Hypoplastic left heat syndrome (HLHS) is a complex cardiac malformation in neonates suffering from congenital heart disease and occurs in nearly 1 per 5000 births. HLHS is uniformly fatal within the first hours or days after birth as the severly malformed anatomies of the left ventricle, mitral, and aortic valves, and ascending aorta are not compatable with life. The regularly implemented treatment, the Norwood operation, is a complex open heart procedure that attempts to establish univenticular circulation by removing the atrial septum ( communicating the right and left ventricle), reconstructing the malformed aortic arch, and connecting the main pulmonary artery into the reconstructed arch to allow direct perfusion from the right ventricle into the systemic circulation. A relatively new treatment being utilized,the Hybrid Norwood procedure, involves a less invasive strategy to establish univentricular circulation that avoids a cardiopulmonary bypass (heart-lung machine), deliberate cardiac arrest, and circulatroy arrest of the patient during the procedure. The resulting systemic-pulmonary circulation is unconventional; blood is pumped simotaneously and in parallel to the systemic and pulmonary arteries after the procedure. Cardiac surgeons are deeply interested in understanding the global and local hemodynamics of this anotomical configuration. To this end, a multiscale model of the entire circulatory system was developed utilizing an electrical lumped parameter model for the peripheralor distal circulation coupled with a #D Computational Fluid Dynamics (CFD) model to understand the local hemodynamics. The lumped parameter (LP) model is mainly a closed loop circut comprised of RLC comartments that model cardiac function as well as the viscous drag, flow intertia, and compliance of the different atrial and venous beds in the body. A system of 32 first-order differential equations is formulated and solved for the LP model using a fourth-order adaptive Runge-Kutta solver. The output pressure and flow waveforms obtained from the LP model are imposed as boundary conditions on the CFD model. Coupling of the two models is done through an iterative process where the parameters in the LP model are adjusted to match the CFD solution. The CFD model domain is a representative HLHS anatomy of an infant after undergoing the Hybrid Norwood procedure and is comprised of the neo-aorta, pulmonary roots, aortic arch with branching arteries, and pulmonary arteries. The flow field is solved over several cardiac cycles using an implicit-unsteady RANS equation solver with the k-epsilon turbulence model.; Hypoplastic left heart syndrome (HLHS) is a complex cardiac malformation in neonates suffering from congenital heart disease and occurs in nearly 1 per 5000 births. HLHS is uniformly fatal within the first hours or days after birth as the severely malformed anatomies of the left ventricle, mitral and aortic valves, and ascending aorta are not compatible with life. The regularly implemented treatment, the Norwood operation, is a complex open heart procedure that attempts to establish univentricular circulation by removing the atrial septum (communicating the right and left ventricle), reconstructing the malformed aortic arch, and connecting the main pulmonary artery into the reconstructed arch to allow direct perfusion from the right ventricle into the systemic circulation. A relatively new treatment being utilized, the Hybrid Norwood procedure, involves a less invasive strategy to establish univentricular circulation that avoids a cardiopulmonary bypass (heart-lung machine), deliberate cardiac arrest, and circulatory arrest of the patient during the procedure. The resulting systemic-pulmonary circulation is unconventional; blood is pumped simultaneously and in parallel to the systemic and pulmonary arteries after the procedure. Cardiac surgeons are deeply interested in understanding the global and local hemodynamics of this anatomical configuration. To this end, a multiscale model of the entire circulatory system was developed utilizing an electrical lumped parameter model for the peripheral or distal circulation coupled with a 3D Computational Fluid Dynamics (CFD) model to understand the local hemodynamics. The lumped parameter (LP) model is mainly a closed loop circuit comprised of RLC compartments that model cardiac function as well as the viscous drag, flow inertia, and compliance of the different arterial and venous beds in the body.

Iron-based ferritic alloys are used for a plethora of industrial applications. These alloys contain foreign atoms purposely employed to improve certain properties as well as some unwanted impurities introduced during fabrication. Materials properties are decisively influenced by diffusion processes. Very often diffusion cannot be avoided during fabrication and application. Therefore, many efforts are made to understand the underlying atomic-level mechanisms by both experimental and theoretical investigations. In this thesis work a multiscale modelling approach is used to study oxygen and vacancy diffusion in dilute ferritic iron alloys. Due to the extremely low solubility of oxygen the measurement of oxygen diffusion in iron is difficult. Only few experimental data are available. Experimental investigation of vacancy migration is still more complicated. The lack of reliable experimental data is therefore an important motivation for theoretical investigations. Gaining fundamental data on oxygen and vacancy diffusion in dilute iron alloys is essential for many applications. Oxygen plays a crucial role in the corrosion of iron-based alloys. Oxygen and the vacancy are also important in the formation and evolution of Y-Ti-O nanoclusters in oxide dispersion strengthened ferritic Fe-Cr alloys, which are considered as promising candidates for structural materials of future fusion and fission reactors. Furthermore, vacancies are formed during neutron and ion irradiation and their diffusion affects radiation-induced nanostructure formation in ferritic alloys. In the first part of this thesis work, the diffusion of interstitial oxygen under the influence of substitutional atoms or solutes (Al, Si, P, S, Ti, Cr, Mn, Ni, Y, Mo and W) in bcc Fe is investigated by the combination of Density Functional Theory (DFT) and Atomistic Kinetic Monte Carlo (AKMC) simulations. The substitutional atoms are assumed to be immobile because oxygen diffusion is much faster than that of the solutes. DFT is applied to gain data on binding energies between interstitial oxygen and the substitutional foreign atoms, and to calculate the migration barriers for oxygen in the environment of the solutes. Using the migration barriers obtained by DFT, the diffusion coefficient of oxygen is determined by AKMC simulation. It is found that Si, P, Ni, Mo, and W have negligible influence on the oxygen diffusion coefficient. Al, Cr, Mn, S, Ti, and Y cause a considerable reduction of oxygen mobility. In these cases, the temperature dependence of oxygen diffusivity shows deviations from Arrhenius behavior. This is explained in detail by the significant temperature dependence of the ratio between residence times in the respective states. In the second part of the work a method is presented which allows for an efficient calculation of the diffusion coefficient of oxygen and other interstitial atoms in dilute alloys. The method is applied to examples considered in the first part of the work. The calculation procedure is based on the separation of the diffusion path into a contribution related to migration in the interaction region between the mobile interstitial and the substitutional solute and another part related to diffusion in perfect bcc Fe. In this manner AKMC simulation must be performed only for one concentration of the substitutional solute, and the obtained results can be employed to obtain data for other concentrations using analytical expressions containing binding energies between the interstitial and the substitutional solute. The focus of third part of the work is on the mutual dependence of oxygen and vacancy diffusion in bcc Fe and dilute iron alloys. Here both O and v must be considered as mobile while the substitutional atoms are assumed to be immobile. DFT is applied to determine the binding energy between O and v for different distances, the migration barriers for O in the environment of v, and the corresponding barriers of v in the vicinity of O. In agreement with previous work O and v have a very strong binding at the 1st neighbor distance. On the other hand, the calculations show that the Ov pair at the 6th neighbor distance is instable. The newly found simultaneous or coupled jumps of both O and v compensate the lack of jump paths that would occur due to this instability. The DFT results are employed to determine the diffusion coefficient of O and v using the scheme of the AKMC-based calculation method presented in the second part of the thesis work. At first a model system with fixed O and v concentrations is studied. It is found that a small v content of some ppm can already lead to a strong reduction of the O diffusivity. A similar effect is obtained for v diffusion under the influence of O. Furthermore, investigations on the interdependence of O and v diffusion during thermal processing of oxide dispersion strengthened iron alloys are performed, and the influence of the substitutional atoms Y and Ti is studied. A simple thermodynamic model is employed to determine the concentration of O, Y, and Ti monomers as well as the total v concentration, for a typical total content of O, Y, and Ti. These results are used in calculations of the diffusion coefficients of O and v. Not only a strong mutual dependence but also a significant influence of Y on O diffusion is found. Finally, O and v diffusivities in a system with a total O content close to the thermal solubility are calculated. The monomer O concentration as well as the total v concentration was determined using two different models considering equilibrium of O and v with Ov, or equilibrium of O and v with Ov and O2v or Ov2. Despite the very small value of thermal solubility of O in bcc Fe, both the O and v diffusion coefficient are very different from that in pure iron. Even for such a low amount of O in the alloy the diffusion coefficients differ strongly from those in perfect bcc Fe. The results of the present work have important consequences for planning and performing new experiments on O and v diffusion in dilute iron alloys. In particular, a very precise knowledge of the concentrations of O and v, as well as of other foreign atoms and traps such as dislocations is required.

<p>Long-acting injectables (LAI) offer many practical benefits for patients in improving drug adherence to therapies for chronic diseases. LAI, administered either subcutaneously (SC) or intramuscularly (IM), can improve drug bioavailability, and reduce frequency of administration as well as regimen complexity. SC also has additional benefits over IM injections as being safer, less painful, and able to be administered at home. However, development and translation of these products into the clinic is often limited because of physiological complexity at injection site, such that absorption rate mechanisms are not well understood. Common predictive and correlative methods used in oral formulations, such as <em>in vitro-in vivo </em>correlations, are not well suited for SC physiology and are only capable of measuring a few parameters at a time, meaning relationships between parameters cannot be discriminately measured.</p> <p><br></p> <p>This project seeks to address this gap in knowledge by using computation to bridge the gap between suboptimal preclinical testing methods and human pharmacokinetic data. A Multiscale framework was developed by integrating a first-principles Multiphysics model of the SC space to experimental plasma concentration profiles using simulated absorption rates. First, our lab’s previous framework for lymphatic absorption of monoclonal antibodies (mAbs) was converted into small molecule absorption into the capillaries. Drug and formulation critical quality attributes (CQA) were determined for a solution injection of methotrexate, and a nanocrystal formulation of medroxyprogesterone acetate (MPA, Depo-SubQ Provera). Two dissolution models were incorporated to compare the difference between using average particle size (Noyes-Whitney) and particle size distributions (Population Balance Model, PBM) as CQA for nanocrystal LAI specifically. Absorption rates were validated using compartmental pharmacokinetic models, and sensitivity analyses were conducted to determine model parametric sensitivity. Overall, the modeling framework was able to determine the importance of and discriminate the effect of parameters on SC absorption rates. </p>

Many experiments demonstrate that the effects of hydrogen solutes decrease macroscopic fracture stresses and strains in ductile materials. Hydrogen-related failures have occurred in nearly all industries involving hydrogen-producing environments. The financial losses incurred from those failures reaches millions if not billions of dollars annually. With the ever-urgent needs for alternative energy sources, there is a strong push for a hydrogen economy from government and private sectors. Safe storage and transportation of hydrogen increases the momentum for studying hydrogen-related failures, especially in ductile materials. To quantify ductile material damage with the effects of hydrogen embrittlement, it is necessary to add hydrogen effects into the void nucleation, void growth, and void coalescence equations. In this research, hydrogen-enhanced void nucleation is our focus, with hydrogen-enhanced void growth and void coalescence t be studied in the future. Molecular Dynamic (MD) and Monte Carlo (MC) simulations with Embedded Atom Method (EAM) potentials were performed to study how hydrogen affects dislocation nucleation, dislocation structure formation and nanovoid nucleation at nickel grain boundaries. The results were inserted into the continuum void nucleation model by Horstemeyer and Gokhale, and the relationships between stress triaxiality-driven void nucleation, grain boundary hydrogen concentrations and local grain geometries were extracted. MD and MC simulations with EAM potentials were also performed to study how hydrogen interstitials affect the dislocation nucleation, dislocation structure formation and subsequent anovoid nucleation of single crystal nickel in different hydrogen-charging conditions. Evolutions of dislocation structures of nickel single crystal with different hydrogen concentrations were compared. The effects of nanovoid nucleation stress and strain at different hydrogen concentrations were quantified. The results were also inserted into the Horstemeyer and Gokhale model and the relationship between stress triaxiality-driven void nucleation and hydrogen concentration caused by stress gradient, which showed similar trends as the grain boundary studies. From nanoscale studies and existing experimental observations, a continuum void nucleation model with hydrogen effects was proposed and used in a continuum damage model based upon Bammann and coworkers. The damage model was implemented into user material code in FEA code ABAQUS. Finite element analyses were performed and the results were compared to the experimental data by Kwon and Asaro.

No description available.

No description available.

For simple fluids, or Newtonian fluids, the study of the Navier-Stokes equations in the high Reynolds number limit brings about two fundamental research subjects, the Euler equations and the Prandtl's system. The consideration of infinite Reynolds number reduces the Navier-Stokes equations to the Euler equations, both of which are dealing with the entire flow region. Prandtl's system consists of the governing equations of the boundary layer, a thin layer formed at the wall boundary where viscosity cannot be neglected. In this dissertation, we investigate the upper convected Maxwell(UCM) model for complex fluids, or non-Newtonian fluids, in the high Weissenberg number limit. This is analogous to the Newtonian fluids in the high Reynolds number limit. We present two well-posedness results. The first result is on an initial-boundary value problem for incompressible hypoelastic materials which arise as a high Weissenberg number limit of viscoelastic fluids. We first assume the stress tensor is rank-one and develop energy estimates to show the problem is locally well-posed. Then we show the more general case can be handled in the same spirit. This problem is closely related to the incompressible ideal magneto-hydrodynamics (MHD) system. The second result addresses the formulation of a time-dependent elastic boundary layer through scaling analysis. We show the well-posedness of this boundary layer by transforming to Lagrangian coordinates. In contrast to the possible ill-posedness of Prandtl's system in Newtonian fluids, we prove that in non-Newtonian fluids the stress boundary layer problem is well-posed. / Ph. D.

Ionomeric polymer transducers exhibit electromechanical coupling capabilities. The transport of charge due to electric stimulus is the primary mechanism of actuation for a class of polymeric active materials known as ionomeric polymer transducers (IPTs). The research presented in this dissertation focuses on modeling the cation transport and cation steady state distribution due to the actuation of an IPT. Ion transport in the IPT depends on the morphology of the hydrated Nafion membrane and the morphology of the metal electrodes. Recent experimental findings show that adding conducting powders at the polymer-conductor interface increases the displacement output. However, it is difficult for a traditional continuum model based on transport theory to include morphology in the model. In this dissertation, a two-dimensional Monte Carlo simulation of ion hopping has been developed to describe ion transport in materials that have fixed and mobile charge similar to the structure of the ionic polymer transducer. In the simulation, cations can hop around in a square lattice. A step voltage is applied between the electrodes of the IPT, causing the thermally-activated hopping between multiwell energy structures. By sampling the ion transition time interval as a random variable, the system evolution is obtained. Conducting powder spheres have been incorporated into the Monte Carlo simulation. Simulation results demonstrate that conducting powders increase the ion conductivity. Successful implementation of parallel computation makes it possible for the simulation to include more powder spheres to find out the saturation percentage of conducting powders for the ion conductivity. To compare simulation results with experimental data, a multiscale model has been developed to increase the scale of Monte Carlo simulation. Both transient responses and steady state responses show good agreement with experimental measurements. / Ph. D.

The accurate and efficient numerical simulation of geophysical flows is of great interest in numerical weather prediction and climate modeling as well as in numerous critical areas and industries, such as agriculture, construction, tourism, transportation, weather-related disaster management, and sustainable energy technologies. Oceanic and atmospheric flows display an enormous range of temporal and spatial scales, from seconds to decades and from centimeters to thousands of kilometers, respectively. Scale interactions, both spatial and temporal, are the dominant feature of all aspects of general circulation models in geophysical fluid dynamics. In this thesis, to decrease the cost for these geophysical flow computations, several types of multiscale methods were systematically developed and tested for a variety of physical settings including barotropic and stratified wind-driven large scale ocean circulation models, decaying and forced two-dimensional turbulence simulations, as well as several benchmark incompressible flow problems in two and three dimensions. The new models proposed here are based on two classes of modern multiscale methods: (i) interpolation based approaches in the context of the multigrid/multiresolution methodologies, and (ii) deconvolution based spatial filtering approaches in the context of large eddy simulation techniques. In the first case, we developed a coarse-grid projection method that uses simple interpolation schemes to go between the two components of the problem, in which the solution algorithms have different levels of complexity. In the second case, the use of approximate deconvolution closure modeling strategies was implemented for large eddy simulations of large-scale turbulent geophysical flows. The numerical assessment of these approaches showed that both the coarse-grid projection and approximate deconvolution methods could represent viable tools for computing more realistic turbulent geophysical flows that provide significant increases in accuracy and computational efficiency over conventional methods. / Ph. D.

The goal of this research is developing a computational framework to study mechanical fatigue and fracture at different length scales for a broad range of materials. The developed multiscale framework is utilized to study the details of fracture and fatigue for the rolling contact in rails, additively manufactured alloys, and bio-inspired hierarchical materials. Rolling contact fatigue (RCF) is a major source of failure and a dominant cause of maintenance and replacements in many railways around the world. The highly-localized stress in a relatively small contact area at the wheel-rail interface promotes micro-crack initiation and propagation near the surface of the rail. 2D and 3D microstructural-based computational frameworks are developed for studying the rolling contact fatigue in rail materials. The method can predict RCF life and simulate crack initiation sites under various conditions. The results obtained from studying RCF behavior in different conditions will help better maintenance of the railways and increase the safety of trains. The developed framework is employed to study the fracture and fatigue behavior in 3D printed metallic alloys fabricated by selective laser melting (SLM) method. SLM method as a part of metal additive manufacturing (AM) technologies is revolutionizing the manufacturing sector and is being utilized across a diverse array of industries, including biomedical, automotive, aerospace, energy, consumer goods, and many others. Since experiments on 3D printed alloys are considerably time-consuming and expensive, computational analysis is a proper alternative to reduce cost and time. In this research, a computational framework is developed to study fracture and fatigue in different scales in 3D printed alloys fabricated by the SLM method. Our method for studying the fatigue at the microstructural level of 3D printed alloys is pioneering with no similar work being available in the literature. Our studies can be used as a first step toward establishing comprehensive numerical frameworks to investigate fracture and fatigue behavior of 3D metallic devices with complex geometries, fabricated by 3D printing. Composite materials are fabricated by combining the attractive mechanical properties of materials into one system. A combination of materials with different mechanical properties, size, geometry, and order of different phases can lead to fabricating a new material with a wide range of properties. A fundamental problem in engineering is how to find the design that exhibits the best combination of these properties. Biological composites like bone, nacre, and teeth attracted much attention among the researchers. These materials are constructed from simple building blocks and show an uncommon combination of high strength and toughness. By inspiring from simple building blocks in bio-inspired materials, we have simulated fracture behavior of a pre-designed composite material consisting of soft and stiff building blocks. The results show a better performance of bio-inspired composites compared to their building blocks. Furthermore, an optimization methodology is implemented into the designing the bio-inspired composites for the first time, which enables us to perform the bio-inspired material design with the target of finding the most efficient geometries that can resist defects in their structure. This study can be used as an effective reference for creating damage-tolerant structures with improved mechanical behavior. / Doctor of Philosophy / The goal of this research is developing a multiscale framework to study the details of fracture and fatigue for the rolling contact in rails, additively manufactured alloys, and bio-inspired hierarchical materials. Rolling contact fatigue (RCF) is a major source of failure and a dominant cause of maintenance and replacements in many railways around the world. Different computational models are developed for studying rolling contact fatigue in rail materials. The method can predict RCF life and simulate crack initiation sites under various conditions and the results will help better maintenance of the railways and increase the safety of trains. The developed model is employed to study the fracture and fatigue behavior in 3D printed metals created by the selective laser melting (SLM) method. SLM method as a part of metal additive manufacturing (AM) technologies is revolutionizing industries including biomedical, automotive, aerospace, energy, and many others. Since experiments on 3D printed metals are considerably time-consuming and expensive, computational analysis is a proper alternative to reduce cost and time. Our method for studying the fatigue at the microstructural level of 3D printed alloys can help to create more fatigue and fracture resistant materials. In the last section, we have studied fracture behavior in bio-inspired materials. A fundamental problem in engineering is how to find the design that exhibits the best combination of mechanical properties. Biological materials like bone, nacre, and teeth are constructed from simple building blocks and show a surprising combination of high strength and toughness. By inspiring from these materials, we have simulated fracture behavior of a pre-designed composite material consisting of soft and stiff building blocks. The results show a better performance of bio-inspired structure compared to its building blocks. Furthermore, an optimization method is implemented into the designing the bio-inspired structures for the first time, which enables us to perform the bio-inspired material design with the target of finding the most efficient geometries that can resist defects in their structure.