Matching Items (7)
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- All Subjects: Computational Fluid Dynamics
- Creators: Adrian, Ronald
Description
The flow around a golf ball is studied using direct numerical simulation (DNS). An immersed boundary approach is adopted in which the incompressible Navier-Stokes equations are solved using a fractional step method on a structured, staggered grid in cylindrical coordinates. The boundary conditions on the surface are imposed using momentum forcing in the vicinity of the boundary. The flow solver is parallelized using a domain decomposition strategy and message passing interface (MPI), and exhibits linear scaling on as many as 500 processors. A laminar flow case is presented to verify the formal accuracy of the method. The immersed boundary approach is validated by comparison with computations of the flow over a smooth sphere. Simulations are performed at Reynolds numbers of 2.5 × 104 and 1.1 × 105 based on the diameter of the ball and the freestream speed and using grids comprised of more than 1.14 × 109 points. Flow visualizations reveal the location of separation, as well as the delay of complete detachment. Predictions of the aerodynamic forces at both Reynolds numbers are in reasonable agreement with measurements. Energy spectra of the velocity quantify the dominant frequencies of the flow near separation and in the wake. Time-averaged statistics reveal characteristic physical patterns in the flow as well as local trends within dimples. A mechanism of drag reduction due to the dimples is confirmed, and metrics for dimple optimization are proposed.
ContributorsSmith, Clinton E (Author) / Squires, Kyle D (Thesis advisor) / Balaras, Elias (Committee member) / Herrmann, Marcus (Committee member) / Adrian, Ronald (Committee member) / Stanzione, Daniel C (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2011
Description
A method of determining nanoparticle temperature through fluorescence intensity levels is described. Intracellular processes are often tracked through the use of fluorescence tagging, and ideal temperatures for many of these processes are unknown. Through the use of fluorescence-based thermometry, cellular processes such as intracellular enzyme movement can be studied and their respective temperatures established simultaneously. Polystyrene and silica nanoparticles are synthesized with a variety of temperature-sensitive dyes such as BODIPY, rose Bengal, Rhodamine dyes 6G, 700, and 800, and Nile Blue A and Nile Red. Photographs are taken with a QImaging QM1 Questar EXi Retiga camera while particles are heated from 25 to 70 C and excited at 532 nm with a Coherent DPSS-532 laser. Photographs are converted to intensity images in MATLAB and analyzed for fluorescence intensity, and plots are generated in MATLAB to describe each dye's intensity vs temperature. Regression curves are created to describe change in fluorescence intensity over temperature. Dyes are compared as nanoparticle core material is varied. Large particles are also created to match the camera's optical resolution capabilities, and it is established that intensity values increase proportionally with nanoparticle size. Nile Red yielded the closest-fit model, with R2 values greater than 0.99 for a second-order polynomial fit. By contrast, Rhodamine 6G only yielded an R2 value of 0.88 for a third-order polynomial fit, making it the least reliable dye for temperature measurements using the polynomial model. Of particular interest in this work is Nile Blue A, whose fluorescence-temperature curve yielded a much different shape from the other dyes. It is recommended that future work describe a broader range of dyes and nanoparticle sizes, and use multiple excitation wavelengths to better quantify each dye's quantum efficiency. Further research into the effects of nanoparticle size on fluorescence intensity levels should be considered as the particles used here greatly exceed 2 ìm. In addition, Nile Blue A should be further investigated as to why its fluorescence-temperature curve did not take on a characteristic shape for a temperature-sensitive dye in these experiments.
ContributorsTomforde, Christine (Author) / Phelan, Patrick (Thesis advisor) / Dai, Lenore (Committee member) / Adrian, Ronald (Committee member) / Arizona State University (Publisher)
Created2011
Description
Next generation gas turbines will be required to produce low concentrations of pollutants such as oxides of nitrogen (NOx), carbon monoxide (CO), and soot. In order to design gas turbines which produce lower emissions it is essential to have computational tools to help designers. Over the past few decades, computational fluid dynamics (CFD) has played a key role in the design of turbomachinary and will be heavily relied upon for the design of future components. In order to design components with the least amount of experimental rig testing, the ensemble of submodels used in simulations must be known to accurately predict the component's performance. The present work aims to validate a CFD model used for a reverse flow, rich-burn, quick quench, lean-burn combustor being developed at Honeywell. Initially, simulations are performed to establish a baseline which will help to assess impact to combustor performance made by changing CFD models. Rig test data from Honeywell is compared to these baseline simulation results. Reynolds averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) turbulence models are both used with the presumption that the LES turbulence model will better predict combustor performance. One specific model, the fuel spray model, is evaluated next. Experimental data of the fuel spray in an isolated environment is used to evaluate models for the fuel spray and a new, simpler approach for inputting the spray boundary conditions (BC) in the combustor is developed. The combustor is simulated once more to evaluate changes from the new fuel spray boundary conditions. This CFD model is then used in a predictive simulation of eight other combustor configurations. All computer simulations in this work were preformed with the commercial CFD software ANSYS FLUENT. NOx pollutant emissions are predicted reasonably well across the range of configurations tested using the RANS turbulence model. However, in LES, significant under predictions are seen. Causes of the under prediction in NOx concentrations are investigated. Temperature metrics at the exit of the combustor, however, are seen to be better predicted with LES.
ContributorsSpencer, A. Jeffrey (Author) / Herrmann, Marcus (Thesis advisor) / Chen, Kangping (Committee member) / Adrian, Ronald (Committee member) / Arizona State University (Publisher)
Created2012
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 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
Description
Cerebral aneurysms are pathological balloonings of blood vessels in the brain, commonly found in the arterial network at the base of the brain. Cerebral aneurysm rupture can lead to a dangerous medical condition, subarachnoid hemorrhage, that is associated with high rates of morbidity and mortality. Effective evaluation and management of cerebral aneurysms is therefore essential to public health. The goal of treating an aneurysm is to isolate the aneurysm from its surrounding circulation, thereby preventing further growth and rupture. Endovascular treatment for cerebral aneurysms has gained popularity over traditional surgical techniques due to its minimally invasive nature and shorter associated recovery time. The hemodynamic modifications that the treatment effects can promote thrombus formation within the aneurysm leading to eventual isolation. However, different treatment devices can effect very different hemodynamic outcomes in aneurysms with different geometries.
Currently, cerebral aneurysm risk evaluation and treatment planning in clinical practice is largely based on geometric features of the aneurysm including the dome size, dome-to-neck ratio, and parent vessel geometry. Hemodynamics, on the other hand, although known to be deeply involved in cerebral aneurysm initiation and progression, are considered to a lesser degree. Previous work in the field of biofluid mechanics has demonstrated that geometry is a driving factor behind aneurysmal hemodynamics.
The goal of this research is to develop a more combined geometric/hemodynamic basis for informing clinical decisions. Geometric main effects were analyzed to quantify contributions made by geometric factors that describe cerebral aneurysms (i.e., dome size, dome-to-neck ratio, and inflow angle) to clinically relevant hemodynamic responses (i.e., wall shear stress, root mean square velocity magnitude and cross-neck flow). Computational templates of idealized bifurcation and sidewall aneurysms were created to satisfy a two-level full factorial design, and examined using computational fluid dynamics. A subset of the computational bifurcation templates was also translated into physical models for experimental validation using particle image velocimetry. The effects of geometry on treatment were analyzed by virtually treating the aneurysm templates with endovascular devices. The statistical relationships between geometry, treatment, and flow that emerged have the potential to play a valuable role in clinical practice.
Currently, cerebral aneurysm risk evaluation and treatment planning in clinical practice is largely based on geometric features of the aneurysm including the dome size, dome-to-neck ratio, and parent vessel geometry. Hemodynamics, on the other hand, although known to be deeply involved in cerebral aneurysm initiation and progression, are considered to a lesser degree. Previous work in the field of biofluid mechanics has demonstrated that geometry is a driving factor behind aneurysmal hemodynamics.
The goal of this research is to develop a more combined geometric/hemodynamic basis for informing clinical decisions. Geometric main effects were analyzed to quantify contributions made by geometric factors that describe cerebral aneurysms (i.e., dome size, dome-to-neck ratio, and inflow angle) to clinically relevant hemodynamic responses (i.e., wall shear stress, root mean square velocity magnitude and cross-neck flow). Computational templates of idealized bifurcation and sidewall aneurysms were created to satisfy a two-level full factorial design, and examined using computational fluid dynamics. A subset of the computational bifurcation templates was also translated into physical models for experimental validation using particle image velocimetry. The effects of geometry on treatment were analyzed by virtually treating the aneurysm templates with endovascular devices. The statistical relationships between geometry, treatment, and flow that emerged have the potential to play a valuable role in clinical practice.
ContributorsNair, Priya (Author) / Frakes, David (Thesis advisor) / Vernon, Brent (Committee member) / Chong, Brian (Committee member) / Pizziconi, Vincent (Committee member) / Adrian, Ronald (Committee member) / Arizona State University (Publisher)
Created2016
Description
This dissertation introduces FARCOM (Fortran Adaptive Refiner for Cartesian Orthogonal Meshes), a new general library for adaptive mesh refinement (AMR) based on an unstructured hexahedral mesh framework. As a result of the underlying unstructured formulation, the refinement and coarsening operators of the library operate on a single-cell basis and perform in-situ replacement of old mesh elements. This approach allows for h-refinement without the memory and computational expense of calculating masked coarse grid cells, as is done in traditional patch-based AMR approaches, and enables unstructured flow solvers to have access to the automated domain generation capabilities usually only found in tree AMR formulations.
The library is written to let the user determine where to refine and coarsen through custom refinement selector functions for static mesh generation and dynamic mesh refinement, and can handle smooth fields (such as level sets) or localized markers (e.g. density gradients). The library was parallelized with the use of the Zoltan graph-partitioning library, which provides interfaces to both a graph partitioner (PT-Scotch) and a partitioner based on Hilbert space-filling curves. The partitioned adjacency graph, mesh data, and solution variable data is then packed and distributed across all MPI ranks in the simulation, which then regenerate the mesh, generate domain decomposition ghost cells, and create communication caches.
Scalability runs were performed using a Leveque wave propagation scheme for solving the Euler equations. The results of simulations on up to 1536 cores indicate that the parallel performance is highly dependent on the graph partitioner being used, and differences between the partitioners were analyzed. FARCOM is found to have better performance if each MPI rank has more than 60,000 cells.
The library is written to let the user determine where to refine and coarsen through custom refinement selector functions for static mesh generation and dynamic mesh refinement, and can handle smooth fields (such as level sets) or localized markers (e.g. density gradients). The library was parallelized with the use of the Zoltan graph-partitioning library, which provides interfaces to both a graph partitioner (PT-Scotch) and a partitioner based on Hilbert space-filling curves. The partitioned adjacency graph, mesh data, and solution variable data is then packed and distributed across all MPI ranks in the simulation, which then regenerate the mesh, generate domain decomposition ghost cells, and create communication caches.
Scalability runs were performed using a Leveque wave propagation scheme for solving the Euler equations. The results of simulations on up to 1536 cores indicate that the parallel performance is highly dependent on the graph partitioner being used, and differences between the partitioners were analyzed. FARCOM is found to have better performance if each MPI rank has more than 60,000 cells.
ContributorsBallesteros, Carlos Alberto (Author) / Herrmann, Marcus (Thesis advisor) / Adrian, Ronald (Committee member) / Chen, Kangping (Committee member) / Huang, Huei-Ping (Committee member) / Lopez, Juan (Committee member) / Arizona State University (Publisher)
Created2019
Description
Atomization of fluids inside combustion chamber has been a very complex and long-lasting subject that is still researched into for maximum efficiency in mixing oxidizer and fuel. This thesis focuses on an injector called the Liquid-Liquid Swirl Coaxial Injector (LLSC) to be used in a small-scale rocket engine due to its high efficiency in spray angles and low pressure drops. Injectors are the elements that exist as a connection in between the plumbing and the combustion chamber of the rocket engine. The performance of injectors can greatly affect the stability and efficiency of the engine. Injectors proportionally help breakup the fluid into small droplets that help in the efficiency of vaporization of fluids while combusting. Helios Rocketry, Arizona State University’s student-led engineering organization, is working to design and successfully launch a small-scale bi-propellant liquid rocket engine to a 100 km (Karman Line) in space as part of the Base11 challenge. For this task a highly efficient injector element needed to be designed that can achieve high amounts of atomization with a large spray angle, to help with combustion in a relatively small sized chamber. The purpose of this thesis is to explore a specific type of injector element called a LLSC injector element. This is performed by simulating it through an LES model in computational fluid dynamics using a Voronoi based meshing scheme, by using codes from Cascade Technologies. In the end a 35-injector element design was used for an injector plate. This helped minimize the pressure drop and keep the wall stress below the safety limit.
ContributorsDave, Himanshu Hitendra (Author) / Herrmann, Marcus (Thesis director) / Adrian, Ronald (Committee member) / Mechanical and Aerospace Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05