IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i17p2167-d629386.html
   My bibliography  Save this article

Optimization of Microjet Location Using Surrogate Model Coupled with Particle Swarm Optimization Algorithm

Author

Listed:
  • Mohammad Owais Qidwai

    (Department of Mechanical Engineering, Delhi Skill and Entrepreneurship University, Okhla Campus-1, Okhla Industrial Estate, Phase-III, New Delhi 110020, India)

  • Irfan Anjum Badruddin

    (Mechanical Engineering Department, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia)

  • Noor Zaman Khan

    (Department of Mechanical Engineering, National Institute of Technology Srinagar, Hazratbal, Srinagar 190006, Jammu and Kashmir, India)

  • Mohammad Anas Khan

    (Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi 110025, India)

  • Saad Alshahrani

    (Mechanical Engineering Department, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia)

Abstract

This study aimed to present the design methodology of microjet heat sinks with unequal jet spacing, using a machine learning technique which alleviates hot spots in heat sinks with non-uniform heat flux conditions. Latin hypercube sampling was used to obtain 30 design sample points on which three-dimensional Computational Fluid Dynamics (CFD) solutions were calculated, which were used to train the machine learning model. Radial Basis Neural Network (RBNN) was used as a surrogate model coupled with Particle Swarm Optimization (PSO) to obtain the optimized location of jets. The RBNN provides continuous space for searching the optimum values. At the predicted optimum values from the coupled model, the CFD solution was calculated for comparison. The percentage error for the target function was 0.56%, whereas for the accompanied function it was 1.3%. The coupled algorithm has variable inputs at user discretion, including gaussian spread, number of search particles, and number of iterations. The sensitivity of each variable was obtained. Analysis of Variance (ANOVA) was performed to investigate the effect of the input variable on thermal resistance. ANOVA results revealed that gaussian spread is the dominant variable affecting the thermal resistance.

Suggested Citation

  • Mohammad Owais Qidwai & Irfan Anjum Badruddin & Noor Zaman Khan & Mohammad Anas Khan & Saad Alshahrani, 2021. "Optimization of Microjet Location Using Surrogate Model Coupled with Particle Swarm Optimization Algorithm," Mathematics, MDPI, vol. 9(17), pages 1-19, September.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:17:p:2167-:d:629386
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/17/2167/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/17/2167/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Khudhayr A. Rashedi & Mohd Tahir Ismail & Nawaf N. Hamadneh & S. AL Wadi & Jamil J. Jaber & Muhammad Tahir & Riaz Ahmad, 2021. "Application of Radial Basis Function Neural Network Coupling Particle Swarm Optimization Algorithm to Classification of Saudi Arabia Stock Returns," Journal of Mathematics, Hindawi, vol. 2021, pages 1-8, April.
    2. Abo-Zahhad, Essam M. & Ookawara, Shinichi & Radwan, Ali & El-Shazly, A.H. & Elkady, M.F., 2019. "Numerical analyses of hybrid jet impingement/microchannel cooling device for thermal management of high concentrator triple-junction solar cell," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    3. Jaroslaw Krzywanski, 2019. "A General Approach in Optimization of Heat Exchangers by Bio-Inspired Artificial Intelligence Methods," Energies, MDPI, vol. 12(23), pages 1-32, November.
    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. Taher Maatallah & Mussad Alzahrani & Souheil El Alimi & Sajid Ali, 2025. "Optothermal Modeling for Sustainable Design of Ultrahigh-Concentration Photovoltaic Systems," Sustainability, MDPI, vol. 17(12), pages 1-20, June.
    2. Asmaa Ahmed & Katie Shanks & Senthilarasu Sundaram & Tapas Kumar Mallick, 2020. "Theoretical Investigation of the Temperature Limits of an Actively Cooled High Concentration Photovoltaic System," Energies, MDPI, vol. 13(8), pages 1-10, April.
    3. Karolina Papis-Frączek & Krzysztof Sornek, 2022. "A Review on Heat Extraction Devices for CPVT Systems with Active Liquid Cooling," Energies, MDPI, vol. 15(17), pages 1-49, August.
    4. Cameron, William J. & Shanks, Katie & Mallick, Tapas K. & Reddy, K. Srinivas, 2024. "Theoretical investigation of height and width tapered microchannel cooling systems for ultra-high concentrator photovoltaic thermal hybrids," Renewable Energy, Elsevier, vol. 234(C).
    5. Dorian Skrobek & Jaroslaw Krzywanski & Marcin Sosnowski & Anna Kulakowska & Anna Zylka & Karolina Grabowska & Katarzyna Ciesielska & Wojciech Nowak, 2020. "Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)," Energies, MDPI, vol. 13(24), pages 1-16, December.
    6. Kang, Ying & Xia, Zhi-xun & Luo, Zhen-bing & Deng, Xiong & Zhu, Yin-xin & Peng, Can, 2024. "Experimental study on a dual synthetic jets liquid cooling device," Applied Energy, Elsevier, vol. 372(C).
    7. Du, Yadong & Hu, Chenxing & Yang, Ce & Wang, Haimei & Dong, Wuqiang, 2022. "Size optimization of heat exchanger and thermoeconomic assessment for supercritical CO2 recompression Brayton cycle applied in marine," Energy, Elsevier, vol. 239(PD).
    8. Fahad Ghallab Al-Amri & Taher Maatallah & Richu Zachariah & Ahmed T. Okasha & Abdullah Khalid Alghamdi, 2022. "Enhanced Net Channel Based-Heat Sink Designs for Cooling of High Concentration Photovoltaic (HCPV) Systems in Dammam City," Sustainability, MDPI, vol. 14(7), pages 1-22, March.
    9. Grabowska, K. & Sztekler, K. & Krzywanski, J. & Sosnowski, M. & Stefanski, S. & Nowak, W., 2021. "Construction of an innovative adsorbent bed configuration in the adsorption chiller part 2. experimental research of coated bed samples," Energy, Elsevier, vol. 215(PA).
    10. Aroa González Fuentes & Nélida M. Busto Serrano & Fernando Sánchez Lasheras & Gregorio Fidalgo Valverde & Ana Suárez Sánchez, 2020. "Prediction of Health-Related Leave Days among Workers in the Energy Sector by Means of Genetic Algorithms," Energies, MDPI, vol. 13(10), pages 1-16, May.
    11. Seong Won Moon & Tong Seop Kim, 2020. "Advanced Gas Turbine Control Logic Using Black Box Models for Enhancing Operational Flexibility and Stability," Energies, MDPI, vol. 13(21), pages 1-23, October.
    12. Abou-Ziyan, Hosny & Ibrahim, Mohammed & Abdel-Hameed, Hala, 2020. "Performance modeling and analysis of high-concentration multi-junction photovoltaics using advanced hybrid cooling systems," Applied Energy, Elsevier, vol. 269(C).
    13. Peng, Hao & Du, Yanlian & Hu, Fenfen & Tian, Zhen & Shen, Yijun, 2023. "Thermal management of high concentrator photovoltaic system using a novel double-layer tree-shaped fractal microchannel heat sink," Renewable Energy, Elsevier, vol. 204(C), pages 77-93.
    14. Maghrabie, Hussein M., 2021. "Heat transfer intensification of jet impingement using exciting jets - A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    15. Wang, Wei-Wei & Liu, Teng & Guo, Jun-Zhe & Li, Bin & Zhang, Hong-Liang & Cai, Yang & Zhao, Fu-Yun & Liu, Di, 2025. "Experimental investigation on the thermal performance of high-concentrated photovoltaic module utilizing the thermal sink of a novel Fan-shaped plate pulsating heat pipe," Applied Energy, Elsevier, vol. 377(PA).
    16. Marcin Sosnowski & Jaroslaw Krzywanski & Norbert Skoczylas, 2022. "Adsorption Desalination and Cooling Systems: Advances in Design, Modeling and Performance," Energies, MDPI, vol. 15(11), pages 1-6, May.
    17. Chen, Weixiong & Qian, Yiran & Tang, Xin & Fang, Huawei & Yi, Jingwei & Liang, Tiebo & Zhao, Quanbin & Yan, Junjie, 2023. "System-component combined design and comprehensive evaluation of closed-air Brayton cycle," Energy, Elsevier, vol. 278(C).
    18. Wen, Xiaoqiang & Li, Kaichuang & Wang, Jianguo, 2023. "NOx emission predicting for coal-fired boilers based on ensemble learning methods and optimized base learners," Energy, Elsevier, vol. 264(C).
    19. Ahmed T. Okasha & Fahad Ghallab Al-Amri & Taher Maatallah & Nagmeldeen A. M. Hassanain & Abdullah Khalid Alghamdi & Richu Zachariah, 2022. "Numerical Study of Single-Layer and Stacked Minichannel-Based Heat Sinks Using Different Truncating Ratios for Cooling High Concentration Photovoltaic Systems," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    20. Waqar Muhammad Ashraf & Ghulam Moeen Uddin & Muhammad Farooq & Fahid Riaz & Hassan Afroze Ahmad & Ahmad Hassan Kamal & Saqib Anwar & Ahmed M. El-Sherbeeny & Muhammad Haider Khan & Noman Hafeez & Arman, 2021. "Construction of Operational Data-Driven Power Curve of a Generator by Industry 4.0 Data Analytics," Energies, MDPI, vol. 14(5), pages 1-18, February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jmathe:v:9:y:2021:i:17:p:2167-:d:629386. 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.