Leihong Li

Runway Assignments That Minimize Terminal Airspace and Airport Surface Emissions

Air traffic operations at and around major airports in the United States are in need of improvement. From the perspective of arrivals, when one or more runways are in great demand, unnecessary delay and emissions occur during peak periods at major airports while other runways at the same airport are operating under capacity. The primary cause of this imbalance in runway utilization is that traffic flow into and out of terminal areas is asymmetric (as a result of airline scheduling practices) and arrivals are typically assigned to the runway nearest the fix through which they enter the terminal area. From the perspective of departures, delays and emissions are incurred because arrivals take precedence over departures with regard to the utilization of runways (despite the absence of binding safety constraints) and because arrival trajectories often include level segments that ensure “procedural separation” from arriving traffic while planes are not allowed to climb unrestricted along the most direct path to...

Runway Assignment by Minimizing Emissions in Terminal Airspace

xes to runways, and taxi costs from runways to gates. This paper also includes details of mathematical formulations and the computation method of emissions. At the end of the paper, we provide a numerical example for planning landings and takeos at the Detroit international airport. The optimization results show that ight delays reduce as much as 44.7%, much greater than the runway sequence without runway assignment. Meanwhile, the emissions of optimal solution reduce as much as 25.4%. The proposed model for strategically planning terminal airspace operations is benecial to improve airport eciency and local environments.

Tensorial Parameterization of Rotation and Motion

The parameterizations of rotation and motion are the subject of continuous research and development in many theoretical and applied fields of mechanics such as rigid body, structural, and multibody dynamics. Tensor analysis expresses the invariance of the laws of physics with respect to the change of basis and change of frame operations. Consequently, it is imperative to formulate mechanics problems in terms of tensorial quantities. This paper presents formal proofs that rotation and motion parameterizations are tensors if and only if they are parallel to the eigenvectors of the rotation and motion tensors, respectively, associated with their unit eigenvalues. Furthermore, it also establishes that the tangent operators of rotation and motion are of a tensorial nature if and only if they are expressed in terms of the vectorial parameterizations of rotation and motion, respectively. Finally, important tensor identities are shown to hold for all vectorial parameterization of rotation and motion.

A simulation-based method for estimating metroplex efficiency

The nature of metroplex operations is interdependencies among its component airports. The operational interdependencies require a system view to study metroplex operations and a system-wide coordination solution method to solve and improve metroplex issues. This paper developed a link-node simulation model to study three typical generic metroplex layouts: tandem, parallel, and crossing. By studying the impact of sharing fixes and system-wide scheduling metroplex operations in the given generic metroplex layouts, decoupling fixes and temporal coordination among airports can improve system efficiency in a certain level.

Tensorial Deformation Measures for Flexible Joints

Flexible joints, sometimes called bushing elements or force elements, are found in all multibody dynamics codes. In their simplest form, flexible joints simply consist of sets of three linear and three torsional springs placed between two nodes of a multibody system. For infinitesimal deformations, the selection of the lumped spring constants is an easy task, which can be based on a numerical simulation of the joint or on experimental measurements. If the joint undergoes finite deformations, the identification of its stiffness characteristics is not so simple, especially if the joint itself is a complex system. When finite deformations occur, the definition of deformation measures becomes a critical issue. Indeed, for finite deformation, the observed nonlinear behavior of materials is partly due to material characteristics and partly due to kinematics. This paper focuses on the determination of the proper finite deformation measures for elastic bodies of finite dimension. In contrast, classical strain measures, such as the Green-Lagrange or Almansi strains, among many others, characterize finite deformations of infinitesimal elements of a body. It is argued that proper finite deformation measures must be of a tensorial nature, i.e., must present specific invariance characteristics. This requirement is satisfied if and only if the deformation measures are parallel to the eigenvector of the motion tensor.

A probabilistic decision-making model for runway configuration planning under stochastic wind conditions

Local meteorological conditions such as wind direction, cloud ceiling heights, and visibility directly influence the safety and efficiency of an airport. The safety and efficiency, generally contradictory, are associated with the selection of a particular runway configuration that is a part of job of airport tower controllers. When the wind speed and directions exceed the maximum allowable limit defined by the FAA operational procedures, controllers must change runway configurations. During this configuration change, the status of all arriving and departing aircrafts are turned into airborne or ground holding, respectively, until the new flight paths and the new taxi paths are clarified. This situation greatly influences the airport operational efficiency with its associated cost of delays, fuel burn and emissions. Despite its prominence, only a few studies that discuss the timing of decision-making for the configuration change can be found. In this study, an innovative decision-making approach is proposed for runway configuration planning under stochastic wind conditions. The goal of the decision-making approach is to maximize the airport throughput and minimize the airborne delay in terminal area, given a sequence of wind forecast data. The optimization techniques of dynamic programming and backwards induction are used to solve the probabilistic optimality equation. Based on the simulation results of JFK test case, the proposed approach is shown to reduce the average delay time and improve the throughput of runway systems without violating operational procedures.

Impact of Automatic Dependent Surveillance - Broadcast (ADS-B) on Traffic Alert and Collision Avoidance System (TCAS) Performance

The Traffic Alert and Collision Avoidance System (TCAS) has contributed to an increase in aviation safety by assisting flight crews with the resolution of conflicts that would have otherwise resulted in a mid-air collision. As TCAS uses secondary radar data, its performance could be improved with the greater positioning accuracies and sampling rates afforded by Automatic Dependent Surveillance-Broadcast (ADS-B), the satellite-based surveillance system that will be a key component of the Next Generation Air Transportation System. In this paper, we present the results of research carried out to determine the impact of ADS-B on TCAS. Three encounter scenarios were modeled including two aircraft with a level flight path intersection, an intruding aircraft descending towards another aircraft and two aircraft using continuous descent approaches to minimum-spaced parallel runways. The models were then probabilistically evaluated for both the current TCAS system and a TCAS employing ADS-B. The simulations showed that small improvements in TCAS performance could be realized through ADS-B, with several other factors having larger impacts. Nomenclature τ = total time taken by the aircraft to the projected closest point of approach (CPA) maneuver aircraft t _ = time taken to safely execute the escape maneuvers, including aircraft pull-up time and time-toclimb to the designated climb/descent rate of 1500 ft/min g proces data t sin _ = time taken for TCAS to process the data received from external sources pilot

Airport configuration planning with uncertain weather and noise abatement procedures

This paper develops a runway resource allocation model that is suitable for airport strategical planning. The model optimizes the selection of landing and takeoff runways and allocates capacity according to air traffic demand by minimizing delay and noise costs. The multi-objective optimization model is subject to a number of constraints, related to operational procedures, runway configuration capacity, safety, and weather conditions. Because weather accuracy is far from the accuracy requirements to make a deterministic perfect decision at the right time, we provide a method to quantify weather forecast accuracy. By using the probability density function of forecast errors, we derive formulations to calculate the probability that a runway configuration satisfies safety constraints given the predicted wind, ceiling, and visibility. Therefore, the optimization model will generate a best solution in the sense of probability.

Satisficing Game Approach to Collaborative Decision Making Including Airport Management

Collaborative decision making (CDM) has been used as an essential paradigm to increase the efficiency of air traffic flow management (ATFM), including takeoff or landing operations at airports. Air traffic control (ATC) services and airlines have been involved in the current CDM, but airport management service, an important stakeholder, has not been involved yet, generally. This paper proposes a new CDM model, which is named satisficing CDM, that is based on the satisficing game theory. This model includes three main entities (ATC, airlines, and airport management) in ATFM. The complete set of functions (preference, rejectability, and selectability) is established for each of the entities. Because the delay due to ground or air holding potentially alters the takeoff or the landing order of a flight, the sequence of takeoff and landing is determined through the satisficing negotiation process. To demonstrate the utility of the developed intelligent system, experiments are run with real air traffic in the terminal area of Sao Paulo. The experimental results show the importance and effectiveness of including airport management services in CDM. The sequences of takeoff and landing determined by the proposed model mostly meet the preferences of the three stakeholders in the given real traffic scenarios.

Air Traffic Flow Management Data Mining and Analysis for In-flight Cost Optimization

As the air traffic volume has increased significantly over the world, the great mass of traffic management data, named as Big Data, have also accumulated day by day. This factor presents more opportunities and also challenges as well in the study and development of Air Traffic Management (ATM). Usually, Decision Support Systems (DSS) are developed to improve the efficiency of ATM. The main problem for these systems is the data analysis to acquisition sufficient knowledge for the decision. This paper introduces the application of the methods of Data Mining to get the knowledge from air traffic Big Data in management processes. The proposed approach uses a Bayesian network for the data analysis to reduce the costs of flight delay. The process makes possible to adjust the flight plan such as the schedule of arrival at or departure from an airport and also checks the airspace control measurements considering weather conditions. An experimental study is conducted based on the flight scenarios between Los Angeles International Airport (LAX) and Miami International Airport (MIA).