Hybrid multi-objective optimization and hybridized self-organizing response surface method

Numerical optimization is a technique where a computer is used to explore design parameter combinations to find extremes in performance factors. In multi-objective optimization several performance factors can be optimized simultaneously. The solution to multi-objective optimization problems is not a single design, but a family of optimized designs referred to as the Pareto frontier. The Pareto frontier is a trade-off curve in the objective function space composed of solutions where performance in one objective function is traded for performance in others. A Multi-Objective Hybridized Optimizer (MOHO) was created for the purpose of solving multi-objective optimization problems by utilizing a set of constituent optimization algorithms. MOHO tracks the progress of the Pareto frontier approximation development and automatically switches amongst those constituent evolutionary optimization algorithms to speed the formation of an accurate Pareto frontier approximation. Aerodynamic shape optimization is one of the oldest applications of numerical optimization. MOHO was used to perform shape optimization on a 0.5-inch ballistic penetrator traveling at Mach number 2.5. Two objectives were simultaneously optimized: minimize aerodynamic drag and maximize penetrator volume. This problem was solved twice. The first time the problem was solved by using Modified Newton Impact Theory (MNIT) to determine the pressure drag on the penetrator. In the second solution, a Parabolized Navier-Stokes (PNS) solver that includes viscosity was used to evaluate the drag on the penetrator. The studies show the difference in the optimized penetrator shapes when viscosity is absent and present in the optimization. In modern optimization problems, objective function evaluations may require many hours on a computer cluster to perform these types of analysis. One solution is to create a response surface that models the behavior of the objective function. Once enough data about the behavior of the objective function has been collected, a response surface can be used to represent the actual objective function in the optimization process. The Hybrid Self-Organizing Response Surface Method (HYBSORSM) algorithm was developed and used to make response surfaces of objective functions. HYBSORSM was evaluated using a suite of 295 non-linear functions. These functions involve from 2 to 100 variables demonstrating robustness and accuracy of HYBSORSM.

Design Optimization of Submerged Jet Nozzles for Enhanced Mixing

The purpose of this thesis 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 a Computational Fluid Dynamics (CFD) 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. A multi-objective optimization software utilized the response surface to generate designs with the best combination of parameters to achieve maximum shear stress and maximum average shear stress. The optimal configuration of parameters achieved larger shear stress values over a commercially available design.

The investigation of photocatalysts and iron based materials in the oxidation and adsorption of toxic organic and chromium materials

The presences of heavy metals, organic contaminants and natural toxins in natural water bodies pose a serious threat to the environment and the health of living organisms. Therefore, there is a critical need to identify sustainable and environmentally friendly water treatment processes. In this dissertation, I focus on the fundamental studies of advanced oxidation processes and magnetic nano-materials as promising new technologies for water treatments. Advanced oxidation processes employ reactive oxygen species (ROS) which can lead to the mineralization of a number of pollutants and toxins. The rates of formation, steady-state concentrations, and kinetic parameters of hydroxyl radical and singlet oxygen produced by various TiO2 photocatalysts under UV or visible irradiations were measured using selective chemical probes. Hydroxyl radical is the dominant ROS, and its generation is dependent on experimental conditions. The optimal condition for generation of hydroxyl radical by of TiO2 coated glass microspheres is studied by response surface methodology, and the optimal conditions are applied for the degradation of dimethyl phthalate. Singlet oxygen (1O2) also plays an important role for advanced processes, so the degradation of microcystin-LR by rose bengal, an 1O2 sensitizer was studied. The measured bimolecular reaction rate constant between MC-LR and 1O2 is ∼ 106 M-1 s-1 based on competition kinetics with furfuryl alcohol. The typical adsorbent needs separation after the treatment, while magnetic iron oxides can be easily removed by a magnetic field. Maghemite and humic acid coated magnetite (HA-Fe3O4) were synthesized, characterized and applied for chromium(VI) removal. The adsorption of chromium(VI) by maghemite and HA-Fe3O4 follow a pseudo-second-order kinetic process. The adsorption of chromium(VI) by maghemite is accurately modeled using adsorption isotherms, and solution pH and presence of humic acid influence adsorption. Humic acid coated magnetite can adsorb and reduce chromium(VI) to non-toxic chromium (III), and the reaction is not highly dependent on solution pH. The functional groups associated with humic acid act as ligands lead to the Cr(III) complex via a coupled reduction-complexation mechanism. Extended X-ray absorption fine structure spectroscopy demonstrates the Cr(III) in the Cr-loaded HA-Fe 3O4 materials has six neighboring oxygen atoms in an octahedral geometry with average bond lengths of 1.98 Å.

Design Optimization of Nozzle Shapes for Maximum Uniformity of Exit Flow

The objective of this study is to identify the optimal designs of converging-diverging supersonic and hypersonic nozzles that perform at maximum uniformity of thermodynamic and flow-field properties with respect to their average values at the nozzle exit. Since this is a multi-objective design optimization problem, the design variables used are parameters defining the shape of the nozzle. This work presents how variation of such parameters can influence the nozzle exit flow non-uniformities. A Computational Fluid Dynamics (CFD) software package, ANSYS FLUENT, was used to simulate the compressible, viscous gas flow-field in forty nozzle shapes, including the heat transfer analysis. The results of two turbulence models, k-e and k-ω, were computed and compared. With the analysis results obtained, the Response Surface Methodology (RSM) was applied for the purpose of performing a multi-objective optimization. The optimization was performed with ModeFrontier software package using Kriging and Radial Basis Functions (RBF) response surfaces. Final Pareto optimal nozzle shapes were then analyzed with ANSYS FLUENT to confirm the accuracy of the optimization process.