Version 1
: Received: 27 June 2023 / Approved: 27 June 2023 / Online: 27 June 2023 (14:28:16 CEST)
How to cite:
Zhang, L.; Yang, Z.; Mou, Q. A Methodology for Assessing Airport Terminal Capacity Based on Service Resource Equilibrium. Preprints2023, 2023061926. https://doi.org/10.20944/preprints202306.1926.v1
Zhang, L.; Yang, Z.; Mou, Q. A Methodology for Assessing Airport Terminal Capacity Based on Service Resource Equilibrium. Preprints 2023, 2023061926. https://doi.org/10.20944/preprints202306.1926.v1
Zhang, L.; Yang, Z.; Mou, Q. A Methodology for Assessing Airport Terminal Capacity Based on Service Resource Equilibrium. Preprints2023, 2023061926. https://doi.org/10.20944/preprints202306.1926.v1
APA Style
Zhang, L., Yang, Z., & Mou, Q. (2023). A Methodology for Assessing Airport Terminal Capacity Based on Service Resource Equilibrium. Preprints. https://doi.org/10.20944/preprints202306.1926.v1
Chicago/Turabian Style
Zhang, L., Ze Yang and Qifeng Mou. 2023 "A Methodology for Assessing Airport Terminal Capacity Based on Service Resource Equilibrium" Preprints. https://doi.org/10.20944/preprints202306.1926.v1
Abstract
To effectively estimate airport terminal area capacity and assess the maximum throughput the sector can achieve when the capacity is given, this research proposes an approach to assess the terminal area capacity from the viewpoint of service provision resources. Terminal area capacity is optimized based on the equilibrium of air traffic service resource supply and demand. The supply-demand nexus is examined in consideration of terminal area route structure, traffic flow characteristics, and safety regulations. A flight service probability matrix and a terminal area demand and supply service time model are constructed to quantify resource expenditure at varied capacity levels. A optimization model is then developed to apportion maximal capacity under resource limitations. Model computation and computation results demonstrate the deviation between estimated and amended capacities is under 0.3 flight sorties per hour. The outcomes are congruent with historical statistics, thereby validating the accuracy and reliability of the model proposed in this study. Given capacity parameters, the model can deduce the maximal aircraft quantity served concurrently in terminal areas during peak periods. These revelations indicate the submitted model furnishes theoretical foundation and reference for terminal area sector partition and traffic alerting.
Keywords
Airport capacity management; Service resource allocation; Monte Carlo simulation; Mathematical modeling
Subject
Engineering, Transportation Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
