Shales: Comprehensive Laboratory Characterization(2020-12) [Dissertation]
Advisor: Santamarina, Carlos
Committee members: Vahrenkamp, Volker C.; Mai, Paul Martin; Frost, David; Finkbeiner, ThomasUnconventional formations have become an increasingly important source of energy resources. Proper rock mechanic characterization is needed not only to identify the most promising areas for stimulation, but to increase our understanding of the sealing capabilities of cap-rock formations for carbon geological storage. However, shale assessment is challenging with current standard techniques. This research explores the index and rock mechanic properties of different shale specimens considered as source rocks for oil and gas (Eagle Ford, Wolfcamp, Jordanian, Mancos, Bakken, and Kimmeridge), and presents an in-depth analysis of tools and protocols to identify inherent biases. New test protocols proposed in this thesis provide robust and cost-effective measurement techniques to characterize shale formations in general; these include: 1) new energy methods computed from the area under the stress-strain curve or proposed boundary asymptotes (strength and stiffness) to assess brittle/ductile conditions in the field, 2) tensile strength analyses to determine anisotropy in shale formations, 3) Coda wave analysis to monitor pre-failure damage evolution during compression, and 4) a combination of index tests to anticipate the complicated geology or layered characteristics, which include high-resolution imaging, hardness, and scratch tests. Experimental results combined with extensive databases provide unprecedented information related to the mechanical behavior of shale formations needed for the enhanced design and analysis of geo-engineering applications. Calcareous shales display strong interlayer bonding and lower compressive strength anisotropy than siliceous shales. Tensile strength anisotropy is more pronounced than in compressive strength and reflects bedding orientation and loading conditions that affect fracture propagation and ensuing failure surface topography.
Spots and Sequences: Multi-method population assessment of whale sharks in the Red Sea(2020-12) [Dissertation]
Advisor: Berumen, Michael L.
Committee members: Gojobori, Takashi; Jones, Burton; Hsu, Hua HsunIn 1938 Dr. Eugene Gudger concluded of the Red Sea that "whale sharks must surely abound in this region." Seventy years later, multi-method research began on a whale shark (Rhincodon typus) aggregation at Shib Habil, a reef near Al Lith, Saudi Arabia. However, in 2017 and 2018, a dramatic decline in encounters at this site drew questions about the aggregation's future and overall whale shark population trends in the region. In this dissertation, I describe and discuss the two-year decline in encounters and show that neither remotely sensed sea surface temperature nor chlorophyll-a concentrations were significantly different in seasons with or without sharks. Citizen science-based photo identification was used to characterize the northern Red Sea population, the Red Sea population as a whole, show limited crossover within the basin, and connections with another aggregation in Djibouti. Scarring rates within the Red Sea are compared to recent global studies, and the Red Sea uniquely had no predator bites observed, suggesting boat collisions are likely the leading cause of major scars. Finally, building upon previous genetic work comparing Red Sea and Tanzanian sharks using microsatellites, the mitochondrial control region was sequenced, and two global haplotype networks were produced and compared to each other and previous work. The stability of genetic diversity within the Shib Habil aggregation is compared to declines previously measured in Australia. As tourism develops along the northern Saudi Arabian coast and citizen science increases in the Red Sea, population dynamics within the region could be better understood. The genetic connectivity of Red Sea whale sharks to the Indo-Pacific population exemplifies the need for continued collaborative research beyond local aggregations and multinational conservation measures.
Exploring Entity Relationship in Pairwise Ranking: Adaptive Sampler and Beyond(2020-12) [Dissertation]
Advisor: Zhang, Xiangliang
Committee members: Moshkov, Mikhail; Hoehndorf, Robert; Karypis, GeorgeLiving in the booming age of information, we have to rely on powerful information retrieval tools to seek the unique piece of desired knowledge from such a big data world, like using personalized search engine and recommendation systems. As one of the core components, ranking model can appear in almost everywhere as long as we need a relative order of desired/relevant entities. Based on the most general and intuitive assumption that entities without user actions (e.g., clicks, purchase, comments) are of less interest than those with user actions, the objective function of pairwise ranking models is formulated by measuring the contrast between positive (with actions) and negative (without actions) entities. This contrastive relationship is the core of pairwise ranking models. The construction of these positive-negative pairs has great influence on the model inference accuracy. Especially, it is challenging to explore the entity relationships in heterogeneous information network. In this thesis, we aim at advancing the development of the methodologies and principles of mining heterogeneous information network through learning entity relations from a pairwise learning to rank optimization perspective. More specifically we first show the connections of different relation learning objectives modified from different ranking metrics including both pairwise and list-wise objectives. We prove that most of popular ranking metrics can be optimized in the same lower bound. Secondly, we propose the class-imbalance problem imposed by entity relation comparison in ranking objectives, and prove that class-imbalance problem can lead to frequency 5 clustering and gradient vanishment problems. As a response, we indicate out that developing a fast adaptive sampling method is very essential to boost the pairwise ranking model. To model the entity dynamic dependency, we propose to unify the individual-level interaction and union-level interactions, and result in a multi-order attentive ranking model to improve the preference inference from multiple views.
Sustainability Evaluation of Hybrid Desalination Systems: Multi Effect Distillation – Adsorption (MED-AD) and Forward Osmosis – Membrane Distillation (FO-MD)(2020-12) [Dissertation]
Advisor: Ghaffour, NorEddine
Committee members: Vrouwenvelder, Johannes S.; Pinnau, Ingo; Orfi, JamelWater is life for all living organisms on earth, and all human beings need water for every socio-economic activity in their daily lives. However, constant challenges are faced in securing quality water resources due to environmental pollution, a growing demand, and climate changes. To overcome imminent worldwide challenges on water resources, desalination of seawater and saline wastewater became inevitable, and significant efforts have been deployed by the desalination research community to advance the technology. However, there is still a gap to take it to a higher sustainability and compatibility compared to conventional water treatment technologies. Among all efforts, the hybridization of two or more processes stands among the promising solutions for sustainable desalination, which synergizes benefits of multiple technologies. To evaluate the sustainability of hybrid desalination technologies, two different systems, namely; (i) multi-effect distillation – adsorption (MED-AD) and (ii) forward osmosis – membrane distillation (FO-MD), are investigated in this study. The method developed for the analysis of primary energy consumption in complex desalination systems is used to evaluate the performance of the MED-AD pilot facility at King Abdullah University of Science and Technology (KAUST). Results of the MED-AD pilot operation showed an improvement in water production with a higher energy efficiency under the same operating conditions (near the ambient temperature with the solar thermal system). For the FO-MD hybrid system, an investigation is carried out on a novel in-house integrated module and a comparative analysis with the conventional module is provided. An isolation barrier carefully placed in the novel design enhanced the hybrid performance by reducing both concentration and temperature polarization. In addition, the FO-MD hybrid process is evaluated for brine reclamation application in a SWRO-MD-FO system. The sustainability of the proposed system and the potential of a flexible sustainable operation are presented with the experimental study with real seawater and brine from the full-scale desalination plant.
Mesoscale Eddy Dynamics and Scale in the Red Sea(2020-12) [Dissertation]
Advisor: Jones, Burton
Committee members: Ellis, Joanne; Berumen, Michael L.; Hoteit, Ibrahim; Rainville, LucRecent efforts in understanding the variability inherent in coastal and offshore waters have highlighted the need for higher resolution sampling at finer spatial and temporal resolutions. Gliders are increasingly used in these transitional waters due to their ability to provide these finer resolution data sets in areas where satellite coverage may be poor, ship-based surveys may be impractical, and important processes may occur below the surface. Since no single instrument platform provides coverage across all needed spatial and temporal scales, Ocean Observation systems are using multiple types of instrument platforms for data collection. However, this results in increasingly large volumes of data that need to be processed and analyzed and there is no current “best practice” methodology for combining these instrument platforms. In this study, high resolution glider data, High Frequency Radar (HFR), and satellite-derived data products (MERRA_2 and ARMOR3D NRT Eddy Tracking) were used to quantify: 1) dominant scales of variability of the central Red Sea, 2) determine the minimum sampling frequency required to adequately characterize the central Red Sea, 3) discriminate whether the fine scale persistency of oceanographic variables determined from the glider data are comparable to those identified using HFR and satellite-derived data products, and 4) determine additional descriptive information regarding eddy occurrence and strength in the Red Sea from 2018-2019. Both Integral Time Scale and Characteristic Length Scale analysis show that the persistence time frame from glider data for temperature, salinity, chlorophyll-α, and dissolved oxygen is 2-4 weeks and that these temporal scales match for HFR and MERRA_2 data, matching a similar description of a ”weather-band” level of temporal variability. Additionally, the description of eddy activity in the Red Sea also supports this 2-4-week time frame, with the average duration of cyclonic and anticyclonic eddies from 2018-2019 being 22 and 27 days, respectively. Adoption of scale-based methods across multiple ocean observation areas can help define “best practice” methodologies for combining glider, HFR, and satellite-derived data to better understand the naturally occurring variability and improve resource allocation.
The equations of polyconvex thermoelasticity(2020-11-25) [Dissertation]
Advisor: Tzavaras, Athanasios
Committee members: Hoteit, Ibrahim; Markowich, Peter A.; Christoforou, Cleopatra; Dafermos Constantine, M.In my Dissertation, I consider the system of thermoelasticity endowed with poly- convex energy. I will present the equations in their mathematical and physical con- text, and I will explain the relevant research in the area and the contributions of my work. First, I embed the equations of polyconvex thermoviscoelasticity into an aug- mented, symmetrizable, hyperbolic system which possesses a convex entropy. Using the relative entropy method in the extended variables, I show convergence from ther- moviscoelasticity with Newtonian viscosity and Fourier heat conduction to smooth solutions of the system of adiabatic thermoelasticity as both parameters tend to zero and convergence from thermoviscoelasticity to smooth solutions of thermoelasticity in the zero-viscosity limit. In addition, I establish a weak-strong uniqueness result for the equations of adiabatic thermoelasticity in the class of entropy weak solutions. Then, I prove a measure-valued versus strong uniqueness result for adiabatic poly- convex thermoelasticity in a suitable class of measure-valued solutions, de ned by means of generalized Young measures that describe both oscillatory and concentra- tion e ects. Instead of working directly with the extended variables, I will look at the parent system in the original variables utilizing the weak stability properties of certain transport-stretching identities, which allow to carry out the calculations by placing minimal regularity assumptions in the energy framework. Next, I construct a variational scheme for isentropic processes of adiabatic polyconvex thermoelasticity. I establish existence of minimizers which converge to a measure-valued solution that dissipates the total energy. Also, I prove that the scheme converges when the limit- ing solution is smooth. Finally, for completeness and for the reader's convenience, I present the well-established theory for local existence of classical solutions and how it applies to the equations at hand.
Quantile Function Modeling and Analysis for Multivariate Functional Data(2020-11-25) [Dissertation]
Advisor: Sun, Ying
Committee members: Ombao, Hernando; Tester, Mark A.; He, XumingQuantile function modeling is a more robust, comprehensive, and flexible method of statistical analysis than the commonly used mean-based methods. More and more data are collected in the form of multivariate, functional, and multivariate functional data, for which many aspects of quantile analysis remain unexplored and challenging. This thesis presents a set of quantile analysis methods for multivariate data and multivariate functional data, with an emphasis on environmental applications, and consists of four significant contributions. Firstly, it proposes bivariate quantile analysis methods that can predict the joint distribution of bivariate response and improve on conventional univariate quantile regression. The proposed robust statistical techniques are applied to examine barley plants grown in saltwater and freshwater conditions providing interesting insights into barley’s responses, informing future crop decisions. Secondly, it proposes modeling and visualization of bivariate functional data to characterize the distribution and detect outliers. The proposed methods provide an informative visualization tool for bivariate functional data and can characterize non-Gaussian, skewed, and heavy-tailed distributions using directional quantile envelopes. The radiosonde wind data application illustrates our proposed quantile analysis methods for visualization, outlier detection, and prediction. However, the directional quantile envelopes are convex by definition. This feature is shared by most existing methods, which is not desirable in nonconvex and multimodal distributions. Thirdly, this challenge is addressed by modeling multivariate functional data for flexible quantile contour estimation and prediction. The estimated contours are flexible in the sense that they can characterize non-Gaussian and nonconvex marginal distributions. The proposed multivariate quantile function enjoys the theoretical properties of monotonicity, uniqueness, and the consistency of its contours. The proposed methods are applied to air pollution data. Finally, we perform quantile spatial prediction for non-Gaussian spatial data, which often emerges in environmental applications. We introduce a copula-based multiple indicator kriging model, which makes no distributional assumptions on the marginal distribution, thus offers more flexibility. The method performs better than the commonly used variogram approach and Gaussian kriging for spatial prediction in simulations and application to precipitation data.
Efficient Ensemble Data Assimilation and Forecasting of the Red Sea Circulation(2020-11-23) [Dissertation]
Advisor: Hoteit, Ibrahim
Committee members: Knio, Omar; Al-Naffouri, Tareq Y.; Iskandarani, MohamadThis thesis presents our efforts to build an operational ensemble forecasting system for the Red Sea, based on the Data Research Testbed (DART) package for ensemble data assimilation and the Massachusetts Institute of Technology general circulation ocean model (MITgcm) for forecasting. The Red Sea DART-MITgcm system efficiently integrates all the ensemble members in parallel, while accommodating different ensemble assimilation schemes. The promising ensemble adjustment Kalman filter (EAKF), designed to avoid manipulating the gigantic covariance matrices involved in the ensemble assimilation process, possesses relevant features required for an operational setting. The need for more efficient filtering schemes to implement a high resolution assimilation system for the Red Sea and to handle large ensembles for proper description of the assimilation statistics prompted the design and implementation of new filtering approaches. Making the most of our world-class supercomputer, Shaheen, we first pushed the system limits by designing a fault-tolerant scheduler extension that allowed us to test for the first time a fully realistic and high resolution 1000 ensemble members ocean ensemble assimilation system. In an operational setting, however, timely forecasts are of essence, and running large ensembles, albeit preferable and desirable, is not sustainable. New schemes aiming at lowering the computational burden while preserving reliable assimilation results, were developed. The ensemble Optimal Interpolation (EnOI) algorithm requires only a single model integration in the forecast step, using a static ensemble of preselected members for assimilation, and is therefore computationally significantly cheaper than the EAKF. To account for the strong seasonal variability of the Red Sea circulation, an EnOI with seasonally-varying ensembles (SEnOI) was first implemented. To better handle intra-seasonal variabilities and enhance the developed seasonal EnOI system, an automatic procedure to adaptively select the ensemble members through the assimilation cycles was then introduced. Finally, an efficient Hybrid scheme combining the dynamical flow-dependent covariance of the EAKF and a static covariance of the EnOI was proposed and successfully tested in the Red Sea. The developed Hybrid ensemble data assimilation system will form the basis of the first operational Red Sea forecasting system that is currently being implemented to support Saudi Aramco operations in this basin.
Active Control of Surface Plasmons in MXenes for Advanced Optoelectronics(2020-11-18) [Dissertation]
Advisor: Alshareef, Husam N.
Committee members: Mohammed, Omar F.; Schwingenschlögl, Udo; Ooi, Boon S.; Gogotsi, YuryMXenes, a new class of two-dimensional (2D) materials, have recently demonstrated impressive optoelectronic properties associated with its ultrathin layered structure. Particularly, Ti3C2Tx, the most studied MXene by far, was shown to exhibit intense surface plasmons (SPs), i.e. collective oscillations of free charge carriers, when excited by electromagnetic waves. However, due to the lack of information about the spatial and energy variation of those SPs over individual MXene flakes, the potential use of MXenes in photonics and plasmonics is still marginally explored. Hence, the main objective of this dissertation is to shed the light upon the plasmonic behavior of MXenes at the nanoscale and extend their use beyond their typical electrochemical applications. To fulfill our objective, we first elucidated the underlying characteristics governing the plasmonic behavior of MXenes. Then, we revealed the existence of various tunable SP modes supported by different MXenes, i.e. Ti3C2Tx and Mo2CTx, and investigated their energy and spatial distribution over individual flakes. Further, we fabricated an array of MXene-based flexible photodetectors that only operate at the resonant frequency of the SPs supported by MXenes. We also unveiled the existence of tunable SPs supported by another 2D nanomaterial (i.e. MoO2) and juxtaposed its plasmonic behavior with that of MXenes, to underline the uniqueness of the latter. Noteworthy, as in the case of MXenes, this was the first progress made on studying specific SP modes supported by MoO2 nanostructures. In this part of the dissertation, we were able to identify and tailor multipolar SPs supported by MoO2 and illustrate their dependence on their bulk band structure. In the end, we show that, on the contrary, SPs in MXenes are mainly controlled by the surface band structure. To confirm this, we selectively altered the subsurface band structure of Ti3C2Tx and modulated its work function (from 4.37 to 4.81 eV) via charge transfer doping. Interestingly, thanks to the unchanged surface stoichiometry of Ti3C2Tx, the plasmonic behavior of Ti3C2Tx was not affected by its largely tuned electronic structure. Notably, the ability to attain MXenes with tunable work functions, yet without disrupting their plasmonic behavior, is appealing to many application fields.
Development and application of novel fusion approaches for elemental analysis of carbon-based materials(2020-11-16) [Dissertation]
Advisor: Da Costa, Pedro M. F. J.
Committee members: Nunes, Suzana Pereira; Cavallo, Luigi; Pumera, MartinGraphite and graphitic materials underpin a number of modern technologies such as electrodes for energy storage and conversion systems. Due to their aromatic honeycomb-type lattice and layered structure, these carbons host a rich variety of foreign elements in their interstices. Whether possessing a tubular morphology - that enables the encapsulation of inorganic compounds, or a planar texture - where anions and molecules can intercalate, the chemical analysis of graphite and graphitic materials is often confronted with the need to disintegrate the carbon matrix to quantify target elements, most often metals. However, the resilience of the sp2-hybridized carbon lattice to chemical attacks is an obstacle to its facile solubilization, a necessary step to perform some of the most common elemental analysis measurements. Over the years, a range of alternative approaches have sprung out to address this issue such as the combustion of the carbon matrix followed by the acid dissolution of its ash product. Unfortunately, none of these represents a viable method that can be applied to batteries, in great part because of the different components that make up the carbon-based electrodes. In this dissertation, a new protocol has been developed to digest graphitic materials aiming to access their elemental composition in bulk scale. The approach is based on the use of molten alkaline salts to promote the oxidation of the carbon lattice and leach out metals into a dilute acid solution. As a model sample, given the existence of standards with a matching matrix, single-walled carbon nanotubes were examined. After being subjected to the alkaline oxidation (a.k.a. fusion), they were solubilized and analyzed with Inductively Coupled Plasma-Optical Emission Spectroscopy, a widely popular tool for elemental analysis of metals. Structural analysis ensued to understand the interaction of the molten salts with the nanotubes. After evaluating the applicability of the protocol to other carbons, a more complex system was investigated, namely the carbon-based anode of an intercalation-type potassium ion battery. In this process, a direct way to quantify the mass of the alkali metal was discovered, one which makes use of complementary chemical and structural analytical tools.
III-Oxide Epitaxy, Heterostructure, Material Characterizations, and Applications(2020-11-15) [Dissertation]
Advisor: Ooi, Boon S.
Committee members: Schwingenschlögl, Udo; Tung, Vincent; Zhao, ChaoB-Ga2O3 is one of the emerging semiconductor materials with high breakdown field strength (~ 8 MV/cm) and ultrawide-bandgap (UWBG) 4.9 eV. Therefore, B-Ga2O3 and related compound semiconductors are ideal for power electronics and deep/vacuum ultraviolet-wavelength photodetector applications. High-crystal-quality B-Ga2O3 semiconductor materials epitaxially deposited on the various substrate are prerequisites for realizing any practical application. However, it is still challenging to grow high-crystal-quality V-Ga2O3 layer and to integrate B-Ga2O3 with other semiconductor materials by direct epitaxy. Understanding the epitaxial relationship of the integrated oxide heterostructure and the substrate used helps to shed light on the feasibility of heterojunctions formation for photonic applications, such as the ultraviolet-wavelength photodetectors developed in this thesis. By optimizing pulsed laser deposition (PLD) conditions, such as laser energy, ambient gas, pressure, etc., a single-crystalline oxide heterostructure were successfully integrated into a photonic platform. This included p-NiO/n-B-Ga2O3/a-Al2O3, B-Ga2O3/y-In2O3/a-Al2O3, and B-Ga2O3/TiN/MgO structures. The epitaxial thin film crystallographic and chemical properties were investigated by different characterization techniques. The high-resolution X-ray diffraction (HRXRD) was applied to study the heterostructures’ epitaxial orientation relationship by out-of-plane XRD w-2θ-scan and asymmetric skew ɸ-scan. The lattice-mismatch at the heterostructure interfaces were examined and the crystal quality of the epitaxial thin films were measured by means of full-width at half-maximum (FWHM) fitting. Scanning-TEM energy-dispersive X-ray spectroscopy (STEM-EDX) was applied to qualitatively study the chemical elements’ spatial distribution. Rutherford backscattering spectroscopy (RBS) was applied to study the epitaxial thin film chemical composition, material stoichiometry, and inter-diffusion. The X-ray photoelectron spectroscopy (XPS) was applied to study the conduction and valence band offsets which is essential to determine the types of heterostructures formed. Finally, the p-NiO/n-B-Ga2O3/a-Al2O3 B-Ga2O3/y-In2O3/a-Al2O3, and B-Ga2O3/TiN/MgO epitaxial thin-film were fabricated into ultraviolet-wavelength photodetectors. The wavelength-dependent and power-dependent characterizations were applied to measure the cut-off wavelength and the peak responsivity. The time response characterization was applied to measure the photodetectors’ responses to pulse signals, and the rise and decay times were fitted by a double exponential function.
Spatio-Temporal Statistical Modeling with Application to Wind Energy Assessment in Saudi Arabia(2020-11-08) [Dissertation]
Advisor: Genton, Marc G.
Committee members: Huser, Raphaël G.; Stenchikov, Georgiy L.; Zhang, HaoSaudi Arabia has been trying to change its long tradition of relying on fossil fuels and seek renewable energy sources such as wind power. In this thesis, I firstly provide a comprehensive assessment of wind energy resources and associated spatio-temporal patterns over Saudi Arabia in both current and future climate conditions, based on a Regional Climate Model output. A high wind energy potential exists and is likely to persist at least until 2050 over a vast area ofWestern Saudi Arabia, particularly in the region between Medina and the Red Sea coast and during Summer months. Since an accurate assessment of wind extremes is crucial for risk management purposes, I then present the first high-resolution risk assessment of wind extremes over Saudi Arabia. Under the Bayesian framework, I measure the uncertainty of return levels and produce risk maps of wind extremes, which show that locations in the South of Saudi Arabia and near the Red Sea and the Persian Gulf are at very high risk of disruption of wind turbine operations. In order to perform spatial predictions of the bivariate wind random field for efficient turbine control, I propose parametric variogram matrix (function) models for cokriging, which have the advantage of allowing for a smooth transition between a joint second-order and intrinsically stationary vector random field. Under Gaussianity, the covariance function is central to spatio-temporal modeling, which is useful to understand the dynamics of winds in space and time. I review the various space-time covariance structures and models, some of which are visualized with animations, and associated tests. I also discuss inference issues and a case study based on a high-resolution wind-speed dataset. The Gaussian assumption commonly made in statistics needs to be validated, and I show that tests for independently and identically distributed data cannot be used directly for spatial data. I then propose a new multivariate test for spatial data by accounting for the spatial dependence. The new test is easy to compute, has a chi-square null distribution, and has a good control of the type I error and a high empirical power.
Electromagnetic Properties of Geomaterials(2020-11) [Dissertation]
Advisor: Santamarina, Carlos
Committee members: Ahmed, Shehab; Mishra, Himanshu; Lin, Chih-Ping; Schuster, Gerard T.The advancement of both electronics and instrumentation technology has fostered the development of multi-physics platforms that can probe the earth’s subsurface. Remote, non-destructive testing techniques have led to the increased deployment of electromagnetic waves in sensor technology. Electromagnetic wave techniques are reliable and have the capacity to sense materials and associated properties with minimal perturbation. However, meticulous data analyses and mathematical derivations reveal inconsistencies in some formulations. Thus, revisiting the fundamental physics that underlies both electrical impedance experimental setups and electromagnetic properties are paramount. This study aims to unravel inherent limitations in the understanding of the relationships between electromagnetic and non-electromagnetic properties that are relevant to the characterization of fluids in porous media. These correlations pervade porosity, permeability, specific surface, pore size distribution, tortuosity, fluid discrimination, diffusion coefficient, degree of saturation, viscosity, temperature, phase transformation, miscibility, salinity, and the presence of impurities. The focus is on the assessment of liquids, soils, rocks, and colloids using broad spectral frequency complex permittivity, conductivity, magnetic permeability, and nuclear magnetic resonance relaxometry. Broadband electrical properties measurement for saturated porous media can provide multiple physical phenomena: Ohmic conduction, electrode polarizations, Maxwell-Wagner spatial polarizations, rotational, and segmental polarizations. Liquids dominate the electromagnetic signatures in porous media as dry minerals are inherently non-polar and non-conductive. Results reveal that voltage drops due to the discontinuity of charge-carrier at the electrode-electrolyte interface named electrode polarization inherently affect the low-frequency electrical measurements both in two- and four-probe configurations. Rotational polarizations that occur in MHz-GHz ranges are defined by the electrical dipole moment and effective molecular volume. Both viscosity and effective molecular volume govern the NMR transverse relaxation time. An engineered soil suspension with ferromagnetic inclusions exhibits excellent characteristics for drilling fluid application. Overall, the study highlights the complementary nature of conductivity, permittivity, and NMR relaxation for the advanced characterization of fluid saturated geomaterials.
Probing Chemical Interactions of Asphaltene-like Compounds with Silica and Calcium Carbonate in the Context of Improved Oil Recovery(2020-11) [Dissertation]
Advisor: Patzek, Tadeusz
Committee members: Hoteit, Hussein; Sun, Shuyu; Radke, Clayton J.Crude oil recovery is related to surface wettability, which is controlled by crude interactions with rock surfaces. Understanding these interactions is associated with studying the complex asphaltenes that (1) are irreversibly deposited from oil-brine interfaces onto reservoir mineral surfaces, (2) are bulky super-molecules and (3) incorporate several chemical groups by stacking aromatic rings together. This is a difficult task because of varying crude oil composition, asphaltene interfacial and chemical activity, and the potential of irreversibly contaminating analytical equipment by such substances. To overcome these challenges, we split the problem into parts by studying how different mono- and poly-functional groups mimic asphaltene interaction with mineral surfaces, such as silica and calcium carbonate. The amine, carboxylate, and sulfate groups were identified as the highest potential functional groups responsible for asphaltene adsorption. Experiments included quartz crystal micro-balance with dissipation, bulk adsorption, and core samples. Adsorption tests for the mono-functional surfactants studied were fully reversible and, therefore, not representative of asphaltenes. Poly-functional compounds demonstrated irreversible adsorption, mimicking asphaltenes, through ion exchange and ion-bridging, depending on the type of functional group, chain length, mineral surface, and brine ionic composition. Poly-amines adsorb irreversibly onto silica and calcium carbonate surfaces regardless of the brine ionic composition or surface charge. However, irreversible adsorption of poly-sulfates and poly-carboxylates onto surfaces requires (1) sufficiently long chains and (2) an abundant presence of calcium ions in solution to allow ion-bringing mechanism. These findings suggest that crudes containing amine groups and long chains of carboxylates or sulfates have a higher tendency to be adsorbed onto surfaces and change wettability. This is important for designing an efficient detachment of asphaltenic oil from rock surfaces, where no complete desorption or drastic wettability change is required. The weakening of asphaltene interactions may be sufficient to induce spontaneous imbibition and consequently increase the efficiency of two-phase displacement. This work emphasizes the importance of understating crude-brine-rock interactions for the purpose of oil recovery. In summary, evaluating potential candidates for deploying enhanced oil recovery, such as low salinity waterflooding, should consider rock and crude types, as successful implementation requires “specific” properties collaborating together to enable incremental oil production
Numerical Modeling of Soot Formation in Diffusion Flames(2020-11) [Dissertation]
Advisor: Im, Hong G.
Committee members: Sarathy, Mani; Parsani, Matteo; Cuoci, AlbertoThe combustion of petroleum-based fuels leads to the formation of several pollutants. Among them, soot particles are particularly harmful due to their severe consequences on human health. Over the past decades, strict regulations have been placed on automotive and aircraft engines to limit these particulate matter emissions. This work is primarily focused on understanding the fundamental behaviour of soot particles and their formation. Though the focus of this work is on soot formation and growth pathways, the study of the gas-phase combustion process was also an integral part to validate the mechanism. A reduced mechanism is developed with retaining the larger PAH species till coronene from KAUST-ARAMCO mechanism. Counterflow diffusion flames had emphasized the simulation of canonical configuration where the reduced mechanism is validated and the soot growth pathways are evaluated. The importance of the significant contribution of larger PAH species on the soot growth pathways in both SF and SFO flames is evident in this analysis. The sensitivity of these flames with respect to strain rates, dilution, and at higher pressures are analysed. Direct Numerical Simulation (DNS) of two-dimensional counterflow diffusion flames is conducted to understand the impact of vortex interactions on soot characteristics. The results indicate that the larger PAH species contributes to the soot formation in the air-side perturbation regimes, whereas the soot formation is dominated by the soot transport in fuel-side perturbation. The study is extended to simulate and compare coflow laminar flame using different statistical moment methods MOMIC, HMOM and CQMOM.
Stability Limits and Exhaust Emissions from Ammonia Flames in a Swirl Combustor at Elevated Pressures(2020-11) [Dissertation]
Advisor: Roberts, William L.
Committee members: Lacoste, Deanna; Ruiz-Martinez, Javier; de Joannon, MaraIntimate knowledge of ammonia fueling gas turbines is of crucial importance for power generation sectors, owing to its carbon-free nature and high hydrogen capacity. Anticipated challenges include, among others, the difficulty to stabilize ammonia flames and on top of that the propensity of ammonia flames to produce large quantities of nitrogen monoxide emissions. In gas turbine devices, combustion in practice occurs in a turbulent swirl flow and at elevated pressure conditions. The stability of ammonia flames and the production of NO emissions are sensitive to such parameters. This body of work focuses on the development of a swirl combustor, ~30kW thermal power, for investigating behaviors of flame stability limits and NO emissions from the combustion of ammonia fuel with mixtures of hydrogen or methane at pressure conditions up to 5 bar. Data show that increasing the ammonia addition increases the equivalence ratio at the lean blowout limit but also reduces the flames’ propensity to flashback. If the volume fraction of ammonia in the fuel blend exceeds a critical value, increasing the equivalence ratio at a fixed bulk velocity does not yield flashback and rich blow-out occurs instead. This significantly widens the range of equivalence ratios yielding stable ammonia flames. Regardless of the fuel blend, increasing the pressure increases the propensity to flashback if the bulk velocity remains constant. Pure ammonia-air flames are stable under elevated pressures, and the stable range of equivalence ratio becomes wider as the pressure increases. The NO emissions are measured for large ranges of equivalence ratios, ammonia fractions, and pressures. Regardless of the ammonia fraction, data show that competitively low NO emissions can be found for slightly rich equivalence ratios. Good NO performance is also found for very lean ammonia-hydrogen-air mixtures, regardless of the pressure. NO mole fractions for lean ammonia mixtures can be reduced as pressure increases, demonstrating the strong potential of fueling gas turbines with ammonia-hydrogen mixtures.
Expanding the Aiptasia coral model system to study host-bacteria interactions(2020-11) [Dissertation]
Advisor: Voolstra, Christian R.
Committee members: Daffonchio, Daniele; Hirt, Heribert; Fraune, SebastianThe coral holobiont, comprised of the cnidarian animal host, its associated algal endosymbionts of the family Symbiodiniaceae, and other microbes (bacteria, fungi, viruses, etc.), is the foundation metaorganism of coral reefs. Despite the putative importance of associated microorganisms, elucidation of the specific functions bacteria contribute to the coral holobiont are still largely missing. The sea anemone Aiptasia (sensu Exaiptasia diphana) is regarded as a tractable model to study cnidarian-algal symbioses due to its ability to associate with similar Symbiodiniaceae strains as corals and surviving in symbiotic and aposymbiotic (algal-free) states. The motivation of this dissertation was to expand Aiptasia as a coral model to interrogate host-bacteria interactions. I firstly compared bacterial community composition of Aiptasia in symbiotic and aposymbiotic states and found them to be significantly different. I could also show that some identified bacterial taxa were similar to those found in corals. I further assessed the ectodermal surface topography of several cnidarians as putative bacterial habitats, using electron microscopy. I could show that Aiptasia and corals possess similar surface topographies which differ from other cnidarian models, such as Hydra. In addition, bacterial carrying capacity of Aiptasia polyps was estimated to be between 104 - 105 bacterial cells, roughly equating to the 106 bacterial cells/cm2 reported for corals. To assess the prospect of microbiome manipulation as a tool to study bacterial function and alter bacterial association, I first developed a method to generate bacteria-depleted/gnotobiotic Aiptasia and axenic Symbiodiniaceae cultures and subsequently conducted inoculation experiments. In a pilot experiment, I could show that endogenous and exogenous bacterial isolates could be detected after re-inoculation to gnotobiotic Aiptasia. Further, I conducted coral microbiome transplants to Aiptasia. I could show that some bacterial taxa from corals were detected and active 7 days after transplantation, indicating a certain degree of plasticity in the anemone’s bacterial associations. Overall, my work suggests that Aiptasia might be a suitable model to study coral-bacteria interactions. The thesis presents a foundation for further studies and sheds light on the difficulties associated with generating axenic cnidarian hosts and manipulating bacterial associations.
A Contemporary Investigation on Phytoplankton Ecological Indicators in the Red Sea(2020-11) [Dissertation]
Advisor: Hoteit, Ibrahim
Committee members: Moran, Xose Anxelu G.; Raitsos, Dionysisos; Daffonchio, Daniele; Sathyendranath, ShubhaEcological indicators are defined as quantifiable metrics that can be used to monitor the state of ecosystems and their response to environmental perturbations. In the global oceans, commonly used indicators are typically based on the presence and distribution of phytoplankton (as indexed by the concentration of chlorophyll-a [Chl-a]), which form the base of oceanic food webs. Phytoplankton phenology (the timing of phytoplankton growth) and phytoplankton size structure are particularly important ecological indicators that can be derived via ocean colour remote sensing. Phytoplankton phenology has a direct control on food availability, which subsequently impacts the survival of higher trophic levels and the structure of marine ecosystems. Meanwhile, phytoplankton size structure can be used to define the major functional groups that ultimately influence marine food web structure, biogeochemical cycling and carbon export. The Red Sea is a relatively unexplored tropical marine ecosystem, particularly in relation to its large-scale biological dynamics. In light of recent evidence of rapid regional warming, the need to monitor the response of the Red Sea to potential future ecosystem modifications is becoming more imminent. Using a combination of contemporary oceanographic tools, with an emphasis on ocean colour remote sensing, this PhD thesis attempts to validate the retrieval of phytoplankton ecological indicators in the Red Sea - specifically phytoplankton abundance, phenology and size structure. The interannual variability of both indicators and their linkages with the regional physical environment are also explored.
Enhancing the bonding of CFRP adhesive joints through laser-based surface preparation strategies(2020-11) [Dissertation]
Advisor: Lubineau, Gilles
Committee members: Thoroddsen, Sigurdur T; Mai, Paul Martin; Gonzalez, Carlos; VERGHESE, NikhilNowadays, Carbon Fiber-Reinforced Polymers (CFRPs) have been widely applied in the aerospace and automotive industries. Secondary adhesive bonding, instead of using rivets or bolts in conventional mechanical fastenings, is promising in joining CFRPs because it is simple and applicable for cured parts, widely applied for repairing structures, and of light weight. However, the mechanical performance of secondary bonding is very sensitive to the treatment of CFRP parts. Besides, another concern arises from the fact that secondary bonded specimen often prematurely fails due to delamination and leads to a catastrophic structural collapse. While enhancing the joint strength and toughness is important, limiting the progression of damage is crucial, to ensure confidence in the design and allow enough time for maintenance and repair. Therefore, it is significant to introduce a crack arrest feature into the joints, to slow down (or even stop) the crack growth and achieve progressive failure. In this thesis, we employ advanced surface preparation strategies to enhance the strength, toughness, and safety of adhesively bonded CFRP joints. Globally uniform surface pretreatments, using conventional mechanical abrasion, peel-ply, and pulsed CO2 laser irradiation, are employed at first to improve the mechanical responses of adhesively bonded CFRP joints. Then, to better understand damage mechanisms and guide the joint design, characterizations of surface chemistry, surface energy, and surface morphology are correlated with obtained strength and toughness. Next, trench patterns, ablated by pulsed CO2 laser irradiation, are applied to CFRP substrate to further analyze the role of surface roughness on increased mode I energy release rate. Finally, a novel surface patterning strategy is proposed to achieve superior toughness enhancement in adhesively bonded CFRP joints to improve the joint safety. Such surface preparation strategy is assessed through 2D numerical models and realized experimentally by patterning of pulsed CO2 laser irradiation, illustrating its potential in toughening the joint and successfully delaying the crack propagation.
UAV Enabled IoT Network Designs for Enhanced Estimation, Detection, and Connectivity(2020-11) [Dissertation]
Advisor: Al-Naffouri, Tareq Y.
Committee members: Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim; Shamma, Jeff S.; Shihada, Basem; Gesbert, DavidThe Internet of Things (IoT) is a foundational building block for the upcoming information revolution. Particularly, the IoT bridges the cyber domain to anything within our physical world which enables unprecedented monitoring, connectivity, and smart control. The utilization of Unmanned Aerial Vehicles (UAVs) can offer an extra level of flexibility which results in more advanced and efficient connectivity and data aggregation. In the first part of the thesis, we focus on the optimal IoT devices placement and, the spectral and energy budgets management for accurate source estimation. Practical aspects such as measurement accuracy, communication quality, and energy harvesting are considered. The problem is formed such that a set of cheap and expensive sensors are placed to minimize the estimation error under limited system cost. The IoT revolution relies on aggregating big data from massive numbers of devices that are widely scattered in our environment. These devices are expected to be of low- complexity, low-cost, and limited power supply, which impose stringent constraints on the network operation. Aerial data transmission offers strong line-of-sight links and flexible/instant deployment. The UAV-enabled IoT networks can, for instance, offer solutions to avoid and manage natural disasters such as forest fire. We investigate in this thesis the aerial data aggregation for field estimation, wildfire detection, and connection coverage enhancement via UAVs. To accomplish the network task, the field of interest is divided into several subregions over which the UAVs hover to collect samples from the underlying nodes. To this end, we formulate and solve optimization problems to minimize total hovering and traveling times. This goal is fulfilled by optimizing the UAV hovering locations, the hovering time at each location, and the trajectory traversed between hovering locations. Finally, we propose the utilization of the tethered UAV (T-UAV) to assist the terrestrial network, where the tether provides power supply and connects the T-UAV to the core network through a high capacity link. The T-UAV however has limited mobility due to the limited tether length. A stochastic geometry-based analysis is provided for the optimal coverage probability of T-UAV-assisted cellular networks.