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NAERINGSPH-Nærings-phd

Prediction of aircraft icing based on the microphysical properties of condensed water vapour outside mixed-phased clouds

Alternative title: Prediction of aircraft icing based on the microphysical properties of condensed water vapour outside mixed-phased clouds

Awarded: NOK 1.8 mill.

Project Number:

322161

Application Type:

Project Period:

2021 - 2023

Funding received from:

Prediction of aircraft icing based on the microphysical properties of condensed water vapour outside mixed-phased clouds The goal of this project is research supporting the development of a sensor package for unmanned aerial vehicles (UAVs) that predicts icing conditions during flight. Icing on aircrafts occur when supercooled droplets in clouds or fog strike the surface of the aircraft and freeze almost instantaneously. This presents a hazard to aviation, as icing affects the aerodynamics and weight of the aircraft. For small UAVs, where conventional anti-icing or de-icing solutions are not possible, the hazard is exacerbated as even small amounts of accreted ice can be potentially catastrophic. To predict icing, knowledge of the microphysical processes governing cloud formation is needed, especially those occurring in mixed-phase clouds. Mixed-phase clouds are clouds containing both liquid water and ice. Scientific measurements of parameters relevant for icing are also needed and will be collected and analysed. This will serve as the foundation for models describing the chance of encountering supercooled droplets along the current flight trajectory. In addition, sensors measuring relevant variables at high frequency while airborne will be developed. In particular, measuring relative humidity accurately and frequently poses a challenge. The result of this project will be a sensor package that monitors the environment in real time during flight, and continuously evaluates the danger of icing. The present work focusses on the software part of the sensor package, where fundamental atmopheric parameters, together with basic knowledge of cloud microphysics are used to predict icing conditions. Being able to predict where icing might occur permits safer operation of UAVs in challenging weather conditions. Feedback to the operator will be color-coded and easy to understand ? green means no danger, yellow that evasive action may soon be required, and red that immediate evasive action must be taken.

Kommersiell bruk av droner innen landbruk, anleggsarbeid, transport og kommunikasjon er under sterk vekst i hele verden. Veksten medfører nødvendighet for å operere droner året rundt, også under vanskelige værforhold. Sterk nedbør og sterk vind legger åpenbare begrensninger på droneoperasjon. På vinteren er ising en trussel for sikker operasjon. Droner, som opereres BLOS («beyond-line-of-sight») eller autonomt, kan uten forvarsel havne f.eks. i underkjølt tåke eller underkjølte skyer. Noe som kan føre til at piloten mister kontroll over farkosten innenfor få sekunder, og utstyr og frakt blir skadet. I verste fall kan tredjeparter bli skadelidende. En sensorpakke, som vi kaller «IceWarn» har som målsetting å redusere denne faren ved å gi piloten eller droneoperatøren et varsel før fartøyet kommer i slike forhold. Å evaluere faren for ising før isingen begynner behøver omfattende kunnskap om prosesser mellom is og vannpartikler inni og utenfor skyer og deres mikrofysikalske sammenheng. Prosjektet skal bidra til å øke forståelsen for samspillet mellom is og vannpartikler, samt utvikling og kvalitetstesting av sensoren «IceWarn», som skal gi tryggere flyging under vanskelige forhold for operatører og piloter.

Activity:

NAERINGSPH-Nærings-phd