• Nano Antenna Integrated Diode (Rectenna) For Infrared Energy Harvesting

      Gadalla, Mena N. (2013-01)
      In this work full parametric analysis of nano antennas is presented. To begin with, optical or electronic properties of noble metals such as gold and copper were studied in details to get a clear understanding of their reaction to an incident electromagnetic wave. Complex frequency dependent dielectric functions indicated that in THz metals acts as a dielectric with significant absorption. Simultaneous optimization of the length and the bow angle of a bow-tie antenna resulted in relative electric field intensity enhancement of 8 orders of magnitude for 0.5nm gap and 4 orders of magnitude for 50nm around 28THz resonance frequency. These results are at least 2 orders of magnitude greater than the published optical antennas. Physical reasons behind field localization and intensity enhancement  are  discussed  in  details.  The  solution  of  Maxwell’s  equations  at   the  interface between metallic nano antenna and air is also present in this piece of research. The derived dispersion relation of surface plasmons shows momentum matching at 28.3 THz between free propagating electromagnetic fields’ modes in air and localized modes at the interface. Consequently, Propagating electromagnetic waves are ensured to couple to localized surface propagating modes producing filed enhancement. The integrated SiO2 matching section is theoretically proven to increase transmission to substrate to 75% (compared to 40% without it) which in turn improves the coupled power by 40 times. Nano antennas were fabricated in house using Electron beam lithography with a precise gap of 50nm. In addition, THz diode was designed, fabricated and integrated to the nano antennas to rectify the enhanced THz signal. The integration of the nano diode required a precise overlap of the two arms of the antenna in the rage of 100nm. In order to overcome two arms overlap fabrication challenges, three layer alignment technique was used to produce precise overlap.The THz rectifier was electrically tested and shown high sensitivity and rectification ability without any bias. Finally, nano antenna integrated diode is under optical testing using a 10.6μm Co2 laser at Electro-Optics Lab, Prince Sultan Advanced Technologies Research Institute (PSATRI), King Saud University due to the unavailability of the measurement setup in KAUST.
    • Nano-Reinforcement of Interfaces in Prepreg-Based Composites Using a Carbon Nanotubes Spraying Method

      Almuhammadi, Khaled (2012-11)
      Multi-scale reinforcement of composite materials is a topic a great interest owing to the several advantages provided, e.g. increased stiffness, improved aging resistance, and fracture toughness. It is well known, that the fracture toughness of epoxy resins used as matrix materials for CFRP composites can be increased by the addition of nano-sized fillers such as Carbon nanotubes (CNTs). CNTs are particularly well suited for this purpose because of their nano-scale diameter and high aspect ratio which allow enhancing the contact area and adhesion to the epoxy matrix. On the other hand, CNTs can also be used to improve the interlaminar strength of composite, which is the resistance offered to delamination. Several fabrication techniques have been devised to this purpose, such as powder dispersion [51-53], spraying [54], roll coating [2] and electrospinning [55, 56]. The aim of this work is to extend the knowledge in this field. In particular, MWCNTs were dispersed throughout the interface of a carbon fiber composite laminate ([0o]16) through spraying and the resulting fracture toughness was investigated in detail. To this purpose, Double Cantilever Beam (DCB) specimens were fabricated by placing 0.5 wt.% CNTs at the interface of mid-plane plies and the fracture toughness was determined using the ASTM standard procedures. For comparison, baseline samples were prepared using neat prepregs. In order to corroborate the variation of fracture toughness to the modifications of interfacial damage mechanisms, Scanning Electron Microscopy (SEM) of the failed surfaces was also undertaken. The results of this work have shown that functionalized MWCNTs can enhance the interlaminar fracture toughness; indeed, compared to the neat case, an average increase around 17% was observed. The SEM analysis revealed that the improved fracture toughness was related to the ability of the Nano-reinforcement to spread the damage through crack bridging, i.e. CNTs pull-out and peeling.
    • Nanocomposite Membrane via Magnetite Nanoparticle Assembly

      Xie, Yihui (2012-07)
      Membrane technology is one of the most promising technologies for addressing the global water crisis as well as in many other applications. One of the drawbacks of current ultra- and nanofiltration membranes is the relatively broad pore size distribution. Block copolymer membranes with ultrahigh permeability and very regular pore sizes have been recently demonstrated with pores being formed by the supramolecular assembly of core/shell micelles. Our study aimed at developing an innovative and economically efficient alternative method to fabricate isoporous membrane by self-assembly of magnetic nanoparticle with a polystyrene shell, mimicking the behavior of block copolymer micelle. Fe3O4 nanoparticles of ~13 nm diameter were prepared by co-precipitation as cores. The initiator for ATRP was covalently bonded onto the surface of magnetic nanoparticles with two strategies. Then the surface initiated ATRP of styrene was carried out to functionalize nanoparticles with polystyrene through a “grafting from” method. Finally, the nanocomposite membrane was cast from 50 wt % Fe3O4@PS brush polymer solution in DMF via non solvent phase inversion. Microscopies reveal an asymmetric membrane with a dense thin layer on top of a porous sponge-like layer. This novel class of asymmetric membrane, based on the pure assembly of functionalized nanoparticles was prepared for the first time. The nanoparticles are well distributed however with no preferential order yet in the as-cast film.I would like to thank my committee chair and advisor, Prof. Suzana Nunes, and other committee members, Prof. Klaus-Viktor Peinemann and Prof. Gary Amy, for their guidance and support throughout the course of this research. My appreciation also goes to my colleagues in our group for useful discussions and suggestions. I also want to extend my gratitude to the staff from the KAUST Core Lab for Advanced Nanofabrication, Imaging and Characterization, especially Dr. Ali Reza Behzad, Dr. Rachid Sougrat, and Dr. Long Chen, for their assistance for various microscopy measurements. Finally, my heartfelt gratitude is extended to my parents and all my friends. I cannot finish this thesis without their encouragement and support.
    • Nanofabrication of SERS Substrates for Single/Few Molecules Detection

      Melino, Gianluca (2015-05-04)
      Raman spectroscopy is among the most widely employed methods to investigate the properties of materials in several fields of study. Evolution in materials science allowed us to fabricate suitable substrates, at the nanoscale, capable to enhance the electromagnetic field of the signals coming from the samples which at this range turn out to be in most cases singles or a few molecules. This particular variation of the classical technique is called SERS (Surface Enanched Raman Spectroscopy). In this work, the enhancement of the electromagnetic field is obtained by manipulation of the optical properties of metals with respect to their size. By using electroless deposition (bottom up technique), gold and silver nanoparticles were deposited in nanostructured patterns obtained on silicon wafers by means of electron beam lithography (top down technique). Rhodamine 6G in aqueous solution at extremely low concentration (10-8 M) was absorbed on the resultant dimers and the collection of the Raman spectra demonstrated the high efficiency of the substrates.
    • Nanoscopical dissection of ancestral nucleoli in Archaea: a case of study in Evolutionary Cell Biology

      Islas Morales, Parsifal (2018-04)
      Is the nucleolus a sine qua non condition of eukaryotes? The present project starts from this central question to contribute to our knowledge about the origin and the evolution of the cells. The nucleolus is a cryptic organelle that plays a central role in cell function. It is responsible for the orchestration of ribosomal RNA expression, maturation and modification in the regulatory context of cellular homeostasis. Ribosomal expression is undoubtedly the greatest transcriptional and regulatory activity of any cell. The nucleolus is not just a conventional organelle –membrane-limited-, but a magnificent transcriptional puff: a dichotomy between structure and process, form and function. What is the minimum nucleolus? Evolution should bring some light into these questions. Evolutionary cell biology (ECB) has raised increasing attention in the last decades. Is this a new discipline and an historical opportunity to combine functional and evolutionary biology towards the insight that cell evolution underlies organismic complexity? In the post-genomic era, we have developed the potential of combining high throughput acquisition of data with functional in situ and in sillico approaches: integration understood as omics approaches. Can this provide a real consilience between evolutionary and functional approaches? The reduced number of model organisms and cultivation techniques still excludes the majority of the extant diversity of cells from the scope of experimental inquiry. Furthermore, at the conceptual level, the simplification of evolutionary processes in biosciences still limits the conformation of a successful disciplinary link between functional and evolutionary biology. This limits the formulation of questions and experiments that properly address the mechanistic nature of cellular events that underlie microbial and organismic diversity and evolution. Here we provide a critical and comparative review to the historical background of ECB. This project takes the lessons learned from ECB and attempts to find a homologue structure of the eukaryotic nucleolus within the Archaea. We found nanometric structures in S. solfactarius that either are positive to specific nucleolar techniques such as Nucleolar organizer regions NOR silver staining. These is structures are novel and its significance should be revised on the evolutionary cell biology perspective.
    • Nanostructured Membranes Functionalized with Gold Nanoparticles for Separation and Recovery of Monoclonal Antibodies

      Soldan, Giada (2017-11)
      The need of purified biomolecules, such as proteins or antibodies, has required the biopharmaceutical industries to look for new recovering solutions to reduce time and costs of bioseparations. In the last decade, the emergent field of membrane chromatography has gained attention as possible substituent of the common used protein A affinity chromatography for bioseparations. In this scenario, gold nanoparticles can be used as means for offering affinity, mainly because of their biocompatible and reversible binding behavior, together with their high surface area-to-volume ratio, which offers a large number of binding sites. This work introduces a new procedure for purification of monoclonal antibodies based on polymeric membranes functionalized with gold nanoparticles. This novel approach shortens the process of purification by promoting selective binding of antibodies, while separating a mixture of biomolecules during a filtration process. The effects of gold nanoparticles and the surrounding ligand on the proteins adsorption and filtration are investigated. The results confirm that the functionalization helps in inducing a selective binding, preventing the non-selective one, and it also improves the selectivity of the separation process.
    • Neural Inductive Matrix Completion for Predicting Disease-Gene Associations

      Hou, Siqing (2018-05-21)
      In silico prioritization of undiscovered associations can help find causal genes of newly discovered diseases. Some existing methods are based on known associations, and side information of diseases and genes. We exploit the possibility of using a neural network model, Neural inductive matrix completion (NIMC), in disease-gene prediction. Comparing to the state-of-the-art inductive matrix completion method, using neural networks allows us to learn latent features from non-linear functions of input features. Previous methods use disease features only from mining text. Comparing to text mining, disease ontology is a more informative way of discovering correlation of dis- eases, from which we can calculate the similarities between diseases and help increase the performance of predicting disease-gene associations. We compare the proposed method with other state-of-the-art methods for pre- dicting associated genes for diseases from the Online Mendelian Inheritance in Man (OMIM) database. Results show that both new features and the proposed NIMC model can improve the chance of recovering an unknown associated gene in the top 100 predicted genes. Best results are obtained by using both the new features and the new model. Results also show the proposed method does better in predicting associated genes for newly discovered diseases.
    • A new deterministic Ensemble Kalman Filter with one-step-ahead smoothing for storm surge forecasting

      Raboudi, Naila (2016-11)
      The Ensemble Kalman Filter (EnKF) is a popular data assimilation method for state-parameter estimation. Following a sequential assimilation strategy, it breaks the problem into alternating cycles of forecast and analysis steps. In the forecast step, the dynamical model is used to integrate a stochastic sample approximating the state analysis distribution (called analysis ensemble) to obtain a forecast ensemble. In the analysis step, the forecast ensemble is updated with the incoming observation using a Kalman-like correction, which is then used for the next forecast step. In realistic large-scale applications, EnKFs are implemented with limited ensembles, and often poorly known model errors statistics, leading to a crude approximation of the forecast covariance. This strongly limits the filter performance. Recently, a new EnKF was proposed in [1] following a one-step-ahead smoothing strategy (EnKF-OSA), which involves an OSA smoothing of the state between two successive analysis. At each time step, EnKF-OSA exploits the observation twice. The incoming observation is first used to smooth the ensemble at the previous time step. The resulting smoothed ensemble is then integrated forward to compute a "pseudo forecast" ensemble, which is again updated with the same observation. The idea of constraining the state with future observations is to add more information in the estimation process in order to mitigate for the sub-optimal character of EnKF-like methods. The second EnKF-OSA "forecast" is computed from the smoothed ensemble and should therefore provide an improved background. In this work, we propose a deterministic variant of the EnKF-OSA, based on the Singular Evolutive Interpolated Ensemble Kalman (SEIK) filter. The motivation behind this is to avoid the observations perturbations of the EnKF in order to improve the scheme's behavior when assimilating big data sets with small ensembles. The new SEIK-OSA scheme is implemented and its efficiency is demonstrated by performing assimilation experiments with the highly nonlinear Lorenz model and a realistic setting of the Advanced Circulation (ADCIRC) model configured for storm surge forecasting in the Gulf of Mexico during Hurricane Ike.
    • A New Interpolation Approach for Linearly Constrained Convex Optimization

      Espinoza, Francisco (2012-08)
      In this thesis we propose a new class of Linearly Constrained Convex Optimization methods based on the use of a generalization of Shepard's interpolation formula. We prove the properties of the surface such as the interpolation property at the boundary of the feasible region and the convergence of the gradient to the null space of the constraints at the boundary. We explore several descent techniques such as steepest descent, two quasi-Newton methods and the Newton's method. Moreover, we implement in the Matlab language several versions of the method, particularly for the case of Quadratic Programming with bounded variables. Finally, we carry out performance tests against Matab Optimization Toolbox methods for convex optimization and implementations of the standard log-barrier and active-set methods. We conclude that the steepest descent technique seems to be the best choice so far for our method and that it is competitive with other standard methods both in performance and empirical growth order.
    • A New Outlier Detection Method for Multidimensional Datasets

      Abdel Messih, Mario A. (2012-07)
      This study develops a novel hybrid method for outlier detection (HMOD) that combines the idea of distance based and density based methods. The proposed method has two main advantages over most of the other outlier detection methods. The first advantage is that it works well on both dense and sparse datasets. The second advantage is that, unlike most other outlier detection methods that require careful parameter setting and prior knowledge of the data, HMOD is not very sensitive to small changes in parameter values within certain parameter ranges. The only required parameter to set is the number of nearest neighbors. In addition, we made a fully parallelized implementation of HMOD that made it very efficient in applications. Moreover, we proposed a new way of using the outlier detection for redundancy reduction in datasets where the confidence level that evaluates how accurate the less redundant dataset can be used to represent the original dataset can be specified by users. HMOD is evaluated on synthetic datasets (dense and mixed “dense and sparse”) and a bioinformatics problem of redundancy reduction of dataset of position weight matrices (PWMs) of transcription factor binding sites. In addition, in the process of assessing the performance of our redundancy reduction method, we developed a simple tool that can be used to evaluate the confidence level of reduced dataset representing the original dataset. The evaluation of the results shows that our method can be used in a wide range of problems.
    • Nitrogen fixation in Red Sea seagrass meadows

      Abdallah, Malak (2017-05)
      Seagrasses are key coastal ecosystems, providing many ecosystem services. Seagrasses increase biodiversity as they provide habitat for a large set of organisms. In addition, their structure provides hiding places to avoid predation. Seagrasses can grow in shallow marine coastal areas, but several factors regulate their growth and distribution. Seagrasses can uptake different kinds of organic and inorganic nutrients through their leaves and roots. Nitrogen and phosphorous are the most important nutrients for seagrass growth. Biological nitrogen fixation is the conversion of atmospheric nitrogen into ammonia by diazotrophic bacteria. This process provides a significant source of nitrogen for seagrass growth. The nitrogen fixation is controlled by the nif genes which are found in diazotrophs. The main goal of the project is to measure nitrogen fixation rates on seagrass sediments, in order to compare among various seagrass species from the Red Sea. Moreover, we will compare the fixing rates of the Vegetated areas with the bare sediments. This project will help to ascertain the role of nitrogen fixing bacteria in the development of seagrass meadows.
    • Nonlinear Dynamics of Electrostatically Actuated MEMS Arches

      Al Hennawi, Qais M. (2015-05)
      In this thesis, we present theoretical and experimental investigation into the nonlinear statics and dynamics of clamped-clamped in-plane MEMS arches when excited by an electrostatic force. Theoretically, we first solve the equation of motion using a multi- mode Galarkin Reduced Order Model (ROM). We investigate the static response of the arch experimentally where we show several jumps due to the snap-through instability. Experimentally, a case study of in-plane silicon micromachined arch is studied and its mechanical behavior is measured using optical techniques. We develop an algorithm to extract various parameters that are needed to model the arch, such as the induced axial force, the modulus of elasticity, and the initially induced initial rise. After that, we excite the arch by a DC electrostatic force superimposed to an AC harmonic load. A softening spring behavior is observed when the excitation is close to the first resonance frequency due to the quadratic nonlinearity coming from the arch geometry and the electrostatic force. Also, a hardening spring behavior is observed when the excitation is close to the third (second symmetric) resonance frequency due to the cubic nonlinearity coming from mid-plane stretching. Then, we excite the arch by an electric load of two AC frequency components, where we report a combination resonance of the summed type. Agreement is reported among the theoretical and experimental work.
    • Nonlinear Dynamics of Memristor Based 2nd and 3rd Order Oscillators

      Talukdar, Abdul Hafiz (2011-05)
      Exceptional behaviours of Memristor are illustrated in Memristor based second order (Wien oscillator) and third order (phase shift oscillator) oscillator systems in this Thesis. Conventional concepts about sustained oscillation have been argued by demonstrating the possibility of sustained oscillation with oscillating resistance and dynamic poles. Mathematical models are also proposed for analysis and simulations have been presented to support the surprising characteristics of the Memristor based oscillator systems. This thesis also describes a comparative study among the Wien family oscillators with one Memristor. In case of phase shift oscillator, one Memristor and three Memristors systems are illustrated and compared to generalize the nonlinear dynamics observed for both 2nd order and 3rd order system. Detail explanations are provided with analytical models to simplify the unconventional properties of Memristor based oscillatory systems.
    • Nonlinear Wave Propagation and Solitary Wave Formation in Two-Dimensional Heterogeneous Media

      Luna, Manuel (2011-05)
      Solitary wave formation is a well studied nonlinear phenomenon arising in propagation of dispersive nonlinear waves under suitable conditions. In non-homogeneous materials, dispersion may happen due to effective reflections between the material interfaces. This dispersion has been used along with nonlinearities to find solitary wave formation using the one-dimensional p-system. These solitary waves are called stegotons. The main goal in this work is to find two-dimensional stegoton formation. To do so we consider the nonlinear two-dimensional p-system with variable coefficients and solve it using finite volume methods. The second goal is to obtain effective equations that describe the macroscopic behavior of the variable coefficient system by a constant coefficient one. This is done through a homogenization process based on multiple-scale asymptotic expansions. We compare the solution of the effective equations with the finite volume results and find a good agreement. Finally, we study some stability properties of the homogenized equations and find they and one-dimensional versions of them are unstable in general.
    • Novel Metal Clusters for Imaging Applications

      Alsaiari, Shahad K. (2014-05)
      During the past few years, gold nanoparticles (AuNPs) have received considerable attention in many fields due to their optical properties, photothermal effect and biocompatibility. AuNPs, particularly AuNCs and AuNRs, exhibit great potential in diagnostics and imaging. In the present study, AuNCs were used to selectively image and quantify intracellular antioxidants. It was reported by Chen et al. that the strong fluorescence of AuNCs is quenched by highly reactive oxygen species (hROS). Most of applications depend on fluorescence quenching, however, for our project we designed turn-on fluorescent sensors using AuNCs that sense antioxidants. In the presence of antioxidants, AuNCs fluorescence switch on, while in the absence of antioxidants their fluorescence immediately turn off due to hROS effect. AuNRs were also used for cellular imaging in which AuNRs were conjugated to Cy3-labelled molecular beacon (MB) DNA. Next, the previous complex was loaded in two different strains of magnetotactic bacteria (MTB). MTB were used as a targeted delivery vehicle in which magnetosomes direct the movement of bacteria. The DNA sequence was specific to a certain sequence in mitochondria. The exposure of MTB to an alternating magnetic field (AMF) leads to the increase of temperature inside the bacteria, which destruct the cell wall, and hence, bacterial payload is released. When MD-DNA hybrid with the target sequence, AuNR and Cy3 separate from each other, the fluorescence of the Cy3 is restored.
    • A Novel Non-coding RNA Regulates Drought Stress Tolerance in Arabidopsis thaliana

      Albesher, Nour H. (2014-05)
      Drought (soil water deficit) as a major adverse environmental condition can result in serious reduction in plant growth and crop production. Plants respond and adapt to drought stresses by triggering various signalling pathways leading to physiological, metabolic and developmental changes that may ultimately contribute to enhanced tolerance to the stress. Here, a novel non-coding RNA (ncRNA) involved in plant drought stress tolerance was identified. We showed that increasing the expression of this ncRNA led to enhanced sensitivity during seed germination and seedling growth to the phytohormone abscisic acid. The mutant seedlings are also more sensitive to osmotic stress inhibition of lateral root growth. Consistently, seedlings with enhanced expression of this ncRNA exhibited reduced transiprational water loss and were more drought-tolerant than the wild type. Future analyses of the mechanism for its role in drought tolerance may help us to understand how plant drought tolerance could be further regulated by this novel ncRNA.
    • Novel Techniques to Characterize Pore Size of Porous Materials

      Alabdulghani, Ali J. (2016-04-24)
      Porous materials are implemented in several industrial applications such as water desalination, gas separation and pharmaceutical care which they are mainly governed by the pore size and the PSD. Analyzing shale reservoirs are not excluded from these applications and numerous advantages can be gained by evaluating the PSD of a given shale reservoir. Because of the limitations of the conventional characterization techniques, novel methods for characterizing the PSD have to be proposed in order to obtain better characterization results for the porous materials, in general, and shale rocks in particular. Thus, permporosimetry and evapoporometry (EP) technologies were introduced, designed and utilized for evaluating the two key parameters, pore size and pore size distribution. The pore size and PSD profiles of different shale samples from Norway and Argentina were analyzed using these technologies and then confirmed by mercury intrusion porosimeter (MIP). Norway samples showed an average pore diameter of 12.94 nm and 19.22 nm with an average diameter of 13.77 nm and 23.23 nm for Argentina samples using permporosimetry and EP respectively. Both techniques are therefore indicative of the heterogeneity of the shales. The results from permporosimetry are in good agreement with those obtained from MIP technique, but EP for most part over-estimates the average pore size. The divergence of EP results compared to permporosimetry results is referred to the fact that the latter technique measures only the active pores which is not the case with the former technique. Overall, both techniques are complementary to each other which the results from both techniques seem reasonable and reliable and provide two simple techniques to estimate the pore size and pore size distributions for shale rocks.
    • Numerical Investigation of Shock Bubble Interaction using Wavelet Adaptive Multi-Resolution Method

      Dhopeshwar, Rahul (2018-07)
      When a shock interacts with a bubble having a different density than the environment or medium, the interaction causes compression and deformation of the bubble and generation of a vortex pair. Later, secondary vortices appear causing enhanced mixing. The enhanced mixing induced by the shock bubble interactions is particularly of interest in supersonic combustion and detonation. The Wavelet Adaptive Multi-resolution Representation (WAMR) method is particularly suitable for challenging continuum physics problems like shock bubble interaction, which has strong multi-scale character. This method provides an efficient strategy to create a dynamically adaptive spatial grid and to obtain a verified solution. Since the wavelet amplitude provides a first-hand estimate of the local error at each point, the method is able to efficiently capture a wide spectrum of spatial scales by dynamically changing the adaptive grid. Highly resolved computations are done only in the regions where abrupt transition occurs. In this work a detailed investigation of Shock Bubble Interaction (SBI) is carried out using shocks having Mach numbers from 1.2 to 3 for helium, nitrogen and krypton bubbles. Simulations carried out using WAMR method were used to analyze the effects of Mach number and density contrast on the shape, location and velocity of the bubble as well as vorticity and pressure in the flow field.
    • Numerical Modelling of Soot Formation in Laminar Axisymmetric Ethylene-Air Coflow Flames at Atmospheric and Elevated Pressures

      Rakha, Ihsan Allah (2015-05)
      The steady coflow diffusion flame is a widely used configuration for studying combustion kinetics, flame dynamics, and pollutant formation. In the current work, a set of diluted ethylene-air coflow flames are simulated to study the formation, growth, and oxidation of soot, with a focus on the effects of pressure on soot yield. Firstly, we assess the ability of a high performance CFD solver, coupled with detailed transport and kinetic models, to reproduce experimental measurements, like the temperature field, the species’ concentrations and the soot volume fraction. Fully coupled conservation equations for mass, momentum, energy, and species mass fractions are solved using a low Mach number formulation. Detailed finite rate chemistry describing the formation of Polycyclic Aromatic Hydrocarbons up to cyclopenta[cd]pyrene is used. Soot is modeled using a moment method and the resulting moment transport equations are solved with a Lagrangian numerical scheme. Numerical and experimental results are compared for various pressures. Reasonable agreement is observed for the flame height, temperature, and the concentrations of various species. In each case, the peak soot volume fraction is predicted along the centerline as observed in the experiments. The predicted integrated soot mass at pressures ranging from 4-8 atm, scales as P2.1, in satisfactory agreement with the measured integrated soot pressure scaling (P2.27). Significant differences in the mole fractions of benzene and PAHs, and the predicted soot volume fractions are found, using two well-validated chemical kinetic mechanisms. At 4 atm, one mechanism over-predicts the peak soot volume fraction by a factor of 5, while the other under-predicts it by a factor of 5. A detailed analysis shows that the fuel tube wall temperature has an effect on flame stabilization.
    • Numerical Simulation of Shale Gas Production with Thermodynamic Calculations Incorporated

      Urozayev, Dias (2015-06)
      In today’s energy sector, it has been observed a revolutionary increase in shale gas recovery induced by reservoir fracking. So-called unconventional reservoirs became profitable after introducing a well stimulation technique. Some of the analysts expect that shale gas is going to expand worldwide energy supply. However, there is still a lack of an efficient as well as accurate modeling techniques, which can provide a good recovery and production estimates. Gas transports in shale reservoir is a complex process, consisting of slippage effect, gas diffusion along the wall, viscous flow due to the pressure gradient. Conventional industrial simulators are unable to model the flow as the flow doesn’t follow Darcy’s formulation. It is significant to build a unified model considering all given mechanisms for shale reservoir production study and analyze the importance of each mechanism in varied conditions. In this work, a unified mathematical model is proposed for shale gas reservoirs. The proposed model was build based on the dual porosity continuum media model; mass conservation equations for both matrix and fracture systems were build using the dusty gas model. In the matrix, gas desorption, Knudsen diffusion and viscous flow were taken into account. The model was also developed by implementing thermodynamic calculations to correct for the gas compressibility, or to obtain accurate treatment of the multicomponent gas. Previously, the model was built on the idealization of the gas, considering every molecule identical without any interaction. Moreover, the compositional variety of shale gas requires to consider impurities in the gas due to very high variety. Peng-Robinson equation of state was used to com- pute and correct for the gas density to pressure relation by solving the cubic equation to improve the model. The results show that considering the compressibility of the gas will noticeably increase gas production under given reservoir conditions and slow down the production decline curve. Therefore, for a more accurate prediction of shale gas production, it is crucial to consider compressibility behavior of the gas.