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Position TitleComputational Water Quality Modeling Internship
SummaryClimate change and increased demands for food and energy production place growing stresses on surface water resources. Predicting the impacts of these activities for water resources management requires sophisticated water quality models. The proposed internship will focus on development of a three dimensional water quality model that incorporates buoyant temperature effects from thermal pollution to assess the dynamics of fluid flow, heat transfer, and nutrients in surface water reservoirs.
Job DescriptionThe thermal characteristics of river systems play a critical role in both their natural ecological and economic functions. During extreme heat and drought periods, the capacity of rivers to assimilate pollutants is diminished, atmospheric heat loadings increase, and water quality is diminished. Warmer water increases rates of algal bloom formation, accelerates depletion of oxygen, and negatively affects fish populations. These changes are exacerbated in systems used for thermal power generation. Facilities that utilize once-through cooling may have water available but at temperatures that pose risks to receiving water bodies and/or exceed surface water permits. Advanced computational tools are needed to simulate the effects of thermal loadings to surface water resources, which affects the dynamics of oxygen and nutrients in reservoirs.

The proposed intern will construct a novel, three dimensional water quality model of Sooner Lake Reservoir, OK, which acts as a cooling pond for a power plant. The model will then be used to assess the impacts of thermal loadings on the reservoir's dynamics. The buoyancy effects of thermal loadings from a power plant will be simulated using a coupled system consisting of the incompressible Navier-Stokes Equations and the heat equation. The governing equations will be solved using the finite element method with the open-source SU2 code, which consists of a suite of modules written in C++ with extensions to the Python Programming Language. A suitable penalization scheme may be used to tackle the incompressibility condition. The numerical simulations will have to account for the complicated geometry of the reservoir and associated boundary conditions. Python has numerous extendible tools and is well-suited for integration of climate and model boundary conditions into the code. The intern will work with the mentor to learn how to use parallel computing for simulation of reservoir dynamics and Python to integrate the hydrographic and climate forcing data and postprocess simulation results.
Use of Blue WatersThe proposed simulations will involve substantial computing requirements and need to be performed on a suitable computational cluster. We will apply for an allocation on the Blue Waters supercomputer to develop the proposed model. The Oklahoma State University High Performance Computing Center Cluster is available for use for this research in the event that arrangements cannot be made on Blue Waters.
Conditions/QualificationsThe student should have completed a basic programming course and other coursework in a discipline relevant to water resources management (Civil, Agricultural, or Environmental Engineering, Environmental Science, or Geology). The student should have a minimum 3.75 grade point average on a 4.0 scale and basic experience in Python or Matlab Programming. The internship will take place on the Oklahoma State University campus, so the intern will need to be physically located in Stillwater, OK during the year to perform the research in coordination with the faculty mentor.
Start Date05/31/2018
End Date05/31/2019
LocationThe proposed internship will take place in Stillwater, OK in the School of Civil & Environmental Engineering.
Asma Tamang