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A 2D image-based approach for CFD validation of liquid mixing in a free-surface condition

Rodríguez Ocampo, P. E [autor] | Ring, M [autor] | Hernández Fontes, J. V [autor] | Alcérreca Huerta, Juan Carlos [autor] | Mendoza Ramírez, Eduardo [autor] | Gallegos Diez Barroso, Gabriel [autor] | Silva, R [autor].
Tipo de material: Artículo
 en línea Artículo en línea Nota de acceso: Acceso en línea sin restricciones En: Journal of Applied Fluid Mechanics. Volume 13, número 5 (2020), páginas 1487-1500. --ISSN: 1735-3645Número de sistema: 41543Resumen:
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This study proposes an image-based approach to evaluate the validity of numerical results for cases where the setup can be assumed to be two-dimensional (2D) and mixing between liquids of different densities occurs under a free-surface condition. The proposed methodology is based on the estimation of the relative errors of the model through density matrices generated from images of the experimental and numerical results (i.e., post-processing snapshots of the density field). To demonstrate the use of the methodology, experimental tests and numerical simulations were performed for a double-dam-break problem with two miscible liquids. For the experiments, a high-speed camera was employed to capture details of the fluid interactions after the dam breaking. For the numerical simulations, an OpenFOAM® multiphase solver was employed to reproduce the benchmarking tests. Three turbulence approaches were tested: a zero-equation RANS model, a two-equation (k-epsilon) RANS model, and a Large-Eddy Simulation (LES) model. The experimental results compared favorably against the numerical results, with average drelative errors of ~17 and ~19% for the zero-equation and the two-equation turbulence models, respectively, and ~14% for the LES model. From the results obtained, it can be inferred that the two-equation (k-epsilon) model had limitations in reproducing the mixing between the liquid phases in terms of relative errors. The LES model reproduces the mixing between phases more accurately than zero and two-equation RANS models, which were seen to be more suitable for capturing the formation of large eddies in the initial phase of the experiment. The present methodology canbe improved and extended for different multiphase flow configurations.

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Acceso en línea sin restricciones

This study proposes an image-based approach to evaluate the validity of numerical results for cases where the setup can be assumed to be two-dimensional (2D) and mixing between liquids of different densities occurs under a free-surface condition. The proposed methodology is based on the estimation of the relative errors of the model through density matrices generated from images of the experimental and numerical results (i.e., post-processing snapshots of the density field). To demonstrate the use of the methodology, experimental tests and numerical simulations were performed for a double-dam-break problem with two miscible liquids. For the experiments, a high-speed camera was employed to capture details of the fluid interactions after the dam breaking. For the numerical simulations, an OpenFOAM® multiphase solver was employed to reproduce the benchmarking tests. Three turbulence approaches were tested: a zero-equation RANS model, a two-equation (k-epsilon) RANS model, and a Large-Eddy Simulation (LES) model. The experimental results compared favorably against the numerical results, with average drelative errors of ~17 and ~19% for the zero-equation and the two-equation turbulence models, respectively, and ~14% for the LES model. From the results obtained, it can be inferred that the two-equation (k-epsilon) model had limitations in reproducing the mixing between the liquid phases in terms of relative errors. The LES model reproduces the mixing between phases more accurately than zero and two-equation RANS models, which were seen to be more suitable for capturing the formation of large eddies in the initial phase of the experiment. The present methodology canbe improved and extended for different multiphase flow configurations. eng

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