Optimization Design of Energy-Saving Mixed Flow Pump Based on MIGA-RBF Algorithm

Based on the three-dimensional design platform, this article conducted parametrization of blade leading and trailing edge positions, and analyzed the influence of different position parameters on mixed-flow pump hydraulic performance and internal flow with model test and numerical simulation. The results showed that the hydraulic efficiency η of a mixed-flow pump increased slightly when the position parameter θh of the blade leading edge on the hub increased, and η increased significantly when the position parameter θt of the blade leading and trailing edge positions on the shroud increased. However, with θt increasing, the growth rate of η decreased. Numerical simulation has shown that by selecting a proper value of θt, the impeller energy conversion capacity can be effectively improved, and the distributions of static pressure and total energy can be more uniform in the flow passage. Meanwhile, with θt increasing, blade angle on the blade trailing edge decreased. Correspondingly, the absolute velocity in the outlet zone decreased, and the hydraulic loss in the outlet zone also decreased, which is beneficial to improving hydraulic efficiency of the mixed-flow pump. Within the value range of 7–9°, with different combinations of position parameter θt1 of the blade leading edge on the shroud and position parameter θt2 of the blade trailing edge on the shroud, the mixed-flow pump hydraulic efficiency η and blade wrap angle ϕ show a linear positive correlation, suggesting that an increase in ϕ could significantly improve impeller energy conversion capacity. Compared to θt1, θt2 has a more significant influence on ϕ and η. Thus, the value of θt2 should be carefully attended to during design process.

Class function/shape function transformation (CST) is an advanced geometry representation method employed to generate airfoil coordinates. Aiming at the morbidity of the CST coefficient matrix, the pivot element weighting iterative (PEWI) method is proposed to improve the condition number of the ill-conditioned matrix in the CST. The feasibility of the PEWI method is evaluated by using the RAE2822 and S1223 airfoil. The aerodynamic optimization of the S1223 airfoil is conducted based on the Isight software platform. First, the S1223 airfoil is parameterized by the CST with the PEWI method. It is very significant to confirm the range of variables for the airfoil optimization design. So the normalization method of design variables is put forward in the paper. Optimal Latin Hypercube sampling is applied to generate the samples, whose aerodynamic performances are calculated by the numerical simulation. Then the Radial Basis Functions (RBF) neural network model is trained by these aerodynamic performance data. Finally, the multi-island genetic algorithm is performed to achieve the maximum lift-drag ratio of S1223. The results show that the robustness of the CST can be improved. Moreover, the lift-drag ratio of S1223 increases by 2.27% and the drag coefficient decreases by 1.4%.

Collaborative optimization with relaxation factor is proposed for the lines design of an underwater vehicle. The hydrodynamic performances and energy consumption are considered in optimization framework. Hydrodynamic performances include the resistance, sway force and yaw moment. The efficient power of the propeller is selected to reflect the energy consumption. Analytic hierarchy process (AHP) combined with Delphi method is used to allocate the weights of disciplines in the objective function at the top level. A gradient-based algorithm, sequential quadratic programming (SQP) in combination with an intelligent-based algorithm, the multi-island genetic algorithm (MIGA) is taken into account as the optimization algorithm. To increase the efficiency of optimization, an approximate model based on optimal Latin hypercube and radial basis function (RBF) is introduced to replace the time-consuming discipline analysis model. Full-appendage SUBOFF model is used to test the proposed optimization scheme. The optimization results show that the drag of the underwater vehicle is reduced by 2.05 %, the lateral force by 6.38 %, the yaw moment by 5.90 %, and the energy consumption by 2.15 %. Compared with a single algorithm (e.g., PSO), the proposed hybrid algorithm (MIGA-SQP) reduces the value of the comprehensive objective function by 2.5-4.8 %.The innovations of this paper are as follows: 1. The Delphi-AHP method is combined with the cooperative optimization of relaxation factors to improve the objectivity of weights; 2. An OLH-RBF surrogate model is constructed, which increases the CFD calculation efficiency by 4 times.

HVAC systems are major energy consumers in buildings, accounting for 30% to 50% of total energy usage. Supply outlets, as the terminal devices of HVAC systems, significantly influence the system’s operational performance, energy consumption, and indoor environmental quality. However, current designs and performance optimizations of supply outlets still encounter challenges such as high resistance and low energy efficiency, posing substantial obstacles to building energy conservation, indoor air quality, and fan energy consumption. To address the optimization of resistance reduction and efficiency enhancement for local components (specifically the supply outlets) in HVAC systems, this study focuses on the commonly used disk diffusers. Utilizing a combined research methodology that integrates theoretical analysis, numerical simulation, full-scale experiments, surrogate model prediction, and multi-island genetic algorithm optimization, this study investigates both fluid flow and resistance distribution characteristics. The ADEI comprehensive evaluation index is employed to assess the operational energy efficiency of the disk diffusers. Based on an optimized Latin hypercube sampling method and incorporating RBF surrogate models, surrogate models relating the structural parameters of disk diffusers to their resistance and range are developed. A multi-island genetic algorithm is then applied to optimize the RBF surrogate models. The optimization results demonstrate that the new type of disk diffuser achieves a 33.07% reduction in ADEI compared to traditional disk diffusers, while resistance decreases by 23.10% and jet length increases by 7.19%.

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.

Calibration methodology for energy management system of a plug-in hybrid electric vehicle

In order to improve the endurance of pure electric vehicles, improving the energy utilisation is an effective way to increase the mileage. Energy utilisation can be effectively improved by using the new structure of dual motor coupling drive system as the power source. In the new structure, the energy utilisation is improved by eight mode switching. In this paper, CRUISE is used to build the vehicle model of pure electric vehicle, its control strategy is established by Simulink. The reliability of the model and control strategy is verified by using CRUISE and Simulink joint simulation method. The preset parameters in the control strategy are optimised by Multi Island Genetic Algorithm, making the model, parameters and control strategy more accurate so as to provide a scheme for the research of improving the energy utilisation rate of pure electric vehicles.

This paper presents three different multi-objective optimization strategies for a high specific speed centrifugal volute pump design. The objectives of the optimization consist of maximizing the efficiency and minimizing the cavitation while maintaining the Euler head. The first two optimization strategies use a 3D inverse design method to parametrize the blade geometry. Both meridional shape and 3D blade geometry is changed during the optimization. In the first approach Design of Experiment method is used and the efficiency computed from CFD computations, while cavitation is evaluated by using minimum pressure on blade surface predicted by 3D inverse design method. The design matrix is then used to create a surrogate model where optimization is run to find the best tradeoff between cavitation and efficiency. This optimized geometry is manufactured and tested and is found to be 3.9% more efficient than the baseline with little cavitation at high flow. In the second approach the 3D inverse design method output is used to compute the efficiency and cavitation parameters and this leads to considerable reduction to the computational time. The resulting optimized geometry is found to be similar to the more computationally expensive solution based on 3D CFD results. In order to compare the inverse design based optimization to the conventional optimization an equivalent optimization is carried out by parametrizing the blade angle and meridional shape. Two different approaches are used for conventional optimization one in which the blade angle at TE is not constrained and one in which blade angles are constrained. In both cases larger variation in head is obtained when compared with the inverse design approach. This makes it impossible to create an accurate surrogate model. Furthermore, the efficiency levels in the conventional optimization is generally lower than the inverse design based optimization.

Counter-rotating blade rows in single stage machines have been widely investigated in several applications like naval propulsion [1], axial fan [2] and axial pump design [3]. Previous publications have presented this design philosophy as a promising way to improve efficiency and cavitation performance [4]. Differently the goal of the presented design is to achieve lower required rotational speeds and at the same time a higher power density ratio, indirectly improving also the cavitation’s performance, aspiring actually to a compact design. However, a literature survey did not produce any evidence of significant advantage in axial-flow machines from this design philosophy in terms of machine power density. This paper presents a preliminary analysis of the applicability of the counter-rotating impeller concept on mixed-flow and radial-flow pumps. The design example presented in this paper constitutes a mixed-flow first rotor with a radial second rotor that rotates in opposite direction. A 1-D design model demonstrates that power density coefficient has a maximum for optimum speeds of the rotors range. The design example parameters were selected based on the highest power density coefficient and efficiency. Unlike most published literature where the rotor speed ratios are not fixed, instead the speeds can be independently varied through two separate electric drives. Both the front and rear rotor were developed using multi-streamline curvature analysis which combines fluid dynamic loss model [5] with a slip model at the rotor exit [6]. Several hypotheses were considered to determine the most significant and independent parameters that run through a response surface optimizer tool, scripted in MATLAB®. It detects optimum specific speed for the rotors which maximizes the benefits of counter-rotating impeller design compared to rotor-stator machine with same design point. Assuming steady numerical approximation error, the fitness function of the optimizer tool is based on steady state CFD results. The fitness function depends on total head and hydraulic efficiency, which show a maximum as a result. Optimum geometries were identified and one was chosen for manufacturing and testing in a test rig. Transient CFD analysis was also done to determine volute losses and incidence losses between first and second rotor and pressure pulsations generated. At this stage, manufacturing of hydraulic components of test model is in progress, while the mechanical design of the machine is close to completion.

To enhance the hydraulic performance and operational stability of a full tubular pump (FTP), this study conducts a systematic investigation and optimization of the impeller structural parameters based on computational fluid dynamics (CFD) simulations and multi-parameter optimization techniques. The number of blades and hub ratio were selected as key geometric variables, and their effects on the head and efficiency characteristics were analyzed using a single-factor approach. The results indicate that increasing the blade number improves the head but shifts the best-efficiency point toward a lower flow rate. In contrast, decreasing the hub ratio deteriorates the low-flow performance while slightly improving the high-flow performance, exhibiting a nonlinear hydraulic response. Subsequently, a surrogate model was constructed using a radial basis function (RBF) neural network (NN) within the Isight platform, and a multi-objective optimization was performed employing the multi-island genetic algorithm (MIGA). Under the constraint of an approximately constant specific speed, the blade outlet angle and blade cascade solidity were identified as the dominant factors influencing head and efficiency. The optimized impeller demonstrated a remarkable improvement in overall efficiency, a more uniform distribution of the blade boundary vorticity flux (BVF), and a significantly improved internal flow structure.

In this article, design optimization was carried out to improve the suction performance and efficiency of a mixed-flow pump impeller. Commercial computational fluid dynamics code and a response surface method were used in the optimization to design a mixed-flow pump impeller. When it comes to a mixed-flow pump, the two main research objectives namely efficiency and suction performance tend to contradict. It is very important that the design technology improves the suction performance while maintaining high efficiency. Meridional plane and vane plane development variables were defined in the design of the impeller. The meridional plane expresses the shapes and sizes of the blades, while the vane plane development describes the impeller inlet and outlet angles as well as the blade angle distribution. The blade angle distribution of the impeller was designed using the traditional method by which inlet and outlet angles are connected smoothly. The surface response method was applied to the design variables of the impeller inlet part in this design optimization because they influence the performance of the mixed-flow pump. Objective functions were set to satisfy the total head at the design flow rate as well as to improve efficiency and suction performance. Design variables of the impeller inlet part of the mixed-flow pump and the changes in performance were analyzed in order to produce the optimal shape. The performance of the optimally designed shape was verified by numerical analysis, and the reliability of the test result was checked by comparative analysis against the reference model.

Optimal design of an autonomous underwater helicopter's shape based on combinatorial optimization strategy

Long-term rotary left ventricular assist devices (LVADs) are increasingly employed to bridge patients with end-stage heart failure to transplant or as a destination therapy. Significant recent device development has increased patient support times, shifting further development focus toward physiologically sensitive control of the pump operation. Sensorless control of these devices would benefit from increased observability of the ventricular volume/preload to the pump, in order to regulate flow based on preload, imitating the native Frank-Starling flow control. Monitoring the transmitted flow pulse through the pump has been used as a surrogate for preload, although means of maximizing its transmission are not clear. However, it is known that a flat hydraulic performance curve of the rotary pump induces high changes in flow for a given change in pressure head. The aim of this study was to determine geometric pump parameters responsible for increasing this flow pulse transmission and to demonstrate this increase in vitro. The sensitivity of the performance gradient to blade angles, blade heights, blade clearance, and channel areas were studied. Resulting pressure head, flow, and hydraulic efficiency were analyzed with respect to textbook designed procedures. Then pumps with comparably "flat" and "steep" performance curves were used to simulate LVAD support in vitro over a range of pump flow rates to observe the transmitted flow pulsatility. It was found that an outlet blade angle of 90°, inlet blade angle between 25 and 45°, and large throat area generated a "flatter" performance curve. The transmitted flow pulsatility through a pump with a flat performance curve was 68% higher than that of a steep performance curve at a flow rate of 5 L/min. Substantial gains in the observability of LVAD preload/resident blood volume in the ventricle exist through the careful selection of specific pump geometries.

Hyperparameters allow metaheuristics to be tuned to a wide range of problems. However, even though formalized tuning of metaheuristic parameters can affect the quality of the solution, it is rarely performed. The empirical selection method and the trial-and-error method are the primary conventional parameter selection techniques for optimization heuristics. Both require a priori knowledge of the problem and involve multiple experiments requiring significant time and effort, yet neither guarantees the attainment of optimum parameter values. Of the studies that perform formal parameter tuning, experimental design is the most commonly used method. Although experimental design is feasible for systematic experimentation, it is also time-consuming and requires extensive effort for large optimization problems. The computational effort in this study refers to the number of experimental runs required for hyperparameter tuning, not the computational time for each run. This study proposes a simpler, faster method based on an optimized Latin hypercube sampling (OLHS) technique augmented with response surface methodology for estimating the best hyperparameter settings for a hybrid simulated annealing algorithm. The method is applied to solve the aircraft landing problem with time windows (ALPTW), a combinatorial optimization problem that seeks to determine the optimal landing sequence within a predetermined time window while maintaining minimum separation criteria. The results showed that the proposed method improves sampling efficiency, providing better coverage and higher accuracy with 70% fewer sample points and only 30% of the total runs compared to full factorial design.

In order to solve the problems arising from the manual calibration method in the developing process of vehicle automatic transmission control unit (TCU), known as time-consuming, heavy workload, high cost and over-dependence on subjective experience, this article researches on a virtual calibration method based on an approximate model to obtain optimal parameters for TCU. The neural network approximate model is established from the test data chosen with the method of DoE (Design of Experiment). The virtual calibration method is then conducted through Optimal Latin Hypercube Design (OLHD) and multi-island genetic algorithm (MIGA) to search the optimal parameters. By comparing the new calibration method with original manual one on the condition of gear 1 up to gear 2, the result shows that the new method can increase the efficiency significantly.