Fuzzy multi-objective optimization of a train suspension using response surface model

2000 ◽  
Author(s):  
Tael Lee ◽  
Kwangki Lee ◽  
Chankyoung Park
Keyword(s):  
Response Surface ◽  
Response Surface Model ◽  
Surface Model ◽  
Multi Objective Optimization ◽  
Multi Objective

Finite Element Analysis and Multi-Objective Optimization of the Precision Horizontal Machining Center Bed

2014 ◽  
Vol 889-890 ◽  
pp. 130-134
Author(s):  
Xue Yan Li ◽  
Wen Tie Niu ◽  
Jun Qiang Wang ◽  
Ling Jun Xue
Keyword(s):  
Response Surface ◽  
Response Surface Model ◽  
Least Square ◽  
Surface Model ◽  
Multi Objective Optimization ◽  
Element Analysis ◽  
Maximum Deformation ◽  
Multi Objective ◽  
Machining Center ◽  
Sample Points

In order to improve dynamic and static performance of the precision horizontal machining center, the method of multi-objective optimization based on the response surface model was applied for optimizing design of the bed structure. The design variables were the layout parameters of the rib plates. Sample points were obtained by the Box-Behnken design experiment, and responses of sample points were analyzed by SAMCEF. The maximum deformation of guide rails and the low-order natural frequency were extracted to fit the response surface model by least square method. The layout parameters of the rib plates were optimized through the application of multi-objective genetic algorithms. Then, relationship between the lightening holes and the performance were analyzed to determine the suitable diameter. The results verify the validity of the optimization method, and the paper provides methodological guidance for optimization of machine tool structural parts.

Design and optimization of spin micro-generator's rotating rack used in trajectory correction fuze under high-impact loadings

2018 ◽  
Vol 233 (13) ◽  
pp. 4421-4438
Author(s):  
Jianghai Hui ◽  
Min Gao ◽  
Xinpeng Li
Keyword(s):  
Elastic Modulus ◽  
Response Surface ◽  
Coupling Model ◽  
Response Surface Model ◽  
Surface Model ◽  
Multi Objective Optimization ◽  
Design And Optimization ◽  
Multi Objective ◽  
Trajectory Correction ◽  
Buffer Structure

Buffer structure is a traditional measure to improve the ammunition's performance of withstanding impact loadings during launch process. On that basis, this paper proposes a parametric optimization for the gasket, which is served as buffer structure in spin microgenerator's rotating rack used in trajectory correction fuze to effectively reduce the stress of bearings used in the rack. It is a finite element dynamic simulation based on rack-projectile-barrel coupling to acquire variation of the bearings' stress. A rack-projectile-barrel coupling model is built and the simulation pre-process is described. At first, the parametric analysis for the gasket is conducted. The effect of the gasket's axial thickness and elastic modulus on the bearings' stress is studied, and the results show that singly changing one of the two gasket's parameters cannot effectively reduce the two-ball bearings' stress. Then, based on the two gasket's parameters, the design of experiment method is applied with 25 sample points established. A kind of approximation, response surface model is created and its fitting accuracy is verified. Single-objective and multi-objective optimization are conducted based on the response surface model, respectively. And the multi-objective optimization for the gasket can successfully reduce the two bearings' stress to the value below the bearing material's yield strength. In addition, to check the optimization's effectiveness, an experiment is carried out and the results indicate that the gasket whose axial thickness and elastic modulus have been optimized can effectively improve the rotating rack's performance of withstanding impact loadings.

Multi-Objective Aerodynamic Design Optimization Based on Camber Line and Thickness Distribution for a Transonic Compressor Rotor

2008 ◽  
Author(s):  
Xiangfeng Wang ◽  
Songtao Wang ◽  
Wanjin Han
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Response Surface ◽  
Total Pressure ◽  
Optimization Problems ◽  
Thickness Distribution ◽  
Response Surface Model ◽  
Navier Stokes ◽  
Surface Model ◽  
Multi Objective

The paper describes a new optimization system for computationally expensive design optimization problems of turbomachinery, combined with design of experiment (DOE), response surface models (RSM), multi-objective genetic algorithm (MOGA) and a 3-D Navier-Stokes solver. A flow field solver code was developed based on three dimensional Navier-Stokes equations and validated by comparing computation results with experimental data. The improved non-dominated sorting genetic algorithm (NSGA-II) was used to solve the multi-objective problems. A constraint handling method without penalty function used to treat constrained optimization problems was improved and applied to constrained multi-objective problems. Data points for response evaluations were selected by the improved-hypercube sampling (IHS) algorithm and 3-D Navier-Stokes analysis was carried out at these sample points. The quadratic response surface model was used to approximate the relationships between the design variables and flow parameters. The genetic algorithm was applied to the response surface model to perform global optimization and obtain the optimum design. The above optimization method was applied to aerodynamic redesign of NASA Rotor37 with camber line and thickness distribution, the objects were to maximize the total pressure ratio and the adiabatic efficiency. Results showed the adiabatic efficiency improved by 0.7% and the total pressure by 0.66%. The multi-objective optimization design method is feasible.

Multi-Objective Optimization of Quality in Laser Cutting Based on Response Surface Model

2013 ◽  
Vol 756-759 ◽  
pp. 3712-3716
Author(s):  
Hui Juan Hao ◽  
Mao Li Wang ◽  
Feng Qi Hao
Keyword(s):  
Response Surface ◽  
Laser Cutting ◽  
Removal Rate ◽  
Quality Characteristics ◽  
Surface Model ◽  
Multi Objective Optimization ◽  
Yag Laser ◽  
Multi Objective ◽  
Important Means

Prediction and optimization of quality characteristics is an important means to improve the quality of laser cutting. Kerf width (KW) and material removal rate (MRR) are selected as the quality characteristics in this paper. The fitting response surface models (RSM) of KW and MRR are considered as the optimization objective function in pulsed Nd: YAG laser cutting of alloy steel for multi-objective optimization. An improved Pareto genetic algorithm is used in the optimization, and the significant factors have been found. The predicted results are basically consistent with the experimental. Therefore, the method used in this paper can be used for optimization of KW and MRR in pulse Nd: YAG laser cutting. The study can provide theoretical basis for the prediction and optimization of quality in laser cutting.

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