Computational evaluation of microalgae biomass conversion to biodiesel

被引：22

作者：

Milic, Momir ^{[1
]}

Petkovic, Biljana ^{[2
]}

Selmi, Abdellatif ^{[3
,4
]}

Petkovic, Dalibor ^{[5
]}

Jermsittiparsert, Kittisak ^{[6
,7
,8
]}

Radivojevic, Aleksandar ^{[9
]}

Milovancevic, Milos ^{[10
]}

Khan, Afrasyab ^{[11
]}

Vidosavljevic, Sladana T. ^{[12
]}

Denic, Nebojsa ^{[13
]}

Kuzman, Boris ^{[14
]}

机构：

[1] Alfa BK Univ, Fac Informat Technol, Belgrade, Serbia

[2] Univ Kragujevac, Fac Econ, Licej Knezevine Srbije 3, Kragujevac, Serbia

[3] Prince Sattam Bin Abdulaziz Univ, Dept Civil Engn, Coll Engn, Al Kharj 11942, Saudi Arabia

[4] Ecole Natl Ingenieurs Tunis ENIT, Civil Engn Lab, BP 37, Tunis 1002, Tunisia

[5] Univ Nis, Pedag Fac Vranje, Partizanska 14, Vranje 17500, Serbia

[6] Duy Tan Univ, Inst Res & Dev, Da Nang 550000, Vietnam

[7] Duy Tan Univ, Fac Humanities & Social Sci, Da Nang 550000, Vietnam

[8] Henan Univ Econ & Law, MBA Sch, Zhengzhou 450046, Henan, Peoples R China

[9] Univ Nis, Fac Sci & Math, Nish, Serbia

[10] Univ Nis, Fac Mech Engn, Nish, Serbia

[11] South Ural State Univ SUSU, Inst Engn & Technol, Dept Hydraul & Hydraul & Pneumat Syst, Lenin Prospect 76, Chelyabinsk 454080, Russia

[12] Univ Pristina Kosovska Mitrov, Teacher Educ Fac, Leposavic 18218, Serbia

[13] Univ Pristina, Fac Sci & Math, Lole Ribara 29, Kosovska Mitrovica, Serbia

[14] Inst Agr Econ, Belgrade, Serbia

来源：

BIOMASS CONVERSION AND BIOREFINERY | 2023年 / 13卷 / 04期

关键词：

Microalgae; Biodiesel; Optimization; ANFIS; Soft computing; COLUMN CONNECTIONS; SHEAR-STRENGTH; CONCRETE BEAMS; OPTIMIZATION; PREDICTION; TRANSESTERIFICATION; BEHAVIOR; NETWORK; SAFETY; MODEL;

D O I：

10.1007/s13399-021-01314-2

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Since there are large requirements for green energy sustainability, in this study, optimization of in situ transesterification of microalgae slurry conversion into biodiesel was performed. The main aim was to perform a selection procedure of the optimal predictors for fatty acid methyl ester yield and exergy efficiency in situ transesterification process. The adaptive neuro fuzzy inference system (ANFIS) as a soft computing approach was used for the optimization of the predictors for the fatty acid methyl ester yield and exergy efficiency. Based on the obtained results, the optimal combination for fatty acid methyl ester yield was ultrasonic power and reaction time while the optimal combination for the exergy efficiency was concentrations of methanol and chloroform in oil. These selected predictors could be used effectively in order to maximize the fatty acid methyl ester yield and exergy efficiency.

引用

页码：3179 / 3186

页数：8

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