İstanbul Gelişim Üniversitesi Kurumsal Açık Erişim Arşivi
DSpace@Gelişim, İstanbul Gelişim Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Effect of Different Heat Sink Designs on Thermoelectric Generator System Performance in a Turbocharged Tractor
(MDPI, MDPI AG, Grosspeteranlage 5, CH-4052 BASEL, SWITZERLAND, 2025) Gürcan, Ali; Yakar, Gülay
In this study, the effects of different heat sink designs on the cold side of the modules in a thermoelectric generator (TEG) system placed between the compressor and the intercooler of a turbocharged tractor on the system performance were numerically analyzed. In the current literature, heat sinks used in TEG modules generally consist of plate fins. In this study, by using perforated and slotted fins, the thermal boundary layer behaviors were changed and there was an attempt to increase the heat transfer from the cold surface compared to plate fins. Thus, the performance of the TEG system was also increased. When looking at the literature, it is seen that there are studies which aim to increase the performance of TEG modules by changing the dimensions of p and n type semiconductors. However, there is no study aiming to increase the performance of TEG modules by making changes on the plate fins of the heat sinks used in these modules and thus increasing the heat transfer amount. In this respect, this study offers important results for the literature. According to the numerical analysis results, the total TEG output power, output voltage, and thermal efficiency obtained for S0.5H15 were 6.2%, about 3%, and about 5% higher than those for PF, respectively. In addition, the pressure drop values obtained for different heat sinks, except for aluminum foam, were approximately close to each other. In cases with TEG systems where different heat sinks were used, the intercooler inlet air temperatures decreased by approximately 3.4–3.5% compared to the case without the TEG system. This indicates that the use of TEG will positively affect the improvement in engine efficiency.
Do the United States’fscal decentralization, money supply, and environmental policies promote the clean energy transition?
(SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS, 2025) Haseeb, Mohammad; Hossain, Md. Emran; Hossain, Mohammad Razib; Rehman, Mohd Ziaur; Bekun, Festus Victor
Following the “Glasgow Climate Change Conference (COP26)” in 2021, policymakers pay more light on the role of cleaner fuels in curbing environmental destruction. Despite being the second-largest user of renewable energy, the United States (USA) has not given much attention to the factors that determine “renewable energy consumption (RENC)”. In this milieu, this study considers some unique determinants such as “monetary policy, fscal decentralization, eco-innovation, economic growth, CO2e, the environmental policy stringency index, and economic policy uncertainty” to explore RENC. The current study uses wavelet coherence, as well as partial and multiple wavelet coherence techniques, with quarterly data extending from 1990Q1 to 2020Q4. The wavelet coherence fndings show a signifcant long-and medium-term in-phase connection between RENC, fscal decentralization, and economic growth, whereas money supply shows a signifcant in-phase connection in the medium-term frequency. Besides, increased carbon emissions, environmental policy stringency, and eco-innovation lead to higher RENC in the short-medium term. The analysis of partial and multiple are somewhat like the fndings of wavelet coherence in diferent frequency and time domains. These results have signifcant policy ramifcations for promoting RENC and achieving the “UN Sustainable Development Goals (UNSDGs) 7 (afordable clean energy)”. From a policy lens, the USA should decentralize its fscal policy at the state level, allocating more funds to clean technology research and development. Additionally, sufcient fnancial resources for increasing investment in the renewable energy industry and stricter environmental regulations may increase the usage of clean energy.
Vibration analysis of sandwich beams with nonuniform cross-section made of FGP core and FGM faces resting on Winkler elastic foundation
(TAYLOR & FRANCIS INC, 530 WALNUT STREET, STE 850, PHILADELPHIA, PA 19106, 2025) Aslan, Timuçin Alp; Noori, Ahmad Reshad; Temel, Beytullah; Özer, Asena Pınar
This research proposes the complementary functions method (CFM) and the Laplace transformation to carry out the free vibration frequencies of sandwich beams resting on the Winkler elastic foundation. The beam is assumed to have a variable width and a constant height. The top and bottom faces are made of functionally graded materials (FGM) while the core has a functionally graded porous material (FGPM). The governing equations are canonical ones based on the first-order shear deformation theory. The Laplace transformation is implemented in this set of equations. The transferred equations are solved numerically by reducing them from twopoint boundary value problems to initial value problems via the CFM. The comparison with the available literature shows that the CFM can be used efficiently in the numerical solution of the present class of problems. It is observed that the dependence of the natural frequencies are highly influenced by boundary conditions, spring constants, porosity functions, porosity coefficients, face–core–face layer ratios, length/height ratios, and material gradient index. Notably, as the non-dimensional Winkler spring constants increase, the effect of the material gradient index on the natural frequencies becomes less pronounced.
Machine learning-based estimation of occupational radiation dose in interventional cardiology
(OXFORD UNIV PRESS, GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND, 2025) Hisiroglu, Kevser A.; Toker, Ozan; Toker Özşahin, Melis; İçelli, Orhan
In interventional cardiology, occupational radiation exposure for medical personnel can reach high levels, underscoring the critical need for effective radiation protection and monitoring methods. This study employs machine learning algorithms to estimate radiation doses received by personnel within a virtual 3D angiography room designed to reflect realistic clinical settings. Monte Carlo simulations generated radiation data across various scenarios, accounting for personnel positions, radiation source distance, and exposure angles typical in angiography. The simulation data were used to train five machine-learning algorithms (Gradient Boosting, K-nearest neighbors, Random Forest, Linear Regression, and Decision Tree). Key findings showed that machine learning models, particularly Gradient Boosting, could effectively predict dose levels by utilizing spatial and operational parameters without requiring physical dosemeter. This study provides a framework that could streamline radiation monitoring practices, making dose assessments more accessible and efficient for routine use in clinical environments.
Microbiota awareness of Turkish adults is associated with plant-based dietary patterns
(EMERALD GROUP PUBLISHING LTD, Floor 5, Northspring 21-23 Wellington Street, Leeds, W YORKSHIRE LS1 4DL, ENGLAND, 2025) Kenger, Emre Batuhan; Özlü Karahan, Tuğçe; Bayram, Hatice Merve; Öztürkcan, Seyfettin Arda
Purpose – Knowledge of microbiota and how it affects health can lead individuals to healthier lifestyle choices, such as dietary choices. The purpose of this study was to assess microbiota awareness and investigate its impact on plant-based dietary patterns, which are known to have proven benefits for both the environment and human health. In this study, the authors hypothesized that the microbiota awareness of Turkish adults may affect plant-based dietary patterns. Design/methodology/approach – A cross-sectional study was conducted among 1,676 adults (63.8% women; 27.8 ± 13.0 years) in Turkey between March and May 2023. Data were collected using an online questionnaire that included demographic variables, anthropometric measurements, a validated microbiota awareness scale (64.7 ± 16.8) and a semi-quantitative food frequency questionnaire (FFQ). A plant-based diet index (PDI), a healthy plant-based diet index (hPDI) and an unhealthy plant-based diet index (uPDI) were derived from dietary assessments by a validated semi-quantitative FFQ. Findings – Females had significantly higher microbiota awareness scores than males (67.3 ± 15.7 vs 60.1 ± 17.7, p = 0.001). Microbiota awareness scores of individuals in the second tertile (65.9 ± 15.9) were significantly higher than those in the third tertile of uPDI (59.3 ± 17.9) (p < 0.05). For PDI and hPDI scores, microbiota awareness scores of individuals in the first tertile were significantly lower than in the third tertile. Multivariate linear regression analyses revealed that microbiota awareness was an independent predictor for PDI (β = 0.035, p = 0.002), hPDI (β = 0.141, p = 0.001) and uPDI (β = −0.158, p < 0.001). Originality/value – Considering that awareness of microbiota may result in shifting lifestyle choices such as dietary patterns, further studies are needed to determine the relationship between microbiota awareness and PDI.
