A Preliminary Study of Taxi-out Times Using Discrete-Event Simulation of an Airport with Intersecting Runways

Jiansen Wang; Shantanu Gupta; Mary E. Johnson

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Conference: 2024 ASEE North Central Section Conference
Location: Kalamazoo, Michigan
Publication Date: March 22, 2024
Start Date: March 22, 2024
End Date: March 23, 2024
Page Count: 9
DOI: 10.18260/1-2--45591
Permanent URL: https://peer.asee.org/45591
Download Count: 18

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Paper Authors

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Jiansen Wang orcid.org/0009-0001-2663-834X

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Jiansen is a PhD candidate in the School of Aviation and Transportation Technology at Purdue University. He began his PhD study in Technology at Purdue University in 2021, under the supervision of Dr. Mary E Johnson. His research focuses on improving airport capacity and sustainability. Jiansen completed his M.S degree in Aviation and Aerospace Management at Purdue University in 2020. During his masters study, Jiansen earned second place award in Airport Cooperative Research Program Competition in 2020. Prior to graduate school, Jiansen completed his B.S. degree in Engineering from Civil Aviation University of China.

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Shantanu Gupta Purdue University at West Lafayette (PPI) orcid.org/0000-0002-5619-7012

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Shantanu Gupta is a PhD candidate in the School of Aviation and Transportation Technology at Purdue University with Dr. Mary E. Johnson. He earned his B.E in Mechanical Engineering from Visvesvaraya Technological University, India, and M.S in Aviation and Aerospace Management from Purdue University, West Lafayette. Mr. Gupta is currently working with Dr. Johnson as research assistant on the PEGASAS Project 33 – Augmented Weather Information Project (AWIP) and Project 35 - Enhanced Hands-Minimized Weather Interfaces (EHMI) for pilots.

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Mary E. Johnson Ph.D. Purdue University at West Lafayette (PPI) orcid.org/0000-0002-6572-0979

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Mary E. Johnson is a Professor and Associate Head for Graduate Studies and Research in the School of Aviation and Transportation Technology (SATT) at Purdue University in West Lafayette, Indiana. She earned her BS, MS and PhD in Industrial Engineering from UTArlington

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Abstract

Aircraft taxi operations at airports affect fuel consumption, operation efficiency, and emissions. Taxi operations refer to the aircraft movement on airport ground movement area. Understanding taxi operation patterns may potentially improve airport capacity and reduce fuel burn and aircraft emission. Student use of queuing theory and statistical analysis to answer questions is a common objective in many engineering and technology courses from several disciplines such as industrial engineering, mathematics, operations research, aviation management, and information systems, among others.

In this paper, the researchers use ARENA® to build a dynamic, stochastic, discrete-event simulation model of aircraft taxi operations at an airport with two intersecting runways. The simulation model is based on a fictional airport inspired by the layout of William P. Hobby Airport (HOU), Houston, TX. Take-off operations in the simulation model are generated from the airport operation data collected from the FAA Aviation System Performance Metrics (ASPM) dataset by determining the distribution and frequency of departure flights at HOU. In this study, the researchers develop and run a simulation model to measure aircraft taxi-out times 1) at two different numbers of take-off operations per hour, and 2) using either one runway or two. Deconfliction of runway and taxiway use are kept to one set of rules for all simulation runs. The research question answered by the model is: What difference does it make on taxi-out time when there are two different take-off rates and use of either one runway or two runways?

Learning airport taxi operation patterns may help researchers to make better predictions about airport operations. Airport engineers and managers may use similar models to better improve airport total capacity, and reduce congestion and emissions. Engineering educators may use this paper for classes with projects that involve data collection, data consolidation, and simulation analysis. Using ARENA® to build simulation models provides students with graphical and statistical outputs that may be used to enhance achievement of learning objectives. This research may also be useful for undergraduate and graduate students to better understand queuing theory using an example of airport operation and airport design.

Citation
Format

Wang, J., & Gupta, S., & Johnson, M. E. (2024, March), A Preliminary Study of Taxi-out Times Using Discrete-Event Simulation of an Airport with Intersecting Runways Paper presented at 2024 ASEE North Central Section Conference, Kalamazoo, Michigan. 10.18260/1-2--45591

TY - CPAPER
AB - Aircraft taxi operations at airports affect fuel consumption, operation efficiency, and emissions. Taxi operations refer to the aircraft movement on airport ground movement area. Understanding taxi operation patterns may potentially improve airport capacity and reduce fuel burn and aircraft emission. Student use of queuing theory and statistical analysis to answer questions is a common objective in many engineering and technology courses from several disciplines such as industrial engineering, mathematics, operations research, aviation management, and information systems, among others.

In this paper, the researchers use ARENA® to build a dynamic, stochastic, discrete-event simulation model of aircraft taxi operations at an airport with two intersecting runways. The simulation model is based on a fictional airport inspired by the layout of William P. Hobby Airport (HOU), Houston, TX. Take-off operations in the simulation model are generated from the airport operation data collected from the FAA Aviation System Performance Metrics (ASPM) dataset by determining the distribution and frequency of departure flights at HOU. In this study, the researchers develop and run a simulation model to measure aircraft taxi-out times 1) at two different numbers of take-off operations per hour, and 2) using either one runway or two. Deconfliction of runway and taxiway use are kept to one set of rules for all simulation runs. The research question answered by the model is: What difference does it make on taxi-out time when there are two different take-off rates and use of either one runway or two runways?

Learning airport taxi operation patterns may help researchers to make better predictions about airport operations. Airport engineers and managers may use similar models to better improve airport total capacity, and reduce congestion and emissions. Engineering educators may use this paper for classes with projects that involve data collection, data consolidation, and simulation analysis. Using ARENA® to build simulation models provides students with graphical and statistical outputs that may be used to enhance achievement of learning objectives. This research may also be useful for undergraduate and graduate students to better understand queuing theory using an example of airport operation and airport design.

AU - Jiansen Wang
AU - Shantanu Gupta
AU - Mary E. Johnson Ph.D.
CY - Kalamazoo, Michigan
DA - 2024/03/22
PB - ASEE Conferences
TI - A Preliminary Study of Taxi-out Times Using Discrete-Event Simulation of an Airport with Intersecting Runways
UR - https://peer.asee.org/45591
DO - 10.18260/1-2--45591
ER -