Fakültemiz İşletme Bölümü öğretim üyesi Doç.Dr. Kasım BAYNAL’ın Q2 kategorisinde 2 SSCI makalesi yayınlanmıştır.
Fakültemiz İşletme Bölümü öğretim üyesi Doç.Dr. Kasım BAYNAL’ın Q2 kategorisinde 2 SSCI makalesi yayınlanmıştır.
1. Yildirim, S.T; Keskin, F.S; Baynal, K; Shahmaleki, P (2022) Investigation on properties of cement mortar with bottom ash and perlite, Structural Concrete, DOI:10.1002/suco.202100882
Abstract
Perlite and some recycled materials are preferably used to provide thermal insulation and lightness in mortar. Cement is often used as a binder in such a composite, although it makes the composite heavier and impairs its insulation properties. In this study, recycled bottom ash (BA) and expanded perlite (EP) as the aggregate, and cement as the binder and the optimum solution were investigated by using Taguchi Method. Depending on the specimens prepared using orthogonal array L9, the values of compressive strength, flexural strength, flowability, dry unit weight, water absorption, capillarity coefficient, and thermal conductivity coefficient were calculated. In general, it was found that the cement dosage was the most effective parameter and the thermal conductivity coefficient increased in parallel with the increase in unit weight and strength.
Yildirim, S.T; Keskin, F.S; Baynal, K; Shahmaleki, P (2022) Investigation on properties of cement mortar with bottom ash and perlite, Structural Concrete, DOI:10.1002/suco.202100882
2.Yildiz, C.; Kaptan, C.; Arici, M; Baynal, K; Karabay, H. (2022) Taguchi optimization of automotive radiator cooling with nanofluids, European Physical Journal-Special Topics, DOI10.1140/epjs/s11734-022-00597-4
Taguchi optimization of automotive radiator cooling with nanofluids
Abstract
Considering the influences of the heat transfer rate in automotive radiators on several aspects such as engine performance, fuel economy and available space for components, the present study numerically investigates the impacts of different nanofluids on the heat transfer and pressure drop in an automotive radiator. Four different parameters each having four levels are taken into consideration, which are nanoparticle volume fraction (phi = 0.1, 0.3, 0.7, and 1%), Reynolds number (Re = 9350, 13,800, 18,500 and 23,000), type of base fluid (EG20, EG40, EG60, and water) and type of nanoparticle (Fe3O4, CuO, Al2O3, and SiO2). Taguchi method is employed for reducing the number of parameter combinations from 256 to 16. It is found that the nanofluid utilization improves heat transfer between 3.2 and 45.9% depending on the combination of the investigated parameters. Pressure drop is noticeably increased due to nanofluid utilization. Regarding the Taguchi optimization, using Fe3O4-water nanofluid with 0.3% volume fraction at Re = 9350 is the most appropriate option for a high heat transfer with relatively low pressure drop. It is concluded that the radiator size can be reduced by 10.8% by using nanofluids due to the improvement in heat transfer, which consequently allow a larger space to designers for placing other components.
