Browsing by Author "Yapici, Ekin Ozgirgin"

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Citation - WoS: 1
Citation - Scopus: 1
Analysıs Of Heat Transfer Enhancement In Tubes Wıth Capsule Dımpled Surfaces And Al2o3-Water Nanofluıd
(Turkish Soc thermal Sciences Technology, 2022) Yapici, Ekin Ozgirgin; Türkoğlu, Haşmet; Ibrahim, Mahmoud Awni A. Haj; Turkoglu, Hasmet; 31329
This study aims to numerically investigate and evaluate the enhancement of heat transfer by new capsule dimples on tube surfaces for flow of water and Al2O3-water nanofluid with different concentrations, under uniform surface heat flux. The originality of this work lies in combining two passive heat transfer enhancement methods such as geometrical improvements and nanofluids together. Capsule dimples with different depths were considered. Al2O3- water nanofluid was modeled as a single-phase flow based on the mixture properties. The effects of dimple depth and nanoparticle concentrations on Nusselt number, friction factor and performance evaluation criteria (PEC) were studied. Numerical computations were performed using ANSYS Fluent commercial software for 2000-14000 Reynolds number range. It was found that when laminar, transient and fully developed turbulent flow cases are considered, increase in the dimple depth increases the Nusselt number and friction factor for both pure water and Al2O3-water nanofluids cases. Also, the friction factor increases as dimple depth increases. Results show that increase in PEC is more pronounced in the laminar region than in the transition region, it starts to decrease for turbulent flows. For nanofluid, PEC values are considerably higher than pure water cases. The variation of PEC for capsule dimpled tubes are dependent on flow regimes and dimple depths. Increasing the nano particle volume concentration and dimple depth in laminar flows increase the PEC significantly.
Citation - WoS: 2
Citation - Scopus: 2
Analysis of heat transfer enhancement of passive methods in tubes with machine learning
(Sage Publications Ltd, 2024) Yapici, Ekin Ozgirgin; Türkoğlu, Haşmet; Ayli, Ece; Turkoglu, Hasmet; 31329; 265836; 12941
This study investigates the efficacy of machine learning techniques and correlation methods for predicting heat transfer performance in a dimpled tube under varying flow conditions, including the presence of nanoparticles. A comprehensive numerical analysis involving 120 cases was conducted to obtain Nusselt numbers and friction factors, considering different dimple depths and velocities for both pure water and water-Al2O3 nanofluid at 1%, 2%, and 3% volume concentrations. Utilizing the data acquired from the numerical simulations, a correlation equation, SVM ANN architectures were developed. The predictive capabilities of the statistical approach, ANN, and SVM models for Nusselt number distribution and friction factor were meticulously assessed through mean average percentage error (MAPE) and correlation coefficients (R2). The research findings reveal that machine learning techniques offer a highly effective approach for accurately predicting heat transfer performance in a dimpled tube, with results closely aligned with Computational Fluid Dynamics (CFD) simulations. Particularly noteworthy is the superior performance of the ANN model, demonstrating the most precise predictions with an error rate of 2.54% and an impressive R2 value of 0.9978 for Nusselt number prediction. In comparison, the regression model achieved an average error rate of 6.14% with an R2 value of 0.8623, and the SVM model yielded an RMSE value of 2.984% with an R2 value of 0.9154 for Nusselt number prediction. These outcomes underscore the ANN model's ability to effectively capture complex patterns within the data, resulting in highly accurate predictions. In conclusion, this research showcases the promising potential of machine learning techniques in accurately forecasting heat transfer performance in dimpled tubes. The developed ANN model exhibits notable superiority in predicting Nusselt numbers, making it a valuable tool for enhancing thermal system analyses and engineering design optimization.
Citation - WoS: 0
Citation - Scopus: 0
Clean Energy Generation in Residential Green Buildings- CH2
(inst Engineering Tech-iet, 2019) Yapici, Ekin Ozgirgin; Ayli, Ece
Due to the recent investigations, buildings consume a considerable amount of the electricity, drinking water, global final energy use and as a result are responsible for one third of the global carbon emissions. Therefore, building sector has a key role to reach global energy targets. In this sight, this study draws attention to the sustainable energy performances of green buildings (GBs) and aims towards the GBs concept which includes renewable sources in the construction and lifetime utilization. The remainder of the chapter is subjected as follows: Section 2.1 gives a brief information about residential GBs, and in Section 2.2, certification systems for sustainability ratings of residential GBs are given. This is followed by case studies related to the certification systems in Section 2.3 part. In Section 2.4, GBs incentives are summarized. Section 2.5 provides information about energy demand modelling for residential GBs, and in Section 2.6, clean energy generation systems in residential GBs are described in detail. Finally, outlook for the works that is performed up to now and the outlook for the future is given.
Citation - WoS: 40
Citation - Scopus: 45
Numerical investigation on the performance of a small scale solar chimney power plant for different geometrical parameters
(Elsevier Sci Ltd, 2020) Yapici, Ekin Ozgirgin; Ayli, Ece; Nsaif, Osama; 31329; 265836
In recent decades, demand for energy has been significantly increased, and considering environmental impacts and the degrading nature of fossil fuels, clean and emission-free renewable energy production has attracted a great deal of attention. One of the most promising renewable energy sources is solar energy due to low cost and low harmful emissions, and from the 1980s, one of the most beneficial applications of solar energy is the utilization of solar chimney power plants (SCPP). A SCPP is a simple and reliable system that consists of three main components; a solar collector, a chimney (tower) and a turbine to utilize electrical energy. Recently, by the advancement in computer technology, the use of CFD methodology for studying SCPP has become an extensive, robust and powerful technique. In light of the above, in this study, numerical simulations of a SCPP through three-dimensional axisymmetric modeling is performed. A numerical model is created using CFD software, and the results are verified with an experimental study from the literature. After ensuring good agreement with the experiments, chimney's and collector's geometric parameters effects and different configurations effects on SCPP performance, simultaneously and additively is investigated. The study introduces an insight to the performance enhancement methods and finding the best configuration of a SCPP model, which will be the basis of a detailed prototyping process. Based on the numerical results, the best configuration of the SCPP has been found as the diverging chimney which enhances the generated power. The results of the study showed that the chimney height and collector radius increase has a positive effect on the power output and efficiency of the system, but when construction and material costs are also considered, each has an optimal value. The maximum impact on the performance is found to be by the chimney tower radius and the collector height and inclination are found to have optimum values considering performance. According to the obtained results, the best performance for the SCPP was obtained with 3.5 m chimney height, 30 cm tower diameter, 400 cm of collector diameter with 6 cm height and zero inclination angle. By the correct selection of the dominant performance parameter which can be done by correctly interpreting the results of this study, "the best" design of a SCPP real scale prototype considering maximum power requirement can be done. (C) 2020 Elsevier Ltd. All rights reserved.