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- Member of: ASU Electronic Theses and Dissertations
Description
Many physical phenomena and industrial applications involve multiphase fluid flows and hence it is of high importance to be able to simulate various aspects of these flows accurately. The Dynamic Contact Angles (DCA) and the contact lines at the wall boundaries are a couple of such important aspects. In the past few decades, many mathematical models were developed for predicting the contact angles of the inter-face with the wall boundary under various flow conditions. These models are used to incorporate the physics of DCA and contact line motion in numerical simulations using various interface capturing/tracking techniques. In the current thesis, a simple approach to incorporate the static and dynamic contact angle boundary conditions using the level set method is developed and implemented in multiphase CFD codes, LIT (Level set Interface Tracking) (Herrmann (2008)) and NGA (flow solver) (Desjardins et al (2008)). Various DCA models and associated boundary conditions are reviewed. In addition, numerical aspects such as the occurrence of a stress singularity at the contact lines and grid convergence of macroscopic interface shape are dealt with in the context of the level set approach.
ContributorsPendota, Premchand (Author) / Herrmann, Marcus (Thesis advisor) / Rykaczewski, Konrad (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2015
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
The objective of this research is to develop robust, accurate, and adaptive algorithms in the framework of the extended finite element method (XFEM) for fracture analysis of highly heterogeneous materials with complex internal geometries. A key contribution of this work is the creation of novel methods designed to automate the incorporation of high-resolution data, e.g. from X-ray tomography, that can be used to better interpret the enormous volume of data generated in modern in-situ experimental testing. Thus new algorithms were developed for automating analysis of complex microstructures characterized by segmented tomographic images.
A centrality-based geometry segmentation algorithm was developed to accurately identify discrete inclusions and particles in composite materials where limitations in imaging resolution leads to spurious connections between particles in close contact.To allow for this algorithm to successfully segment geometry independently of particle size and shape, a relative centrality metric was defined to allow for a threshold centrality criterion for removal of voxels that spuriously connect distinct geometries.
To automate incorporation of microstructural information from high-resolution images, two methods were developed that initialize signed distance fields on adaptively-refined finite element meshes. The first method utilizes a level set evolution equation that is directly solved on the finite element mesh through Galerkins method. The evolution equation is formulated to produce a signed distance field that matches geometry defined by a set of voxels segmented from tomographic images. The method achieves optimal convergence for the order of elements used. In a second approach, the fast marching method is employed to initialize a distance field on a uniform grid which is then projected by least squares onto a finite element mesh. This latter approach is shown to be superior in speed and accuracy.
Lastly, extended finite element method simulations are performed for the analysis of particle fracture in metal matrix composites with realistic particle geometries initialized from X-ray tomographic data. In the simulations, particles fracture probabilistically through a Weibull strength distribution. The model is verified through comparisons with the experimentally-measured stress-strain response of the material as well as analysis of the fracture. Further, simulations are then performed to analyze the effect of mesh sensitivity, the effect of fracture of particles on their neighbors, and the role of a particles shape on its fracture probability.
A centrality-based geometry segmentation algorithm was developed to accurately identify discrete inclusions and particles in composite materials where limitations in imaging resolution leads to spurious connections between particles in close contact.To allow for this algorithm to successfully segment geometry independently of particle size and shape, a relative centrality metric was defined to allow for a threshold centrality criterion for removal of voxels that spuriously connect distinct geometries.
To automate incorporation of microstructural information from high-resolution images, two methods were developed that initialize signed distance fields on adaptively-refined finite element meshes. The first method utilizes a level set evolution equation that is directly solved on the finite element mesh through Galerkins method. The evolution equation is formulated to produce a signed distance field that matches geometry defined by a set of voxels segmented from tomographic images. The method achieves optimal convergence for the order of elements used. In a second approach, the fast marching method is employed to initialize a distance field on a uniform grid which is then projected by least squares onto a finite element mesh. This latter approach is shown to be superior in speed and accuracy.
Lastly, extended finite element method simulations are performed for the analysis of particle fracture in metal matrix composites with realistic particle geometries initialized from X-ray tomographic data. In the simulations, particles fracture probabilistically through a Weibull strength distribution. The model is verified through comparisons with the experimentally-measured stress-strain response of the material as well as analysis of the fracture. Further, simulations are then performed to analyze the effect of mesh sensitivity, the effect of fracture of particles on their neighbors, and the role of a particles shape on its fracture probability.
ContributorsYuan, Rui (Author) / Oswald, Jay (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Liu, Yongming (Committee member) / Solanki, Kiran (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2015
Description
Environmentally responsive microgels have drawn significant attention due to their intrinsic ability to change volume in response to various external stimuli such as pH, temperature, osmotic pressure, or electric and magnetic fields. The extent of particle swelling is controlled by the nature of the polymer-solvent interaction. This thesis focuses on design and synthesis of environmentally responsive microgels and their composites, and encompasses methods of utilizing microgel systems in applications as vehicles for the adsorption, retention, and targeted delivery of chemical species. Furthermore, self-assembled microgel particles at ionic liquid (IL)-water interfaces demonstrate responsive colloidal lattice morphology. The thesis first reports on the fundamental aspects of synthesis, functionalization, and characteristic properties of multifunctional environmentally responsive microgels derived from poly(N-isopropylacrylamide) (PNIPAm) and other functional co-monomers. In particular, the uptake and release of active chemical species such as rheology modifiers into and from these ionic microgels is demonstrated. Moreover, a facile tunable method for the formation of organic-inorganic composites with Fe3O4 nanoparticles adsorbed and embedded within ionic microgel particles is explored. Additionally, the development of zwitterionic microgels (ZI-MG) is presented. These aqueous ZI-MG dispersions exhibit reversible parabolic swelling as a function of pH and display a minimum hydrodynamic diameter at a tunable isoelectric point (IEP). This study also elucidates the controlled uptake and release of surfactants from these particle systems. The extent of surfactant loading and the ensuing relative swelling/deswelling behaviors within the polymer networks are explained in terms of their binding interactions. The latter part of this thesis highlights the versatility of fluorescently labeled microgel particles as stabilizers for IL-water droplets. When the prepared particles form monolayers and equilibrate at the liquid-liquid interface, the colloidal lattice organization may re-order itself depending on the surface charge of these particles. Finally, it is shown that the spontaneously formed and densely packed layers of microgel particles can be employed for extraction applications, as the interface remains permeable to small active species.
ContributorsChen, Haobo (Author) / Dai, Lenore L (Committee member) / Chen, Kangping (Committee member) / Forzani, Erica (Committee member) / Lind, Mary Laura (Committee member) / Mu, Bin (Committee member) / Arizona State University (Publisher)
Created2015
Description
This dissertation describes a process for interface capturing via an arbitrary-order, nearly quadrature free, discontinuous Galerkin (DG) scheme for the conservative level set method (Olsson et al., 2005, 2008). The DG numerical method is utilized to solve both advection and reinitialization, and executed on a refined level set grid (Herrmann, 2008) for effective use of processing power. Computation is executed in parallel utilizing both CPU and GPU architectures to make the method feasible at high order. Finally, a sparse data structure is implemented to take full advantage of parallelism on the GPU, where performance relies on well-managed memory operations.
With solution variables projected into a kth order polynomial basis, a k+1 order convergence rate is found for both advection and reinitialization tests using the method of manufactured solutions. Other standard test cases, such as Zalesak's disk and deformation of columns and spheres in periodic vortices are also performed, showing several orders of magnitude improvement over traditional WENO level set methods. These tests also show the impact of reinitialization, which often increases shape and volume errors as a result of level set scalar trapping by normal vectors calculated from the local level set field.
Accelerating advection via GPU hardware is found to provide a 30x speedup factor comparing a 2.0GHz Intel Xeon E5-2620 CPU in serial vs. a Nvidia Tesla K20 GPU, with speedup factors increasing with polynomial degree until shared memory is filled. A similar algorithm is implemented for reinitialization, which relies on heavier use of shared and global memory and as a result fills them more quickly and produces smaller speedups of 18x.
With solution variables projected into a kth order polynomial basis, a k+1 order convergence rate is found for both advection and reinitialization tests using the method of manufactured solutions. Other standard test cases, such as Zalesak's disk and deformation of columns and spheres in periodic vortices are also performed, showing several orders of magnitude improvement over traditional WENO level set methods. These tests also show the impact of reinitialization, which often increases shape and volume errors as a result of level set scalar trapping by normal vectors calculated from the local level set field.
Accelerating advection via GPU hardware is found to provide a 30x speedup factor comparing a 2.0GHz Intel Xeon E5-2620 CPU in serial vs. a Nvidia Tesla K20 GPU, with speedup factors increasing with polynomial degree until shared memory is filled. A similar algorithm is implemented for reinitialization, which relies on heavier use of shared and global memory and as a result fills them more quickly and produces smaller speedups of 18x.
ContributorsJibben, Zechariah J (Author) / Herrmann, Marcus (Thesis advisor) / Squires, Kyle (Committee member) / Adrian, Ronald (Committee member) / Chen, Kangping (Committee member) / Treacy, Michael (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
Conventional fluid dynamics models such as the Navier-Stokes equations are derived for prediction of fluid motion at or near equilibrium, classic examples being the motion of fluids for which inter-molecular collisions are dominant. Flows at equilibrium permit simplifications such as the introduction of viscosity and also lead to solutions that are single-valued. However, many other regimes of interest include "fluids"' far from equilibrium; for example, rarefied gases or particle-laden flows in which the dispersed phase can be comprised of granular solids, droplets, or bubbles. Particle motion in these flows is not typically dominated by collisions and may exhibit significant memory effects; therefore, is often poorly described using continuum, field-based (Eulerian) approaches. Non-equilibrium flows generally lack a straightforward counterpart to viscosity and their multi-valued solutions cannot be represented by most Eulerian methods. This strongly motivates different strategies to address current shortcomings and the novel approach adopted in this work is based on the Conditional Quadrature Method of Moments (CQMOM). In CQMOM, moment equations are derived from the Boltzmann equation using a quadrature approximation of the velocity probability density function (PDF). CQMOM circumvents the drawbacks of current methods and leads to multivariate and multidimensional solutions in an Eulerian frame of reference. In the present work, the discretized PDF is resolved using an adaptive two-point quadrature in three-dimensional velocity space. The method is applied to computation of a series of non-equilibrium flows, ranging from simple two-dimensional test cases to fully-turbulent three-dimensional wall-bounded particle-laden flows. The primary contribution of the present effort is on development, application, and assessment of CQMOM for predicting the key features of dilute particle-laden flows. Statistical descriptors such as mean concentration and mean velocity are in good agreement with previous results, for both collision-less and collisional flows at varying particle Stokes numbers. Turbulent statistics and measures of local accumulation agree less favorably with prior results and identify areas for improvement in the modeling strategy.
ContributorsDunn, Dennis Martin (Author) / Squires, Kyle D. (Thesis advisor) / Calhoun, Ronald J. (Committee member) / Chen, Kangping (Committee member) / Dai, Lenore L. (Committee member) / Herrmann, Marcus (Committee member) / Arizona State University (Publisher)
Created2015
Description
A numerical study of incremental spin-up and spin-up from rest of a thermally- stratified fluid enclosed within a right circular cylinder with rigid bottom and side walls and stress-free upper surface is presented. Thermally stratified spin-up is a typical example of baroclinity, which is initiated by a sudden increase in rotation rate and the tilting of isotherms gives rise to baroclinic source of vorticity. Research by (Smirnov et al. [2010a]) showed the differences in evolution of instabilities when Dirichlet and Neumann thermal boundary conditions were applied at top and bottom walls. Study of parametric variations carried out in this dissertation confirmed the instability patterns observed by them for given aspect ratio and Rossby number values greater than 0.5. Also results reveal that flow maintained axisymmetry and stability for short aspect ratio containers independent of amount of rotational increment imparted. Investigation on vorticity components provides framework for baroclinic vorticity feedback mechanism which plays important role in delayed rise of instabilities when Dirichlet thermal Boundary Conditions are applied.
ContributorsKher, Aditya Deepak (Author) / Chen, Kangping (Thesis advisor) / Huang, Huei-Ping (Committee member) / Herrmann, Marcus (Committee member) / Arizona State University (Publisher)
Created2011
Description
Cavitation erosion is a significant cause of wear in marine components, such as impellers, propellers or rudders. While the erosion process has been widely studied on metals, the effect of cavitation on polymers is not well-understood. The stress response in metals differs greatly from that of polymers, e.g. rate and temperature effects are far more important, thus damage and wear mechanisms of polymers under cavitating flows are significantly different. In this work, heat-driven failure caused by viscous dissipation and void nucleation resulting from tensile stresses arising from stress wave reflections are investigated as two possible material failure mechanisms.
As a first step in developing a fundamental understanding of the cavitation erosion process on polymer surfaces, simulations are performed of the collapse of individual bubbles against a compliant surface e.g. metallic substrates with polyurea coatings. The surface response of collapse-driven impact loads is represented by a idealized, time-dependent, Gaussian pressure distribution on the surface. A two-dimensional distribution of load radii and durations is considered corresponding to characteristic of cavitating flows accelerated erosion experiments. Finite element simulations are performed to fit a response curve that relates the loading parameters to the energy dissipated in the coating and integrated with collapse statistics to generate an expected heat input into the coating.
The impulsive pressure, which is generated due to bubble collapse, impacts the material and generates intense shock waves. The stress waves within the material reflects by interaction with the substrate. A transient region of high tensile stress is produced by the interaction of these waves. Simulations suggests that maximum hydrostatic tension which cause failure of polyurea layer is observed in thick coating. Also, the dissipated viscous energy and corresponding temperature rise in a polyurea is calculated, and it is concluded that temperature has influence on deformation.
As a first step in developing a fundamental understanding of the cavitation erosion process on polymer surfaces, simulations are performed of the collapse of individual bubbles against a compliant surface e.g. metallic substrates with polyurea coatings. The surface response of collapse-driven impact loads is represented by a idealized, time-dependent, Gaussian pressure distribution on the surface. A two-dimensional distribution of load radii and durations is considered corresponding to characteristic of cavitating flows accelerated erosion experiments. Finite element simulations are performed to fit a response curve that relates the loading parameters to the energy dissipated in the coating and integrated with collapse statistics to generate an expected heat input into the coating.
The impulsive pressure, which is generated due to bubble collapse, impacts the material and generates intense shock waves. The stress waves within the material reflects by interaction with the substrate. A transient region of high tensile stress is produced by the interaction of these waves. Simulations suggests that maximum hydrostatic tension which cause failure of polyurea layer is observed in thick coating. Also, the dissipated viscous energy and corresponding temperature rise in a polyurea is calculated, and it is concluded that temperature has influence on deformation.
ContributorsPanwar, Ajay (Author) / Oswald, Jay (Thesis advisor) / Dooley, Kevin (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2015
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 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