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dc.contributor.authorGirdwood, J
dc.date.accessioned2023-12-11T12:17:55Z
dc.date.available2023-12-11T12:17:55Z
dc.date.issued2023-09-30
dc.identifier.urihttp://hdl.handle.net/2299/27277
dc.description.abstractAerosols and clouds are persistent causes of uncertainty in climate and weather models, which is due to their heterogeneous suspension and occurrence within the atmosphere, and complex interactions which are chaotic and exist on small scales. Unmanned aerial vehicles (UAVs) have grown in popularity, and are becoming more commonly used for general atmospheric measurement, particularly measurement of aerosols and clouds. This thesis presents and evaluates a synergy between two UAVs, a multi-rotor: the UH-AeroSAM octocopter and a fixed-wing: the FMI-Talon, and an optical particle instrument: the Universal Cloud and Aerosol Sounding System. Computational fluid dynamics with Lagrangian particle tracking (CFD-LPT) was used as a tool for the characterisation of the velocity fields and particle trajectories around both UAVs. In both instances CFD-LPT was used to develop an operational envelope, with particular attention to angle of attack constraints and size distribution perturbation, for the UAV – instrument synergy. UCASS was the first open path instrument to be used on a UAV, and a good case has been made for its continued use, particularly on fixed-wing UAVs, which exhibit less complex aerodynamics and superior stability in the induced sampling airflow through the instrument.en_US
dc.language.isoenen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subjectOPCen_US
dc.subjectUCASSen_US
dc.subjectUAVen_US
dc.subjectSUAen_US
dc.subjectOPC-N2en_US
dc.subjectOPC-N3en_US
dc.subjectOPC-N4en_US
dc.subjectRCASSen_US
dc.subjectUCASS-V2en_US
dc.subjectSuperSondeen_US
dc.subjectUH-AeroSAMen_US
dc.subjectRCASSen_US
dc.subjectFMI-Talonen_US
dc.titleOptical Measurement of Airborne Particles on Unmanned Aircraften_US
dc.typeinfo:eu-repo/semantics/doctoralThesisen_US
dc.identifier.doidoi:10.18745/th.27277*
dc.identifier.doi10.18745/th.27277
dc.type.qualificationlevelDoctoralen_US
dc.type.qualificationnamePhDen_US
dcterms.dateAccepted2023-09-30
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US
rioxxterms.versionNAen_US
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0/en_US
rioxxterms.licenseref.startdate2023-12-11
herts.preservation.rarelyaccessedtrue
rioxxterms.funder.projectba3b3abd-b137-4d1d-949a-23012ce7d7b9en_US


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