Modelling and process optimization for biodiesel production from Nannochloropsis salina using artificial neural network

被引：50
|
作者：
Raj, J. Vinoth Arul [1 ]
Kumar, R. Praveen [1 ]
Vijayakumar, B. [2 ]
Gnansounou, Edgard [3 ]
Bharathiraja, B. [2 ]
机构：
[1] Arunai Engn Coll, Dept Biotechnol, Thiruvannaamalai 606603, India
[2] Vel Tech High Tech Dr Rangarajan Dr Sakunthala En, Chennai 600062, Tamil Nadu, India
[3] Ecole Polytech Fed Lausanne EPFL, Bioenergy & Energy Planning Res Grp, CH-1015 Lausanne, Switzerland
来源：
BIORESOURCE TECHNOLOGY | 2021年 / 329卷
关键词：
Nannochloropsis salina; Artificial neural network; Biodiesel; Egg shell; Nanocatalyst; RESPONSE-SURFACE METHODOLOGY; WASTE COOKING OIL; TRANSESTERIFICATION; CATALYST; SHELL; ANN; NANOCATALYST; FAME; RSM;
D O I：
10.1016/j.biortech.2021.124872
中图分类号：
S2 [农业工程];
学科分类号：
0828 ;
摘要：
In the present investigation, calcium oxide solid nanocatalyst derived from the egg shell and Nannochloropsis salina were used for the production of biodiesel. The morphological characteristics and functional groups of synthesized nanocatalyst was characterized by SEM and FTIR analysis. Process variables optimization for biodiesel production was studied using RSM and ANN. The R-2 values for RSM and ANN was found to be 0.8751 and 0.957 which showed that the model was significantly fit with the experimental data. The maximum FAME conversion for the synthesized nanocatalyst CaO was found to be 86.1% under optimum process conditions (nanocatalyst amount: 3% (w/v); oil to methanol ratio 1:6 (v/v); reaction temperature: 60 degrees C; reaction time 55 min). Concentration of FAME present in biodiesel was identified by GC-MS analysis.
引用
收藏
页数：8
相关论文
共 50 条
  • [1] Synthesis of biodiesel from the composite oil and process parameters optimization using artificial neural network
    Kalos, Pritam S.
    Kharat, Reena
    Vivekanandan, Nallu
    Kannan, Rajeswari
    Balamurugan, Samraj
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING, 2024,
  • [2] Process optimization based on artificial neural network of alkali to preparing biodiesel
    Wang, Changmei
    Wu, Shaobing
    Zhang, Wudi
    Chen, Yubao
    Yin, Fang
    Liu, Shiqing
    Zhao, Xingling
    Liu, Jing
    Energy Education Science and Technology Part A: Energy Science and Research, 2013, 31 (01): : 593 - 596
  • [3] Process Optimization Based on Artificial Neural Network of Plant Oli to Preparing Biodiesel
    Wang, Changmei
    Wu, Shaobing
    Zhang, Wudi
    Chen, Yubao
    Yin, Fang
    Liu, Shiqing
    Liu, Jing
    Zhao, Xingling
    MATERIALS, MECHANICAL ENGINEERING AND MANUFACTURE, PTS 1-3, 2013, 268-270 : 401 - +
  • [4] Process Optimization Based on Artificial Neural Network of Potassium Hydroxide to Preparing Biodiesel
    Wang, Changmei
    Wu, Shaobing
    Zhang, Wudi
    Chen, Yubao
    Yin, Fang
    Liu, Shiqing
    Liu, Jing
    Zhao, Xingling
    INFORMATION TECHNOLOGY APPLICATIONS IN INDUSTRY, PTS 1-4, 2013, 263-266 : 2225 - +
  • [5] Development of direct conversion method for microalgal biodiesel production using wet biomass of Nannochloropsis salina
    Kim, Tae-Hyoung
    Suh, William I.
    Yoo, Gursong
    Mishra, Sanjiv K.
    Farooq, Wasif
    Moon, Myounghoon
    Shrivastav, Anupama
    Park, Min S.
    Yang, Ji-Won
    BIORESOURCE TECHNOLOGY, 2015, 191 : 438 - 444
  • [6] Artificial neural network modelling for the removal of lead from wastewater by using adsorption process
    Mahdi, Ayat Hussein
    Jaid, Ghaidaa Majeed
    Alardhi, Saja Mohsen
    DESALINATION AND WATER TREATMENT, 2021, 244 : 110 - 119
  • [7] Process parameter optimization of biodiesel production from algal oil by response surface methodology and artificial neural networks
    Garg, Akshay
    Jain, Siddharth
    FUEL, 2020, 277
  • [8] Artificial neural network-genetic algorithm-based optimization of biodiesel production from Simarouba giauca
    Sivamani, Selvaraju
    Selvakumar, Selvaraj
    Rajendran, Karthik
    Muthusamy, Shanmugaprakash
    BIOFUELS-UK, 2019, 10 (03): : 393 - 401
  • [9] Modeling of lime production process using artificial neural network
    Daeichian, Abolghasem
    Shahramfar, Rana
    Heidari, Elham
    CHEMICAL PRODUCT AND PROCESS MODELING, 2022, 17 (06): : 655 - 667
  • [10] Modelling and simulation of desalination process using artificial neural network: a review
    Mahadeva, Rajesh
    Manik, Gaurav
    Verma, Om Prakash
    Sinha, Shishir
    DESALINATION AND WATER TREATMENT, 2018, 122 : 351 - 364
12345