• H-Seda: Partial Packet Recovery with Heterogeneous Block Sizes for Wireless Sensor Networks

      Meer, Ammar M. (2012-12-08)
      Wireless sensor networks (WSN) have been largely used in various applications due to its ease of deployment and scalability. The throughput of such networks, however, suffers from high bit error rates mainly because of medium characteristics. Maximizing bandwidth utilization while maintaining low frame error rate has been an interesting problem. Frame fragmentation into small blocks with dedicated error detection codes per block can reduce the unnecessary retransmission of the correctly received blocks. The optimal block size, however, varies based on the wireless channel conditions. In addition, blocks within a frame can have different optimal sizes based on the variations on interference patterns. This thesis studies two dynamic partial packet recovery approaches experimentally over several interference intensities with various transmission-power levels. It also proposes a dynamic data link layer protocol: Hybrid Seda (H-Seda). H-Seda effectively addresses the challenges associated with dynamic partitioning of blocks while taking the observed error patterns into consideration. The design of H-Seda is discussed in details and compared to other previous approaches, namely Seda+ and Seda. The implementation of H-Seda shows substantial enhancements over fixed-size partial packet recovery protocols, achieving up to 2.5x improvement in throughput when the channel condition is noisy, while delay experienced decreases to only 14 % of the delay observed in Seda. On average, it shows 35% gain in goodput across all channel conditions used in our experiments. This significant improvement is due to the selective nature of H-Seda which minimizes retransmission overhead by selecting the appropriate number of blocks in each data frame. Additionally, H-Seda successfully reduces block overhead by 50% through removing block number field reaching to better performance when channel conditions are identical.
    • Hand Gesture Recognition Using Ultrasonic Waves

      AlSharif, Mohammed Hussain (2016-04)
      Gesturing is a natural way of communication between people and is used in our everyday conversations. Hand gesture recognition systems are used in many applications in a wide variety of fields, such as mobile phone applications, smart TVs, video gaming, etc. With the advances in human-computer interaction technology, gesture recognition is becoming an active research area. There are two types of devices to detect gestures; contact based devices and contactless devices. Using ultrasonic waves for determining gestures is one of the ways that is employed in contactless devices. Hand gesture recognition utilizing ultrasonic waves will be the focus of this thesis work. This thesis presents a new method for detecting and classifying a predefined set of hand gestures using a single ultrasonic transmitter and a single ultrasonic receiver. This method uses a linear frequency modulated ultrasonic signal. The ultrasonic signal is designed to meet the project requirements such as the update rate, the range of detection, etc. Also, it needs to overcome hardware limitations such as the limited output power, transmitter, and receiver bandwidth, etc. The method can be adapted to other hardware setups. Gestures are identified based on two main features; range estimation of the moving hand and received signal strength (RSS). These two factors are estimated using two simple methods; channel impulse response (CIR) and cross correlation (CC) of the reflected ultrasonic signal from the gesturing hand. A customized simple hardware setup was used to classify a set of hand gestures with high accuracy. The detection and classification were done using methods of low computational cost. This makes the proposed method to have a great potential for the implementation in many devices including laptops and mobile phones. The predefined set of gestures can be used for many control applications.
    • Hardware Realization of Chaos Based Symmetric Image Encryption

      Barakat, Mohamed L. (2012-06)
      This thesis presents a novel work on hardware realization of symmetric image encryption utilizing chaos based continuous systems as pseudo random number generators. Digital implementation of chaotic systems results in serious degradations in the dynamics of the system. Such defects are illuminated through a new technique of generalized post proceeding with very low hardware cost. The thesis further discusses two encryption algorithms designed and implemented as a block cipher and a stream cipher. The security of both systems is thoroughly analyzed and the performance is compared with other reported systems showing a superior results. Both systems are realized on Xilinx Vetrix-4 FPGA with a hardware and throughput performance surpassing known encryption systems.
    • Hardware Realization of Chaos-based Symmetric Video Encryption

      Ibrahim, Mohamad A. (2013-05)
      This thesis reports original work on hardware realization of symmetric video encryption using chaos-based continuous systems as pseudo-random number generators. The thesis also presents some of the serious degradations caused by digitally implementing chaotic systems. Subsequently, some techniques to eliminate such defects, including the ultimately adopted scheme are listed and explained in detail. Moreover, the thesis describes original work on the design of an encryption system to encrypt MPEG-2 video streams. Information about the MPEG-2 standard that fits this design context is presented. Then, the security of the proposed system is exhaustively analyzed and the performance is compared with other reported systems, showing superiority in performance and security. The thesis focuses more on the hardware and the circuit aspect of the system’s design. The system is realized on Xilinx Vetrix-4 FPGA with hardware parameters and throughput performance surpassing conventional encryption systems.
    • High Data Rate Optical Wireless Communications Based on Ultraviolet Band

      Sun, Xiaobin (2017-10)
      Optical wireless communication systems based on ultraviolet (UV)-band has a lot inherent advantages, such as low background solar radiation, low device dark noise. Besides, it also has small restrictive requirements for PAT (pointing, acquisition, and tracking) because of its high atmospheric scattering with molecules and aerosols. And these advantages are driving people to explore and utilize UV band for constructing and implementing a high-data-rate, less PAT communication links, such as diffuse-line-of-sight links (diffuse-LOS) and non-line-of-sight (NLOS). The responsivity of the photodetector at UV range is far lower than that of visible range, high power UV transmitters which can be easily modulated are under investigation. These factors make it is hard to realize a high-data-rate diffuse-LOS or NLOS UV communication links. To achieve a UV link mentioned above with current devices and modulation schemes, this thesis presents some efficient modulation schemes and available devices for the time being. Besides, a demonstration of ultraviolet-B (UVB) communication link is implemented utilizing quadrature amplitude modulation (QAM) orthogonal frequency-division multiplexing (OFDM). The demonstration is based on a 294-nm UVB-light-emitting-diode (UVB-LED) with a full-width at half-maximum (FWHM) of 9 nm, and according to the measured L-I-V curve, we set the bias voltage as 7V for maximum the ac amplitude and thus get a high signal-noise-ratio (SNR) channel, and the light output power is 190 μW with such bias voltage. Besides, there is a unique silica gel lens on top of the LED to concentrate the beam. A -3-dB bandwidth of 29 MHz was measured and a high-speed near-solar-blind communication link with a data rate of 71 Mbit/s was achieved using 8-QAM-OFDM at perfect alignment, and 23.6 Mbit/s using 2-QAM-OFDM when the angle subtended by the pointing direction of the UVB-LED and photodetector (PD) is 12 degrees, thus establishing a diffuse-line-of-sight (LOS) link. The measured bit-error rate (BER) of 2.8 × 10−4 and 2.4 × 10−4, respectively, are well below the forward error correction (FEC) criterion of 3.8 × 10−3. The demonstrated high data-rate OFDM-based UVB communication link paves the way for realizing high-speed non-line-of-sight free-space optical (FSO) communications.
    • High Frequency Asymptotic Methods for Traveltimes and Anisotropy Parameter Estimation in Azimuthally Varying Media

      Masmoudi, Nabil (2014-05)
      Traveltimes are conventionally evaluated by solving the zero-order approximation of the Wentzel, Kramers and Brillouin (WKB) expansion of the wave equation. This high frequency approximation is good enough for most imaging applications and provides us with a traveltime equation called the eikonal equation. The eikonal equation is a non-linear partial differential equation which can be solved by any of the familiar numerical methods. Among the most popular of these methods is the method of characteristics which yields the ray tracing equations and the finite difference approaches. In the first part of the Master Thesis, we use the ray tracing method to solve the eikonal equation to get P-waves traveltimes for orthorhombic models with arbitrary orientation of symmetry planes. We start with a ray tracing procedure specified in curvilinear coordinate system valid for anisotropy of arbitrary symmetry. The coordinate system is constructed so that the coordinate lines are perpendicular to the symmetry planes of an orthorohombic medium. Advantages of this approach are the conservation of orthorhombic symmetry throughout the model and reduction of the number of parameters specifying the model. We combine this procedure with first-order ray tracing and dynamic ray tracing equations for P waves propagating in smooth, inhomogeneous, weakly anisotropic media. The first-order ray tracing and dynamic ray tracing equations are derived from the exact ones by replacing the exact P-wave eigenvalue of the Christoffel matrix by its first-order approximation. In the second part of the Master Thesis, we compute traveltimes using the fast marching method and we develop an approach to estimate the anisotropy parameters. The idea is to relate them analytically to traveltimes which is challenging in inhomogeneous media. Using perturbation theory, we develop traveltime approximations for transversely isotropic media with horizontal symmetry axis (HTI) as explicit functions of the anellipticity parameter and the symmetry axis azimuth in inhomogeneous background media. Specifically, our expansion assumes an inhomogeneous elliptically anisotropic background medium, which may be obtained from well information and stacking velocity analysis in HTI media. This formulation has advantages on two fronts: on one hand, it alleviates the computational complexity associated with solving the HTI eikonal equation, and on the other hand, it provides a mechanism to scan for the best fitting parameters without the need for repetitive modeling of traveltimes, because the traveltime coefficients of the expansion are independent of the perturbed parameters.
    • High Performance Regenerated Cellulose Membranes from Trimethylsilyl Cellulose

      Ali, Ola (2013-05)
      Regenerated cellulose (RC) membranes are extensively used in medical and pharmaceutical separation processes due to their biocompatibility, low fouling tendency and solvent resistant properties. They typically possess ultrafiltration and microfiltration separation characteristics, but recently, there have been attempts to widen their pool of applications in nanofiltration processes. In this work, a novel method for preparing high performance composite RC membranes was developed. These membranes reveal molecular weight cut-offs (MWCO) of less than 250 daltons, which possibly put them ahead of all commercial RC membranes and in competition with high performance nanofiltration membranes. The membranes were prepared by acidic hydrolysis of dip-coated trimethylsilyl cellulose (TMSC) films. TMSC, with a degree of silylation (DS) of 2.8, was prepared from microcrystalline cellulose by reaction with hexamethyldisilazane under the homogeneous conditions of LiCl/DMAC solvent system. Effects of parameters, such as coating solution concentration and drying rates, were investigated. It was concluded that higher TMSC concentrations as well as higher solvent evaporation rates favor better MWCOs, mainly due to increase in the selective layer thickness. Successful cross-linking of prepared membranes with glyoxal solutions, in the presence of boric acid as a catalyst, resulted in MWCOs less than 250 daltons. The suitability of this crosslinking reaction for large scale productions was already proven in the manufacturing of durable-press fabrics. For us, the inexpensive raw materials as well as the low reaction times and temperatures were of interest. Moreover, the non-toxic nature of glyoxal is a key advantage in medical and pharmaceutical applications. The membranes prepared in this work are strong candidates for separation of small organic solutes from organic solvents streams in pharmaceutical industries. Their hydrophilicity, compared to typical nanofiltration membranes, offer high fouling resistance and higher fluxes in aqueous applications.
    • High Productivity Programming of Dense Linear Algebra on Heterogeneous NUMA Architectures

      Alomairy, Rabab M. (2013-07)
      High-end multicore systems with GPU-based accelerators are now ubiquitous in the hardware landscape. Besides dealing with the nontrivial heterogeneous environ- ment, end users should often take into consideration the underlying memory architec- ture to decrease the overhead of data motion, especially when running on non-uniform memory access (NUMA) platforms. We propose the OmpSs parallel programming model approach using its Nanos++ dynamic runtime system to solve the two challeng- ing problems aforementioned, through 1) an innovative NUMA node-aware scheduling policy to reduce data movement between NUMA nodes and 2) a nested parallelism feature to concurrently exploit the resources available from the GPU devices as well as the CPU host, without compromising the overall performance. Our approach fea- tures separation of concerns by abstracting the complexity of the hardware from the end users so that high productivity can be achieved. The Cholesky factorization is used as a benchmark representative of dense numerical linear algebra algorithms. Superior performance is also demonstrated on the symmetric matrix inversion based on Cholesky factorization, commonly used in co-variance computations in statistics. Performance on a NUMA system with Kepler-based GPUs exceeds that of existing implementations, while the OmpSs-enabled code remains very similar to its original sequential version.
    • High Resolution Robust GPS-free Localization for Wireless Sensor Networks and its Applications

      Mirza, Mohammed (2011-12-12)
      In this thesis we investigate the problem of robustness and scalability w.r.t. estimating the position of randomly deployed motes/nodes of a Wireless Sensor Network (WSN) without the help of Global Positioning System (GPS) devices. We propose a few applications of range independent localization algorithms that allow the sensors to actively determine their location with high resolution without increasing the complexity of the hardware or any additional device setup. In our first application we try to present a localized and centralized cooperative spectrum sensing using RF sensor networks. This scheme collaboratively sense the spectrum and localize the whole network efficiently and with less difficulty. In second application we try to focus on how efficiently we can localize the nodes, to detect underwater threats, without the use of beacons. In third application we try to focus on 3-Dimensional localization for LTE systems. Our performance evaluation shows that these schemes lead to a significant improvement in localization accuracy compared to the state-of-art range independent localization schemes, without requiring GPS support.
    • High-Dimensional Analysis of Convex Optimization-Based Massive MIMO Decoders

      Ben Atitallah, Ismail (2017-04)
      A wide range of modern large-scale systems relies on recovering a signal from noisy linear measurements. In many applications, the useful signal has inherent properties, such as sparsity, low-rankness, or boundedness, and making use of these properties and structures allow a more efficient recovery. Hence, a significant amount of work has been dedicated to developing and analyzing algorithms that can take advantage of the signal structure. Especially, since the advent of Compressed Sensing (CS) there has been significant progress towards this direction. Generally speaking, the signal structure can be harnessed by solving an appropriate regularized or constrained M-estimator. In modern Multi-input Multi-output (MIMO) communication systems, all transmitted signals are drawn from finite constellations and are thus bounded. Besides, most recent modulation schemes such as Generalized Space Shift Keying (GSSK) or Generalized Spatial Modulation (GSM) yield signals that are inherently sparse. In the recovery procedure, boundedness and sparsity can be promoted by using the ℓ1 norm regularization and by imposing an ℓ∞ norm constraint respectively. In this thesis, we propose novel optimization algorithms to recover certain classes of structured signals with emphasis on MIMO communication systems. The exact analysis permits a clear characterization of how well these systems perform. Also, it allows an automatic tuning of the parameters. In each context, we define the appropriate performance metrics and we analyze them exactly in the High Dimentional Regime (HDR). The framework we use for the analysis is based on Gaussian process inequalities; in particular, on a new strong and tight version of a classical comparison inequality (due to Gordon, 1988) in the presence of additional convexity assumptions. The new framework that emerged from this inequality is coined as Convex Gaussian Min-max Theorem (CGMT).
    • High-Speed Imaging of a Water Droplet Impacting a Super Cold Surface

      Khaled, Narimane (2016-08)
      Frost formation is of a major research interest as it can affect many industrial processes. Frost appears as a thin deposit of ice crystals when the temperature of the surface is below the freezing point of the liquid. The objective of this research is to study icing with hope to propose new anti-icing and deicing methods. In the beginning of the research, cracking of the ice layer was observed when a deionized water droplet impacts a ?50 oC cooled sphere surface that is in contact with dry ice. To further investigate the cracks occurrence, multiple experiments were conducted. It was observed that the sphere surface temperature and droplet temperature (ranges from 10-80 oC) have no effect on the crack formation. On the other hand, it was observed that formation of a thin layer of frost on the sphere before the drop impact leads the lateral cracking of the ice. Thus, attempts to reproduce the cracks on clean super cold sphere surfaces were made using scratched and sandblasted spheres as well as superhydrophobized and polymer particle coated spheres. Furthermore, innovative methods were tried to initiate the cracks by placing epoxy glue bumps and ice-islands coatings on the surface of the spheres. All of these attempts to reproduce the crack formation without the presence of frost, failed. Nonetheless, the adding of isolated frost on the sphere surfaces always leads to the crack formation. Generally, frost forms on the small spheres faster than it does on the bigger ones. Additionally, the cold water droplet produces thicker water and ice layer compared to a hot water droplet; and the smaller the sphere the larger its water and ice layer thicknesses.
    • High-­Performance Carbon Molecular Sieve Gas Separation Membranes Based on a Carbon-­Rich Intrinsically Microporous Polyimide Precursor

      Hazazi, Khalid (2018-04)
      The objective of this study was to investigate the transport properties and the microstructure of CMS membranes derived from a carbon-rich intrinsically microporous polyimide precursor. CMS membranes were prepared by a heat treatment of the polyimide precursor using a well-defined heating protocol in a horizontal tube furnace up to 1000 °C. A nitrogen purge was kept inside the furnace to remove all the evolved by-products as the precursor started to decompose and carbonize. The microstructures of the carbon molecular sieve membranes (CMSMs) were examined using wide-angle x-ray diffraction, Raman spectra, N2 adsorption and CO2 adsorption. The average interlayer spacing (d002) between the graphite plates was estimated using the data obtained by the WXRD. The average d002 decreased as a result of increasing the pyrolysis temperature; average d002 distances for CMS prepared at 700 and 1000 °C were estimated to be 0.40 to 0.38 nm, respectively. Raman spectra confirmed the progressive structural ordering as heat-treatment temperature increased. A substantial decrease in the intensity of the D band was observed as a function of pyrolysis temperature, indicating a decrease in the disordered structure. Graphitic structure and turbostratic carbon coexist in the as-prepared carbon membranes, of which the microcrystal size La and the stacking height Lc were increasing as a function of pyrolysis temperature. N2 adsorption showed a remarkable increase in the BET surface area as a function of pyrolysis temperature. BET surface areas for the pristine and CMSs prepared at 700 to 900 °C were in the range of 650 to 680 m2/g with a remarkable shift in the pore size distribution toward the ultra- microporous region. CO2 adsorption was used to estimate the surface area for pores with sizes of less than 1 nm. Surface areas were observed to increase from 350 m2/g at 500 °C to 857 m2/g at 800 °C, and then started dropping slightly from 857 to 650 m2/g at 800 to 1000 °C, respectively. This is believed to be caused by pore shrinkage effect being severe after 800 °C, which caused some pores to be hard to spot by the CO2 adsorption technique. The transport properties of the pristine and CMS membranes were tested using pure gases He, H2, N2, CH4, CO2, and O2. From the pristine to SBFDA-DMN-700°C, the selectivity increased significantly, with a massive loss in the permeability except for He and H2. From SBFDA-DMN- 700 °C to 900 °C, a substantial increase in selectivity with a moderate decline in permeability was observed. Beyond 900 °C, the permeability again decreased moderately, but a tremendous increase in the selectivity for N2/CH4, CO2/CH4, and H2/CH4 was observed.
    • Higher Order Modes Excitation of Micro Cantilever Beams

      Jaber, Nizar (2014-05)
      In this study, we present analytical and experimental investigation of electrically actuated micro cantilever based resonators. These devices are fabricated using polyimide and coated with chrome and gold layers from both sides. The cantilevers are highly curled up due to stress gradient, which is a common imperfection in surface micro machining. Using a laser Doppler vibrometer, we applied a noise signal to experimentally find the first four resonance frequencies. Then, using a data acquisition card, we swept the excitation frequency around the first four natural modes of vibrations. Theoretically, we derived a reduced order model using the Galerkin method to simulate the dynamics of the system. Extensive numerical analysis and computations were performed. The numerical analysis was able to provide good matching with experimental values of the resonance frequencies. Also, we proved the ability to excite higher order modes using partial electrodes with shapes that resemble the shape of the mode of interest. Such micro-resonators are shown to be promising for applications in mass and gas sensing.
    • History Matching of 4D Seismic Data Attributes using the Ensemble Kalman Filter

      Ravanelli, Fabio M. (2013-05)
      One of the most challenging tasks in the oil industry is the production of reliable reservoir forecast models. Because of different sources of uncertainties the numerical models employed are often only crude approximations of the reality. This problem is tackled by the conditioning of the model with production data through data assimilation. This process is known in the oil industry as history matching. Several recent advances are being used to improve history matching reliability, notably the use of time-lapse seismic data and automated history matching software tools. One of the most promising data assimilation techniques employed in the oil industry is the ensemble Kalman filter (EnKF) because its ability to deal with highly non-linear models, low computational cost and easy computational implementation when compared with other methods. A synthetic reservoir model was used in a history matching study designed to predict the peak production allowing decision makers to properly plan field development actions. If only production data is assimilated, a total of 12 years of historical data is required to properly characterize the production uncertainty and consequently the correct moment to take actions and decommission the field. However if time-lapse seismic data is available this conclusion can be reached 4 years in advance due to the additional fluid displacement information obtained with the seismic data. Production data provides geographically sparse data in contrast with seismic data which are sparse in time. Several types of seismic attributes were tested in this study. Poisson’s ratio proved to be the most sensitive attribute to fluid displacement. In practical applications, however the use of this attribute is usually avoided due to poor quality of the data. Seismic impedance tends to be more reliable. Finally, a new conceptual idea was proposed to obtain time-lapse information for a history matching study. The use of crosswell time-lapse seismic tomography to map velocities in the interwell region was demonstrated as a potential tool to ensure survey reproducibility and low acquisition cost when compared with full scale surface surveys. This approach relies on the higher velocity sensitivity to fluid displacement at higher frequencies. The velocity effects were modeled using the Biot velocity model. This method provided promising results leading to similar RRMS error reductions when compared with conventional history matched surface seismic data.
    • Host-Guest Chemistry of Inorganic Porous Platforms

      Alsufyani, Maryam (2018-07)
      Complexes made by hosts that completely surround their guests provide a mean to stabilize reactive chemical intermediates, transfer biologically active cargo to a diseased cell, and construct molecular scale devices. By the virtue of inorganic host‐guest self‐assembly, the nucleation processes in the cavity of a {P8W48}‐archetype phosphotungstate has afforded a nanoscale 16‐GaIII‐32‐oxo cluster that contain the largest number of GaIII ions yet found in polyoxometalate chemistry. Catalytic activity via thus “Metal-Oxo Cluster within Cluster” Assembly has been preliminarily investigated. Besides, the hybrid aggregates composed of the inorganic {P8W48} and orgainc cyclic moiety has been studied.
    • How does light affect the heat stress response in Arabidopsis?

      Kim, Eunje (2018-11)
      Light and temperature are two of the most important environmental factors regulating plant development. Although heat stress has been well studied, little is known about the interaction between light and temperature. In this study, we performed phenotypic assays comparing seedling responses to heat under light and dark conditions. Seedlings exposed to heat in the dark show lower survival rates than seedlings stressed in the light. To identify transcriptional changes underlying light-dependent heat tolerance, we used RNA-sequencing. The light-dependent heat stress responses involved a plethora of genes which could be potential candidate genes for light-induced heat tolerance, including transcription factors (bHLH) and genes commonly associated with biotic stress. By using the latest high-throughput phenotyping facility, we found that the light-dependent heat tolerance is reflected more on the maintenance of photosynthetic capacity, rather than leaf temperature. These results provide insights into how light increases heat stress tolerance in Arabidopsis seedlings and suggest its underlying mechanisms.
    • Hybrid Adaptive Multilevel Monte Carlo Algorithm for Non-Smooth Observables of Itô Stochastic Differential Equations

      Rached, Nadhir B. (2013-12)
      The Monte Carlo forward Euler method with uniform time stepping is the standard technique to compute an approximation of the expected payoff of a solution of an Itô SDE. For a given accuracy requirement TOL, the complexity of this technique for well behaved problems, that is the amount of computational work to solve the problem, is O(TOL-3). A new hybrid adaptive Monte Carlo forward Euler algorithm for SDEs with non-smooth coefficients and low regular observables is developed in this thesis. This adaptive method is based on the derivation of a new error expansion with computable leading-order terms. The basic idea of the new expansion is the use of a mixture of prior information to determine the weight functions and posterior information to compute the local error. In a number of numerical examples the superior efficiency of the hybrid adaptive algorithm over the standard uniform time stepping technique is verified. When a non-smooth binary payoff with either GBM or drift singularity type of SDEs is considered, the new adaptive method achieves the same complexity as the uniform discretization with smooth problems. Moreover, the new developed algorithm is extended to the MLMC forward Euler setting which reduces the complexity from O(TOL-3) to O(TOL-2(log(TOL))2). For the binary option case with the same type of Itô SDEs, the hybrid adaptive MLMC forward Euler recovers the standard multilevel computational cost O(TOL-2(log(TOL))2). When considering a higher order Milstein scheme, a similar complexity result was obtained by Giles using the uniform time stepping for one dimensional SDEs. The difficulty to extend Giles' Milstein MLMC method to the multidimensional case is an argument for the flexibility of our new constructed adaptive MLMC forward Euler method which can be easily adapted to this setting. Similarly, the expected complexity O(TOL-2(log(TOL))2) is reached for the multidimensional case and verified numerically.
    • Hybrid Broadband Ground-Motion Simulation Using Scenario Earthquakes for the Istanbul Area

      Reshi, Owais A. (2016-04-13)
      Seismic design, analysis and retrofitting of structures demand an intensive assessment of potential ground motions in seismically active regions. Peak ground motions and frequency content of seismic excitations effectively influence the behavior of structures. In regions of sparse ground motion records, ground-motion simulations provide the synthetic seismic records, which not only provide insight into the mechanisms of earthquakes but also help in improving some aspects of earthquake engineering. Broadband ground-motion simulation methods typically utilize physics-based modeling of source and path effects at low frequencies coupled with high frequency semi-stochastic methods. I apply the hybrid simulation method by Mai et al. (2010) to model several scenario earthquakes in the Marmara Sea, an area of high seismic hazard. Simulated ground motions were generated at 75 stations using systematically calibrated model parameters. The region-specific source, path and site model parameters were calibrated by simulating a Mw4.1 Marmara Sea earthquake that occurred on November 16, 2015 on the fault segment in the vicinity of Istanbul. The calibrated parameters were then used to simulate the scenario earthquakes with magnitudes Mw6.0, Mw6.25, Mw6.5 and Mw6.75 over the Marmara Sea fault. Effects of fault geometry, hypocenter location, slip distribution and rupture propagation were thoroughly studied to understand variability in ground motions. A rigorous analysis of waveforms reveal that these parameters are critical for determining the behavior of ground motions especially in the near-field. Comparison of simulated ground motion intensities with ground-motion prediction quations indicates the need of development of the region-specific ground-motion prediction equation for Istanbul area. Peak ground motion maps are presented to illustrate the shaking in the Istanbul area due to the scenario earthquakes. The southern part of Istanbul including Princes Islands show high amplitudes of shaking. The study serves as a step towards dynamic risk quantification for the Istanbul area that integrates physics based ground-motion simulations into an innovative dynamic exposure model to quantify risk.
    • The Hybrid of Classification Tree and Extreme Learning Machine for Permeability Prediction in Oil Reservoir

      Prasetyo Utomo, Chandra (2011-06)
      Permeability is an important parameter connected with oil reservoir. Predicting the permeability could save millions of dollars. Unfortunately, petroleum engineers have faced numerous challenges arriving at cost-efficient predictions. Much work has been carried out to solve this problem. The main challenge is to handle the high range of permeability in each reservoir. For about a hundred year, mathematicians and engineers have tried to deliver best prediction models. However, none of them have produced satisfying results. In the last two decades, artificial intelligence models have been used. The current best prediction model in permeability prediction is extreme learning machine (ELM). It produces fairly good results but a clear explanation of the model is hard to come by because it is so complex. The aim of this research is to propose a way out of this complexity through the design of a hybrid intelligent model. In this proposal, the system combines classification and regression models to predict the permeability value. These are based on the well logs data. In order to handle the high range of the permeability value, a classification tree is utilized. A benefit of this innovation is that the tree represents knowledge in a clear and succinct fashion and thereby avoids the complexity of all previous models. Finally, it is important to note that the ELM is used as a final predictor. Results demonstrate that this proposed hybrid model performs better when compared with support vector machines (SVM) and ELM in term of correlation coefficient. Moreover, the classification tree model potentially leads to better communication among petroleum engineers concerning this important process and has wider implications for oil reservoir management efficiency.
    • Hydro-Metathesis of Long-Chain Olefin (1-decene) using Well-Defined Silica-Supported Tungsten (VI), Molybdenum (VI) and Tantalum (V) Catalysts

      Saidi, Aya (2016-11)
      Nowadays, catalysis lies at the heart of economy growth mainly in the petroleum industry. Catalysis can offer real and potential solutions to the current challenges for a long-term sustainable energy, green chemistry, and environmental protection. In this context, one of the most important and future prosperity promising catalytic applications in the petrochemical field is hydrocarbons metathesis; it consists on the conversion of both renewable and non-petroleum fossil carbon sources to transportation fuels. Olefin metathesis has become one of the standard methodologies for constructing C-C bonds in many organic transformation reactions. This owed to the numerous types of metathesis reactions that have been developed, for example, enyne, ring-opening and closing, self and cross metathesis, etc. But the one step conversion of olefin to alkanes has not been studied much. Recently, only one such a work has been published for the hydro-metathesis of propylene by tantalum hydride supported on KCC-1 in dynamic reactor. With this knowledge, we thought to study the hydro-metathesis using liquid olefin (1-decene). Another aspect of using 1-decene comes from our previous experience on metathesis of n-decane where the first step is the conversion of decane to 1-decene and subsequently to different chain length alkanes with W-alkyl/alkylidene catalyst. In this way, it would be easy for us to use different catalysts and compare them with parent catalyst concerning TON. We found 100% conversion with TON of 1010 using supported WMe6 onto SiO2-700 [(≡Si-O-)WMe5] against the previous results for n-decane showing 20% conversion and TON of 153. In this work, we disclose the hydro-metathesis reaction of 1-decene using well-defined silica supported W(VI), Mo(VI) and Ta(V) alkyl catalysts in batch reactor condition. This work is divided into three major sections; first chapter contains an introduction to the field of catalysis and surface organometallic chemistry. In second chapter, we describe all the experimental procedures of the catalysts. The third chapter is devoted to the characterization and interpretation followed by catalytic reactions. Finally, a brief conclusion of the present study is given.