Sürdürülebilir Kalkınma Amaçları
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- MakaleYalnız künye2025Scopus SJRQ1Optimization of surface modification parameters of fly ash with high calcium oxide (CaO) content to use as a filling material
Uçurum, Metin; Özdemir, Akın; Teke, Çağatay
Fly ash (FA) is the fine-grained waste product obtained by burning coal after being ground to specific sizes in thermal power plants, carried with flue gases, and kept in cyclones or electro-filters. Like every industrial waste, the possibilities of utilizing FA have been investigated, and it can be utilized as an additive in cement and concrete. Despite this, industrial waste, which increases daily in the world, brings many problems, especially environmental problems. For this reason, alternative usage areas of the waste in question are constantly being investigated. In this paper, FA containing approximately 50 % CaO from Afşin-Elbistan, Turkiye was processed with stearic acid in a planetary mill to be used as a filling material in industrial products, and it has a grain size of 68.10 μm on a d50 basis, a specific surface area (SSA) of 176.40 m2/g and a contact angle of 13.89. An optimization and characterization study was conducted to make the hydrophilic surface structure hydrophobic by mechanochemical surface modification. Also, surface modification parameters, such as operational speed (rpm), ball filling ratio (%), FA filling ratio (%), pulp density, stearic acid dosage (% of FA), and modification time (min.) were optimized with the D-optimal experimental design. Based on the optimum surface modification parameters, a coated fly ash (CFA) product was obtained with an active ratio of 99.70 %, a contact angle of 95.06o, a medium size (d50) size of 10.60 μm, and an SSA of 926.90 m2/g.
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İncele - MakaleAçık Erişim2021Scopus SJRQ3A novel weighted mean-squared error optimization model to obtain optimal conditions of adsorption factors for a lead removal process
Özdemir, Akın; Teke, Çağatay; Serencam, Hüseyin; Uçurum, Metin; Gündoğdu, Ali
Lead (Pb) removal process from wastewater is an important issue to prevent health problems for people. For this particular purpose, a low-cost adsorbent may be beneficial for improving the adsorption capacity for the Pb removal process. The aims of this paper are four-fold. First of all, a D-optimal experimental design was selected to reduce experimental runs and its cost. Second, the effect of four adsorption design factors, stirring speed (rpm), adsorbent dosage (g), pH level, and initial metal concentration (ppm), was examined. Also, the yellow natural stone, which is from Bayburt, Turkey, was used as a cheap adsorbent for the Pb removal process from the solu-tion. Third, a novel weighted mean-squared error optimization model was developed to obtain optimal adsorption levels for adsorption factors. Besides, a verification study was conducted to verify the results of the adsorption experiment. Finally, the lead (Pb(II)) removal capacity of the yellow Bayburt stone was obtained to be 46.031 mg/g, and the results of the experiment from the proposed methodology showed a good performance for the removal study.
- MakaleYalnız künye2020Scopus SJRQ1D-optimal experimental design for production models in nonstandard experiments
Özdemir, Akın
Robust design is an effective Quality by Design method to reduce product variation by selecting levels of design factors. For a number of situations, a nonstandard design region with linearly limited resources is needed to conduct an experiment. In the literature, little attention has been given to the development of robust design models for the nonstandard design region with a combination of linearly limited resources and a limited number of design points. In this paper, a selection scheme of D-optimal experimental design points is proposed to generate design points using the modified exchange algorithm for the nonstandard design region while specifying linearly limited resources and the limited number of design points. The modified exchange algorithm is able to generate global design points with less time complexity than the improved Fedorov algorithm. In addition, robust design models linking a D-optimal experimental design with quality considerations are proposed in order to obtain optimum settings of design factors for the product. Comparative studies are also presented. Finally, a real-life experimental study shows that the proposed models with the desirability function and the sequential quadratic programming technique achieve greater variance reduction than the traditional counterparts.
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