IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i17p6158-d896834.html
   My bibliography  Save this article

An Experimental Analysis and ANN Based Parameter Optimization of the Influence of Microalgae Spirulina Blends on CI Engine Attributes

Author

Listed:
  • S. Charan Kumar

    (Department of Mechanical Engineering, Lovely Professional University, Punjab 144401, India)

  • Amit Kumar Thakur

    (Department of Mechanical Engineering, Lovely Professional University, Punjab 144401, India)

  • J. Ronald Aseer

    (Department of Mechanical Engineering, National Institute of Technology Puducherry, Karaikal 609609, India)

  • Sendhil Kumar Natarajan

    (Department of Mechanical Engineering, National Institute of Technology Puducherry, Karaikal 609609, India)

  • Rajesh Singh

    (Uttaranchal Institute of Technology, Uttaranchal University, Dehradun 248012, India)

  • Neeraj Priyadarshi

    (Department of Electrical Engineering, JIS College of Engineering, Kolkata 741235, India)

  • Bhekisipho Twala

    (Digital Transformation Portfolio, Tshwane University of Technology, Staatsartillerie Rd., Pretoria West, Pretoria 0183, South Africa)

Abstract

In this present investigation, emittance and performance attributes of a diesel engine using micro-algae spirulina blended biodiesel mixtures of various concentrations (20%, 35%, 50%, 65%, 80%, and 100%) were evaluated. An optimization model was also developed using an Artificial Neural Network (ANN) to characterize the experimental parameters. Experimental findings demonstrated significant improvement in brake specific fuel consumption (BSFC) using varied blends. Furthermore, brake thermal efficiency (BTE) is decreased gradually for biodiesel blends as compared to diesel. Micro-algae spirulina blends have shown lower concentrations of NO X and HC while increasing CO 2 relative to pure diesel. To develop the model, three sets of optimizers, namely, adam, nadam, and adagrad, along with activation functions, such as sigmoid, softmax, and relu, were selected. The results revealed that sigmoid activation function with adam learning optimizer by using 32 hidden layer neurons has given the least value of mean squared error (MSE). Hence, the ANN approach was proven to be capable of predicting engine attributes with a least mean squared error of 0.00013, 0.00060, 0.00021, 0.00011, and 0.00104 for NO X , HC, CO 2 , brake thermal efficiency, and brake specific fuel consumption, respectively. The Artificial Neural Network approach is capable of predicting CI engine attributes with accuracy and ease of investigation.

Suggested Citation

  • S. Charan Kumar & Amit Kumar Thakur & J. Ronald Aseer & Sendhil Kumar Natarajan & Rajesh Singh & Neeraj Priyadarshi & Bhekisipho Twala, 2022. "An Experimental Analysis and ANN Based Parameter Optimization of the Influence of Microalgae Spirulina Blends on CI Engine Attributes," Energies, MDPI, vol. 15(17), pages 1-19, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6158-:d:896834
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/17/6158/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/17/6158/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Datta, Ambarish & Mandal, Bijan Kumar, 2016. "A comprehensive review of biodiesel as an alternative fuel for compression ignition engine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 799-821.
    2. Srihari, S. & Thirumalini, S. & Prashanth, K., 2017. "An experimental study on the performance and emission characteristics of PCCI-DI engine fuelled with diethyl ether-biodiesel-diesel blends," Renewable Energy, Elsevier, vol. 107(C), pages 440-447.
    3. Krishnamoorthi, M. & Malayalamurthi, R., 2018. "Engine characteristics analysis of chaulmoogra oil blends and corrosion analysis of injector nozzle using scanning electron microscopy/energy dispersive spectroscopy," Energy, Elsevier, vol. 165(PB), pages 1292-1319.
    4. Nirmala, N. & Dawn, S.S. & Harindra, C., 2020. "Analysis of performance and emission characteristics of Waste cooking oil and Chlorella variabilis MK039712.1 biodiesel blends in a single cylinder, four strokes diesel engine," Renewable Energy, Elsevier, vol. 147(P1), pages 284-292.
    5. Babu, D. & Thangarasu, Vinoth & Ramanathan, Anand, 2020. "Artificial neural network approach on forecasting diesel engine characteristics fuelled with waste frying oil biodiesel," Applied Energy, Elsevier, vol. 263(C).
    6. Nautiyal, Piyushi & Subramanian, K.A. & Dastidar, M.G. & Kumar, Ashok, 2020. "Experimental assessment of performance, combustion and emissions of a compression ignition engine fuelled with Spirulina platensis biodiesel," Energy, Elsevier, vol. 193(C).
    7. Can, Özer & Öztürk, Erkan & Yücesu, H. Serdar, 2017. "Combustion and exhaust emissions of canola biodiesel blends in a single cylinder DI diesel engine," Renewable Energy, Elsevier, vol. 109(C), pages 73-82.
    8. Datta, Ambarish & Mandal, Bijan Kumar, 2017. "Engine performance, combustion and emission characteristics of a compression ignition engine operating on different biodiesel-alcohol blends," Energy, Elsevier, vol. 125(C), pages 470-483.
    9. Dwivedi, Gaurav & Sharma, M.P., 2014. "Prospects of biodiesel from Pongamia in India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 114-122.
    10. Bahri, Bahram & Shahbakhti, Mahdi & Aziz, Azhar Abdul, 2017. "Real-time modeling of ringing in HCCI engines using artificial neural networks," Energy, Elsevier, vol. 125(C), pages 509-518.
    11. Mohamed Mohamed & Chee-Keong Tan & Ali Fouda & Mohammed Saber Gad & Osayed Abu-Elyazeed & Abdel-Fatah Hashem, 2020. "Diesel Engine Performance, Emissions and Combustion Characteristics of Biodiesel and Its Blends Derived from Catalytic Pyrolysis of Waste Cooking Oil," Energies, MDPI, vol. 13(21), pages 1-13, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pachiannan, Tamilselvan & Zhong, Wenjun & Rajkumar, Sundararajan & He, Zhixia & Leng, Xianying & Wang, Qian, 2019. "A literature review of fuel effects on performance and emission characteristics of low-temperature combustion strategies," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    2. Krishnamoorthi, M. & Malayalamurthi, R. & Sakthivel, R., 2019. "Optimization of compression ignition engine fueled with diesel - chaulmoogra oil - diethyl ether blend with engine parameters and exhaust gas recirculation," Renewable Energy, Elsevier, vol. 134(C), pages 579-602.
    3. Aydın, Selman, 2020. "Comprehensive analysis of combustion, performance and emissions of power generator diesel engine fueled with different source of biodiesel blends," Energy, Elsevier, vol. 205(C).
    4. Rajak, Upendra & Nashine, Prerana & Verma, Tikendra Nath, 2019. "Characteristics of microalgae spirulina biodiesel with the impact of n-butanol addition on a CI engine," Energy, Elsevier, vol. 189(C).
    5. Simsek, Suleyman & Uslu, Samet & Simsek, Hatice, 2022. "Proportional impact prediction model of animal waste fat-derived biodiesel by ANN and RSM technique for diesel engine," Energy, Elsevier, vol. 239(PD).
    6. Radhakumari, Muktham & Taha, Mohamed & Shahsavari, Esmaeil & Bhargava, Suresh K. & Satyavathi, Bankupalli & Ball, Andrew S., 2017. "Pongamia pinnata seed residue – A low cost inedible resource for on-site/in-house lignocellulases and sustainable ethanol production," Renewable Energy, Elsevier, vol. 103(C), pages 682-687.
    7. Jagtap, Sharad P. & Pawar, Anand N. & Lahane, Subhash, 2020. "Improving the usability of biodiesel blend in low heat rejection diesel engine through combustion, performance and emission analysis," Renewable Energy, Elsevier, vol. 155(C), pages 628-644.
    8. Upendra Rajak & Abhishek Dasore & Prem Kumar Chaurasiya & Tikendra Nath Verma & Prerana Nashine & Anil Kumar, 2023. "Effects of microalgae -ethanol-methanol-diesel blends on the spray characteristics and emissions of a diesel engine," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(1), pages 1-22, January.
    9. Gavaskar, T. & Ramanan M, Venkata & Arun, K. & Arivazhagan, S., 2023. "The combined effect of green synthesized nitrogen-doped carbon quantum dots blended jackfruit seed biodiesel and acetylene gas tested on the dual fuel engine," Energy, Elsevier, vol. 275(C).
    10. Jarosław Ziółkowski & Mateusz Oszczypała & Jerzy Małachowski & Joanna Szkutnik-Rogoż, 2021. "Use of Artificial Neural Networks to Predict Fuel Consumption on the Basis of Technical Parameters of Vehicles," Energies, MDPI, vol. 14(9), pages 1-23, May.
    11. Suiuay, Chokchai & Laloon, Kittipong & Katekaew, Somporn & Senawong, Kritsadang & Noisuwan, Phakamat & Sudajan, Somposh, 2020. "Effect of gasoline-like fuel obtained from hard-resin of Yang (Dipterocarpus alatus) on single cylinder gasoline engine performance and exhaust emissions," Renewable Energy, Elsevier, vol. 153(C), pages 634-645.
    12. Ennaceri, Houda & Fischer, Kristina & Schulze, Agnes & Moheimani, Navid Reza, 2022. "Membrane fouling control for sustainable microalgal biodiesel production: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    13. El-Shafay, A.S. & Ağbulut, Ümit & Attia, El-Awady & Touileb, Kamel Lounes & Gad, M.S., 2023. "Waste to energy: Production of poultry-based fat biodiesel and experimental assessment of its usability on engine behaviors," Energy, Elsevier, vol. 262(PB).
    14. Tolgahan Kaya & Osman Akın Kutlar & Ozgur Oguz Taskiran, 2018. "Evaluation of the Effects of Biodiesel on Emissions and Performance by Comparing the Results of the New European Drive Cycle and Worldwide Harmonized Light Vehicles Test Cycle," Energies, MDPI, vol. 11(10), pages 1-14, October.
    15. Hoseinpour, Marziyeh & Sadrnia, Hassan & Tabasizadeh, Mohammad & Ghobadian, Barat, 2017. "Energy and exergy analyses of a diesel engine fueled with diesel, biodiesel-diesel blend and gasoline fumigation," Energy, Elsevier, vol. 141(C), pages 2408-2420.
    16. Cao, Yan & Doustgani, Amir & Salehi, Abozar & Nemati, Mohammad & Ghasemi, Amir & Koohshekan, Omid, 2020. "The economic evaluation of establishing a plant for producing biodiesel from edible oil wastes in oil-rich countries: Case study Iran," Energy, Elsevier, vol. 213(C).
    17. Can, Özer & Baklacioglu, Tolga & Özturk, Erkan & Turan, Onder, 2022. "Artificial neural networks modeling of combustion parameters for a diesel engine fueled with biodiesel fuel," Energy, Elsevier, vol. 247(C).
    18. Jaliliantabar, Farzad & Ghobadian, Barat & Carlucci, Antonio Paolo & Najafi, Gholamhassan & Mamat, Rizalman & Ficarella, Antonio & Strafella, Luciano & Santino, Angelo & De Domenico, Stefania, 2020. "A comprehensive study on the effect of pilot injection, EGR rate, IMEP and biodiesel characteristics on a CRDI diesel engine," Energy, Elsevier, vol. 194(C).
    19. Elahi, Ehsan & Zhang, Zhixin & Khalid, Zainab & Xu, Haiyun, 2022. "Application of an artificial neural network to optimise energy inputs: An energy- and cost-saving strategy for commercial poultry farms," Energy, Elsevier, vol. 244(PB).
    20. Mahmudul, H.M. & Hagos, F.Y. & Mamat, R. & Adam, A. Abdul & Ishak, W.F.W. & Alenezi, R., 2017. "Production, characterization and performance of biodiesel as an alternative fuel in diesel engines – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 497-509.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6158-:d:896834. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.