Formation temperature is an important parameter in geothermal drilling since it affects all the components of the system such as drilling fluid, drilling operations and equipment through mud temperatures. The main objective of this study is to estimate the formation temperatures of five geothermal wells in Germencik-&Ouml / merbeyli geothermal field by using inlet and outlet mud temperatures obtained during drilling. For this purpose, GTEMP, a wellbore thermal simulation model is used to simulate the process of drilling and to estimate the formation and bit temperatures of five wells. With the formation and bit temperature estimations of GTEMP and inlet and outlet mud temperature data from field / temperatures vs. depth graphs are plotted for five wells for two cases. In Case 1, cooling tower effect on mud temperatures is neglected whereas in Case 2 it is taken into account. For the estimation of formation temperature of the final depth, Case 2 showed better results with % 1,5-24,5 deviation compared to the % 3,6-25,2 deviation obtained in Case 1.

High greenhouse gas emissions increased the importance of renewable energy resources. Hydropower is among the most widely used type of renewable energy. Oppositions to big hydropower projects with reservoirs increased the use of small hydropower plants. Development of a small hydropower project is a challenging engineering task. Different software&rsquo / s are developed and used to make initial estimations of energy generation and initial costs of the project. RETScreen Clean Energy Analysis Software which can be used worldwide allows the user to estimate initial energy output and costs. In this study, three consecutive hydropower projects (HEPP), namely, Kemer&ccedil / ayir, &Uuml / &ccedil / hanlar and &Uuml / &ccedil / harmanlar HEPP&rsquo / s and four alternative project formulations to these projects are evaluated using RETScreen. The results of the evaluations are compared and best formulation for the projects is identified. In addition to economical profitability, hydropower plants need to be evaluated in terms of their environmental impacts and sustainability aspects. Sustainable development is a fundamental concept of natural resources management. International Hydropower Association prepared the Sustainability Assessment Protocol to evaluate new or existing hydropower facilities with respect to various environmental, social and economic sustainability aspects. The Sustainability Assessment Protocol of IHA is used to evaluate Kemer&ccedil / ayir HEPP. Due to lack of necessary information, rather than conducting a sustainability assessment of a small hydropower project (SHP), necessary information required to conduct such a study is identified.

In recent years the negative effects of tsunamis in the Indian Ocean dramatically increased. Although, this subject became very popular lately, the far-field activities of tsunamis are needed to be evaluated in Indian Ocean. In this thesis, Maldives and Sumatra islands were emphasized to analyze the effects of the transoceanic propagation of tsunamis in Indian Ocean. At first, using GIS Based softwares, the geographical data of the region were extracted and organized for analyzing. Secondly, a worst earthquake scenario was initiated at Sumatra which is located at a long distance from Maldives Islands. Then, corresponding effects of transoceanic tsunami were analyzed and accordingly coastal amplifications near Maldivian Islands were computed by NAMI DANCE. As a final step, an evaluation study was carried out to understand the transoceanic propagation behavior of tsunamis in Indian Ocean and results were discussed.

The most important issue during a tunnel fire is safety of human life. The tunnel fire structural research and investigations have gained more importance in the last decade but studies show variable results depending on the concrete quality and tunnel design fire. For instance, a certain type of concrete with high moisture content can tend to explode in the first 10-15 minutes of fire with rapid increase of heat release rate. A sudden collapse of the tunnel roof during the fire is unacceptable. Especially in Netherlands, the possible sagging of cut and cover tunnel roof is undesired and prevention systems are applied. The main purpose of this research is to investigate fire response of the positive moment region of cut and cover tunnel roof through an experimental and analytical program without use of any protection. In this context a standard one cell rail road cut and cover tunnel has been designed for loads of backfill, lateral earth pressure and self weight. The typical concrete cover used in Turkish railroad tunnels is 6 centimeters. Four pairs of representative sample tunnel roof segments have been manufactured and only one segment out of each pair are tested under 2 hours extreme design tunnel fire in a furnace. Out of these four types, two types have been internally pre-stressed to simulate the internal loads at the positive moment region of the tunnel roof. Four pairs of sample segments are simply supported during the static load test and static load is applied at the mid-span to measure the difference in the post-fire structural performance. Compressive strength of concrete, tensile strength of reinforcing bars, electron microscope evaluation of concrete, moisture content of concrete are recorded during the test program. A finite element based solution is developed to simulate the results of static load tests. Post-fire structural performances of burnt segments are observed to be not much different than the unburnt segments.

A flow duration curve (FDC) defines the relation between the flow amount of any time (daily, yearly, or another time) and its frequency. Moreover, FDCs are used in many water resources projects. However, the ungauged basins or limited amount of gauging in a basin is a common problem. Therefore, regional FDCs are needed to be developed in ungauged basins. Oltu basin has been chosen as the study area, which is located in the north-eastern part of Turkey in &Ccedil / oruh Basin. Two parametric approaches and a statistical approach have been applied to develop regional flow duration curves (FDCs) in Oltu Basin. Parametric approaches cover two different models, namely Model Kocatepe, which is a five parameter model depending on the regression analysis between discharge having certain probability of occurrences and geomorphologic and climatic factors / Model Quimpo, which is a two parameter model proposed by Quimpo. Lognormal distribution has been used in the statistical approach. Several performance indices have been evaluated to decide on if the model dependable or not. As a result of these analysis, it is concluded that, Model Quimpo gives good results in small basins, whereas, Model Kocatepe is effective in large areas. Statistical approach is not an appropriate method to use while regionalizing FDCs in Oltu basin.The analysis performed for short-term duration has revealed that 5-years record lengths of discharges are enough to develop a dependable FDC compared to regional FDC. The validation results and the performance indices are presented with the analysis results.

In this thesis study wind-induced circulation and sediment transport in semi-enclosed basins are carried out for Fethiye Bay. Hydrodynamics of bays are very complex, mainly affected by wind and wave climate, sea bed slope and sediment characteristics. The sea bed profile at the bay changes under winter and summer storms of different speeds and directions. A case study is carried out with the developed methodology. For this reason, Fethiye Bay is selected for the study area. Present structure of Fethiye Bay is determined, sea bed changes since the year 1956 are analyzed. A circulation modeling is applied to the study area. For this purpose, Finite Volume Coastal Ocean Model (FVCOM) numerical model is used. Water exchange and current pattern in the study area for different wind conditions is analyzed. Sediment distribution in the bay is analyzed for different wind directions, river discharges and sediment loads.

The malicious intrusions to computer systems result in the loss of money, time and hidden information which require deployment of intrusion detection systems. Existing intrusion detection methods analyze packet payload to search for certain strings and to match them with a rule database which takes a long time in large size packets. Because of buffer limits, packets may be dropped or the system may stop working due to high CPU load. In this thesis, we investigate signature based intrusion detection with signatures that only depend on the packet header information without payload inspection. To this end, we analyze the well-known DARPA 1998 dataset to manually extract such signatures and construct a new rule set to detect the intrusions. We implement our rule set in a popular intrusion detection software tool, Snort. Furthermore we enhance our rule set with the existing rules of Snort which do not depend on payload inspection. We test our rule set on DARPA data set as well as a new data set that we collect using attack generator tools. Our results show around 30% decrease in detection time with a tolerable decrease in the detection rate. We believe that our method can be used as a complementary component to speed up intrusion detection systems.

The assimilation process to produce daily Snow Water Equivalent (SWE) maps is modified by using Helsinki University of Technology (HUT) snow emission model and AMSR-E passive microwave data. The characteristics of HUT emission model is analyzed in-depth and discussed with respects to the extinction coefficient function. A new extinction coefficient function for the HUT model is proposed for snow over mountainous areas. Performance of the modified model is checked against original and other modified cases against ground truth data covering 2003-2007 winter periods. A new approach to calculate grain size and density is integrated inside the developed data assimilation process. An extensive validation is successfully carried out by means of snow data measured at ground stations during 2008-2010 winter periods. Validation results were less satisfactory for SWE smaller than 75.0 mm and greater than 200.0 mm. Overestimation is especially observed for stations located below 1750.0 m elevation where SWE is less than 75.0 mm. Applied methodology is fine tuned to improve its performance for shallow snow depths observed below 1750 m elevation using a relationship that integrates 10.7 GHz channel data. But an underestimation for SWE greater than 150 mm could not beresolved due to microwave signal saturation that is expected in dense snowpack.

License plate recognition (LPR) technology has great importance for the development of Intelligent Transportation Systems by automatically identifying the vehicles using image processing and pattern recognition techniques. Conventional LPR systems consist of license plate detection (LPD), character segmentation (CS) and character recognition (CR) steps. Successful detection of license plate and character locations have vital role for proper LPR. Most LPD and CS techniques in the literature assume fixed distance and orientation from the vehicle to the imaging system. Hence, application areas of LPR systems using these techniques are limited to stationary platforms. However, installation of LPR systems on mobile platforms is required in many applications and algorithms that are invariant to distance, orientation, and illumination should be developed for this purpose. In this thesis work, a LPD algorithm that is based on multi-scale vertical edge density feature, and a character segmentation algorithm based on local thresholding and connected component analysis operations are proposed. Performance of the proposed algorithm is measured using ground truth positions of the license plate and characters. Algorithm parameters are optimized using recall and precision curves. Proposed techniques for each step give satisfying results for different license plate datasets and algorithm complexity is proper for real-time implementation if optimized.

Feature modeling is a common way of representing commonality and variability in Software Product Lines. There are alternative notations reported in the literature to represent feature models. Compared to the graphical notations, the text-based notations are more amenable to automated processing and tool interoperability. This study presents an XML-based feature modeling language to represent extended feature models that can include complex relationships involving attributes. We first provide a Context Free Grammar for the extended feature model definitions including such complex relationships. Then we build the XML Schema Definitions and present a number of XML instances in accordance with the defined schema. In addition, we discuss a validation process for the validation of the XML instances against the defined schema, which also includes additional tasks such as well-formedness checking for the XML instances.