Optical gradation for crushed limestone aggregates

The strength and durability of asphalt pavement is directly affected by the characteristics of its main ingredient, mineral aggregate. Besides material strength, research has shown that mixture properties such as particle shape and mixture gradation have a significant affect on the quality of the asphalt concrete. A standard called Superpave has been developed which sets forth specifications for material selection and methods for measurement of aggregate properties. These standards require monitoring of aggregate properties, particularly gradation. In this dissertation, the feasibility of developing an optically based method for determining aggregate gradation was explored. The physical system primarily consists of a standard monochrome CCD video camera and a computer with a frame grabber board. Software was developed to separate touching or overlapping particles in the image, and to detect the size and shape of each particle. Correlation to estimate each particle\u27s mass and to predict the sieving behavior for crushed limestone aggregates was developed and tested. Laboratory testing demonstrated the ability to measure gradation over a range of particle sizes from 4.75 mm to 25 mm with an accuracy of +/-3 in terms of percent-passing residual when compared with mechanical sieving

Engineering Multicomponent Nanomaterials for Plasmonic Catalysis

Heterogenous catalysis is an important technology used to facilitate chemical transformations. As increasing demand for chemicals and materials stresses the availability of resources and the environment, it is becoming ever more important to design catalysts with near perfect selectivity in the conversion of reactant feedstock to desired products. In traditional heterogeneous catalysis, heat is used to drive the conversion of reactants to products. An unintended side effect of this approach is that energy is unselectively deposited into all possible reaction pathways resulting in the simultaneous activation of undesired reactions, waste of feedstock resources, and production of chemical waste. An alternative mechanism for activating chemical reactions employs visible light to deposit energy into reactants. This mechanism could in principle make it possible to achieve much higher product selectivities but has been considered impractical as it requires high intensity lasers to produce sufficiently high reaction rates. Recently, it has been shown that plasmonic metal nanoparticles (Cu, Ag, and Au) can perform light-driven chemical reactions under relatively low intensity light on the order of sunlight. These findings have reignited interest in light-driven chemical reactions in heterogeneous catalysis and led to the emergence of a new field known as plasmonic catalysis. A major limitation of plasmonic catalysis is that it is restricted to reactions that can be performed by the plasmonic metals, Cu, Ag, and Au. In this dissertation, we address this limitation through the design of multicomponent plasmonic catalysts which combine plasmonic metals with catalytically-active materials. In particular, we focus on combining plasmonic metals, such as Ag, with catalytically-active metals, such as Pt, through the fabrication of bimetallic nanoparticles. We consider two extremes for synthesizing nanoparticles composed of both metals: 1) alloy nanoparticles in which both metals are well-mixed and 2) core-shell structures in which a large Ag core is completely surrounded with a thin shell of Pt. We develop novel synthesis approaches for creating both structures and use a suite of characterization tools to shed light on the nanoscale structure and composition of the resulting materials. We then use the well-defined core-shell nanoparticles to perform a mechanistic investigation of the energy transfer mechanisms which allow for energy to be transferred from photoexcited plasmonic metals to catalytically-active sites. These studies demonstrate that coating a thin layer of a catalytic metal, such as Pt, on a plasmonic metal drastically biases the flow of energy in the nanoparticles towards absorption in the catalytic metal. We then design reactor studies showing that this re-routing of plasmonic energy enables plasmon-driven reactions to take place on non-plasmonic metal surfaces. These discoveries not only introduce new methods for precision synthesis of multimetallic nanostructures but also present a clear understanding for the physical mechanisms which allow for energy transfer from plasmonic metals to catalytically active sites thereby paving the way for the design of new hybrid plasmonic-catalytic materials for performing light-driven chemical reactions.PHDChemical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145860/1/uaslam_1.pd

Quantification of spheroid formation mechanism by size and shape analysis

Ph.DDOCTOR OF PHILOSOPH

New Exact and Numerical Solutions of the (Convection-)Diffusion Kernels on SE(3)

We consider hypo-elliptic diffusion and convection-diffusion on $\mathbb{R}^3 \rtimes S^2$, the quotient of the Lie group of rigid body motions SE(3) in which group elements are equivalent if they are equal up to a rotation around the reference axis. We show that we can derive expressions for the convolution kernels in terms of eigenfunctions of the PDE, by extending the approach for the SE(2) case. This goes via application of the Fourier transform of the PDE in the spatial variables, yielding a second order differential operator. We show that the eigenfunctions of this operator can be expressed as (generalized) spheroidal wave functions. The same exact formulas are derived via the Fourier transform on SE(3). We solve both the evolution itself, as well as the time-integrated process that corresponds to the resolvent operator. Furthermore, we have extended a standard numerical procedure from SE(2) to SE(3) for the computation of the solution kernels that is directly related to the exact solutions. Finally, we provide a novel analytic approximation of the kernels that we briefly compare to the exact kernels.Comment: Revised and restructure

Ash Tree Identification Based on the Integration of Hyperspectral Imagery and High-density Lidar Data

Monitoring and management of ash trees has become particularly important in recent years due to the heightened risk of attack from the invasive pest, the emerald ash borer (EAB). However, distinguishing ash from other deciduous trees can be challenging. Both hyperspectral imagery and Light detection and ranging (LiDAR) data are two valuable data sources that are often used for tree species classification. Hyperspectral imagery measures detailed spectral reflectance related to the biochemical properties of vegetation, while LiDAR data measures the three-dimensional structure of tree crowns related to morphological characteristics. Thus, the accuracy of vegetation classification may be improved by combining both techniques. Therefore, the objective of this research is to integrate hyperspectral imagery and LiDAR data for improving ash tree identification. Specifically, the research aims include: 1) using LiDAR data for individual tree crowns segmentation; 2) using hyperspectral imagery for extraction of relative pure crown spectra; 3) fusing hyperspectral and LiDAR data for ash tree identification. It is expected that the classification accuracy of ash trees will be significantly improved with the integration of hyperspectral and LiDAR techniques. Analysis results suggest that, first, 3D crown structures of individual trees can be reconstructed using a set of generalized geometric models which optimally matched LiDAR-derived raster image, and crown widths can be further estimated using tree height and shape-related parameters as independent variables and ground measurement of crown widths as dependent variables. Second, with constrained linear spectral mixture analysis method, the fractions of all materials within a pixel can be extracted, and relative pure crown-scale spectra can be further calculated using illuminated-leaf fraction as weighting factors for tree species classification. Third, both crown shape index (SI) and coefficient of variation (CV) can be extracted from LiDAR data as invariant variables in tree’s life cycle, and improve ash tree identification by integrating with pixel-weighted crown spectra. Therefore, three major contributions of this research have been made in the field of tree species classification:1) the automatic estimation of individual tree crown width from LiDAR data by combining a generalized geometric model and a regression model, 2) the computation of relative pure crown-scale spectral reflectance using a pixel-weighting algorithm for tree species classification, 3) the fusion of shape-related structural features and pixel-weighted crown-scale spectral features for improving of ash tree identification

Three-Dimensional Structural Analysis of Temple 16 and Rosalila at Copan Ruinas

Temple 16 is an ancient Maya structure located at the heart of the Copán Ruinas Acropolis in Western Honduras. Temple 16 contains several earlier structures within it that were built on top of each other throughout Copán’s history. One of these earlier structures, Rosalila, is one of the most culturally significant structures within the Acropolis due to its preservation. An intricate series of archeological tunnels have been excavated throughout Temple 16 to allow for its study. However, significant cracking has been observed within Rosalila and several tunnels have experienced partial collapse. This not only poses a life safety issue for those utilizing the tunnels, but also demonstrates the risk to invaluable cultural heritage. To this end, this thesis aims to provide a rigorous structural assessment of Temple 16 and the buried Rosalila structure, accounting for its complex 3D tunnel system, to understand the leading causes of tunnel collapse and structure deterioration. Geometric data was collected of the acropolis, Temple 16, Rosalila, and the complex network of tunnels using a combination of ground-based lidar and uncrewed aerial systems. The resulting point clouds were vectorized to yield a series of connected surfaces, which were then meshed as a solid to facilitate finite element analysis. Analyses were conducted to understand both the current stress distribution within Temple 16 as well as to study the impact of various hypothetical tunnel backfilling scenarios to provide recommendations for preservation and tunnel safety. The generated finite element models were analyzed under three water saturation levels to account for the impact of heavy rainy seasons and water infiltration on the stress levels of the tunnels. From the analyses, sixty-three highly stressed areas were identified among the current tunnel system, with most of them being close or directly underneath Rosalila. From the tested hypothetical backfilling scenarios, it was found that, backfilling excavated sections can improve or worsen these stress concentrations depending on the location of the tunnel within the system. Finally, by analyzing Rosalila’s current geometry, it was observed that the structure experiences high levels of stress on its southern side due to its location within Temple 16. From this, it was concluded that fixing exposed areas of Rosalila that were affected by excavation on its southern side can significantly alleviate the existing deterioration and improve the stress flow in these areas. Advisors: Christine E. Wittich & Richard L. Wood

Electrochemical Oxidation of Individual Silver Nanoparticles: Exploring the Effect of Particle Shape, Capping Ligand, Electrolyte, and Potential on the Signal

Nanomaterials have revolutionized science and technology. Their unique properties can be exploited, and nanoparticles are being used as catalysts, antimicrobials, drug delivery vehicles, sensors, and more. However, the fundamental properties of nanomaterials and their interactions with their surrounding environments are still poorly understood. In this work, a single-particle approach was used to observe the effects of capping ligand, surrounding solution, and particle shape on the oxidative process to gain deeper understanding of silver nanoparticle properties. When allowed the opportunity, the particles will adsorb to the electrode surface then oxidize in rapid succession upon electrode activation, regardless of capping ligand as long as the electrolyte and applied potential are appropriate. The presence of potassium chloride encourages the oxidation of polyethylene glycol capped particles at an increasing rate over time, but rarely allows oxidation poly-vinylpyrrolidone capped particles. Instead, these particles are better oxidized to silver oxide either in potassium nitrate at high potentials or under alkaline conditions at lower potentials. Successful oxidation of poly-vinylpyrrolidone capped particles enabled the work to be expanded from spheres to cubes and plates, the shape of which bore no effect on the rate of oxidation to silver chloride. Furthermore, a new method of single particle characterization was developed to improve the accuracy and precision of nanoparticle characterization. By combining redox magnetohydrodynamics with dark field microscopy, silver and gold coated silica particles were successfully sized from a flowing mixture in both forward and reverse directions

Effect of post-fill pressure and nanoclay on void morphology in resin transfer molded composites.

Resin transfer molded (RTM) composites usually suffer from the formation of flow-induced defects such as voids. Detrimental effects of voids on performance of molded parts have been studied extensively. Yet, knowledge of effective void removal strategies, along with detailed morphological void distribution within molded composites is very limited. In this investigation, effects of post-fill pressure on void content is investigated for random-mat, E-glass/epoxy RTM disks. Measured void contents agree well with results obtained in other studies for similar ranges of modified capillary number values. Packing helped significantly reduce void contents in RTM parts. In addition, voids are found to concentrate primarily within or adjacent to the fibers. Three-dimensional features of the formed voids are included in more detailed analyses of morphology variations of voids within the composite from both through-the-thickness and planar surfaces.Effects of applying a packing pressure on void morphology are investigated for similar composites. Packing pressures of zero and 570 kPa are applied and voidage is evaluated from both through-the-thickness and planar views. The packed composite is found to contain almost 92% less void content than the unpacked composite, accompanied by a 40% drop in average void size. Along the flow direction, removal of voids seems to depend on their arrangement at the end of the filling stage.Finally, effect of nanoclay content on void morphology in RTM nanoclay/E-glass/epoxy composites are investigated. ClositeRTM25A nanoclay loads of 0, 2, 5, and 10 wt% are mixed with a low-viscosity epoxy resin prior to filling. Void occurrence is observed to increase considerably with increasing nanoclay content from 2.1% in the composite without nanoclay to 5.1 and 8.3% in 5%- and 10%-nanocomposites, respectively. However, the composite with 2 wt% nanoclay yields the lowest void content of 0.7%. Voids are observed to be smaller after the addition of nanoclay at all concentrations

VIRTUALIZATION OF FUELBEDS: BUILDING THE NEXT GENERATION OF FUELS DATA FOR MULTIPLE –SCALE FIRE MODELING AND ECOLOGICAL ANALYSIS

The primary goal of this research is to advance methods for deriving fine-grained, scalable, wildland fuels attributes in 3-dimensions using terrestrial and airborne laser scanning technology. It is fundamentally a remote sensing research endeavor applied to the problem of fuels characterization. Advancements in laser scanning are beginning to have significant impacts on a range of modeling frameworks in fire research, especially those utilizing 3-dimensional data and benefiting from efficient data scaling. The pairing of laser scanning and fire modeling is enabling advances in understanding how fuels variability modulates fire behavior and effects. This dissertation details the development of methods and techniques to characterize and quantify surface fuelbeds using both terrestrial and airborne laser scanning. The primary study site is Eglin Airforce Base, Florida, USA, which provides a range of fuel types and conditions in a fire-adapted landscape along with the multi-disciplinary expertise, logistical support, and prescribed fire necessary for detailed characterization of fire as a physical process. Chapter 1 provides a research overview and discusses the state of fuels science and the related needs for highly resolved fuels data in the southeastern United States. Chapter 2, describes the use of terrestrial laser scanning for sampling fuels at multiple scales and provides analysis of the spatial accuracy of fuelbed models in 3-D. Chapter 3 describes the development of a voxel-based occupied volume method for predicting fuel mass. Results are used to inform prediction of landscape-scale fuel load using airborne laser scanning metrics as well as to predict post-fire fuel consumption. Chapter 4 introduces a novel fuel simulation approach which produces spatially explicit, statistically-defensible estimates of fuel properties and demonstrates a pathway for resampling observed data. This method also can be directly compared to terrestrial laser scanning data to assess how energy interception of the laser pulse affects characterization of the fuelbed. Chapter 5 discusses the contribution of this work to fire science and describes ongoing and future research derived from this work. Chapters 2 and 4 have been published in International Journal of Wildland Fire and Canadian Journal of Remote Sensing, respectively, and Chapter 3 is in preparation for publication