Modeling and Global Optimization of Biodiesel Synthesis Using Hybrid Response Surface Methodology‐Crow Search Algorithm: Case Study of Papaya Seed Waste Oil Utilization

2021 ◽  
Author(s):  
S. M. Zakir Hossain ◽  
N. Sultana ◽  
S. Taher ◽  
A. Khan ◽  
S. A. Razzak ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Global Optimization ◽  
Response Surface ◽  
Search Algorithm ◽  
Waste Oil ◽  
Biodiesel Synthesis ◽  
Oil Utilization ◽  
Papaya Seed

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.

scholarly journals Combination of optimization techniques to find of processing optimal condition of postharvest broccoli by vacuum cooling process

2018 ◽  
Vol 40 (1) ◽  
pp. 36222 ◽  
Author(s):  
Tian Ding ◽  
Charles Gobber ◽  
José Carlos Curvelo Santana ◽  
Wonder Alexandre Luz Alves ◽  
Sidnei Alves de Araújo ◽  
...  
Keyword(s):  
Weight Loss ◽  
Response Surface Methodology ◽  
Tabu Search ◽  
Optimal Condition ◽  
Response Surface ◽  
Search Algorithm ◽  
Optimization Techniques ◽  
Water Volume ◽  
Tabu Search Algorithm ◽  
Vacuum Cooling

This study aimed to investigate the impact of each factor on the weight loss of postharvest broccoli and treatment efficacy, and also attempted to fix the optimal condition for vacuum cooling treatment on postharvest broccoli by response surface methodology combined with tabu search techniques. Fresh broccoli samples were harvested from a Chinese farm and the green heads of selected samples were cut into smaller ones with approximately 3~4 cmdiameter, and sequentially equilibrated to room temperature. Pressure (200-600 Pa), broccoli weight (200-500 g), water volume (2-6 %, v v-1) and time (20-40 min) were used as factors and weight loss, final temperature and cost as responses. A tabu search algorithm was developed to find the optimum condition for processing broccoli and its initial condition were from response surface methodology. Results demonstrates a good adjust of tabu search algorithm in simulation of the broccoli freezing process. From tabu list the best condition were found as follows: the broccoli weight between 273.5 and 278.0 g with a water volume of 3.0%, processed for 40.0 min and at 200 Pa, where the weight loss was 0.34 ± 0.01%, of end temperature was 2.0 ± 0.0°C and profit percent was 99.66 ± 0.01%. 

scholarly journals Optimization of chlorite and talc flotation using experimental design methodology: Case study of the MCG plant, Morocco

2020 ◽  
Vol 120 (12) ◽  
Author(s):  
K. Boujounoui ◽  
A. Abidi ◽  
A. Baçaoui ◽  
K. El Amari ◽  
A. Yaacoubi
Keyword(s):  
Response Surface Methodology ◽  
Central Composite Design ◽  
Response Surface ◽  
Desirability Functions ◽  
Sulphide Ore ◽  
Experimental Values ◽  
Experimental Design Methodology ◽  
Central Composite ◽  
Good Agreement

SYNOPSIS Response surface methodology (RSM), central composite design (CCD), and desirability functions were used for modelling and optimization of the operating factors in chlorite and talc (collectively termed 'mica') flotation. The influence of pulp pH, cyanide (NaCN) consumption, and particle size was studied with the aim of optimizing ssilicate flotation while minimizing recoveries of galena, chalcopyrite, and sphalerite. Flotation tests were carried out on a representative sample of a complex sulphide ore from Draa Sfar mine (Morocco). The model predictions for the flotation of each of the minerals concerned were found to be in good agreement with experimental values, with R2 values of 0.91, 0.98, 0.99, and 0.90 for mica, galena, chalcopyrite, and sphalerite recoveries, respectively. RSM combined with desirability functions and CCD was successfully applied for the modelling of mica flotation, considering simultaneously the four flotation responses to achieve the maximum recovery of mica and minimal loss of Pb, Cu, and Zn to the flotation concentrate. Keywords: chlorite, talc, flotation, response surface methodology, central composite design, optimization.

scholarly journals Response Surface Methodology Applied to the Optimization of Phenolic Compound Extraction from Brassica

2021 ◽  
Author(s):  
Valentin Reungoat ◽  
Morad Chadni ◽  
Irina Ioannou
Keyword(s):  
Response Surface Methodology ◽  
Phenolic Compounds ◽  
Response Surface ◽  
Phenolic Compound ◽  
Process Optimization ◽  
Prediction Models ◽  
State Of The Art ◽  
Process Engineering ◽  
Statistical Tool

The response surface methodology (RSM) is a relevant mathematical and statistical tool for process optimization. A state of the art on the optimization of the extraction of phenolic compounds from Brassica has shown that this approach is not sufficiently used. The reason for this is certainly an apparent complexity in comparison with the implementation of a one-factor-at-a-time (OFAT) optimization. The objective of this chapter is to show how one implement the response surface methodology in a didactic way on a case study: the extraction of sinapine from mustard bran. Using this approach, prediction models have been developed and validated to predict the sinapine content extracted as well as the purity of the extract in sinapine. The methodology presented in this chapter can be reproduced on any other application in the field of process engineering.

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