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A platform for research: civil engineering, architecture and urbanism
A spatiotemporal passenger distribution model for airport terminal energy simulation
https://orcid.org/0000-0003-0187-5194
Airport terminals provide a safe, convenient and comfortable environment for passengers. Over 50% of energy in terminals was consumed by the HVAC system. The number of passengers and their constant flow distribution in the airport is an important consideration from the operational perspective to influence the energy consumption. This paper proposed a spatiotemporal passenger distribution model. In this model, a terminal was divided into 13 different zones along the departure or arrival process, and the passenger variation for each day was described for each zone. Over a year, 12 monthly average passenger flow values were adopted instead of the peak hour passenger flow to represent the yearly passenger flow distribution. The model was validated by the operation data of the Nanning Airport and compared the data against the validated people movement model of passengers’ flow profile in each zone and occupant densities. The model was then input into an energy simulation software to verify the impact of the passenger flow on energy consumption. Based on the spatiotemporal passenger distribution model, the annual cooling consumption could be reduced by 17.14% compared to results based on the traditional passenger flow calculation method which has a simple assumption of daily constant passenger flow.
A spatiotemporal passenger distribution model for airport terminal energy simulation
https://orcid.org/0000-0003-0187-5194
Airport terminals provide a safe, convenient and comfortable environment for passengers. Over 50% of energy in terminals was consumed by the HVAC system. The number of passengers and their constant flow distribution in the airport is an important consideration from the operational perspective to influence the energy consumption. This paper proposed a spatiotemporal passenger distribution model. In this model, a terminal was divided into 13 different zones along the departure or arrival process, and the passenger variation for each day was described for each zone. Over a year, 12 monthly average passenger flow values were adopted instead of the peak hour passenger flow to represent the yearly passenger flow distribution. The model was validated by the operation data of the Nanning Airport and compared the data against the validated people movement model of passengers’ flow profile in each zone and occupant densities. The model was then input into an energy simulation software to verify the impact of the passenger flow on energy consumption. Based on the spatiotemporal passenger distribution model, the annual cooling consumption could be reduced by 17.14% compared to results based on the traditional passenger flow calculation method which has a simple assumption of daily constant passenger flow.
A spatiotemporal passenger distribution model for airport terminal energy simulation
https://orcid.org/0000-0003-0187-5194
Airport terminals provide a safe, convenient and comfortable environment for passengers. Over 50% of energy in terminals was consumed by the HVAC system. The number of passengers and their constant flow distribution in the airport is an important consideration from the operational perspective to influence the energy consumption. This paper proposed a spatiotemporal passenger distribution model. In this model, a terminal was divided into 13 different zones along the departure or arrival process, and the passenger variation for each day was described for each zone. Over a year, 12 monthly average passenger flow values were adopted instead of the peak hour passenger flow to represent the yearly passenger flow distribution. The model was validated by the operation data of the Nanning Airport and compared the data against the validated people movement model of passengers’ flow profile in each zone and occupant densities. The model was then input into an energy simulation software to verify the impact of the passenger flow on energy consumption. Based on the spatiotemporal passenger distribution model, the annual cooling consumption could be reduced by 17.14% compared to results based on the traditional passenger flow calculation method which has a simple assumption of daily constant passenger flow.
A spatiotemporal passenger distribution model for airport terminal energy simulation
Gu, Xianliang (author) / Xie, Jingchao (author) / Huang, Chengyang (author) / Liu, Jiaping (author)
Indoor and Built Environment ; 31 ; 1834-1857
2022-08-01
24 pages
Article (Journal)
Electronic Resource
English
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