Optimisation of biomass catalytic depolymerisation conditions by using response surface methodology

The aim of this study is to present the optimum operating conditions for reducing energy consumption in the process of obtaining bio-oil from the mixture of sawdust, waste lubricating oil, lime, and commercial catalyst. In the study where the catalytic pressureless depolymerisation (also called Katalytische Drucklose Verölung – KDV) was applied, the operating conditions were analysed with response surface methodology. According to the analysis of variance results, a mathematical model was obtained for specific product yield (bio-oil amount/energy consumption g kWe−1). Effects of temperature (260°C–290°C), catalyst rate (1–2 wt.%) and reaction time (0.5–1 h) were investigated. The optimum conditions for the three independent variables (temperature, catalyst rate, reaction time) were 279 ± 2°C, 2 wt.% and 0.5 h, respectively. Maximum specific product yield was obtained as 970.17 g kWe−1. While the reaction time was the most effective regarding the amount of bio-oil obtained at 1 kWe energy consumption, the temperature was found to be the least effective. In addition to these, bio-oil obtained under optimum conditions were characterised and compared with standard diesel specifications.

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Optimization of Bio-oil Production from Empty Palm Fruit Bunches by Pyrolysis using Response Surface Methodology

REAKTOR ◽

10.14710/reaktor.20.1.1-9 ◽

2020 ◽

Vol 20 (1) ◽

pp. 1-9

Author(s):

Tutuk Djoko Kusworo ◽

Bayu Aji Pratama ◽

Dhea Putri Safira

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Optimal Operation ◽

Operating Conditions ◽

Fuel Oil ◽

Oil Yield ◽

Human Populations ◽

Operation Condition ◽

Palm Fruit ◽

Bio Oil

The need for fuel oil continues to increase in line with the increasing number of human populations and the growth rate of dependence on fuel oil. Bio-oil is a condensed-liquid mixture that results from the thermal derivation of biomass containing hemicellulose, lignin, and cellulose. This research developed an optimization of the operation condition of bio-oil from empty palm fruit bunches (OPEFB) using a modified pyrolysis reactor. The temperature and mass of empty palm fruit bunches were the two parameters considered in this study. Optimization was carried out on process parameters using the surface response methodology (RSM) and variance analysis (ANOVA). The significance of the different parameters and the effect of the relationship between parameters on the bio-oil yield is determined using a full factorial central composite design. The optimal operation condition of pyrolysis was found to be 570.71 oC, and the mass of empty palm fruit bunch 420.71 gr. Predictions from the optimum variable of operating conditions produce a bio-oil yield of 5.58%. The actual bio-oil yield on the optimum condition that was be validated is 5.6 %. The chemical composition of bio-oil obtained was evaluated by GCMS to ensure its characterization as a fuel.Keywords: Empty palm fruit bunches, Bio-oil, Pyrolysis, Response Surface Methodology, Optimization

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Optimization to Hydrothermal Liquefaction of Low Lipid Content Microalgae Spirulina sp. Using Response Surface Methodology

Journal of Chemistry ◽

10.1155/2018/2041812 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 3

Author(s):

Xuan Wei ◽

Dengfei Jie

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Lipid Content ◽

Oil Production ◽

Hydrothermal Liquefaction ◽

Holding Time ◽

Optimum Conditions ◽

Bio Oil ◽

Contour Plots ◽

Central Composite

The production and nature of the biocrude obtained from Spirulina sp. by hydrothermal liquefaction (HTL) technology is focused in this investigation. Our aim is to evaluate the interaction of different factors on the bio-oil production through HTL using microalgae that contains relatively low lipid content and high protein. Optimization of three key parameters—concentration (mass of algae per mass of solvent), reaction temperature, and holding time—was carried out by response surface methodology (RSM). In this work, we used central composite design to conduct the experiment process. Graphical response surface and contour plots were used to locate the optimum point. The final results showed that the optimum concentration, temperature, and holding time were 10.5%, 357°C, and 37 min, respectively. Under the optimum conditions established, yield of the biocrude (41.6 ± 2.2%) was experimentally obtained using the fresh microalgae. This study showed the potential of bio-oil production of Spirulina sp. by HTL technology, but it still needs more improvement of the biocrude for utilization.

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Enzyme-Assisted Mechanical Peeling of Cassava Tubers

Catalysts ◽

10.3390/catal10010066 ◽

2020 ◽

Vol 10 (1) ◽

pp. 66

Author(s):

Ziba Barati ◽

Sajid Latif ◽

Sebastian Romuli ◽

Joachim Müller

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Surface Area ◽

Incubation Time ◽

Operating Conditions ◽

Optimum Operating ◽

Optimum Conditions ◽

Peeling Process ◽

Pre Treatment

In this study, the effect of enzymatic pre-treatment and the size of cassava tubers on mechanical peeling was examined. Cassava tubers were sorted based on their mass as small, medium and large. Viscozyme® L and an abrasive cassava peeling machine was used for the enzymatic pre-treatment and the mechanical peeling, respectively. Response surface methodology (RSM) was used to investigate the effect of the enzyme dose (0.5–1.9 mL g−1), incubation time (1.5–6 h), peeling time (1.5–4.5 min) and size of the tubers (small, medium and large) on the peeling process. Peeled surface area (PSA) and peel loss (PL) were measured as main responses in RSM. Results showed that the PSA and PL were significantly (p < 0.05) influenced by the enzyme dose, incubation time and peeling time. The size of tubers only had a significant impact on the PSA. The optimum operating conditions for different sizes of tubers were found and validated. Under optimum conditions, the PSA of the large tubers (89.52%) was significantly higher than the PSA of the medium and small tubers (p < 0.05). Application of enzymatic pre-treatment can improve the mechanical peeling process especially for larger cassava tubers.

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Modelling Dimethoate Removal by Fenton-Like Process Using Response Surface Methodology

Proceedings ◽

10.3390/proceedings2110649 ◽

2018 ◽

Vol 2 (11) ◽

pp. 649

Author(s):

Berrak Erol Nalbur ◽

Arzu Teksoy ◽

Seval Kutlu Akal Solmaz ◽

Hilal Safiye Azak

Keyword(s):

Response Surface Methodology ◽

Reaction Time ◽

Toxic Effect ◽

Response Surface ◽

Analytical Methods ◽

Significant Variable ◽

Optimum Conditions ◽

Independent Variables ◽

Oxidation Efficiency

The (RSM) is a useful method for optimizing analytical methods and it has been applied to evaluate independent variables in FPs. In this study, the removal of dimethoate (DMT) which is a commonly used pesticide and has a toxic effect on the environment, was evaluated in terms of oxidation and mineralization efficiency using response surface methodology (RSM) in the Fenton-like process (FLP). The obtained optimum conditions for DMT oxidation and mineralization using the FLP included DMT/Fe+3/H2O2 ratio of 0.018 mM/0.03 mM/0.15 mM and reaction time of 65 min. DMT oxidation efficiency was 78% and mineralization efficiency was 18%. The initial DMT concentration was the most significant variable affecting both the oxidation and mineralization efficiency of DMT.

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Optimization of an Ultrasonic-Assisted Biodiesel Production Process from One Genotype of Rapeseed (TERI (OE) R-983) as a Novel Feedstock Using Response Surface Methodology

Energies ◽

10.3390/en12142656 ◽

2019 ◽

Vol 12 (14) ◽

pp. 2656 ◽

Cited By ~ 3

Author(s):

Sara Almasi ◽

Barat Ghobadian ◽

Gholam Hassan Najafi ◽

Talal Yusaf ◽

Masoud Dehghani Soufi ◽

...

Keyword(s):

Response Surface Methodology ◽

Reaction Time ◽

Response Surface ◽

Methyl Esters ◽

Operating Conditions ◽

Biodiesel Production ◽

Molar Ratio ◽

Climate Conditions ◽

Ultrasonic Assisted ◽

Optimized Conditions

In recent years, due to the favorable climate conditions of Iran, the cultivation of rapeseed has increased significantly. The aim of this study was to investigate the possibility of biodiesel production from one genotype of rapeseed (TERI (OE) R-983). An ultrasonic approach was used in order to intensify the reaction. Response surface methodology (RSM) was applied to identify the optimum conditions of the process. The results of this research showed that the conversion of biodiesel was found to be 87.175% under the optimized conditions of a 4.63:1 molar ratio (methanol to oil), 56.50% amplitude, and 0.4 s pulses for a reaction time of 5.22 min. Increasing the operating conditions, such as the molar ratio from 4:1 to 5.5:1, amplitude from 50% to 72.5%, reaction time from 3 min to 7 min, and pulse from 0.4 s to 1 s, increased the FAME (fatty acid methyl esters) yield by approximately 4.5%, 2.3%, 1.2%, and 0.5%, respectively. The properties of the TERI (OE) R-983 methyl ester met the requirements of the biodiesel standard (ASTM D6751), indicating the potential of the produced biodiesel as an alternative fuel.

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Optimization and modelling using the response surface methodology (RSM) for ciprofloxacin removal by electrocoagulation

Water Science & Technology ◽

10.2166/wst.2015.649 ◽

2015 ◽

Vol 73 (7) ◽

pp. 1673-1679 ◽

Cited By ~ 9

Author(s):

Sibel Barışçı ◽

Ozge Turkay

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Operating Conditions ◽

Process Time ◽

Optimum Conditions ◽

Applied Current ◽

Box Behnken Design ◽

Operational Conditions ◽

Density Process ◽

Ciprofloxacin Removal

In this study, response surface methodology (RSM) was used to investigate the effects of different operating conditions on the removal of ciprofloxacin (CIP) by the electrocoagulation (EC) with pure iron electrodes. Box-Behnken design was used for the optimization of the EC process and to evaluate the effects and interactions of process variables such as applied current density, process time, initial CIP concentration and pH on the removal of CIP by the EC process. The optimum conditions for maximum CIP removal (86.6%) were found as pH = 4; Co = 5 mg.L1−; Id = 4.325 mA.cm2−; tprocess = 10 min. The model adequacy and the validity of the optimization step were confirmed with additional experiments which were performed under the proposed optimum conditions. The predicted CIP removal as 86.6% was achieved at each experiment by using the optimum conditions. These results specify that the RSM is a useful tool for optimizing the operational conditions for CIP removal by the EC process.

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Application of Response Surface Methodology (RSM) for optimizing removal of Cr(VI) wastewater using Cr(VI)-reducing biofilm systems

Malaysian Journal of Fundamental and Applied Sciences ◽

10.11113/mjfas.v6n1.169 ◽

2014 ◽

Vol 6 (1) ◽

Author(s):

Nurfadilah Mohammed ◽

Wan Azlina Ahmad

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Operating Conditions ◽

Optimal Conditions ◽

Optimum Conditions ◽

Nutrient Supplementation ◽

Dependent Variables ◽

Reduction Efficiency ◽

Central Composite ◽

Experimental Runs

Response surface methodology (RSM) involving central composite design (CCD) was employed to obtain optimal conditions for Cr(VI) wastewater treatment by Cr (VI) reducing biofilm systems. On the basis of a CCD, RSM was used to determine the effect of initialmetal concentrations (40-100 mgL-1), nutrient supplementations (10-20%) and flowrate (3-6 mLmin-1) on the levels of response, i.e. Cr(VI) reduction efficiency. A set of 20 experimental runs were needed for optimizing of the operating conditions. Quadratic regressionmodels with estimated coefficients were developed to describe the Cr (VI) reduction. Analysis of variance (ANOVA) showed a highcoefficient of determination (R2) value of 0.9941, thus ensuring a satisfactory adjustment of the second-order regression model with theexperimental data. Cr (VI) reduction had significant effect on all the three dependent variables. The experimental results show that Cr(VI)-reducing biofilm systems could effectively reduce Cr (VI), 100% at the optimum conditions of initial metal concentration of 100mgL-1, nutrient supplementation of 20% and flowrate of 3 mLmin-1. The experimental observations were in reasonable agreement withthe modelled values.

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Parametric and energy consumption optimization of Basic Red 2 removal by electrocoagulation/egg shell adsorption coupling using response surface methodology in a batch system

Water Science & Technology ◽

10.2166/wst.2015.627 ◽

2015 ◽

Vol 73 (11) ◽

pp. 2572-2582 ◽

Cited By ~ 2

Author(s):

Helder Pereira de Carvalho ◽

Jiguo Huang ◽

Meixia Zhao ◽

Gang Liu ◽

Xinyu Yang ◽

...

Keyword(s):

Response Surface Methodology ◽

Energy Consumption ◽

Reaction Time ◽

Response Surface ◽

Removal Efficiency ◽

Current Density ◽

Batch System ◽

Energy Consumption Optimization ◽

Initial Ph ◽

Rsm Model

In this study, response surface methodology (RSM) model was applied for optimization of Basic Red 2 (BR2) removal using electrocoagulation/eggshell (ES) coupling process in a batch system. Central composite design was used to evaluate the effects and interactions of process parameters including current density, reaction time, initial pH and ES dosage on the BR2 removal efficiency and energy consumption. The analysis of variance revealed high R2 values (≥85%) indicating that the predictions of RSM models are adequately applicable for both responses. The optimum conditions when the dye removal efficiency of 93.18% and energy consumption of 0.840 kWh/kg were observed were 11.40 mA/cm2 current density, 5 min and 3 s reaction time, 6.5 initial pH and 10.91 g/L ES dosage.

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Effective Chromium Adsorption From Aqueous Solutions and Tannery Wastewater Using Bimetallic Fe/Cu Nanoparticles: Response Surface Methodology and Artificial Neural Network

Air Soil and Water Research ◽

10.1177/11786221211028162 ◽

2021 ◽

Vol 14 ◽

pp. 117862212110281

Author(s):

Ahmed S. Mahmoud ◽

Nouran Y. Mohamed ◽

Mohamed K. Mostafa ◽

Mohamed S. Mahmoud

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Industrial Effluent ◽

Oxygen Demand ◽

Operating Conditions ◽

Tannery Wastewater ◽

P Value ◽

Cu Nanoparticles ◽

Artificial Neural ◽

Cr Removal

Tannery industrial effluent is one of the most difficult wastewater types since it contains a huge concentration of organic, oil, and chrome (Cr). This study successfully prepared and applied bimetallic Fe/Cu nanoparticles (Fe/Cu NPs) for chrome removal. In the beginning, the Fe/Cu NPs was equilibrated by pure aqueous chrome solution at different operating conditions (lab scale), then the nanomaterial was applied in semi full scale. The operating conditions indicated that Fe/Cu NPs was able to adsorb 68% and 33% of Cr for initial concentrations of 1 and 9 mg/L, respectively. The removal occurred at pH 3 using 0.6 g/L Fe/Cu dose, stirring rate 200 r/min, contact time 20 min, and constant temperature 20 ± 2ºC. Adsorption isotherm proved that the Khan model is the most appropriate model for Cr removal using Fe/Cu NPs with the minimum error sum of 0.199. According to khan, the maximum uptakes was 20.5 mg/g Cr. Kinetic results proved that Pseudo Second Order mechanism with the least possible error of 0.098 indicated that the adsorption mechanism is chemisorption. Response surface methodology (RSM) equation was developed with a significant p-value = 0 to label the relations between Cr removal and different experimental parameters. Artificial neural networks (ANNs) were performed with a structure of 5-4-1 and the achieved results indicated that the effect of the dose is the most dominated variable for Cr removal. Application of Fe/Cu NPs in real tannery wastewater showed its ability to degrade and disinfect organic and biological contaminants in addition to chrome adsorption. The reduction in chemical oxygen demand (COD), biological oxygen demand (BOD), total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN), Cr, hydrogen sulfide (H2S), and oil reached 61.5%, 49.5%, 44.8%, 100%, 38.9%, 96.3%, 88.7%, and 29.4%, respectively.

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Modeling and Sensitivity Analysis of the Forward Osmosis Process to Predict Membrane Flux Using a Novel Combination of Neural Network and Response Surface Methodology Techniques

Membranes ◽

10.3390/membranes11010070 ◽

2021 ◽

Vol 11 (1) ◽

pp. 70

Author(s):

Jasir Jawad ◽

Alaa H. Hawari ◽

Syed Javaid Zaidi

Keyword(s):

Response Surface Methodology ◽

Experimental Design ◽

Response Surface ◽

Forward Osmosis ◽

Feed Solution ◽

Operating Conditions ◽

Ann Model ◽

Membrane Flux ◽

Input Variables ◽

Rsm Model

The forward osmosis (FO) process is an emerging technology that has been considered as an alternative to desalination due to its low energy consumption and less severe reversible fouling. Artificial neural networks (ANNs) and response surface methodology (RSM) have become popular for the modeling and optimization of membrane processes. RSM requires the data on a specific experimental design whereas ANN does not. In this work, a combined ANN-RSM approach is presented to predict and optimize the membrane flux for the FO process. The ANN model, developed based on an experimental study, is used to predict the membrane flux for the experimental design in order to create the RSM model for optimization. A Box–Behnken design (BBD) is used to develop a response surface design where the ANN model evaluates the responses. The input variables were osmotic pressure difference, feed solution (FS) velocity, draw solution (DS) velocity, FS temperature, and DS temperature. The R2 obtained for the developed ANN and RSM model are 0.98036 and 0.9408, respectively. The weights of the ANN model and the response surface plots were used to optimize and study the influence of the operating conditions on the membrane flux.

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