scholarly journals Application of response surface methodology for color removing from dyeing effluent using de-oiled activated algal biomass

2021 ◽  
Vol 45 (1) ◽  
Author(s):  
Samar A. El-Mekkawi ◽  
Rehab A. Abdelghaffar ◽  
Fatma Abdelghaffar ◽  
S. A. Abo El-Enin
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Industrial Development ◽  
Industrial Effluents ◽  
Quadratic Model ◽  
Activation Process ◽  
Prime Concern ◽  
Desirability Approach ◽  
Dyeing Effluent

Abstract Background Conservation of the ecosystem is a prime concern of human communities. Industrial development should adopt this concern. Unfortunately, various related activities release lots of noxious materials concurrently with significant leakage of renewable resources. This work presents a new biosorbent activated de-oiled microalgae, Chlorella vulgaris, (AC) for biosorption of Acid Red 1 (AR1) from aqueous solution simulated to textile dyeing effluent. The biosorption characteristics of AC were explored as a function of the process parameters, namely pH, time, and initial dye concentration using response surface methodology (RSM). Results Optimization is carried out using the desirability approach of the process parameters for maximum dye removal%. The ANOVA analysis of the predicted quadratic model elucidated significant model terms with a regression coefficient value of 0.97, F value of 109.66, and adequate precision of 34.32 that emphasizes the applicability of the model to navigate the design space. The optimization depends on the priority of minimizing the time of the process to save energy and treating high concentrated effluent resulted in removal % up to 83.5%. The chemical structure and surface morphology of AC, and the dye-loaded biomass (AB) were characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy-dispersive X-ray analysis (EDX), and transmission electron microscope (TEM). The activation process transforms the biomass surface into a regular and small homogeneous size that increases the surface area and ultimately enhances its adsorption capacity Conclusion The optimization of the process parameters simultaneously using RSM performs a high-accurate model which describes the relationship between the parameters and the response through minimum number of experiments. This study performed a step towards an integrated sustainable solution applicable for treating industrial effluents through a zero-waste process. Using the overloaded biomass is going into further studies as micronutrients for agricultural soil.

Multi-objective Optimization of UV Spot Curing Technique of Slider - Suspension Attachment Process Using Response Surface Methodology Approach

2021 ◽  
Author(s):  
Santi Pumkrachang
Keyword(s):  
Response Surface Methodology ◽  
Shear Strength ◽  
Response Surface ◽  
Process Parameters ◽  
Epoxy Adhesive ◽  
Quadratic Model ◽  
Uv Curable ◽  
Multi Objective ◽  
Validation Experiment ◽  
Cure Time

The ultraviolet (UV) curing of slider-suspension attachment is going to change from a manual to an automated process. As a result, the bonding parameters of adhesive between slider and suspension needs to be optimized. This paper aims to study two output responses of the UV curable epoxy adhesive i.e., shear strength force and pitch static attitude (PSA) of the joint between slider and suspension in a head gimbal assembly (HGA). Four process parameters were investigated using response surface methodology (RSM) based on face-centered central composite design (FCCD). The RSM was applied to establish a mathematical model to correlate the significance of process parameters and the responses. Then the based multi-objective was applied to determine a quadratic model and obtained the output maximization at 224 g of shear strength force and PSA value close to the target at 1.8 degrees. The input process parameters were optimized at 0.7 s of UV bottom cure time, 120 °C of UV dual side temperature, 5.0 s of UV dual side cure time, and 230 μm of adhesive dot size. The validation experiment showed a prediction response error of less than 7% of the actual value.

scholarly journals Optimization of Chromium Removal by the Indigenous Bacterium Bacillus spp. REP02 Using the Response Surface Methodology

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
C. K. Venil ◽  
V. Mohan ◽  
P. Lakshmanaperumalsamy ◽  
M. B. Yerima
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Yeast Extract ◽  
Industrial Effluents ◽  
Quadratic Model ◽  
Coefficient Of Determination ◽  
Indigenous Bacterium ◽  
Bacillus Spp ◽  
Chromium Electroplating ◽  
Bacterium Bacillus

An indigenous bacterium, Bacillus REP02, was isolated from locally sourced chromium electroplating industrial effluents. Response surface methodology was employed to optimize the five critical medium parameters responsible for higher % Cr2+ removal by the bacterium Bacillus REP02. A three-level Box-Behnken factorial design was used to optimize K2HPO4, yeast extract, MgSO4, NH4NO3, and dextrose for Cr2+ removal. A coefficient of determination (R2) value (0.93), model F-value (3.92) and its low P-value (F<0.0008) along with lower value of coefficient of variation (5.39) indicated the fitness of response surface quadratic model during the present study. At optimum parameters of K2HPO4 (0.6 g L−1), yeast extract (5.5 g L−1), MgSO4 (0.04 g L−1), NH4NO3 (0.20 g L−1), and dextrose (12.50 g L−1), the model predicted 98.86% Cr2+ removal, and experimentally, 99.08% Cr2+ removal was found.

Experimental investigation of machinability and geometrical behavior of Titanium Alloy (Ti–6Al–4V) using Abrasive Waterjet Circular cut using Response Surface Methodology-Desirability approach

2021 ◽  
Author(s):  
Umanath Karuppusamy ◽  
Devika D ◽  
Rashia Begum S
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Titanium Alloy ◽  
Response Surface ◽  
Process Parameters ◽  
Abrasive Waterjet ◽  
Optimum Level ◽  
Machining Parameters ◽  
Input Parameters ◽  
Desirability Approach

Abstract In the current study, the research explored the effect of the process parameters on the Titanium Alloy (Ti–6Al–4V) to improve the machining, surface and geometric characteristics of the circular cut-off profile by determining the optimum parameters for the Abrasive Water Jet Machining (AWJM). The input parameters considered are the Abrasive Flow Rate (AFR), Stand-off Distance (SoD), and Traverse Rate (TR). There are various input parameters to evaluate output parameters like Circularity, Cylindricity, and Surface Roughness (SR) of the circular cut profile. The experiments are conducted using Central Composite Design (CCD) in the Response Surface Methodology (RSM). Analysis of variance (ANOVA) is carried out to define most influenced process parameters and percentage of contribution. The RSM is used to predict the mathematical models for formulating the objective function using experimental results. RSM desirability approach is included in the method for determining optimum levels and discerning impacts on response variables of machining parameters. Confirmation tests with an optimum level of machining parameters have been completed to determine the adequacy of the RSM. In addition to that, the cutting profiles are also analysed using Scanning Electron Microscope (SEM). The Atomic Force Microscope(AFM) is often used to verify the minimum Surface Roughness of the AWJM machined surface.

scholarly journals Optimization Study of Biomass Hydrogenation to Ethylene Glycol Using Response Surface Methodology

Processes ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 588
Author(s):  
Poh Gaik Law ◽  
Noor Haida Sebran ◽  
Ashraf Zin Zawawi ◽  
Azlan Shah Hussain
Keyword(s):  
Response Surface Methodology ◽  
Ethylene Glycol ◽  
Response Surface ◽  
Process Parameters ◽  
Quadratic Function ◽  
Quadratic Model ◽  
Coefficient Of Determination ◽  
Mass Ratio ◽  
Empty Fruit Bunches ◽  
Binary Catalyst

Statistical-based study using response surface methodology (RSM) was conducted to study the effects of process parameters towards biomass hydrogenation. Using Malaysian oil palm empty fruit bunches (EFB) fibres as feedstock, the central composite design (CCD) technique was employed and 18 runs were generated by CCD when four parameters (mass ratio of binary catalyst, hydrogen pressure, temperature and mass ratio of catalyst to feedstock) were varied with two center points to determine the effects of process parameters and eventually to get optimum ethylene glycol (EG) yield. RSM with quadratic function was generated for biomass hydrogenation, indicating all factors except temperature, were important in determining EG yield. Analysis of variance (ANOVA) showed a high coefficient of determination (R2) value of >0.98, ensuring a satisfactory prediction of the quadratic model with experimental data. The quadratic model suggested the optimum EG yield should be >25 wt.% and the EG yield results were successfully reproduced in the laboratory.

Optimization of process parameters in magnetic field assisted powder mixed EDM of aluminium 6061 alloy

2020 ◽  
pp. 095440622095910
Author(s):  
Arun Kumar Rouniyar ◽  
Pragya Shandilya
Keyword(s):  
Magnetic Field ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Discharge Current ◽  
Electrical Discharge Machining ◽  
Desirability Function ◽  
Fine Powder ◽  
Quadratic Model ◽  
Electrode Wear

Magnetic field assisted powder mixed electrical discharge machining (MFAPM-EDM) is a variant of EDM process where magnetic field coupled with electric field is used with addition of fine powder in dielectric to improve the surface quality, machining rate and stability of the process. Aluminium 6061 alloy as workpiece was selected due to growing use in aviation, automotive, naval industries. In this present work, parametric study and optimization was carried out on MFAPM-EDM machined Aluminium 6061 alloy. In this study, process parameters such as discharge current (IP), spark duration (PON), pause duration (POFF), concentration of powder (CP) and magnetic field (MF) were considered to analyze the effect on material erosion rate (MER) and electrode wear rate (EWR). Box Behnken design approach based on response surface methodology (RSM) was utilized for performing the experiments. Quadratic model to predict the MER and EWR were developed using response surface methodology. Discharge current has most significant effect of 50.176% and 36.36% on MER and EWR, respectively among all others process parameters. Teacher-learning-based optimization (TLBO) was employed for determining the optimal process parameters for maximum MER and minimal EWR. The results obtained with TLBO was compared with well-known optimization methods such as genetic algorithm (GA) and desirability function of RSM. Minimum EWR (0.1021 mm3/min) and maximum MER (30.4687 mm3/min) obtained using TLBO algorithm for optimized process parameters was found to better as compared to GA and desirability function.

OPTIMIZATION OF THE MECHANICAL STRENGTH PROPERTIES OF POLY(L-LACTIDE)/MULTI-WALLED CARBON NANOTUBE SCAFFOLDS USING RESPONSE SURFACE METHODOLOGY

NANO ◽  
2011 ◽  
Vol 06 (02) ◽  
pp. 113-122 ◽  
Author(s):  
HASSAN ADELI ◽  
SHARIF HUSSEIN SHARIF ZEIN ◽  
SOON HUAT TAN ◽  
ABDUL LATIF AHMAD
Keyword(s):  
Response Surface Methodology ◽  
Carbon Nanotube ◽  
Mechanical Strength ◽  
Response Surface ◽  
Process Parameters ◽  
Response Strength ◽  
Strength Properties ◽  
Quadratic Model ◽  
Factors Affecting ◽  
Multi Walled Carbon Nanotube

In this study the response surface methodology (RSM) coupled with the central composite design (CCD) were used to optimize the mechanical strength properties of poly(L-lactide)/multi-walled carbon nanotube (MWCNT) scaffolds. The scaffolds were prepared by the freeze-extraction method. MWCNTs were incorporated into PLLA composite as a reinforcement agent in order to improve the strength properties of the scaffolds. The effect of process parameters such as ratio of PLLA/(PLLA + MWCNT) (93–100%), solvent amount (100–200 ml), freezing time (5–7 h) and immersing time (2–4 days) were studied using the design of experiment (DOE). Based on CCD, quadratic model was obtained and developed to correlate the process parameters to the strength of the scaffolds. An analysis of variance (ANOVA) was applied to determine the significant factors affecting the experimental design response (strength) of the scaffolds. The predicted values after optimization process were in good agreement with the experimental values. The model was able to accurately predict the response of strength with less than 5% error.

Comparison of the Optimized Process Parameters of Double-Sided Friction Stir Welded Aluminium Alloy Joints Using Statistical and Evolutionary Techniques

2016 ◽  
Vol 852 ◽  
pp. 317-323 ◽  
Author(s):  
S. Vignesh ◽  
P. Dinesh Babu ◽  
C. Balamurugan ◽  
S. Martin Vinoth
Keyword(s):  
Response Surface Methodology ◽  
Evolutionary Algorithm ◽  
Response Surface ◽  
Process Parameters ◽  
Welding Speed ◽  
Rotational Speed ◽  
Welding Process ◽  
Regression Equations ◽  
Friction Stir ◽  
Desirability Approach

One of the most innovative solid state welding techniques used in the aerospace, automotive, defence, rail and marine industries is Friction Stir Welding (FSW) process, as it is used for joining aluminium, copper and magnesium alloys. The weld quality is decided by the FSW process parameters such as rotational speed, welding speed and pin profile. A regression model was developed relating the welding input parameters (tool rotational speed, welding speed and pin profile) and the output response parameters (tensile strength, hardness and toughness) based on the experiments carried out with the help of Response Surface Methodology. The obtained regression equations were used in determining the optimal welding process parameters. A new method, Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) based on evolutionary algorithm has been used in the optimisation. The optimum results gathered from the desirability approach through Response Surface Methodology (RSM) were compared with those obtained through the evolutionary algorithm. The results show that the proposed evolutionary method is much effective, faster than the desirability approach discussed in the work.

EXTRACTION OPTIMIZATION AND ANTIOXIDANT ACTIVITY OF PHENOLIC COMPOUNDS FROM AVOCADO PEEL

2019 ◽  
pp. 49-59
Author(s):  
Nu Linh Giang Ton ◽  
Thi Hoai Nguyen ◽  
Quoc Hung Vo
Keyword(s):  
Antioxidant Activity ◽  
Response Surface Methodology ◽  
Antioxidant Capacity ◽  
Response Surface ◽  
Total Antioxidant Capacity ◽  
Total Phenolic Content ◽  
Phenolic Content ◽  
Quadratic Model ◽  
Total Phenolic ◽  
Total Antioxidant

Avocado peel has been considered as a potential source of natural antioxidants in which phenolics are among the most important compounds. Therefore, this study aims to optimize the extraction process of phenolics using response surface methodology and evaluate the corresponding antioxidant activity. From the quadratic model, the optimal condition was determined including the ethanol concentration 54.55% (v/v), the solvent/solute ratio 71.82/1 (mL/g), temperature 53.03 oC and extraction time 99.09 min. The total phenolic content and the total antioxidant capacity at this condition with minor modifications were 26,74 ± 0,04 (mg GAE/g DW) and 188.06 ± 1.41 (mg AAE/g DW), respectively. The significant correlation between total phenolic content and total antioxidant capacity was also confirmed. Key words: response surface methodology, central composite rotatable design, total phenolic content, total antioxidant capacity, avocado peel

scholarly journals Optimization of Lignin Extraction Variables by Response Surface Methodology from Pine Saw Dust, and Quantification of Major Structural Units in Isolated Lignin Fraction

2021 ◽  
Vol 11 (4) ◽  
pp. 1739
Author(s):  
Muhammad Ajaz Ahmed ◽  
Jae Hoon Lee ◽  
Joon Weon Choi
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Quantum Coherence ◽  
Resonance Spectrum ◽  
Quadratic Model ◽  
Molecular Weights ◽  
Solids Loading ◽  
A Value ◽  
Lignin Extraction ◽  
Lignin Fraction

A synergistic combination of dioxane, acetic acid, and HCl was investigated for lignin extraction from pine wood biomass. After initial screening of reagent combination, response surface methodology (RSM) was used to optimize the lignin yield with respect to the variables of time 24–72 h, solids loading 5–15%, and catalyst dose 5–15 mL. A quadratic model predicted 8.33% of the lignin yield, and it was further confirmed experimentally and through the analysis of variance (ANOVA). Lignin at optimum combination exhibited features in terms of derivatization followed by reductive cleavage (DFRC) with a value of (305 µmol/gm), average molecular weights of 4358 and polydispersity of 1.65, and 2D heteronuclear single quantum coherence nuclear magnetic resonance spectrum (2D-HSQC NMR) analysis showing relative β-O-4 linkages (37.80%). From here it can be suggested that this fractionation can be one option for high quality lignin extraction from lignocellulosic biomass.

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