Recent Submissions

  • Mechanistic Investigation into the Conversion of Methanol to Hydrocarbons by Zeolite Catalysts

    Liu, Zhaohui (2018-10)
    Catalytic conversion of methanol to hydrocarbons (MTH) provides an alternative route to the production of fuels and important industrial chemicals that are currently mainly produced from the refinery of petroleum. The ability to control the product distribution of MTH according to the demands of specific applications is of crucial importance, which relies on the thorough understanding of the reaction pathways and mechanisms. Despite the significant research efforts devoted to zeolite-catalyzed MTH, it remains a challenge to establish a firm correlation between the physicochemical properties of zeolites and their catalytic activity and selectivity. In this dissertation, we designed a series of experiments to gain fundamental understanding of how the structural and compositional parameters of zeolites influence their catalytic performances in MTH. We investigated different types of zeolites, covering large-pore Beta, medium-pore ZSM-5, and small-pore DDR zeolites, and tune their crystallite size/diffusion length, hierarchical (mesoporous) structure, and Si/Al ratio (density of acid sites) by controlled synthesis or post-synthesis treatments. The influence of mesoporosity of a zeolite catalyst on its catalytic performance for MTH, with zeolite Beta, was first investigated. The shorter diffusion length associated with the hierarchical structure results in a lower ethylene selectivity but higher selectivity towards C4-C7 aliphatics. Then we investigated the correlation between the Al content and the ethylene selectivity by ZSM-5 zeolites with similar crystal sizes but varied Si/Al ratios. We realized that ethylene selectivity is promoted with the increase of aluminum content in the framework. These two observations can be explained by the same mechanistic reason: the ethylene selectivity is associated with the propagation degree of the aromatics catalytic cycle and essentially determined by the number of the acid sites that methylbenzenes would encounter before they exit the zeolite crystallite. Last we explored how to maximize the propylene selectivity by tuning the physicochemical properties of DDR zeolites. Due to the confined pore space in DDR, the propagation of olefins-based catalytic cycle can be preferentially promoted in a tunable manner, which cannot be realized with zeolites having larger pores. Thus, the propylene selectivity increases with increasing the Si/Al ratio and decreasing the crystallite size.
  • Urban Image Analysis with Convolutional Sparse Coding

    Affara, Lama (2018-09-18)
    Urban image analysis is one of the most important problems lying at the intersection of computer graphics and computer vision research. In addition, Convolutional Sparse Coding (CSC) is a well-established image representation model especially suited for image restoration tasks. This dissertation handles urban image analysis using an asset extraction framework, studies CSC for the reconstruction of both urban and general images using supervised data, and proposes a better computational approach to CSC. Our asset extraction framework uses object proposals which are currently used for increasing the computational efficiency of object detection. In this dissertation, we propose a novel adaptive pipeline for interleaving object proposals with object classification and use it as a formulation for asset detection. We first preprocess the images using a novel and efficient rectification technique. We then employ a particle filter approach to keep track of three priors, which guide proposed samples and get updated using classifier output. Tests performed on over 1000 urban images demonstrate that our rectification method is faster than existing methods without loss in quality, and that our interleaved proposal method outperforms current state-of-the-art. We further demonstrate that other methods can be improved by incorporating our interleaved proposals. We also extend the applicability of the CSC model by proposing a supervised approach to the problem, which aims at learning discriminative dictionaries instead of purely reconstructive ones. We incorporate a supervised regularization term into the traditional unsupervised CSC objective to encourage the final dictionary elements to be discriminative. Experimental results show that using supervised convolutional learning results in two key advantages. First, we learn more semantically relevant filters in the dictionary and second, we achieve improved image reconstruction on unseen data. We finally present two computational contributions to the state of the art in CSC. First, we significantly speed up the computation by proposing a new optimization framework that tackles the problem in the dual domain. Second, we extend the original formulation to higher dimensions in order to process a wider range of inputs, such as RGB images and videos. Our results show up to 20 times speedup compared to current state-of-the-art CSC solvers.
  • Polynuclear Rare-earth (RE) based Metal-Organic Frameworks (MOFs): From Topological Exploration to Preparation of Tailor-made MOFs

    Assen, Ayalew H. (2018-09)
    Metal-organic frameworks (MOFs) have emerged as a unique class of solid-state materials, exemplifying the power of combining organic and inorganic chemistries to address the enduring challenge pertaining to designing solid state materials with desired attributes. Notably, a myriad of MOFs were constructed in the last two decades. In particular, the use of well-defined polyatomic clusters as molecular building blocks (MBBs) permitted access to the looked-for geometrical features, incorporated in preselected building units prior to the assembly process, guiding the assembly of a targeted network. Nevertheless, the diverse coordination modes and geometries of rareearth (RE) elements requires the introduction of a sophisticated controlled approach for their use as polynuclear cluster MBBs. Subsequently, our group has introduced the use of 2-fluorobenzoic acid (2-FBA) modulator that consistently allows the in situ control and formation of multi-nuclear RE MBBs. The presented work in this thesis demonstrates the use of elaborate RE MBBs and their successful deployment in reticular chemistry for the construction of particular MOF platforms expressing unique properties in term of gas separations. Accordingly, the RE hexanuclear clusters were used to construct fcu- and fluMOF platforms with controlled pore-aperture sizes. Markedly, the isolated RE-MOFs, REfum-fcu-MOF and RE-bqdc-flu-MOF, showed unprecedented paraffin/isoparaffin molecular sieving. Further tuning of the windows of RE-fcu-MOFs afforded the assembly of a MOF suitable for propylene/propane separation. The exceptional thermal and chemical stability and high adsorption selectivity of some of these MOFs prompted us to explore the fcu-MOF platform for selective removal of H2S/CO2 from CH4 and for sensing of toxic gases, namely H2S and NH3. Additionally, the research presented in this dissertation highlights the topological exploration for the formation of new MOFs: i) highly-connected polyatomic RE-MOFs in combination with tetrahedrally oriented tetracarboxylate ligands afforded the formation MOFs with new underlying topologies, namely kna-, kel- and kem-MOFs; ii) mixed-metal approach (RE plus other elements) was employed to fabricate MOFs containing in situ formed metalo-linker MBBs that are difficult to be pre-assembled by organic synthesis; iii) supermolecular building layer (SBL) approach was extended from the prevalent sql to the less explored double sql layer for the rational design of pillared MOFs.
  • Free Space Optics for 5G Backhaul Networks and Beyond

    Alheadary, Wael (2018-08)
    The exponential increase of mobile users and the demand for high-speed data services has resulted in signi cant congestions in cellular backhaul capacity. As a solution to satisfy the tra c requirements of the existing 4G network, the 5G net- work has emerged as an enabling technology and a fundamental building block of next-generation communication networks. An essential requirement in 5G backhaul networks is their unparalleled capacity to handle heavy tra c between a large number of devices and the core network. Microwave and optic ber technologies have been considered as feasible solutions for next-generation backhaul networks. However, such technologies are not cost e ective to deploy, especially for the backhaul in high-density urban or rugged areas, such as those surrounded by mountains and solid rocks. Addi- tionally, microwave technology faces alarmingly challenging issues, including limited data rates, scarcity of licensed spectrum, advanced interference management, and rough weather conditions (i.e., rain, which is the main weather condition that a ects microwave signals the most). The focus of this work is to investigate the feasibility of using free-space-optical (FSO) technology in the 5G cellular backhaul network. FSO is a cost-e ective and wide-bandwidth solution as compared to traditional backhaul solutions. However, FSO links are sensitive to atmospheric turbulence-induced fad- ing, path loss, and pointing errors. Increasing the reliability of FSO systems while still exploiting their high data rate communications is a key requirement in the de- ployment of an FSO backhaul network. Overall, the theoretical models proposed in this work will be shown to enhance FSO link performance. In the experimental direction, we begin by designing an integrated mobile FSO system. To the best of our knowledge, no work in the literature has addressed the atmospheric path loss characterization of mobile FSO channels in a coastal envi- ronment. Therefore, we investigate the impact of weather e ects in Thuwal, Saudi Arabia, over FSO links using outdoor and indoor setups. For the indoor experiments, results are reported based on a glass climate chamber in which we could precisely control the temperature and humidity.
  • Autoignition chemistry of liquid and gaseous fuels in non-premixed systems

    Alfazazi, Adamu (2018-08)
    Heat-release in CI engines occurs in the presence of concentration and temperature gradients. Recognizing the need for a validation of chemical kinetic models in transport-affected systems, this study employs non-premixed systems to better understand complex couplings between low/high temperature oxidation kinetics and diffusive transport. This dissertation is divided into two sections. In the first section, a two-stage Lagrangian model compares model prediction of ignition delay time and experimental data from the KAUST ignition quality tester, and ignition data for liquid sprays in constant volume combustion chambers. The TSL employed in this study utilizes detailed chemical kinetics while also simulating basic mixing processes. The TSL model was found to be efficient in simulating IQT in long ignition delay time fuels; it was also effective in CVCC experiments with high injection pressures, where physical processes contributed little to ignition delay time. In section two, an atmospheric pressure counterflow burner was developed and fully validated. The counterflow burner was employed to examine the effects of molecular structure on low/high temperature reactivity of various fuels in transport-affected systems. These effects were investigated through measurement of conditions of extinction and ignition of various fuel/oxidizer mixtures. Data generated were used to validate various chemical kinetic models in diffusion flames. Where necessary, suggestions were made for improving these models. For hot flames studies, tested fuels included C3-C4 alcohols and six FACE gasoline fuels. Results for alcohols indicated that the substituted alcohols were less reactive than the normal alcohols. The ignition temperature of FACE gasoline was found to be nearly identical, while there was a slight difference in their extinction limits. Predictions by Sarathy et al. (2014) alcohol combustion model, and by the gasoline surrogate model (Sarathy et al., 2015), agreed with the experimental data. For cool diffusion flames studies, tested fuels included butane isomers, naphtha, gasolines and their surrogates. Results revealed that the addition of ozone successfully established cool flames in the fuels at low and moderate strain rates. Numerical simulations were performed to replicate the extinction limits of the cool flames of butane isomers. The model captured experimental trends for both fuels; but over-predicted their extinction limits.
  • Paving the Way for Efficient Content Delivery in Mobile Networks

    Lau, Chun Pong (2018-07-10)
    The flexibility of future mobile networks exploiting modern technologies such as cloud-optimized radio access and software-defined networks opens a gateway to deploying dynamic strategies for live and on-demand content delivery. Traditional live broadcasting systems are spectral inefficient. It takes up a lot more radio spectrum than that of mobile networks, to cover the same size of an area. Furthermore, content caching at base stations reduces network traffic in core networks. However, numerous duplicated copies of contents are still transmitted in the unicast fashion in radio access networks. It consumes valuable radio spectrum and unnecessary energy. Finally, due to the present of numerous mobile receivers with a wide diversity of wireless channels in a base station coverage area, it is a challenge to select a proper modulation scheme for video broadcasting to optimize the quality of services for users. In this thesis, the challenges and the problems in the current strategies for content delivery are addressed. A holistic novel solution is proposed that considers user preferences, user mobility, device-to-device communication, physical-layer resource allocation, and video quality prediction. First, a system-level scheduling framework is introduced to increase the spectral efficiency on broadcasting live contents onto mobile networks. It considers the audience preferences for allocating radio resources spatially and temporally. Second, to reduce the redundant transmissions in radio access networks, a content distribution system that exploits user mobility is proposed that utilizes the urban-scale user mobility and broadcasting nature of wireless communication for delay-tolerant large size content. Third, to further reduce the energy consumption in network infrastructure, a content distribution system that relies on both user mobility, and device-to-device communication is proposed. It leverages the mobile users as content carriers to offload the heavy mobile traffic from network-level onto device-level. Fourth, to mitigate the multi-user channel diversity problem, a cross-layer approach is deployed to increase the video quality for users especially for those who have a low signal-to-noise ratio signal. Finally, data mining techniques are employed to predict video qualities of wireless transmissions over mobile networks. The holistic solution has been empirically developed and evaluated. It achieves high spectral and energy efficiency and mitigates the video quality degradation in mobile networks.
  • Ecology of the Mangrove Microbiome

    Booth, Jenny (2018-07)
    Plants and animals have evolved unique morpho-physiological adaptions to cope with the harsh and steep environmental gradients that characterise the mangrove ecosystem. However, the capacity of these two main components of the system to thrive, and the extraordinary productivity of mangrove forests in extreme conditions, has been overlooked in terms of the role of the microbiome. By combining approaches that included molecular microbial ecology, biogeochemical analyses, microscopy, raman spectroscopy and microsensor measurements, this thesis aimed to investigate the potential role of bacterial symbiosis in the adaptation of mangrove crabs to their environment and subsequently how these different animals modify their environment. Finally, with a field-based approach monitoring microbial communities, sediment metabolism and plant performance, the thesis aimed to investigate the plant/animal/bacterial dynamics in relation to seasonal environmental changes to contribute to understand the mangrove plant productivity paradox of high productivity under conditions of limited nutrents. Crab species were associated with distinct gill-bacteria communities, that produced carotenoids, according with their level of terrestrial adaptation. These carotenoids may be involved in protecting the gills from oxidative stress during air exposure. The main groups of ecosystem engineering crabs in mangroves had significant but diverse effects on the sediment environment and microbiome predominantly related to their ecology (i.e. filter feeder vs herbivore). Burrows increase aerobic microbial activity in the immediate burrow wall with a cascade effect on sediment microbial communities and nutrient distribution observed consistently across mangroves in different locations and with diverse environmental conditions. Microorganisms play an important role in adapting crabs on their evolutionary path to land and could contribute to the success of their colonization. At high population densities, of more than 50 individuals per square meter in some mangroves, these crabs deeply impact the functioning of the mangrove ecosystem, affecting microbial networks and nutrient recycling in the sediment, which may ameliorate conditions for plant growth. The microbiome is an understudied component of mangroves that lies at the basis of the functioning of these systems, influencing the success of the animal inhabitants (ecosystem engineers) that deeply modify the sediment microbiome, therefore influencing ecosystem functioning and resilience and, potentially, the success of the plants themselves (ecosystem architects).
  • Single molecule analysis of the diffusion and conformational dynamics

    Abadi, Maram (2018-07)
    Spatial and temporal dynamics of polymer chains play critical roles in their rheological properties, which have a significant influence on polymer processing and fabrication of polymer-based (nano) materials. Many theoretical and experimental studies have aimed at understanding polymer dynamics at the molecular level that give rise to its bulk phase properties. While much progress has been made in the field over the past ~60 years, many aspects of polymers are still not understood, especially in complicated systems such as entangled fluids and polymers of different topologies. In addition, the physical properties of biological macromolecules, i.e. DNA, are expected to affect the spatial organization of chromosome in a cell, which has the potential impact on a broad epigenetics research. Here, we propose new methods for simultaneous visualization of diffusive motion and conformational dynamics of individual polymer chains, two most important factors that characterize polymer dynamics, based on a new single-molecule tracking technique, cumulative-area (CA) tracking method. We demonstrate the applicability of the CA tracking to the quantitative characterization of the motion and relaxation of individual topological polymer molecules under entangled conditions, which is possible only by using the newly-developed CA tracking, using fluorescently-labeled linear and cyclic dsDNA as model systems. We further extend the technique to multi-color CA tracking that allows for the direct visualization and characterization of motion and conformation of interacting molecules. We also develop a new imaging method based on recently developed 3D super-resolution fluorescence microscopy technique, which allows direct visualization of nanoscale motion and conformation of the single molecules that is not possible by any other methods. Using these techniques, we investigate spatial and temporal dynamics of polymers at the single-molecule level, with special emphasis on the effect of topological forms of the molecules and the confined geometry on their spatiotemporal dynamics. Our results demonstrate that the new methods developed in this thesis provide an experimental platform to address key questions in the entangled topological polymer dynamics. The research will provide a platform for developing new polymer-based materials and open the possibility of studying spatial organization of DNA in a confined geometry from physics point of view.
  • Diversity, ecology, and biotechnological potential of microorganisms naturally associated with plants in arid lands

    Mosqueira Santillán, María José (2018-07)
    Plants naturally host complex microbial communities in which the plant and the symbiotic partners act as an integrated metaorganism. These communities include beneficial (i.e. plant growth promoting, PGP) microorganisms which provide fundamental ecological services able to enhance host plant fitness and stress tolerance. PGP microorganisms represent a potential bioresource for agricultural applications, especially for desert farming under the harsh environmental conditions occurring in hot/arid regions (i.e. drought and salinity). In this context, understanding the ecological aspects of the associated microorganisms is crucial to take advantage of their ecological services. Here, hot/desert ecosystems were selected and two contrasting plant categories were used as models: (i) wild plants (i.e. speargrasses) growing in hot-desert sand dunes and (ii) the main crop cultivated in desert ecosystems, the date palm. By using highthroughput DNA sequencing and microscopy, the ecology and functionality of the microbial communities associated with these plants were characterized. Additionally, the PGP services of bacteria isolated from date palm were explored. I found that the harsh conditions of the desert strongly affect the selection and assembly of microbial communities associated with three different speargrass species, determining a plant species-independent core microbiome always present among the three plant species and carrying important PGP traits. On the contrary, in agroecosystems where desert farming practices are used, the plant species, i.e. date palm exerts a stronger selective pressure than the environmental and edaphic factors favoring the recruitment of conserved microbial assemblages, independent of the differences in the soil and environmental conditions among the studied oases. Such selective pressure also favors the recruitment of conserved PGP microorganisms (i.e. Pseudomonas sp. bacterial strains) able to protect their host from salinity stress through the induction of root architectural changes regulated by the modification of the root system auxin homeostasis. Overall, we found that deserts are unique ecosystems that challenge the paradigm of microbial community assembly, as it was defined from studies in non-arid ecosystems. The understanding of the ecological features regulating the ecological properties of such unique microbial community assembly will be a key-step to improve the chances of successful application of ‘PGP microorganisms’ in arid agroecosystems.
  • Scalable Discovery and Analytics on Web Linked Data

    Abdelaziz, Ibrahim (2018-07)
    Resource Description Framework (RDF) provides a simple way for expressing facts across the web, leading to Web linked data. Several distributed and federated RDF systems have emerged to handle the massive amounts of RDF data available nowadays. Distributed systems are optimized to query massive datasets that appear as a single graph, while federated systems are designed to query hundreds of decentralized and interlinked graphs. This thesis starts with a comprehensive experimental study of the state-of-the-art RDF systems. It identifies a set of research problems for improving the state-of-the-art, including: supporting the emerging RDF analytics required by many modern applications, querying linked data at scale, and enabling discovery on linked data. Addressing these problems is the focus of this thesis. First, we propose Spartex; a versatile framework for complex RDF analytics. Spartex extends SPARQL to seamlessly combine generic graph algorithms with SPARQL queries. Spartex implements a generic SPARQL operator as a vertex-centric program that interprets SPARQL queries and executes them efficiently using a built-in optimizer. We demonstrate that Spartex scales to datasets with billions of edges, and is at least as fast as the state-of-the-art specialized RDF engines. For analytical tasks, Spartex is an order of magnitude faster than existing alternatives. To address the scalability limitation of federated RDF engines, we propose Lusail; a scalable system for querying geo-distributed RDF graphs. Lusail follows a two-tier strategy: (i) locality-aware decomposition of the query into subqueries to maximize the computations at the endpoints and minimize intermediary results, and (ii) selectivity-aware execution to reduce network latency and increase parallelism. Our experiments on billions of triples show that Lusail outperforms existing systems by orders of magnitude in scalability and response time. Finally, enabling discovery on linked data is challenging due to the prior knowledge required to formulate SPARQL queries. To address these challenges; we develop novel techniques to (i) predict semantically equivalent SPARQL queries from a set of keywords by leveraging word embeddings, and (ii) generate fine-grained and non-blocking query plans to get fast and early results.
  • Potential of Bacterial Volatile Organic Compounds for Biocontrol of Fungal Phytopathogens and Plant Growth Promotion Under Abiotic Stress

    Soussi, Asma (2018-07)
    Bacterial volatile organic compounds (VOCs) are signal molecules that may have beneficial roles in the soil-plant-microbiome ecosystem. In this Ph.D. thesis, I aimed to assess and characterize the role of bacterial VOCs in plant tolerance to drought and in the biocontrol of fungal pathogens. I started by studying two root endophytic bacteria isolated from pepper plants cultivated under desert farming conditions. They showed an enhancement of pepper tolerance to drought stress and an amelioration of its physiological status. Moreover, they induced the expression of a vacuolar pyrophosphatase proton pump (V-PPase), implicated in the regulation of the vacuolar osmotic pressure, facilitating water uptake. Besides, the exposure of Arabidopsis thaliana plants, grown under salinity stress, to the volatile 2,3-butanediol, described for its plant growth promotion (PGP) potential, enhanced the plants tolerance to salinity, proving the potential involvement of this volatile in the osmotic stress resistance mechanism. Then, I studied VOCs released by three bacteria associated to healthy rice plants. Their released VOCs mixtures modified the color pattern of Magnaporthe oryzae, the agent of the rice blast disease, and protected rice from the pathogen infection. A significant reduction of melanin production, sporulation and appressoria formation was measured in presence of the bacterial VOCs, without major effects on mycelial proliferation. 1-butanol-3-methyl, one of the nine VOCs co-produced by the studied bacteria, proved its potential of reducing M. oryzae melanin in vitro. In vivo tests confirmed the infection inhibition effects mediated by the rice-bacterial VOCs, with a reduction of 94% of the disease incidence. Lastly, I compared the genomes of the five bacteria considered in the previous experimental studies. The PGP traits and the VOCs pathways identified from the genome analyses confirmed the effects observed with the in vitro and in vivo assays, revealing a complex mode of promotion and protection offered by the studied plant-associated bacteria. In conclusion, plant-associated bacterial VOCs can play potentially important roles in modulating plant drought tolerance and reducing fungal virulence. Such biological resources represent novel tools to counteract the deleterious effects of abiotic and biotic stresses and have the potential to be exploited for sustainable approaches in agriculture.
  • Molecular Fingerprinting to Understand Diazotrophic Microbe Distribution in Oligotrophic Oceans

    MOHAMED, ROSLINDA (2018-07)
    In oligotrophic systems, where primary production is low and nitrogen is in short supply, nitrogen fixation process is intense. Although a few diazotrophs (eg. Trichodesmium) have been widely-studied, the rest of the diazotrophic community is still poorly understood. Furthermore, the global distribution of diazotrophs are yet to be clearly resolved. This dissertation assessed the distribution of diazotrophs in oligotrophic systems, particularly in the tropical and subtropical oceans, using genomics tools including next-generation sequencing. We first tested out a pair of nifH-specific primer that previously performed well in silico, but found that its application on seawater samples was biased towards paralogous, non-functional nitrogenase nifH genes. Instead, we found that the use of a nested PCR method using different primers sets to be more effective in amplifying functional nifH genes. Trichodesmium sp., UCYN-A and Pseudomonas sp. forms the core of the diazotrophic communities in oligotrophic oceans. Temperature is the primary driver of the abundances and distributions of these organisms in the Pacific, Atlantic and Indian Oceans, as well as in the oligotrophic Red Sea. Trichodesmium tends to dominate warm, surface waters, while UCYN-A prefers cooler environments and dwell in sub-surface waters in the Red Sea. Due to the dominance of Pseudomonas in the large-sized fraction samples, they are believed to be part of the Trichodesmium-associated consortia, although this requires further investigations. We also found non-cyanobacterial species of diazotrophs to be dominant previously-described hotspots of nitrogen fixation, and found evidence for the widespread of alternative nitrogenases (Cluster II). Using the Red Sea as an exemplar for future warming ocean, we found patterns of niche partitioning in the Red Sea diazotrophs, based on their distribution along seasons, latitude and depth. Our one-year observation of Red Sea Trichodesmium population witnessed the collapse of the population at temperatures above 32°C. This dissertation not only improve our understanding of the effects of future rising temperature on the natural populations of diazotrophs, but it also helps to establish a baseline understanding of the structure, spatial and temporal dynamics of Red Sea diazotrophs, which has not been discussed elsewhere.
  • Real-Time and Ultra-High De finition Video Transmission in Underwater Wireless Optical Networks

    Al-Halafi, Abdullah (2018-07)
    Oceans form about three quarters of our planet Earth, and house immense resources that are critical for future generations. Exploring and monitoring such resources is becoming essential to protect the effected ones by the irresponsible human behavior, and to discover new ones. The limitations of depths mandate the search for alternatives and where human divers become endangered. Using remotely operated vehicles is commonly used for marine explorations, while tethered to ships. To be fully autonomous and to avoid damaging the fragile marine environment, they must be equipped with wireless communication solutions that enable real-time control and feedback on their maneuvering and mobility. Also, the ultimate tool to monitor, inspect and repair underwater structures is to use video streaming to mimic the reality of those unseen parts of the world. Existing underwater communications do not provide the necessary features to transmit video from the deep. Acoustic waves as well as the radio frequency waves are either limited in bandwidths or strongly attenuated by the water medium. On the other hand, wireless optical communication is an emerging technology that provides high transmission speeds and can enable video streaming underwater. This motivates bringing wireless optical technologies for real-time video streaming underwater to a practical implementation by undertaking theoretical and experimental studies of systems and techniques that can provide optimized solutions within our proposed framework. We present our video transmission architecture that facilitates programmable system configurations. Software defined platforms provide us with the means of configuring several setups to test our approach. In order to fully utilize the available optical spectrum, we have additionally implemented several modulation techniques in various laboratory scenarios. Real-time and ultra-high definition video has been successfully demonstrated. The overall system performance and throughput analysis have been provided. A thorough investigation of the system performance under various underwater channel conditions was undertaken. Also, as the delay resulting from queuing, when video packets are waiting for service, is key in time critical applications, we derive the mathematical model and investigate the delay effects and the packet dropping probability on the overall system performance when our setup is extended to a multi-channel configuration.
  • Exploration of Low-Cost, Natural Biocidal Strategies to Inactivate New Delhi Metallo-beta-lactamase (NDM)-Positive Escherichia coli PI-7, an Emerging Wastewater-Contaminant

    Aljassim, Nada I. (2018-07)
    Conventional wastewater treatment plants are able to reduce contaminant loads within regulations but do not take into account emerging contaminants. Antibiotic resistance genes and antibiotic resistant bacteria have been shown to survive wastewater treatment and remain detectable in effluents. The safety of treated wastewaters is crucial, otherwise unregulated and unmitigated emerging contaminants pose risks to public health and impede wastewater reuse. This dissertation aimed to further understanding of emerging microbial threats, and tested two natural and low-cost tools for their mitigation: sunlight, and bacteriophages. A wastewater bacterial isolate, named E. coli PI-7, which is highly antibiotic resistant, carries the novel antibiotic resistance gene New Delhi metallo-beta-lactamase NDM-1 gene, and displays pathogenic traits, was chosen to model responses to the treatments. Results found that solar irradiation was able to achieve a 5-log reduction in E. coli PI-7 numbers within 12 hours of exposure. However, the results also emphasized the risks from emerging microbial contaminants since E. coli PI-7, when compared with a non-pathogenic strain E. coli DSM1103 that has less antibiotic resistance, showed longer survival under solar irradiation. In certain instances, E. coli PI-7 persisted for over 6 hours before starting to inactivate, exhibited complex stress resistance gene responses, and activated many of its concerning pathogenicity and antibiotic resistance traits. However, upon solar irradiation, gene expression results obtained from both E. coli strains also showed increased susceptibility to bacteriophages. Hence, bacteriophages were coupled with solar irradiation as an additional mitigation strategy. Results using the coupled treatment found reduced cell-wall and extracellular matrix production in E. coli PI-7. DNA repair and other cellular defense functions like oxidative stress responses were also impeded, rendering E. coli PI-7 more susceptible to both stressors and successfully hastening the onset of its inactivation. Overall, the dissertation is built upon the need to develop strategies to further mitigate risks associated with emerging microbial contaminants. Solar irradiation and bacteriophages demonstrate potential as natural and low-cost mitigation strategies. Sunlight was able to achieve significant log-reductions in tested E. coli numbers within a day’s exposure. Bacteriophages were able to overwhelm E. coli PI-7’s capacity to resist solar inactivation while not affecting the indigenous microbiota.
  • Autoignition behavior of practical fuels

    Naser, Nimal (2018-07)
    Spark ignition (SI) and compression ignition (CI) engine fuels are characterized by standards developed in 1927 and 1932, respectively. Over the course of these years, modern engines have drastically changed their operating conditions; however, these fuel indexes are still used today with no significant change to their definition. The requirements for fuels in future advanced engines, employing low temperature combustion (LTC) concepts, may be somewhere between gasoline and diesel in terms of their autoignition characteristics. With this focus, this study examines methodologies to bridge the gap between those fuels classified between gasoline and diesel. First, the ignition delay times (IDTs) at various temperatures obtained from an ignition quality tester (IQT), was correlated with the octane index (OI), an anti-knock scale combining the effect of the operating condition and the anti-knock quality of the fuel given by the RON/MON. This study was extended to introduce a new concept of IDT sensitivity (IDS) in an IQT. It was observed that IDS could be correlated with fuel octane sensitivity (OS = RON − MON), offering an additional methodology to estimate RON/MON with an IQT. Chemical kinetics are most sensitive to fuel molecular structure; remarkable progress has been made in covering high carbon-number fuels, relevant to gasoline fuels, for better understanding of the chemical processes that lead to engine knock. To this end, a methodology to relate IDTs calculated from homogeneous batch-reactor simulations with gasoline fuel indexes was developed. This methodology enabled correlation of a kinetic property (i.e., IDT) with RON/MON values. The influence of various components present in gasolines, and their anti-knock quality, was investigated. A spinning band distillation system was utilized to separate the components of various gasolines. Ignition quality and the functional group distribution of various boiling ranges were investigated with an IQT and 1H nuclear magnetic resonance (NMR) spectroscopy. Finally, the importance of physical and chemical fuel properties in fuel stratification in LTC engine concepts was undertaken in a CI engine with a multi hole solid-cone injector. The findings suggest that the physical properties of fuel played a dominant role when fuel stratification occurred in the engine combustion chamber.
  • Modeling of Pre-ignition and Super-knock in Spark Ignition Engines

    mubarak ali, mohammed jaasim (2018-07)
    Advanced combustion concepts are required to meet the increasing global energy demand and stringent emission regulations imposed by the governments on automobile manufacturers. Improvement in efficiency and reduction in emissions can be achieved by downsizing the Spark Ignition (SI) engines. The operating range of SI engine is limited by occurrence of knock, pre-ignition and the following super-knock due to boosting of intake pressure, to account for the reduction of power, as a result of downsizing the engine. Super-knock, which represents high momentary pressure accompanied with pressure oscillations, is known to permanently damage the moving component of the engines. Therefore fundamental comprehensive understanding of the mechanism involved in pre-ignition and super-knock are required to design highly efficient spark ignition engines with lower emissions that can meet the increasing government regulations. The thesis focuses on auto-ignition characteristics of endgas and the bulk mixture properties that favor transition of pre-ignition to super-knock. Direct numerical studies indicate that super-knock occurs to due to initiation of premature flame front that transition into detonation. In literature, many sources are reported to trigger pre-ignition. Due to the uncertainty of the information on the sources that trigger pre-ignition, it is extremely difficult to predict and control pre-ignition event in SI engines. Since the information on the source of pre-ignition is not available, the main focus of this work is to understand the physical and chemical mechanisms involved in super-knock, factors that influence super-knock and methods to predict super-knock. 
Pre-ignition was initiated at known locations and crank angle using a hotspot of known size and strength. Different parametric cases were studied and the location and timing of pre-ignition initiation is found to be extremely important in determining the transition of pre-ignition event to super-knock. Pre-ignition increases the temperature of the endgas and the overall bulk mixture, that transitions the pre-ignition flame front to a detonation. The transition of the flame propagation mode from deflagration to detonation was investigated with different type of analysis methods and all results confirmed the transition of pre-ignition flame front to detonation that results in super- knock.
  • First principles based fuel design: investigating fuel properties and combustion chemistry

    Ahmed, Ahfaz (2018-07)
    Advanced combustion engine concepts require fuels which are meticulously designed to harness full potential of novel engine technologies. To develop such fuels, better understanding of fuel properties and their effect on combustion parameters is needed. The investigations reported in this work establishes relationships between several fuel properties and combustion parameters at engine relevant conditions. Further, these findings along with conclusions from other studies are utilized to synthesize fuels and surrogate fuels with tailored combustion properties. This approach of designing fuels relies on constrained non-linear optimization of several combustion properties simultaneously to design surrogate fuels for transportation fuels to enable combustion simulations. This scheme of fuel design has been devised and presented as Fuel Design Tool in Ahmed et al. Fuel 2015. Detailed investigations have been made to understand the effect of fuel properties on the ignition of fuels in Rapid compression machines utilizing a custom built multi-zone model. The study was further extended to explore fuel effects on engine combustion utilizing experiments and modelling to gather understanding of instances of engine knocking and pollutant formation. Bio-blended fuels allow mitigation of harmful pollutants and also enables engines to operate at higher efficiency. Ignition characteristics of two high octane bio-blended gasolines were studied experimentally in rapid compression machine and shock tube and detailed chemical kinetic analysis was conducted to understand how the presence of biofuels (i.e., ethanol) in gasoline influences the evolution of important radicals controlling ignition. Another set of biofuels namely methyl acetate and ethyl acetate were studied employing fundamental experimental and computational methods. The investigation involved development and analysis of combustion chemistry models, speciation studies in jet stirred reactors, ignition delay measurements and determination of laminar burning velocities. These fuels are found suited for high performance advanced spark ignition engines and the developed model and analysis will lead to optimization of combustion performance. The developed fuel design tool along with enhanced understanding of combustion chemistry and fuel properties enables a complete toolkit ready to be utilized to develop fuels with better suited properties for the advanced combustion modes.
  • On the role of thermal fluctuations in fluid mixing

    Narayanan, Kiran (2018-07)
    Fluid mixing that is induced by hydrodynamic instability is ubiquitous in nature; the material interface between two fluids when perturbed even slightly, changes shape under the influence of hydrodynamic forces, and an additional zone called the mixing layer where the two fluids mix, develops and grows in size. This dissertation reports a study on the role of thermal fluctuations in fluid mixing at the interface separating two perfectly miscible fluids of different densities. Mixing under the influence of two types of instabilities is studied; the Rayleigh-Taylor (RTI) and Richtmyer-Meshkov (RMI) instabilities. The study was conducted using numerical simulations after verification of the simulation methodology. Specifically, fluctuating hydrodynamic simulations were used; the fluctuating compressible Navier-Stokes equations were the physical model of the system, and they were solved using numerical methods that were developed and implemented in-house. Our results indicate that thermal fluctuations can trigger the onset of RTI at an initially unperturbed fluid-fluid interface, which subsequently leads to mixing of multi-mode character. In addition we find that for both RMI and RTI, whether or not thermal fluctuations quantitatively affect the mixing behavior, depends on the magnitude of the dimensionless Boltzmann number of the hydrodynamic system in question, and not solely on its size. When the Boltzmann number is much smaller than unity, the quantitative effect of thermal fluctuations on the mixing behavior is negligible. Under this circumstance, we show that mixing behavior is the average of the outcome from several stochastic instances, with the ensemble of stochastic instances providing the bounds on mixing-related metrics such as the mixing width. Most macroscopic hydrodynamic systems fall in this category. However, when the system is such that the Boltzmann number is of order unity, we show that thermal fluctuations can significantly affect the mixing behavior; the ensemble-averaged solution shows a departure from the deterministic solution. We conclude that for such systems, it is important to account for thermal fluctuations in order to correctly capture their physical behavior.
  • Investigation on the reactivity of 1,3-bis (chloromethyl) tetramethyl disiloxane: 1-Interaction with Lewis acidic metal salts. 2-Application on Ionic Liquids.

    Alhaddad, Maha (2018-07)
    This research explored the amination reaction of 1,3-bis-chloromethyl-tetramethyl-disiloxane in two different pathways. First, will discuss the synthesis of a new bipodal amino siloxane ligand which was achieved by the reaction of bis-chloromethyl-tetramethyl-disiloxane with t-BuNH3 in the presence of n-BuLi. The new ligand, of t-Butyl-[3-(t-butylamino-methyl)-1,1,3,3-tetramethyl disiloxanylmethyl]-amine (L1), is a model ligand designed to simulate the SOMC model of silica support and bipodal amido ligand that has been presented by the Basset group. Hence, developing this type of siloxane ligand and their complexes will be valuable in the synthesis of new homogenous catalyst, studying the reactivity and attempt to connect them with the SOMC examples. For this, the reaction of L1 with several Lewis acids and afforded several uncommon dimer and cluster complexes in the solid state. The second part of this research found that heating of bis-chloromethyl-tetramethyl-disiloxane with a 4-6 equivalent of amine, affording 4-N-Alkyl-tetramethyl- oxazadisilinane as six heterocycle ring by using a new simple and neat method. Using six different amine functional groups afforded six new oxazadisilinane compounds with different alkyls substituted. Each oxazadisilinane compound was utilized and reacted with four different acids, affording a series of twenty-one examples of new siloxane protic ionic liquids (Si-PILs). Also, the reaction of the cation with methyl iodide provided two examples of siloxane aprotic ionic liquids (Si-AILs). The new family of Si-ILs were well characterized by using NMR, mass, melting point, elemental analysis and thermal gravimetric analyses. Additionally, twelve crystals were suitable for X-ray diffraction as Si-PILs and one for Si-AILs. By studying their chemical and physical properties, a good library of the new Si-ILs has been built. Finally, one group of the new Si-PILs was used for butyl acetate esterification. The 5-X group of new Si-PILs salt was tested for esterification of butanol with acetic acid by thermal heat and under microwave irradiation. The salt 5-BF4- showed a good result in both systems with easy separation from the reaction mixture and recyclability discriminates the 5-BF4- as a good catalyst for the esterification reaction.
  • Decision and Inhibitory Trees for Decision Tables with Many-Valued Decisions

    Azad, Mohammad (2018-06-06)
    Decision trees are one of the most commonly used tools in decision analysis, knowledge representation, machine learning, etc., for its simplicity and interpretability. We consider an extension of dynamic programming approach to process the whole set of decision trees for the given decision table which was previously only attainable by brute-force algorithms. We study decision tables with many-valued decisions (each row may contain multiple decisions) because they are more reasonable models of data in many cases. To address this problem in a broad sense, we consider not only decision trees but also inhibitory trees where terminal nodes are labeled with “̸= decision”. Inhibitory trees can sometimes describe more knowledge from datasets than decision trees. As for cost functions, we consider depth or average depth to minimize time complexity of trees, and the number of nodes or the number of the terminal, or nonterminal nodes to minimize the space complexity of trees. We investigate the multi-stage optimization of trees relative to some cost functions, and also the possibility to describe the whole set of strictly optimal trees. Furthermore, we study the bi-criteria optimization cost vs. cost and cost vs. uncertainty for decision trees, and cost vs. cost and cost vs. completeness for inhibitory trees. The most interesting application of the developed technique is the creation of multi-pruning and restricted multi-pruning approaches which are useful for knowledge representation and prediction. The experimental results show that decision trees constructed by these approaches can often outperform the decision trees constructed by the CART algorithm. Another application includes the comparison of 12 greedy heuristics for single- and bi-criteria optimization (cost vs. cost) of trees. We also study the three approaches (decision tables with many-valued decisions, decision tables with most common decisions, and decision tables with generalized decisions) to handle inconsistency of decision tables. We also analyze the time complexity of decision and inhibitory trees over arbitrary sets of attributes represented by information systems in the frameworks of local (when we can use in trees only attributes from problem description) and global (when we can use in trees arbitrary attributes from the information system) approaches.

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