Redirigiendo al acceso original de articulo en 19 segundos...
Inicio  /  Aerospace  /  Vol: 8 Par: 12 (2021)  /  Artículo
ARTÍCULO
TITULO

A System Dynamics Prediction Model of Airport Environmental Carrying Capacity: Airport Development Mode Planning and Case Study

Qiuping Peng    
Lili Wan    
Tianci Zhang    
Zhan Wang and Yong Tian    

Resumen

Airport environmental carrying capacity (AECC) provides the fundamental conditions for airport development and operation activities. The prediction of AECC is a necessary condition for planning an appropriate development mode for the airport. This paper studies the dynamic prediction method of the AECC to explore the development characteristics of AECC in different airports. Based on the driving force-pressure-state-response (DPSR) framework, the method selects 17 main variables from economic, social, environmental and operational dimensions, and then combines the drawing of causal loop diagrams and the establishment of system flow diagrams to construct the system dynamics (SD) model of AECC. The predicted values of AECC are obtained through SD model simulation and accelerated genetic algorithm projection pursuit (AGA-PP) model calculation. Considering sustainable development needs, different scenarios are set to analyze the appropriate development mode of the airport. The case study of the Pearl River Delta airports resulted in two main conclusions. First, in the same economic zone, different airports with similar aircraft movements have similar development characteristics of AECC. Second, the appropriate development modes for different airports are different, and the appropriate development modes for the airport in different periods are also different. The case study also proves that the AECC prediction based on SD model and AGA-PP model can realize short-term policy formulation and long-term planning for the airport development mode, and provide decision-making support for relevant departments of airport.

 Artículos similares

       
 
Wen Tian, Xuefang Zhou, Jianan Yin, Yuchen Li and Yining Zhang    
The complex layout of the airport surface, coupled with interrelated vehicle behaviors and densely mixed traffic flows, frequently leads to operational conflict risks. To address this issue, research was conducted on the recognition of characteristics an... ver más
Revista: Aerospace

 
Chang-Ming Liaw, Chen-Wei Yang and Pin-Hong Jhou    
This paper presents the development of an airport bipolar DC microgrid and its interconnected operations with the utility grid, electric vehicle (EV), and more electric aircraft (MEA). The microgrid DC-bus voltage is established by the main sources, phot... ver más
Revista: Aerospace

 
Marco-Michael Temme, Olga Gluchshenko, Lennard Nöhren, Matthias Kleinert, Oliver Ohneiser, Kathleen Muth, Heiko Ehr, Niklas Groß, Annette Temme, Martina Lagasio, Massimo Milelli, Vincenzo Mazzarella, Antonio Parodi, Eugenio Realini, Stefano Federico, Rosa Claudia Torcasio, Markus Kerschbaum, Laura Esbrí, Maria Carmen Llasat, Tomeu Rigo and Riccardo Biondiadd Show full author list remove Hide full author list    
In the H2020 project ?Satellite-borne and INsitu Observations to Predict The Initiation of Convection for ATM? (SINOPTICA), an air traffic controller support system was extended to organize approaching traffic even under severe weather conditions. During... ver más
Revista: Aerospace

 
Silvia Carpitella, Bruno Brentan, Antonella Certa and Joaquín Izquierdo    
This paper introduces a recommendation system aimed at enhancing the sustainable process of risk management within airport operations, with a special focus on Occupational Stress Risks (OSRs). The recommendation system is implemented via a flexible Pytho... ver más
Revista: Algorithms

 
Matthias Kleinert, Oliver Ohneiser, Hartmut Helmke, Shruthi Shetty, Heiko Ehr, Mathias Maier, Susanne Schacht and Hanno Wiese    
The information air traffic controllers (ATCos) communicate via radio telephony is valuable for digital assistants to provide additional safety. Yet, ATCos have to enter this information manually. Assistant-based speech recognition (ABSR) has proven to b... ver más
Revista: Aerospace