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Description
The atomization of a liquid jet by a high speed cross-flowing gas has many applications such as gas turbines and augmentors. The mechanisms by which the liquid jet initially breaks up, however, are not well understood. Experimental studies suggest the dependence of spray properties on operating conditions and nozzle geom- etry. Detailed numerical simulations can offer better understanding of the underlying physical mechanisms that lead to the breakup of the injected liquid jet. In this work, detailed numerical simulation results of turbulent liquid jets injected into turbulent gaseous cross flows for different density ratios is presented. A finite volume, balanced force fractional step flow solver to solve the Navier-Stokes equations is employed and coupled to a Refined Level Set Grid method to follow the phase interface. To enable the simulation of atomization of high density ratio fluids, we ensure discrete consistency between the solution of the conservative momentum equation and the level set based continuity equation by employing the Consistent Rescaled Momentum Transport (CRMT) method. The impact of different inflow jet boundary conditions on different jet properties including jet penetration is analyzed and results are compared to those obtained experimentally by Brown & McDonell(2006). In addition, instability analysis is performed to find the most dominant insta- bility mechanism that causes the liquid jet to breakup. Linear instability analysis is achieved using linear theories for Rayleigh-Taylor and Kelvin- Helmholtz instabilities and non-linear analysis is performed using our flow solver with different inflow jet boundary conditions.
ContributorsGhods, Sina (Author) / Herrmann, Marcus (Thesis advisor) / Squires, Kyle (Committee member) / Chen, Kangping (Committee member) / Huang, Huei-Ping (Committee member) / Tang, Wenbo (Committee member) / Arizona State University (Publisher)
Created2013
Description
Lidar has demonstrated its utility in meteorological studies, wind resource assessment, and wind farm control. More recently, lidar has gained widespread attention for autonomous vehicles.
The first part of the dissertation begins with an application of a coherent Doppler lidar to wind gust characterization for wind farm control. This application focuses on wind gusts on a scale from 100 m to 1000 m. A detecting and tracking algorithm is proposed to extract gusts from a wind field and track their movement. The algorithm was implemented for a three-hour, two-dimensional wind field retrieved from the measurements of a coherent Doppler lidar. The Gaussian distribution of the gust spanwise deviation from the streamline was demonstrated. Size dependency of gust deviations is discussed. A prediction model estimating the impact of gusts with respect to arrival time and the probability of arrival locations is introduced. The prediction model was applied to a virtual wind turbine array, and estimates are given for which wind turbines would be impacted.
The second part of this dissertation describes a Time-of-Flight lidar simulation. The lidar simulation includes a laser source module, a propagation module, a receiver module, and a timing module. A two-dimensional pulse model is introduced in the laser source module. The sampling rate for the pulse model is explored. The propagation module takes accounts of beam divergence, target characteristics, atmosphere, and optics. The receiver module contains models of noise and analog filters in a lidar receiver. The effect of analog filters on the signal behavior was investigated. The timing module includes a Time-to-Digital Converter (TDC) module and an Analog-to-Digital converter (ADC) module. In the TDC module, several walk-error compensation methods for leading-edge detection and multiple timing algorithms were modeled and tested on simulated signals. In the ADC module, a benchmark (BM) timing algorithm is proposed. A Neyman-Pearson (NP) detector was implemented in the time domain and frequency domain (fast Fourier transform (FFT) approach). The FFT approach with frequency-domain zero-paddings improves the timing resolution. The BM algorithm was tested on simulated signals, and the NP detector was evaluated on both simulated signals and measurements from a prototype lidar (Bhaskaran, 2018).
The first part of the dissertation begins with an application of a coherent Doppler lidar to wind gust characterization for wind farm control. This application focuses on wind gusts on a scale from 100 m to 1000 m. A detecting and tracking algorithm is proposed to extract gusts from a wind field and track their movement. The algorithm was implemented for a three-hour, two-dimensional wind field retrieved from the measurements of a coherent Doppler lidar. The Gaussian distribution of the gust spanwise deviation from the streamline was demonstrated. Size dependency of gust deviations is discussed. A prediction model estimating the impact of gusts with respect to arrival time and the probability of arrival locations is introduced. The prediction model was applied to a virtual wind turbine array, and estimates are given for which wind turbines would be impacted.
The second part of this dissertation describes a Time-of-Flight lidar simulation. The lidar simulation includes a laser source module, a propagation module, a receiver module, and a timing module. A two-dimensional pulse model is introduced in the laser source module. The sampling rate for the pulse model is explored. The propagation module takes accounts of beam divergence, target characteristics, atmosphere, and optics. The receiver module contains models of noise and analog filters in a lidar receiver. The effect of analog filters on the signal behavior was investigated. The timing module includes a Time-to-Digital Converter (TDC) module and an Analog-to-Digital converter (ADC) module. In the TDC module, several walk-error compensation methods for leading-edge detection and multiple timing algorithms were modeled and tested on simulated signals. In the ADC module, a benchmark (BM) timing algorithm is proposed. A Neyman-Pearson (NP) detector was implemented in the time domain and frequency domain (fast Fourier transform (FFT) approach). The FFT approach with frequency-domain zero-paddings improves the timing resolution. The BM algorithm was tested on simulated signals, and the NP detector was evaluated on both simulated signals and measurements from a prototype lidar (Bhaskaran, 2018).
ContributorsZhou, Kai (Author) / Calhoun, Ronald (Thesis advisor) / Chen, Kangping (Committee member) / Tang, Wenbo (Committee member) / Peet, Yulia (Committee member) / Krishnamurthy, Raghavendra (Committee member) / Arizona State University (Publisher)
Created2019
Description
A numerical study of chemotaxis in 3D turbulence is presented here. Direct Numerical
Simulation were used to calculate the nutrient uptake for both motile and non-motile bacterial
species and by applying the dynamical systems theory the effect of flow topology on the
variability of chemotaxis is analyzed. It is done by injecting a highly localized patch of nutrient
in the turbulent flow, and analyzing the evolution of reaction associated with the observed
high and low stretching regions. The Gaussian nutrient patch is released at different locations
and the corresponding nutrient uptake is obtained. The variable stretching characteristics of
the flow is depicted by Lagrangian Coherent Structures and the roles they play in affecting the
uptake are analyzed. The Lagrangian Coherent Structures are quantified by the Finite Time
Lyapunov Exponents which is a measure of the average stretching experienced by the flow in
finite time. It is found that in high stretching regions, the motile bacteria are attracted to the
nutrient patch very quickly, but also dispersed quickly; whereas in low stretching regions the
bacteria respond slower towards the nutrient patch. However the total uptake is intricately
determined by stretching history. These reaction characteristics are reflected in the several
realizations of simulations. This helps in understanding turbulence intensity and how it affects
the uptake of the nutrient.
Simulation were used to calculate the nutrient uptake for both motile and non-motile bacterial
species and by applying the dynamical systems theory the effect of flow topology on the
variability of chemotaxis is analyzed. It is done by injecting a highly localized patch of nutrient
in the turbulent flow, and analyzing the evolution of reaction associated with the observed
high and low stretching regions. The Gaussian nutrient patch is released at different locations
and the corresponding nutrient uptake is obtained. The variable stretching characteristics of
the flow is depicted by Lagrangian Coherent Structures and the roles they play in affecting the
uptake are analyzed. The Lagrangian Coherent Structures are quantified by the Finite Time
Lyapunov Exponents which is a measure of the average stretching experienced by the flow in
finite time. It is found that in high stretching regions, the motile bacteria are attracted to the
nutrient patch very quickly, but also dispersed quickly; whereas in low stretching regions the
bacteria respond slower towards the nutrient patch. However the total uptake is intricately
determined by stretching history. These reaction characteristics are reflected in the several
realizations of simulations. This helps in understanding turbulence intensity and how it affects
the uptake of the nutrient.
ContributorsGeorge, Jino (Author) / Tang, Wenbo (Thesis advisor) / Peet, Yulia (Thesis advisor) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2017