• Statistical Analysis and Bayesian Methods for Fatigue Life Prediction and Inverse Problems in Linear Time Dependent PDEs with Uncertainties

      Sawlan, Zaid A (2018-11-10)
      This work employs statistical and Bayesian techniques to analyze mathemati- cal forward models with several sources of uncertainty. The forward models usu- ally arise from phenomenological and physical phenomena and are expressed through regression-based models or partial differential equations (PDEs) associated with un- certain parameters and input data. One of the critical challenges in real-world ap- plications is to quantify uncertainties of the unknown parameters using observations. To this purpose, methods based on the likelihood function, and Bayesian techniques constitute the two main statistical inferential approaches considered here. Two problems are studied in this thesis. The first problem is the prediction of fatigue life of metallic specimens. The second part is related to inverse problems in linear PDEs. Both problems require the inference of unknown parameters given certain measurements. We first estimate the parameters by means of the maximum likelihood approach. Next, we seek a more comprehensive Bayesian inference using analytical asymptotic approximations or computational techniques. In the fatigue life prediction, there are several plausible probabilistic stress-lifetime (S-N) models. These models are calibrated given uniaxial fatigue experiments. To generate accurate fatigue life predictions, competing S-N models are ranked according to several classical information-based measures. A different set of predictive information criteria is then used to compare the candidate Bayesian models. Moreover, we propose a spatial stochastic model to generalize S-N models to fatigue crack initiation in general geometries. The model is based on a spatial Poisson process with an intensity function that combines the S-N curves with an averaged effective stress that is computed from the solution of the linear elasticity equations.
    • Multi-scale Inference of Lithospheric Seismic Structure in Saudi Arabia

      Tang, Zheng (2018-11)
      The complex geology of the Arabian plate together with the sparse nature of previous datasets have prevented a detailed characterization of the lithospheric structure and its spatial relationship to surface geology. With newly acquired large amount of seismic data, we investigate the crustal and upper-mantle velocity structure and develop highresolution 3-D shear-wave velocity models for Saudi Arabia using receiver functions and surface wave dispersion velocities. Our datasets, including teleseismic data for obtaining receiver functions and regional earthquake data for measuring Rayleigh-wave dispersion curves, are recorded by Saudi National Seismic Network (SNSN) stations operated by the Saudi Geological Survey (SGS). Our results reveal significant lateral variations in shearwave speeds of the crust and upper mantle, bulk Vp/Vs ratio, crustal thickness, and Lithosphere-Asthenosphere Boundary (LAB) depth beneath Saudi Arabia. Particularly, we notice interesting mantle-lid velocity and temperature patterns in which slow shearvelocities and high temperatures are observed below the southern and northern tips of the Arabian shield, compared with the values obtained for the central shield. Also, we detect high crustal bulk Vp/Vs ratios in Harrat Lunayyir and a few crustal low shear-velocity anomalies below the Cenozoic lava fields in the Arabian shield. In addition, a rather thin lithosphere and an upper-mantle low shear-velocity zone below western Arabia are imaged. We discuss our results and how they are related to previous geochemical observations, the origin of the Cenozoic volcanism, the influence of the Red Sea rift and the Afar plume on the volcanism, as well as possible plumbing system of magmas underneath western Arabia.
    • Wave-Equation Elastic Least-Squares Migration and Migration Velocity Analysis

      Feng, Zongcai (2018-11)
      This thesis develops novel wave-equation based seismic imaging and inversion methods that invert for the high- and low-wavenumber components of P- and Svelocity models. To invert for the P- and S-wave velocity perturbations (highwavenumber component), I first propose a linearized elastic waveform inversion method denoted as elastic least-squares reverse time migration (LSRTM). Elastic LSRTM solves the linearized elastic-wave equation for forward modeling and the adjoint equations for backpropagating the residual wavefield. Both synthetic- and field-data results prove that this method can accurately reconstruct the P- and S-wave velocity perturbations. Compared with the elastic reverse time migration (RTM) method, the elastic LSRTM images have fewer artifacts, higher resolution and better amplitude balancing. In addition, elastic LSRTM mitigates the coupling effect between elastic parameters, and so gives accurate relative information about the P- and S-wave velocity distributions. Elastic LSRTM method suffers from a slow convergence rate because of blurring effects and crosstalk artifacts. To mitigate these problems, I propose a multiparameter deblurring filter that approximates the multiparameter inverse Hessian. This method significantly improves the quality for multiparameter migration images. Numerical tests show that the multiparameter deblurring filter can compute elastic migration images similar in quality to the ones inverted by elastic LSRTM at a much lower cost. It can also be used as a preconditioner to accelerate the convergence rate in multiparameter inversion. In general, the proposed method can also be applied to elastic full waveform inversion (FWI) or any multiparameter migration/inversion operator. One of most crucial problems for elastic inversion is the accurate estimation of the background P- and S-wave velocity models (low-wavenumber component). To accurately estimate the velocity models, I propose a joint PP and PS wave-equation migration velocity analysis method using plane-wave common image gathers (CIGs) with depth consistency. Both the moveout residuals of CIGs and relative depth shifts between PP and PS images are transformed into weighted image perturbations for updating the velocity models. Numerical tests with synthetic and multicomponent field data demonstrate that this method can accurately invert for P- and S-wave velocity models.
    • Full-Dimension Massive MIMO Technology for Fifth Generation Cellular Networks

      Nadeem, Qurrat-Ul-Ain (2018-11)
      Full dimension (FD) multiple-input multiple-output (MIMO) technology has recently attracted substantial research attention in the 3rd Generation Partnership Project (3GPP) as a promising technique for the next-generation of wireless communication networks. FD-MIMO scenarios utilize a planar two-dimensional (2D) active antenna system (AAS) that not only allows a large number of antenna elements to be placed within feasible base station (BS) form factors, but also provides the ability of elevation beamforming. This dissertation presents the elevation beamforming analysis for cellular networks utilizing FD massive MIMO antenna arrays. In particular, two architectures are proposed for the AAS - the uniform linear array (ULA) and the uniform circular array (UCA) of antenna ports, where each port is mapped to a group of vertically arranged antenna elements with a corresponding downtilt weight vector. To support FD-MIMO techniques, this dissertation presents two di erent 3D ray-tracing channel modeling approaches, the ITU based `antenna port approach' and the 3GPP technical report (TR) 36.873 based `antenna element approach'. The spatial correlation functions (SCF)s for both FD-MIMO arrays are characterized based on the antenna port approach. The resulting expressions depend on the underlying angular distributions and antenna patterns through the Fourier series coe cients of the power spectra and are therefore valid for any 3D propagation environment. Simulation results investigate the performance patterns of the two arrays as a function of several channel and array parameters. The SCF for the ULA of antenna ports is then characterized in terms of the downtilt weight vectors, based on the more recent antenna element approach. The derived SCFs are used to form the Rayleigh correlated 3D channel model. All these aspects are put together to provide a mathematical framework for the design of elevation beamforming schemes in single-cell and multi-cell scenarios. Finally, this dissertation proposes to use the double scattering channel to model limited scattering in realistic propagation environments and derives deterministic equivalents of the signal-to-interference-plus-noise ratio (SINR) and ergodic rate with regularized zeroforcing (RZF) precoding. The performance of a massive MIMO system is shown to be limited by the number of scatterers. To this end, this dissertation points out future research directions.
    • Modeling, Analysis, and Design of 5G Networks using Stochastic Geometry

      Ali, Konpal (2018-11)
      Improving spectral-utilization is a core focus to cater the ever-increasing demand in data rate and system capacity required for the development of 5G. This dissertation focuses on three spectrum-reuse technologies that are envisioned to play an important role in 5G networks: device-to-device (D2D), full-duplex (FD), and nonorthogonal multiple access (NOMA). D2D allows proximal user-equipments (UEs) to bypass the cellular base-station and communicate with their intended receiver directly. In underlay D2D, the D2D UEs utilize the same spectral resources as the cellular UEs. FD communication allows a transmit-receive pair to transmit simultaneously on the same frequency channel. Due to the overwhelming self-interference encountered, FD was not possible until very recently courtesy of advances in transceiver design. NOMA allows multiple receivers (transmitters) to communicate with one transmitter (receiver) in one time-frequency resource-block by multiplexing in the power domain. Successive-interference cancellation is used for NOMA decoding. Each of these techniques significantly improves spectral efficiency and consequently data rate and throughput; however, the price paid is increased interference. Since each of these technologies allow multiple transmissions within a cell on a time-frequency resource-block, they result in interference within the cell (i.e., intracell interference). Additionally, due to the increased communication, they increase network interference from outside the cell under consideration as well (i.e., increased intercell interference). Real networks are becoming very dense; as a result, the impact of intercell interference coming from the entire network is significant. As such, using models that consider a single-cell/few-cell scenarios result in misleading conclusions. Hence, accurate modeling requires considering a large network. In this context, stochastic geometry is a powerful tool for analyzing random patterns of points such as those found in wireless networks. In this dissertation, stochastic geometry is used to model and analyze the different technologies that are to be deployed in 5G networks. This gives us insight into the network performance, showing us the impacts of deploying a certain technology into real 5G networks. Additionally, it allows us to propose schemes for integrating such technologies, mode-selection, parameter-selection, and resource-allocation that enhance the parameters of interest in the network such as data rate, coverage, and secure communication.
    • Contributions Towards Modern MIMO and Passive Radars

      Jardak, Seifallah (2018-11)
      The topic of multiple input multiple output (MIMO) radar recently gained considerable interest because it can transmit partially correlated or fully independent waveforms. The inherited waveform diversity helps MIMO radars identify more targets and adds flexibility to the beampattern design. The realized advantages come at the expense of enhanced processing requirements and increased system complexity. In this regards, a closed-form method is derived to generate practical finite-alphabet waveforms with specific correlation properties to match the desired beampattern. Next, the performance of adaptive estimation techniques is examined. Indeed, target localization or reflection coefficient estimation usually involves optimizing a given cost-function over a grid of points. The estimation performance is directly affected by the grid resolution. In this work, the cost function of Capon and amplitude and phase estimation (APES) adaptive beamformers are reformulated. The new cost functions can be evaluated using the two-dimensional fast-Fourier-transform (2D-FFT) which reduces the estimation runtime. Generalized expressions of the Cram´er-Rao lower bound are computed to assess the performance of our estimators. Afterward, a novel estimation algorithm based on the monopulse technique is proposed. In comparison with adaptive methods, monopulse requires less number of received pulses. Hence, it is widely used for fast target localization and tracking purposes. This work suggests an approach that localizes two point targets present in the hemisphere using one set of four antennas. To separate targets sharing the same elevation or azimuth angles, a second set of antennas is required. Two solutions are suggested to combine the outputs from the antenna sets and improve the overall detection performance. The last part of the dissertation focuses on the application and implementation side of radars rather than the theoretical aspects. It describes the realized hardware and software design of a compact portable 24 GHz frequency-modulated-continuous-wave (FMCW) radar. The prototype can assist the visually impaired during their outdoor journeys and prevents collisions with their surrounding environment. Moreover, the device performs diverse tasks such as range-direction mapping, velocity estimation, presence detection, and vital sign monitoring. The experimental result section demonstrates the device’s capabilities in different use-cases.
    • Rare Events Simulations with Applications to the Performance Evaluation of Wireless Communication Systems

      Ben Rached, Nadhir (2018-10-08)
      The probability that a sum of random variables (RVs) exceeds (respectively falls below) a given threshold, is often encountered in the performance analysis of wireless communication systems. Generally, a closed-form expression of the sum distribution does not exist and a naive Monte Carlo (MC) simulation is computationally expensive when dealing with rare events. An alternative approach is represented by the use of variance reduction techniques, known for their efficiency in requiring less computations for achieving the same accuracy requirement. For the right-tail region, we develop a unified hazard rate twisting importance sampling (IS) technique that presents the advantage of being logarithmic efficient for arbitrary distributions under the independence assumption. A further improvement of this technique is then developed wherein the twisting is applied only to the components having more impacts on the probability of interest than others. Another challenging problem is when the components are correlated and distributed according to the Log-normal distribution. In this setting, we develop a generalized hybrid IS scheme based on a mean shifting and covariance matrix scaling techniques and we prove that the logarithmic efficiency holds again for two particular instances. We also propose two unified IS approaches to estimate the left-tail of sums of independent positive RVs. The first applies to arbitrary distributions and enjoys the logarithmic efficiency criterion, whereas the second satisfies the bounded relative error criterion under a mild assumption but is only applicable to the case of independent and identically distributed RVs. The left-tail of correlated Log-normal variates is also considered. In fact, we construct an estimator combining an existing mean shifting IS approach with a control variate technique and prove that it possess the asymptotically vanishing relative error property. A further interesting problem is the left-tail estimation of sums of ordered RVs. Two estimators are presented. The first is based on IS and achieves the bounded relative error under a mild assumption. The second is based on conditional MC approach and achieves the bounded relative error property for the Generalized Gamma case and the logarithmic efficiency for the Log-normal case.
    • 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.
    • Mid-IR Laser Absorption Diagnostics for Shock Tube and Rapid Compression Machine Experiments

      Nasir, Ehson Fawad (2018-10)
      High-fidelity chemical kinetic models for low-temperature combustion processes require high-fidelity data from fundamental experiments conducted in idealized transient reactors, such as shock tubes and rapid compression machines (RCM). Non-intrusive laser absorption diagnostics, in particular quantum cascade lasers (QCL) in the mid-infrared wavelength region, provide a unique opportunity to obtain quantitative, time-resolved species concentration and temperature from these reactive systems. In this work, three novel laser absorption diagnostics in the mid-infrared wavelength region are presented for three different experimental applications. The first diagnostic was developed for measuring CO2 concentration using an external cavity QCL centered in the ν3 fundamental vibrational band of CO2. Absorption cross-sections were measured in a shock tube, at a fixed wavelength for the R(32) line centered at 2371.42 cm-1 (4.217 µm) over 700 – 2900 K and nominal pressures of 1, 5 and 10 bar. The diagnostic was used to measure rate coefficients for the reaction between carbon monoxide and hydroxyl radical over 700 – 1230 K and 1.2 – 9.8 bar using highly dilute mixtures. The second diagnostic was developed for measuring CO concentration using a pulsed QCL centered at 2046.28 cm-1 (4.887 µm) and an off-axis cavity implemented on the RCM. The duty cycle and pulse repetition rate of the laser were optimized for increased tuning range, high chirp rate and increased line-width to achieve effective laser-cavity coupling. A gain factor of 133 and time resolution of 10 μs were demonstrated. CO concentration-time profiles during the oxidation of highly dilute n-heptane/air mixtures were recorded and compared with chemical kinetic models. This represents the first application of a cavity-enhanced absorption diagnostic in an RCM. Finally, a calibration-free temperature diagnostic based on a pair of pulsed QCLs centered at 2196.66 cm-1 and 2046.28 cm-1 was implemented on the RCM. The down-chirp phenomenon resulted in large spectral tuning (∆v ~ 2.8 cm-1) within a single pulse of each laser at a high pulse repetition frequency (100 kHz). The diagnostic for was used to measure the temperature rise during first-stage ignition of n-pentane at nominal pressures of 10 and 15 bar for the first time.
    • Electrical Impedance Characterization for Damage Detection in Carbon Fiber-Reinforced Polymer (CFRP) Laminated Composites

      Almuhammadi, Khaled H. (2018-10)
      The use of modern carbon fiber-reinforced polymer (CFRP) composite materials is becoming increasingly widespread recently. However, the failure modes of such composite structures are extremely complex and, unlike metals, they may suffer significant degradation with barely visible surface damage. Since the damage may cause serious decrease in material strength and lead to catastrophic failure, the development of reliable structural health monitoring techniques is indispensable and has a tremendous impact on the life-cycle cost spent for inspection and repair. Such techniques that are based on the change in the electrical properties of materials are promising and viable approach for maintaining the structural integrity. They are low-cost, fast, effective, and have high potential to be applicable on real structures where they can be monitored online and real-time. The topic of this PhD dissertation is mainly focused on a number of key developments and milestones towards monitoring damage in CFRP laminated composites and making electrical-based methods practical on real structures. One of the major components of these methods is the electrode, which is the interface between the external hardware and the monitored structure. We develop a novel method for surface preparation of composite laminates for better electrode quality using pulsed laser irradiation. Further, we provide a new insight on the anisotropic behavior of the contact impedance for the electrodes on CFRP laminated composites. Another major component for achieving reliable monitoring techniques is the in-depth understanding of impedance response of these materials when subjected to an alternating electrical excitation, information that is only partially available in the literature. For more efficient electrical signal-based inspections, we investigate the electrical impedance spectroscopy response at various frequencies of laminates chosen to be representative of classical layups employed in composite structures. Finally, we use different electrodes configurations on CFRP plates applied to one side mimicking the case of real structures that is undergoing a quasi-static indentation representative of the impact load. We investigate the coupling between the electrical measurements and the type of mechanical degradation using an in-house built electro-mechanical system that measures the change in impedance and phase angle in-situ and real-time.
    • 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.
    • How Corals Got Bones - Comparative Genomics Reveals the Evolution of Coral Calcification

      Wang, Xin (2018-09)
      Scleractinian corals represent the foundation species of one of the most diverse and productive ecosystem on earth, coral reefs. Corals not only constitute the trophic basis of these ecosystems, but also provide essential habitats and shelter for a wide variety of marine species, many of which are commercially relevant. They also provide other important ecosystem services such as food provision, shoreline protection and opportunities for ecotourism. Despite the ecological importance of corals, very little is known about how their soft-bodied ancestor evolved the ability to form a calcified skeleton and became the ecosystem builders they are today. Corallimorpharia are closely related to reef-building corals but lack the ability to form calcified skeletons. Here we assembled and annotated two draft genomes of the corallimorpharians, Amplexidiscus fenestrafer and Discosoma sp., and further provided an online interface to facilitate the use of these resources. The two genomes can not only inform on the current evolutionary gap in genomic resources for the subclass of Hexacorallia but also provide important resources for comparative genomic studies aiming at understanding the evolution of coral specific traits. Our broad phylogenomic approach using whole genome data, including phylogenetic analyses of nuclear encoding genes as well as genome-wide presence/absence information and synteny conservation from six hexacorallian species, provides robust evidence that corallimorpharians are a monophyletic sister group of scleractinians, therefore rejecting the “naked coral” hypothesis. Being the closest non-calcifying relative of scleractinian corals, corallimorpharians appear to be the best candidates to understand the evolutionary origin of coral calcification. Molecular divergence analysis of scleractinian coral and Corallimorpharia genes suggests that the soft-bodied ancestor of corals evolved the ability to calcify within approximately 80 million years after the divergence of these two orders. To uncover the molecular basis of coral skeletal formation and growth, we integrate genomic and transcriptomic data as well as skeletal proteomic data, and show that gene and domain duplications have been the main evolutionary mechanisms underlying the evolution of calcification in scleractinian corals.
    • 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.
    • Robotic Manipulation and Control for Mobile Autonomous Platforms: Design and Implementation

      Shaqura, Mohammad (2018-08)
      This thesis presents contributions to applied robotic control and manipulation in the areas of motion algorithm design, hardware, and software robotic system design. Mobile robotic systems are widely used in several applications. Control of such systems poses many challenges caused by system modeling uncertainty. Complex physics phenomena and environmental effects are usually neglected to simplify analysis and control design. In motion planning, this thesis introduces an algorithm for navigation learning in mobile robots that aims to reduce the effect of modeling uncertainties on control performance. Starting from an initial feasible state and input trajectories, the objective is to reduce navigation time through iterative trials. A nominal model of the actual system and the experimental system output are used to update the control input in every iteration for incremental improvement. The navigation problem is formulated as an optimal control problem that is solved after each trial to generate a vector of input deviations for the next trial. The formulation of the approach, simulation, and experimental results shows the effectiveness of the presented method. The design part focuses on developing hardware and software systems for manipulation and aerial robots. A software tool for automated generation of multirotor simulation models is developed utilizing CAD software API and Matlab. In the area of human-robot interaction, a human-supervised UAV inspection system has been developed and tested. The UAV is guided by a human operator using a handheld laser pointing device that is designed and fabricated in-house. In the field of robotic manipulation, a novel gripper mechanism is designed and implemented. The proposed mechanism targets applications where a grasped object lies in areas with limited surrounding clearance and where external torques affect the grasped object. This design was implemented on a mobile manipulation platform and tested during an international robotics competition.
    • 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.