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| Tekkaya, A. Erman |
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| Förster, Peter |
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| Mudimu, George T. |
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| Shibata, Lillian Marie |
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| Talabbeydokhti, Nasser |
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| Laffite, Ernesto Dante Rodriguez |
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| Schöpke, Benito |
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| Gobis, Anna |
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| Alfares, Hesham K. |
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| Münzel, Thomas |
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| Joy, Gemini Velleringatt |
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| Oubahman, Laila |
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| Filali, Youssef |
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| Philippi, Paula |
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| George, Alinda |
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| Lucia, Caterina De |
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| Avril, Ludovic |
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| Belachew, Zigyalew Gashaw |
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| Kassens-Noor, Eva | Darmstadt |
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| Cho, Seongchul |
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| Tonne, Cathryn |
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| Hosseinlou, Farhad |
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| Ganvit, Harsh |
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| Schmitt, Konrad Erich Kork |
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| Grimm, Daniel |
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Ratei, Patrick
in Cooperation with on an Cooperation-Score of 37%
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Publications (18/18 displayed)
- 2024Can Urban Air Mobility become reality? Opportunities and challenges of UAM as innovative mode of transport and DLR contribution to ongoing researchcitations
- 2023System of Systems Explorations of Urban Air Mobility Aircraft Design and Operations: An Overview of the Conceptual Vehicle Design Approach in HorizonUAM
- 2023An Overview of the Collaborative Systems of Systems Simulation of Urban Air Mobility
- 2022DLR Design Challenge 2022: Design of a next generation VTOL firefighting aircraft
- 2022A Collaborative Systems of Systems Simulation of Urban Air Mobility: Architecture Process and Demonstration of Capabilities
- 2022Development of a Vertical Take-Off and Landing Aircraft Design Tool for the Application in a System of Systems Simulation Framework
- 2022Development of an Urban Air Mobility Vehicle Family Concept by System of Systems Aircraft Design and Assessmentcitations
- 2022Modelling and simulation of Urban Air Mobility: an extendable approach
- 2022Simulation of Urban Air Mobility: progress from the HorizonUAM Project
- 2022System of Systems driven fleet design for Urban Air Mobility: heterogeneity over homogeneity?
- 2022DLR Design Challenge 2022 on Advanced Aerial Firefighting
- 2021UAM Aircraft Design, Technology Integration and Fleet Evaluation Using a System of Systems Framework
- 2021Conceptual Aircraft Design and Comparison of Different eVTOL Aircraft for Urban Air Mobility
- 2021System of Systems Simulation Driven Wildfire Fighting Aircraft Design and Fleet Assessmentcitations
- 2021Exploration of Aerial Firefighting Fleet Effectiveness and Cost by System of Systems Simulations
- 2021System of Systems Simulation driven Urban Air Mobility Vehicle Design and Fleet Assessmentcitations
- 2021Aircraft Architecture and Fleet Assessment Framework for Urban Air Mobility using a System of Systems Approachcitations
- 2021Sensitivity Analysis of Urban Air Mobility Aircraft Design and Operations Including Battery Charging and Swapping
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conferencepaper
System of Systems driven fleet design for Urban Air Mobility: heterogeneity over homogeneity?
Abstract
Urban Air Mobility (UAM) represents a new paradigm in aviation involving high intensity short distance air travel using low capacity vertical take-off and landing aircraft. As this new paradigm necessitates a departure from many traditional aspects of the existing air transportation system, a large body of research is necessary to better understand the novel requirements and how they can be served by different technologies. These aspects include but are not limited to airspace management, vertiport design and management, aircraft design with innovative subsystem technologies, etc. A wide range of operational scenarios is envisioned for UAM involving different ranges, tempos of operations, and expected demand. This translates to a suite of different vehicles being developed by the industry with different architecture and top-level requirements. The aim of this work is to evaluate the need for heterogenous fleets to suit the different operational scenarios envisioned for UAM. Two optimized aircraft concepts, a multirotor and a tiltrotor concept, derived from a system of systems driven aircraft design approach is first evaluated in a homogenous fleet, and then in a heterogenous fleet with varying degrees of heterogeneity. The ideal mix of heterogeneity is identified for a given setup considering economic and ecological efficiency from which generalizations are drawn. For this evaluation, a nominal use case is setup to represent a mixed operational scenario of intra-city and suburban scenarios. The fleets are evaluated against Measures of Effectiveness (MoEs) including passenger throughput, share of received requests that were served, wait time of passengers, deadhead ratio, load factor, and total energy consumption of the network. These MoEs are obtained using an agent-based simulation of UAM system of systems.
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