## 4 Discussion  
The integration of bio-inspired dimple-type non-smooth surfaces into wide-range electric submersible centrifugal pumps (ESPs) demonstrates significant potential for enhancing hydraulic performance under dynamic reservoir conditions. The findings align with prior studies emphasizing the efficacy of bio-inspired surfaces in drag reduction and efficiency optimization [14; 15; 16; 17; 18; 19], while also extending their application to low-flow, multiphase flow regimes typical of offshore oilfields. This study corroborates the hypothesis that localized placement of non-smooth structures in high-shear-stress regions maximizes drag reduction benefits, as proposed by [PERSON] et al. [25]. The observed head gain of 12.98% (simulation) and 11.5% (experiment), alongside efficiency improvements of 8.55% and 4.6%, respectively, highlight the critical role of pressure surface trailing-edge optimization in suppressing boundary layer separation. However, the nonlinear relationship between dimple size and performance underscores the necessity of multi-parameter optimization to balance hydraulic gains with manufacturability constraints. Table 2 presents the relative deviations between experimental data and numerical predictions at different flow rates. As shown in Table 2, significant efficiency deviation occurs at low flow rates, where head is systematically overestimated while efficiency is consistently underestimated. Discrepancies between experimental and numerical results primarily stem from the following three mechanisms:  
* **Simplification of anisotropic wall roughness modeling:** Actual pump wall roughness exhibits anisotropy, whereas simulations adopt an isotropic model. This simplification underestimates turbulent dissipation, leading to inaccurate boundary layer predictions. At low flow rates, boundary layer separation exhibits heightened sensitivity to roughness anisotropy; neglecting this effect results in underestimated frictional losses and consequently overpredicted efficiency. Furthermore, the isotropic assumption causes overpredicted head at high flow rates (where actual head is lower due \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Flow Rate** & \multicolumn{2}{c}{**Head Deviation (\%)**} & \multicolumn{2}{c}{**Efficiency Deviation (\%)**} \\ \cline{2-5}
**(m\({}^{3}\)/d)** & **Original Impeller** & **Bionic Non-Smooth Impeller** & **Original Impeller** & **Bionic Non-Smooth Impeller** \\ \hline
50 & 3.30 & 1.24 & 13.92 & \(-\)11.64 \\
100 & 2.12 & 4.27 & 0.07 & \(-\)2.82 \\
150 & 0.07 & \(-\)5.46 & 2.24 & \(-\)3.81 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Relative deviations: experimental vs. simulated data. Figure 12: Efficiency comparison curves. to greater frictional losses), despite enhanced hydrodynamic influence of the bionic non-smooth surfaces. * **Microstructural defects in 3D-printed components:** Layer lines, pores, and other printing-induced defects increase surface roughness and induce unintended vortices, reducing actual efficiency. This effect is particularly pronounced for bionic non-smooth impellers: the 0.9 mm radius of dimple structures approaches the \(\pm\)0.15 mm printing tolerance, rendering experimental specimens highly susceptible to surface defects that persistently reduce efficiency below simulated values. * **Random deviations from flowmeter/pressure sensor calibration errors and mechanical vibrations. ** Furthermore, the limitations of the k-\(\omega\) turbulence model at high Reynolds numbers partially explain discrepancies between simulations and experiments, particularly in efficiency prediction accuracy. Its incomplete capture of secondary flow losses and strong turbulent mixing effects in actual flows exacerbates deviations in high-flow-rate regions. Nevertheless, the consistent trends observed between simulations and experiments demonstrate the model's robustness in near-wall flow characterization, supporting its utility in preliminary design stages.