On the Values for the Turbulent Schmidt Number in Environmental Flows
By Carlo Gualtieri, Athanasios Angeloudis, Fabián A. Bombardelli, Thorsten Stoesser. 2017
212 citations recorded by the source corpus.
Computational Fluid Dynamics (CFD) has consolidated as a tool to provide understanding and quantitative information regarding many complex environmental flows. The accuracy and reliability of CFD modelling results oftentimes come under scrutiny because of issues in the implementation of and input data for those simulations. Regarding the input data, if an approach based on the Reynolds-Averaged Navier-Stokes (RANS) equations is applied, the turbulent scalar fluxes are generally estimated by assuming the standard gradient diffusion hypothesis (SGDH), which requires the definition of the turbulent Schmidt number, Sct (the ratio of momentum diffusivity to mass diffusivity in the turbulent flow). However, no universally-accepted values of this parameter have been established or, more importantly, methodologies for its computation have been provided. This paper firstly presents a review of previous studies about Sct in environmental flows, involving both water and air systems. Secondly, three case studies are presented where the key role of a correct parameterization of the turbulent Schmidt number is pointed out. These include: (1) transverse mixing in a shallow water flow; (2) tracer transport in a contact tank; and (3) sediment transport in suspension. An overall picture on the use of the Schmidt number in CFD emerges from the paper.
Subfields: Computational Mechanics, Environmental Engineering, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/9efccd491ee74b1585b4c0d5229fee4e777bca8e
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In Computational Mechanics
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Citations in the corpus
- The physical oceanography of the transport of floating marine debris (2020, background): “The value of this Schmidt number is an open question (Tominaga and Stathopoulos 2007, Gualtieri et al 2017).”
- Optical flow for image-based river velocity estimation (2019, background): “Heitz et al. (2008) suggested to refrain from multi-resolution strategy for PIV applications because the smoothing and sub-sampling of images will suppress the particles in the coarsest resolution levels.”