In Situ Process Monitoring and Machine Learning Based Modeling of Defects and Anomalies in Wire-Arc Additive Manufacturing

Wire Arc Additive Manufacturing (WAAM) has made great strides in recent years however, there remain numerous persistent challenges still hindering more widespread adoption. Defects in the parts produced degrade their mechanical performance. Inconsistency in the geometry of the weld beads or undesirable anomalies such as waviness, or humps can lead to loss of geometric accuracy and in extreme cases, when anomalies propagate to subsequent layers, build failure. Such defects can be mitigated by a controls framework, which would require a model that maps undesirable outcomes to information about the process that can be obtained in real time. This thesis explores the development of a multi-sensor framework for real time data acquisition and several approaches for arriving at such a model, employing well known machine learning methodologies including Random Forests, Artificial Neural Networks and Long Short Term Memory. The merits and drawbacks of these methods is discussed, and a physics based approach intended to mitigate some of the drawbacks is explored. The models are trained first on data obtained on a single build layer, and subsequently on a multi-layer wall

Fine-scale Inventory of Forest Biomass with Ground-based LiDAR

Biomass measurement provides a baseline for ecosystem valuation required by modern forest management. The advent of ground-based LiDAR technology, renowned for 3D sampling resolution, has been altering the routines of biomass inventory. The thesis develops a set of innovative approaches in support of fine-scale biomass inventory, including automatic extraction of stem statistics, robust delineation of plot biomass components, accurate classification of individual tree species, and repeatable scanning of plot trees using a lightweight scanning system. Main achievements in terms of accuracy are a relative root mean square error of 11% for stem volume extraction, a mean classification accuracy of 0.72 for plot wood components, and a classification accuracy of 92% among seven tree species. The results indicate the technical feasibility of biomass delineation and monitoring from plot-level and multi-species point cloud datasets, whereas point occlusion and lack of fine-scale validation dataset are current challenges for biomass 3D analysis from ground.S.G.S. International Tuition Award from the University of Lethbridge The Dean's Scholarship from the University of Lethbridge Campus Alberta Innovates Program NSERC Discovery Grants Progra

Complementary 2D/3D Imaging of Functional Materials using X-ray & Electron Microscopy

Catalysts and other functional materials are generally hierarchically structured materials. Hence, the detailed characterization at different length scales, and especially under reaction conditions, are necessary to unravel their mechanisms and to improve their performance and catalytic activities. Besides, a combination of several techniques is required to acquire complementary information owing to the lack of a single technique able to cover all the length scales. With respect to length, the best way to investigate is by microscopy either in 2D or more preferably in 3D. The work began with an exploration of three different 3D imaging techniques, i.e. ptychographic X-ray computed tomography, electron tomography, and focused ion beam slice-and view. Using nanoporous gold as the model, this study aimed to exhibit the versatility of 3D microscopy as a method beyond imaging as well as to confirm the necessity of complementary nature between them, where electron offers better spatial resolution and X-ray provides larger field of view. The study then continued by utilizing ptychographic X-ray computed tomography for quasi in situ thermal treatment of the same materials under atmospheric pressure. This study highlighted its ease of use of implementing in situ studies, complemented by electron tomography to prove its powerful ability to resolve what ptychographic tomography cannot. The resulting 3D volumes were then used for air permeability and CO2 diffusion simulations, along with material’s electrical and thermal conductivity simulations in order to further expose another excellent benefit from 3D microscopy. Ultimately, the work proceeded into developing two cells in order to perform full in situ investigations under controlled temperatures and atmospheres, where one cell was built for 2D only (X-ray) ptychography experiments with simultaneous X-ray fluorescence mapping, and the other was constructed with an additional capability for 3D limited-angle ptychographic tomography experiments. The feasibility tests were conducted using several functional materials, i.e. nanoporous gold, zeolite, and cobalt-manganese-oxides hollow sphere, as the models for thermal annealing process under specific atmospheres. This work eventually attests the importance of in situ studies in precisely determining the onset annealing temperatures under particular environments, to visualize the morphology online either in 2D or 3D, and to simultaneously map elemental distributions live. Moreover, a complementary technique via transmission electron microscopy was also demonstrated on the same sample, adding up another advantage in using the cells. Despite the preliminary results from in situ limited-angle ptychographic tomography experiments for limitation in data reconstruction, a new tomographic reconstruction technique was recently developed as a solution to acquire 3D images with shortened acquisition times. In conclusions, the work here converges into the ideal case of performing all-around in situ 3D imaging of functional materials for quantitative analysis and simulation

Implementation and Characterisation of Monolithic CMOS Pixel Sensors for the CLIC Vertex and Tracking Detectors

Different CMOS technologies are being considered for the vertex and tracking layers of the detector at the proposed high-energy e$^{+}$e$^{−}$ Compact Linear Collider (CLIC). CMOS processes have been proven to be suitable for building high granularity, large area detector systems with low material budget and low power consumption. An effort is put on implementing detectors capable of performing precise timing measurements. Two Application-Specific Integrated Circuits (ASICs) for particle detection have been developed in the framework of this thesis, following the specifications of the CLIC vertex and tracking detectors. The process choice was based on a study of the features of each of the different available technologies and an evaluation of their suitability for each application. The CLICpix Capacitively Coupled Pixel Detector (C3PD) is a pixelated detector chip designed to be used in capacitively coupled assemblies with the CLICpix2 readout chip, in the framework of the vertex detector at CLIC. The chip comprises a matrix of 128×128 square pixels with 25 µm pitch. A commercial 180 nm High-Voltage (HV) CMOS process was used for the C3PD design. The charge is collected with a large deep N-well, while each pixel includes a preamplifier placed on top of the collecting electrode. The C3PD chip was produced on wafers with different values for the substrate resistivity (∼ 20, 80, 200 and 1000 Ωcm) and has been extensively tested through laboratory measurements and beam tests. The design details and characterisation results of the C3PD chip will be presented. The CLIC Tracker Detector (CLICTD) is a novel monolithic detector chip developed in the context of the silicon tracker at CLIC. The CLICTD chip combines high density, mixed mode circuits on the same substrate, while it performs a fast time-tagging measurement with 10 ns time bins. The chip is produced in a 180 nm CMOS imaging process with a High-Resistivity (HR) epitaxial layer. A matrix of 16×128 detecting cells, each measuring 300 × 30 µm$^{2}$ , is included. A small N-well is used to collect the charge generated in the sensor volume, while an additional deep N-type implant is used to fully deplete the epitaxial layer. Using a process split, additional wafers are produced with a segmented deep N-type implant, a modification that has been simulated to result in a faster charge collection time. Each detecting cell is segmented into eight front-ends to ensure prompt charge collection in the sensor diodes. A simultaneous 8-bit timing and 5-bit energy measurement is performed in each detecting cell. A detailed description of the CLICTD design will be given, followed by the first measurement results

Multiscale dynamics in honeybee societies

In this dissertation, I examine the social organization of a model organism, the honeybee, at multiple scales. I begin in Part I at the microbial scale, by studying the relationship between the social caste of individuals and the microbes they harbour in their gastrointestinal tracts. Using 16S rRNA sequence data, I reconstruct the gut microbiomes of honeybees of different castes. I find that the microbiomes of two previously-uncharacterized social castes -- drones and queens -- contain the same bacteria as those in the guts of worker bees. However, despite this similarity, I show that the compositions of these bacteria in drones and queens are sufficiently different that their microbiomes can be distinguished from those of workers. In Part II, I study the honeybee society at the level of its individual constituents, in particular, the set of foragers. I characterize the distribution of foraging activity across these individuals in the society, and find that this is highly skewed, with some individuals contributing much more to the activity of the colony than others. I establish these results in the framework used to describe the wealth of individuals in human society, and also characterize the temporal variation and resilience of foraging activity. In Part III, I describe a system to track individual honeybees and their interactions inside a two-dimensional observation hive with high spatiotemporal resolution. At the level of individual honeybees, I study the temporal statistics of trophallaxis, an important social interaction that occurs in honeybee societies, and find that the distribution of trophallaxis durations is similar to the distribution of face-to-face interactions among humans. I propose a scaling argument to explain the scaling exponent of these distributions, and test the argument in simple random-walk models of proximity interactions. I then study the honeybee society at the collective scale of the trophallaxis interaction network, and find that although bees exhibit bursty patterns of trophallaxis just as humans do in communication, the dynamics of simulated spreading on the trophallaxis networks is fast relative to randomized reference models, unlike in human temporal networks

Fabrication, characterization, and modeling of silicon multi-gate devices

Ph.DDOCTOR OF PHILOSOPH

Optimisation of pixel modules for the ATLAS inner tracker at the high-luminosity LHC

The Large Hadron Collider and its pre-accelerator complex will be upgraded in three steps to allow for the high luminosity phase. A factor of ten times more data will be collected in this period by facilitating the increased instantaneous luminosity being seven times as large as the original design value. A new inner tracker system is in preparation for the ATLAS detector in view of the high luminosity phase to start operation around 2026. This all silicon tracker relies on various innovative technologies to cope with the severe challenges arising from the increased luminosity. The pixel detector employs a new readout chip to decrease the pixel size to a fifth of the pixel size of the present generation to be able to disentangle all tracks in the high multiplicity environment close to the interaction point. Thanks to their reduced power dissipation and high charge collection efficiency after irradiation, thin planar n-in-p pixel sensors are ideally suited to cope with the expected unprecedented radiation damage. TCAD simulations are being performed to optimise the sensor layout for the new pixel cell size of 50x50um2. In this study, charge collection efficiency, electronic noise and electrical field properties are investigated both before and after irradiation. The RD53A prototype readout chip is used to build modules based on the proposed thin planar n-in-p sensors. The performance of different sensor designs is assessed by analysing data from various test-beam campaigns. The effects of storage time at room temperature for the ITk pixel detector during maintenance periods are reproduced on real modules. Pixel detector modules built with sensors of 100-150um thickness are characterised with testbeam measurements. The charge collection and hit efficiencies are compared before and after annealing at room temperature up to one year

NASA SBIR abstracts of 1991 phase 1 projects

The objectives of 301 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1991 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 301, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1991 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included