<p dir="ltr">Approximately 95% of global steel production relies on continuous casting, there is a need for a practical, cost-effective, and accurate method to guide real-world production. A successful integration of three individual CFD models – spray cooling model, solidification model, and carbon segregation model – was accomplished. To understand the heat transfer behavior on a heated surface, a three-dimensional model was used to simulate the interaction of liquid droplets with a heated surface during the secondary cooling process, employing air-mist nozzles. The real nozzle layout, as employed in a full-scale continuous caster to provide HTC data on slab surface. For solidification model, enthalpy-porosity methods were applied to estimate the metallurgical length and surface temperatures. Carbon transport within the continuous caster was considered, revealing a phenomenon of positive segregation at the center of the slab. Building upon this foundation, further investigations were carried out to assess the implications of nozzle clogging. These effects encompass surface temperature, metallurgical length, and carbon concentration. Commercial software ANSYS Fluent 2021 R2 and Simcenter STAR-CCM+ 2302 are chosen for their exceptional computational performance. MATLAB and Python play key roles in both pre and post processing, including mapping HTC profiles, visualizing shell growth, and extracting temperature and cooling profiles.</p>

The behaviour of particles in pulsating and oscillating flows is of practical interest in devices such as pulsation reactors and ultrasonic elevators. In addition to the resulting flow patterns, the influence of the flow on heat and mass transfer is often important. The state of the art in this area is already quite well developed with many different models, theories, and experiments published. However, only small parameter ranges of the behaviour of particles in pulsating and oscillating flows are considered, while an overarching theoretical framework does not yet exist. Therefore, this work presents a three-stage model for the behaviour of solid single particles in oscillating (pulsating) flows. The relative velocity between particle and fluid as well as the flow patterns around the particle, together with the heat and mass transfer at the particle are considered. The model levels build on top of each other, with the introduced ϵ-Re plain as a common connection between the levels. The number of input parameters could be limited to the five most important ones (fluid velocity amplitude, fluid oscillation frequency, fluid temperature, particle diameter, particle density), but these are considered in very large ranges. The relative velocity is largely calculated analytically using various flow resistance approaches. Direct numerical simulations were carried out to qualitatively estimate the flow patterns around the particle. The quantitative determination of a meta correlation for the entire ϵ-Re plane was carried out using 33 data sets from the literature. Conditions in pulsation reactors are particularly emphasized and their influence investigated.:Chapter 1. Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Chapter 2. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Chapter 3. State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.1. Material Treatment in the Pulsation Reactor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.2. Particle Motion in an Oscillating Fluid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.3. Steady Streaming (Flow Pattern). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.4. Heat and Mass Transfer in Oscillating Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.5. Heat and Mass Transfer in Pulsating Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.6. Non-continuum Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Chapter 4. Basic Assumptions and Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.1. Input Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 4.2. Pulsating Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.3. Forces on the Particle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 4.4. Motion of Particles - Stokes Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 4.5. Harmonic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 4.6. Dimensionless Numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 4.7. The ϵ-Re Plane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Chapter 5. Motion of the Particle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 5.1. Drag Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 5.2. Slip Velocity Amplitude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 5.3. Particle Relaxation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 5.4. Navigation in the ϵ-Re Plane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 5.5. Extension of the Stokes Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 5.6. Additional Effects at Micro Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 5.7. Analytical Particle Motion - Summary and Conclusion . . . . . . . . . . . . . . . . . . . . 61 Chapter 6. Flow Patterns in the Vicinity of the Particle . . . . . . . . . . . . . . . . . . . . . . . . . . 63 6.1. Creeping Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 6.2. Quasi-steady Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 6.3. Steady Streaming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Chapter 7. Heat and Mass Transfer to Particles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 7.1. Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 7.2. The Quasi-Steady HMT Area of the Plane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 7.3. Models for Oscillating Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 7.4. Meta Correlation Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 7.5. Deviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 7.6. Quasi-Steady Assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 7.7. Heat and Mass Transfer to Small Particles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 7.8. Conclusion of Heat and Mass Transfer to Particles . . . . . . . . . . . . . . . . . . . . . . . . . 83 Chapter 8. Summary & Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 8.1. Model Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 8.2. Inŕuence of input parameters on the HMT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 8.3. The ϵ-Re Plane in the Special Case of the Pulsation Reactor . . . . . . . . . . . . . . 91 8.4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Chapter 9. Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 Appendix A. Derivation and Solution of Particle Motion in the Stokes Model . . . . . i Appendix B. Derivation and Solution of Particle Motion in the Landau & Lifshitz Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Appendix C. Derivation of Deviation between Stokes and Schiller & Naumann . . . . x Appendix D. Parameters and Algorithm of the Direct Numerical Simulation and Flow Pattern Visualisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii Appendix E. Conducted Data Preparation for HMT Models . . . . . . . . . . . . . . . . . . . . . . xv / Das Verhalten von Partikeln in pulsierenden und oszillierenden Strömungen findet praktisches Interesse in Apparaten wie Pulsationsreaktoren und Ultraschalllevitatoren. Dabei ist neben den entstehenden Strömungsmustern oft der Einfluss der Strömung auf den Wärme- und Stoffübergang von Bedeutung. Der Stand der Technik in der Literatur in diesem Bereich ist bereits recht weit entwickelt mit vielen verschiedenen Modellen, Theorien und Experimenten. Dabei werden jedoch stets nur kleine Parameterbereiche des Verhaltens von Partikeln in pulsierenden und oszillierenden Strömungen betrachtet, während ein übergreifender theoretischer Rahmen noch nicht existiert. Deshalb wird in dieser Arbeit ein dreistufiges Modell vorgestellt für das Verhalten von festen Einzelpartikeln in oszillierenden (pulsierenden) Fluidströmungen. Sowohl die Relativgeschwindigkeit zwischen Partikel und Fluid als auch die Strömungsmuster um das Partikel und der Wärme- und Stoffübergang am Partikel werden hierbei betrachtet. Die Modellebenen bauen aufeinander auf, wobei die eingeführte ϵ-Re-Ebene die Modellebenen miteinander verbinden. Die Anzahl der Eingangsparameter konnte auf die wichtigsten fünf (Fluidgeschwindigkeitsamplitude, Fluidoszillationsfrequenz, Fluidtemperatur, Partikeldurchmesser, Partikeldichte) begrenzt werden, diese werden jedoch in sehr großen Bereichen betrachtet. Die Relativgeschwindigkeit wird mittels verschiedener Strömungswiderstandsansätze größtenteils analytisch berechnet. Zur qualitativen Abschätzung der Strömungsmuster um das Partikel wurden direkte numerische Simulationen durchgeführt. Die quantitative Bestimmung einer Metakorrelation für die gesamte ϵ-Re-Ebene wurde mittels 33 Datensätze aus der Literatur durchgeführt. Dabei werden Bedingungen in Pulsationsreaktoren besonders herausgestellt und deren Einfluss untersucht.:Chapter 1. Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Chapter 2. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Chapter 3. State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.1. Material Treatment in the Pulsation Reactor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.2. Particle Motion in an Oscillating Fluid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.3. Steady Streaming (Flow Pattern). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.4. Heat and Mass Transfer in Oscillating Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.5. Heat and Mass Transfer in Pulsating Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.6. Non-continuum Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Chapter 4. Basic Assumptions and Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.1. Input Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 4.2. Pulsating Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.3. Forces on the Particle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 4.4. Motion of Particles - Stokes Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 4.5. Harmonic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 4.6. Dimensionless Numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 4.7. The ϵ-Re Plane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Chapter 5. Motion of the Particle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 5.1. Drag Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 5.2. Slip Velocity Amplitude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 5.3. Particle Relaxation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 5.4. Navigation in the ϵ-Re Plane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 5.5. Extension of the Stokes Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 5.6. Additional Effects at Micro Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 5.7. Analytical Particle Motion - Summary and Conclusion . . . . . . . . . . . . . . . . . . . . 61 Chapter 6. Flow Patterns in the Vicinity of the Particle . . . . . . . . . . . . . . . . . . . . . . . . . . 63 6.1. Creeping Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 6.2. Quasi-steady Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 6.3. Steady Streaming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Chapter 7. Heat and Mass Transfer to Particles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 7.1. Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 7.2. The Quasi-Steady HMT Area of the Plane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 7.3. Models for Oscillating Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 7.4. Meta Correlation Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 7.5. Deviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 7.6. Quasi-Steady Assumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 7.7. Heat and Mass Transfer to Small Particles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 7.8. Conclusion of Heat and Mass Transfer to Particles . . . . . . . . . . . . . . . . . . . . . . . . . 83 Chapter 8. Summary & Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 8.1. Model Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 8.2. Inŕuence of input parameters on the HMT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 8.3. The ϵ-Re Plane in the Special Case of the Pulsation Reactor . . . . . . . . . . . . . . 91 8.4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Chapter 9. Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 Appendix A. Derivation and Solution of Particle Motion in the Stokes Model . . . . . i Appendix B. Derivation and Solution of Particle Motion in the Landau & Lifshitz Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Appendix C. Derivation of Deviation between Stokes and Schiller & Naumann . . . . x Appendix D. Parameters and Algorithm of the Direct Numerical Simulation and Flow Pattern Visualisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii Appendix E. Conducted Data Preparation for HMT Models . . . . . . . . . . . . . . . . . . . . . . xv

Sol-gel-based silica monoliths with hierarchical mesopores/macropores are promising catalyst support and flow reactors. Here, we report the successful preparation of cylindrically shaped Pt-loaded silica monoliths (length: 2 cm, diameter: 0.5 cm) with a variable mean macropore width of 1, 6, 10, or 27 μm at a fixed mean mesopore width of 17 nm. The Pt-loaded monolithic catalysts were housed in a robust cladding made of borosilicate glass for use as a flow reactor. The monolithic reactors exhibit a permeability as high as 2 μm2 with a pressure drop below 9 bars over a flow rate range of 2–20 cm3 min−1 (solvent: water). The aqueous-phase hydrogenation of p-nitrophenol to p-aminophenol with NaBH4 as a reducing agent was used as a test reaction to study the influence of mass transfer on catalytic activity in continuous flow. No influence of flow rate on conversion at a fixed contact time of 2.6 s was observed for monolithic catalysts with mean macropore widths of 1, 10, or 27 µm. As opposed to earlier studies conducted at much lower flow velocities, this strongly indicates the absence of external mass-transfer limitations or stagnant layer formation in the macropores of the monolithic catalysts.

No description available.

No description available.

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No description available.

<p>Flow-Accelerated Corrosion (FAC) is a pipe wall thinning mechanism affecting carbon steel piping systems in power generation plants. Mass transfer is the rate limiting factor, even though chemistry and materials determine the overall potential for FAC. Different localized thinning rates in back to back elbow configurations between the first and second elbow have been noted at nuclear power plants, and this difference depends on the length of pipe between the elbows, flow conditions, and the configuration of the back to back elbows (e.g. S, C, or out of plane). In this thesis, mass transfer measurements in back to back elbows arranged in an out of plane configuration under single and annular two-phase flow conditions are presented.</p> <p>The mass transfer measurements were performed using a wall dissolving technique with bend sections cast from gypsum. The diffusivity of gypsum in water is similar to the diffusivity of iron from the magnetite layer of carbon steel pipe in water, thus providing analogous mass transfer conditions to FAC in power generation plants. The wall dissolution of gypsum allows the surface roughness to develop due to the flow. The mass transfer is determined by passing water through the gypsum test sections in a flow loop system. The test sections are then sectioned into two halves to expose the worn surface. The surface topology is measured using a three dimensional laser scanner. The wear progression of the surface with time provides local mass transfer rates, locations of high mass transfer and local surface roughness.</p> <p>The single-phase flow experiments were performed at a Reynolds number of 70,000 for different lengths of pipe (0, 1, 2 and 5 pipe diameters) between the elbows. The mass transfer results show regions of higher mass transfer in the second elbow in comparison to the first el­­bow. The maximum mass transfer rate in the second elbow decreases when the length of the pipe between the elbows was increased from 0 to 5 pipe diameters. Surface features corresponding to flow streaks on the second elbow surface indicated swirling flow, and its strength decreases with increasing separation distance between the elbows. The surface roughness was found to be higher in the regions of high mass transfer and decreases with increasing elbow separation distance.</p> <p>The effect of air and water superficial velocities on the mass transfer for the bends with a separation distance of 0 pipe diameters was measured under two-phase air-water annular flow. In addition, the effect of separation distance of 0, 1 and 5 pipe diameters in length between the elbows was studied for one annular flow condition. The highest mass transfer was found on the outer wall of the first elbow for all cases. The maximum mass transfer in the second elbow was found to be approximately 60 percent of the maximum value in the first elbow, and was not affected significantly when the elbow separation distance was increased from 0 to 1 and 5 pipe diameters. The separation distance between the elbows did not affect the maximum mass transfer on the outer wall of the first elbow. The mass transfer increased with an increase in either the water or air superficial velocity, with the air velocity having a greater effect. The mass transfer enhancement factor relative to that in a straight pipe only increases significantly with increasing air superficial velocity. The roughness development in the pipe was modest, but increases significantly in the high mass transfer region of the first and second elbow.</p> / Master of Applied Science (MASc)

Protecting the quality and quantity of our water resources requires advanced treatment technologies capable of removing nutrients from wastewater. This research work investigated the capability of one such technology, a hollow-fiber membrane-aerated biofilm reactor (HFMBR), to achieve completely autotrophic nitrogen removal from a wastewater with high nitrogen content. Because the extent of oxygenation is a key parameter for controlling the metabolic processes that occur in a wastewater treatment system, the first part of the research investigated oxygen transfer characteristics of the HFMBR in clean water conditions and with actively growing biofilm. A mechanistic model for oxygen concentration and flux as a function of length along the non-porous membrane fibers that comprise the HFMBR was developed based on material properties and physical dimensions. This model reflects the diffusion mechanism of non-porous membranes; namely that oxygen follows a sorption-dissolution-diffusion mechanism. This is in contrast to microporous membranes in which oxygen is in the gas phase in the fiber pores up to the membrane surface, resulting in higher biofilm pore liquid dissolved oxygen concentrations. Compared to offgas oxygen analysis from the HFMBR while in operation with biofilm growing, the model overpredicted mass transfer by a factor of approximately 1.3. This was in contrast to empirical mass transfer coefficient-based methods, which were determined using either bulk aqueous phase dissolved oxygen (DO) concentration or the DO concentration at the membrane-liquid interface, measured with oxygen microsensors. The mass transfer coefficient determined with the DO measured at the interface was the best predictor of actual oxygen transfer under biofilm conditions, while the bulk liquid coefficient underpredicted by a factor of 3. The mechanistic model exhibited sensitivity to parameters such as the initial lumen oxygen concentration (at the entry to the fiber) and the diffusion coefficient and partitioning coefficients of oxygen in the silicone membrane material. The mechanistic model has several advantages over empirical-based methods. Namely, it does not require experimental determination of KL, it is relatively simple to solve without the use of advanced mathematical software, and it is based upon selection of the membrane-biofilm interfacial DO concentration. The last of these is of particular importance when designing and operating HFMBR systems with redox (aerobic/anoxic/anaerobic) stratification, because the DO concentration will determine the nature of the microenvironments, the microorganisms present, and the metabolisms that occur. During the second phase of the research, the coupling of two autotrophic metabolisms, partial nitrification to nitrite (nitritation) and anaerobic ammonium oxidation, was demonstrated in a single HFMBR. The system successfully treated a high-strength nitrogen wastewater intended to mimic a urine stream from such sources as extended space missions. For the last 250 days of operation, operating with an average oxygen to ammonia flux (J_O₂/J_NH₄⁺) of 3.0 resulted in an average nitrogen removal of 74%, with no external organic carbon added. Control of nitrite-oxidizing bacteria (NOB) presented a challenge that was addressed by maintaining the J_O₂/J_NH₄⁺ below the stoichiometric threshold for complete nitrification to nitrate (4.57 g O₂ / g NH₄⁺). The DO-limiting condition resulted in formation of harmful gaseous emissions of nitrogen oxides (NO, N2O), which could not be prevented by short-term control strategies. Controlling JO2/JNH4+ prevented NOB proliferation long enough to allow an anaerobic ammoniaoxidizing bacteria (AnaerAOB) population to develop and be retained for >250 days. Addition of a supplemental nutrient solution may have contributed to the growth of AnaerAOB by overcoming a possible micronutrient deficiency. Disappearance of the gaseous nitrogen oxide emissions coincided with the onset of anaerobic ammonium oxidation, demonstrating a benefit of coupling these two autotrophic metabolisms in one reactor. Obvious differences in biofilm density were evident across the biofilm depth, with a region of low density in the middle of the biofilm, suggesting that low cell density or exocellular polymeric substances were primarily present in this region, Microbial community analysis using fluorescence in situ hybridization (FISH) did not reveal consistent trends with respect to length along the fibers, but radial stratification of aerobic ammonia-oxidizing bacteria (AerAOB), NOB, and AnaerAOB were visible in biofilm section samples. AerAOB were largely found in the first 25% of the biofilm near the membrane, AnaerAOB were found in the outer 30%, and NOB were found most often in the mid-depth region of the biofilm. This community structure demonstrates the importance of oxygen availability as a determinant of how microbial groups spatially distribute within an HFMBR biofilm. The combination of these two aspects of the research, predictive oxygen transfer capability and the effect of oxygen control on performance and populations, provides a foundation for future application of HFMBR technology to a broad range of wastewaters and treatment scenarios. / Ph. D.

<p dir="ltr">On many hypersonic vehicles, gaps are present on the outer surface of the vehicle and the interaction of the hypersonic freestream flow over these gaps can cause significant heat transfer to the vehicle. The project described in this thesis analyzed selected hypersonic gap problems and attempted to offer solutions to combat the heat transfer occurring in the gap. The first section of this thesis is a parametric study to understand the changes to the heat transfer and flow that modifications to the gap geometry can make. The second section is a comparison of the computational model to experimental data. The results of the studies show that adding a simple fillet or chamfer to the downstream step of the gap can reduce the maximum heat flux by over 90%. These results can be used to reduce the heat transfer caused by flow impingement in the gaps of hypersonic vehicles with a simple modification of the geometry and is consistent with the findings of other work in gap heating.</p>