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dc.contributor.authorOlbert, Agnieszka Indiana
dc.contributor.authorNash, Stephen
dc.contributor.authorHartnett, Michael
dc.identifier.citationOlbert AI, Nash S, Ragnoli E, Hartnett M (2014) Parameterization of turbulence models using 3DVAR data 11th International Conference on Hydroinformaticsen_IE
dc.descriptionConference paperen_IE
dc.description.abstractIn this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ε model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ε model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. 3DVAR allows also to identify and quantify shortcomings of the numerical model. Such comprehensive analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows.en_IE
dc.description.sponsorshipIRCSET / IBM Enterprise Partnership Scheme (EPSPD/2011/231)en_IE
dc.publisherCity University of New Yorken_IE
dc.relation.ispartof11th International Conference on Hydroinformaticsen
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland
dc.subject3DVAR data assimilationen_IE
dc.subjectTurbulence modellingen_IE
dc.titleParameterization of turbulence models using 3DVAR dataen_IE
dc.typeConference Paperen_IE
dc.local.contactAgnieszka Indiana Olbert, Civil Engineering, Neb Room 2030, Nui Galway. 3208 Email:

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