Multi-objective optimization design for a hydrodynamic retarder based on CFD simulation considering cavitation effect

2021 ◽  
pp. 095440622110145
Author(s):  
Konghua Yang ◽  
Chunbao Liu ◽  
Qingtao Wu ◽  
Xuesong Li
Keyword(s):  
Flow Field ◽  
Optimization Design ◽  
Cfd Simulation ◽  
Internal Flow ◽  
Structure Design ◽  
Multi Objective Optimization ◽  
Hexahedral Mesh ◽  
Nsga Ii ◽  
Multi Objective ◽  
Cavitation Effect

It is important to suppress cavitation phenomenon for lower vibration and noise, which can be realized by structure optimization to reduce cavitation bubbles of flow field. Nonetheless, performance factors in hydrodynamic retarder are usually conflicted when conducting a structure design, it is hard to simultaneously restrain cavitation and improve the retarding performance. In our study, a combination of comprehensive CFD simulation and multi-objective optimization is developed to improve the retarding torque ([Formula: see text]), lessen the volume of Retarder ([Formula: see text]) and reduce the volume of bubbles ([Formula: see text]) in the internal flow field. First, the elaborate CFD simulation calculation, included a refined hexahedral mesh and the stress-blended eddy simulation (SBES), is proposed to investigate the unsteady flow field considering the cavitation, and its accuracy is validated by experimental data. Then, the RSM (Respond Surface Method) approximation model is constructed by combination of DOE (Design of Method) and CFD methods. The NSGA-II (Non-Dominated Sorting Genetic Algorithm) is selected as multi-objective optimization algorithm, and the weight and scale factor of each sub objective are specified. The optimization results, verified by theoretical calculation, show that [Formula: see text] is increased by 22%–24%, [Formula: see text] is reduced by 32%–45% and [Formula: see text] is reduced by 1%. Furthermore, the comparison of the vortex distributions before and after optimization demonstrates that the optimization improves the flow field impact and pressure loss in the retarder and reduces the number of bubbles resulting in the increasing vortex. Additionally, parameters’ effect on the cavitation and the braking performance are analyzed to efficiently achieve the best comprehensive performance of the retarder design. The newly-developed optimization method, which can understand the optimization principle and guide a balance between the cavitation and the retarding performance improvement, will reduce huge trial cost and time cost in the manufacture.

Particles Separation of Hydrocyclone Based on CFD Simulation

2014 ◽  
Vol 535 ◽  
pp. 495-499
Author(s):  
Jing Song ◽  
Wei He ◽  
Zhe Kun Li ◽  
Wen Li Shi
Keyword(s):  
Flow Field ◽  
Optimization Design ◽  
Cfd Simulation ◽  
Internal Flow ◽  
Structure Design ◽  
Separation Performance ◽  
Flow Field Simulation ◽  
Research Status ◽  
Field Simulation

Analyzed the research status of hydrocyclone separation. By using CFD software, the important parameters of velocity and pressure in the hydrocyclone are analyzed and contrasted. Through simulation, it can accurately reflect the internal flow field, and can be used to predict the hydrocyclone separation performance. The results of flow field simulation will help to finish structure design of hydrocyclone and to provide the basis for the optimization design of hydrocyclone.

scholarly journals Design and characterization of effective solar cells

2021 ◽  
Author(s):  
Varun Ojha ◽  
Giorgio Jansen ◽  
Andrea Patanè ◽  
Antonino La Magna ◽  
Vittorio Romano ◽  
...  
Keyword(s):  
Solar Cells ◽  
Quantum Efficiency ◽  
Cost Benefit Analysis ◽  
Cost Minimization ◽  
Cell Structure ◽  
Cost Benefit ◽  
Structure Design ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective

AbstractWe propose a two-stage multi-objective optimization framework for full scheme solar cell structure design and characterization, cost minimization and quantum efficiency maximization. We evaluated structures of 15 different cell designs simulated by varying material types and photodiode doping strategies. At first, non-dominated sorting genetic algorithm II (NSGA-II) produced Pareto-optimal-solutions sets for respective cell designs. Then, on investigating quantum efficiencies of all cell designs produced by NSGA-II, we applied a new multi-objective optimization algorithm II (OptIA-II) to discover the Pareto fronts of select (three) best cell designs. Our designed OptIA-II algorithm improved the quantum efficiencies of all select cell designs and reduced their fabrication costs. We observed that the cell design comprising an optimally doped zinc-oxide-based transparent conductive oxide (TCO) layer and rough silver back reflector (BR) offered a quantum efficiency ($$Q_e$$ Q e ) of 0.6031. Overall, this paper provides a full characterization of cell structure designs. It derives relationship between quantum efficiency, $$Q_e$$ Q e of a cell with its TCO layer’s doping methods and TCO and BR layer’s material types. Our solar cells design characterization enables us to perform a cost-benefit analysis of solar cells usage in real-world applications.

Multi-objective optimization of squirrel cage fan for range hood based on Kriging model

2021 ◽  
pp. 095440622199586
Author(s):  
Qianhao Xiao ◽  
Jun Wang ◽  
Boyan Jiang ◽  
Weigang Yang ◽  
Xiaopei Yang
Keyword(s):  
Flow Rate ◽  
Optimization Design ◽  
Volume Flow Rate ◽  
Kriging Model ◽  
Volume Flow ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Squirrel Cage

In view of the multi-objective optimization design of the squirrel cage fan for the range hood, a blade parameterization method based on the quadratic non-uniform B-spline (NUBS) determined by four control points was proposed to control the outlet angle, chord length and maximum camber of the blade. Morris-Mitchell criteria were used to obtain the optimal Latin hypercube sample based on the evolutionary operation, and different subsets of sample numbers were created to study the influence of sample numbers on the multi-objective optimization results. The Kriging model, which can accurately reflect the response relationship between design variables and optimization objectives, was established. The second-generation Non-dominated Sorting Genetic algorithm (NSGA-II) was used to optimize the volume flow rate at the best efficiency point (BEP) and the maximum volume flow rate point (MVP). The results show that the design parameters corresponding to the optimization results under different sample numbers are not the same, and the fluctuation range of the optimal design parameters is related to the influence of the design parameters on the optimization objectives. Compared with the prototype, the optimized impeller increases the radial velocity of the impeller outlet, reduces the flow loss in the volute, and increases the diffusion capacity, which improves the volume flow rate, and efficiency of the range hood system under multiple working conditions.

scholarly journals Multi-Objective Optimization Design of a Notch Filter Based on Improved NSGA-II for Conducted Emissions

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 83213-83223 ◽  
Author(s):  
Lu Zhang ◽  
Hongjuan Ge ◽  
Ying Ma ◽  
Jianliang Xue ◽  
Huang Li ◽  
...  
Keyword(s):  
Optimization Design ◽  
Notch Filter ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Conducted Emissions

PD/PID Controller Design for Seismic Control of High-Rise Buildings Using Multi-Objective Optimization: A Comparative Study with LQR Controller

2017 ◽  
Vol 11 (03) ◽  
pp. 1750009 ◽  
Author(s):  
Sadegh Etedali ◽  
Saeed Tavakoli
Keyword(s):  
Optimization Design ◽  
Tall Buildings ◽  
Pid Controllers ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Seismic Control ◽  
High Rise ◽  
Lqr Controller ◽  
Structural Responses

This paper developed multi-objective optimization design of proportional–derivative (PD) and proportional–integral–derivative (PID) controllers for seismic control of high-rise buildings. The case study is an 11-story realistic building equipped with active tuned mass damper (ATMD). Four earthquakes and nine performance indices are taken into account to assess the performance of the controllers. To create a good trade-off between the performance and robustness of the closed-loop structural system, a non-dominated sorting genetic algorithm, NSGA-II, is employed. To evaluate the degree of robustness of the controllers, four structural models with uncertainties in the nominal model of the structure is considered. For comparison purposes, a linear quadratic regulator (LQR) controller is also designed in the numerical simulations. Simulation results show that the proposed PD and PID controllers significantly perform better than the LQR in reduction of structural responses. Also, it is shown that the LQR does not provide a good performance in strong earthquakes. However, PD and PID controllers are able to significantly reduce structural responses. Moreover, it is shown that the PID has a better performance than the PD. The results also show that the proposed controllers are capable of maintaining a desired performance in the presence of modeling errors. They also have several advantages over modern controllers in terms of simplicity and reduction of required sensors and computational resources in tall buildings.

The Multi-Objective Optimization Design of a Forklift Steering Mechanism

2014 ◽  
Vol 1049-1050 ◽  
pp. 884-887
Author(s):  
Qin Man Fan ◽  
Yong Hai Wu
Keyword(s):  
Hydraulic System ◽  
Optimization Design ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Oil Pump ◽  
System Pressure ◽  
Steering Mechanism ◽  
Steering Torque

The design and quality of steering mechanism is directly related to forklift traction, mobility, steering stability and safe operation. A multi-objective optimization model of the forklift steering mechanism is established in this paper. The objective function is minimum oil cylinder stroke difference and the minimum power oil pump. Steering torque, geometrical angles, geometry size and the hydraulic system pressure are used as constraint conditions. We use non dominated sorting genetic algorithm (NSGA II) based on the Pareto optimal concept to optimize and calculate model and get the optimal design of steering mechanism.

Study on Multi-Objective Optimization Design Method for SRHSC Beams

2011 ◽  
Vol 243-249 ◽  
pp. 362-365
Author(s):  
Shan Suo Zheng ◽  
Yi Hu ◽  
Qing Lin Tao ◽  
Zhi Qiang Li ◽  
Lei Li
Keyword(s):  
Optimization Design ◽  
Optimization Problems ◽  
Design Method ◽  
High Strength ◽  
Shear Capacity ◽  
Structure Design ◽  
Complex Method ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Design Variables

According to the thought of engineering optimization and the theory of composite structure design, the minimum of the project cost and the maximum of the diagonal shear capacity are taken as the optimization objectives whose importance can be adjusted by weighting factors and the linear weighted method is used to establish evaluation function which changes multi-objective into single-objective in optimization. Taking the various constraints into consideration and choosing the sensitive design variables, the mathematical model of the multi-objective optimization design for steel reinforced high-strength concrete beams is provided. Based on the optimization thought of the Complex Method, the nonlinear optimization problems are solved by MATLAB program.

scholarly journals Multi-Objective Optimization Design of a Novel Integral Squeeze Film Bearing Damper

Machines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 206
Author(s):  
Yipeng Zhang ◽  
Lidong He ◽  
Jianjiang Yang ◽  
Gang Zhu ◽  
Xingyun Jia ◽  
...  
Keyword(s):  
Optimization Design ◽  
Structural Parameters ◽  
Rotor System ◽  
Squeeze Film ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Practical Applications ◽  
Multi Objective ◽  
Transmitted Force

In order to better control the vibration of the rotor system so as to improve the stability and safety of the rotor, a novel vibration control solution is needed. In this paper, the multi-objective optimization problem is used for designing a novel integral squeeze film bearing damper (ISFBD). The method attempts to reduce the stiffness and stress convergence of ISFBD, which can greatly decrease the transmitted force of the rotor system and better use the damping effect to dissipate the vibration energy. The finite element model of ISFBD is established to analyze the stiffness and stress, and the correctness of the calculation is verified by setting up a stiffness test platform. The sensitivity of different structural parameters of stiffness and stress is analyzed by ANOVA. Meanwhile, the non-dominated sorting genetic algorithm (NSGA-II) and grey correlation analysis (GRA) algorithms are coupled for multi-objective optimization of stiffness and stress. The results indicate that optimized ISFBD can distribute 26.6% of the rotor system’s energy and reduce 59.3% of the transmitted force at the bearing location. It is also proved that the optimization strategy is effective, which can provide a useful method for ISFBD design in practical applications.

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