Yazarlar

• Akçadirci, Esra(1)
• Cuce, Erdem(1)
• Cuce, Pinar Mert(1)
• Güneş, Sibel(1)
• Manay, Eyüphan(1)
• Oztekin, Erman Kadir(1)
• Çakir, Ǔur(1)
• Çomakli, Ömer(1)
• Özceyhan, Veysel(1)

• MakaleYalnız künye2019Scopus SJRQ2/r/bayburt/13939
  Heat transfer enhancement in cylindrical fins through longitudinal parabolic perforations

  Cuce, Erdem; Oztekin, Erman Kadir; Cuce, Pinar Mert

  In our previous works, it is clearly addressed that optimisation of fin profile is of vital importance in terms of the rate of heat transfer from a hot surface, and the optimisation procedure depends on several factors. Within the scope of this research, a longitudinal cylindrical fin profile is under interest for the optimisation research. The purpose is to investigate the effects of longitudinal parabolic perforations on the fin parameters such as temperature distribution, effectiveness and efficiency, in which the fin surface is cooled by natural convection and radiation. Different concavity levels are considered to form parabolic perforations. The rate of heat transfer from fin surface is numerically correlated with the fin mass with respect to different concavity levels. According to results, heat transfer from unit fin mass is enhanced with the new designs. The outcome of the study can be used to optimise the needs for particular applications by making a decision between heat loss and weight options. That is, the increase in the concavity level of the perforation results in a lighter and cheaper design, but yielding a lower heat loss. However, heat transfer from unit mass is still enhanced.

  AtıfScopus4·WoS5·OpenAlex9

  İncele
• MakaleYalnız künye2012Scopus SJRQ3/r/bayburt/14026
  The prediction of heat transfer and fluid characteristics for equilateral triangular bodies in tandem arrangement by artificial neural networks

  Manay, Eyüphan; Güneş, Sibel; Akçadirci, Esra; Özceyhan, Veysel; Çakir, Ǔur; Çomakli, Ömer

  The objective of this study is to investigate the effect of the spacing between equilateral dual triangular bodies symmetrically placed into the channel axis under steady state conditions on heat transfer and fluid characteristics by using artificial neural networks (ANN). The Back Propagation (BP) training algorithm was applied to train the model. The successful application proved that ANN model can be used for predicting the Nusselt number and skin friction coefficient as a convenient and effective method. The distribution of local Nusselt number, skin friction coefficient along the channel wall and overall enhancement ratio of all investigated cases are presented.

  AtıfScopus5

  İncele