Influence of gap-ratio on flow dynamics and heat transfer for a square cylinder approaching a moving wall in turbulent regime

Tanweer, Sartaj; Dewan, Anupam; Sanghi, Sanjeev

doi:10.1016/j.ijheatmasstransfer.2021.121122

Cited by 7 publications

(1 citation statement)

References 38 publications

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“…Figure 8 shows the 3D temperature distribution. Tanweer et al [26] studied heat transfer around a single square cylinder. Khanafer and Vafai [27] When the cylinder was hot and the walls of the environment housing the cylinder were colder; it could be seen that the temperature spread in waves around the cylinder.…”

Section: Resultsmentioning

confidence: 99%

Modeling of Heat Transfer Around a Square and a Circle: A Novel ANN-Based Approch

Yetik¹

2021

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi

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ÖzetArtificial neural network (ANN) is a modelling of the human brain. The aim of this study is to estimate the heat distribution with ANN around different cylinders. Within the scope of the study, square and circular cylinders were discussed. In this study, the temperature analysis of the cylinders was carried out with a program written in Fortran, not using a package program whose exact background is unknown. The results obtained from a writing code are more reliable. The study is discussed in two dimensions. The 3 most commonly used algorithms (Levenberg -Marguardt (LM), Pola-Ribiere Conjugate Gradient (CGP) and Scaled Conjugate Gradient (SCG)) were used to train with ANN. Cylinder type, x-coordinate and y-coordinate were the input variables; and temperature was the output variable. The most suitable algorithm was found to be LM-18 algorithm. The proximity of artificial neural networks and real values was evaluated statistically. These were R 2 , CoV and RMSE. R 2 , CoV and RMSE values in the training phase of Levenberg -Marguardt -18 neuron were determined to be 0.9939, 0.0044, 0.0107 while their values in the test phase were 0.9850, 0.0043 and 0.0190 respectively. The fact that the R 2 value is so close to 1 is an indication that ANN is working very well. Yapay sinir ağları (ANN) insan beyninin bir modellemesidir. Bu çalışmanın amacı da ANN ile farklı silindirler etrafındaki ısı dağılımını tahmin etmektir. Çalışma kapsamında kare ve daire silindirler ele alınmıştır. Bu çalışmada, silindirlerin sıcaklık analizi, tam arka planda ne yaptığı bilinmeyen bir paket program kullanılmadan, fortran dili kullanılarak gerçekleştirilmiştir. Kod yazarak elde edilen sonuçlar daha güvenilir sonuçlardır. Çalışma iki boyutlu olarak ele alınmıştır. ANN ile verilerin eğitilmesinde en yaygın kullanılan 3 farklı algoritma (Levenberg-Marguardt (LM), Pola-Ribiere Conjugate Gradient (CGP) ve Scaled Conjugate Gradient (SCG)) kullanılmıştır. Silindir tipi, x-koordinatı ve y koordinatı girdi verileri, sıcaklık ise çıktı verisidir. En uygun algoritma LM-18 algoritması olarak bulunmuştur. Yapay sinir ağları ile gerçek değerlerin birbirine yakınlığı istatistiksel olarak değerlendirilmiştir. Bunlar R 2 , CoV ve RMSE'dir. LM-18 algritmasının eğitim aşamasındaki R 2 , CoV ve RMSE değerleri sırasıyla 0.9939, 0.0044, 0.0107; test aşamasındaki değerleri sırasıyla 0.9850, 0.0043, 0.0190'dir. R 2 değerinin 1'e bu kadar yakın olması ANN'nin çok iyi çalıştığının da göstergesidir.

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Section: Resultsmentioning

confidence: 99%

Modeling of Heat Transfer Around a Square and a Circle: A Novel ANN-Based Approch

Yetik¹

2021

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi

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Numerical investigation on compressible flow around a cylinder in proximity to the heated wall

Liu,

Qu,

Tao

et al. 2024

J Hydrodyn

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Effect of free-stream inclination and buoyancy on flow past a square cylinder in large-scale heating regime

Arif

Hasan

2021

Physics of Fluids

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The combined effects of free-stream inclination (α) and heating [ϵ=(Tw−T∞)/T∞] on aerodynamic and heat transfer parameters are studied at fixed Reynolds number (Re = 100), Prandtl number (Pr = 0.71), cylinder inclination (ϕ=0°), Froude number (Fr = 1.0), and Mach number (M = 0.1) in the large-scale heating regime. For this purpose, a non-Oberbeck–Boussinesq compressible model for thermally perfect gases incorporating volumetric straining as well as transport property variations under large-scale heating is employed. The free-stream inclination (α) is varied in the range [0°, 90°] while the over-heat ratio (ϵ) is varied in the range of [0, 1]. It is found that at small free-stream inclinations (α≤45°), increase in heating causes a significant increase in mean drag coefficient, while at large α (α>45°), heating has little effect on mean drag coefficient. The mean lift coefficient (CL) increases by increasing ϵ for any value of α except α = 0. At a fixed heating level, the variation of mean CL is very non-monotonic with lower values at α=45° and 90°. It is found that the increase in flow inclination from 0° to 90° reduces the sensitivity of Strouhal number (St) to heating. For ϵ≤0.6, mean Nusselt number exhibits a non-monotonic trend with increase in α and attains a maximum value at α ≅ 40°. However, for ϵ>0.6, heat transfer decreases with increase in α and is maximum for aligned flow (α=0°).

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Influence of gap-ratio on flow dynamics and heat transfer for a square cylinder approaching a moving wall in turbulent regime

Cited by 7 publications

References 38 publications

Modeling of Heat Transfer Around a Square and a Circle: A Novel ANN-Based Approch

Modeling of Heat Transfer Around a Square and a Circle: A Novel ANN-Based Approch

Numerical investigation on compressible flow around a cylinder in proximity to the heated wall

Effect of free-stream inclination and buoyancy on flow past a square cylinder in large-scale heating regime

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