Experimental and numerical study on air cores for cylindrical tank draining

Park, Il Seouk; Sohn, Chang Hyun

doi:10.1016/j.icheatmasstransfer.2011.05.002

Cited by 39 publications

(24 citation statements)

References 8 publications

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“…In the case of 1 st order of time discretization scheme, the draining time completion obtained from the current simulation using DNS, RANS − , RANS − and LES are 91s, 72s, 70s and 101.5, respectively. The draining times for RANS − and RANS − are 8.26s and 10.26s earlier than the result obtained from the experiment by Park and Sohn [10]. Meanwhile, the draining time completion obtained from DNS and LES are 10.74s and 21.24s slower than the result obtained from the experiment by Park and Sohn [10].…”

Section: Comparison Of Drainage Timementioning

confidence: 59%

“…The sensitivity of the results of the time discretization scheme is also assessed for all turbulence models. Table 3 compares the result of the current study with the similar study by Park and Sohn [10]. The theoretical value that is calculated from equation 10is also compared.…”

Section: Comparison Of Drainage Timementioning

confidence: 74%

“…The theoretical value that is calculated from equation 10is also compared. According to Park and Sohn [10], the draining time can be expressed theoretically with the following equation:…”

Section: Comparison Of Drainage Timementioning

confidence: 99%

“…In this study, a model is intentionally made the same as the experimental and numerical investigations of Park and Sohn [10] so that a comparison study can be made. Additionally, this model is also a general model for a draining tank, where a benchmark study can be adopted.…”

Section: Introductionmentioning

confidence: 99%

“…The bottom and top of the tank are in the atmospheric condition and the fluid is drained naturally by gravity, g, downward. In order to reproduce the generation of the air-core, initial rotation with the speed of 120 RPM is imparted to the wall of the tank before the liquid is started to drain [10]. Figure 1 shows the schematic diagram of the draining tank.…”

Section: Introductionmentioning

confidence: 99%

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Benchmark on the Dynamics of Liquid Draining Inside a Tank

Sakri

Ali²,

Zaki³

2019

E3S Web Conf.

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Immense information and details observation of flow physics inside a draining tank can be achieved by adopting reliable numerical simulations. Yet the accuracy of numerical results has been always debatable and it is mainly affected by the grid convergence error and computational modeling approaches. Hence, this study is divided into two stages. In the first stage, this paper determines a systematic method of refining a computational grid for a liquid draining inside a tank using OpenFOAM software. The sensitivity of the computed flow field on different mesh resolutions is also examined. In order to study the effect of grid dependency, three different grid refinements are investigated: fine, medium and coarse grids. By using a form of Richardson extrapolation and Grid Convergence Index (GCI), the level of grid independence is attained. In this paper, a monotonic convergence criteria is reached when the fine grid has the GCI value below 10% for each parameter. In the second stage, different computational modeling approaches (DNS, RANS k-ε, RANS k-ω and LES turbulence models) are investigated using the finer grid from the first stage. The results for the draining time and flow visualization of the generation of an air-core are in a good agreement with the available published data. The Direct Numerical Simulation (DNS) seems most reasonably satisfactory for VOF studies relating air-core compared to other different turbulence modeling approaches.

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Section: Comparison Of Drainage Timementioning

confidence: 59%

Section: Comparison Of Drainage Timementioning

confidence: 74%

“…The theoretical value that is calculated from equation 10is also compared. According to Park and Sohn [10], the draining time can be expressed theoretically with the following equation:…”

Section: Comparison Of Drainage Timementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations