9
Archived Theses
0
DOIs Assigned
0%
DOI Rate
Discipline
Çimento harçlarında ahşap atık kullanımı
It is a well-known fact that CO2 emission generated during cement manufacturing is threatening the global pollution. Since concrete is the second most consumed substance on Earth after water, it is not surprising that a cement industry accounts for around 5 percent of global carbon dioxide emissions itself. Generation of all kinds of wastes is another alarming matter in terms of the environment and health. This study addresses the influence of the use of wood waste on the fresh and hardened properties of cement mortars. Wood wastes used in this study were in the form of wood powder and wood fibre. Physical characterisation namely X-Ray Fluorescence as well as particle size distribution were performed in this thesis. Mechanical properties such as compressive and flexural strength as well as porosity and permeability of cement mortars combined wood wastes were measured. Resistance to freeze and thaw of these mortars are also examined in the thesis. Experimental results have shown that inclusion of wood wastes in cement mortars enhances the mechanical properties of these mortars. Durability characteristics of these mortars were also found to be improved when wood waste is used as substitution material. Combining waste wood in cement mortars have also found to positively influence the cost efficiency of these mortars. The results reported in the thesis do not only provide a more sustainable development of cement-based materials for construction practices but also suggest an approach for the waste management scheme to be recognised particularly for the undeveloped countries.
Işık soğuran silicon-karbon nanotüp tabanlı meta malzemelerin elektro-optik özellikleri üzerindeki mekanik etkilerin incelenmesi
The use of metamaterial (MTM) technology has been popular recently due to having extensive range of applications and being a promising field of interest. MTMs are commonly used in medical, energy, and military fields. Solar photovoltaics (PV) is one of the fields that MTMs are used in order to increase the generated energy. In this thesis, three silicon-carbon nanotube (Si-CNT) based MTM absorbers are proposed and the effect of mechanical bending stresses on the electro-optical properties of three proposed designs are investigated within the frequency range of 400 THz to 1200 THz (Visible and Ultraviolet). The proposed absorbers consist of three layers, namely: resonators, substrate, and ground plate. The resonators and ground plate are made of aluminum whereas the substrate is made of silicon-carbon nanotube composite with 5% CNT. According to the simulation results, at least 72% of solar radiation is absorbed among three absorbers. Moreover, resonance frequency shifts, dual-band frequency response, and increase in absorption rates are observed when bending deformations are applied to the proposed absorbers.
Geliştirilmiş Petrol Çıkarma Amacıyla Güneş Enerjisiyle Buhar Üretme Uygulamasının Fizibilitesini Değerlendirmek İçin Bir Tarama Aracının Geliştirilmesi
Enhanced oil recovery (EOR) involves the implementation of various techniques for increasing oil recovery, which typically involves injection of an agent that help to increase the oil flow. Steam injection is a common method to increase the recovery from heavy-oil reservoirs, which contain oil that has very high viscosity that may not be produced at economic rates due to inability to flow by viscous forces. Using concentrating solar power (CSP) as a renewable-energy system is one means to attain this objective, with a reduction in CO2 emissions and fuel usage in generating steam, and could be at a lower cost than burning natural gas. The objective of this study to develop a coupled solar-energy/steam-injection forecasting tool to understand the impact of certain designs and natural parameters on the process. The study would use an existing data driven screening tool (artificial neural network), trained with numerical-simulation results, to optimize the steam-injection efficiency. Then solar-energy and steam-injection models, are going to be integrated so that both models can communicate. In the entirety of the project, economic indicators such as steam cost, capital investments for solar system would be reflected amongst other operational parameters to present a more realistic analysis. Finally, integrated models will be organized in a graphical-user-interface (GUI) input/output type application to convert the coupled models into a user-friendly screening tool, easy to use and understand by an investor or an engineer.
ODTÜ KKK'deki güneş fotovoltaik santralinin uzun vadeli enerji verimi tahmini
Installing large scales of solar energy introduces some financial risks for the investors since the solar resource is variable. Thus, a long-term energy yield estimation is needed to see the variability of the solar resource. This study aims to see the relation between long-term trends of global horizontal irradiation (GHI) with the energy yield and the levelized cost of electricity (LCOE). Probability of exceedance (POE) values were found to assess the bankability of installing a solar PV power plant. Different datasets, such as typical meteorological year (TMY), satellite-based and ground-measured data, were used. Quality assessment was done to check the accuracy of ground-measured data using quality control tests. Erroneous GHI data was estimated using the Erbs model. Global tilted irradiation (GTI) was also estimated using the isotropic sky-diffuse model, and it was compared with measured GTI. The interannual variability of GHI was found as 5.94% and 2.21% for ground-measured and satellite-based data, respectively. The comparison of TMY and P50 values showed that TMY datasets underpredicted the annual GHI by about 5.15% and the energy yield by about 6.83% on average. When Normal distribution was compared with the empirical method, the P50 value was underpredicted by 0.93% for energy yield, whereas, Normal cumulative distribution function (CDF) overpredicted P90 value than the empirical CDF 3.93%. Doing stochastic simulations resulted in the highest POE values: P50 and P90 values increased by 3.30% and 6.10%, respectively, compared to the empirical method. Moreover, while the range of energy yield increased to about 1500-2000 kWh/kWp, LCOE range increased to 0.05-0.19 $/kWh in stochastic simulations. As the overall uncertainty of energy yield was found as about 7.08%, it can be further reduced by searching for other sources of error such as temperature and soiling.
Kuzey Kıbrıs için yağmur suyu hasadı analizi
Rainwater harvesting is a sustainable water resources management technique to harvest, store and reuse rainwater through rainwater harvesting systems (RWHSs). This study aims to determine the optimum rainwater storage (RWS) tank size of a RWHS to minimize the cost of water supplied from the utility network, wastewater cost and the RWS tank cost to attain the maximum financial benefit and analyze the rainwater harvesting potential for Northern Cyprus. A Linear Programming (LP) model is developed to achieve this aim. The LP model considers the daily precipitation data, the collector area at the roof of the building, the water consumption per capita, the number of residents, the unit water cost, the unit wastewater cost, the unit cost of the RWS tank and the discount rate as inputs. This model is applied to 33 case study locations (CSLs) selected from semi-arid Northern Cyprus, Cyprus Island, Eastern Mediterranean. Results show that the RWHS investment is financially feasible for almost one-third of the CSLs investigated. The optimum RWS tank sizes at the CSLs are calculated to range from 1.6 m3 to 3.2 m3. The financial benefit and the RWS tank size's sensitivity to the number of residents, the collector area, the discount rate, the daily average water consumption per capita and the RWS tank unit cost are further analyzed. Sensitivity analysis results show that the utilization of accurate parameters in the LP model is necessary because the change in the parameters affects the optimum RWS tank size and the net financial benefit of the RWHS considerably. From the environmental point of view, a total annual CO2 equivalent emission of 444 ton/year, a total annual social carbon cost of nearly 150,000 TL/year (i.e., $18,750/year) and a total annual electrical energy generation cost of 640,000 TL/year (i.e., $80,000/year), resulting from Turkey – Northern Cyprus Water Supply Project, can be avoided if RWHSs are implemented at Girne, Mağusa, İskele and Lefke.
Marka ilkinlemesinin sürdürülebilir tüketim tutum ve davranışları üzerindeki etkisi
Research on factors affecting sustainable consumption tends to focus on enduring factors like personality traits, value orientations, and demographics. Little research has examined situational factors, such as marketing stimuli, which may promote or inhibit sustainable consumption. The present research attempts to understand how brand priming affects sustainable consumption attitudes and behaviors. Priming is a term that describes how a given unconscious stimulus affects subsequent psychological states and behaviors, such as decision-making. Within this scope, brand priming deals with how mere exposure to a brand can elicit behavioral changes and attitudes in response to the brand exposure. Effects of brand priming on various consumption behaviors have been examined; however, there is no research examining the effects of brand priming on sustainable consumer attitudes and behaviors. This research attempts to fill this gap by conducting two experiments. In the first experiment, subjects were primed with a luxury brand concept to test whether materialistic values could be activated and, in turn, affect sustainable consumption attitudes and behaviors. In the second experiment, subjects were primed with a sustainability positioned brand information to test whether altruistic values could be activated and, in turn, affect sustainable consumption attitudes and behaviors. The first experiment demonstrated that priming with luxury brands activated materialistic values, which decreased sustainable consumption attitudes and behaviors. The second experiment demonstrated that priming with a sustainability positioned brand concept activated altruistic values, which increased sustainable consumption attitudes and behaviors. Implications of these results for theory and practice, as well directions for future research are discussed.
Kuzey Kıbrıs yıllık yağışlarının zaman serisi modellemesi ve kuraklık frekans analizi
Cyprus which is the third biggest island in the Mediterranean Sea is located in the south of Turkey. The island has a semi-arid climate The rainfall is the main source of the island, therefore, the analysis of existing rainfall data across the island has vital importance for a better sustainable water resource management. In this study, annual rainfall data of 33 meteorological stations across North Cyprus were used. The main objectives of the study are modeling the annual observed rainfall of North Cyprus by using ARIMA models and finding the return period of the most critical historical drought events by using ARIMA models. As a result, low order ARIMA models were generally found suitable for North Cyprus annual rainfall data. Also, for average annual North Cyprus rainfall, the return period of the most severe drought event with severity of 406.3 mm, was found as 63 years. For the four sub-regions of North Cyprus namely, the West part of North Cyprus, North Coast and Mesaria Plain, Central Mesaria Plain, and West Coast and Karpas Peninsula, the return periods of the most severe droughts with the severity of 572.4 mm, 319.5 mm, 319.8 mm, and 555.1 mm, were obtained as 137 years, 26 years, 40 years, and 116 years, respectively. These results will be very beneficial for the sustainable water resource management of North Cyprus. Important precautions can be taken to minimize the devastating effects of climate change by the related government authorities.
Derin öğrenme algoritmaları kullanarak küresel yatay ışınlamanın çok değişkenli tahmini
Increasing photovoltaic (PV) panel instalments jeopardise the electrical grid frequency, especially in island countries, such as Cyprus. For a continuous growth in the PV instalments in Northern Cyprus as well as minimal usage of conventional energy sources in power generation, it is of utter importance for a grid manager to possess information on the energy production of PV panels, hence knowledge on received radiation, i.e. Global Horizontal Irradiation (GHI). Therefore, the prediction of GHI plays an essential role in the growth of renewable energy in Northern Cyprus. This study focuses on forecasting long-term and short-term GHI for Kalkanlı, Northern Cyprus. For long-term forecasting, a dataset is obtained from NASA while the short-term GHI prediction is carried out with a dataset recorded at METU NCC. Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) algorithms are employed for the long-term GHI forecasting. Support Vector Regression (SVR) is employed in addition to CNN and LSTM algorithms in the short-term GHI estimation. For both datasets, hybrid and stand-alone models are constructed, and their performances evaluated extensively. Additionally, seasonal forecasting is carried out for the short-term GHI estimation with a hybrid model of CNN, LSTM and SVR.
Deniz sondajı kuyu patlamalarının olasılık bazlı risk değerlendirmesi
A blowout is the eruption of underground reservoir fluids to the surface during drilling operations. This has devastating results, which are described by the serious impact on human health, environmental problems, and economic loss. Blowout events are unpredictable due to uncertainty of how they evolve. Blowout risk usually lies with parts of the safety system that are expected to function fully, and prevent blowouts. Fault Tree Analysis (FTA) is a graphical method offering a way to identify Causal Factors (CF) of the safety system failure, and to evaluate the contribution level of each event to blowout. In this study, an FTA model for offshore blowout probability is mapped to a Bayesian Network (BN). This BN-based model is utilized for Probabilistic Risk Assessment (PRA) of hazards, accounting for uncertainty in both safety system failure rates and subsurface formation pressures. To the best of our knowledge, this is the first time all of the commonly encountered safety barriers are combined in a single PRA analysis. The PRA is performed using importance measures of FTA roots. According to results herein, the blowout event is attributed mostly to human error in monitoring safety barriers. Also, blowout events are highly probable due to inability to precisely identify abnormal subsurface pressure zones. Finally, casing failure is found to be the third significant contributor to blowout.