Dallas-Fort Worth International Airport Research Articles

Deep-Learning Framework for Terminal Airspace Trajectory Prediction and In-Time Prognostics

Terminal airspace around an airport is the biggest bottleneck for commercial operations in the National Airspace System. To prognosticate the safety status of the terminal airspace, effective prediction of the airspace evolution is necessary. While there are fixed procedural structures for managing operations at an airport, the confluence of a large number of aircraft and the complex interactions between the pilots and air traffic controllers make it challenging to predict its evolution. Modeling the high-dimensional spatiotemporal interactions in the airspace given different environmental and infrastructural constraints is necessary for effective predictions of future aircraft trajectories that characterize the airspace state at any given moment. A novel deep-learning architecture using Graph Neural Networks is proposed to predict trajectories of aircraft 10 min into the future and estimate prognostic metrics for the airspace. The uncertainty in the future is quantified by predicting distributions of future trajectories instead of point estimates. The framework’s viability for trajectory prediction and prognosis is demonstrated with terminal airspace data from Dallas Fort Worth International Airport.

An examination of sUAS operations in proximity to a major U.S. Airport

The use of small, Unmanned Aircraft Systems (sUAS) has proliferated in the past several years. While operators are supposed to avoid operations in the immediate vicinity of airports, there are sometimes violations. In extreme cases, these violations can result in the complete grounding of flights at major airports around the world. These disruptions can lead to thousands of flights canceled and hundreds of thousands of passengers displaced. A compounding problem is the lack of empirical data to understand the amount of, and types of, sUAS operations around major airports. The purpose of this study was to assess the characteristics of sUAS operations near the Dallas-Fort Worth International Airport (DFW) by objectively analyzing data collected over a 36-month timeframe. The findings provide empirical data on the types of sUAS operations around DFW, yearly variance in operations, levels of UAS facility map compliance, types and times of sUAS flown, and sUAS launching points. The data indicates a growing trend in operations between 2018 and 2020, with a possible plateau in 2021 and beyond. sUAS operations in the airport vicinity are high, with approximately 70 % operating in the 400-foot grid levels or at points farther away from critical airport operations. Flights appear to follow seasonality and daily operation patterns, and growth seems to be in smaller vehicles with weights less than 250 g. In addition to the results, the authors discuss practical implications for National Airspace System (NAS) safety and the implications of integrating new operations into communities, such as drone deliveries and Advanced Air Mobility operations.

Data-driven simulation-based planning for electric airport shuttle systems: A real-world case study

Many airports are adopting battery electric buses in their shuttle fleets due to concerns over air quality and regulations. This study proposes a simulation-based optimization modeling framework to help airport shuttle operators effectively deploy electric buses. We evaluated a planned airport electric shuttle system with an event-driven simulator. Empirical data collected from existing systems were used to drive the simulations. We then proposed a simulation-based optimization model to determine the battery capacity, charging power, and number of chargers so that predefined objective(s) (e.g., minimizing total capital cost, minimizing emissions) are optimized. Compared to existing studies, the primary contribution of the proposed method is that it can model the real-world stochastic nature of operations in an electric bus system with much higher fidelity. To demonstrate the proposed modeling framework, we study a real-world shuttle system at the Dallas-Fort Worth International Airport, and present extensive numerical studies. When considering partial fleet electrification, the model can provide a set of Pareto optimal solutions. When considering full fleet electrification, the optimal solution requires a 50-kWh battery capacity and four 210-kW chargers, resulting in a total capital cost of $26,744,000. The results demonstrate that the proposed modeling framework can effectively optimize the planning of electric airport shuttle systems with partial or full fleet electrification.

Impact of Airspace Restrictions on Urban Air Mobility Airport Shuttle Service Route Feasibility

Initial urban air mobility (UAM) operations are anticipated to include airport shuttle services between airport terminals and city centers. UAM airport shuttle operations have the potential to improve the customer experience and provide airports with new revenue streams but risk interfering with current airport operations. In this paper, we develop a discrete, heuristics-based optimization framework to explore the impact of airspace constraints and the placement of vertiports in the airport terminal area on the feasibility of UAM shuttle operations. The framework is applied to the terminal areas of Hartsfield-Jackson Atlanta International Airport (ATL), Dallas Fort Worth International Airport (DFW), and Los Angeles International Airport (LAX). Small-scale UAM operations are found to be feasible at all three airports with current terminal-area procedures, particularly if UAM aircraft are classified as helicopters. Scaled-up operations are found to be most feasible at ATL because of the possibility of segregating UAM aircraft from commercial traffic, whereas scaled-up operations at LAX and DFW are expected to require the adoption of new technologies, procedures, and regulations.

A discrete-event simulation tool for airport deicing activities: Dallas-Fort Worth International Airport

Aircraft deicing/anti-icing fluids (ADFs) are applied to remove and prevent icing on aircraft during taxi and takeoff. The Dallas-Fort Worth (DFW) International Airport uses deicing pads for deicing activities that collect and contain the spent deicing fluids for proper treatment or disposal. Local waterways receive ADF as “drip and shear” during the aircraft taxi on the runway and then takeoff. The glycol-based ADF serves as a nutrient for bacteria that grow exponentially, deplete dissolved oxygen (DO) from receiving waterways, and subsequently kill aquatic life. In this paper, we present a data-driven discrete-event simulation modeling process developed in collaboration with DFW Airport to assess aircraft assignment strategies to deicing pad locations by monitoring impact on DO. Our process consists of the following phases: (1) Data Collection, (2) Probability Distribution Modeling, and (3) State Transition Modeling. Both Phases (2) and (3) utilized data mining approaches, including treed regression and variable selection via false discovery rate. Detailed implementation of these phases is described for the DFW Airport case study, and the DFW Airport deicing activities simulation tool framework is presented. The actual data and simulation results were compared in terms of the DO levels in airport receiving waterways to verify the model validity after implementing the proposed model for DFW. Thus, the proposed model can be implemented by airports to control and minimize the adverse environmental effects resulting from deicing activities by optimizing the aircraft assignment to the pad locations.

A modeling framework for designing and evaluating curbside traffic management policies at Dallas-Fort Worth International Airport

Emerging mobility technologies are changing the transportation system landscape. This is especially evident at airports, such as the Dallas-Fort Worth International Airport (DFW). Without careful analysis, these changes could lead to inefficient and costly airport operations. This paper presents a modeling framework that integrates travel mode encoding, demand projection, and microsimulation to enable airports to develop, simulate, and evaluate curbside traffic managements policies and measure their impact. The framework is utilized to analyze several traffic scenarios and policies for DFW: a baseline scenario which represents DFW traffic pattern as observed in 2018 and projected to 2045, a transit network company (TNC) electrification policy, a TNC queuing policy, a policy that increased transit ridership, a bus-only policy which considers the use of only buses inside DFW, an autonomous vehicle (AV) policy which investigates the impact of autonomous vehicle (AV) adoption on airport operations, and an example COVID-19 scenario which models the impact of the COVID19 pandemic. The simulations’ results demonstrate that: increasing the DFW transit ridership postpones the need for airport curbside expansion the most; encouraging shared-mobility with the bus-only policy produces the most savings in curbside congestion delays; automation and electrification for all passenger vehicle trips to/from DFW generates the most saving in fuel consumption and emissions; and uncontrolled AV adoption incurs the highest increase in fuel consumption, delay, and emissions and could require immediate airport capacity extension. Without policy intervention or investment in additional infrastructure capacity, these results predict the current operations would face significant congestion on high demand days starting as early as 2028. While derived in close partnership with DFW, the methodology presented here can be generalized to any airport.

Joint Modeling of Access Mode and Parking Choice of Air Travelers Using Revealed Preference Data

Airport ground access mode choice is distinct from everyday mode choice decisions, necessitating context-specific choice model estimation. Understanding airport ground access mode choice decisions is not only important for developing infrastructure planning strategies, but also for assessing the impacts of emerging modes on airport revenues, particularly from parking. However, parking choice is an often-overlooked dimension in airport ground access choice modeling. This paper addresses this gap through the development of a joint model of airport access mode and parking option choice using a passenger survey conducted at Dallas-Fort Worth (DFW) International Airport in 2015. Compared with a traditional conditional logit model that does not consider parking options available at DFW airport, the joint model of mode and parking decisions was found to generate more realistic values of travel time and was shown to have better predictive performance, both of which are critical for obtaining better airport parking revenue estimates and identifying traveler cohorts who may respond more strongly to potential policies targeting curb congestion and parking demand.

A data-driven operational model for traffic at the Dallas Fort Worth International Airport

Airports are on the front line of significant innovations, allowing the movement of more people and goods faster, cheaper, and with greater convenience. As air travel continues to grow, airports will face challenges in responding to increasing passenger vehicle traffic, which leads to lower operational efficiency, poor air quality, and security concerns. This paper evaluates methods for traffic demand forecasting combined with traffic microsimulation, which will allow airport operations staff to accurately predict traffic and congestion. Using two years of detailed data describing individual vehicle arrivals and departures, aircraft movements, and weather at Dallas-Fort Worth (DFW) International Airport, we evaluate multiple prediction methods including the Auto Regressive Integrated Moving Average (ARIMA) family of models, traditional machine learning models, and DeepAR, a modern recurrent neural network (RNN). We find that these algorithms are able to capture the diurnal trends in the surface traffic, and all do very well when predicting the next 30 minutes of demand. Longer forecast horizons are moderately effective, demonstrating the challenge of this problem and highlighting promising techniques as well as potential areas for improvement.Traffic demand is not the only factor that contributes to terminal congestion, because temporary changes to the road network, such as a lane closure, can make benign traffic demand highly congested. Combining a demand forecast with a traffic microsimulation framework provides a complete picture of traffic and its consequences. The result is an operational intelligence platform for exploring policy changes, as well as infrastructure expansion and disruption scenarios. To demonstrate the value of this approach, we present results from a case study at DFW Airport assessing the impact of a policy change for vehicle routing in high demand scenarios. This framework can assist airports like DFW as they tackle daily operational challenges, as well as explore the integration of emerging technology and expansion of their services into long term plans.

Route optimization for energy efficient airport shuttle operations – A case study from Dallas Fort worth International Airport

The objective of this research is to reduce energy consumption from intra airport shuttle operations by optimizing routes and schedules, without compromising on passenger travel experience. To achieve this objective, we propose an optimization model that generates optimal airport shuttle routes for a given set of constraints and a discrete-event simulator that evaluates the optimal shuttle routes in a stochastic environment to understand the tradeoffs between the amount of time passengers wait for shuttles, and shuttle energy consumption. The proposed optimization model and stochastic simulation are tested using shuttle route data provided by the Dallas Fort Worth International Airport. Results indicate that optimized routes can lead to a 20% energy reduction in shuttle operations with a modest 2-min increase in average shuttle wait times. The optimization model and simulator presented here are designed to be generalizable and can be adapted to optimize shuttle operations at any major airport.

AERIAL ART, THE NEW LANDSCAPE OF ROBERT SMITHSON

Aircraft were to play a decisive role in the short career of Robert Smithson. In 1969, when he published his article Aerial Art, Walther Prokosch, an architect specializing in aviation, put him in contact with TAMS engineering. This gave rise to his involvement in a land altering operation as vertiginous and brutal as the construction of Dallas Fort-Worth International Airport. At that point Smithson became aware of the human capacity to transform Mother Earth and the importance of contemplation from the air. He incorporated these interests into his artistic creation, thus paving the way for earthwork, crucial to the evolution of Land Art. The study of the documents included among Robert Smithson’s Papers at the Smithsonian Museum of American Art allows us to reconstruct a history that shared interests and concerns with Moholy-Nagy’s New Vision or Le Corbusier’s Loi du Méandre.

Cultural Resources Survey of the DPS Outdoor Bomb and Gun Range Project, Dallas Fort Worth International Airport, Tarrant County, Texas

This report documents the substantive findings and management recommendations of a cultural resources survey conducted by Integrated Environmental Solutions, LLC (IES) for the DPS Outdoor Bomb and Gun Range project located within the Dallas Fort Worth International Airport (DFW) property in Tarrant County, Texas. The proposed project pertains to improvements of the current facility within approximately 71.8 acres located between Texas State Highway (SH) 360 and West Airfield Drive. Approval from the Federal Aviation Administration (FAA) will be required to modify the Airport Layout Plan (ALP) to reflect the permanent alterations on the DFW property. Since the ALP is considered a federal action, the project will require compliance with the National Environmental Policy Act (NEPA) and Section 106 of the National Historic Preservation Act (NHPA). Additionally, as the DFW is a political subdivision of the State of Texas, the project will be subjected to the provisions of the Antiquities Code of Texas (ACT). The goal of the survey was to locate, identify, and assess any cultural resources that could be adversely affected by the proposed development, and to evaluate such resources for their potential eligibility for listing as a State Antiquities Landmark (SAL) and eligibility for listing in the National Register of Historic Places (NRHP). The cultural resources inventory survey was conducted on 16 December 2019 and 08 January 2020 by Project Archeologists Anne Gibson and Thomas Chapman, and Staff Archeologist Josh McCormick. All work conformed to 13 Texas Administrative Code 26, which outlines the regulations for implementing the ACT, and was conducted under Texas Antiquities Permit No. 9161. During the survey, one previously recorded historic-age archeological site (41TR87) was revisited within the APE. Based on the lack of association with historically important individuals or events, absence of significant architectural features, the degree of prior disturbance, and lack of contextual integrity, site 41TR87 is recommended to remain not eligible for listing in the NRHP or designation as a SAL. Although multi-component site 41TR18 was partially located within the APE, the site was not evaluated during the survey. However, the results from a previous IES investigation in 2015 indicate the site should remain ineligible for NRHP listing. Project records will be permanently curated at the Center for Archeological Research (CAR) at The University of Texas at San Antonio (UTSA). It is the recommendation of IES that the DPS Outdoor Bomb and Gun Range Project be permitted to continue without the need for further cultural resources investigations. However, if any cultural resources, other than those discussed in this report, are encountered during construction, the operators should stop construction activities in the vicinity of the inadvertent discovery, and immediately contact the project cultural resources representative to initiate coordination with the Texas Historical Commission (THC) prior to resuming construction activities.

Life-cycle cost analysis of a short-haul underground freight transportation system for the DFW Airport

Purpose The purpose of this paper is to conduct life-cycle cost analysis of a short-haul underground freight transportation (UFT) system for the Dallas Fort Worth international airport. Design/methodology/approach The research approach includes: identifying the cost components of the proposed airport UFT system; estimating life-cycle cost (LCC) of system components using various methods; determining life-cycle cash flows; evaluating the reliability of the results using sensitivity analysis; and assessing the validity of the results using analogues cases. Findings Although the capital cost of constructing an airport UFT system seems to be the largest cost of such innovative projects, annual costs for running the system are more significant, taking a life-cycle perspective. System administrative cost, tunnel operation and maintenance, and tunnel construction cost are the principle cost components of the UFT system representing approximately 46, 24 and 19 percent of the total LCC, respectively. The shipping cost is estimated to be $4.14 per ton-mile. Although this cost is more than the cost of transporting cargos by trucks, the implementation of UFT systems could be financially justified considering their numerous benefits. Originality/value This paper, for the first time, helps capital planners understand the LCC of an airport UFT system with no or limited past experience, and to consider such innovative solutions to address airport congestion issues.

Application of underground short-haul freight pipelines to large airports

The Dallas Fort Worth International Airport handles about 600,000 metric tons of cargo annually. These shipments are currently transported by trucks from the airport cargo terminals. An underground freight transportation (UFT) system has the potential to substantially reduce the truck traffic within the DFW Airport area and thus improve safety, efficiency, and air quality. The main reason for designing a UFT system in the DFW Airport is security vulnerability, when trucks drive under or near active runways and taxiways and may have hazardous or explosive cargo. Besides, the proposed UFT system is expected to reduce the number of trucks on airport grounds and the airport access roadways, thus enhancing both the roadway access capacity and safety as well as reducing adverse environmental impacts such as emissions and noise. The objective of this paper is to examine the feasibility of underground short-haul freight pipelines to a large airport such as Dallas-Fort Worth (DFW) International Airport. The proposed short-haul UFT system transports standard air freight crates between an airport cargo terminal and a distribution center off the secured airport grounds. The DFW Airport UFT system design includes planning level configurations of the tracks, vehicle, propulsion system, end-point terminals, and loading/unloading mechanisms at those terminals. Operational attributes such as speeds, headways, loading/unloading times, and line capacities are also determined.

Modeling the Impact of Airport Deicing/Anti-icing Activities on the Dissolved Oxygen Levels in the Receiving Waterways

This paper evaluates the efficacy of the environmental management system (EMS) at Dallas Fort Worth International Airport (DFW) in capturing spent aircraft dei…

Data-driven optimization for Dallas Fort Worth International Airport deicing activities

Airplane deicing is a safety measure to eliminate/prevent icing on airplanes that can lead to airflow disruption and emergency conditions. Aircraft deicing/anti-icing fluids (ADF) are high in glycol content. At Dallas Fort Worth International Airport (DFW), the major aircraft deicing activities are conducted at designated deicing pads called Source Isolation Deicing Sites, where ADF run-off can be captured and conveyed into the airport’s glycol collection system. A portion of ADF drips from the aircraft during taxiing and shears off the aircraft during take-off, entering nearby waterways without treatment. Glycol acts as a nutrient for bacteria in the airport’s receiving waterways, resulting in an increase in bacterial growth and a subsequent reduction in dissolved oxygen (DO), potentially endangering aquatic life. This paper proposes a prototype data-driven deicing activities management framework for DFW to address the complexity of airport deicing operations and its impacts. The proposed framework uses stochastic dynamic programming (SDP) to assign airplanes in each hour to deicing pad locations, so as to maximize DO in the receiving waters, subject to airport constraints. Some data were artificially generated using the available knowledge of airport operations. The state transition equations in SDP were estimated. The proposed framework was demonstrated using three cases during major deicing events. Improvements in DO compared with actual DO recorded in the data were mixed; however, the results motivated DFW to implement a new data collection process to replace the artificially-generated data, so that a more accurate optimization could be conducted in the future.

Texas Takes Wing: A Century of Flight in the Lone Star State by Barbara Ganson (review)

Reviewed by: Texas Takes Wing: A Century of Flight in the Lone Star State by Barbara Ganson J’Nell Pate Texas Takes Wing: A Century of Flight in the Lone Star State. By Barbara Ganson. (Austin: University of Texas Press, 2014. Pp. 310. Illustrations, appendices, notes, bibliography, index.) Beginning with the first airplane flight in Texas, that of French aviator Louis Paulhan on February 18, 1910, author Barbara Ganson carries the story forward to 2010. She worked on a special aviation collection for the Bob Bullock Texas State History Museum in Austin for the 2010 centennial of flight in Texas. The first military airplane flight in Texas arrived less than two weeks after Paulhan’s [End Page 337] four separate flights that totaled less than an hour in the sky. Lt. Benjamin D. Foulois flew a Wright Flyer at Fort Sam Houston on March 2, 1910, a nice commemoration of Texas’ Independence Day in San Antonio that may or may not have been on purpose. With good flying weather and plenty of wide open spaces, Texas by 1922 possessed more landing fields for aircraft (162) than any other state. During World War II Texans constructed approximately 70 military airfields across the state, and Texas became one of the major training centers for pilots, including those of our allies. Even the headquarters for all pilot training in the nation during the war was in Fort Worth. The book’s nine chapters are arranged loosely in chronological order from the early days to World War I, barnstormers, record setters, and flying services between the wars, and then Texas activity during World War II. Later chapters discuss aircraft designers, manufacturers, the Cold War, and the space age. Within each chapter the author takes a topical, encyclopedic approach with each entry set off by italics. Some topics seem to receive more coverage than necessary, while often important persons or events receive only brief attention. Even so, the author has assembled a tremendous amount of information, some of it new or little known. Hopefully, this will encourage other researchers to engage in future study. Emphasis is on people, and the author was fortunate to interview in person many of those active in Texas’s aviation history. Some are native Texans, while others engaged in aviation careers in the state. To tell these stories she made use of numerous manuscript collections from museums and libraries not only in Texas, but throughout the nation. From these sources she gleaned a large number of photographs that appear throughout the book. Ganson asserts that Texas “has been at the forefront of aircraft manufacturing in the United States” (168), and in an extensive epilogue she sums up the contributions of Texas and Texans in the fields of general, industrial, and commercial aviation. Of Texas’s 387 airports, Dallas–Fort Worth International Airport is the third busiest in the United States, and Alliance Airport, also in the Dallas–Fort Worth Metroplex, “serves as an inland port for international trade” (185). Texas is the home of more major U.S. airlines than any other state. Among four appendices in the book, the first one cites a timeline of important aviation events in Texas from 1910 to 2010. While a few events and persons were omitted, the author reached her goal of making available a great deal of information on the aviation role that Texas has played during the last century as “Texas Takes Wing.” [End Page 338] J’Nell Pate Fort Worth, Texas Copyright © 2014 The Texas State Historical Association

Human–Systems Integration Design Process of the Air Traffic Control Tower Flight Data Manager

A user-friendly system that yields operational benefit results from data-driven prototype evaluations and benefits analyses that iteratively feed back into the prototype design and development. In this study, initial requirements development and field evaluations were conducted using a shadow operations technique at the center tower backup Dallas–Fort Worth International Airport air traffic control tower (ATCT). Results are discussed in reference to the design process of the Tower Flight Data Manager (TFDM) prototype. Nonintrusive measures for quantitatively validating human–systems design issues were identified for this study, including visual gaze analysis and verbal command sequence analysis. Behavioral validation of design issues simplifies the process to prioritize beneficial design changes. The iterative process used resulted in an interim TFDM prototype that was rated by active air traffic controllers as both beneficial and usable in an operational ATCT environment.

Data mining modeling on the environmental impact of airport deicing activities

This paper presents a statistical analysis on the environmental impact of airport deicing activities at Dallas-Fort Worth (D/FW) International Airport. The focus of this paper is on aircraft deicing, which typically uses a spray of aircraft deicing and anti-icing fluids (ADAF). ADAF has a high concentration of ethylene/propylene/diethylene glycol, which shears off airfoil surfaces during takeoff and drips to the runways during taxiing. A significant portion of the glycol runs off and mixes with the airport’s receiving waters during heavy deicing periods, resulting in bacterial growth that causes an increase in chemical oxygen demand (COD) and a subsequent reduction in dissolved oxygen (DO) in the receiving waters. In this study, statistical methods for data mining were employed to evaluate the impact of airport deicing activities on COD and DO in the receiving waters immediately surrounding D/FW Airport. In particular, decision tree models were developed to determine important explanatory variables for predicting levels of COD and DO in the airport’s waterways. The decision tree modeling and analysis of COD determined north–south wind, glycol usage at a specific deicing pad, and monitoring site to be significant explanatory variables. The impact of glycol usage on DO was apparent as every decision tree at least one group with a median DO below 4.0 mg/l, and these low-DO groups were associated with high glycol usage. These results are crucial to D/FW Airport in their goal to minimize the potential adverse impact of deicing activities on the water quality in waterways proximate to the airport. The advantages of data-driven modeling and analysis are its cost-effectiveness due to its potential to be implemented without making major changes in physical systems, ease of application, and usefulness in making future management decisions.

Multivariate analysis of the impacts of NAS investments: A case study of a capacity expansion at Dallas-Fort Worth Airport

Multivariate statistical analysis is used to estimate the impacts of a major capacity expansion at Dallas-Fort Worth International Airport. The model relates the Daily Flight Time Index (DFTI) to demand, weather, origin airport congestion, and the expansion itself. The effect of the capacity expansion on DFTI is found to depend strongly on visibility. On average, the index in the post-expansion period is 1.3 min less as a consequence of investment. This change includes a larger reduction in departure delay that is offset by an increase in taxi time. Moreover, the reduction caused by the expansion has been more than offset by increases in the DFTI resulting from other factors, notably increased demand and worse weather.

Voice recognition: software solutions in real-time ATC workstations

Speech recognition features desired by air traffic controllers, such as the ability to use complex messages and address hundreds of individual aircraft could not be implemented a decade ago, but these tasks became possible with improved speech recognition engines and an increase in processing power and memory. Speech recognition was a key element in the air traffic controller (ATC) workstation used to support a Controller-Pilot Data Link Communications (CPDLC) system. Our work, under the direction of the Avionics Engineering Center at Ohio University, was in support of the Federal Aviation Administration's (FAA) Runway Incursion Reduction Program (RIRP) and the National Aeronautics and Space Administration's (NASA) Runway Incursion Prevention System (RIPS) conducted at the Dallas-Fort Worth International Airport (DFW). This paper examines the challenges and opportunities of developing voice recognition software solutions in ATC workstations using multiple dialects and accents, complex and varied grammars and terminology, accuracy, hardware restrictions, and user-training procedures.