Airport Cargo Handling after a Natural Disaster Event: Modelling and Analysis of Airport Cargo Handling after a Natural Disaster Event
The severity of natural disasters is increasing every year, having an impact on many people's lives. During the response phase of disasters, airports are important hubs where relief aid arrives while people need to be evacuated out of there. However, the airport often forms a bottleneck in thes...
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Other Authors: | , |
Format: | Master Thesis |
Language: | English |
Published: |
2022
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Online Access: | http://resolver.tudelft.nl/uuid:a7b54080-ffda-461c-8283-5f26f5e05326 |
_version_ | 1821579807439192064 |
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author | Van de Sype, Luka (author) |
author2 | Sharpanskykh, Alexei (mentor) Delft University of Technology (degree granting institution) |
author_facet | Van de Sype, Luka (author) |
author_sort | Van de Sype, Luka (author) |
collection | Delft University of Technology: Institutional Repository |
description | The severity of natural disasters is increasing every year, having an impact on many people's lives. During the response phase of disasters, airports are important hubs where relief aid arrives while people need to be evacuated out of there. However, the airport often forms a bottleneck in these relief operations, because of the sudden need for increased capacity. Limited research is done on the operational side of airport disaster management. Experts identify the main problems as lack of information on all incoming flights and the lack of resources. The goal of this research is to gain understanding of the effects of incomplete knowledge of incoming flights with different resource allocation strategies, on the performance of the cargo handling operations in an airport after a natural disaster event. To answer the research question, the following approach is taken: first, a better understanding of the existing model developed by van Liere for a relevant case study is provided. Secondly, a base model is created based on van Liere's model. In this model, realistic offloading strategies with different degrees of information uncertainty are implemented in the base model. The data required for the model and the generated outputs were validated by interviews with experts in the field. The model performance is measured by the average turn-around time, which can be split in offloading time, boarding time and the cumulative waiting times. The results show that the effects of one unannounced aircraft are negligible. However, all waiting times increase the more aircraft arrive unannounced. %The effects of anticipation are negligible Aerospace Engineering |
format | Master Thesis |
genre | Martin Island |
genre_facet | Martin Island |
geographic | Martin Island |
geographic_facet | Martin Island |
id | fttudelft:oai:tudelft.nl:uuid:a7b54080-ffda-461c-8283-5f26f5e05326 |
institution | Open Polar |
language | English |
long_lat | ENVELOPE(56.967,56.967,-66.733,-66.733) |
op_collection_id | fttudelft |
op_relation | http://resolver.tudelft.nl/uuid:a7b54080-ffda-461c-8283-5f26f5e05326 |
op_rights | © 2022 Luka Van de Sype |
publishDate | 2022 |
record_format | openpolar |
spelling | fttudelft:oai:tudelft.nl:uuid:a7b54080-ffda-461c-8283-5f26f5e05326 2025-01-16T23:03:03+00:00 Airport Cargo Handling after a Natural Disaster Event: Modelling and Analysis of Airport Cargo Handling after a Natural Disaster Event Van de Sype, Luka (author) Sharpanskykh, Alexei (mentor) Delft University of Technology (degree granting institution) 2022-04-28 http://resolver.tudelft.nl/uuid:a7b54080-ffda-461c-8283-5f26f5e05326 en eng http://resolver.tudelft.nl/uuid:a7b54080-ffda-461c-8283-5f26f5e05326 © 2022 Luka Van de Sype Agent-Based Modeling Python MESA Airport Cargo Handling Evacuation Operations Airport Disaster Management Disaster Resilience Princess Juliana International Airport Saint Martin Island master thesis 2022 fttudelft 2023-07-08T20:44:13Z The severity of natural disasters is increasing every year, having an impact on many people's lives. During the response phase of disasters, airports are important hubs where relief aid arrives while people need to be evacuated out of there. However, the airport often forms a bottleneck in these relief operations, because of the sudden need for increased capacity. Limited research is done on the operational side of airport disaster management. Experts identify the main problems as lack of information on all incoming flights and the lack of resources. The goal of this research is to gain understanding of the effects of incomplete knowledge of incoming flights with different resource allocation strategies, on the performance of the cargo handling operations in an airport after a natural disaster event. To answer the research question, the following approach is taken: first, a better understanding of the existing model developed by van Liere for a relevant case study is provided. Secondly, a base model is created based on van Liere's model. In this model, realistic offloading strategies with different degrees of information uncertainty are implemented in the base model. The data required for the model and the generated outputs were validated by interviews with experts in the field. The model performance is measured by the average turn-around time, which can be split in offloading time, boarding time and the cumulative waiting times. The results show that the effects of one unannounced aircraft are negligible. However, all waiting times increase the more aircraft arrive unannounced. %The effects of anticipation are negligible Aerospace Engineering Master Thesis Martin Island Delft University of Technology: Institutional Repository Martin Island ENVELOPE(56.967,56.967,-66.733,-66.733) |
spellingShingle | Agent-Based Modeling Python MESA Airport Cargo Handling Evacuation Operations Airport Disaster Management Disaster Resilience Princess Juliana International Airport Saint Martin Island Van de Sype, Luka (author) Airport Cargo Handling after a Natural Disaster Event: Modelling and Analysis of Airport Cargo Handling after a Natural Disaster Event |
title | Airport Cargo Handling after a Natural Disaster Event: Modelling and Analysis of Airport Cargo Handling after a Natural Disaster Event |
title_full | Airport Cargo Handling after a Natural Disaster Event: Modelling and Analysis of Airport Cargo Handling after a Natural Disaster Event |
title_fullStr | Airport Cargo Handling after a Natural Disaster Event: Modelling and Analysis of Airport Cargo Handling after a Natural Disaster Event |
title_full_unstemmed | Airport Cargo Handling after a Natural Disaster Event: Modelling and Analysis of Airport Cargo Handling after a Natural Disaster Event |
title_short | Airport Cargo Handling after a Natural Disaster Event: Modelling and Analysis of Airport Cargo Handling after a Natural Disaster Event |
title_sort | airport cargo handling after a natural disaster event: modelling and analysis of airport cargo handling after a natural disaster event |
topic | Agent-Based Modeling Python MESA Airport Cargo Handling Evacuation Operations Airport Disaster Management Disaster Resilience Princess Juliana International Airport Saint Martin Island |
topic_facet | Agent-Based Modeling Python MESA Airport Cargo Handling Evacuation Operations Airport Disaster Management Disaster Resilience Princess Juliana International Airport Saint Martin Island |
url | http://resolver.tudelft.nl/uuid:a7b54080-ffda-461c-8283-5f26f5e05326 |