scholarly journals Optimization of Chlorine Bleaching Parameters for Indigo Denim Textile Based on the Model of Response Surface Model and Genetic Algorithm

2020 ◽  
Vol 1621 ◽  
pp. 012026
Author(s):  
Sheng Li ◽  
Xuejiao Fang ◽  
Xinyi Zhou ◽  
Bihan Bie ◽  
Jie Xu ◽  
...  
Author(s):  
Xiangfeng Wang ◽  
Songtao Wang ◽  
Wanjin Han

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.


2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Mamta Chauhan ◽  
Rajinder Singh Chauhan ◽  
Vijay Kumar Garlapati

Microbial enzymes from extremophilic regions such as hot spring serve as an important source of various stable and valuable industrial enzymes. The present paper encompasses the modeling and optimization approach for production of halophilic, solvent, tolerant, and alkaline lipase from Staphylococcus arlettae through response surface methodology integrated nature inspired genetic algorithm. Response surface model based on central composite design has been developed by considering the individual and interaction effects of fermentation conditions on lipase production through submerged fermentation. The validated input space of response surface model (with R2 value of 96.6%) has been utilized for optimization through genetic algorithm. An optimum lipase yield of 6.5 U/mL has been obtained using binary coded genetic algorithm predicted conditions of 9.39% inoculum with the oil concentration of 10.285% in 2.99 hrs using pH of 7.32 at 38.8°C. This outcome could contribute to introducing this extremophilic lipase (halophilic, solvent, and tolerant) to industrial biotechnology sector and will be a probable choice for different food, detergent, chemical, and pharmaceutical industries. The present work also demonstrated the feasibility of statistical design tools integration with computational tools for optimization of fermentation conditions for maximum lipase production.


Author(s):  
Weilin Yi ◽  
Hongyan Huang ◽  
Wanjin Han

The paper describes a new optimization strategy for computationally expensive design optimization problems of turbomachinery, combined with design of experiment (DOE), response surface models (RSM), genetic algorithm (GA) and a 3-D Navier-Stokes solver. Data points for response evaluations were selected by Latin hypercube design (LHD) and 3-dimensional 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 to obtain the optimum design. The above method was applied to the optimization design of NASA rotor37. The object was to maximize the adiabatic efficiency. An optimum leading edge line was found which produced a new 3-dimensional blade combined with sweep and composite bowing. As a result of this optimization, the adiabatic efficiency was successfully increased by 1.58%. It was found that the strategy of this paper provides a reliable design optimization method for turbomachinery blades at reasonable computing cost.


2006 ◽  
Vol 326-328 ◽  
pp. 1213-1216
Author(s):  
Jae Seob Kwak ◽  
Long Zhu Chi ◽  
Yang Koo ◽  
Yeong Deug Jeong ◽  
Man Kyung Ha

This study aimed to achieve optimization of grinding parameters for aluminum-based metal matrix composites using response surface model and genetic algorithm. Experiments were conducted in accordance with a preplanned orthogonal array. The effect of grinding parameters on surface roughness and grinding forces was evaluated and second-order response surface models were developed for predicting grinding outcomes. Optimal grinding parameters were determined from the genetic algorithm and the response surface models.


Author(s):  
Niu Zijie ◽  
Sun Zhijun ◽  
Zhu Hua ◽  
Zhang Jun

The stators of hollow-type traveling wave ultrasonic motors have certain problems stemming from their complex and hollow structures, significant differences between the two orthogonal modal frequencies, incomplete separation of the design model and interferential model, low-vibration amplitude, and significant localized inner stress during vibration, etc. In this paper, a dimensional parameterized finite elemental model for the motor was established by utilizing the finite elemental method. Afterwards, modal assurance criteria were used to identify the vibration models with various objectives for optimization established from this and integrating multiple objectives for optimization into a single optimization objective. Then a response surface model was established in the design space the Latin-hypercube random sampling method. Finally, a globally optimal solution was obtained according to the self-adaptive genetic algorithm and the response surface model. In order to prove the reasonableness of the optimized result, the stators are processed according to the sizes determined before and after the optimization. This paper describes the vibration of stators tested by a Doppler vibration tester. The Z-direction amplitude of the optimized stator changed from 1.0 µm to 2.5 µm. According to the testing results, the structural optimization plan used in this paper is reasonable and obviously helpful for vibration optimization of the stator.


Sign in / Sign up

Export Citation Format

Share Document