This work presents a three-objective design optimization of a centrifugal pump impeller to reduce flow recirculation and cavitation using three-dimensional (3D) Reynolds-averaged Navier–Stokes equations. A cavitation model was used to simulate the multiphase cavitating flow inside the centrifugal pump. The numerical results were validated by comparing them with experimental data for the total head coefficient and critical cavitation number. To achieve the optimization goals, blockage at 50% of the design flow rate, hydraulic efficiency at the design flow rate, and critical cavitation number for a head-drop of 3% at 125% of the design flow rate were selected as the objective functions. Based on the results of the elementary effect (EE) method, the design variables selected were the axial length of the blade, the control point for the meridional profile of the shroud, the inlet radius of the blade hub, and the incidence angle of tip of the blade. Kriging models were constructed to approximate the objective functions in the design space using the objective function values calculated at the design points selected by Latin hypercube sampling (LHS). Pareto-optimal solutions were obtained using a multi-objective genetic algorithm (MOGA). Six representative Pareto-optimal designs (POD) were analyzed to evaluate the optimization results. The PODs showed large improvements in the objective functions compared to the baseline design. Thus, both the hydraulic performance and the reliability of the centrifugal pump were improved by the optimization.

Multiphase pumps are core equipment for offshore plant industry. They are utilized in diverse areas. According to a report about the tendency of multiphase pumps for offshore plant, a helico-axial pump is the most preferred. A helico-axial pump with advanced technologies is widely known to have large handling capacity and operability even at high GVF ranges. However, its disadvantage is that its mechanical efficiency is lower than other multiphase pumps. Because of this, a numerical optimization was performed in this study to enhance the hydraulic performance of multiphase pumps. Before numerical optimization, reliability verification of numerical analysis for single-phase and multiphase flow was carried out. To perform a single objective optimization for high efficiency, design variables and ranges were selected. The single objective optimization was conducted for both impeller and diffuser. The objective function was evaluated at design points using Latin-hypercube sampling, one experiment technique, in design ranges. The performance of the experiment sets was evaluated using advanced computational fluid dynamics. After that, the response surface of a second-order polynomial function which was produced based on the performance evaluation results was used to find the optimal point. The results showed remarkable increases in a higher performance level than the base model. The reason for performance improvement was analyzed through comparison of the internal flow field. Additionally, numerical results were compared to results of performance evaluation through experiment.

Most multi-phase pumps used in crude oil production have been developed to satisfy certain pressure specifications. In the design of these pumps, the flow characteristics of the posterior stage are different from those of the prior stage. For this reason, the design of the second stage needs to be supplemented. To optimize performance in this stage, multi-objective optimization to simultaneously increase pressure and efficiency is reported in this article. Flow analyses of the single and multiple phases of the multi-phase pump were conducted by solving three-dimensional steady Reynolds-averaged Navier–Stokes equations. For the numerical optimization, two design variables related to the blade inlet angle were selected. The impeller and the diffuser blades were optimized using a systematic optimization technique combined with a central composite method and a hybrid multi-objective evolutionary algorithm coupled with a surrogate model. The selected optimal model yielded better hydrodynamic performance than the base model, and reasons for this are investigated through internal flow field analysis.

This research aimed to systematically maximize hydraulic efficiency and suction specific speed for mixed-flow pump using a commercial CFD packages and optimization tool. First, mixed-flow pump was initially designed according to the traditional design method, and then the blade shape was re-designed by focusing on the hydraulic efficiency. Second, the efficiency-oriented optimum design was selected as the reference model. The objective was to improve the suction specific speed under the specific condition of the mixed-flow pump through the multi-objective optimization technique. The incidence angles and meridional plane were optimized through a systematic optimization process, namely, central composite method and response surface approximation. The optimization results indicated that the suction specific speed values of the reference and optimum model were 88.13 and 289.65, respectively. Furthermore, the hydraulic efficiency was kept within ± 1% compared to the reference model as the constraint condition. The hydraulic efficiency of the reference and optimum model were 91.44% and 90.40%, respectively. The reasons for the improved efficiency and suction performance were investigated through internal flow field analysis. Finally, the reliability of the optimization was demonstrated by comparing the numerical and experimental results.