RSM and ANN modeling for electrocoagulation of copper from simulated wastewater: Multi objective optimization using genetic algorithm approach

Bhatti, Manpreet S.; Kapoor, Dhriti; Kalia, Rajeev K.; Reddy, A. S.; Thukral, Ashwani Kumar

doi:10.1016/j.desal.2011.01.083

Cited by 168 publications

(67 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A decrease in the sorption capacity at higher speed of agitation may be attributed to improper contact between the dye ions and the binding sites on the biomass, as the suspension is no longer homogenous due to vortex formation, which makes the adsorption of dye ions difficult [38,39]. The effect of contact time on the removal of RO 13 dye indicated that a longer contact time favored the reaction toward the equilibrium Locating the region of optimum response by the PSA In the current investigation, PSA was employed to move from the current operating conditions to the optimum region in the most efficient way by using the minimum number of experiments.…”

Section: Resultsmentioning

confidence: 99%

Statistical optimization of biosorption of Reactive Orange 13 by dead biomass of Rhizopus arrhizus NCIM 997 using response surface methodology

Saraf¹,

Vaidya²

2015

Int J Ind Chem

View full text Add to dashboard Cite

Background Increasing environmental awareness is forcing waste creators to consider new options such as biosorption for the disposal of colored wastewaters. Due to prohibitive costs of commercially available activated carbon, low-cost biosorbents with high adsorption capacities have gained increasing attention. The present investigation deals with utilization of a low-cost, fungal biosorbent of Rhizopus arrhizus NCIM 997 and optimization of conditions for the removal of Reactive Orange 13 dye from an aqueous solution using sequential statistically designed experiments.Results Plackett-Burman design with six independent variables (pH, temperature, biosorbent dosage, dye concentration, contact time and speed of agitation) was used to identify the most important factors influencing dye biosorption. Path of steepest ascent and central composite design were used to move toward the vicinity of the optimum operating conditions and to determine the optimum levels of the variables, respectively. The maximum biosorption capacity (133.63 mg/g) was obtained under the following conditions: pH 2.0, dye concentration 114 mg/L, biosorbent dosage 0.8 g/L and speed of agitation 85 rpm. Validation experiments and application of artificial neural network showed excellent correlation between predicted and experimental values. Conclusions Response surface methodology using central composite design was employed at the specified combinations of four independent significant factors identified by Plackett-Burman design. The fitted model was used to arrive at the best operating conditions to achieve a maximum response. Sequential optimization was successfully used to increase biosorption by 49.04 %. The study indicated that the fungal biosorbent was an effective and economical alternative for the removal of Reactive Orange 13 dye.

show abstract

Section: Resultsmentioning

confidence: 99%

Statistical optimization of biosorption of Reactive Orange 13 by dead biomass of Rhizopus arrhizus NCIM 997 using response surface methodology

Saraf¹,

Vaidya²

2015

Int J Ind Chem

View full text Add to dashboard Cite

show abstract

“…Main aim of RSM is to obtain an optimal response. Researchers have used various techniques in RSM including Central Composite Design (CCD) [25,26], Box-Behnken statistical experiment design (BBD) [27,28], and two-level full factorial design (FFD) [29] to predict the ultimate response.…”

Section: Response Surface Methodologymentioning

confidence: 99%

Application of Central Composite Design approach for removal of chromium (VI) from aqueous solution using weakly anionic resin: Modeling, optimization, and study of interactive variables

Bajpai

Gupta

Dey

et al. 2012

Journal of Hazardous Materials

121

View full text Add to dashboard Cite

“…Various methods in RSM such as Central Composite Design (CCD) [16,17], Box Behnken experimental design [18,19] and two-level full factorial design [20] have been used by researchers so as to predict the ultimate response(s). CCD allows the calculation of linear and quadratic effects, as well as interactions for any pair of selected parameters with the best possible precision at minimum number of experiments.…”

Section: Experimental Designmentioning

confidence: 99%

High flux electrospun nanofiberous membrane: Preparation by statistical approach, characterization, and microfiltration assessment

Shahabadi

Mousavi

Bastani

2016

Journal of the Taiwan Institute of Chemical Engineers

View full text Add to dashboard Cite

RSM and ANN modeling for electrocoagulation of copper from simulated wastewater: Multi objective optimization using genetic algorithm approach

Cited by 168 publications

References 32 publications

Statistical optimization of biosorption of Reactive Orange 13 by dead biomass of Rhizopus arrhizus NCIM 997 using response surface methodology

Statistical optimization of biosorption of Reactive Orange 13 by dead biomass of Rhizopus arrhizus NCIM 997 using response surface methodology

Application of Central Composite Design approach for removal of chromium (VI) from aqueous solution using weakly anionic resin: Modeling, optimization, and study of interactive variables

High flux electrospun nanofiberous membrane: Preparation by statistical approach, characterization, and microfiltration assessment

Contact Info

Product

Resources

About