Next generation horizontal-axis wind turbines (HAWTs) will operate at very high wind speeds. Existing engineering approaches for modeling the flow phenomena are based on blade element theory, and cannot adequately account for 3-D separated, unsteady flow effects. Therefore, researchers around the world are beginning to model these flows using first principles-based computational fluid dynamics (CFD) approaches. In this study, an existing first principles-based Navier-Stokes approach is being enhanced to model HAWTs at high wind speeds. The enhancements include improved grid topology, implicit time-marching algorithms, and advanced turbulence models. The advanced turbulence models include the Spalart-Allmaras one-equation model, k-epsilon, k-omega and Shear Stress Transport (k-omega-SST) models. These models are also integrated with detached eddy simulation (DES) models. Results are presented for a range of wind speeds, for a configuration termed National Renewable Energy Laboratory Phase VI rotor, tested at NASA Ames Research Center. Grid sensitivity studies are also presented. Additionally, effects of existing transition models on the predictions are assessed. Data presented include power/torque production, radial distribution of normal and tangential pressure forces, root bending moments, and surface pressure fields. Good agreement was obtained between the predictions and experiments for most of the conditions, particularly with the Spalart-Allmaras-DES model.

Thesis (Ph. D.)--Ohio State University, 2004. / Title from first page of PDF file. Document formatted into pages; contains xv, 253 p.; also includes graphics. Includes abstract and vita. Advisor: Chris Brew, Dept. of Linguistics. Includes bibliographical references (p. 245-253).

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In this thesis we explore the the theory and history behind RNA alignment. Normal sequence alignments as studied by computer scientists can be completed in O(n2) time in the naive case. The process involves taking two input sequences and finding the list of edits that can transform one sequence into the other. This process is applied to biology in many forms, such as the creation of multiple alignments and the search of genomic sequences. When you take into account the RNA sequence structure the problem becomes even harder. Multiple RNA structure alignment is particularly challenging because covarying mutations make sequence information alone insufficient. Existing tools for multiple RNA alignments first generate pair-wise RNA structure alignments and then build the multiple alignment using only the sequence information. Here we present PMFastR, an algorithm which iteratively uses a sequence-structure alignment procedure to build a multiple RNA structure alignment. PMFastR also has low memory consumption allowing for the alignment of large sequences such as 16S and 23S rRNA. Specifically, we reduce the memory consumption to ∼O(band2 ∗ m) where band is the banding size. Other solutions are ∼ O(n2 ∗ m) where n and m are the lengths of the target and query respectively. The algorithm also provides a method to utilize a multi-core environment. We present results on benchmark data sets from BRAliBase, which shows PMFastR outperforms other state-of-the-art programs. Furthermore, we regenerate 607 Rfam seed alignments and show that our automated process creates similar multiple alignments to the manually-curated Rfam seed alignments. While these methods can also be applied directly to genome sequence search, the abundance of new multiple species genome alignments presents a new area for exploration. Many multiple alignments of whole genomes are available and these alignments keep growing in size. These alignments can provide more information to the searcher than just a single sequence. Using the methodology from sequence-structure alignment we developed AlnAlign, which searches an entire genome alignment using RNA sequence structure. While programs have been readily available to align alignments, this is the first to our knowledge that is specifically designed for RNA sequences. This algorithm is presented only in theory and is yet to be tested.

Doctor of Philosophy (PhD) / Ultra-lean methane combustion in porous burners is investigated by means of a pilot-scale demonstration of the technology supported by a computational fluid dynamics (CFD) modelling study. The suitability of porous burners as a lean-burn technology for the mitigation of methane emissions is also evaluated. Methane constitutes 14.3% of total global anthropogenic greenhouse gas emissions. The mitigation of these emissions could have a significant near-term effect on slowing global warming, and recovering and burning the methane would allow a wasted energy resource to be exploited. The typically low and fluctuating energy content of the emission streams makes combustion difficult; however porous burners—an advanced combustion technology capable of burning low-calorific value fuels below the conventional flammability limit—are a possible mitigation solution. A pilot-scale porous burner is designed expressly for the purpose of ultra-lean methane combustion. The burner comprises a cylindrical combustion chamber filled with a porous bed of alumina saddles, combined with an arrangement of heat exchanger tubes for preheating the incoming methane/air mixture. A CFD model is developed to aid in the design process. Results illustrating the operating range and behaviour of the burner are presented. Running on natural gas, the stable lean flammability limit of the system is 2.3 vol%, a considerable extension of the conventional lean limit of 4.3 vol%; operating in the transient combustion regime allows the lean limit to be reduced further still, to 1.1 vol%. The heat exchanger arrangement is found to be effective; preheat temperatures of up to 800K are recorded. Emissions of carbon monoxide and unburned hydrocarbons are negligible. The process appears stable to fluctuations in fuel concentration and flow rate, typically taking several hours to react to any changes. A CFD model of the porous burner is developed based on the commercial CFD code ANSYS CFX 12.0. The burner is modelled as a single 1-dimensional porous domain. Pressure loss due to the presence of the porous solid is accounted for using an isotropic loss model. Separate energy equations for the gas and solid phases are applied. Models for conductive heat transfer within the solid phase, and for convective heat transport between the gas and solid phases, are added. Combustion is modelled using a finite rate chemistry model; a skeletal mechanism for ultra-lean methane combustion is developed and incorporated into the model to describe the combustion reaction. Results from the model are presented and validated against experimental data; the model correctly predicts the main features of burner behaviour. Porous burners are found to show potential as a methane mitigation technology.

Doctor of Philosophy (PhD) / Ultra-lean methane combustion in porous burners is investigated by means of a pilot-scale demonstration of the technology supported by a computational fluid dynamics (CFD) modelling study. The suitability of porous burners as a lean-burn technology for the mitigation of methane emissions is also evaluated. Methane constitutes 14.3% of total global anthropogenic greenhouse gas emissions. The mitigation of these emissions could have a significant near-term effect on slowing global warming, and recovering and burning the methane would allow a wasted energy resource to be exploited. The typically low and fluctuating energy content of the emission streams makes combustion difficult; however porous burners—an advanced combustion technology capable of burning low-calorific value fuels below the conventional flammability limit—are a possible mitigation solution. A pilot-scale porous burner is designed expressly for the purpose of ultra-lean methane combustion. The burner comprises a cylindrical combustion chamber filled with a porous bed of alumina saddles, combined with an arrangement of heat exchanger tubes for preheating the incoming methane/air mixture. A CFD model is developed to aid in the design process. Results illustrating the operating range and behaviour of the burner are presented. Running on natural gas, the stable lean flammability limit of the system is 2.3 vol%, a considerable extension of the conventional lean limit of 4.3 vol%; operating in the transient combustion regime allows the lean limit to be reduced further still, to 1.1 vol%. The heat exchanger arrangement is found to be effective; preheat temperatures of up to 800K are recorded. Emissions of carbon monoxide and unburned hydrocarbons are negligible. The process appears stable to fluctuations in fuel concentration and flow rate, typically taking several hours to react to any changes. A CFD model of the porous burner is developed based on the commercial CFD code ANSYS CFX 12.0. The burner is modelled as a single 1-dimensional porous domain. Pressure loss due to the presence of the porous solid is accounted for using an isotropic loss model. Separate energy equations for the gas and solid phases are applied. Models for conductive heat transfer within the solid phase, and for convective heat transport between the gas and solid phases, are added. Combustion is modelled using a finite rate chemistry model; a skeletal mechanism for ultra-lean methane combustion is developed and incorporated into the model to describe the combustion reaction. Results from the model are presented and validated against experimental data; the model correctly predicts the main features of burner behaviour. Porous burners are found to show potential as a methane mitigation technology.

<p dir="ltr">Microfluidic techniques have been widely adopted in biomedical research due to the pre- cise control of fluids, small volume requirement, low cost and etc, and have boosted the development of biomolecular interaction analysis, point-of-care diagnostics, and biosensors.</p><p dir="ltr">Protein-protein interaction plays a key role in biological, biomedical and pharmaceutical research. The technical development of biosensors, new drugs and vaccines, and disease diagnostics heavily rely on the characterization of protein-protein interaction kinetics. The current gold standard assays for measuring protein-protein interaction are surface plasmon resonance (SPR), and bio-layer interferometry (BLI). These commercial devices are accurate but expensive, however.</p><p dir="ltr">Here, I have developed new microfluidic techniques and models in protein-protein in- teraction kinetics measurement, rotational diffusion coefficient modeling, electrochemical impedance spectroscopy-based biosensors, and two-phase porous media flow models. Firstly, I applied particle diffusometry (PD) in the streptavidin-biotin binding kinetics measurement, utilizing a Y-junction microchannel. Secondly, to reduce solution volumes used in an analysis experiment, I designed a low-volume chip and coupled it with PD to measure the binding kinetics of human immunodeficiency virus p24 antibody-antigen interactions. Thirdly, con- sidering the Brownian motion of the non-symmetric particles, I developed a new model to efficiently compute particles’ rotational diffusion coefficients. Fourthly, to make economic biosensors to detect multiple biomarkers, I created a new chip, enabling hundreds of tests in a single droplet (∼ 50 μL) on one chip. Finally, to understand the liquid flow in porous media, such as nitrocellulose in lateral flow assays, I built a new two-phase porous media flow model based on the Navier-Stokes equation and compared it with experiments. These techniques and models underwent rigorous experimental and computational validation, demonstrating their effectiveness and performance.</p>

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