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Description
Stereolithography files (STL) are widely used in diverse fields as a means of describing complex geometries through surface triangulations. The resulting stereolithography output is a result of either experimental measurements, or computer-aided design. Often times stereolithography outputs from experimental means are prone to noise, surface irregularities and holes in an

Stereolithography files (STL) are widely used in diverse fields as a means of describing complex geometries through surface triangulations. The resulting stereolithography output is a result of either experimental measurements, or computer-aided design. Often times stereolithography outputs from experimental means are prone to noise, surface irregularities and holes in an otherwise closed surface.

A general method for denoising and adaptively smoothing these dirty stereolithography files is proposed. Unlike existing means, this approach aims to smoothen the dirty surface representation by utilizing the well established levelset method. The level of smoothing and denoising can be set depending on a per-requirement basis by means of input parameters. Once the surface representation is smoothened as desired, it can be extracted as a standard levelset scalar isosurface.

The approach presented in this thesis is also coupled to a fully unstructured Cartesian mesh generation library with built-in localized adaptive mesh refinement (AMR) capabilities, thereby ensuring lower computational cost while also providing sufficient resolution. Future work will focus on implementing tetrahedral cuts to the base hexahedral mesh structure in order to extract a fully unstructured hexahedra-dominant mesh describing the STL geometry, which can be used for fluid flow simulations.
ContributorsKannan, Karthik (Author) / Herrmann, Marcus (Thesis advisor) / Peet, Yulia (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2014
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Description
With a ground-based Doppler lidar on the upwind side of a wind farm in the Tehachapi Pass of California, radial wind velocity measurements were collected for repeating sector sweeps, scanning up to 10 kilometers away. This region consisted of complex terrain, with the scans made between mountains. The dataset was

With a ground-based Doppler lidar on the upwind side of a wind farm in the Tehachapi Pass of California, radial wind velocity measurements were collected for repeating sector sweeps, scanning up to 10 kilometers away. This region consisted of complex terrain, with the scans made between mountains. The dataset was utilized for techniques being studied for short-term forecasting of wind power by correlating changes in energy content and of turbulence intensity by tracking spatial variance, in the wind ahead of a wind farm. A ramp event was also captured and its propagation was tracked.

Orthogonal horizontal wind vectors were retrieved from the radial velocity using a sector Velocity Azimuth Display method. Streamlines were plotted to determine the potential sites for a correlation of upstream wind speed with wind speed at downstream locations near the wind farm. A "virtual wind turbine" was "placed" in locations along the streamline by using the time-series velocity data at the location as the input to a modeled wind turbine, to determine the extractable energy content at that location. The relationship between this time-dependent energy content upstream and near the wind farm was studied. By correlating the energy content with each upstream location based on a time shift estimated according to advection at the mean wind speed, several fits were evaluated. A prediction of the downstream energy content was produced by shifting the power output in time and applying the best-fit function. This method made predictions of the power near the wind farm several minutes in advance. Predictions were also made up to an hour in advance for a large ramp event. The Magnitude Absolute Error and Standard Deviation are presented for the predictions based on each selected upstream location.
ContributorsMagerman, Beth (Author) / Calhoun, Ronald (Thesis advisor) / Peet, Yulia (Committee member) / Huang, Huei-Ping (Committee member) / Krishnamurthy, Raghavendra (Committee member) / Arizona State University (Publisher)
Created2014
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Description
This work helps to explain the drag reduction mechanisms at low and moderate turbulent Reynolds numbers in pipe flows. Through direct numerical simulation, the effects of wall oscillations are observed on the turbulence in both the near wall and the bulk region. Analysis of the average Reynolds

This work helps to explain the drag reduction mechanisms at low and moderate turbulent Reynolds numbers in pipe flows. Through direct numerical simulation, the effects of wall oscillations are observed on the turbulence in both the near wall and the bulk region. Analysis of the average Reynolds Stresses at various phases of the flow is provided along with probability density functions of the fluctuating components of velocity and vorticity. The flow is also visualized to observe, qualitatively, changes in the total and fluctuating field of velocity and vorticity. Linear Stochastic Estimation is used to create a conditional eddy (associated with stress production) in the flow and visualize the effects of transverse wall oscillations on hairpin growth, auto-generation and structure.
ContributorsCoxe, Daniel (Author) / Peet, Yulia (Thesis advisor) / Adrian, Ronald (Thesis advisor) / Herrmann, Marcus (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Autonomic closure is a new general methodology for subgrid closures in large eddy simulations that circumvents the need to specify fixed closure models and instead allows a fully- adaptive self-optimizing closure. The closure is autonomic in the sense that the simulation itself determines the optimal relation at each point and

Autonomic closure is a new general methodology for subgrid closures in large eddy simulations that circumvents the need to specify fixed closure models and instead allows a fully- adaptive self-optimizing closure. The closure is autonomic in the sense that the simulation itself determines the optimal relation at each point and time between any subgrid term and the variables in the simulation, through the solution of a local system identification problem. It is based on highly generalized representations of subgrid terms having degrees of freedom that are determined dynamically at each point and time in the simulation. This can be regarded as a very high-dimensional generalization of the dynamic approach used with some traditional prescribed closure models, or as a type of “data-driven” turbulence closure in which machine- learning methods are used with internal training data obtained at a test-filter scale at each point and time in the simulation to discover the local closure representation.

In this study, a priori tests were performed to develop accurate and efficient implementations of autonomic closure based on particular generalized representations and parameters associated with the local system identification of the turbulence state. These included the relative number of training points and bounding box size, which impact computational cost and generalizability of coefficients in the representation from the test scale to the LES scale. The focus was on studying impacts of these factors on the resulting accuracy and efficiency of autonomic closure for the subgrid stress. Particular attention was paid to the associated subgrid production field, including its structural features in which large forward and backward energy transfer are concentrated.

More than five orders of magnitude reduction in computational cost of autonomic closure was achieved in this study with essentially no loss of accuracy, primarily by using efficient frame-invariant forms for generalized representations that greatly reduce the number of degrees of freedom. The recommended form is a 28-coefficient representation that provides subgrid stress and production fields that are far more accurate in terms of structure and statistics than are traditional prescribed closure models.
ContributorsKshitij, Abhinav (Author) / Dahm, Werner J.A. (Thesis advisor) / Herrmann, Marcus (Committee member) / Hamlington, Peter E (Committee member) / Peet, Yulia (Committee member) / Kim, Jeonglae (Committee member) / Arizona State University (Publisher)
Created2019
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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

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.
ContributorsGeorge, Jino (Author) / Tang, Wenbo (Thesis advisor) / Peet, Yulia (Thesis advisor) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2017
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Description
The central purpose of this work is to investigate the large-scale, coherent structures that exist in turbulent Rayleigh-Bénard convection (RBC) when the domain is large enough for the classical ”wind of turbulence” to break down. The study exclusively focuses on the structures that from when the RBC geometry is a

The central purpose of this work is to investigate the large-scale, coherent structures that exist in turbulent Rayleigh-Bénard convection (RBC) when the domain is large enough for the classical ”wind of turbulence” to break down. The study exclusively focuses on the structures that from when the RBC geometry is a cylinder. A series of visualization studies, Fourier analysis and proper orthogonal decomposition are employed to qualitatively and quantitatively inspect the large-scale structures’ length and time scales, spatial organization, and dynamic properties. The data in this study is generated by direct numerical simulation to resolve all the scales of turbulence in a 6.3 aspect-ratio cylinder at a Rayleigh number of 9.6 × 107 and Prandtl number of 6.7. Single and double point statistics are compared against experiments and several resolution criteria are examined to verify that the simulation has enough spatial and temporal resolution to adequately represent the physical system.

Large-scale structures are found to organize as roll-cells aligned along the cell’s side walls, with rays of vorticity pointing toward the core of the cell. Two different large- scale organizations are observed and these patterns are well described spatially and energetically by azimuthal Fourier modes with frequencies of 2 and 3. These Fourier modes are shown to be dominant throughout the entire domain, and are found to be the primary source for radial inhomogeneity by inspection of the energy spectra. The precision with which the azimuthal Fourier modes describe these large-scale structures shows that these structures influence a large range of length scales. Conversely, the smaller scale structures are found to be more sensitive to radial position within the Fourier modes showing a strong dependence on physical length scales.

Dynamics in the large-scale structures are observed including a transition in the global pattern followed by a net rotation about the central axis. The transition takes place over 10 eddy-turnover times and the subsequent rotation occurs at a rate of approximately 1.1 degrees per eddy-turnover. These time-scales are of the same order of magnitude as those seen in lower aspect-ratio RBC for similar events and suggests a similarity in dynamic events across different aspect-ratios.
ContributorsSakievich, Philip Sakievich (Author) / Peet, Yulia (Thesis advisor) / Adrian, Ronald (Committee member) / Squires, Kyle (Committee member) / Herrmann, Marcus (Committee member) / Kostelich, Eric (Committee member) / Arizona State University (Publisher)
Created2017
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Description
In this study, the stereolithography (SLA) 3D printing method is used to manufacture honeycomb-shaped flat sorbents that can capture CO2 from the air. The 3D-printed sorbents were synthesized using polyvinyl alcohol (PVA), propylene glycol, photopolymer resin, and an ion exchange resin (IER). The one-factor-at-a-time (OFAT) design-of-experiment approach was employed to

In this study, the stereolithography (SLA) 3D printing method is used to manufacture honeycomb-shaped flat sorbents that can capture CO2 from the air. The 3D-printed sorbents were synthesized using polyvinyl alcohol (PVA), propylene glycol, photopolymer resin, and an ion exchange resin (IER). The one-factor-at-a-time (OFAT) design-of-experiment approach was employed to determine the best combination ratio of materials to achieve high moisture swing and a good turnout of printed sorbents. The maximum load limit of the liquid photopolymer resin to enable printability of sorbents was found to be 44%. A series of moisture swing experiments was conducted to investigate the adsorption and desorption performance of the 3D-printed sorbents and compare them with the performance of IER samples prepared by a conventional approach. Results from these experiments conducted indicate that the printed sorbents showed less CO2 adsorptive characteristics compared to the conventional IER sample. It is proposed for future research that a liquid photopolymer resin made up of an IER be synthesized in order to improve the CO2-capturing ability of manufactured sorbents.
ContributorsObeng-Ampomah, Terry (Author) / Phelan, Patrick (Thesis advisor) / Lackner, Klaus (Committee member) / Shuaib, Abdelrahman (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Modern aircraft propulsion systems such as the ultra high bypass ratio turbofan impose constraints on engine installation below the wing, causing jet–wing interactions. Similar interactions are encountered when a jet-powered aircraft takes off on airport runway or aircraft carrier deck. High-speed jet flow near a solid surface shows markedly different

Modern aircraft propulsion systems such as the ultra high bypass ratio turbofan impose constraints on engine installation below the wing, causing jet–wing interactions. Similar interactions are encountered when a jet-powered aircraft takes off on airport runway or aircraft carrier deck. High-speed jet flow near a solid surface shows markedly different turbulence characteristics compared with free jet, including attached turbulent jet and development of non-equilibrium boundary layer down- stream. Wall pressure fluctuations tend to be more unsteady and stronger, leading to increased vibration affecting aircraft cabin noise and modified jet noise radiation. Large-eddy simulation (LES) is useful to characterize turbulent jet flows over a solid surface as well as wall pressure distribution to promote physical understanding and modeling studies. In this study, LES is performed for an installed setup of a Mach 0.7 turbulent jet where the jet–plate distance is fixed at 2D where D is the nozzle-exit diameter. Unstructured-grid LES is used to validate the corresponding experiment (from literature). In addition, a high-fidelity numerical database is built for further analysis and modeling. Turbulence statistics and energy spectra show that agreement with the experimental measurement for the installed case is encouraging, paving a way for future analysis and modeling.
ContributorsTamhane, Nikhil (Author) / Kim, Jeongale (Thesis advisor) / Peet, Yulia (Thesis advisor) / Jeun, Jinah (Committee member) / Arizona State University (Publisher)
Created2022