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

REAKTOR ◽  
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

Thermogravimetric analysis and the optimisation of bio-oil yield from fixed-bed pyrolysis of rice husk using response surface methodology (RSM)

2011 ◽  
Vol 33 (2) ◽  
pp. 481-487 ◽  
Author(s):  
Khairuddin Md Isa ◽  
Suhardy Daud ◽  
Nasrul Hamidin ◽  
Khudzir Ismail ◽  
Saiful Azhar Saad ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Thermogravimetric Analysis ◽  
Response Surface ◽  
Rice Husk ◽  
Fixed Bed ◽  
Oil Yield ◽  
Bio Oil

Optimisation of biomass catalytic depolymerisation conditions by using response surface methodology

2019 ◽  
Vol 38 (3) ◽  
pp. 322-331
Author(s):  
Mehmet Ünsal ◽  
Işıl Işık-Gülsaç ◽  
Ersin Üresin ◽  
Mustafa Salih Budak ◽  
Kader Özgür-Büyüksakallı ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Energy Consumption ◽  
Reaction Time ◽  
Response Surface ◽  
Product Yield ◽  
Operating Conditions ◽  
Optimum Conditions ◽  
Specific Product ◽  
Bio Oil ◽  
Specific Product Yield

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.

Optimized bio-oil yield from Swietenia macrophylla seeds via ultrasonic cavitation through response surface methodology

2018 ◽  
Vol 3 (5) ◽  
pp. 266-278 ◽  
Author(s):  
Rey P. Gumaling ◽  
Jay R E. Agusan ◽  
Neil Ven Cent R. Ellacer ◽  
Gretel Mary T. Abi Abi ◽  
Jasmin Roxatte P. Pajaron ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Ultrasonic Cavitation ◽  
Oil Yield ◽  
Swietenia Macrophylla ◽  
Bio Oil

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

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.

scholarly journals 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 ◽  
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.

Optimization of biodiesel synthesis under simultaneous ultrasound-microwave irradiation using response surface methodology (RSM)

2015 ◽  
Vol 4 (4) ◽  
Author(s):  
Seyed Mohammad Safieddin Ardebili ◽  
Teymor Tavakoli Hashjin ◽  
Barat Ghobadian ◽  
Gholamhasan Najafi ◽  
Stefano Mantegna ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Microwave Irradiation ◽  
Response Surface ◽  
Palm Oil ◽  
Catalyst Concentration ◽  
Irradiation Time ◽  
Operating Conditions ◽  
Molar Ratio ◽  
Reaction Conditions ◽  
Biodiesel Synthesis

AbstractThis work investigates the effect of simultaneous ultrasound-microwave irradiation on palm oil transesterification and uncovers optimal operating conditions. Response surface methodology (RSM) has been used to analyze the influence of reaction conditions, including methanol/palm oil molar ratio, catalyst concentration, reaction temperature and irradiation time on biodiesel yield. RSM analyses indicate 136 s and 129 s as the optimal sonication and microwave irradiation times, respectively. Optimized parameters for full conversion (97.53%) are 1.09% catalyst concentration and a 7:3.1 methanol/oil molar ratio at 58.4°C. Simultaneous ultrasound-microwave irradiation dramatically accelerates the palm oil transesterification reaction. Pure biodiesel was obtained after only 2.2 min while the conventional method requires about 1 h.

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