Sujay Rajendra Deshpande disputerer for ph.d.-graden i ingeniørvitenskap og vil offentlig forsvare avhandlingen / Sujay Rajendra Deshpande will defend his thesis for the PhD degree in Engineering Science:
“Sea Spray Icing Prediction: Integrating Experiments, Machine Learning, and Computational Fluid Dynamics”.
Sujay Rajendra Deshpande disputerer for ph.d.-graden i ingeniørvitenskap og vil offentlig forsvare avhandlingen / Sujay Rajendra Deshpande will defend his thesis for the PhD degree in Engineering Science:
“Sea Spray Icing Prediction: Integrating Experiments, Machine Learning, and Computational Fluid Dynamics”.
Avhandlingen er tilgjengelig (lenke kommer) / The doctoral thesis is available (link is coming soon).
Auditoriet er åpent for publikum. Disputasen vil også bli strømmet. Opptak av disputasen vil være tilgjengelig i en måned.
The auditorium is open to the public. The defense will be streamed. A recording of the defense will be available for one month.
Prøveforelesningen starter kl. 10:15 / The trial lecture starts at 10:15. Tittel / title:
“Uncertainty in laboratory and field measurements. How it can be assessed and how it should be taken into account”.
Disputasen starter kl. 12:15 / The defense starts at 12:15.
Prøveforelesning strømmes her, disputas strømmes her. / The trial lecture will be streamed here, and defense will be streamed here.
Sammendrag av avhandlingen / Summary of the thesis:
The study proposes a hybrid Computational Fluid Dynamics - Machine Learning model for prediction of icing rates due to freezing sea spray, ‘SPICE’. When a wave impacts a ship or a structure, a spray of tiny sea water droplets is formed. In negative temperatures, these droplets freeze upon impact on the surface of a vessel or structure. Freezing sea spray accounts for 80-90% of all offshore icing incidents. In severe conditions, lopsided icing loads can lead to structural failure or capsizing. Prediction of sea spray icing helps in mitigating its dangers by allowing to take precautionary measures and for design optimization. SPICE is capable of predicting icing rates and the spatial distribution of icing on the surface of structures and any arbitrary moving vessel.
Veiledere / Supervisors:
Hovedveileder / Main supervisor:
Professor Per-Arne Sundsbø, Department of Building, Energy and Material Technology, UiT The Arctic University of Norway,
Biveileder / Co-supervisor:
Professor Ove Tobias Gudmestad, Department of Technology and Safety, UiT The Arctic University of Norway.
Bedømmelseskomité / Evaluation committee:
Prøveforelesning og disputas ledes av prodekan for forskning, Svein-Erik Sveen /
The trial lecture and defense are led by Vice Dean of research, Svein-Erik Sveen.
De som ønsker å opponere ex auditorio kan sende e-post til Svein-Erik Sveen / Opponents ex auditorio should contact Svein-Erik Sveen.