Electricly enhanced flows can be found in various technical applications as, for example, in air cleaning devices and liquid metal or redox flow batteries. For both examples mentioned it is crucial to develop a general understanding of the relevant physical processes and model them economically. Additionally, a correct upscaling procedure is specifically relevant for the transition into the industrial scale. All of these aspects are challenging because of the multiscale and multiphysics nature of these flows. In this paper we present a lower-order modeling strategy that aims to bridge the gap between fundamental research and applications by utilizing stochastic one-dimensional turbulence (ODT). Two case studies are performed. One is for two-way coupled turbulent Couette flow of electrolytes and another for one-way coupled planar Poiseuille flow in a wire-plate electrostatic precipitator. By comparison with reference data, we show that the modeling approach is robust and has predictive capabilities. Nevertheless, we also discuss some limitations of the purely one-dimensional and stochastic dynamical representation.
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