Sweep Frequency Response (SFR) measurement on a transformer is a low voltage, offline exercise. So, it virtually permits determination of any network or system function, by imposing any desired terminal condition for the nontested windings and terminals. The terminal conditions employed have significant influence on the achievable fault detection ability, and maximizing this ability should obviously be one of the main aims of frequency response measurements. Simply stated, this requirement translates to the ability to identify/measure as many natural frequencies as possible. However, there is a practical limitation that not all system functions can exhibit all natural frequencies. Hence, it is necessary to determine the most appropriate combination of terminal connection and system function for achieving this objective. The growing popularity of SFR measurements has led to a new IEEE Guide. This document (IEEE Std PC57.149TM/D1) on SFR measurement lists out most of the possible terminal connections and system functions, for both 1φ and 3φ transformers. Surprisingly, it does not identify and recommend any one of them as preferred for maximizing this objective. Initially, considering the high frequency equivalent circuit representation of a 1φ, twowinding transformer, system function for different terminal conditions were computed. Depending on the number of natural frequencies distinguishable in the amplitude frequency response of a system function, each measuring condition was ranked. Thus, it led to identification of the best configuration. Later, these findings were verified on an actual 1φ, two-winding transformer. However, 3φ transformers are quite different in construction compared to 1φ transformers. So, whether the same configuration would also be applicable for SFR measurements on 3φ transformers had to be ascertained. So, the study was next extended to 3φ transformers. Performance of best configuration identified during this investigation are compared with currently employed low-voltage impulse test (used during short-circuit testing of transformers) and currently practiced SFR measurement test conditions, and found to be better. In conclusion, it is believed that after adequate field verifications, the identified configuration can be declared as the preferred way of making SFR measurement on transformers.

Foam-assisted low interfacial tension and foam-improved sweep efficiency are attractive enhanced oil recovery (EOR) methods with numerous studies and researches have been conducted in the past few decades. For example, CO₂-Enhanced Oil Recovery (CO₂-EOR) is very efficient in terms of oil displacement. However, due to the low viscosity of super critical CO₂, the process usually suffers from poor sweep efficiency. One method of increasing sweep efficiency in CO₂-EOR has been identified through the use of surfactants to create "foams" or more correctly CO₂-in-water (C/W) macroemulsions. Polymer flooding techniques such as Alkali -- Polymer (AP), Surfactant -- Polymer (SP), and Alkali -- Surfactant -- Polymer (ASP) have been the only proven chemical EOR method in sandstone reservoirs with many successful pilot tests and field projects. However, the use of polymer is limited in carbonates due to unfavorable conditions related to natural characteristics of this type of lithology. In this case, foam-assisted EOR, specifically Alkali -- Surfactant -- Gas (ASG) process, can be an alternative for polymer flooding. It is a fact that large amount of the world's oil reserves resides in carbonate reservoirs. Therefore, an increase in oil recovery from carbonates would help meet the world's increasing energy demand. This study consists of two parts: (1) the development of new surfactant for creating CO₂ -- in -- water macroemulsions for improving sweep efficiency in CO₂ -- EOR processes; (2) systematic study of ASG method as a novel EOR technique and an alternative for polymer flooding in carbonate reservoirs. Both studies are related to the use of foam as a mobility control agent. In the first part, the design and synthesis of twin tailed surfactants for use at the CO₂/water interface is discussed. The hydrohobes for these surfactants are synthesized from epichlorohydrin and an excess alcohol. Subsequent ethoxylation of the resulting symmetrical dialkyl glycerin yields the water soluble dual tailed surfactants. The general characteristics of these surfactants in water are described. A comparison is carried out between twin-tailed dioctylglycerine surfactants and linear secondary alcohol surfactant based on results from a core flood. The results show that even above the cloud point of the surfactants, the twin tailed surfactants create a significant mobility reduction, likely due to favorable partitioning into the CO₂ phase. The data covers surfactant structures designed specifically for the CO₂-water interface and can be used by producers and service companies in designing new CO₂-floods, especially in areas that might not have been considered due to problems with reservoir heterogeneity. Second part contains a systematic study of ASG process on carbonate rocks through a series of experiments. The purpose is to demonstrate the performance as well as the potential of ASG as a new EOR technique. In this study, basic concepts in chemical EOR are presented, while the design of chemical formulation, phase behavior, and the role of foam are discussed in details. Experimental results showed relatively good recovery, low surfactant retention. However, pressure drop during chemical injections were high, which indicates the formation of both strong foam and viscous microemulsion at the displacement front when surfactant starts solubilizing oil. Overall, ASG showed good performance on carbonate rocks. Optimization can be made on surfactant formula to form less viscous microemulsion and therefore improve efficiency of the process. / text

Continuous and discrete-time Successive Backward Sweep (SBS) methods for solving nonlinear optimal control problems involving terminal and control constraints are proposed in this dissertation. They closely resemble the Neighboring Extremals and Differential Dynamic Programming algorithms, which are based on the successive solutions to a series of linear control problems with quadratic performance indices. The SBS methods are relatively insensitive to the initial guesses of the state and control histories, which are not required to satisfy the system dynamics. Hessian modifications are utilized, especially for non-convex problems, to avoid singularities during the backward integration of the gain equations. The SBS method requires the satisfaction of the Jacobi no-conjugate point condition and hence, produces optimal solutions. The standard implementation of the SBS method for continuous-time systems incurs terminal boundary condition errors due to an algorithmic singularity as well as numerical inaccuracies in the computation of the gain matrices. Alternatives for boundary error reduction are proposed, notably the aiming point and the switching between two forms of the sweep expansion formulae. Modification of the sweep formula expands the domain of convergence of the SBS method and allows for a rigorous testing for the existence of conjugate points. Numerical accuracy of the continuous-time formulation of the optimal control problem can be improved with the use of symplectic integrators, which generally are implicit schemes in time. A time-explicit group preserving method based on the Magnus series representation of the state transition is implemented in the SBS setting and is shown to outperform a non-symplectic integrator of the same order. Discrete-time formulations of the optimal control problem, directly accounting for a specific time-stepping method, lead to consistent systems of equations, whose solutions satisfy the boundary conditions of the discretized problem accurately. In this regard, the second-order, implicit mid-point averaging scheme, a symplectic integrator, is adapted for use with the SBS method. The performance of the mid-point averaging scheme is compared with other methods of equal and higher-order non-symplectic schemes to show its advantages. The SBS method is augmented with a homotopy- continuation procedure to isolate and regulate certain nonlinear effects for difficult problems, in order to extend its domain of convergence. The discrete-time SBS method is also extended to solve problems where the controls are approximated to be impulsive and to handle waypoint constraints as well. A variety of highly nonlinear optimal control problems involving orbit transfer, atmospheric reentry, and the restricted three-body problem are treated to demonstrate the performance of the methods developed in this dissertation.

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In wireless sensor network, we usually need to combine the information gathered from multiple sensors to detect an event. To answer this question we present a new type of query, Geo-Range query. This query reports the geographic points where the average value of nearby sensors are greater than certain threshold. To perform this query, we developed two fast, efficient algorithms. The Brute-Force algorithm use exhaustive method to enumerate all possible values, which takes O(n^3) running time. The Sweep-Line algorithm applies a conceptual line sweeping through the plane. The sweep-line moves through the plane and keeps tracking all the sensor points encountered. The algorithm takes O( n^2 \log n ) running time, while it still gives exact solution to the problem. We implement and simulate our algorithms in Visual Basic.Net.

This research investigates an extension of the glancing angle deposition (GLAD) technique and a biosensing application of films produced by GLAD. The extension to GLAD, called phi-sweep (PS), improves column isolation compared to films grown by traditional GLAD (TG) as well as modifies the column tilt angle, , of the slanted columns according to tan(_{PS}) = tan(_{TG}) cos(), where is the sweep angle. The biosensing application makes use of localized surface plasmon resonance in noble metal GLAD films functionalized with rabbit immunoglobulin G (rIgG) to detect binding of anti-rabbit immunoglobulin G (anti-rIgG) to the films' surface. The extinction peak red-shifts a distance dependent on the concentration of anti-rIgG solution in a manner described by the Langmuir isotherm with a saturation value, _{max}, of 29.4 0.7 nm and a surface confined thermodynamic binding constant, K, of (2.7 0.3)10 M. / Microsystems and Nanodevices

Les phénotypes complexes observés dans les populations humaines contemporaines sont déterminés par la génétique, ainsi que par des facteurs environnementaux. Par exemple, la nutrition et les modes de vie jouent un rôle important dans le développement de maladies multifactorielles, comme l'obésité ou le diabète. L'adaptation sur de tels traits phénotypiques complexes survient généralement sous la forme de modification des fréquences alléliques à de multiple locus, un phénomène nommé sélection polygénique. Les avancées récentes des méthodes statistiques, ainsi que l'émergence des données issues du séquençage haut-débit permettent dorénavant la détection de ces signaux. Ici, nous visons à comprendre à quel point des changements environnementaux peuvent entraîner des modifications dans les pressions sélectives, ainsi que leurs impacts sur la sensibilité aux maladies. Dans ce but, nous proposons une analyse d'enrichissement en groupes de gènes (GSEA, Gene Set Enrichment Analysis) en utilisant des données de scores de sélection sur du polymorphisme nucléotidique (SNP, Single Nucleotide Polymorphism), pour quantifier la pression de sélection sur ces SNP (qui pourrait issus par exemple de méthodes de scan génomique). D'abord, nous effectuons une analyse de sensibilité des méthodes de scan génomique pour examiner leur exactitude. Nous utilisons une analyse par simulation pour étudier leurs performances sous un large éventail de scénarios démographiques complexes et des hypothèses de balayage sélectif fort (hard sweep) ou faible (soft sweep). Ensuite, nous développons SEL-GSEA, un outil utilisant des données de SNP pour identifier des voies biochimiques enrichies en pressions sélectives. Enfin, dans l'optique d'examiner les effets de potentiels changements environnementaux qui pourraient représenter des changements dans les pressions sélectives, nous utilisons SEL-GSEA et Gowinda (un outil disponible en ligne) lors d'une étude population-centrée. Nous analysons trois différentes populations (africains, européens et asiatiques) de la base de données HapMap. Pour obtenir les scores de sélection des SNP qui servent de base à SEL-GSEA, nous utilisons une combinaison de deux méthodes (iHS et XP-CLR) qui sont les plus performantes dans notre analyse de sensibilité. Les résultats de notre analyse montrent une forte pression de sélection sur les voies biochimiques liées à l'immunité, principalement en Afrique, ainsi que sur la glycolyse et la néoglucogenèse en Europe, qui sont des voies liées au métabolisme et au diabète. / The complex phenotypes observed nowadays in human populations are determined by genetic as well as environmental factors. For example, nutrition and lifestyle play important roles in the development of multifactorial diseases such as obesity and diabetes. Adaptation on such complex phenotypic traits may occur via allele frequency shifts at multiple loci, a phenomenon known as polygenic selection. Recent advances in statistical approaches and the emergence of high throughput Next Generation Sequencing data has enabled the detection of such signals. Here we aim to understand the extent to which environmental changes lead to shifts in selective pressures as well as the impact of those on disease susceptibility. To achieve that, we propose a gene set enrichment analysis using SNP selection scores that are simply scores that quantify the selection pressure on SNPs and they could be derived from genome-scan methods. Initially we carry out a sensitivity analysis to investigate which of the recent genome-scan methods identify accurately the selected region. A simulation approach was used to assess their performance under a wide range of complex demographic structures under both hard and soft selective sweeps. Then, we develop SEL-GSEA, a tool to identify pathways enriched for evolutionary pressures, which is based on SNP data. Finally, to examine the effect of potential environmental changes that could represent changes in selection pressures, we apply SEL-GSEA as well as Gowinda, an available online tool, on a population-based study. We analyzed three populations (Africans, Europeans and Asians) from the HapMap database. To acquire the SNP selection scores that are the basis for SEL-GSEA, we used a combination of two genome scan methods (iHS and XPCLR) that performed the best in our sensitivity analysis. The results of our analysis show extensive selection pressures on immune related pathways mainly in Africa population as well as on the glycolysis and gluconeogenesis pathway in Europeans, which is related to metabolism and diabetes.

This thesis deals with the adjustment of the current distribution routes of the company CHEMIE STAR Ltd. and at the same time with a creating of new distribution routes with the aim of economic savings, which is achieved through a reduction in the length of routes and the time required for the routes. In the introductory theoretical part of the work the logistics is defined, its functions, importance and influence on the enterprise. And this part also provides an overview of methods dealing with the traveling salesman problem. In the practical part the optimization of the input data into the model at the current routes is performed, where there is always selected the cheapest route between the two nodes using unit costs. Subsequently, the methods solving the traveling salesman problem are applied, namely the method of the Nearest neighbor, Vogel approximation method and Clark-Wright method. The layout of the new routes, which is limited in capacity by car and the purchasers requirements, is done using Mayer method and Sweep algorithm and with the subsequent application of the method solving the problem of traveling salesman problem. In the chapter evaluation of the results and recommendation all obtained outcomes are compared and interpreted.

abstract: Modern aircraft are expected to fly faster and more efficiently than their predecessors. To improve aerodynamic efficiency, designers must carefully consider and handle shock wave formation. Presently, many designers utilize computationally heavy optimization methods to design wings. While these methods may work, they do not provide insight. This thesis aims to better understand fundamental methods that govern wing design. In order to further understand the flow in the transonic regime, this work revisits the Transonic Similarity Rule. This rule postulates an equivalent incompressible geometry to any high speed geometry in flight and postulates a “stretching” analogy. This thesis utilizes panel methods and Computational Fluid Dynamics (CFD) to show that the “stretching” analogy is incorrect, but instead the flow is transformed by a nonlinear “scaling” of the flow velocity. This work also presents data to show the discrepancies between many famous authors in deriving the accurate Critical Pressure Coefficient (Cp*) equation for both swept and unswept wing sections. The final work of the thesis aims to identify the correct predictive methods for the Critical Pressure Coefficient. / Dissertation/Thesis / Masters Thesis Aerospace Engineering 2016