Weight optimization of hydrogen storage vessels for quadcopter UAV using genetic algorithm

Lee, Youngheon; Park, Eu-Tteum; Jeong, Jinseok; Shi, Ha-Young; Kim, Jeong; Kang, Beom-Soo; Song, Woo‐Jin

doi:10.1016/j.ijhydene.2020.09.014

“…using the approach proposed by Angel et al 28 for geometric rectification of UAV image data. The ability to collect near-continuous data from a hovering UAV is restricted by the battery life, which is generally limited to 20–60 min for most quadcopters, although new hydrogen fuel cells for UAVs have extended hovering times to over 2 h 29 . To overcome the limitations of battery capacity, tethering of UAVs via an attached power line is a potential solution for extending hovering capabilities in future studies 30 .…”

Section: Discussionmentioning

confidence: 99%

Dye tracing and concentration mapping in coastal waters using unmanned aerial vehicles

Johansen

¹

,

Dunne

²

,

Tu

³

et al. 2022

Sci Rep

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Coastal water flows facilitate important nutrient exchanges between mangroves, seagrasses and coral reefs. However, due to the complex nature of tidal interactions, their spatiotemporal development can be difficult to trace via traditional field instrumentations. Unmanned aerial vehicles (UAVs) serve as ideal platforms from which to capture such dynamic responses. Here, we provide a UAV-based approach for tracing coastal water flows using object-based detection of dye plume extent coupled with a regression approach for mapping dye concentration. From hovering UAV images and nine subsequent flight surveys covering the duration of an ebbing tide in the Red Sea, our results show that dye plume extent can be mapped with low omission and commission errors when assessed against manual delineations. Our results also demonstrated that the interaction term of two UAV-derived indices may be employed to accurately map dye concentration (coefficient of determination = 0.96, root mean square error = 7.78 ppb), providing insights into vertical and horizontal transportation and dilution of materials in the water column. We showcase the capabilities of high-frequency UAV-derived data and demonstrate how field-based dye concentration measurements can be integrated with UAV data for future studies of coastal water flow dynamics.

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“…using the approach proposed by Angel et al [26] for geometric recti cation of UAV image data. The ability to collect near continuous data from a hovering UAV is restricted by the battery life, which is generally limited to 20-60 min for most quadcopters, although new hydrogen fuel cells for UAVs have extended hovering times to over 2 hours [27]. To overcome the limitations of battery capacity, tethering of UAVs via an attached power line is a potential solution for extending hovering capabilities in future studies [28].…”

Section: Discussionmentioning

confidence: 99%

Dye Tracing and Concentration Mapping in Coastal Waters Using Unmanned Aerial Vehicles

Johansen

¹

,

Dunne

²

,

Tu

³

et al. 2021

Preprint

0

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Coastal water flows facilitate important nutrient exchanges between mangroves, seagrasses and coral reefs. However, due to the complex nature of tidal interactions, their spatiotemporal development can be difficult to trace via traditional field instrumentations. Unmanned aerial vehicles (UAVs) serve as ideal platforms from which to capture such dynamic responses. Here, we provide a UAV-based approach for tracing coastal water flows using object-based detection of dye plume extent coupled with a regression approach for mapping dye concentration. From hovering UAV images and nine subsequent flight surveys covering the duration of an ebbing tide in the Red Sea, our results show that dye plume extent can be mapped with low omission and commission errors when assessed against manual delineations. Our results also demonstrated that the interaction term of two UAV-derived indices may be employed to accurately map dye concentration (coefficient of determination = 0.96, root mean square error = 7.78 ppb), providing insights into vertical and horizontal transportation and dilution of materials in the water column. We showcase the capabilities of high-frequency UAV-derived data and demonstrate how field-based dye concentration measurements can be integrated with UAV data for future studies of coastal water flow dynamics.

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“…The comparison of this method to that performed by Roh [93] indicated that the two methods reduced the weight of Type IV cylinders by 9.8 and 11.2%, respectively. Lee et al [95] optimized the winding layer and winding angle of Type IV cylinders based on the genetic algorithm, and this reduced the weight of hydrogen cylinders by 23.79%, thus increasing the hovering time of a quadrotor drone with a 650 W fuel cell by 17.73%, which is 37.85% longer than the hovering time of the battery-powered drone with the same power.…”

Section: High-pressure Gas Cylinders and Hydrogen Regulatorsmentioning

confidence: 99%

A Review on Key Technologies and Developments of Hydrogen Fuel Cell Multi-rotor Drones

Shen,

Liu,

Zhu

et al. 2024

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0

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Multi-rotor drones, a kind of unmanned equipment which is widely used in military, commercial consumption and other fields, has been developed very rapidly in recent years. However, their short flight time has hindered the expansion of their application range. This can be addressed by utilizing hydrogen fuel cells, which exhibit high energy density, strong adaptability to ambient temperature, and no pollution emissions, as the power source. Accordingly, the application of hydrogen fuel cells as the power source in multi-rotor drones is a promising technology that has attracted significant research attention. This paper summarizes the development process of hydrogen fuel cell mul-ti-rotor drones and analyzes the key obstacles that need to be addressed for the further development of hydrogen fuel cell multi-rotor drones, including structural lightweight, hydrogen storage methods, energy management strategies. Additionally, prospects for the future development of hydrogen fuel cell multi-rotor drones are presented.

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Weight optimization of hydrogen storage vessels for quadcopter UAV using genetic algorithm

Cited by 19 publications

References 18 publications

Dye tracing and concentration mapping in coastal waters using unmanned aerial vehicles

Dye tracing and concentration mapping in coastal waters using unmanned aerial vehicles

Dye Tracing and Concentration Mapping in Coastal Waters Using Unmanned Aerial Vehicles

A Review on Key Technologies and Developments of Hydrogen Fuel Cell Multi-rotor Drones

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