Estimating groundwater nitrate fate and transport is an important task in water resources and environmental management because excess nitrate loads may have negative impacts on human and environmental health. This work discusses the development of a simplified nitrate transport model and its implementation as a geographic information system (GIS)-based screening tool, whose purpose is to estimate nitrate loads to surface water bodies from onsite wastewater-treatment systems (OWTS). Key features of this project are the reduced data demands due to the use of a simplified model, as well as ease of use compared to traditional groundwater flow and transport models, achieved by embedding the model within a GIS. The simplified conceptual model consists of a simplified groundwater flow model in the surficial aquifer, and a simplified transport model that makes use of an analytical solution to the advection-dispersion equation, used for determining nitrate fate and transport. Denitrification is modeled using first order decay in the analytical solution with the decay constant obtained from literature and/or site-specific data. The groundwater flow model uses readily available topographic data to approximate the hydraulic gradient, which is then used to calculate seepage velocity magnitude and direction. The flow model is evaluated by comparing the results to a previous numerical modeling study of the U.S. Naval Air Station, Jacksonville (NAS) performed by the USGS. The results show that for areas in the vicinity of the NAS, the model is capable of predicting groundwater travel times from a source to a surface water body to within ±20 years of the USGS model, 75% of the time. The transport model uses an analytical solution based on the one by Domenico and Robbins (1985), the results of which are then further processed so that they may be applied to more general, real-world scenarios. The solution, as well as the processing steps are tested using artificially constructed scenarios, each meant to evaluate a certain aspect of the solution. For comparison purposes, each scenario is solved using a well known numerical contaminant transport model. The results show that the analytical solution provides a reasonable approximation to the numerical result. However, it generally underestimates the concentration distribution to varying degrees depending on choice of parameters, especially along the plume centerline. These results are in agreement with previous studies (Srinivasan et al., 2007; West et al., 2007). The adaptation of the analytical solution to more realistic scenarios results in an adequate approximation to the numerically calculated plume, except in areas near the advection front, where the model produces a plume whose shape differs noticeably from the numerical solution. Load calculations are carried out using a mass balance approach where the system is considered to be in the steady state. The steady-state condition allows for a load estimate by subtracting the mass removal rate due to denitrification from the input mass rate. The input mass rate is calculated by taking into account advection and dispersion while the mass removal rate due to denitrification is calculated from the definition of a first order reaction. Comparison with the synthetic scenarios of the transport model shows that for the test cases, when decay rates are low, the model agrees well with the load calculation from the numerical model. As decay rates increase and the plume becomes shorter, the input load is overestimated by about 9% in the test cases and the mass removed due to denitrification is underestimated by 30% in the worst case. These results are likely due to the underestimation of concentration values by the analytical solution of the transport model. / A Thesis Submitted to the Department of Scientific Computing in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Fall Semester, 2010. / October 22, 2010. / Simplified model, Denitrification, OWTS, GIS, Septic tank, Contaminant transport, Nitrate contamination / Includes bibliographical references. / Ming Ye, Professor Directing Thesis; Janet Peterson, Committee Member; Sachin Shanbhag, Committee Member; James Wilgenbusch, Committee Member.

In this thesis, we discuss the development of a new Boids system that simulates flocking behavior inside the Blender Game Engine and within the framework of the Real-Time Par- ticles System (RTPS) library developed by Ian Johnson. The collective behavior of Boids is characterized as an emergent behavior caused by following three steering behaviors: sep- aration, alignment, and cohesion. The implementation leverages OpenCL to maintain the portability of the Blender across different graphics cards and operating systems. Bench- marks of the RTPS-FLOCK system show that our implementation speeds up Blender's original Boids implementation (which only runs outside the game engine) by more than an order of magnitude. We demonstrate our boids system in three ways. First, we illustrate how symmetry of the steering behavior is maintained in time. Second, we consider the behavior of a "swarm of bees" approaching their hive. And third, we simulate the motion of a "crowd" constrained to a two-dimensional plane. / A Thesis Submitted to the Department of ScientifiC Computing in Partial FulfiLlment of the Requirements for the Degree of Master of Science. / Summer Semester, 2011. / June 24, 2011. / RTPS, Blender, boids, flocking / Includes bibliographical references. / Gordon Erlebacher, Professor Directing Thesis; Ming Ye, Committee Member; Xiaoqiang Wang, Committee Member.

Prediction markets have been demonstrated to be accurate predictors of the outcomes of future events. They have been successfully used to predict the outcomes of sporting events, political elections and even business decisions. Their prediction accuracy has even outperformed the accuracy of other prediction methods such as polling. As an attempt to reproduce their predictive capability, a machine learning model of prediction markets is developed herein for classification. This model is a novel classifier aggregation technique that generalizes linear aggregation techniques. This prediction market aggregation technique is shown to outperform or match Random Forest on both artificial and real data sets. The notion of specialization is also developed and explored herein. This leads to a new kind of classifier referred to as a specialized classifier. These specialized classifiers are shown to improve the accuracy of prediction market aggregation even to perfection. / A Thesis submitted to the Department of ScientifiC Computing in partial fulfillment of the requirements for the degree of Master of Science. / Fall Semester, 2009. / November 5, 2009. / Machine Learning, Aggregation, Random Forest / Includes bibliographical references. / Adrian Barbu, Professor Directing Thesis; Anke Meyer-Baese, Committee Member; Tomasz Plewa, Committee Member.

We are exploring the effect of using various vertical mixing closures on resolving the physical process known as overflow. This is when cold dense water overflows from a basin in the ocean. This process is responsible for the majority of the Ocean's dense water transport, and also creates many of the dense water currents that are part of what is known as the Ocean Conveyor Belt. One of the main places this happens is in the North Atlantic, in the Denmark strait and the Faroe Bank Sea Channel. To simulate this process, two ocean models are used, the Parallel Ocean Program (POP) and the hybrid-coordinate Parallel Ocean Program (HyPOP). Using these models, differences are observed in three main vertical mixing schemes Constant, Richardson Number, and KPP. Though, not included in this thesis the research also explores three different vertical griding schemes, Z-Grid, Sigma Coordinate, and Isopycnal grids. The goal is to attempt to determine which combination gives the most acceptable results for resolving the overflow process. This is motivated by the large role this process plays in the ocean, as well as the difficulty in modeling this process. If an ocean model cannot accurately simulate overflow, then a large portion of the ocean model will be incorrect and one cannot hope to get reasonable results for long simulations out of it. / A Thesis submitted to the Department of ScientifiC Computing in partial fulfillment of the requirements for the degree of Master of Science. / Fall Semester, 2009. / November 6, 2009. / Overflow, Ocean Modeling, Vertical Mixing, Viscosity, Diffusion / Includes bibliographical references. / Max Gunzburger, Professor Directing Thesis; Gordon Erlebacher, Committee Member; Janet Peterson, Committee Member.

Spherical centroidal Voronoi tessellations (SCVT) are used in many applications in a variety of fields, one being climate modeling. They are a natural choice for spatial discretizations on the surface of the Earth. New modeling techniques have recently been developed that allow the simulation of ocean and atmosphere dynamics on arbitrarily unstructured meshes, including SCVTs. Creating ultra-high resolution SCVTs can be computationally expensive. A newly developed algorithm couples current algorithms for the generation of SCVTs with existing computational geometry techniques to provide the parallel computation of SCVTs and spherical Delaunay triangulations. Using this new algorithm, computing spherical Delaunay triangulations shows a speed up on the order of 4000 over other well known algorithms, when using 42 processors. As mentioned previously, newly developed numerical models allow the simulation of ocean and atmosphere systems on arbitrary Voronoi meshes providing a multi-resolution modeling framework. A multi-resolution grid allows modelers to provide areas of interest with higher resolution with the hopes of increasing accuracy. However, one method of providing higher resolution lowers the resolution in other areas of the mesh which could potentially increase error. To determine the effect of multi-resolution meshes on numerical simulations in the shallow-water context, a standard set of shallow-water test cases are explored using the Model for Prediction Across Scales (MPAS), a new modeling framework jointly developed by the Los Alamos National Laboratory and the National Center for Atmospheric Research. An alternative approach to multi-resolution modeling is Adaptive Mesh Refinement (AMR). AMR typically uses information about the simulation to determine optimal locations for degrees of freedom, however standard AMR techniques are not well suited for SCVT meshes. In an effort to solve this issue, a framework is developed to allow AMR simulations on SCVT meshes within MPAS. The resulting research contained in this dissertation ties together a newly developed parallel SCVT generator with a numerical method for use on arbitrary Voronoi meshes. Simulations are performed within the shallow-water context. New algorithms and frameworks are described and bench-marked. / A Dissertation submitted to the Department of ScientifiC Computing in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester, 2011. / June 14, 2011. / spherical centroidal voronoi tessellation, grid generation, high performance computing, spherical delaunay triangulation, adaptive mesh refinement, shallow-water equations, ocean modeling / Includes bibliographical references. / Max Gunzburger, Professor Directing Thesis; Doron Nof, University Representative; Janet Peterson, Committee Member; Gordon Erlebacher, Committee Member; Michael Navon, Committee Member; John Burkardt, Committee Member; Todd Ringler, Committee Member.

Over the past decade, Web Services have played a prominent role in the Internet area and in the business world. My interest is focused on developing the toolkits for automatic web service and graphical user interface (GUI) generation, KWATT. The standalone KWATT service generator(KSG) is a C++ application that generates web services from Tcl, Python, and Ruby scripts uploaded by end user with KGT(Kwatt Gui Tools), with minimal user intervention. KSG Parser parses the scripts and extracts information about procedures and user-defined control statements, embedded as comments. The KSG creates all necessary C++ wrappers, along with the code stubs required by gSOAP, a C++ interface to the SOAP protocol. Initially conceived to translate VTK front-end Tcl scripts into Web Services, the architecture is sufficiently general to accommodate a wide range of input languages. The work is extanded by considering the automatic creation of graphical user interfaces to allow interaction between an end user and the web service generated by the KSG. Kwatt GUI Generator(KGG) was developed to achieve this. The KGG is a web service that runs inside a service of Java-based open source, and it performs four major steps of GUI generation. First, the KGG receives the scripts from KGT (KWATT GUI Tools) after the corresponding web service generated successfully. Comment lines inserted into the scripts provide hints to the XML generator about the interface widgets. Second, the structure of the GUI is encoded into an XML file by parsing those scripts with the XML generator. Third, the KGG extracts information from the generated XML file, then passes them to a plugin. Finally, the plugin generates the corresponding language user interface that is sent back to the user by the KGG. / A Thesis submitted to the Department of Scientific Computing in partial fulfillment of the requirements for the degree of Master of Science. / Summer Semester, 2009. / July 27, 2009. / GUI, Web Service, SOAP / Includes bibliographical references. / Gordon Erlebacher, Professor Directing Thesis; Ming Ye, Committee Member; Xiaoqiang Wang, Committee Member.

This work implements inverse methods in various polymer characterization problems. In the first topic, a new approach is proposed to infer the comonomer content using Crystaf method considering and quantifying the associated uncertainty. In the second topic, a comparison is carried out between various rheological probes (methods) to determine their sensitivity in long-chain branching (LCB) detection and measurement. In the last topic, an open-source software is implemented to infer continuous and discrete relaxation modulus. / A Dissertation submitted to the Department of Scientific Computing in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester, 2014. / May 29, 2014. / Characterization, Inverse methods, Polymer, Uncertainty Quantification / Includes bibliographical references. / Sachin Shanbhag, Professor Directing Dissertation; William Oates, University Representative; Anke Meyer-Baese, Committee Member; Peter Beerli, Committee Member; Jim Wilgenbusch, Committee Member.

No description available.

This dissertation presents a duality theorem of the Aubin-Nitsche type for discontinuous Petrov Galerkin (DPG) methods. This explains the numerically observed higher convergence rates in weaker norms. Considering the specific example of the mild-weak (or primal) DPG method for the Laplace equation, two further results are obtained. First, for triangular meshes, the DPG method continues to be solvable even when the test space degree is reduced, provided it is odd. Second, a non-conforming method of analysis is developed to explain the numerically observed convergence rates for a test space of reduced degree. Finally, for rectangular meshes, the test space is reduced, yet the convergence is recovered regardless of parity.

Magnetic nanoparticles (NPs) with sizes ranging from 2 to 20 nm in diameter represent an important class of artificial nanostructured materials, since the NP size is comparable to the size of a magnetic domain. They have potential applications in data storage, catalysis, permanent magnetic nanocomposites, and biomedicine. To begin with, a brief overview on the background of Fe-based bimetallic NPs and their applications for data-storage and catalysis was presented in Chapter 1. In Chapter 2, L10-ordered FePt NPs with high coercivity were directly prepared from a novel bimetallic acetylenic alternating copolymer P3 by a one-step pyrolysis method without post-thermal annealing. The chemical ordering, morphology and magnetic properties were studied. Magnetic measurements showed that a record coercivity of 3.6 T (1 T = 10 kOe) was obtained in FePt NPs. By comparison of the resultant FePt NPs synthesized under Ar and Ar/H2, the characterization proved that the incorporation of H2 would affect the nucleation and promote the growth of FePt NPs. The L10 FePt NPs were also successfully patterned on Si substrate by nanoimprinting lihthography (NIL). The highly ordered ferromagnetic arrays on a desired substrate for bit-patterned media (BPM) were studied and promised bright prospects for the progress of data-storage. Furthermore, we also reported a new FePt-containing metallopolymer P4 as the single-source precursor for metal alloy NPs synthesis, where the metal fractions were on the side chain and the ratio could be easily controlled. This polymer was synthesized from random copolymer poly(styrene-4-ethynylstyrene) PES-PS and bimetallic precursor TPy-FePt ([Pt(4’-ferrocenyl-(N^N^N))Cl]Cl) by Sonogashira coupling reaction. After pyrolysis of P4, the stoichiometry of Fe and Pt atoms in the synthesized NPs (NPs) is nearly close to 1:1, which is more precise than using TPy-FePt as precursor. Polymer P4 was also more favorable for patterning by high throughout NIL as compared to TPy-FePt. Ferromagnetic nanolines, potentially as bit-patterned magnetic recording media, were successfully fabricated from P4 and fully characterized. In Chapter 3, a novel organometallic compound TPy-FePd-1 [4’-ferrocenyl-(N^N^N)PdOCOCH3] was synthesized and structurally characterized, whose crystal structure showed a coplanar Pd center and Pd-Pd distance (3.17 Å). Two metals Fe and Pd were evenly embedded in the molecular dimension and remained tightly coupled between each other benefiting to the metalmetal (Pd-Pd) and ligand ππ stacking interactions, all of which made it facilitate the nucleation without sintering during preparing the FePd NPs. Ferromagnetic FePd NPs of ca. 16.2 nm in diameter were synthesized by one-pot pyrolysis of the single-source precursor TPy-FePd-1 under getter gas with metal-ion reduction and minimal nanoparticle coalescence, which have a nearly equal atomic ratio (Fe/Pd = 49/51) and exhibited coercivity of 4.9 kOe at 300 K. By imprinting the mixed chloroform solution of TPy-FePd-1 and polystyrene (PS) on Si, reproducible patterning of nanochains was formed due to the excellent self-assembly properties and the incompatibility between TPy-FePd-1 and PS under the slow evaporation of the solvents. The FePd nanochains with average length of ca. 260 nm were evenly dispersed around the PS nanosphere by self-assembly of TPy-FePd-1. In addition, the orientation of the FePd nanochains could also be controlled by tuning the morphology of PS, and the length was shorter in confined space of PS. Orgnic skeleton in TPy-FePd-1 and PS were carbonized and removed by pyrolysis under Ar/H2 (5 wt%) and only magnetic FePd alloy nanochains with domain structure were left. Besides, a bimetallic complex TPy-FePd-2 was prepared and used as a single-source precursor to synthesize ferromagnetic FePd NPs by one-pot pyrolysis. The resultant FePd NPs have a mean size of 19.8 nm and show the coercivity of 1.02 kOe. In addition, the functional group (-NCMe) in TPy-FePd-2 was easily substituted by a pyridyl group. A random copolymer PS-P4VP was used to coordinate with TPy-FePd-2, and the as-synthesized polymer made the metal fraction disperse evenly along the flexible chain. Fabrication of FePd NPs from the polymers was also investigated, and the size could be easily controlled by tuning the metal fraction in polymer. FePd NPs with the mean size of 10.9, 14.2 and 17.9 nm were prepared from the metallopolymer with 5 wt%, 10 wt% and 20wt% of metal fractions, respectively. In Chapter 4, molybdenum disulfide (MoS2) monolayers decorated with ferromagnetic FeCo NPs on the edges were synthesized through a one-step pyrolysis of precursor molecules in an argon atmosphere. The FeCo precursor was spin coated on the MoS2 monolayer grown on Si/SiO2 substrate. Highly-ordered body-centered cubic (bcc) FeCo NPs were revealed under optimized pyrolysis conditions, possessing coercivity up to 1000 Oe at room temperature. The FeCo NPs were well-positioned along the edge sites of MoS2 monolayers. The vibration modes of Mo and S atoms were confined after FeCo NPs decoration, as characterized by Raman shift spectroscopy. These MoS2 monolayers decorated with ferromagnetic FeCo NPs can be used for novel catalytic materials with magnetic recycling capabilities. The sizes of NPs grown on MoS2 monolayers are more uniform than from other preparation routines. Finally, the optimized pyrolysis temperature and conditions provide receipts for decorating related noble catalytic materials. Finally, Chapters 5 and 6 present the concluding remarks and the experimental details of the work described in Chapters 2-4.