Year: 2026
Type: article
Abstract: In engineering, one of the common problems is determining head losses in operational structures. Determining this parameter has been the focus of studies for many years. As a result, several approaches have been developed with the main aim of minimising the discrepancies between experimental values and theoretical values. Until now, this determination has been made by considering the characteristics of the structure in new condition and under ideal operating conditions. This does not take into account the environment and the actual operating conditions of each structure. With this in mind, we have proposed another method for determining head loss in a pressurised pipe. To do this, we modelled the penstocks of two hydroelectric dams in Cameroon (the Songloulou and Lagdo dams) in Gambit 2.2 software. Next, we used Fluent 6.2.2 to simulate the flow of clear water through this structure in order to see the impact of the structure’s configuration (layout) on the determination of the friction coefficient and, consequently, the pressure drop. This simulation initially allowed us to see a variation in the velocity in the pipe, despite the inlet velocity. This clearly shows the limitations of the standard analytical approach, which considers a constant velocity for a section of pipe, regardless of its length. Knowing that a variation in velocity implies a variation in friction, we graphically generated the evolution of friction on each wall. This allowed us to confirm that for the same section of pipe and at the same velocity, we have different values for the friction coefficient. We then proposed an improved expression that takes into account the variation in key parameters during the operation of structures. Similarly, we proposed a more effective and contextualised alternative approach for structures in their various forms and environments.
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W7225770734