Optimization for Extraction of Astaxanthin from Shrimp Shell Using Response Surface Method

2011 ◽  
Vol 396-398 ◽  
pp. 609-613
Author(s):  
Hong Chao Liu ◽  
Peng Li ◽  
Guang Wang ◽  
He Ping Yu ◽  
Zong Qiang Zeng ◽  
...  
Keyword(s):  
Sodium Hydroxide ◽  
Response Surface ◽  
Organic Solvents ◽  
Response Surface Method ◽  
Extraction Method ◽  
Alkali Solution ◽  
Surface Method ◽  
Shrimp Shell ◽  
Shrimp Head ◽  
Bioactive Substance

In this work, the extraction of astaxanthin i.e. bioactive substance in the shrimp head and shell was studied. The extraction method of astaxanthin was established: the alkali method and organic solvents method were combined to extract astaxanthin, the solvent of the alkali solution was ethanol:water =4:1, dichloromethane was selected as the extractant. The best extraction conditions for astaxanthin were optimized: the concentration of sodium hydroxide was 1.4mol / L, the optimum extaction process was at 54°C for 24 h, and the ration of solid to liquid was 8:1. In this condition, the absorption value of astaxanthin was 1.2048, the concentration of astaxanthin was 3.26μg/mL, which was equivalent to 32.6 μg/g dry shrimp shell.

A Proposal of PSO with Presumption Function of the Solution Landscape by Response Surface Method

2014 ◽  
Vol 134 (9) ◽  
pp. 1293-1298
Author(s):  
Toshiya Kaihara ◽  
Nobutada Fuji ◽  
Tomomi Nonaka ◽  
Yuma Tomoi
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Surface Method

scholarly journals Creep-Based Reliability Evaluation of Turbine Blade-Tip Clearance with Novel Neural Network Regression

Materials ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 3552 ◽  
Author(s):  
Chun-Yi Zhang ◽  
Jing-Shan Wei ◽  
Ze Wang ◽  
Zhe-Shan Yuan ◽  
Cheng-Wei Fei ◽  
...  
Keyword(s):  
Neural Network ◽  
High Pressure ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Tip Clearance ◽  
Strong Nonlinearity ◽  
Surface Method ◽  
Blade Tip ◽  
Blade Tip Clearance

To reveal the effect of high-temperature creep on the blade-tip radial running clearance of aeroengine high-pressure turbines, a distributed collaborative generalized regression extremum neural network is proposed by absorbing the heuristic thoughts of distributed collaborative response surface method and the generalized extremum neural network, in order to improve the reliability analysis of blade-tip clearance with creep behavior in terms of modeling precision and simulation efficiency. In this method, the generalized extremum neural network was used to handle the transients by simplifying the response process as one extremum and to address the strong nonlinearity by means of its nonlinear mapping ability. The distributed collaborative response surface method was applied to handle multi-object multi-discipline analysis, by decomposing one “big” model with hyperparameters and high nonlinearity into a series of “small” sub-models with few parameters and low nonlinearity. Based on the developed method, the blade-tip clearance reliability analysis of an aeroengine high-pressure turbine was performed subject to the creep behaviors of structural materials, by considering the randomness of influencing parameters such as gas temperature, rotational speed, material parameters, convective heat transfer coefficient, and so forth. It was found that the reliability degree of the clearance is 0.9909 when the allowable value is 2.2 mm, and the creep deformation of the clearance presents a normal distribution with a mean of 1.9829 mm and a standard deviation of 0.07539 mm. Based on a comparison of the methods, it is demonstrated that the proposed method requires a computing time of 1.201 s and has a computational accuracy of 99.929% over 104 simulations, which are improvements of 70.5% and 1.23%, respectively, relative to the distributed collaborative response surface method. Meanwhile, the high efficiency and high precision of the presented approach become more obvious with the increasing simulations. The efforts of this study provide a promising approach to improve the dynamic reliability analysis of complex structures.

scholarly journals The optimization of Sumbawa manganese ore beneficiation using response surface method (RSM)

2021 ◽  
Author(s):  
Alfikri Khair ◽  
Haryudini A. Putri ◽  
Suprapto Suprapto ◽  
Yatim L. Ni’mah
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Manganese Ore ◽  
Surface Method
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