Matching Items (6)
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- All Subjects: Computational Fluid Dynamics
- All Subjects: Fluid Mechanics
- Creators: Lee, Taewoo
Description
Image processing in canals, rivers and other bodies of water has been a very important concern. This research using Image Processing was performed to obtain a photographic evidence of the data of the site which helps in monitoring the conditions of the water body and the surroundings. Images are captured using a digital camera and the images are stored onto a datalogger, these images are retrieved using a cellular/ satellite modem. A MATLAB program was designed to obtain the level of water by just entering the file name into to the program, a curve fit model was created to determine the contrast parameters. The contrast parameters were obtained using the data obtained from the gray scale image mainly the mean and variance of the intensity values. The enhanced images are used to determine the level of water by taking pixel intensity plots along the region of interest. The level of water obtained is accurate to less than 2% of the actual level of water observed from the image. High speed imaging in micro channels have various application in industrial field, medical field etc. In medical field it is tested by using blood samples. The experimental procedure proposed determines the flow duration and the defects observed in these channel using a fluid introduced into the micro channel the fluid being water based dye and whole milk. The viscosity of the fluid shows different types of flow patterns and defects in the micro channel. The defects observed vary from a small effect to the flow pattern to an extreme defect in the channel such as obstruction of flow or deformation in the channel. The sample needs to be further analyzed by SEM to get a better insight on the defects.
ContributorsShasedhara, Abhijeet Bangalore (Author) / Lee, Taewoo (Thesis advisor) / Huang, Huei-Ping (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2011
Description
High Pressure Superheater 1 (HPSH1) is the first heat exchange tube bank inside the Heat Recovery Steam Generator (HRSG) to encounter exhaust flue gas from the gas turbine of a Combined Cycle Power Plant. Steam flowing through the HPSH1 gains heat from the flue gas prior to entering the steam turbine. During cold start-ups, rapid temperature changes in operating condition give rise to significant temperature gradients in the thick-walled components of HPSH1 (manifolds, links, and headers). These temperature gradients produce thermal-structural stresses in the components. The resulting high cycle fatigue is a major concern as this can lead to premature failure of the components. The main objective of this project was to address the thermal-structural stress field induced in HPSH1 during a typical cold start-up transient. To this end, computational fluid dynamics (CFD) was used to carry out the thermal-fluid analysis of HPSH1. The calculated temperature distributions in the component walls were the primary inputs for the finite element (FEA) model that performed structural analysis. Thermal-structural analysis was initially carried out at full-load steady state condition in order to gain confidence in the CFD and FEA methodologies. Results of the full-load steady state thermal-fluid analysis were found in agreement with the temperature values measured at specific locations on the outer surfaces of the inlet links and outlet manifold. It was found from the subsequent structural analysis that peak effective stresses were located at the connecting regions of the components and were well below the allowed stress values. Higher temperature differences were observed between the thick-walled HPSH1 components during the cold start-up transient as compared to the full-load steady state operating condition. This was because of the rapid temperature changes that occurred, especially in the steam temperature at the HPSH1 entry, and the different rates of heating or cooling for components with different wall thicknesses. Results of the transient thermal-fluid analysis will be used in future to perform structural analysis of the HPSH1. The developed CFD and FEA models are capable of analyzing various other transients (e.g., hot start-up and shut-down) and determine their influence on the durability of plant components.
ContributorsHardeep Singh (Author) / Roy, Ramendra P. (Thesis advisor) / Lee, Taewoo (Thesis advisor) / Mignolet, Marc (Committee member) / Arizona State University (Publisher)
Created2012
Description
Theoretical analyses of liquid atomization (bulk to droplet conversion) and turbulence have potential to advance the computability of these flows. Instead of relying on full computations or models, fundamental conservation equations can be manipulated to generate partial or full solutions. For example, integral form of the mass and energy for spray flows leads to an explicit relationship between the drop size and liquid velocities. This is an ideal form to integrate with existing computational fluid dynamic (CFD), which is well developed to solve for the liquid velocities, i.e., the momentum equation(s). Theoretical adaption to CFD has been performed for various injection geometries, with results that compare quite well with experimental data. Since the drop size is provided analytically, computational time/cost for simulating spray flows with liquid atomization is no more than single-phase flows. Some advances have also been made on turbulent flows, by using a new set of perspectives on transport, scaling and energy distributions. Conservation equations for turbulence momentum and kinetic energy have been derived in a coordinate frame moving with the local mean velocities, which produce the Reynolds stress components, without modeling. Scaling of the Reynolds stress is also found at the first- and second-gradient levels. Finally, maximum-entropy principle has been used to derive the energy spectra in turbulent flows.
ContributorsPark, Jung Eun (Author) / Lee, Taewoo (Thesis advisor) / Gardner, Carl (Committee member) / Huang, Huei-Ping (Committee member) / Kim, Jeonglae (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2022
Description
The study of deflagration to detonation transition (DDT) in explosives is of prime importance with regards to insensitive munitions (IM). Critical damage owing to thermal or shock stimuli could translate to significant loss of life and material. The present study models detonation and deflagration of a commonly used granular explosive: cyclotetramethylene-tetranitramine, HMX. A robust literature review is followed by computational modeling of gas gun and DDT tube test data using the Sandia National Lab three-dimensional multi-material Eulerian hydrocode CTH. This dissertation proposes new computational practices and models that aid in predicting shock stimulus IM response. CTH was first used to model experimental data sets of DDT tubes from both Naval Surface Weapons Center and Los Alamos National Laboratory which were initiated by pyrogenic material and a piston, respectively. Analytical verification was performed, where possible, for detonation via empirical based equations at the Chapman Jouguet state with errors below 2.1%, and deflagration via pressure dependent burn rate equations. CTH simulations include inert, history variable reactive burn and Arrhenius models. The results are in excellent agreement with published HMX detonation velocities. Novel additions include accurate simulation of the pyrogenic material BKNO3 and the inclusion of porosity in energetic materials. The treatment of compaction is especially important in modeling precursory hotspots, caused by hydrodynamic collapse of void regions or grain interactions, prior to DDT of granular explosives. The CTH compaction model of HMX was verified within 11% error via a five pronged validation approach using gas gun data and employed use of a newly generated set of P-α parameters for granular HMX in a Mie-Gruneisen Equation of State. Next, the additions of compaction were extended to a volumetric surface burning model of HMX and compare well to a set of empirical burn rates. Lastly, the compendium of detonation and deflagration models was applied to the aforementioned DDT tubes and demonstrate working functionalities of all models, albeit at the expense of significant computational resources. A robust hydrocode methodology is proposed to make use of the deflagration, compaction and detonation models as a means to predict IM response to shock stimulus of granular explosive materials.
ContributorsMahon, Kelly Susan (Author) / Lee, Taewoo (Thesis advisor) / Herrmann, Marcus (Committee member) / Chen, Kangping (Committee member) / Jiao, Yang (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2015
Description
First, in a large-scale structure, a 3-D CFD model was built to simulate flow and temperature distributions. The flow patterns and temperature distributions are characterized and validated through spot measurements. The detailed understanding of them then allows for optimization of the HVAC configuration because identification of the problematic flow patterns and temperature mis-distributions leads to some corrective measures. Second, an appropriate form of the viscous dissipation term in the integral form of the conservation equation was considered, and the effects of momentum terms on the computed drop size in pressure-atomized sprays were examined. The Sauter mean diameter (SMD) calculated in this manner agrees well with experimental data of the drop velocities and sizes. Using the suggested equation with the revised treatment of liquid momentum setup, injection parameters can be directly input to the system of equations. Thus, this approach is capable of incorporating the effects of injection parameters for further considerations of the drop and velocity distributions under a wide range of spray geometry and injection conditions. Lastly, groundwater level estimation was investigated using compressed sensing (CS). To satisfy a general property of CS, a random measurement matrix was used, the groundwater network was constructed, and finally the l-1 optimization was run. Through several validation tests, correct estimation of groundwater level by CS was shown. Using this setup, decreasing trends in groundwater level in the southwestern US was shown. The suggested method is effective in that the total measurements of registered wells can be reduced down by approximately 42 %, sparse data can be visualized and a possible approach for groundwater management during extreme weather changes, e.g. in California, was demonstrated.
ContributorsLee, Joon Young (Author) / Lee, Taewoo (Thesis advisor) / Huang, Huei-Ping (Committee member) / Lopez, Juan (Committee member) / Phelan, Patrick (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2015
Description
Computability of spray flows is an important issue, from both fundamental and practical perspectives. Spray flows have important applications in fuel injection, agriculture, medical devices, and industrial processes such as spray cooling. For this reason, many efforts have been devoted to experimental, computational and some theoretical aspects of spray flows. In particular, primary atomization, the process of bulk liquid transitioning to small droplets, is a central and probably the most difficult aspect of spray flows. This thesis discusses developed methods, results, and needed improvements in the modeling of primary atomization using a predictive Sauter Mean Diameter (SMD) formula. Primary atomization for round injectors and simplex atomizers is modeled using a three-step procedure. For each spray geometry, a volume-of-fluid simulation is run to resolve the trajectory of the intact liquid core. Atomization criterion is applied to the volume-of-fluid velocity field to determine atomization sites. Local droplet size is predicted at the atomization sites using the quadratic formula for Sauter Mean Diameter. Droplets with the computed drop size are injected from the atomization sites and are tracked as point-particles. A User Defined Memory (UDM) code is employed to compute steady-state Sauter Mean Diameter statistics at locations corresponding to experimental interrogation locations. The resulting Sauter Mean Diameter, droplet trajectory, and droplet velocity are compared against experimental data to validate the computational protocol. This protocol can be implemented on coarse-grid, time-averaged simulations of spray flows, and produces convincing results when compared with experimental data for pressure-atomized sprays with and without swirl. This approach is general and can be adapted in any spray geometry for complete and efficient computations of spray flows.
ContributorsGreenlee, Benjamin (Author) / Lee, Taewoo (Thesis advisor) / Herrmann, Marcus (Committee member) / Kasbaoui, Mohamed (Committee member) / Arizona State University (Publisher)
Created2020