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  • Control and Optimization of Chemical Reactors with Model-free Deep Reinforcement Learning

    Alhazmi, Khalid (2020-07) [Thesis]
    Advisor: Sarathy, Mani
    Committee members: Shamma, Jeff S.; Pinnau, Ingo
    Abstract: Model-based control and optimization is the predominant paradigm in process systems engineering. The performance of model-based methods, however, rely heavily on the accuracy of the process model, which declines over the operation cycle due to various causes, such as catalyst deactivation, equipment aging, feedstock variability, and others. This work aims to tackle this challenge by considering two alternative approaches. The first approach replaces existing control and optimization methods with model-free reinforcement learning (RL). We apply a state-of-the-art reinforcement learning algorithm to a network of reactions, evaluate the performance of the RL controller in terms of setpoint tracking, disturbance rejection, and robustness to parameter uncertainties, and optimize the reward function to achieve the desired control and optimization performance. The second approach presents a novel framework for integrating Economic Model Predictive Control (EMPC) and RL for online model parameters estimation. In this framework, EMPC optimally operates the closed-loop system while maintaining closed-loop stability and recursive feasibility. At the same time, the RL agent continuously compares the measured state of the process with the model’s predictions, and modifies the model parameters accordingly to optimize the process. The performance of the proposed framework is illustrated on a network of reactions with challenging dynamics and practical significance.
  • Two-scale Homogenization and Numerical Methods for Stationary Mean-field Games

    Yang, Xianjin (2020-07) [Dissertation]
    Advisor: Gomes, Diogo A.
    Committee members: Shamma, Jeff S.; Parsani, Matteo; Achdou, Yves
    Mean-field games (MFGs) study the behavior of rational and indistinguishable agents in a large population. Agents seek to minimize their cost based upon statis- tical information on the population’s distribution. In this dissertation, we study the homogenization of a stationary first-order MFG and seek to find a numerical method to solve the homogenized problem. More precisely, we characterize the asymptotic behavior of a first-order stationary MFG with a periodically oscillating potential. Our main tool is the two-scale convergence. Using this convergence, we rigorously derive the two-scale homogenized and the homogenized MFG problems. Moreover, we prove existence and uniqueness of the solution to these limit problems. Next, we notice that the homogenized problem resembles the problem involving effective Hamiltoni- ans and Mather measures, which arise in several problems, including homogenization of Hamilton–Jacobi equations, nonlinear control systems, and Aubry–Mather theory. Thus, we develop algorithms to solve the homogenized problem, the effective Hamil- tonians, and Mather measures. To do that, we construct the Hessian Riemannian flow. We prove the convergence of the Hessian Riemannian flow in the continuous setting. For the discrete case, we give both the existence and the convergence of the Hessian Riemannian flow. In addition, we explore a variant of Newton’s method that greatly improves the performance of the Hessian Riemannian flow. In our numerical experiments, we see that our algorithms preserve the non-negativity of Mather mea- sures and are more stable than related methods in problems that are close to singular. Furthermore, our method also provides a way to approximate stationary MFGs.
  • Design and Synthesis of MXene Derived Materials for Advanced Electronics and Energy Harvesting Applications

    Tu, Shao Bo (2020-06-09) [Dissertation]
    Advisor: Zhang, Xixiang
    Committee members: Alshareef, Husam N.; Ooi, Boon S.; Li, Xiaohang; Xu, Bin
    In this thesis, we capitalize on the two-dimensional (2D) nature of MXenes by using them as precursors for the synthesis of 2D functional material. MXenes are easily intercalated with monovalent cations K, Na, Li due to their expanded d-spacing after etching. Based on these ideas, we have developed new synthesis processes of texture functional materials using MXenes as precursors. We have successfully synthesized two-dimensional Nb2C MXene based high aspect ratio ferroelectric potassium niobate (KNbO3) and well-oriented photoluminescent rare earth doped lithium niobate (LiNbO3:Pr3+) crystals, which have great potential in opto-electronics applications. In addition, this thesis demonstrates that poly(vinylidene fluoride) (PVDF)-based percolative composites using two-dimensional (2D) MXene nanosheets as fillers exhibit significantly enhanced dielectric permittivity. Furthermore, we fabricated MXene/in-plane aligned PVDF photo-thermo-mechanical solar tracking actuator for energy harvesting applications.
  • Bacterial Endophytes from Pioneer Desert Plants for Sustainable Agriculture

    Eida, Abdul Aziz (2020-06) [Dissertation]
    Advisor: Hirt, Heribert
    Committee members: Saad, Maged M.; Pain, Arnab; Aranda, Manuel; Kopriva, Stanislav
    One of the major challenges for agricultural research in the 21st century is to increase crop productivity to meet the growing demand for food and feed. Biotic (e.g. plant pathogens) and abiotic stresses (e.g. soil salinity) have detrimental effects on agricultural productivity, with yield losses being as high as 60% for major crops such as barley, corn, potatoes, sorghum, soybean and wheat, especially in semi-arid regions such as Saudi Arabia. Plant growth promoting bacteria isolated from pioneer desert plants could serve as an eco-friendly, sustainable solution for improving plant growth, stress tolerance and health. In this dissertation, culture-independent amplicon sequencing of bacterial communities revealed how native desert plants influence their surrounding bacterial communities in a phylogeny-dependent manner. By culture-dependent isolation of the plant endosphere compartments and a number of bioassays, more than a hundred bacterial isolates with various biochemical properties, such as nutrient acquisition, hormone production and growth under stress conditions were obtained. From this collection, five phylogenetically diverse bacterial strains were able to promote the growth of the model plant Arabidopsis thaliana under salinity stress conditions in a common mechanism of inducing transcriptional changes of tissue-specific ion transporters and lowering Na+/K+ ratios in the shoots. By combining a number of in vitro bioassays, plant phenotyping and volatile-mediated inhibition assays with next-generation sequencing technology, gas chromatography–mass spectrometry and bioinformatics tools, a candidate strain was presented as a multi-stress tolerance promoting bacterium with potential use in agriculture. Since recent research showed the importance of microbial partners for enhancing the growth and health of plants, a review of the different factors influencing plant-associated microbial communities is presented and a framework for the successful application of microbial inoculants in agriculture is proposed. The presented work demonstrates a holistic approach for tackling agricultural challenges using microbial inoculants from desert plants by combining culturomics, phenomics, genomics and transcriptomics. Microbial inoculants are promising tools for studying abiotic stress tolerance mechanisms in plants, and they provide an eco-friendly solution for increasing crop yield in arid and semi-arid regions, especially in light of a dramatically growing human population and detrimental effects of global warming and climate change.
  • Whole Genome Sequencing as a Tool to Study the Genomic Landscape of Pathogens

    Hala, Sharif (2020-06) [Dissertation]
    Advisor: Pain, Arnab
    Committee members: Merzaban, Jasmeen; Khashab, Niveen; Carr , Michael
    In healthcare settings and beyond, the ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) among other pathogens exchange antibiotic resistance and virulence factors and emerge as new infectious clones. According to the Saudi General Authority for Statistics (stats.gov.sa), Saudi Arabia is a country where more than 27 million pilgrims meet in annual continual mass-gathering events. This massive influx of people could introduce novel pathogens to the community that could not necessarily be detected with traditional culture-dependent clinical microbiological tests. Conventional clinical microbiology and environmental pathogen detection methods have had many limitations and narrow search scope. These methods can only target known and culturable pathogens. Over the past decade, applications of next-generation sequencing (NGS) and bioinformatics tools have revolutionized the way pathogens are detected and their relevant phenotypes such as clonal types, antibiotic resistance are predicted to aid in clinical decision making as additional practice to traditional clinical microbiology-based testing protocols. The aim of this study was to apply whole-genome sequencing (WGS) and bioinformatic analysis tools on clinical samples and bacterial isolates in order to pave the way for transforming current clinical microbiology practices in a tertiary referral hospital in Jeddah, Saudi Arabia. My attempt to utilize WGS as a tool on pathogenic strains in this study combined with the clinical data has resulted in discovering a silent outbreak of an emerging hypervirulent strain of Klebsiella pneumoniae (Chapter 2). Analysis of the strains antimicrobial profiles genetically has yielded the first characterization of a misidentified Klebsiella quasipneumoniae harboring plasmid-mediated carbapenemases of Klebsiella pneumoniae carbapenemases (KPC) (Chapter 3). Similarly, I was able to study mobile colistin resistance genes in the isolates and identify a novel occurrence of mcr-1 and mcr-8 (Chapter 4). I applied clinical metagenomic protocol on an intestinal biopsy of an inflammatory bowel disease patient with Crohn’s disease, where I identified an association of three co-occurring and an actively replicating non-tuberculosis mycobacteria (Chapter 5). The deployment of whole-genome sequencing and metagenomic in infectious disease surveillance and diagnostics could prove beneficial in limiting epidemics and detect transmission patterns of antimicrobial-resistant genes.
  • Hybrid Local/Nonlocal Continuum Mechanics Modeling and Simulation for Material Failure

    Wang, Yongwei (2020-06) [Dissertation]
    Advisor: Lubineau, Gilles
    Committee members: Thoroddsen, Sigurdur T.; Hoteit, Ibrahim; Florentin, Eric
    The classical continuum mechanics, which studies the mechanical behavior of structures based on partial differential equations, shows its deficiencies when it encounters a discontinuity. Peridynamics based on integral equations can simulate fracture but suffers from high computational costs. A hybrid local/nonlocal model combining the advantages of peridynamics with those of classical continuum mechanics can simulate fracture and reduce the computational cost. Under the framework of the hybrid local/nonlocal model, this research developed an approach and computational codes for fracture simulations. First, we developed the computational codes based on the hybrid model with a priori partition of the domain between local and nonlocal models to tackle engineering problems with relevant level of difficulty. Second, we developed a strength-induced approach to enhance the capability of the computational codes because the strength-induced approach can limit the peridynamic model to necessary computational steps at the time level and a relatively small zone at the space level during a simulation. The strength-induced approach also improved the hybrid models by enabling an automatic partition of the domain without manual involvement. At last, a strength-induced computational code was developed based on this research. This dissertation complemented and illustrated numerically some previous work of Cohmas laboratory, in which a new route was introduced toward simulating the whole process of material behaviors including elastic deformation, crack nucleation and propagation until structural failure.
  • Structural and Dynamic Profiles of the WT hFEN1 in solution

    Almulhim, Fatimah F. (2020-06) [Thesis]
    Advisor: Jaremko, Mariusz
    Committee members: Falqui, Andrea; Saikaly, Pascal
    Genomic DNA is under constant assault by environmental factors that introduce a variety of DNA lesions. Cells evolved several DNA repair and recombination mechanisms to remove these damages and ensure the integrity of the DNA material. A variety of specific proteins, called nucleases, processes toxic DNA structures that deviate from the heritable duplex DNA as common pathway intermediates. DNA-induced protein ordering is a common feature in all DNA repair nucleases. Still, the conformational requirement of the DNA and the protein and how they control the catalytic selectivity of the nuclease remain largely unknown. This study focus on the bases of catalytic activity of a protein belongs to the 5’ nuclease super-family called the human Flap endonuclease 1 (FEN1); it removes excess 5’ flaps that are generated during DNA replication. hFEN1 mutations and over-expression had been linked to a variety of cancers. This thesis aims to study the structural and dynamic properties of free hFEN1 and the catalytic activity of DNA-bound hFEN1 in solution utilizing the modern high-resolution multidimensional Nuclear Magnetic Resonance (NMR) spectroscopy. It was possible to depict the secondary structure and backbone conformation in solution of wild type (WT) hFEN1 by the usage of the improved list of assigned resonances, derived from the NMR 2D and 3D ¹⁵N-detected experiments and compared to the assignment with the previously published resonance assignment (BMRB id: 27160). I was successfully assigned the new spectrum and enhanced it by assigning seven more residues. Moreover, we tested the interaction of 1:10 ratio of hFEN1-Ca2+ with DNA by the ¹³C-detected 2D CACO experiment. The results indicate hFEN1:DNA interaction. Furthermore, parts of hFEN1 get more ordered/structured once DNA appears, thus we recorded the protein flexibly by 2D ¹H-¹⁵N TROSY-HSQC using the relaxation rate parameters: longitudinal R1, transverse R2 complemented with ¹⁵N-{¹H} NOEs (heteronuclear Overhauser enhancement). It was found that the overall molecular architecture is rigid, and the highest flexibility lies in the α2-α3 loop and arch (α4-α5) regions. Further analysis is needed to understand more profoundly the activity of hFEN1 in an atomic level by inducing mutations and testing the protein in various environmental conditions.
  • Thermo-Hydro-Mechanically Coupled Processes in Fractured Rocks

    Garcia, Adrian (2020-06) [Dissertation]
    Advisor: Santamarina, Juan Carlos
    Committee members: Vahrenkamp., Volker; Jónsson, Sigurjón; Bobet, Antonio
    Energy demand is driven by increasing population and quality of life. Fractures localize mechanical deformations and fluid flow, and they impede heat flow through the rock matrix. Therefore, fractures present a challenge to both the recovery of underground energy and long-term waste disposal solutions like carbon geological storage. Fracture are planar discontinuities that form when brittle rocks. The discrete element method can model the complex micromechanics of rock failure. In this thesis we present a digital rocks analogue which is used to explore 1) the rock brittle-to-ductile transition with increased confining stress 2) the meaning of friction in intact rocks and what factors control confinement-dependent strength, 3) exhumation damage and its effect on rocks strength, and 4) multistage loading. The design, analysis and construction of a large-scale true triaxial load frame opens the door to geophysical studies on fractured rock masses. The frame can subject large cubical rock specimens (50cm × 50cm × 50cm) to boundary stresses up to 3 MPa. Auxiliary systems include active acoustic monitoring, passive acoustic emissions sensing, and high-pressure fluid injection. The evolution of P-wave velocity under anisotropic stress demonstrate the device’s capabilities. The true triaxial load-frame and the high-pressure fluid injection system are used to study hydraulic fracturing in pre-fractured media. We explore the competing influences of stress and rock mass fabric. Notably, even under extreme stress anisotropy, the fluid invades all fracture sets of our pre-fractured specimen. Fracture 5 intersections act as flow conduits and feed the invading fluid into the adjacent fractures, and local phenomena such as gouge-displacive fingering are identified. Thermal contact resistance impedes heat flow between neighboring rock blocks in fractured rocks. Contact resistance manifests as a discontinuous thermal gradient. It strongly influences the rock effective thermal conductivity and makes it sensitive to water saturation, stress, and the presence of gouge material. Finally, we conduct detailed thermal conductivity measurements on sand-silt gouge mixtures and propose physics-inspired models that accurately predict the thermal conductivity and mass density of dry and wet specimens as a function of stress and fines content.
  • Ultraviolet Band Based Underwater Wireless Optical Communication

    Sun, Xiaobin (2020-05) [Dissertation]
    Advisor: Ooi, Boon S.
    Committee members: Shamma, Jeff S.; Jones, Burton; Peng, Gang Ding
    Underwater wireless optical communication (UWOC) has attracted increasing interest for data transfer in various underwater activities. However, the complexity of the water environment poses considerable challenges to establish aligned and reliable UWOC links. Therefore, solutions that are capable of relieving the requirements on positioning, acquisition and tracking (PAT) are highly demanded. Different from the conventional blue-green light band utilized in UWOC, ultraviolet (UV) light is featured with low solar background noise, non-line-of-sight (NLOS) and good secrecy. The proposed work is directed towards the demonstration and evaluating the feasibility of high- speed NLOS UWOC for easing the strict requirement on alignment, and thus circumvent the issues of scintillation, deep-fading, and complete signal blockage presented in conventional LOS UWOC. This work was first started with the investigation of proper NLOS configurations. Path loss (PL) was chosen as a figure-of-merit for link performance. With the understanding of favorable NLOS UWOC configurations, we established a 377-nm laser-based, the first-of-its-kind NLOS UWOC link. The practicality of such NLOS UWOC links has been further tested in a field trial. Besides the underwater communication links, UV-based NLOS is also appealing to be the link for direct communication across the wavy water-air interface. Investigations for such a direct communication link have been carried out to study data rate, coverage and robustness to the dynamic wave movement, based on the performance of different modulation schemes, including non-return-to-zero (NRZ)-OOK and quadrature amplitude modulation (QAM)-orthogonal frequency division multiplexing (OFDM). Further this study, an in-Red Sea canal field in-situ test has been conducted, showing strong robustness of the system. In addition, an in-diving pool drone-aided real-application deployment has been carried on. The trial results indicate link stability, which alleviates the issues brought about by the misalignment and mobility in harsh environments, paving the way towards real applications. Our studies pave the way foreventual applications of UWOC byrelieving the strict requirements on PAT using UV-based NLOS. Such modality is much sought-after for implementing robust, secure, and high-speed UWOC links in harsh oceanic environments.
  • An Experimental and Theoretical Investigation of Pressure-Induced Wetting Transitions

    Ahmad, Zain (2020-05) [Thesis]
    Advisor: Mishra, Himanshu
    Committee members: Nunes, Suzana; Farooq, Aamir; Ghaffour, Noreddine
    A number of industries suffer from inefficient use of energy resources due to frictional drag manifesting at solid-liquid interfaces. A simple method to reduce frictional drag under laminar flow conditions is to entrap air at the liquid-solid interface – in wetting state known as Cassie state. Over time, however, the entrapped air can be lost, and the Cassie state transitions to the fully-filled or the Wenzel state, thereby increasing the frictional drag dramatically. In particular, many practical applications expose surfaces to elevated pressures, and it is thus crucial to investigate pressure-induced Cassie-to-Wenzel transitions in gas-entrapping microtextured surfaces. However, there is a dearth of experimental techniques that can provide high-resolution optical images during wetting transitions at elevated pressures. In this thesis, we address this challenge designing and developing an inexpensive and robust pressure device that can act as an accessory for confocal laser scanning microscopy (CLSM). Equipped with this platform, we set out to visualize Cassie-to-Wenzel transitions in FDTS-coated circular doubly reentrant cavities (DRCs) and simple cavities. We demonstrate that on immersion in water, DRCs stabilize water-air interface, such that on the application of the external pressure as water penetrates into the DRCs, the liquid meniscus at the inlet remains pinned. In stark contrast, in SCs the water meniscus does not get pinned at the inlet, and it keeps on advancing with the increasing pressure along the cavity walls. Since localized laser heating in CLSM can influence wetting transitions, we utilized another custom-built pressure cell connected with upright optical microscopy as a complementary platform. We investigated the following wetting transitions: (i) breakthrough pressures (BtPs), defined as the pressure at which the liquid-vapor meniscus touches the cavity floor, by gradually ramping the external pressure, and (ii) wetting transitions at fixed pressures below the BtP. To understand the physical mechanisms underlying our experimental results, we utilized the Fick’s diffusion model and found that the consideration of air diffusion into water under elevated pressures is crucial. To conclude, we hope that the experimental and theoretical results presented here would advance the rational development of robust gas-entrapping microtextured surfaces for a myriad of applications
  • Conservation and Regulation of the Essential Epigenetic Regulator UHRF1 Across Vertebrata Orthologs

    Aljahani, Abrar (2020-05) [Thesis]
    Advisor: Fischle, Wolfgang
    Committee members: Arold, Stefan T.; Aranda, Manuel
    UHRF1 is a critical epigenetic regulator which serves as a molecular model for understanding the crosstalk between histone modification and DNA methylation. It is integrated in the process of DNA maintenance methylation through its histone ubiquitylation activity, ultimately functioning as a recruiter of DNA methyltransferase 1 (DNMT1). As the faithful propagation of DNA methylation patterns during cell division is a common molecular phenomenon among vertebrates, understanding the underlying conserved mechanism of UHRF1 for executing such a key process is important. Here, I present a broad-range evolutionary comparison of UHRF1 binding behavior and enzymatic activity of six species spanning across the vertebrata subphylum. According to their distinct binding modes to differentially methylated histone H3, a pattern is emerging which separates between mammalian and nonmammalian orthologs. H. sapiens, P. troglodytes and M. musculus UHRF1 orthologs utilize the functionality of both TTD and PHD domains to interact with histone H3 peptides, while G. gallus, X. laevis, and D. rerio employ either TTD or PHD. Further, UHRF1 allosteric regulation by 16:0 PI5P is a unique case to primate orthologs where H3K9me3 peptide binding is enhanced upon hUHRF1 and pUHRF1 interacting with 16:0 PI5P. This is due to their closed and autoinhibited conformation wherein TTD is blocked by the PBR region in linker 4. 16:0 PI5P outcompetes TTD for PBR binding resulting in a release of TTD blockage, hence, enhanced H3K9me3 binding. However, owing to the lack of phosphatidylinositol binding specificity and reduced sequence conservation of linker 4, the regulatory impact of 16:0 PI5P in avian and lower vertebrate orthologs could not be detected. Additionally, all UHRF1 orthologs exert their ubiquitylation enzymatic activity on histone H3 substrates, supporting the notion that the overall functionality of UHRF1 orthologs is conserved, despite their divergent molecular approaches. Taken together, my findings suggest that UHRF1 orthologs adopt distinct conformational states with a differential response to the allosteric regulators 16:0 PI5P and hemi-methylated DNA.
  • A Green and Powerful Method toward Well-defined Polycarbonates and Polycarbonate-Based Block Copolymers from CO2 and Epoxides

    Alzahrany, Yahya (2020-05) [Dissertation]
    Advisor: Hadjichristidis, Nikos
    Committee members: Nunes, Suzana Pereira; Bakr, Osman; Avgeropoulos, Apostolos
    The use of waste gas such as carbon dioxide (CO2) to prepare useful and valuable polymers benefits both the economy and the environment. Various strategies have been developed to reduce CO2 emission as well as to transfer CO2 into high-value products. CO2/epoxide copolymerization is one of the most promising methods of not only reducing the CO2 emission from the atmosphere but also producing biodegradable CO2-based materials that are CO2 as source-abundant, renewable, cheap, non-flammable and non-toxic. However, the activation of CO2 is one of several problems associated with the polymerization of CO2 due to its stability as a thermodynamic end product. Herein, my dissertation describes the effectiveness of new lithium/phosphazene complexes to generate highly active species for CO2/epoxide copolymerization and to capture/activate CO2 molecules for the nucleophilic attack of the active species. Well-defined polycarbonates and polycarbonate-based block copolymers are produced that have control of molecular weights, unimodal distributions and narrow molecular weight distributions (Chapter 3 and 4). Besides, these complexes provide access to prepare CO2-based triblock copolymers that are powerful candidates to serve as the next generation of thermoplastic elastomers (Chapter 4). Additionally, these complexes are applied for the anionic polymerization of petrochemical-based sources such as styrene and dienes producing polymers in faster rate of polymerization with control of molecular characteristics (Chapter 2). A general introduction of polymers and their classification based on composition, chemical structure, mechanical properties, degradability, source, applications, and preparative methods, is covered in Chapter 1
  • Assessing sharks and rays in shallow coastal habitats using baited underwater video and aerial surveys in the Red Sea

    Mcivor, Ashlie (2020-05) [Thesis]
    Advisor: Berumen, Michael Lee
    Committee members: Jones, Burton; Coker, Darren; Spaet , Julia
    Years of unregulated fishing activity have resulted in low abundances of elasmobranch species in the Saudi Arabian Red Sea. Coastal populations of sharks and rays in the region remain largely understudied and may be at risk from large-scale coastal development projects. Here we aim to address this pressing need for information by using fish market, unmanned aerial vehicle and baited remote underwater video surveys to quantify the abundance and diversity of sharks and rays in coastal habitats in the Saudi Arabian central Red Sea. Our analysis showed that the majority of observed individuals were batoids, specifically blue-spotted ribbontail stingrays (Taeniura lymma) and reticulate whiprays (Himantura sp.). Aerial surveys observed a catch per unit effort two orders of magnitude greater than underwater video surveys, yet did not detect any shark species. In contrast, baited camera surveys observed both lemon sharks (Negaprion acutidens) and tawny nurse sharks (Nebrius ferrugineus), but in very low quantities (one individual of each species). The combination of survey techniques revealed a higher diversity of elasmobranch presence than using either method alone, however many species of elasmobranch known to exist in the Red Sea were not detected. Our results suggest that aerial surveys are a more accurate tool for elasmobranch abundance estimates in low densities over mangrove-associated habitats. The importance of inshore habitats, particularly for batoids, calls for a deeper understanding of habitat use in order to protect these environments in the face of unregulated fishing, mangrove removal, and anticipated developments along the coastline of the Saudi Arabian Red Sea.
  • Advanced Sediment Characterization

    Salva Ramirez, Marisol (2020-05) [Dissertation]
    Advisor: Santamarina, Juan Carlos
    Committee members: Ki Kim, Hyun; Vahrenkamp., Volker; Ahmed, Shehab
    Soil data accumulated during the last century and more recent developments in sensors and information technology prompt the development of new geotechnical solutions for soil assessment. We have advanced three complementary tools: Lab-on-a-Bench, the soil properties database with corresponding IT Tool and the in-situ characterization Multiphysics Probe. Lab-on-a-Bench technology combines cutting-edge sensors and sensing concepts within compact devices and effective laboratory protocols to allow multi physics soil characterization: specific surface measurements for fine-grained soils and particle size distribution, shape, packing densities and angle of repose for coarse-grained soils using image analysis and corresponding devices. The soil properties database and complementary IT Tool provide a self-consistent set of soil parameters based on known properties. The advances in in-situ characterization focus on a Multiphysics Probe and include measurements of remnant magnetization to identify metalliferous sediments for deep-sea mining applications and shear wave measurements for stiffness assessments. All methods, protocols, devices and technology are applied to Red Sea sediments to establish a baseline for future industrial and economic developments
  • A Computational Study of Ammonia Combustion

    Khamedov, Ruslan (2020-05) [Thesis]
    Advisor: Im, Hong G.
    Committee members: Roberts, William Lafayette; Knio, Omar; Parsani, Matteo
    The utilization of ammonia as a fuel is a pragmatic approach to pave the way towards a low-carbon economy. Ammonia compromises almost 18 % of hydrogen by mass and accepted as one of the hydrogen combustion enablers with existing infrastructure for transportation and storage. From an environmental and sustainability standpoint, ammonia combustion is an attractive energy source with zero carbon dioxide emissions. However, from a practical point of view, the direct combustion of ammonia is not feasible due to the low reactive nature of ammonia. Due to the low combustion intensity, and the higher nitrogen oxide emission, ammonia was not fully investigated and there is still a lack of fundamental knowledge of ammonia combustion. In this thesis, the computational study of ammonia premixed flame characteristics under various hydrogen addition ratios and moderate or intense low oxygen dilution (MILD) conditions were investigated. Particularly, the heat release characteristics and dominant reaction pathways were analyzed. The analysis revealed that the peak of heat release for ammonia flame occurs near burned gas, which raises a question regarding the physics of this. Further analysis identified the dominant reaction pathways and the intermediate species (NH2 and OH), which are mainly produced in the downstream and back diffused to the leading edge and produce some heat in the low-temperature zone. To overcome low reactivity and poor combustion performance of pure ammonia mixture, the onboard ammonia decomposition to hydrogen and nitrogen followed by blending ammonia with hydrogen is a feasible approach to improve ammonia combustion intensity. With increasing hydrogen amount in the mixture, the enhancement of heat release occurs due to both transport and chemical effect of hydrogen. Another approach to mitigate the low reactive nature of ammonia may be eliminated by applying the promising combustion concept known as MILD combustion. The heat release characteristics and flame marker of ammonia turbulent premixed MILD combustion were investigated. The high fidelity numerical simulation was performed to answer fundamental questions of ammonia turbulent premixed combustion characteristics.
  • SeedQuant: A Deep Learning-based Census Tool for Seed Germination of Root Parasitic Plants

    Ramazanova, Merey (2020-04-30) [Thesis]
    Advisor: Ghanem,Bernard
    Committee members: Wonka, Peter; Thabet, Ali Kassem
    Witchweeds and broomrapes are root parasitic weeds that represent one of the main threats to global food security. By drastically reducing host crops' yield, the parasites are often responsible for enormous economic losses estimated in billions of dollars annually. Parasitic plants rely on a chemical cue in the rhizosphere, indicating the presence of a host plant in proximity. Using this host dependency, research in parasitic plants focuses on understanding the necessary triggers for parasitic seeds germination, to either reduce their germination in presence of crops or provoke germination without hosts (i.e. suicidal germination). For this purpose, a number of synthetic analogs and inhibitors have been developed and their biological activities studied on parasitic plants around the world using various protocols. Current studies are using germination-based bioassays, where pre-conditioned parasitic seeds are placed in the presence of a chemical or plant root exudates, from which the germination ratio is assessed. Although these protocols are very sensitive at the chemical level, the germination rate recording is time consuming, represents a challenging task for researchers, and could easily be sped up leveraging automated seeds detection algorithms. In order to accelerate such protocols, we propose an automatic seed censing tool using computer vision latest development. We use a deep learning approach for object detection with the algorithm Faster R-CNN to count and discriminate germinated from non-germinated seeds. Our method has shown an accuracy of 95% in counting seeds on completely new images, and reduces the counting time by a signi cant margin, from 5 min to a fraction of second per image. We believe our proposed software \SeedQuant" will be of great help for lab bioassays to perform large scale chemicals screening for parasitic seeds applications.
  • Hierarchical Matrix Operations on GPUs

    Boukaram, Wagih Halim (2020-04-26) [Dissertation]
    Advisor: Keyes, David E.
    Committee members: Ketcheson, David I.; Hadwiger, Markus; Turkiyyah, George; Darve, Eric F.
    Large dense matrices are ubiquitous in scientific computing, arising from the discretization of integral operators associated with elliptic pdes, Schur complement methods, covariances in spatial statistics, kernel-based machine learning, and numerical optimization problems. Hierarchical matrices are an efficient way for storing the dense matrices of very large dimension that appear in these and related settings. They exploit the fact that the underlying matrices, while formally dense, are data sparse. They have a structure consisting of blocks many of which can be well-approximated by low rank factorizations. A hierarchical organization of the blocks avoids superlinear growth in memory requirements to store n × n dense matrices in a scalable manner, requiring O(n) units of storage with a constant depending on a representative rank k for the low rank blocks. The asymptotically optimal storage requirement of the resulting hierarchical matrices is a critical advantage, particularly in extreme computing environments, characterized by low memory per processing core. The challenge then becomes to develop the parallel linear algebra operations that can be performed directly on this compressed representation. In this dissertation, I implement a set of hierarchical basic linear algebra subroutines (HBLAS) optimized for GPUs, including hierarchical matrix vector multiplication, orthogonalization, compression, low rank updates, and matrix multiplication. I develop a library of open source batched kernel operations previously missing on GPUs for the high performance implementation of the H2 operations, while relying wherever possible on existing open source and vendor kernels to ride future improvements in the technology. Fast marshaling routines extract the batch operation data from an efficient representation of the trees that compose the hierarchical matrices. The methods developed for GPUs extend to CPUs using the same code base with simple abstractions around the batched routine execution. To demonstrate the scalability of the hierarchical operations I implement a distributed memory multi-GPU hierarchical matrix vector product that focuses on reducing communication volume and hiding communication overhead and areas of low GPU utilization using low priority streams. Two demonstrations involving Hessians of inverse problems governed by pdes and space-fractional diffusion equations show the effectiveness of the hierarchical operations in realistic applications.
  • Evaluating the Application of Allele Frequency in the Saudi Population Variant Detection

    Alsaedi, Sakhaa (2020-04-26) [Thesis]
    Advisor: Hoehndorf, Robert
    Committee members: Gao, Xin; Gojobori, Takashi
    Human Mendelian disease in Saudi Arabia is both significant and challenging. Next-generation sequencing (NGS) has resulted in important discoveries of the genetic variants responsible for inherited disease. However, the success of clinical genomics using NGS requires accurate and consistent identification of rare genome variants. Rarity is one very important criterion for pathogenicity. Here we describe a model to detect variants by analyzing allele frequencies of a Saudi population. This work will enhance the opportunity to improve variant calling workflow to gain robust frequency estimates in order to better detect rare and unusual variants which are frequently associated with inherited disease.
  • Improved Design of Quadratic Discriminant Analysis Classi er in Unbalanced Settings

    Bejaoui, Amine (2020-04-23) [Dissertation]
    Advisor: Alouini, Mohamed Slim
    Committee members: Huser, Raphaël G.; Kammoun, Abla
    The use of quadratic discriminant analysis (QDA) or its regularized version (RQDA) for classi cation is often not recommended, due to its well-acknowledged high sensitivity to the estimation noise of the covariance matrix. This becomes all the more the case in unbalanced data settings for which it has been found that R-QDA becomes equivalent to the classi er that assigns all observations to the same class. In this paper, we propose an improved R-QDA that is based on the use of two regularization parameters and a modi ed bias, properly chosen to avoid inappropriate behaviors of R-QDA in unbalanced settings and to ensure the best possible classi cation performance. The design of the proposed classi er builds on a re ned asymptotic analysis of its performance when the number of samples and that of features grow large simultaneously, which allows to cope e ciently with the high-dimensionality frequently met within the big data paradigm. The performance of the proposed classi er is assessed on both real and synthetic data sets and was shown to be much higher than what one would expect from a traditional R-QDA.
  • Computation of High-Dimensional Multivariate Normal and Student-t Probabilities Based on Matrix Compression Schemes

    Cao, Jian (2020-04-22) [Dissertation]
    Advisor: Genton, Marc G.
    Committee members: Keyes, David E.; Rue, Haavard; Panaretos, Victor
    The first half of the thesis focuses on the computation of high-dimensional multivariate normal (MVN) and multivariate Student-t (MVT) probabilities. Chapter 2 generalizes the bivariate conditioning method to a d-dimensional conditioning method and combines it with a hierarchical representation of the n × n covariance matrix. The resulting two-level hierarchical-block conditioning method requires Monte Carlo simulations to be performed only in d dimensions, with d ≪ n, and allows the dominant complexity term of the algorithm to be O(n log n). Chapter 3 improves the block reordering scheme from Chapter 2 and integrates it into the Quasi-Monte Carlo simulation under the tile-low-rank representation of the covariance matrix. Simulations up to dimension 65,536 suggest that this method can improve the run time by one order of magnitude compared with the hierarchical Monte Carlo method. The second half of the thesis discusses a novel matrix compression scheme with Kronecker products, an R package that implements the methods described in Chapter 3, and an application study with the probit Gaussian random field. Chapter 4 studies the potential of using the sum of Kronecker products (SKP) as a compressed covariance matrix representation. Experiments show that this new SKP representation can save the memory footprint by one order of magnitude compared with the hierarchical representation for covariance matrices from large grids and the Cholesky factorization in one million dimensions can be achieved within 600 seconds. In Chapter 5, an R package is introduced that implements the methods in Chapter 3 and show how the package improves the accuracy of the computed excursion sets. Chapter 6 derives the posterior properties of the probit Gaussian random field, based on which model selection and posterior prediction are performed. With the tlrmvnmvt package, the computation becomes feasible in tens of thousands of dimensions, where the prediction errors are significantly reduced.

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