Abstract: Vortex units are commonly considered for various single and multiphase applications due to their process intensification capabilities. The transition from gas‐only flow to gas–solid flow remains largely unexplored nonetheless. During this transition, primary flow phenomenon, jets, and secondary flow phenomena, counterflow and backflow, are substantially reduced, before a rotating solids bed is established. This transitional flow regime is referred to as the vortex suppression regime. In the present work, this flow transition is identified and validated through experimental and computational studies in two vortex units with a scale differing by a factor of 2, using spherical aluminum and alumina particles. This experimental data supports the proposed theoretical particle monolayer solids loading that allows estimation of vortex suppression regime solids capacity for any vortex unit. It is shown that the vortex suppression regime is established at a solids loading theoretically corresponding to a monolayer being formed in the unit for 1g‐Geldart D‐ and 1g‐Geldart B‐type particles. The model closely agrees with experimental vortex suppression range for both aluminum and alumina particles. The model, as well as the experimental data, shows that the flow suppression regime depends on unit dimensions, particle diameter, and particle density but is independent of gas flow rate. This combined study, based on experimental and computational data and on a theoretical model, reveals the vortex suppression to be one of the basic operational parameters to study flow in a vortex unit and that a simple monolayer model allows to estimate the needed solids loading for any vortex device to induce this flow transition.

Abstract: The use of temperature-time series measured in streambed sediments as input to coupled water flow and heat transport models has become standard when quantifying vertical groundwater-surface water exchange fluxes. We develop a novel methodology, called LPML, to estimate the parameters for 1-D water flow and heat transport by combining a local polynomial (LP) signal processing technique with a maximum likelihood (ML) estimator. The LP method is used to estimate the frequency response functions (FRFs) and their uncertainties between the streambed top and several locations within the streambed from measured temperature-time series data. Additionally, we obtain the analytical expression of the FRFs assuming a pure sinusoidal input. The estimated and analytical FRFs are used in an ML estimator to deduce vertical groundwater-surface water exchange flux and its uncertainty as well as information regarding model quality. The LPML method is tested and verified with the heat transport models STRIVE and VFLUX. We demonstrate that the LPML method can correctly reproduce a priori known fluxes and thermal conductivities and also show that the LPML method can estimate averaged and time-variable fluxes from periodic and nonperiodic temperature records. The LPML method allows for a fast computation of exchange fluxes as well as model and parameter uncertainties from many temperature sensors. Moreover, it can utilize a broad frequency spectrum beyond the diel signal commonly used for flux calculations.