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Description
The Volume-of-Fluid method is a popular method for interface tracking in Multiphase applications within Computational Fluid Dynamics. To date there exists several algorithms for reconstruction of a geometric interface surface. Of these are the Finite Difference algorithm, Least Squares Volume-of-Fluid Interface Reconstruction Algorithm, LVIRA, and the Efficient Least Squares Volume-of-Fluid

The Volume-of-Fluid method is a popular method for interface tracking in Multiphase applications within Computational Fluid Dynamics. To date there exists several algorithms for reconstruction of a geometric interface surface. Of these are the Finite Difference algorithm, Least Squares Volume-of-Fluid Interface Reconstruction Algorithm, LVIRA, and the Efficient Least Squares Volume-of-Fluid Interface Reconstruction Algorithm, ELVIRA. Along with these geometric interface reconstruction algorithms, there exist several volume-of-fluid transportation algorithms. This paper will discuss two operator-splitting advection algorithms and an unsplit advection algorithm. Using these three interface reconstruction algorithms, and three advection algorithms, a comparison will be drawn to see how different combinations of these algorithms perform with respect to accuracy as well as computational expense.
ContributorsKedelty, Dominic (Author) / Herrmann, Marcus (Thesis advisor) / Huang, Huei-Ping (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2015
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Description
The evolution of single hairpin vortices and multiple interacting hairpin vortices are studied in direct numerical simulations of channel flow at Re-tau=395. The purpose of this study is to observe the effects of increased Reynolds number and varying initial conditions on the growth of hairpins and the conditions under which

The evolution of single hairpin vortices and multiple interacting hairpin vortices are studied in direct numerical simulations of channel flow at Re-tau=395. The purpose of this study is to observe the effects of increased Reynolds number and varying initial conditions on the growth of hairpins and the conditions under which single hairpins autogenerate hairpin packets. The hairpin vortices are believed to provide a unified picture of wall turbulence and play an important role in the production of Reynolds shear stress which is directly related to turbulent drag. The structures of the initial three-dimensional vortices are extracted from the two-point spatial correlation of the fully turbulent direct numerical simulation of the velocity field by linear stochastic estimation and embedded in a mean flow having the profile of the fully turbulent flow. The Reynolds number of the present simulation is more than twice that of the Re-tau=180 flow from earlier literature and the conditional events used to define the stochastically estimated single vortex initial conditions include a number of new types of events such as quasi-streamwise vorticity and Q4 events. The effects of parameters like strength, asymmetry and position are evaluated and compared with existing results in the literature. This study then attempts to answer questions concerning how vortex mergers produce larger scale structures, a process that may contribute to the growth of length scale with increasing distance from the wall in turbulent wall flows. Multiple vortex interactions are studied in detail.
ContributorsParthasarathy, Praveen Kumar (Author) / Adrian, Ronald (Thesis advisor) / Huang, Huei-Ping (Committee member) / Herrmann, Marcus (Committee member) / Arizona State University (Publisher)
Created2011
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Description
This thesis focuses on studying the interaction between floating objects and an air-water flow system driven by gravity. The system consists of an inclined channel in which a gravity driven two phase flow carries a series of floating solid objects downstream. Numerical simulations of such a system requires the solution

This thesis focuses on studying the interaction between floating objects and an air-water flow system driven by gravity. The system consists of an inclined channel in which a gravity driven two phase flow carries a series of floating solid objects downstream. Numerical simulations of such a system requires the solution of not only the basic Navier-Stokes equation but also dynamic interaction between the solid body and the two-phase flow. In particular, this requires embedding of dynamic mesh within the two-phase flow. A computational fluid dynamics solver, ANSYS fluent, is used to solve this problem. Also, the individual components for these simulations are already available in the solver, few examples exist in which all are combined. A series of simulations are performed by varying the key parameters, including density of floating objects and mass flow rate at the inlet. The motion of the floating objects in those simulations are analyzed to determine the stability of the coupled flow-solid system. The simulations are successfully performed over a broad range of parametric values. The numerical framework developed in this study can potentially be used in applications, especially in assisting the design of similar gravity driven systems for transportation in manufacturing processes. In a small number of the simulations, two kinds of numerically instability are observed. One is characterized by a sudden vertical acceleration of the floating object due to a strong imbalance of the force acting on the body, which occurs when the mass flow of water is weak. The other is characterized by a sudden vertical movement of air-water interface, which occurs when two floating objects become too close together. These new types of numerical instability deserve future studies and clarifications. This study is performed only for a 2-D system. Extension of the numerical framework to a full 3-D setting is recommended as future work.
ContributorsMangavelli, Sai Chaitanya (Author) / Huang, Huei-Ping (Thesis advisor) / Kim, Jeonglae (Committee member) / Forzani, Erica (Committee member) / Arizona State University (Publisher)
Created2018
Description
Over the past three decades, particle image velocimetry (PIV) has been continuously growing to become an informative and robust experimental tool for fluid mechanics research. Compared to the early stage of PIV development, the dynamic range of PIV has been improved by about an order of magnitude (Adrian, 2005; Westerweel

Over the past three decades, particle image velocimetry (PIV) has been continuously growing to become an informative and robust experimental tool for fluid mechanics research. Compared to the early stage of PIV development, the dynamic range of PIV has been improved by about an order of magnitude (Adrian, 2005; Westerweel et al., 2013). Further improvement requires a breakthrough innovation, which constitutes the main motivation of this dissertation. N-pulse particle image velocimetry-accelerometry (N-pulse PIVA, where N>=3) is a promising technique to this regard. It employs bursts of N pulses to gain advantages in both spatial and temporal resolution. The performance improvement by N-pulse PIVA is studied using particle tracking (i.e. N-pulse PTVA), and it is shown that an enhancement of at least another order of magnitude is achievable. Furthermore, the capability of N-pulse PIVA to measure unsteady acceleration and force is demonstrated in the context of an oscillating cylinder interacting with surrounding fluid. The cylinder motion, the fluid velocity and acceleration, and the fluid force exerted on the cylinder are successfully measured. On the other hand, a key issue of multi-camera registration for the implementation of N-pulse PIVA is addressed with an accuracy of 0.001 pixel. Subsequently, two applications of N-pulse PTVA to complex flows and turbulence are presented. A novel 8-pulse PTVA analysis was developed and validated to accurately resolve particle unsteady drag in post-shock flows. It is found that the particle drag is substantially elevated from the standard drag due to flow unsteadiness, and a new drag correlation incorporating particle Reynolds number and unsteadiness is desired upon removal of the uncertainty arising from non-uniform particle size. Next, the estimation of turbulence statistics utilizes the ensemble average of 4-pulse PTV data within a small domain of an optimally determined size. The estimation of mean velocity, mean velocity gradient and isotropic dissipation rate are presented and discussed by means of synthetic turbulence, as well as a tomographic measurement of turbulent boundary layer. The results indicate the superior capability of the N-pulse PTV based method to extract high-spatial-resolution high-accuracy turbulence statistics.
ContributorsDing, Liuyang (Author) / Adrian, Ronald J (Thesis advisor) / Frakes, David (Committee member) / Herrmann, Marcus (Committee member) / Huang, Huei-Ping (Committee member) / Peet, Yulia (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Understanding and predicting climate changes at the urban scale have been an important yet challenging problem in environmental engineering. The lack of reliable long-term observations at the urban scale makes it difficult to even assess past climate changes. Numerical modeling plays an important role in filling the gap of observation

Understanding and predicting climate changes at the urban scale have been an important yet challenging problem in environmental engineering. The lack of reliable long-term observations at the urban scale makes it difficult to even assess past climate changes. Numerical modeling plays an important role in filling the gap of observation and predicting future changes. Numerical studies on the climatic effect of desert urbanization have focused on basic meteorological fields such as temperature and wind. For desert cities, urban expansion can lead to substantial changes in the local production of wind-blown dust, which have implications for air quality and public health. This study expands the existing framework of numerical simulation for desert urbanization to include the computation of dust generation related to urban land-use changes. This is accomplished by connecting a suite of numerical models, including a meso-scale meteorological model, a land-surface model, an urban canopy model, and a turbulence model, to produce the key parameters that control the surface fluxes of wind-blown dust. Those models generate the near-surface turbulence intensity, soil moisture, and land-surface properties, which are used to determine the dust fluxes from a set of laboratory-based empirical formulas. This framework is applied to a series of simulations for the desert city of Erbil across a period of rapid urbanization. The changes in surface dust fluxes associated with urbanization are quantified. An analysis of the model output further reveals the dependence of surface dust fluxes on local meteorological conditions. Future applications of the models to environmental prediction are discussed.
ContributorsTahir, Sherzad Tahseen (Author) / Huang, Huei-Ping (Thesis advisor) / Phelan, Patrick (Committee member) / Herrmann, Marcus (Committee member) / Chen, Kangping (Committee member) / Clarke, Amanda (Committee member) / Arizona State University (Publisher)
Created2019
Description
The goal of this paper was to do an analysis of two-dimensional unsplit mass and momentum conserving Finite Volume Methods for Advection for Volume of Fluid Fields with interfaces and validating their rates of convergence. Specifically three unsplit transport methods and one split transport method were amalgamated individually with four

The goal of this paper was to do an analysis of two-dimensional unsplit mass and momentum conserving Finite Volume Methods for Advection for Volume of Fluid Fields with interfaces and validating their rates of convergence. Specifically three unsplit transport methods and one split transport method were amalgamated individually with four Piece-wise Linear Reconstruction Schemes (PLIC) i.e. Unsplit Eulerian Advection (UEA) by Owkes and Desjardins (2014), Unsplit Lagrangian Advection (ULA) by Yang et al. (2010), Split Lagrangian Advection (SLA) by Scardovelli and Zaleski (2003) and Unsplit Averaged Eulerian-Lagrangian Advection (UAELA) with two Finite Difference Methods by Parker and Youngs (1992) and two Error Minimization Methods by Pilliod Jr and Puckett (2004). The observed order of accuracy was first order in all cases except when unsplit methods and error minimization methods were used consecutively in each iteration, which resulted in second-order accuracy on the shape error convergence. The Averaged Unsplit Eulerian-Lagrangian Advection (AUELA) did produce first-order accuracy but that was due to a temporal error in the numerical setup. The main unsplit methods, Unsplit Eulerian Advection (UEA) and Unsplit Lagrangian Advection (ULA), preserve mass and momentum and require geometric clipping to solve two-phase fluid flows. The Unsplit Lagrangian Advection (ULA) can allow for small divergence in the velocity field perhaps saving time on the iterative solver of the variable coefficient Poisson System.
ContributorsAnsari, Adil (M.S.) (Author) / Herrmann, Marcus (Thesis advisor) / Peet, Yulia (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2019
Description
Rapid expansion of dense beds of fine, spherical particles subjected to rapid depressurization is studied in a vertical shock tube. As the particle bed is unloaded, a high-speed video camera captures the dramatic evolution of the particle bed structure. Pressure transducers are used to measure the dynamic pressure changes during

Rapid expansion of dense beds of fine, spherical particles subjected to rapid depressurization is studied in a vertical shock tube. As the particle bed is unloaded, a high-speed video camera captures the dramatic evolution of the particle bed structure. Pressure transducers are used to measure the dynamic pressure changes during the particle bed expansion process. Image processing, signal processing, and Particle Image Velocimetry techniques, are used to examine the relationships between particle size, initial bed height, bed expansion rate, and gas velocities.

The gas-particle interface and the particle bed as a whole expand and evolve in stages. First, the bed swells nearly homogeneously for a very brief period of time (< 2ms). Shortly afterward, the interface begins to develop instabilities as it continues to rise, with particles nearest the wall rising more quickly. Meanwhile, the bed fractures into layers and then breaks down further into cellular-like structures. The rate at which the structural evolution occurs is shown to be dependent on particle size. Additionally, the rate of the overall bed expansion is shown to be dependent on particle size and initial bed height.

Taller particle beds and beds composed of smaller-diameter particles are found to be associated with faster bed-expansion rates, as measured by the velocity of the gas-particle interface. However, the expansion wave travels more slowly through these same beds. It was also found that higher gas velocities above the the gas-particle interface measured \textit{via} Particle Image Velocimetry or PIV, were associated with particle beds composed of larger-diameter particles. The gas dilation between the shocktube diaphragm and the particle bed interface is more dramatic when the distance between the gas-particle interface and the diaphragm is decreased-as is the case for taller beds.

To further elucidate the complexities of this multiphase compressible flow, simple OpenFOAM (Weller, 1998) simulations of the shocktube experiment were performed and compared to bed expansion rates, pressure fluctuations, and gas velocities. In all cases, the trends and relationships between bed height, particle diameter, with expansion rates, pressure fluctuations and gas velocities matched well between experiments and simulations. In most cases, the experimentally-measured bed rise rates and the simulated bed rise rates matched reasonably well in early times. The trends and overall values of the pressure fluctuations and gas velocities matched well between the experiments and simulations; shedding light on the effects each parameter has on the overall flow.
ContributorsZunino, Heather (Author) / Adrian, Ronald J (Thesis advisor) / Clarke, Amanda (Committee member) / Chen, Kangping (Committee member) / Herrmann, Marcus (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Rooftop photovoltaic (PV) systems are becoming increasingly common as the efficiency of solar panels increase, the cost decreases, and worries about climate change increase and become increasingly prevalent. An under explored aspect of rooftop solar systems is the thermal effects that the systems have on the local area. These effects

Rooftop photovoltaic (PV) systems are becoming increasingly common as the efficiency of solar panels increase, the cost decreases, and worries about climate change increase and become increasingly prevalent. An under explored aspect of rooftop solar systems is the thermal effects that the systems have on the local area. These effects are investigated in this paper to determine the overall impact that solar systems have on the heating and cooling demands of a building as well as on the efficiency losses of the solar panels due to the increased temperature on the panels themselves. The specific building studied in this paper is the Goldwater Center for Science and Engineering located in the Tempe campus of Arizona State University. The ambient conditions were modeled from a typical July day in Tempe. A numerical model of a simple flat roof was also created to find the average rooftop temperature throughout the day. Through this study it was determined that solar panels cause a decrease in the maximum temperature of the rooftop during the day, while reducing the ability of the roof to be cooled during the night. The solar panels also saw a high temperature during the day during the most productive time of day for solar panels, which saw a decrease in total energy production for the panels.
ContributorsNaber, Nicholas (Author) / Huang, Huei-Ping (Thesis advisor) / Phelan, Patrick (Committee member) / Bocanegra, Luis (Committee member) / Arizona State University (Publisher)
Created2022
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Description
The propulsion matrix provides a compact description of the locomotion of a single flagella molecular motor in a low Reynolds number environment. The locomotion properties of individual flagellar motors are central to bacterial behavior, including chemotaxis, pathogenesis, and biofilm formation. However, because conventional hydrodynamic measurement approaches require applied forces, torques,

The propulsion matrix provides a compact description of the locomotion of a single flagella molecular motor in a low Reynolds number environment. The locomotion properties of individual flagellar motors are central to bacterial behavior, including chemotaxis, pathogenesis, and biofilm formation. However, because conventional hydrodynamic measurement approaches require applied forces, torques, or fluid flows, it is not possible to directly measure the propulsion matrix for an individual microscale helical filament. Here, the limitations inherent to conventional measurement approaches are overcome using a combination of theoretical, experimental, and computational advancements. First, the relationship between the elements of the propulsion matrix with translational and rotational Brownian motion is derived using the fluctuation-dissipation theorem. Next, a volumetric fluorescent imaging using high resolution oblique plane microscopy with sufficient spatio-temporal resolution is conducted to resolve both translation and rotation of individual helical filaments isolated from E.coli's flagellar motor. Finally, a computational framework is developed to track individual helical filaments across six degrees of freedom, extract diffusion coefficients, and quantify the temporal correlation between translation and rotation. This study computed the maximum propulsion efficiency to be around 1.7%. Direct measurement of propulsion efficiency generally agrees with the ensemble and large-scale measurements previously performed using conventional hydrodynamic measurements. The findings suggest that the approach described here can be extended to more complex in-vitro experiments that evaluate microscale molecular motors. For example, evaluating sperm motility without inducing chemotaxis or utilizing a microfluidic setup.
ContributorsDjutanta, Franky (Author) / Hariadi, Rizal (Thesis advisor) / Wang, Robert (Thesis advisor) / Yurke, Bernard (Committee member) / Herrmann, Marcus (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Computing the fluid phase interfaces in multiphase flow is a challenging area of research in fluids. The Volume of Fluid andLevel Set methods are a few algorithms that have been developed for reconstructing the multiphase fluid flow interfaces. The thesis work focuses on exploring the ability of neural networks to reconstruct

Computing the fluid phase interfaces in multiphase flow is a challenging area of research in fluids. The Volume of Fluid andLevel Set methods are a few algorithms that have been developed for reconstructing the multiphase fluid flow interfaces. The thesis work focuses on exploring the ability of neural networks to reconstruct the multiphase fluid flow interfaces using a data-driven approach. The neural network model has liquid volume fraction stencils as an input, and it predicts the radius of the circle as an output of the network which represents a phase interface separating two immiscible fluids inside a fluid domain. The liquid volume fraction stencils are generated for randomly varying circle radii within a 1x1 domain using an open-source VOFI library. These datasets are used to train the neural network. Once the model is trained, the predicted circular phase interface from the neural network output is used to generate back the predicted liquid volume fraction stencils. Error norms values are calculated to assess the error in the neural network model’s predicted liquid volume fraction stencils with the actual liquid volume fraction stencils from the VOFI library. The neural network parameters are optimized by testing them for different hyper-parameters to reduce the error norms. So as to minimize the difference between the predicted and the actual liquid volume fraction stencils and errors in reconstructing the fluid phase interface geometry.
ContributorsPawar, Pranav Rajesh (Author) / Herrmann, Marcus (Thesis advisor) / Zhuang, Houlong (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2023