Electromagnetic interference (EMI) is one of the most common problems encountered in microwave applications. Interaction of electromagnetic (EM) waves from different sources may result in device malfunction due to misinterpretation of the transferred data or information loss. On the other hand, development of materials with reduced radar detectability is desired in defense applications. Considering the limitations in weight and thickness, development of lightweight structural materials with enhanced electromagnetic absorption potential is needed. In this study, development and characterization of glass fiber-reinforced polymer (GFRP) composite materials to be used in EM wave absorbing or EMI shielding applications was aimed. Incorporation of electromagnetic wave absorption characteristic has been achieved by the application of conductive thin film on fiber glass woven fabric reinforcement layers. Characterization of EM wave absorption potential was conducted using &ldquo / free-space method&rdquo / in 18 &ndash / 27 GHz frequency range. Single and multilayered combinations of surface-modified fiber glass woven fabrics were characterized in terms of their EM wave interaction properties and design principles for efficient broadband EM wave absorbing multilayered GFRP composite material have been presented. A computer aided computation method has also developed in order to predict EM wave transmission, reflection, and hence absorption characteristics of multilayered structures from single layer properties. Estimated results were verified compared to free-space measurement results. In the current study, up to 85% electromagnetic wave absorption has been obtained within 18-27 GHz frequency range (K band). Enhancement of EM wave absorption potential of multilayer structure has also been demonstrated by computer aided computation.

In general, a common reference architecture can be derived for Software as a Service (SaaS) architecture. However, while designing particular applications one may derive various different application design alternatives from the same reference SaaS architecture specification. To meet the required functional and nonfunctional requirements of different enterprise applications it is important to model the possible design so that a feasible alternative can be defined. In this thesis, we propose a systematic approach and the corresponding tool support for guiding the design of the SaaS application architecture. The approach defines a SaaS reference architecture, a family feature model and a set of reference design rules. Based on the business requirements an application feature model is defined using the family feature model. Selected features are related to design decisions and a SaaS application architecture design is derived. By defining multiple application architectures based on different application feature models we can even compare multiple alternatives and based on this select the most feasible alternative.

Sensitive devices are affected by extreme vibration excitations during operation so require isolation from high levels of vibration excitations. When these excitation characteristics of the devices are well known, the vibration isolation can be achieved accurately. However, it is possible to have expected profile information of the excitations with respect to frequency. Therefore, it is practical and useful to implement this information in the design process for vibration isolation. In this thesis, passive vibration isolation technique is examined and a computer code is developed which would assist the isolator selection process. Several sample cases in six degree of freedom are designed for a sample excitation and for sample assumptions defined for an inertial measurement unit. Different optimization methods for design optimizations are initially compared and then different designs are arranged according to the optimization results using isolators from catalogues for these sample cases. In the next step, the probable designs are compared according to their isolator characteristics. Finally, one of these designs are selected for each case, taking into account both the probable location deviations and property deviations of isolators.

This study focused on using magnetic sensors for localization and identification of targets with a wireless sensor network (WSN). A wireless sensor network with MICAz motes was set up utilizing a centralized tree-based system. The MTS310, which is equipped with a 2-axis magnetic sensor was used as the sensor board on MICAz motes. The use of magnetic sensors in wireless sensor networks is a topic that has gained limited attention in comparison to that of other sensors. Research has generally focused on the detection of large ferromagnetic targets (e.g., cars and airplanes). Moreover, the changes in the magnetic field intensity measured by the sensor have been used to obtain simple information, such as target direction or whether or not the target has passed a certain point. This work aims at understanding the sensing limitations of magnetic sensors by considering small-scale targets moving within a 30 cm radius. Four heavy iron bars were used as test targets in this study. Target detection, identification and sequential localization were accomplished using the Minimum Euclidean Distance (MED) method. The results show the accuracy of this method for this job. Different forms of sensor sensing region discretization were considered. Target identification was done on the boundaries of sensing regions. Different gateways were selected as entrance point for identification point and the results of them were compared with each other. An online ILS system was implemented and continuous movements of the ferromagnetic objects were monitored. The undesirable factors which affect the measurements were discussed and techniques to reduce or eliminate faulty measurements are presented. A magnetic sensor orientation detector and set/reset strap have been designed and fabricated. Orthogonal Matching Pursuit (OMP) algorithm was proposed for multiple sensors multiple target case in ILS systems as a future work. This study can then be used to design energy-efficient, intelligent magnetic sensor networks

A computer program has been written to perform production optimization in submersible pump lifted wells.Production optimization was achieved by the principles of Nodal Analysis Technique which was applied between the reservoir and the wellhead ignoring the surface choke and separator.computer program has been written according to two lifting environment,which are:pumping with only liquid,pumping with both liquid and gas.