Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Optimizing Inhibitor Injection in Geothermal Wells With Electrical Submersible Pump(Elsevier Ltd, 2025) Aydin, H.; Tezel, S.I.; Erol, S.Electrical submersible pump (ESP) is a reliable artificial lift method to extend productive lifespan of geothermal wells. In the geothermal industry a common practice involves installing ESPs below the well's flashing depth. This placement approach aims to mitigate the risk of mineral precipitation, which can occur when hot geothermal fluids transition to a two-phase state (liquid and vapor) as pressure decreases. Positioning the pump below the flashing depth also prevents pump's underloading and gas cavitation. The inhibitor injection line usually integrated around the ESP string and installed downstream of the ESP motor. However, this standard practice introduces a challenge regarding inhibitor performance. While this placement ensures effective distribution of inhibitors throughout the production flow, the extended travel time from the surface to the point of application at the ESP can diminish inhibitor effectiveness due to continuous exposure to high temperatures throughout the wellbore. This study proposes relocating the inhibitor injection point within the production tubing closer to the flashing depth. This reduces inhibitor travel time from 108 min to 48 min and has the potential to significantly improve inhibitor effectiveness. Consequently, the implementation of capillary tubing is anticipated to yield annual cost savings per wellbore of approximately USD 10,000, coupled with the mitigation of mineral deposits within the studied well equipped with ESP. To evaluate this approach, a wellbore simulation tool and PHREEQC were employed to dynamically model the pressure and temperature profiles alongside the geochemical evolution of the produced fluids in the wellbore. This modeling approach offers significant value by potentially enabling the optimization of inhibitor usage and reducing the length of required inhibitor injection line. © 2024 Elsevier LtdConference Object Optimizing Integrated Shading Device and Light Shelf for Daylight Performance and Visual Comfort in Architecture Studio(Institute of Electrical and Electronics Engineers Inc., 2024) Avci, P.; Ekici, B.; Kazanasmaz, Z.T.To provide a sustainable interior, it is essential to consider visual comfort and energy efficiency for the occupants' well-being. Daylight is crucial in providing visual comfort while proposing energy-efficient design alternatives. Using daylight as a primary source is one of the most crucial strategies. However, controlling daylight for unwanted situations such as discomfort glare is important. There have been several research studies on daylighting, visual comfort, and shading techniques. Shading devices are façade configurations to control daylight, while light shelves distribute daylight evenly through the space. There are two types of classifications for shading devices: adaptive ones and non-adaptive ones. Numerous research studies have been conducted on daylighting, energy consumption, occupancy performance, and shading systems. Shading technologies, whether adaptive or not, provide benefits and drawbacks. Even though optimizing them is one way to design non-adaptive shading devices, they require minimal maintenance. This study aims to integrate adaptive shading devices and light shelves for university campus buildings to provide lighting design strategies. The aim is to create a study environment that promotes well-being and academic achievement. To pursue this study, three optimization algorithms were run to find the nearly optimal solution. The goal was to both maximize Daylight Autonomy and uniformity values. Results showed that HypE and SPEA2 results discovered near-optimal DA above 75% and uniformity between 0.6 and 0.7. © 2024 IEEE.Book Part Application of Geothermal Energy in Hydrogen Production(Taylor and Francis, 2024) Ayzit, T.; Özmumcu, A.; Baba, A.Compared to other renewable resources, geothermal energy is a low-cost, technically proven, reliable, clean, and safe energy source that has been used in various fields and applications for many decades. These energy sources can be used directly or by conversion to other forms of energy. The use of geothermal energy for various purposes such as electricity, heating, cooling, greenhouses, dry food, thermal tourism, fisheries, and mineral extraction is widespread in many countries. Today’s installed geothermal capacity is dominated by the United States with about 3.7 GW, followed by Indonesia (2.1 GW), the Philippines (1.9 GW), Turkey (1.7 GW), and New Zealand. Global geothermal power generation capacity at the end of 2020 was 15.6 GW. The top ten geothermal producers account for nearly 90% of the global market, and many countries, especially Europe, plan to invest in geothermal soon. Looking at the direct use of geothermal energy for thermal applications, only four countries (China, Turkey, Iceland, and Japan) account for three-quarters of the energy consumed. Hydrogen can provide a number of benefits for future energy systems. Hydrogen can serve as storage for intermittent renewables or provide grid services. It can replace natural gas in industrial heating processes that are otherwise difficult to decarbonise. Therefore, geothermal resources can be used to produce clean hydrogen. Within this section, the importance and use of geothermal energy have been highlighted. At the same time, detailed information is given about the importance of hydrogen, its production, and its use in connection with geothermal energy. © 2025 selection and editorial matter, Mohammad Reza Rahimpour, Mohammad Amin Makarem, and Parvin Kiani.Article A New Discrete Differential Evolution Algorithm Coupled With Simulation–optimization Model for Groundwater Management Problems(Springer Science and Business Media Deutschland GmbH, 2024) Şahin, O.G.; Gurarslan, G.; Gündüz, O.Discrete differential evolution (DDE) is a promising algorithm specifically developed to solve discrete problems. In this study, we aim to apply DDE to groundwater management problems and to compare its performance and discrete space search capabilities with the well-known genetic algorithm (GA) techniques. Local search process was used to enhance the performance of GA algorithm. Metaheuristic algorithms are used for finding location of wells as a hybrid optimization procedure. Two examples from the groundwater management literature were selected to test the performance of the algorithm. The main novelty and objective of this study lie in the comparison of the discrete space search capabilities of the mentioned metaheuristics algorithms using the groundwater management problems. In the first test example, discrete space search performances of algorithms are 15% and 93% for GA and DDE, respectively. In the second test example, DDE exhibited a significantly higher test results (77%) compared to GA (1%). The analysis revealed that GA often prematurely converged and was insufficient to produce the optimum result. DDE reaches the solution considerably faster than the other algorithms. The results showed the superior performance of DDE in the discrete space. As the problem becomes more discrete, the performance of the DDE algorithm in finding the optimum solution increases considerably. Thus, it can be revealed that DDE can also be applied to a wider range of water resource management problems as an effective discrete optimization algorithm. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.Book Part Citation - Scopus: 2Comparative Mapping(CRC Press, 2024) Frary, A.; Doganlar, S.; Ratnaparkhe, M.B.In the mid 1980s, restriction fragment length polymorphism (RFLP) analysis was first applied to plants for the purposes of creating genetic linkage maps. Using the maps developed for major crop species, the genes controlling qualitative and quantitative traits could be detected and then selected for (via closely linked molecular markers) in breeding programs. Advances in DNA marker technology not only allowed the rapid generation of high-resolution plant genetic maps, but also facilitated detailed comparisons among species. When complementary molecular markers are mapped across related species, it is then possible to align the chromosomes of those species to create comparative linkage maps. In this way, genomic similarities between species are revealed so that genetic information about one species may be extended to others and evolutionary inferences drawn. © 2008, CRC Press. All rights reserved.Article Trna Wobble Base Modifications and Boric Acid Resistance in Yeast: Boron-Resistant Deletion Mutants Induce the General Amino Acid Control Mechanism and Activate Boron Efflux(NLM (Medline), 2020) Uluisik, I.; С Karakaya, H.; Koc, A.Boric acid is essential for plants and has many vital roles in animals and microorganisms. However, its high doses are toxic to all organisms. We previously screened yeast deletion collections to identify boric acid-resistant and susceptible mutants to identify genes that play a role in boron tolerance. Here, we analyzed boron resistant mutants (elplΔ, elp3Δ, elp6Δ, ncs2Δ, ncs6Δ and ktil2Δ) for their abilities to modulate the general amino acid control system (GAAC) and to induce boron efflux pump ATR1. The mutants analyzed in this study lack the genes that play roles in tRNA Wobble base modifications. We found that all of the boron resistant mutants activated Gcn4-dependent reporter gene activity and increased the transcript level of the ATR1 gene. Additionally, boron resistant cells accumulated less boric acid in their cytoplasm compared to the wild type cells upon boron exposure. Thus, our findings suggested that loss of wobble base modifications in tRNA leads to GAAC activation and ATR1 induction, which in turn reduced intracellular boron levels and caused boron resistance.Article Citation - WoS: 1Citation - Scopus: 1Completeness of Energy Eigenfunctions for the Reflectionless Potential in Quantum Mechanics(Aip Publishing, 2024) Erman, Fatih; Turgut, O. TeomanThere are a few exactly solvable potentials in quantum mechanics for which the completeness relation of the energy eigenstates can be explicitly verified. In this article, we give an elementary proof that the set of bound (discrete) states together with the scattering (continuum) states of the reflectionless potential form a complete set. We also review a direct and elegant derivation of the energy eigenstates with proper normalization by introducing an analog of the creation and annihilation operators of the harmonic oscillator problem. We further show that, in the case of a single bound state, the corresponding wave function can be found from the knowledge of continuum eigenstates of the system. Finally, completeness is shown by using the even/odd parity eigenstates of the Hamiltonian, which provides another explicit demonstration of a fundamental property of quantum mechanical Hamiltonians.Article Citation - WoS: 3Citation - Scopus: 3Two Decades of Research on Roma in Türkiye: Socioeconomic Exclusion, Identity, and State Policies(Liverpool Univ Press, 2024) Celik, Faika; Uştuk, Ozan; Ustuk, OzanThe scholarly investigation of Roma communities in Turkiye has intensified since the 2000s, largely driven by Turkiye's EU accession candidacy and subsequent adaptation process. This alignment, along with internal developments, prompted governments to prioritize Roma issues, implement projects, and issue action plans. The Roma Civil Society Movement in the 1990s further highlighted Roma challenges, resulting in a diverse body of literature. This study critically examines academic literature to map prevailing trends and thematic foci. Key areas of scholarly engagement include the various dimensions of socio-economic exclusion faced by Roma in education, employment, housing, and health. Additionally, scholars analyze how Roma negotiate and resist pejorative representations, construct their identities, and organize to address contemporary challenges. State policies affecting Roma, from past to present, also receive considerable attention. By critically engaging with this scholarship, the present study highlights significant progress and ongoing challenges in Romani Studies in Turkiye, offering insights into future research directions.Article Citation - WoS: 7Citation - Scopus: 7Bond-Based Peridynamic Fatigue Analysis of Ductile Materials With Neuber's Plasticity Correction(Springer, 2024) Altay, Ugur; Dorduncu, Mehmet; Kadioglu, Suat; Madenci, ErdoganThis study introduces an approach for performing bond-based (BB) peridynamic (PD) fatigue analysis of ductile materials. Existing BB PD fatigue models do not account for the effect of plastic deformation. The current approach addresses this by incorporating Neuber's plasticity correction concept into the fatigue model. Neuber's correction adjusts the stress and strain predictions of the PD elastic solution to account for local plastic deformation around crack tips. The PD fatigue simulations demonstrate the effectiveness of this method and improvements in fatigue life predictions by considering local plasticity effects. The numerical results first examine the response of a ductile plate without a crack under quasi-static monotonic loading. Subsequently, specimens exhibiting Mode I and mixed-mode crack propagation paths due to cyclic loading are analyzed. The PD predictions accurately capture the test data. Additionally, the model specifically investigates the effect of a stop hole on fatigue life.Article Citation - WoS: 4Citation - Scopus: 5Diffusion-Based Data Augmentation Methodology for Improved Performance in Ocular Disease Diagnosis Using Retinography Images(Springer Heidelberg, 2024) Aktas, Burak; Ates, Doga Deniz; Duzyel, Okan; Gumus, AbdurrahmanDeep learning models, integral components of contemporary technological landscapes, exhibit enhanced learning capabilities with larger datasets. Traditional data augmentation techniques, while effective in generating new data, have limitations, especially in fields like ocular disease diagnosis. In response, alternative augmentation approaches, including the utilization of generative AI, have emerged. In our study, we employed a diffusion-based model (Stable Diffusion) to synthesize data by faithfully recreating crucial vascular structures in the retina, vital for detecting eye diseases by using the Ocular Disease Intelligent Recognition dataset. Our goal was to augment retinography images for ocular disease diagnosis using diffusion-based models, optimizing the outputs of the fine-tuned Stable Diffusion model, and ensuring the generated data closely resembles real-world scenarios. This strategic approach resulted in improved performance in classification models and augmentation outperformed traditional methods, exhibiting high precision rates ranging from 85% to 76.2% and recall values of 86%, and 75% for 5 classes. Beyond performance enhancement, we demonstrated that the inclusion of synthetic data, coupled with data reduction using the t-SNE method, effectively addressed dataset imbalance. As a result of synthetic data addition, notable increases of 3.4% in the precision metric and 12.8% in the recall metric were observed in the 7-class case. Strategically synthesizing data addressed underrepresented classes, creating a balanced dataset for comprehensive model learning. Surpassing performance improvements, this approach underscores synthetic data's ability to overcome the limitations of traditional methods, particularly in sensitive medical domains like ocular disease diagnosis, ensuring accurate classification. The codes of the study will be shared on GitHub in a way that benefits everyone interested: https://github.com/miralab-ai/generative-data-augmentation.