Electromagnetic treatment-doubled electrocoagulation of humic acid in continuous mode using response surface method for its optimisation and application on two surface waters

2010 ◽  
Vol 22 (1-3) ◽  
pp. 311-329 ◽  
Author(s):  
Djamel Ghernaout ◽  
Abdelkader Mariche ◽  
Badiaa Ghernaout ◽  
Amara Kellil
Keyword(s):  
Humic Acid ◽  
Response Surface ◽  
Response Surface Method ◽  
Surface Waters ◽  
Continuous Mode ◽  
Surface Method ◽  
Electromagnetic Treatment

Removal of humic acid from composted hog waste by the white-rot fungus, Phanerochaete chrysosporium

2015 ◽  
Vol 72 (1) ◽  
pp. 92-98 ◽  
Author(s):  
Junying Liu ◽  
Yunmeng Song ◽  
Roger Ruan ◽  
Yuhuan Liu
Keyword(s):  
Humic Acid ◽  
Response Surface ◽  
Phanerochaete Chrysosporium ◽  
Response Surface Method ◽  
Experimental Results ◽  
White Rot ◽  
White Rot Fungus ◽  
Optimal Conditions ◽  
Surface Method ◽  
Strong Agreement

Abstract The potential hazards of humic acid (HA) associated with hog waste effluent, coupled with increasing awareness of environmental problems, have prompted many countries to control disposal of effluents into water bodies and to maximize removal of HA. Here we employed the white-rot fungus, Phanerochaete chrysosporium, to degrade the HA in composted hog waste effluent, evaluated by the response surface method. Preliminary experiments demonstrate that pH, temperature and quantity of inoculum are significant variables determining success of the fungus. In total, 13 experiments were conducted with three variables designated as A (pH), B (temperature) and C (inoculum amount). The optimal conditions for reduction of HA by P. chrysosporium are pH 6, 31.5°C and an inoculum quantity of 5.86 g. Predicted and experimental results exhibit strong agreement, indicating efficiency in the model obtained by response surface method. Therefore, P. chrysosporium is an effective micro-organism for removal of HA from composted hog waste effluent.

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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