations pertinent to civil aviation, most of the knowledge areas applicable to pilot certification are presented. The Pilot’s Handbook of Aeronautical Knowledge provides basic knowledge for the student pilot learning to fly, as well as pilots seeking advanced pilot certification. For detailed information on a variety of specialized flight topics, see specific Federal Aviation Administration (FAA) handbooks and Advisory Circulars (ACs). Occasionally the word “must” or similar language is used where the desired action is deemed critical. The use of such language is not intended to add to, interpret, or relieve a duty imposed by Title 14 of the Code of Federal Regulations (14 CFR). It is essential for persons using this handbook to become familiar with and apply the pertinent parts of 14 CFR and the Aeronautical Information Manual (AIM). The AIM is available online at www.faa.gov. The current Flight Standards Service airman training and testing material and learning statements for all airman certificates and ratings can be obtained from https://www.faa.gov

A Risk Assessment Architecture for Enhanced Engine Operation

On very rare occasions, in-flight emergencies have occurred that required the pilot to utilize the aircraft's capabilities to the fullest extent possible, sometimes using actuators in ways for which they were not intended. For instance, when flight control has been lost due to damage to the hydraulic systems, pilots have had to use engine thrust to maneuver the plane to the ground and in for a landing. To assist the pilot in these situations, research is being performed to enhance the engine operation by making it more responsive or able to generate more thrust. Enabled by modification of the propulsion control, enhanced engine operation can increase the probability of a safe landing during an inflight emergency. However, enhanced engine operation introduces risk as the nominal control limits, such as those on shaft speed, temperature, and acceleration, are exceeded. Therefore, an on-line tool for quantifying this risk must be developed to ensure that the use of an enhanced control mode does not actually increase the overall danger to the aircraft. This paper describes an architecture for the implementation of this tool. It describes the type of data and algorithms required and the information flow, and how the risk based on engine component lifing and operability for enhanced operation is determined

Pilot\u27s Handbook of Aeronautical Knowledge, 2016

The Pilot’s Handbook of Aeronautical Knowledge provides basic knowledge that is essential for pilots. This handbook introduces pilots to the broad spectrum of knowledge that will be needed as they progress in their pilot training. Except for the Code of Federal Regulations pertinent to civil aviation, most of the knowledge areas applicable to pilot certification are presented. The Pilot’s Handbook of Aeronautical Knowledge provides basic knowledge for the student pilot learning to fly, as well as pilots seeking advanced pilot certification. For detailed information on a variety of specialized flight topics, see specific Federal Aviation Administration (FAA) handbooks and Advisory Circulars (ACs). Occasionally the word “must” or similar language is used where the desired action is deemed critical. The use of such language is not intended to add to, interpret, or relieve a duty imposed by Title 14 of the Code of Federal Regulations (14 CFR). It is essential for persons using this handbook to become familiar with and apply the pertinent parts of 14 CFR and the Aeronautical Information Manual (AIM). The AIM is available online at www.faa.gov. The current Flight Standards Service airman training and testing material and learning statements for all airman certificates and ratings can be obtained from https://www.faa.gov

Intelligent Systems for Unmanned Aircraft Safety Certification

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97143/1/AIAA2012-958.pd

Investigating the Heat Generation Efficiency of Electrically-Conductive Asphalt Mastic Using Infrared Thermal Imaging

One of the emerging technologies for producing sustainable ice-and snow-free pavements is the use of electrically-conductive surface courses, e.g., electrically-conductive asphalt concrete (ECAC) that can melt ice and snow through resistive heating. Modifying the mastic in asphalt concrete with electrically-conductive materials is a promising approach for producing high-quality ECAC. The objective of this study is to evaluate electrical conductivity and heat generation efficiency of electrically-conductive asphalt mastic (ECAM) specimens at a below-freezing temperature—simulating the harsh weather conditions in North America during the wintertime. To this end, asphalt mastic was electrically modified with carbon fiber (CF) at varying volume contents. The ECAM specimens were then powered by 60V AC during a time window of 10 minutes so that their heat generation capacity could be characterized through infrared thermography (IRT). Based on the resistivity measurements and thermal data analysis, the most reasonable CF content enabling rapid heat-generating ECAM was identified; this has future implications with respect to achieving efficient highway, bridge, and airport pavement operations during wintertime

Prediction and Analysis of Ground Stops with Machine Learning

A flight is considered to be delayed when it arrives 15 or more minutes later than scheduled. Delays attributed to the National Airspace System are one of the most common type of delays. Such delays may be caused by Traffic Management Initiatives (TMI) such as Ground Stops (GS), issued at affected airports. Ground Stops are implemented to control air traffic volume to specific airports where the projected traffic demand is expected to exceed the airports’ acceptance rate over a short period of time due to conditions such as inclement weather, volume constraints, closed runways, etc. Ground Stops can be considered to be the strictest Traffic Management Initiative (TMI), particularly because all flights destined to affected airports are grounded until conditions improve. Efforts have been made over the years to reduce the impact of Traffic Management Initiatives on airports and flight operations. However, these efforts have largely focused on otherTraffic Management Initiatives such as Ground Delay Programs (GDP), due to their frequency and duration compared to Ground Stops. Limited work has also been carried out on Ground Stops because of the limited amount of time that traffic management personnel often have between planning and implementing Ground Stops and external factors that influence decisions of traffic management personnel. Consequently, this research primarily focuses on the prediction of weather-related Ground Stops at Newark Liberty International (EWR) and LaGuardia (LGA) airports, with the secondary goal of gaining insights into factors that influence their occurrence. It is expected that this research will provide stakeholders with further insights into factors that influence the occurrence of weather-related Ground Stops at both airports. This is achieved by benchmarking Machine Learning algorithms in order to identify the best suited algorithm(s) for the prediction models, and identifying and analyzing key factors that influence the occurrence of weather-related Ground Stops at both airports. This is achieved by 1) fusing data from the Traffic Flow Management System (TFMS) and Automated Surface Observing Systems (ASOS) datasets, and 2) leveraging supervised Machine Learning algorithms to predict the occurrence of weather-related Ground Stops. The performance of these algorithms is evaluated using balanced accuracy, and identifies the Boosting Ensemble algorithm as the best suited algorithm for predicting the occurrence of Ground Stops at EWR and LGA. Further analysis also revealed that model performance is significantly better when using balanced datasets compared to imbalanced datasets

Mission Analysis and Aircraft Sizing of a Hybrid-Electric Regional Aircraft

The purpose of this study was to explore advanced airframe and propulsion technologies for a small regional transport aircraft concept (approximately 50 passengers), with the goal of creating a conceptual design that delivers significant cost and performance advantages over current aircraft in that class. In turn, this could encourage airlines to open up new markets, reestablish service at smaller airports, and increase mobility and connectivity for all passengers. To meet these study goals, hybrid-electric propulsion was analyzed as the primary enabling technology. The advanced regional aircraft is analyzed with four levels of electrification, 0 percent electric with 100 percent conventional, 25 percent electric with 75 percent conventional, 50 percent electric with 50 percent conventional, and 75 percent electric with 25 percent conventional for comparison purposes. Engine models were developed to represent projected future turboprop engine performance with advanced technology and estimates of the engine weights and flowpath dimensions were developed. A low-order multi-disciplinary optimization (MDO) environment was created that could capture the unique features of parallel hybrid-electric aircraft. It is determined that at the size and range of the advanced turboprop: The battery specific energy must be 750 watt-hours per kilogram or greater for the total energy to be less than for a conventional aircraft. A hybrid vehicle would likely not be economically feasible with a battery specific energy of 500 or 750 watt-hours per kilogram based on the higher gross weight, operating empty weight, and energy costs compared to a conventional turboprop. The battery specific energy would need to reach 1000 watt-hours per kilogram by 2030 to make the electrification of its propulsion an economically feasible option. A shorter range and/or an altered propulsion-airframe integration could provide more favorable results