Multi-objective optimization of a mixed-flow pump impeller using modified NSGA-II algorithm

2015 ◽  
Vol 58 (12) ◽  
pp. 2122-2130 ◽  
Author(s):  
RenFang Huang ◽  
XianWu Luo ◽  
Bin Ji ◽  
Peng Wang ◽  
An Yu ◽  
...  
2019 ◽  
Vol 13 (1) ◽  
pp. 744-762 ◽  
Author(s):  
Jun-Won Suh ◽  
Hyeon-Mo Yang ◽  
Yong-In Kim ◽  
Kyoung-Yong Lee ◽  
Jin-Hyuk Kim ◽  
...  

2017 ◽  
Vol 31 (11) ◽  
pp. 5099-5106 ◽  
Author(s):  
Sung Kim ◽  
Ung-Been Jeong ◽  
Kyoung-Yong Lee ◽  
Jin-Hyuk Kim ◽  
Joon-Yong Yoon ◽  
...  

2019 ◽  
Vol 109 (S1) ◽  
pp. 31-36
Author(s):  
Franz Hahn ◽  
Julian Unterluggauer ◽  
Christian Bauer

Machines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 107
Author(s):  
Rongchao Jiang ◽  
Zhenchao Jin ◽  
Dawei Liu ◽  
Dengfeng Wang

In order to reduce the negative effect of lightweighting of suspension components on vehicle dynamic performance, the control arm and torsion beam widely used in front and rear suspensions were taken as research objects for studying the lightweight design method of suspension components. Mesh morphing technology was employed to define design variables. Meanwhile, the rigid–flexible coupling vehicle model with flexible control arm and torsion beam was built for vehicle dynamic simulations. The total weight of control arm and torsion beam was taken as optimization objective, as well as ride comfort and handling stability performance indexes. In addition, the fatigue life, stiffness, and modal frequency of control arm and torsion beam were taken as the constraints. Then, Kriging model and NSGA-II were adopted to perform the multi-objective optimization of control arm and torsion beam for determining the lightweight scheme. By comparing the optimized and original design, it indicates that the weight of the optimized control arm and torsion beam are reduced 0.505 kg and 1.189 kg, respectively, while structural performance and vehicle performance satisfy the design requirement. The proposed multi-objective optimization method achieves a remarkable mass reduction, and proves to be feasible and effective for lightweight design of suspension components.


2021 ◽  
Author(s):  
Varun Ojha ◽  
Giorgio Jansen ◽  
Andrea Patanè ◽  
Antonino La Magna ◽  
Vittorio Romano ◽  
...  

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.


Sign in / Sign up

Export Citation Format

Share Document