Design Optimization of Submerged Jet Nozzles for Enhanced Mixing
The aim of this thesis is to present jet nozzles which produce large shear stresses on the bottom surface of a waste storage tank for the efficient cleanup of radioactive waste. The purpose thereof was to identify the optimal design parameters for a jet nozzle which obtains a local maximum shear stress while maximizing the average shear stress on the floor of a fluid filled system. This research examined how geometric parameters of a jet nozzle, such as the nozzle's angle, height, and orifice, influence the shear stress created on the bottom surface of a tank. Simulations were run using the ANSYS FLUENT software package to determine shear stress values for a parameterized geometric domain including the jet nozzle. A response surface was created based on the shear stress values obtained from 112 simulated designs.
To arrive at the design which contains the most effective set of parameters, this research carried out an optimization study using evolutionary methods. From the initial 112 real designs, each with 5 input variables and 2 objective output variables, a response surface was created with modeFRONTIER. Using the Parallel Coordinates chart is an effective tool for identifying the best designs, referred to as the Pareto designs. The NSGA-II algorithm was chosen to carry out the optimization in order to achieve maximum shear stress and maximum average shear stress. The optimal configuration of parameters produced larger shear stress values over a commercially available design.