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Under these conditions, the present LFM model allows prediction of calibration results for other gases with approximately three times more accuracy than conventional approaches that plot the flow coefficient as a function of the viscosity coefficient or Re.
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Based on a wide range of experimental data, Devi and Khatua (2017) proposed calibration expressions for secondary flow coefficients as a function of relative depth and with ratio.
The results are presented in the form of the characteristics of the flow coefficient K as a function of the mean velocity of the air passing through a pipeline.
Finally, the discharge coefficient as a function of geometrical and flow variables are presented for design engineers.
On this basis, the discharge coefficient as a function of groove geometry, flow condition, fitting coefficients and its stable value is deduced, proving to be quite consistent with the experimental result.
The solution diffusion model was used to develop power correlations to calculate the permeate side solute mass transfer coefficient as a function of effective cross-flow Reynolds number.
Experimental tests include physical, chemical and rheological characterization of the hazelnut paste and the evaluation of the overall heat transfer coefficient as a function of rotational speeds and mass flow rates.
They introduced a new empirical relation to determine the mobility coefficient as a function of geomorphologic catchment parameters (reflecting some of the flow properties during the depositional part of an event).
A new set of correlations are obtained to predict the Fanning friction factor coefficient as a function of Reynolds number and geometrical characteristics of the insert within the three flow regimes: laminar, transitional and low turbulent.
Determination of the heat transfer coefficient as a function of temperature is also considered.
In particular, the dispersion coefficient as a function of the primary variables was established.
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