Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Machine Learning in Flow Boiling: Predicting Bubble Lift-Off Diameter Despite Data Limitations(Yildiz Technical University, 2025) Tabrizi, Atta Heydarpour; Mohammadpourfard, Mousa; Mohammadpourfard, MostafaThis study concentrates on applying machine learning techniques to flow boiling in order to predict the bubble lift-off diameter. This prediction is critical because the diameter plays a key role in understanding boiling dynamics and calculating heat transfer rates. Additionally, accurately predicting this diameter is essential for optimizing thermal systems and enhancing energy efficiency. By evaluating the performance of three different machine learning algorithms: M5 tree, multilinear regression, and random forest, we aimed to assess their effectiveness in providing reliable predictions even with limited experimental data. This research is essential as it demonstrates the potential of machine learning to enhance predictive accuracy in scenarios where obtaining extensive datasets is challenging. Our findings show that these machine-learning techniques are effective for accurate predictions. The results show that the coefficient of determination ranged from 0.64 to 0.94, indicating how well the models fit the data. The root mean square error was between 0.009 and 0.02, and the mean absolute error ranged from 0.0004 to 0.02. Based on the findings, it can be inferred that the machine learning algorithms used in this study are reliable for predicting bubble lift-off diameter. This reliability also extends to other experimental parameters, suggesting that these techniques can be effectively applied in various contexts with limited data. This study demonstrates the potential of machine learning to predict experimental parameters and advances previous research by identifying key factors that influence bubble lift-off diameter. © 2025 Elsevier B.V., All rights reserved.Article Occurrence of Bromide and Bromate in Chlorinated Indoor Swimming Pools, and Associated Health Risks(Yildiz Technical University, 2023) Dumanoğlu,Y.; Geni̇Şoğlu,M.; Sofuoğlu,S.C.Swimming is a physical activity that is accessible to people of all ages in all seasons. However, continuous organic and inorganic precursor load and disinfectant dosing make pool water chemistry much more complex than other disinfected waters. Carcinogenic bromate compound is one of the hundreds of disinfection by-products in pool water. The occurrence of bromate in pool waters depends on the precursor content of filling water, the disinfection process, operating parameters, and the purity of disinfectants. While the average filling water bromide concentrations of University Campus indoor swimming pool in Gülbahçe –Urla (SP1) and Buca public indoor swimming pool (SP2) were determined to be 182 μg/L and 11.0 μg/L, respectively, the average bromate concentrations of SP1 and SP2 were 59.4 μg/L and 68.3 μg/L. Estimated chronic-toxic health risks of accidental ingestion of pool water during swimming (between 10-3 and 10-1) were lower than the threshold level (‘1’). Although the carcinogenic risks in central tendency scenario (<10-6) indicate negligible risks for swimmers, worst case scenario indicates carcinogenic risks (medians were ranged from 1.61×10-6 to 9.42×10-6) for highly exposed specific swimmer groups. Bromate accumulation in swimming pools needs attention for mitigating the health risks for swimmers. Copyright 2021, Yıldız Technical University.Article Citation - Scopus: 6An Experimental Study on Release Mechanism of Iron and Manganese From Sediments To the Water Column in Reservoirs(Yildiz Technical University, 2021) Vural,B.; Elçi,Ş.; Ökten,H.E.Iron and manganese accumulation in drinking water reservoirs is a challenging issue and should be controlled to prevent their adverse effects on human health. Accumulation of these elements not only clogs pipeline systems but also causes stains on fixtures and laundry. Also, high concentrations of iron and manganese may lead to various health problems when ingested. This study focuses on the release mechanism of iron and manganese from sediments to the water column in reservoirs and investigates methods to prevent this release. Effects of hypoxia, hypolimnetic aeration, alkalinity of water, and thermal stratification on iron and manganese concentrations were investigated through laboratory experiments. Experiments done simulating the water column showed that hypoxia caused more dissolution of ferrous iron when compared with that of manganese. Accordingly, aeration of the water column in hypoxic conditions lead to a significant decrease in ferrous iron concentrations (in our case reaching zero). However, manganese and total iron levels were not affected by the aeration of the water column. Alkalinity level of the water column was observed to have a great effect on the solubility of iron and manganese. Concentrations of total Fe and total Mn measured for acidic (pH = 5) conditions were considerably greater than concentrations measured at neutral conditions. As for alkaline (pH = 11) conditions, the opposite was observed with measured concentrations of total Fe and total Mn being lower than the ones measured for neutral conditions. Thermal stratification had an enhancing effect on the solubility of both iron and manganese ions. While aeration of the stratified water column slightly decreased the concentrations of Total Fe and Mn, it had a greater impact on decreasing Fe2+ concentrations. Copyright 2021, Yıldız Technical University.Article Citation - Scopus: 5Ultrasound Assisted Extraction for the Recovery of Phenolic Compounds From Waste Hazelnut Shell(Yildiz Technical University, 2020) Dal,O.; Şengün,D.; Özşen,A.Y.Hazelnut shell is the primary byproduct of hazelnut industry which has the potential source of antioxidants, and phenolics with interest of pharmaceutical, food, and cosmetic industries. The main goal of this study is to determine effects of extraction method, extraction time, solvent type, solid to liquid ratio, and particle size on extraction yield, antioxidant capacity, and total phenolic content of waste hazelnut shell. The highest extraction yield was found as 15.4% by using methanol as solvent, in combined extraction for 16 h total extraction time. As for the best antioxidant capacity, 0.0508 mg TE mL-1 was observed by using methanol as a solvent in ultrasonic extraction, whereas the highest phenolic content was found as 0.188 mg GAE mL-1 by Soxhlet extraction with acetone for 8 h. After extraction of hazelnut shell waste, major components were found as oleic and palmitic acids for all solvent types according to GC-MS results. © Yildiz Technical University, Environmental Engineering Department. All rights reserved.Article Citation - Scopus: 1Performance Indices of Soft Computing Models To Predict the Heat Load of Buildings in Terms of Architectural Indicators(Yildiz Technical University, 2016) Turhan,C.; Kazanasmaz,T.; Akkurt,G.G.This study estimates the heat load of buildings in Izmir/Turkey by three soft computing (SC) methods; Artificial Neural Networks (ANNs), Fuzzy Logic (FL) and Adaptive Neuro-based Fuzzy Inference System (ANFIS) and compares their prediction indices. Obtaining knowledge about what the heat load of buildings would be in architectural design stage is necessary to forecast the building performance and take precautions against any possible failure. The best accuracy and prediction power of novel soft computing techniques would assist the practical way of this process. For this purpose, four inputs, namely, wall overall heat transfer coefficient, building area/ volume ratio, total external surface area and total window area/total external surface area ratio were employed in each model of this study. The predicted heat load is evaluated comparatively using simulation outputs. The ANN model estimated the heat load of the case apartments with a rate of 97.7% and the MAPE of 5.06%; while these ratios are 98.6% and 3.56% in Mamdani fuzzy inference systems (FL); 99.0% and 2.43% in ANFIS. When these values were compared, it was found that the ANFIS model has become the best learning technique among the others and can be applicable in building energy performance studies. © 2016. All Rights Reserved.Article Citation - Scopus: 1Hand Warmer Types, Silica and Zeolite 4a as Potential Hand Warmers(Yildiz Technical University, 2024) Alp,F.B.; Balköse,D.Hand warmers are used in cold environmental conditions to warm hands. Disposable air activated hand warmers and reusable hand warmers which generate heat by crystallization are present in the market. In the present study utilizing heat of wetting of silica gel and zeolites in warming hands was tested in a system simulated to warm hands by inserting warmer packages in knitted wool gloves. Sodium acetate solution was also tested as a reusable hand warmer by melting and recrystallization. While the commercial warmers released heat slowly for long period, dry silica gel and dry zeolite 4A released heat fast. Around 25% water and inert dilution materials should be used to limit the temperature rise in silica gel and zeolite 4A within reasonable limits. © 2024 Yildiz Technical University. All rights reserved.Article Occurrence of Bromide and Bromate in Chlorinated Indoor Swimming Pools, And Associated Health Risks(Yildiz Technical University, 2023) Dumanoğlu, Y.; Genisoglu, M.; Sofuoglu, S.C.Swimming is a physical activity that is accessible to people of all ages in all seasons. However, continuous organic and inorganic precursor load and disinfectant dosing make pool water chemistry much more complex than other disinfected waters. Carcinogenic bromate compound is one of the hundreds of disinfection by-products in pool water. The occurrence of bromate in pool waters depends on the precursor content of filling water, the disinfection process, operating parameters, and the purity of disinfectants. While the average filling water bromide concentrations of University Campus indoor swimming pool in Gülbahçe –Urla (SP1) and Buca public indoor swimming pool (SP2) were determined to be 182 μg/L and 11.0 μg/L, respectively, the average bromate concentrations of SP1 and SP2 were 59.4 μg/L and 68.3 μg/L. Estimated chronic-toxic health risks of accidental ingestion of pool water during swimming (between 10-3 and 10-1) were lower than the threshold level (‘1’). Although the carcinogenic risks in central tendency scenario (<10-6) indicate negligible risks for swimmers, worst case scenario indicates carcinogenic risks (medians were ranged from 1.61×10-6 to 9.42×10-6) for highly exposed specific swimmer groups. Bromate accumulation in swimming pools needs attention for mitigating the health risks for swimmers. © 2021, Yıldız Technical University.