Degree Type

Thesis

Date of Award

2012

Degree Name

Master of Science

Department

Agricultural and Biosystems Engineering

First Advisor

Zhiyou Wen

Abstract

Algae presents itself as a versatile feedstock for the production of fuels and chemicals ranging from omega-3 fatty acids to Jet-A or JP-8 jet fuels. Mixing of algae culture systems is vital to creating this feedstock. A review of mixing details the many algae culture systems employed to produce algae biomass. It also explores the many mixing methods utilized within the culture system and the importance for the design of these mixing methods. This importance of design has led many researchers to develop mathematical approaches to determining mixing characteristics of algae culture systems. Computational Fluid Dynamics (CFD) uses mathematical techniques to characterize fluid dynamics with the ability to designate thousands of equations to be solved by a computer processor. CFD is known for its strength in design and simulation. This technique allows a user to model a system of fluids to predict movement and therefore effectiveness of design while bypassing physical construction. Studies into this technique are presented and express the strength of CFD as a single phase solver and the current challenges of using CFD as a multiphase solver. To complete an understanding of turbulent mixing effects on algae growth performance, multiphase flows were investigated using a measurement technique of Particle Image Velocimetry (PIV). PIV was used to measure the liquid phase fluid characteristics of a Flat Panel Bioreactor (FPB) that was undergoing mixing by steady state aeration. Parameters such as flow rate (Q), mean velocity (v), and mean Turbulent Kinetic Energy (TKE) were characterized for each experiment that was tested across different aeration schemes. These parameters were weighted against each other to come up with a quality of mixing term, San (M) , which was able to predict the ranking of algae growth performance amongst each experiment. As multiphase flows and their consequent effects on microalgae growth performance are further understood, techniques of CFD may be able to simulate and predict effectiveness solely using computing tools.

DOI

https://doi.org/10.31274/etd-180810-1017

Copyright Owner

Matteo Power del Ninno

Language

en

Date Available

2013-10-31

File Format

application/pdf

File Size

58 pages

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