An investigation on the drag reduction performance of bioinspired pipeline surfaces with transverse microgrooves

Abstract

A novel surface morphology for pipelines using transverse microgrooves was proposed in order to reduce the pressure loss of fluid transport. Numerical simulation and experimental research efforts were undertaken to evaluate the drag reduction performance of these bionic pipelines. It was found that the vortex ‘cushioning’ and ‘driving’ effects produced by the vortexes in the microgrooves were the main reason for obtaining a drag reduction effect. The shear stress of the microgrooved surface was reduced significantly owing to the decline of the velocity gradient. Altogether, bionic pipelines achieved drag reduction effects both in a pipeline and in a concentric annulus flow model. The primary and secondary order of effect on the drag reduction and optimal microgroove geometric parameters were obtained by an orthogonal analysis method. The comparative experiments were conducted in a water tunnel, and a maximum drag reduction rate of 3.21% could be achieved. The numerical simulation and experimental results were cross-checked and found to be consistent with each other, allowing to verify that the utilization of bionic theory to reduce the pressure loss of fluid transport is feasible. These results can provide theoretical guidance to save energy in pipeline transportations.

Quasi-Analytical Solution of Optimum and Maximum Depth of Transverse V-Groove for Drag Reduction at Different Reynolds Numbers

“…Implicit Equation ( 18) is solved by the dichotomy to obtain η ν . In Figure 16, we compare the prediction of Equation (18) with CFD data in the present, The CFD data reported by Wu et al (2019) [5], and the experimental data reported by Liu et al (2020) [32]. The reason why the relationship between η ν and U + ∞ is used, η ν U + s , is shown in Figure 16 and is mainly to facilitate the comparison between the results predicted by Equation ( 18) and the data obtained by previous studies.…”

“…The inconsistency of the application object may have been the reason for the minor errors. Meanwhile, the optimal dimensionless groove depth for pipelines, H + opt = 8.488, was observed by the water tunnel experiment of Liu et al [32] with a Reynolds number of 50,000 (U + ∞ = 17.326). In this case, the optimal dimensionless groove depth predicted by the model is 9.215, and the relative error between the model results and the experimental results is 7.8%, which qualitatively proves the correctness of the model.…”

“…The main reason for the error may be that the changes of h and Re in the CFD cases are discrete, so the presentation of the optimal or maximum h in the CFD cases is not an accurate value (more details shown in Table 4). Table 6 shows the details of the comparison between the predicted results of the model with the numerical results of Wu et al [5] and the experimental results of Liu et al [32]. Wu et al [5] optimized the groove depth on the airfoil with a Reynolds number of 299,444 (U + ∞ = 20.72).…”

“…Cui et al [22] conducted a numerical simulation on the pressure drop in microchannel flow over different transverse-grooved surfaces and found that the drag-reduction rate of V-shaped transverse grooves is better than that of rectangular transverse grooves. The experimental results of Liu et al [32] demonstrated that the drag reduction performance was best when the AR is 2 at a Reynolds number of 50,000. The purpose of this paper is to establish the physical model describing the relationship between the dimensionless depth (H + = Hu τ /υ) of the transverse groove, the dimensionless inflow velocity (U + ∞ = U ∞ /u τ ), and the drag reduction rate (η), so as to quasi-analytically solve the optimal and maximum transverse groove depth according to the different Reynolds numbers.…”

“…14.9 < U + ∞ < 20.35, the predicted drag reduction rates are in good agreement with those from the present numerical simulations and the previous experimental data U + ∞ > 20.35, there is a significant error between the prediction of the model and the numerical results of Wu et al [5], which indicates that this model is not applicable at a high Reynolds number. 2020) [32]. The reason why the relationship between 𝜂 and 𝑈 is used, 𝜂 𝑈 , is shown in Figure 16 and is mainly to facilitate the comparison between the results predicted by Equation ( 18) and the data obtained by previous studies.…”