scholarly journals Modeling the Sorption of Ni2+ and Co2+ on Saprist Peat Using the Response Surface Methodology

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Emmanuel S. Asapo ◽  
Cynthia A. Coles ◽  
Leonard M. Lye
Keyword(s):  
Response Surface ◽  
Second Order ◽  
Sorptive Capacity ◽  
Surface Design ◽  
Response Surface Models ◽  
Wide Range ◽  
Surface Models ◽  
Simulated Wastewater ◽  
Ph Range ◽  
Percentage Sorption

A detailed study of the sorption of Ni2+ and Co2+ from simulated wastewater on saprist peat is presented. The significantly decomposed peat possessed a strong sorptive capacity that was maintained over a wide range of pH. With a metal concentration range of 50 to 200 mg/L, pH range of 3 to 10, peat dose of 2 to 40 g/L, and contact time of 12 to 24 h, batch experiments were conducted based on a four-factor Box-Behnken response surface design. The percentage removals of Ni2+ and Co2+ were analyzed using analysis of variance. Second order response surface models were developed with the significant factors and their interactions to predict the percentage sorption of Ni2+ and Co2+ independently. The prediction equations were verified with additional data not used in developing the equations. The study showed that the saprist peat could be a potential industrial metal adsorbent and the percentage of uptake of Ni2+ and Co2+ could be accurately predicted using the second order response surface models developed. Ni2+ uptake was greater for the two metals and reached a maximum value at just below a neutral pH and Co2+ uptake continued to increase from pH > 5, with higher uptake percentage at pH 10.

Cleaning and Bacteria Removal in Milking Systems by Alkaline Electrolyzed Oxidizing Water with Response Surface Design

2019 ◽  
Vol 62 (5) ◽  
pp. 1251-1258 ◽  
Author(s):  
Yu Liu ◽  
Chaoyuan Wang ◽  
Zhengxiang Shi ◽  
Baoming Li
Keyword(s):  
Water Treatment ◽  
Response Surface ◽  
Treatment Time ◽  
System Response ◽  
Surface Model ◽  
Response Surface Design ◽  
Surface Design ◽  
Response Surface Models ◽  
Surface Models ◽  
Bacteria Removal

Abstract. A wash cycle using an alkaline solution with a dissolved chemical detergent is a standard clean-in-place (CIP) process for cleaning milking systems. However, long-term chemical use may corrode equipment and create difficulties in wastewater treatment. This study investigated the potential for using alkaline electrolyzed oxidizing (EO) water as an alternative to alkaline chemical detergent for removal of microorganisms and adenosine triphosphate (ATP) on milking system materials. Laboratory trials were performed based on a Box-Behnken response surface design to assess the cleaning effect of alkaline EO water on three materials typically used in milking systems: stainless steel, rubber gasket, and polyvinyl chloride (PVC) hose. Results showed that alkaline EO water treatment was generally enhanced with increased treatment time, temperature, and pH, and their interaction effects were also observed in ATP removal. However, treatment time did not have a dominant role in cleaning PVC hose. Response surface models were developed to reliably predict detected microorganisms and relative light units (RLU) on the three materials after alkaline EO water treatment. Based on the response surface models, the three parameters for alkaline EO water cleaning were optimized as treatment time of 10.0 min, temperature of 61.8°C, and pH of 12, after which microorganisms and RLU were nearly undetectable. Alkaline EO water treatment with the optimized parameters had an equivalent or better cleaning ability compared to the commercial detergent, suggesting its potential as a cleaning and bacteria removal agent for milking systems. Keywords: Alkaline electrolyzed oxidizing water, Cleanliness, Milking system, Response surface model.

scholarly journals E-optimal designs for second-order response surface models

2014 ◽  
Vol 42 (4) ◽  
pp. 1635-1656 ◽  
Author(s):  
Holger Dette ◽  
Yuri Grigoriev
Keyword(s):  
Response Surface ◽  
Second Order ◽  
Optimal Designs ◽  
Response Surface Models ◽  
Surface Models

Elemental chlorine-free bleaching of North American hardwood kraft pulps: Evaluation of oxidant-reinforced extraction variables on overall bleaching optimization

TAPPI Journal ◽  
2013 ◽  
Vol 12 (10) ◽  
pp. 33-41 ◽  
Author(s):  
BRIAN N. BROGDON
Keyword(s):  
Response Surface ◽  
Chlorine Dioxide ◽  
North American ◽  
Yield Loss ◽  
Alkaline Extraction ◽  
Kraft Pulps ◽  
Pulp Bleaching ◽  
Response Surface Models ◽  
Elemental Chlorine ◽  
Surface Models

This investigation evaluates how higher reaction temperatures or oxidant reinforcement of caustic extraction affects chlorine dioxide consumption during elemental chlorine-free bleaching of North American hardwood pulps. Bleaching data from the published literature were used to develop statistical response surface models for chlorine dioxide delignification and brightening sequences for a variety of hardwood pulps. The effects of higher (EO) temperature and of peroxide reinforcement were estimated from observations reported in the literature. The addition of peroxide to an (EO) stage roughly displaces 0.6 to 1.2 kg chlorine dioxide per kilogram peroxide used in elemental chlorine-free (ECF) bleach sequences. Increasing the (EO) temperature by Δ20°C (e.g., 70°C to 90°C) lowers the overall chlorine dioxide demand by 0.4 to 1.5 kg. Unlike what is observed for ECF softwood bleaching, the presented findings suggest that hot oxidant-reinforced extraction stages result in somewhat higher bleaching costs when compared to milder alkaline extraction stages for hardwoods. The substitution of an (EOP) in place of (EO) resulted in small changes to the overall bleaching cost. The models employed in this study did not take into account pulp bleaching shrinkage (yield loss), to simplify the calculations.

Modeling and optimization of ultrasound‐assisted cinnamon extraction process using fuzzy and response surface models

2018 ◽  
Vol 42 (2) ◽  
pp. e12978
Author(s):  
Nur Cebi ◽  
Osman Sagdic ◽  
Abdulrahman Mohammed Basahel ◽  
Mohammed Abdullah Balubaid ◽  
Osman Taylan ◽  
...  
Keyword(s):  
Response Surface ◽  
Extraction Process ◽  
Modeling And Optimization ◽  
Response Surface Models ◽  
Surface Models ◽  
Ultrasound Assisted
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