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Thus, a mathematical filter was developed to correct the friction-induced error of the PR measurements.
The corrected data with the friction and the temperature compensations were employed to develop the Arrhenius-type model and BP neural network respectively.
Even though Fanno theory is well-established, its outcome strongly depends on the correct assessment of the friction factor term.
During practical applications, researchers often find that a correct choice of the friction factor can be crucial to make a sound prediction of hydraulic problems.
The correlations for the wall corrected friction factor proposed in the literature (Exp. Heat Transfer 12 (1999) 309), with varying coefficients, fit well to predict the pressure drop through packed beds for both glass beads and SOPs with considering the wall effects.
Results are generated for the appropriate parameter range applicable for the diesel particulate filter application which provide the corrected friction coefficients and Nusselt numbers for nonzero Rew.
The differences in the two approaches are highlighted, indicating that the physically correct stick slip approach describes the friction phenomenon better than the standard signum approach.
The relaxation time corrected to the iso-friction state agrees approximately with the dynamic scaling theories.
The measurements are corrected for a friction stress of 0.34 MPa and compared with a model which incorporates the orientation dependent line tension (ODLT) of a dislocation.
The frequently used equations for horizontal drain hole productivity are corrected for the wellbore friction effect in this work.
While similar control solutions do estimate these parameters, there is no guarantee that they will estimate the correct value of friction parameters.
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