MODELING FUNCTIONAL DATA WITH SPATIALLY HETEROGENEOUS SHAPE CHARACTERISTICS

We propose a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial or temporal location. We use copulas so that the marginal distributions and the dependence structure can be modeled independently. Dependence is modeled with a Gaussian or t-copula, so that there is an underlying latent Gaussian process. We model the marginal distributions using the skew t family. The mean, variance, and shape parameters are modeled nonparametrically as functions of location. A computationally tractable inferential framework for estimating heterogeneous asymmetric or heavy-tailed marginal distributions is introduced. This framework provides a new set of tools for increasingly complex data collected in medical and public health studies. Our methods were motivated by and are illustrated with a state-of-the-art study of neuronal tracts in multiple sclerosis patients and healthy controls. Using the tools we have developed, we were able to find those locations along the tract most affected by the disease. However, our methods are general and highly relevant to many functional data sets. In addition to the application to one-dimensional tract profiles illustrated here, higher-dimensional extensions of the methodology could have direct applications to other biological data including functional and structural MRI.

Simulating dioxane transport in a heterogeneous glacial aquifer system (Washtenaw County, Michigan) using publicly available models and data

The primary challenge in groundwater and contaminant transport modeling is obtaining the data needed for constructing, calibrating and testing the models. Large amounts of data are necessary for describing the hydrostratigraphy in areas with complex geology. Increasingly states are making spatial data available that can be used for input to groundwater flow models. The appropriateness of this data for large-scale flow systems has not been tested. This study focuses on modeling a plume of 1,4-dioxane in a heterogeneous aquifer system in Scio Township, Washtenaw County, Michigan. The analysis consisted of: (1) characterization of hydrogeology of the area and construction of a conceptual model based on publicly available spatial data, (2) development and calibration of a regional flow model for the site, (3) conversion of the regional model to a more highly resolved local model, (4) simulation of the dioxane plume, and (5) evaluation of the model's ability to simulate field data and estimation of the possible dioxane sources and subsequent migration until maximum concentrations are at or below the Michigan Department of Environmental Quality's residential cleanup standard for groundwater (85 ppb). MODFLOW-2000 and MT3D programs were utilized to simulate the groundwater flow and the development and movement of the 1, 4-dioxane plume, respectively. MODFLOW simulates transient groundwater flow in a quasi-3-dimensional sense, subject to a variety of boundary conditions that can simulate recharge, pumping, and surface-/groundwater interactions. MT3D simulates solute advection with groundwater flow (using the flow solution from MODFLOW), dispersion, source/sink mixing, and chemical reaction of contaminants. This modeling approach was successful at simulating the groundwater flows by calibrating recharge and hydraulic conductivities. The plume transport was adequately simulated using literature dispersivity and sorption coefficients, although the plume geometries were not well constrained.

Modeling mechanical response of heterogeneous materials

Heterogeneous materials are ubiquitous in nature and as synthetic materials. These materials provide unique combination of desirable mechanical properties emerging from its heterogeneities at different length scales. Future structural and technological applications will require the development of advanced light weight materials with superior strength and toughness. Cost effective design of the advanced high performance synthetic materials by tailoring their microstructure is the challenge facing the materials design community. Prior knowledge of structure-property relationships for these materials is imperative for optimal design. Thus, understanding such relationships for heterogeneous materials is of primary interest. Furthermore, computational burden is becoming critical concern in several areas of heterogeneous materials design. Therefore, computationally efficient and accurate predictive tools are highly essential. In the present study, we mainly focus on mechanical behavior of soft cellular materials and tough biological material such as mussel byssus thread. Cellular materials exhibit microstructural heterogeneity by interconnected network of same material phase. However, mussel byssus thread comprises of two distinct material phases. A robust numerical framework is developed to investigate the micromechanisms behind the macroscopic response of both of these materials. Using this framework, effect of microstuctural parameters has been addressed on the stress state of cellular specimens during split Hopkinson pressure bar test. A voronoi tessellation based algorithm has been developed to simulate the cellular microstructure. Micromechanisms (microinertia, microbuckling and microbending) governing macroscopic behavior of cellular solids are investigated thoroughly with respect to various microstructural and loading parameters. To understand the origin of high toughness of mussel byssus thread, a Genetic Algorithm (GA) based optimization framework has been developed. It is found that two different material phases (collagens) of mussel byssus thread are optimally distributed along the thread. These applications demonstrate that the presence of heterogeneity in the system demands high computational resources for simulation and modeling. Thus, Higher Dimensional Model Representation (HDMR) based surrogate modeling concept has been proposed to reduce computational complexity. The applicability of such methodology has been demonstrated in failure envelope construction and in multiscale finite element techniques. It is observed that surrogate based model can capture the behavior of complex material systems with sufficient accuracy. The computational algorithms presented in this thesis will further pave the way for accurate prediction of macroscopic deformation behavior of various class of advanced materials from their measurable microstructural features at a reasonable computational cost.

Modeling spontaneous three-dimensional polymerization

For human beings, the origin of life has always been an interesting and mysterious matter, particularly how life arose from inorganic matter through natural processes. Polymerization is always involved in such processes. In this paper we built what we refer to as ideal and physical models to simulate spontaneous polymerization based on certain physical principles. As the modeling confirms, without taking external energy, small and simple inorganic molecules formed bigger and more complicated molecules, which are necessary ingredients of all living organisms. In our simulations, we utilized actual ranges of parameters according to their experimentally observed values. The results from the simulations led to a good agreement with the nature of polymerization. After sorting out through all the models that were built, we arrived at a final model that, it is hoped, can be used to simply and efficiently describe spontaneous polymerization using only three parameters: the dipole moment, the distance between molecules, and the temperature.

INVESTIGATING THE ROLE OF THE CONTACT LINE IN HETEROGENEOUS NUCLEATION WITH HIGH SPEED IMAGING

While nucleation of solids in supercooled liquids is ubiquitous [15, 65, 66], surface crystallization, the tendency for freezing to begin preferentially at the liquid-gas interface, has remained puzzling [74, 18, 68, 69, 51, 64, 72, 16]. Here we employ high-speed imaging of supercooled water drops to study the phenomenon of heterogeneous surface crystallization. Our geometry avoids the "point-like contact" of prior experiments by providing a simple, symmetric contact line (triple line defined by the substrate-liquid-air interface) for a drop resting on a homogeneous silicon substrate. We examine three possible mechanisms that might explain these laboratory observations: (i) Line Tension at the triple line, (ii) Thermal Gradients within the droplets and (iii) Surface Texture. In our first study we record nearly perfect spatial uniformity in the immersed (liquid-substrate) region and, thereby, no preference for nucleation at the triple line. In our second study, no influence of thermal gradients on the preference for freezing at the triple line was observed. Motivated by the conjectured importance of line tension (τ) [1, 66] for heterogeneous nucleation, we also searched for evidence of a transition to surface crystallization at length scales on the order of δ ∼ τ/σ, where σ is the surface tension [14]; poorly constrained τ [49] leads to δ ranging from microns to nanometers. We demonstrate that nano-scale texture causes a shift in the nucleation to the three-phase contact line, while micro-scale texture does not. The possibility of a critical length scale has implications for the effectiveness of nucleation catalysts, including formation of ice in atmospheric clouds [7].

DC MICROGRID STABILIZATION THROUGH FUZZY CONTROL OF INTERLEAVED, HETEROGENEOUS STORAGE ELEMENTS

As microgrid power systems gain prevalence and renewable energy comprises greater and greater portions of distributed generation, energy storage becomes important to offset the higher variance of renewable energy sources and maximize their usefulness. One of the emerging techniques is to utilize a combination of lead-acid batteries and ultracapacitors to provide both short and long-term stabilization to microgrid systems. The different energy and power characteristics of batteries and ultracapacitors imply that they ought to be utilized in different ways. Traditional linear controls can use these energy storage systems to stabilize a power grid, but cannot effect more complex interactions. This research explores a fuzzy logic approach to microgrid stabilization. The ability of a fuzzy logic controller to regulate a dc bus in the presence of source and load fluctuations, in a manner comparable to traditional linear control systems, is explored and demonstrated. Furthermore, the expanded capabilities (such as storage balancing, self-protection, and battery optimization) of a fuzzy logic system over a traditional linear control system are shown. System simulation results are presented and validated through hardware-based experiments. These experiments confirm the capabilities of the fuzzy logic control system to regulate bus voltage, balance storage elements, optimize battery usage, and effect self-protection.

Reaction Control in Quiescent Systems of Free-Radical Retrograde-Precipitation Polymerization

Free-radical retrograde-precipitation polymerization, FRRPP in short, is a novel polymerization process discovered by Dr. Gerard Caneba in the late 1980s. The current study is aimed at gaining a better understanding of the reaction mechanism of the FRRPP and its thermodynamically-driven features that are predominant in controlling the chain reaction. A previously developed mathematical model to represent free radical polymerization kinetics was used to simulate a classic bulk polymerization system from the literature. Unlike other existing models, such a sparse-matrix-based representation allows one to explicitly accommodate the chain length dependent kinetic parameters. Extrapolating from the past results, mixing was experimentally shown to be exerting a significant influence on reaction control in FRRPP systems. Mixing alone drives the otherwise severely diffusion-controlled reaction propagation in phase-separated polymer domains. Therefore, in a quiescent system, in the absence of mixing, it is possible to retard the growth of phase-separated domains, thus producing isolated polymer nanoparticles (globules). Such a diffusion-controlled, self-limiting phenomenon of chain growth was also observed using time-resolved small angle x-ray scattering studies of reaction kinetics in quiescent systems of FRRPP. Combining the concept of self-limiting chain growth in quiescent FRRPP systems with spatioselective reaction initiation of lithography, microgel structures were synthesized in a single step, without the use of molds or additives. Hard x-rays from the bending magnet radiation of a synchrotron were used as an initiation source, instead of the more statistally-oriented chemical initiators. Such a spatially-defined reaction was shown to be self-limiting to the irradiated regions following a polymerization-induced self-assembly phenomenon. The pattern transfer aspects of this technique were, therefore, studied in the FRRP polymerization of N-isopropylacrylamide (NIPAm) and methacrylic acid (MAA), a thermoreversible and ionic hydrogel, respectively. Reaction temperature increases the contrast between the exposed and unexposed zones of the formed microgels, while the irradiation dose is directly proportional to the extent of phase separation. The response of Poly (NIPAm) microgels prepared from the technique described in this study was also characterized by small angle neutron scattering.

SYNTHETIC OLIGODEOXYNUCLEOTIDE PURIFICATION VIA CATCHING BY POLYMERIZATION

Large quantities of pure synthetic oligodeoxynucleotides (ODNs) are important for preclinical research, drug development, and biological studies. These ODNs are synthesized on an automated synthesizer. It is inevitable that the crude ODN product contains failure sequences which are not easily removed because they have the same properties as the full length ODNs. Current ODN purification methods such as polyacrylamide gel electrophoresis (PAGE), reversed-phase high performance liquid chromatography (RP HPLC), anion exchange HPLC, and affinity purification can remove those impurities. However, they are not suitable for large scale purification due to the expensive aspects associated with instrumentation, solvent demand, and high labor costs. To solve these problems, two non-chromatographic ODN purification methods have been developed. In the first method, the full-length ODN was tagged with the phosphoramidite containing a methacrylamide group and a cleavable linker while the failure sequences were not. The full-length ODN was incorporated into a polymer through radical acrylamide polymerization whereas failure sequences and other impurities were removed by washing. Pure full-length ODN was obtained by cleaving it from the polymer. In the second method, the failure sequences were capped by a methacrylated phosphoramidite in each synthetic cycle. During purification, the failure sequences were separated from the full-length ODN by radical acrylamide polymerization. The full-length ODN was obtained via water extraction. For both methods, excellent purification yields were achieved and the purity of ODNs was very satisfactory. Thus, this new technology is expected to be beneficial for large scale ODN purification.