Tesi etd-01272022-172751 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
RASPANTI, MATTEO
URN
etd-01272022-172751
Titolo
Definition of a STAR CCM+ CFD Method for the Analysis of Ventilating Surface-Piercing Cylinders
Dipartimento
INGEGNERIA CIVILE E INDUSTRIALE
Corso di studi
INGEGNERIA AEROSPAZIALE
Relatori
relatore Prof. Lombardi, Giovanni
correlatore Ing. Farnesi, Michele
correlatore Dott.ssa Ramirez, Catherine
correlatore Ing. Farnesi, Michele
correlatore Dott.ssa Ramirez, Catherine
Parole chiave
- cfd
- hydrodynamics
- multiphase
- sailboat
- star ccm +
- ventilation
Data inizio appello
15/02/2022
Consultabilità
Non consultabile
Data di rilascio
15/02/2092
Riassunto
The present work defines a CFD methodology to simulate the ventilation phenomenon which characterizes the hydrodynamics features of a semi-submerged body; in particular the work investigates how to simulate the phenomenon on a circular cylinder semi-submerged in water. Experimental results are used as a comparison and validation method for the numerical procedure, developed using the commercial software Siemens STAR CCM+.
This thesis is included in a collaboration between Syroco, a French company which wants to break the World Sailing Speed Record, the University of Pisa and the Fluid Dynamics Division of Cubit, which provides consulting, hardware resources and know-how to the project.
For all the simulations, a reference computational domain has been used. In the same way, all the cases simulated share the Menter’s SST k-ω turbulence model and use a VOF approach for free surface modelling.
Simulations have been carried along firstly using an unsteady RANS approach, for which the main method structure has been developed. In particular, the problem has been faced by simulating four different speeds of the relative flow and using different ratios of submergence of the cylinder.
Following the need to investigate the effect of turbulence modelling, an alternative approach has been proposed using DES turbulence formulation and observing its effects on one selected combination of speed and submergence ratio.
Results have shown that the proposed RANS methodology can simulate accurately the hydrodynamics forces on the other side, the model seems unable to correctly capture the ventilation depth that results in the experiments, especially in the cases with prevised full ventilation.
Conversely, the DES approach seems to correctly correlate with the experimental ventilation pocket depth. From a forces representation point of view, DES methodology well catches values observed during the experimental campaign but with a huge computational costs increase.
This thesis is included in a collaboration between Syroco, a French company which wants to break the World Sailing Speed Record, the University of Pisa and the Fluid Dynamics Division of Cubit, which provides consulting, hardware resources and know-how to the project.
For all the simulations, a reference computational domain has been used. In the same way, all the cases simulated share the Menter’s SST k-ω turbulence model and use a VOF approach for free surface modelling.
Simulations have been carried along firstly using an unsteady RANS approach, for which the main method structure has been developed. In particular, the problem has been faced by simulating four different speeds of the relative flow and using different ratios of submergence of the cylinder.
Following the need to investigate the effect of turbulence modelling, an alternative approach has been proposed using DES turbulence formulation and observing its effects on one selected combination of speed and submergence ratio.
Results have shown that the proposed RANS methodology can simulate accurately the hydrodynamics forces on the other side, the model seems unable to correctly capture the ventilation depth that results in the experiments, especially in the cases with prevised full ventilation.
Conversely, the DES approach seems to correctly correlate with the experimental ventilation pocket depth. From a forces representation point of view, DES methodology well catches values observed during the experimental campaign but with a huge computational costs increase.
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