Emerging Researchers National (ERN) Conference

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Large-eddy Simulations of Tidally-driven Turbulent Flows in Shallow Continental Shelf

Undergraduate #241
Discipline: Mathematics and Statistics
Subcategory: Civil/Mechanical/Manufacturing Engineering

Jakobi Peets - University of the Virgin Islands
Co-Author(s): Mario Juha and Andres E. Tejada-Martinez, University of South Florida


Computational fluid dynamics was utilized in this research project to conduct preliminary simulations that will eventually help improve models to track the path of oil or other spilled material in coastal regions, such as the recent Deepwater Horizon Spill in the Gulf of Mexico. These preliminary simulations consist of tidal boundary layer flows with surface cooling in order to identify instances during the tidal cycle when conditions become favorable for the development of full-depth convective cells; which lead to turbulent vertical mixing throughout the full-depth of the water column. These simulations are characteristic of shallow continental shelf regions between 10 and 30 meters deep. In the planned simulations, turbulent vertical mixing is caused by surface cooling and the tidally-driven vertical shear in the boundary layer flow. Tidal forcing in conjunction with surface cooling can lead to full-depth convective turbulent structures which homogenize momentum and scalars throughout the water column and thus strongly impact the distribution of spilled material such as oil particles. Furthermore, vertical mixing throughout the full depth of the water column can play an important role in the re-suspension of sediments and subsequent oil sedimentation. The work will contribute towards understanding the wind, wave, tidal and surface buoyancy forcing conditions leading to full-depth mixing of the water column on the continental shelf.

Funder Acknowledgement(s): This material is based upon work supported by the National Science Foundation under Grant No. EEC- 1156905.

Faculty Advisor: Andres E. Tejada-Martinez,

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.