Oxygen flux and dielectric response study of Mixed Ionic-Electronic Conducting (MIEC) heterogeneous functional materials

Dense mixed ionic-electronic conducting (MIEC) membranes consisting of ionic conductive perovskite-type and/or fluorite-type oxides and high electronic conductive spinel type oxides, at elevated temperature can play a useful role in a number of energy conversion related systems including the solid oxide fuel cell (SOFC), oxygen separation and permeation membranes, partial oxidization membrane reactors for natural gas processing, high temperature electrolysis cells, and others. This study will investigate the impact of different heterogeneous characteristics of dual phase ionic and electronic conductive oxygen separation membranes on their transport mechanisms, in an attempt to develop a foundation for the rational design of such membranes. The dielectric behavior of a material can be an indicator for MIEC performance and can be incorporated into computational models of MIEC membranes in order to optimize the composition, microstructure, and ultimately predict long term membrane performance. The dielectric behavior of the MIECs can also be an indicator of the transport mechanisms and the parameters they are dependent upon. For this study we chose a dual phase MIEC oxygen separation membrane consisting of an ionic conducting phase: gadolinium doped ceria-Ce0.8Gd0.2O1.9 (GDC) and an electronic conductive phase: cobalt ferrite-CoFe2O4 (CFO). The membranes were fabricated from mixtures of Nano-powder of each of the phases for different volume percentages, sintered with various temperatures and sintering time to form systematic micro-structural variations, and characterized by structural analysis (XRD), and micro-structural analysis (SEM-EDS). Performance of the membranes was tested for variable partial pressures of oxygen across the membrane at temperatures from 850°C-1060°C using a Gas Chromatography (GC) system. Permeated oxygen did not directly correlate with change in percent mixture. An intermediate mixture 60%GDC-40%CFO had the highest flux compared to the 50%GDC-50%CFO and 80%GDC-20%CFO mixtures. Material characterization suggests the emergence of a third phase contributing to the behavior. Microstructural studies suggested changes in micro-structure of a given volume fraction for different sintering temperature and sintering time. Flux variation was observed for membranes with the same constituent volume fraction but different micro-structure indicating the effects of the micro-structure on the overall oxygen permeation. To correlate the experimental flux measurement with a standard Wagner‟s flux equation, different microstructural characteristics were studied to incorporate them into a modified Wagner‟s flux equation. In-situ broadband dielectric spectroscopy measurements over a temperature range of 850°C-1060°C and frequency range of (0.1Hz-1MHz) of the operating 60%GDC-40%CFO mixture oxygen separation membranes were measured using a NOVOCONTROL dielectric spectroscopy test system. Dielectric response of the operating membrane was studied to identify the charge transfer process in the membrane. A computational model to study the dielectric impedance response of different microstructure was developed using a COMSOLTM Multiphysics qasi-static electromagnetic module. This model was validated using model materials with regular geometric shapes. To measure impedance of real micro/nano-structures of the membrane material, domains required for the COMSOL calculation were obtained from actual micro/nano structures by using 3D scans from X-ray nano and micro tomography. SimplewareTM software was used to generate 3D domains from image slices obtained from the 3D x-ray scans. Initial voltage distributions on the original microstructure were obtained from the computational model. Similarly, development of a primary model for simulating ionic/electronic species flow inside of an MIEC was also begun. The possibility of using broadband dielectric spectroscopy methods to understand and anticipate the flux capabilities of MIECs to reduce the cost and time of development of such material systems was explored

Dynamic interactions between commodity prices and Australian macroeconomic variables

Price swings of commodities affect the economies of commodity exporting nations worldwide and these fluctuations are a major concern for Australian policy makers. Australia is one of the major commodity exporting countries in the global market; therefore, the main focus of this thesis was to shed light on the influence of various fundamental macroeconomic variables on Australian commodity prices. First, emphasis was placed on what magnitude changes in real interest rates and fluctuations of the real exchange rate account for volatility in commodity prices and whether commodity prices tend to show overshooting phenomena (J. Frankel, 1986; J. Frankel, 2006) in reaction to interest rate changes. The possible contribution of global real economic activity to Australian commodities prices was then assessed, which can lead to both higher interest rates and volatile commodity prices (Akram, 2009; Svensson, 2008) within Australia. Similarly, the current slowdown in world economic growth after several years of high growth might clarify the sharp drop in real interest rates and commodity prices. In addition, the present study explored whether Australian resources stock prices had significant predictive ability for the future global commodity price index as suggested by Rossi (2012). Johansen’s (1988, 1991) cointegration technique was utilised to attain the above research objectives and to examine the long-run relationship of the considered variables. This thesis utilised seasonally adjusted monthly time series for real interest rate, real exchange rate, industrial production and resources stock price from January 2000 to December 2015 after considering an appropriate structural break. The study found significant long-run relationships among the variables; therefore, the vector error correction model was applied to judge the short-run dynamic relationship among variables. Then, the forecast ability of all variables was assessed by employing vector error correction Granger causality or block exogeneity tests. Single equation models do not allow the examination of dynamic relations between commodity prices and other macroeconomic variables over different time horizons (Akram, 2009); therefore, the study applied the impulse response technique as well as forecast error variance decomposition to assess the comparative influences of diverse shocks to the variations in key variables of the proposed commodity price model. The research found significant negative relationships between real interest rates and commodity prices. However, the impulse response results did not show any immediate responses of commodity prices because of an impulse in the real interest rate. This showed a significant negative response of commodity prices after six months of the initial shock and the importance of interest rate information to predict the commodity prices in the long run. In two years’ time, approximately one third of the commodity price changes will be explained by the shocks in real interest rate. The shocks from opposite directions showed a significant negative response for real interest rate after having shocks from Australian commodity prices in the medium term. The results of the present study also suggested an immediate fall in Australian commodity prices and thereafter increases at a higher rate significantly in response to the real exchange rate shock, consistent with Frankel’s (1986) overshooting model of commodity prices. This finding raised the question as to whether real exchange rate shocks are a significant factor of Australian macroeconomic instability as commodity export plays an important role in its economy. Results of the present study revealed the response to this query as being in the negative, especially in the long run. The interaction of these two variables from opposite directions showed interesting results. Separate commodity-related drivers of exchange rates results showed that Australian real exchange rate movements were not purely random. Vector error correction-based Granger causality tests indicated a strong support of causality from commodity prices to real exchange rate in the short run. The impulse response results showed the most noteworthy results. The shocks from Australian commodity prices showed immediate significant depreciation in real exchange rates and the index remained depreciated significantly in all horizons, which shows the complete opposite results to many studies (Connolly & Orsmond, 2011; Minifie, Cherastidtham, Mullerworth, & Savage, 2013; Plumb, Kent, & Bishop, 2013; Sheehan & Gregory, 2013). However, this finding is consistent with the theoretical explanation provided by Dumrongrittikul (2012) to explain the puzzle of the Chinese real exchange rate, which is supported by the theoretical explanation of S. Edwards’ (1989) real exchange rate model. The results of the present study also showed that the shock to industrial production had a negative effect on Australian commodity prices and the effect remained significant during all time horizons. It also showed that the commodity price fluctuation had predictive ability of the Australian resources stock prices. After considering these above findings, several policy recommendations for relevant Australian authorities are suggested and limitations are discussed including the pathway for future research

Modified Internal State Variable Models of Plasticity using Nonlocal Integrals in Damage and Gradients in Dislocation Density

To enhance material performance at different length scales, this study strives to develop a reliable analytical and computational tool with the help of internal state variables spanning micro and macro-level behaviors. First, the practical relevance of a nonlocal damage integral added to an internal state variable (BCJ) model is studied to alleviate numerical instabilities associated within the post-bifurcation regime. The characteristic length scale in the nonlocal damage, which is mathematical in nature, can be calibrated using a series of notch tensile tests. Then the same length scale from the notch tests is used in solving the problem of a high-velocity (between 89 and 107 m/s) rigid projectile colliding against a 6061-T6 aluminum-disk. The investigation indicates that incorporating a characteristic length scale to the constitutive model eliminates the pathological mesh-dependency associated with material instabilities. In addition, the numerical calculations agree well with experimental data. Next, an effort is made rather to introduce a physically motivated length scale than to apply a mathematical-one in the deformation analysis. Along this line, a dislocation based plasticity model is developed where an intrinsic length scale is introduced in the forms of spatial gradients of mobile and immobile dislocation densities. The spatial gradients are naturally invoked from balance laws within a consistent kinematic and thermodynamic framework. An analytical solution of the model variables is derived at homogenous steady state using the linear stability and bifurcation analysis. The model qualitatively captures the formation of dislocation cell-structures through material instabilities at the microscopic level. Finally, the model satisfactorily predicts macroscopic mechanical behaviors - e.g., multi-strain rate uniaxial compression, simple shear, and stress relaxation - and validates experimental results

Epileptic Seizure Detection And Prediction From Electroencephalogram Using Neuro-Fuzzy Algorithms

This dissertation presents innovative approaches based on fuzzy logic in epileptic seizure detection and prediction from Electroencephalogram (EEG). The fuzzy rule-based algorithms were developed with the aim to improve quality of life of epilepsy patients by utilizing intelligent methods. An adaptive fuzzy logic system was developed to detect seizure onset in a patient specific way. Fuzzy if-then rules were developed to mimic the human reasoning and taking advantage of the combination in spatial-temporal domain. Fuzzy c-means clustering technique was utilized for optimizing the membership functions for varying patterns in the feature domain. In addition, application of the adaptive neuro-fuzzy inference system (ANFIS) is presented for efficient classification of several commonly arising artifacts from EEG. Finally, we present a neuro-fuzzy approach of seizure prediction by applying the ANFIS. Patient specific ANFIS classifier was constructed to forecast a seizure followed by postprocessing methods. Three nonlinear seizure predictive features were used to characterize changes prior to seizure. The nonlinear features used in this study were similarity index, phase synchronization, and nonlinear interdependence. The ANFIS classifier was constructed based on these features as inputs. Fuzzy if-then rules were generated by the ANFIS classifier using the complex relationship of feature space provided during training. In this dissertation, the application of the neuro-fuzzy algorithms in epilepsy diagnosis and treatment was demonstrated by applying the methods on different datasets. Several performance measures such as detection delay, sensitivity and specificity were calculated and compared with results reported in literature. The proposed algorithms have potentials to be used in diagnostics and therapeutic applications as they can be implemented in an implantable medical device to detect a seizure, forecast a seizure, and initiate neurostimulation therapy for the purpose of seizure prevention or abortion

Modified Internal State Variable Models of Plasticity using Nonlocal Integrals in Damage and Gradients in Dislocation Density

To enhance material performance at different length scales, this study strives to develop a reliable analytical and computational tool with the help of internal state variables spanning micro and macro-level behaviors. First, the practical relevance of a nonlocal damage integral added to an internal state variable (BCJ) model is studied to alleviate numerical instabilities associated within the post-bifurcation regime. The characteristic length scale in the nonlocal damage, which is mathematical in nature, can be calibrated using a series of notch tensile tests. Then the same length scale from the notch tests is used in solving the problem of a high-velocity (between 89 and 107 m/s) rigid projectile colliding against a 6061-T6 aluminum-disk. The investigation indicates that incorporating a characteristic length scale to the constitutive model eliminates the pathological mesh-dependency associated with material instabilities. In addition, the numerical calculations agree well with experimental data. Next, an effort is made rather to introduce a physically motivated length scale than to apply a mathematical-one in the deformation analysis. Along this line, a dislocation based plasticity model is developed where an intrinsic length scale is introduced in the forms of spatial gradients of mobile and immobile dislocation densities. The spatial gradients are naturally invoked from balance laws within a consistent kinematic and thermodynamic framework. An analytical solution of the model variables is derived at homogenous steady state using the linear stability and bifurcation analysis. The model qualitatively captures the formation of dislocation cell-structures through material instabilities at the microscopic level. Finally, the model satisfactorily predicts macroscopic mechanical behaviors - e.g., multi-strain rate uniaxial compression, simple shear, and stress relaxation - and validates experimental results

Non Blind Watermarking Process using RSA Encryption Method

With the growth of technology and continuous rapid improvement in this field, the digital content took an important role in this current era of time. Online transactions keep growing in many parts of the world. As a result it becomes the prime target for hackers and intruders. Consequently security of data has become a critical issue for experts. In this paper a robust algorithm is proposed in watermarking image to secure the digital data. The proposed algorithm is based on SVDDWT with Harr Wavelet Transform (HWT) for embedding and extracting a digital watermark in an image. The experimental result shows that this technique is robust against few attacks like Gaussian, average and JPEG compression

Assessment of Electrode Configurations of Electrical Impedance Myography for the Evaluation of Neuromuscular Diseases

Electrical impedance myography (EIM) is a painless, noninvasive approach to measure the neuromuscular disease status. EIM parameters- resistance (R), reactance (X) and phase (θ) depend significantly on subcutaneous fat thickness, muscle size and inter electrode distance. The objective of this research is to find an electrode configuration which can minimize the effects on EIM parameters due to subcutaneous fat thickness variation. In this study, a model of human upper arm was developed using finite element method (FEM), which has already been established as an appropriate approach for the analysis of non-symmetrical shape for assessing alternations of muscle in disease-induced changes through EIM. Finite element model with two different kinds of electrode shapes namely rectangular (conventional shape) and circular shapes (proposed shape) were designed for a subcutaneous fat range of 5mm to 25mm. The results show that the standard deviation of reactance values measured for this specified range of fat thickness is 0.65 Ω for circular electrodes, whereas for the rectangular electrode this value is 2.04 Ω. Finally, genetic algorithm was implemented to find an optimized electrode shape which also indicates that the conventional rectangular electrode shape is not the ideal shape for EIM measurements

Systematic Analysis of Flammability Reduction of Polymer Nanocomposites

Polymeric materials are widely used around the world along with high fire hazards due to their flammability. With wide applications of nanotechnology, researchers are currently focusing to develop polymer nanocomposites to enhance their performance in flammability reduction. These flame retardant polymer nanocomposites reduce the ignition time but when applied in proper composition they could reduce the peak heat release rate (PHRR) significantly. With an increasing emphasis on this research area, a database is required to record all the formulations and performance of flame retardant polymer nanocomposites. In this paper, major cone calorimeter test parameters such as ignition time, peak heat release rate, total heat release, were recorded from available literature for polymers including polymethyl methacrylate (PMMA), polypropylene (PP), polystyrene (PS), and polyethylene (PE). Judging by the highest reduction (%) of PHRR, the best formulations of flame retardant polymer nanocomposite have been identified and listed. Ranges of PHRR reduction (%) of different formulations for individual polymers were determined. This review will provide insights to select and/or develop best formulations for flame retardant polymers in the future research.Chemical Engineerin

Injection of Species Under Electrical Field to Enhance Bioremediation.

Electrokinetics is one of the most viable alternatives for injecting/extracting water, organic and ionic species in low permeability soils as well as heterogeneous media because the transport processes are independent of the pore sizes. A better understanding of the principles offers the opportunity to employ multi-component species transport under electrical fields to inject electron acceptors, nutrients and other process additives for enhancement of in-situ bioremediation in low permeability and heterogeneous media. This study assesses the potential to employ and exploit the principles of multi-component species transport under electrical fields as mean to supplement, enhance and engineer in-situ bioremediation. It was determined that ammonium, sulfate, nitrate and phosphate ions can be injected in different types of soils and in a layered deposit with significantly different hydraulic and electrical conductivities. Ions transport rates of 8 to 20 cm/day occurred under current densities of 15 to 150 mA/cm\sp2 and voltage gradients less than 1 V/cm. A uniform distribution of the process additives could be achieved across the electrodes. These results are quite encouraging and demonstrate that the electrokinetics injection scheme has significant potential for in-situ bioremediation in low permeability soil as well as heterogeneous media. The transportability of the injected ions also depend on the charge concentration of the other competing ions on the pore fluid. The accumulation of these pore fluid ions in the system would decrease the transference number of the injected ions. The transportability of the injected ions could be increased by flushing intermittently or continuously the electrodes compartments to decrease the conductivity at the boundaries, which would increase the initial pore fluid ions to be flushed out from the system

Self-starting interior permanent magnet motor drive for electric submersible pumps

The interior permanent magnet (IPM) motor drive has evolved as the most energy efficient technology for modern motion control applications. Electric submersible pumps (ESPs) are electric motor driven fluid recovery systems. ESPs are widely used for producing oil and gas from deep downhole reservoirs. Standard ESPs are driven by classical squirrel cage induction motors (IMs) due to its self-starting capability from a balanced 3-phase ac excitation, ruggedness, simplicity, low cost and wide scale availability. Although there has been a tremendous growth in the design and development of highly efficient and reliable IPM motors for traction drive systems, application of the IPM motor technology in ESPs is still in its infancy due to challenges associated with the design and control of IPM motors. In this thesis, a new self-starting, efficient and reliable IPM motor drive technology is proposed for ESP systems to extend their efficiency, longevity and performance. This thesis investigates two different types of self-starting interior permanent magnet (IPM) motors: cage-equipped IPM motors known as line-start IPM motors and a new type of hybrid self-starting motors called hysteresis IPM motors. The limited synchronization capability of line-start IPM motors for high inertial loads is explained in this thesis. To overcome the starting and synchronization problems associated with line-start IPM motors, a new type of hybrid hysteresis IPM motor is proposed in this thesis. Equivalent circuit modeling and finite element analysis of hysteresis IPM motors are carried out in this thesis. A prototype 2.5 kW hysteresis IPM motor is constructed and experimentally tested in the laboratory. In order to limit the inrush current during starting, a stable soft starter has been designed, simulated and implemented for variable speed operations of the motor. The simulation and experimental results are presented and analyzed in this thesis. Self-starting IPM motors suffer from hunting induced torsional oscillations. Electric submersible pumps are vulnerable against sustained hunting and can experience premature failures. In this thesis, a novel stator current signature based diagnostic system for detection of torsional oscillations in IPM motor drives is proposed. The diagnostic system is non-intrusive, fast and suitable for remote condition monitoring of an ESP drive system. Finally, a position sensorless control technique is developed for an IPM motor drive operated from an offshore power supply. The proposed technique can reliably start and stabilize an IPM motor using a back-emf estimation based sensorless controller. The efficacy of the developed sensorless control technique is investigated for a prototype 3-phase, 6-pole, 480V, 10-HP submersible IPM motor drive. In summary, this thesis carried out modeling, analysis and control of different types of self-starting IPM motors to assess their viability for ESP drive systems. Different designs of self-starting IPM motors are presented in this thesis. In future, a fully scalable self-starting IPM motor drive will be designed and manufactured that can meet the industrial demands for high power, highly reliable and super-efficient ESP systems