Computational Techniques for Spatial Logistic Regression with Large Datasets

In epidemiological work, outcomes are frequently non-normal, sample sizes may be large, and effects are often small. To relate health outcomes to geographic risk factors, fast and powerful methods for fitting spatial models, particularly for non-normal data, are required. We focus on binary outcomes, with the risk surface a smooth function of space. We compare penalized likelihood models, including the penalized quasi-likelihood (PQL) approach, and Bayesian models based on fit, speed, and ease of implementation. A Bayesian model using a spectral basis representation of the spatial surface provides the best tradeoff of sensitivity and specificity in simulations, detecting real spatial features while limiting overfitting and being more efficient computationally than other Bayesian approaches. One of the contributions of this work is further development of this underused representation. The spectral basis model outperforms the penalized likelihood methods, which are prone to overfitting, but is slower to fit and not as easily implemented. Conclusions based on a real dataset of cancer cases in Taiwan are similar albeit less conclusive with respect to comparing the approaches. The success of the spectral basis with binary data and similar results with count data suggest that it may be generally useful in spatial models and more complicated hierarchical models.

Coronary artery stent geometry and in-stent contrast attenuation with 64-slice computed tomography

We aimed at assessing stent geometry and in-stent contrast attenuation with 64-slice CT in patients with various coronary stents. Twenty-nine patients (mean age 60 +/- 11 years; 24 men) with 50 stents underwent CT within 2 weeks after stent placement. Mean in-stent luminal diameter and reference vessel diameter proximal and distal to the stent were assessed with CT, and compared to quantitative coronary angiography (QCA). Stent length was also compared to the manufacturer's values. Images were reconstructed using a medium-smooth (B30f) and sharp (B46f) kernel. All 50 stents could be visualized with CT. Mean in-stent luminal diameter was systematically underestimated with CT compared to QCA (1.60 +/- 0.39 mm versus 2.49 +/- 0.45 mm; P < 0.0001), resulting in a modest correlation of QCA versus CT (r = 0.49; P < 0.0001). Stent length as given by the manufacturer was 18.2 +/- 6.2 mm, correlating well with CT (18.5 +/- 5.7 mm; r = 0.95; P < 0.0001) and QCA (17.4 +/- 5.6 mm; r = 0.87; P < 0.0001). Proximal and distal reference vessel diameters were similar with CT and QCA (P = 0.06 and P = 0.03). B46f kernel images showed higher image noise (P < 0.05) and lower in-stent CT attenuation values (P < 0.001) than images reconstructed with the B30f kernel. 64-slice CT allows measurement of coronary artery in-stent density, and significantly underestimates the true in-stent diameter compared to QCA.

Reynolds-stress turbulence model in the KIVA code for engine simulation

A Reynolds-Stress Turbulence Model has been incorporated with success into the KIVA code, a computational fluid dynamics hydrocode for three-dimensional simulation of fluid flow in engines. The newly implemented Reynolds-stress turbulence model greatly improves the robustness of KIVA, which in its original version has only eddy-viscosity turbulence models. Validation of the Reynolds-stress turbulence model is accomplished by conducting pipe-flow and channel-flow simulations, and comparing the computed results with experimental and direct numerical simulation data. Flows in engines of various geometry and operating conditions are calculated using the model, to study the complex flow fields as well as confirm the model’s validity. Results show that the Reynolds-stress turbulence model is able to resolve flow details such as swirl and recirculation bubbles. The model is proven to be an appropriate choice for engine simulations, with consistency and robustness, while requiring relatively low computational effort.

Estimation of the degree of polarization through computational sensing

The degree of polarization of a refected field from active laser illumination can be used for object identifcation and classifcation. The goal of this study is to investigate methods for estimating the degree of polarization for refected fields with active laser illumination, which involves the measurement and processing of two orthogonal field components (complex amplitudes), two orthogonal intensity components, and the total field intensity. We propose to replace interferometric optical apparatuses with a computational approach for estimating the degree of polarization from two orthogonal intensity data and total intensity data. Cramer-Rao bounds for each of the three sensing modalities with various noise models are computed. Algebraic estimators and maximum-likelihood (ML) estimators are proposed. Active-set algorithm and expectation-maximization (EM) algorithm are used to compute ML estimates. The performances of the estimators are compared with each other and with their corresponding Cramer-Rao bounds. Estimators for four-channel polarimeter (intensity interferometer) sensing have a better performance than orthogonal intensities estimators and total intensity estimators. Processing the four intensities data from polarimeter, however, requires complicated optical devices, alignment, and four CCD detectors. It only requires one or two detectors and a computer to process orthogonal intensities data and total intensity data, and the bounds and estimator performances demonstrate that reasonable estimates may still be obtained from orthogonal intensities or total intensity data. Computational sensing is a promising way to estimate the degree of polarization.

Computational prediction of the influence of crosslink distribution on the thermo-mechanical properties of epoxies

Experimental studies on epoxies report that the microstructure consists of highly crosslinked localized regions connected with a dispersed phase of low crosslink density. The various thermo-mechanical properties of epoxies might be affected by the crosslink distribution. But as experiments cannot report the exact number of crosslinked covalent bonds present in the structure, molecular dynamics is thus being used in this work to determine the influence of crosslink distribution on thermo-mechanical properties. Molecular dynamics and molecular mechanics simulations are used to establish wellequilibrated molecular models of EPON 862-DETDA epoxy system with a range of crosslink densities and various crosslink distributions. Crosslink distributions are being varied by forming differently crosslinked localized clusters and then by forming different number of crosslinks interconnecting the clusters. Simulations are subsequently used to predict the volume shrinkage, thermal expansion coefficients, and elastic properties of each of the crosslinked systems. The results indicate that elastic properties increase with increasing levels of overall crosslink density and the thermal expansion coefficient decreases with overall crosslink density, both above and below the glass transition temperature. Elastic moduli and coefficients of linear thermal expansion values were found to be different for systems with same overall crosslink density but having different crosslink distributions, thus indicating an effect of the epoxy nanostructure on physical properties. The values of thermo-mechanical properties for all the crosslinked systems are within the range of values reported in literature.

Filtration and oxidation characteristics of a diesel oxidation catalyst and a catalyzed particulate filter : development of a 1-D 2-layer model

The emissions, filtration and oxidation characteristics of a diesel oxidation catalyst (DOC) and a catalyzed particulate filter (CPF) in a Johnson Matthey catalyzed continuously regenerating trap (CCRT ®) were studied by using computational models. Experimental data needed to calibrate the models were obtained by characterization experiments with raw exhaust sampling from a Cummins ISM 2002 engine with variable geometry turbocharging (VGT) and programmed exhaust gas recirculation (EGR). The experiments were performed at 20, 40, 60 and 75% of full load (1120 Nm) at rated speed (2100 rpm), with and without the DOC upstream of the CPF. This was done to study the effect of temperature and CPF-inlet NO2 concentrations on particulate matter oxidation in the CCRT ®. A previously developed computational model was used to determine the kinetic parameters describing the oxidation characteristics of HCs, CO and NO in the DOC and the pressure drop across it. The model was calibrated at five temperatures in the range of 280 – 465° C, and exhaust volumetric flow rates of 0.447 – 0.843 act-m3/sec. The downstream HCs, CO and NO concentrations were predicted by the DOC model to within ±3 ppm. The HCs and CO oxidation kinetics in the temperature range of 280 - 465°C and an exhaust volumetric flow rate of 0.447 - 0.843 act-m3/sec can be represented by one ’apparent’ activation energy and pre-exponential factor. The NO oxidation kinetics in the same temperature and exhaust flow rate range can be represented by ’apparent’ activation energies and pre-exponential factors in two regimes. The DOC pressure drop was always predicted within 0.5 kPa by the model. The MTU 1-D 2-layer CPF model was enhanced in several ways to better model the performance of the CCRT ®. A model to simulate the oxidation of particulate inside the filter wall was developed. A particulate cake layer filtration model which describes particle filtration in terms of more fundamental parameters was developed and coupled to the wall oxidation model. To better model the particulate oxidation kinetics, a model to take into account the NO2 produced in the washcoat of the CPF was developed. The overall 1-D 2-layer model can be used to predict the pressure drop of the exhaust gas across the filter, the evolution of particulate mass inside the filter, the particulate mass oxidized, the filtration efficiency and the particle number distribution downstream of the CPF. The model was used to better understand the internal performance of the CCRT®, by determining the components of the total pressure drop across the filter, by classifying the total particulate matter in layer I, layer II, the filter wall, and by the means of oxidation i.e. by O2, NO2 entering the filter and by NO2 being produced in the filter. The CPF model was calibrated at four temperatures in the range of 280 – 465 °C, and exhaust volumetric flow rates of 0.447 – 0.843 act-m3/sec, in CPF-only and CCRT ® (DOC+CPF) configurations. The clean filter wall permeability was determined to be 2.00E-13 m2, which is in agreement with values in the literature for cordierite filters. The particulate packing density in the filter wall had values between 2.92 kg/m3 - 3.95 kg/m3 for all the loads. The mean pore size of the catalyst loaded filter wall was found to be 11.0 µm. The particulate cake packing densities and permeabilities, ranged from 131 kg/m3 - 134 kg/m3, and 0.42E-14 m2 and 2.00E-14 m2 respectively, and are in agreement with the Peclet number correlations in the literature. Particulate cake layer porosities determined from the particulate cake layer filtration model ranged between 0.841 and 0.814 and decreased with load, which is about 0.1 lower than experimental and more complex discrete particle simulations in the literature. The thickness of layer I was kept constant at 20 µm. The model kinetics in the CPF-only and CCRT ® configurations, showed that no ’catalyst effect’ with O2 was present. The kinetic parameters for the NO2-assisted oxidation of particulate in the CPF were determined from the simulation of transient temperature programmed oxidation data in the literature. It was determined that the thermal and NO2 kinetic parameters do not change with temperature, exhaust flow rate or NO2 concentrations. However, different kinetic parameters are used for particulate oxidation in the wall and on the wall. Model results showed that oxidation of particulate in the pores of the filter wall can cause disproportionate decreases in the filter pressure drop with respect to particulate mass. The wall oxidation model along with the particulate cake filtration model were developed to model the sudden and rapid decreases in pressure drop across the CPF. The particulate cake and wall filtration models result in higher particulate filtration efficiencies than with just the wall filtration model, with overall filtration efficiencies of 98-99% being predicted by the model. The pre-exponential factors for oxidation by NO2 did not change with temperature or NO2 concentrations because of the NO2 wall production model. In both CPF-only and CCRT ® configurations, the model showed NO2 and layer I to be the dominant means and dominant physical location of particulate oxidation respectively. However, at temperatures of 280 °C, NO2 is not a significant oxidizer of particulate matter, which is in agreement with studies in the literature. The model showed that 8.6 and 81.6% of the CPF-inlet particulate matter was oxidized after 5 hours at 20 and 75% load in CCRT® configuration. In CPF-only configuration at the same loads, the model showed that after 5 hours, 4.4 and 64.8% of the inlet particulate matter was oxidized. The increase in NO2 concentrations across the DOC contributes significantly to the oxidation of particulate in the CPF and is supplemented by the oxidation of NO to NO2 by the catalyst in the CPF, which increases the particulate oxidation rates. From the model, it was determined that the catalyst in the CPF modeslty increases the particulate oxidation rates in the range of 4.5 – 8.3% in the CCRT® configuration. Hence, the catalyst loading in the CPF of the CCRT® could possibly be reduced without significantly decreasing particulate oxidation rates leading to catalyst cost savings and better engine performance due to lower exhaust backpressures.

Development of one-dimensional and two-dimensional computational tools that simulate steady internal condensing flows in terrestrial and zero-gravity environments

This dissertation presents an effective quasi one-dimensional (1-D) computational simulation tool and a full two-dimensional (2-D) computational simulation methodology for steady annular/stratified internal condensing flows of pure vapor. These simulation tools are used to investigate internal condensing flows in both gravity as well as shear driven environments. Through accurate numerical simulations of the full two dimensional governing equations, results for laminar/laminar condensing flows inside mm-scale ducts are presented. The methodology has been developed using MATLAB/COMSOL platform and is currently capable of simulating film-wise condensation for steady (and unsteady flows). Moreover, a novel 1-D solution technique, capable of simulating condensing flows inside rectangular and circular ducts with different thermal boundary conditions is also presented. The results obtained from the 2-D scientific tool and 1-D engineering tool, are validated and synthesized with experimental results for gravity dominated flows inside vertical tube and inclined channel; and, also, for shear/pressure driven flows inside horizontal channels. Furthermore, these simulation tools are employed to demonstrate key differences of physics between gravity dominated and shear/pressure driven flows. A transition map that distinguishes shear driven, gravity driven, and “mixed” driven flow zones within the non-dimensional parameter space that govern these duct flows is presented along with the film thickness and heat transfer correlations that are valid in these zones. It has also been shown that internal condensing flows in a micro-meter scale duct experiences shear driven flow, even in different gravitational environments. The full 2-D steady computational tool has been employed to investigate the length of annularity. The result for a shear driven flow in a horizontal channel shows that in absence of any noise or pressure fluctuation at the inlet, the onset of non-annularity is partly due to insufficient shear at the liquid-vapor interface. This result is being further corroborated/investigated by R. R. Naik with the help of the unsteady simulation tool. The condensing flow results and flow physics understanding developed through these simulation tools will be instrumental in reliable design of modern micro-scale and spacebased thermal systems.

Spin-strain coupling in a 3-D transition metal oxides

ab-initio Hartree Fock (HF), density functional theory (DFT) and hybrid potentials were employed to compute the optimized lattice parameters and elastic properties of perovskite 3-d transition metal oxides. The optimized lattice parameters and elastic properties are interdependent in these materials. An interaction is observed between the electronic charge, spin and lattice degrees of freedom in 3-d transition metal oxides. The coupling between the electronic charge, spin and lattice structures originates due to localization of d-atomic orbitals. The coupling between the electronic charge, spin and crystalline lattice also contributes in the ferroelectric and ferromagnetic properties in perovskites. The cubic and tetragonal crystalline structures of perovskite transition metal oxides of ABO3 are studied. The electronic structure and the physics of 3-d perovskite materials is complex and less well considered. Moreover, the novelty of the electronic structure and properties of these perovskites transition metal oxides exceeds the challenge offered by their complex crystalline structures. To achieve the objective of understanding the structure and property relationship of these materials the first-principle computational method is employed. CRYSTAL09 code is employed for computing crystalline structure, elastic, ferromagnetic and other electronic properties. Second-order elastic constants (SOEC) and bulk moduli (B) are computed in an automated process by employing ELASTCON (elastic constants) and EOS (equation of state) programs in CRYSTAL09 code. ELASTCON, EOS and other computational algorithms are utilized to determine the elastic properties of tetragonal BaTiO3, rutile TiO2, cubic and tetragonal BaFeO3 and the ferromagentic properties of 3-d transition metal oxides. Multiple methods are employed to crosscheck the consistency of our computational results. Computational results have motivated us to explore the ferromagnetic properties of 3-d transition metal oxides. Billyscript and CRYSTAL09 code are employed to compute the optimized geometry of the cubic and tetragonal crystalline structure of transition metal oxides of Sc to Cu. Cubic crystalline structure is initially chosen to determine the effect of lattice strains on ferromagnetism due to the spin angular momentum of an electron. The 3-d transition metals and their oxides are challenging as the basis functions and potentials are not fully developed to address the complex physics of the transition metals. Moreover, perovskite crystalline structures are extremely challenging with respect to the quality of computations as the latter requires the well established methods. Ferroelectric and ferromagnetic properties of bulk, surfaces and interfaces are explored by employing CRYSTAL09 code. In our computations done on cubic TMOs of Sc-Fe it is observed that there is a coupling between the crystalline structure and FM/AFM spin polarization. Strained crystalline structures of 3-d transition metal oxides are subjected to changes in the electromagnetic and electronic properties. The electronic structure and properties of bulk, composites, surfaces of 3-d transition metal oxides are computed successfully.

Integration of computational models and experimental characterization to study internal frost damage in cementitious materials

The objective of this doctoral research is to investigate the internal frost damage due to crystallization pore pressure in porous cement-based materials by developing computational and experimental characterization tools. As an essential component of the U.S. infrastructure system, the durability of concrete has significant impact on maintenance costs. In cold climates, freeze-thaw damage is a major issue affecting the durability of concrete. The deleterious effects of the freeze-thaw cycle depend on the microscale characteristics of concrete such as the pore sizes and the pore distribution, as well as the environmental conditions. Recent theories attribute internal frost damage of concrete is caused by crystallization pore pressure in the cold environment. The pore structures have significant impact on freeze-thaw durability of cement/concrete samples. The scanning electron microscope (SEM) and transmission X-ray microscopy (TXM) techniques were applied to characterize freeze-thaw damage within pore structure. In the microscale pore system, the crystallization pressures at sub-cooling temperatures were calculated using interface energy balance with thermodynamic analysis. The multi-phase Extended Finite Element Modeling (XFEM) and bilinear Cohesive Zone Modeling (CZM) were developed to simulate the internal frost damage of heterogeneous cement-based material samples. The fracture simulation with these two techniques were validated by comparing the predicted fracture behavior with the captured damage from compact tension (CT) and single-edge notched beam (SEB) bending tests. The study applied the developed computational tools to simulate the internal frost damage caused by ice crystallization with the two dimensional (2-D) SEM and three dimensional (3-D) reconstructed SEM and TXM digital samples. The pore pressure calculated from thermodynamic analysis was input for model simulation. The 2-D and 3-D bilinear CZM predicted the crack initiation and propagation within cement paste microstructure. The favorably predicted crack paths in concrete/cement samples indicate the developed bilinear CZM techniques have the ability to capture crack nucleation and propagation in cement-based material samples with multiphase and associated interface. By comparing the computational prediction with the actual damaged samples, it also indicates that the ice crystallization pressure is the main mechanism for the internal frost damage in cementitious materials.

Computational study of internal and external condensing flows and experimental synthesis to investigate their attainability and stability in ground-based and space-based environments

This doctoral thesis presents the computational work and synthesis with experiments for internal (tube and channel geometries) as well as external (flow of a pure vapor over a horizontal plate) condensing flows. The computational work obtains accurate numerical simulations of the full two dimensional governing equations for steady and unsteady condensing flows in gravity/0g environments. This doctoral work investigates flow features, flow regimes, attainability issues, stability issues, and responses to boundary fluctuations for condensing flows in different flow situations. This research finds new features of unsteady solutions of condensing flows; reveals interesting differences in gravity and shear driven situations; and discovers novel boundary condition sensitivities of shear driven internal condensing flows. Synthesis of computational and experimental results presented here for gravity driven in-tube flows lays framework for the future two-phase component analysis in any thermal system. It is shown for both gravity and shear driven internal condensing flows that steady governing equations have unique solutions for given inlet pressure, given inlet vapor mass flow rate, and fixed cooling method for condensing surface. But unsteady equations of shear driven internal condensing flows can yield different “quasi-steady” solutions based on different specifications of exit pressure (equivalently exit mass flow rate) concurrent to the inlet pressure specification. This thesis presents a novel categorization of internal condensing flows based on their sensitivity to concurrently applied boundary (inlet and exit) conditions. The computational investigations of an external shear driven flow of vapor condensing over a horizontal plate show limits of applicability of the analytical solution. Simulations for this external condensing flow discuss its stability issues and throw light on flow regime transitions because of ever-present bottom wall vibrations. It is identified that laminar to turbulent transition for these flows can get affected by ever present bottom wall vibrations. Detailed investigations of dynamic stability analysis of this shear driven external condensing flow result in the introduction of a new variable, which characterizes the ratio of strength of the underlying stabilizing attractor to that of destabilizing vibrations. Besides development of CFD tools and computational algorithms, direct application of research done for this thesis is in effective prediction and design of two-phase components in thermal systems used in different applications. Some of the important internal condensing flow results about sensitivities to boundary fluctuations are also expected to be applicable to flow boiling phenomenon. Novel flow sensitivities discovered through this research, if employed effectively after system level analysis, will result in the development of better control strategies in ground and space based two-phase thermal systems.

Computational simulations of latent heat thermal energy storage systems - with innovative and first-principles based simulation for the underlying unsteady melting (and solidification) processes

This thesis develops an effective modeling and simulation procedure for a specific thermal energy storage system commonly used and recommended for various applications (such as an auxiliary energy storage system for solar heating based Rankine cycle power plant). This thermal energy storage system transfers heat from a hot fluid (termed as heat transfer fluid - HTF) flowing in a tube to the surrounding phase change material (PCM). Through unsteady melting or freezing process, the PCM absorbs or releases thermal energy in the form of latent heat. Both scientific and engineering information is obtained by the proposed first-principle based modeling and simulation procedure. On the scientific side, the approach accurately tracks the moving melt-front (modeled as a sharp liquid-solid interface) and provides all necessary information about the time-varying heat-flow rates, temperature profiles, stored thermal energy, etc. On the engineering side, the proposed approach is unique in its ability to accurately solve – both individually and collectively – all the conjugate unsteady heat transfer problems for each of the components of the thermal storage system. This yields critical system level information on the various time-varying effectiveness and efficiency parameters for the thermal storage system.

Computational fluids domain reduction to a simplified fluid network

The primary goal of this project is to demonstrate the practical use of data mining algorithms to cluster a solved steady-state computational fluids simulation (CFD) flow domain into a simplified lumped-parameter network. A commercial-quality code, “cfdMine” was created using a volume-weighted k-means clustering that that can accomplish the clustering of a 20 million cell CFD domain on a single CPU in several hours or less. Additionally agglomeration and k-means Mahalanobis were added as optional post-processing steps to further enhance the separation of the clusters. The resultant nodal network is considered a reduced-order model and can be solved transiently at a very minimal computational cost. The reduced order network is then instantiated in the commercial thermal solver MuSES to perform transient conjugate heat transfer using convection predicted using a lumped network (based on steady-state CFD). When inserting the lumped nodal network into a MuSES model, the potential for developing a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track temperatures near specific objects (such as equipment in vehicles).

DEVELOPMENT OF A PREDICTIVE COMBUSTION MODEL OF A SPARK IGNITED ENGINE WITH GASOLINE DIRECT INJECTION, VARIABLE VALVE TIMING, DURATION AND LIFT TECHNOLOGIES

There is a need by engine manufactures for computationally efficient and accurate predictive combustion modeling tools for integration in engine simulation software for the assessment of combustion system hardware designs and early development of engine calibrations. This thesis discusses the process for the development and validation of a combustion modeling tool for Gasoline Direct Injected Spark Ignited Engine with variable valve timing, lift and duration valvetrain hardware from experimental data. Data was correlated and regressed from accepted methods for calculating the turbulent flow and flame propagation characteristics for an internal combustion engine. A non-linear regression modeling method was utilized to develop a combustion model to determine the fuel mass burn rate at multiple points during the combustion process. The computational fluid dynamic software Converge ©, was used to simulate and correlate the 3-D combustion system, port and piston geometry to the turbulent flow development within the cylinder to properly predict the experimental data turbulent flow parameters through the intake, compression and expansion processes. The engine simulation software GT-Power © is then used to determine the 1-D flow characteristics of the engine hardware being tested to correlate the regressed combustion modeling tool to experimental data to determine accuracy. The results of the combustion modeling tool show accurate trends capturing the combustion sensitivities to turbulent flow, thermodynamic and internal residual effects with changes in intake and exhaust valve timing, lift and duration.