IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i22p5911-d444165.html
   My bibliography  Save this article

Investigation on the Mechanism of Heat Load Reduction for the Thermal Anti-Icing System

Author

Listed:
  • Rongjia Li

    (College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Guangya Zhu

    (Interdisciplinary Research Institute of Aeronautics and Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Dalin Zhang

    (Interdisciplinary Research Institute of Aeronautics and Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

Abstract

The aircraft ice protection system that can guarantee flight safety consumes a part of the energy of the aircraft, which is necessary to be optimized. A study for the mechanism of the heat load reduction in the thermal anti-icing system under the evaporative mode was presented. Based on the relationship between the anti-icing heat load and the heating power distribution, an optimization method involved in the genetic algorithm was adopted to optimize the anti-icing heat load and obtain the optimal heating power distribution. An experiment carried out in an icing wind tunnel was conducted to validate the optimized results. The mechanism of the anti-icing heat load reduction was revealed by analyzing the influences of the key factors, such as the heating range, the surface temperature and the convective heat transfer coefficient. The results show that the reduction in the anti-icing heat load is actually the decrease in the convective heat load. In the evaporative mode, decreasing the heating range outside the water droplet impinging limit can reduce the convective heat load. Evaporating the runback water in the high-temperature region can lead to the less convective heat load. For the airfoil, the heating power distribution that has an opposite trend with the convective heat transfer coefficient can reduce the convective heat load. Thus, the optimal heating power distribution has such a trend that is low at the leading edge, high at the water droplet impinging limit and zero at the end of the protected area.

Suggested Citation

  • Rongjia Li & Guangya Zhu & Dalin Zhang, 2020. "Investigation on the Mechanism of Heat Load Reduction for the Thermal Anti-Icing System," Energies, MDPI, vol. 13(22), pages 1-19, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:22:p:5911-:d:444165
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/22/5911/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/22/5911/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Villalpando, Fernando & Reggio, Marcelo & Ilinca, Adrian, 2016. "Prediction of ice accretion and anti-icing heating power on wind turbine blades using standard commercial software," Energy, Elsevier, vol. 114(C), pages 1041-1052.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dirk Deschrijver, 2021. "Special Issue: “Improving Energy Efficiency through Data-Driven Modeling, Simulation and Optimization”," Energies, MDPI, vol. 14(6), pages 1-3, March.

    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. Chen, Wanqiu & Qiu, Yingning & Feng, Yanhui & Li, Ye & Kusiak, Andrew, 2021. "Diagnosis of wind turbine faults with transfer learning algorithms," Renewable Energy, Elsevier, vol. 163(C), pages 2053-2067.
    2. Fahed Martini & Hussein Ibrahim & Leidy Tatiana Contreras Montoya & Patrick Rizk & Adrian Ilinca, 2022. "Turbulence Modeling of Iced Wind Turbine Airfoils," Energies, MDPI, vol. 15(22), pages 1-20, November.
    3. Wu, Zhenlong & Bangga, Galih & Cao, Yihua, 2019. "Effects of lateral wind gusts on vertical axis wind turbines," Energy, Elsevier, vol. 167(C), pages 1212-1223.
    4. Maddi Aizpurua-Etxezarreta & Sheila Carreno-Madinabeitia & Alain Ulazia & Jon Sáenz & Aitor Saenz-Aguirre, 2022. "Long-Term Freezing Temperatures Frequency Change Effect on Wind Energy Gain (Eurasia and North America, 1950–2019)," Sustainability, MDPI, vol. 14(9), pages 1-15, May.
    5. Guo, Wenfeng & Shen, He & Li, Yan & Feng, Fang & Tagawa, Kotaro, 2021. "Wind tunnel tests of the rime icing characteristics of a straight-bladed vertical axis wind turbine," Renewable Energy, Elsevier, vol. 179(C), pages 116-132.
    6. Wu, Zhenlong, 2019. "Rotor power performance and flow physics in lateral sinusoidal gusts," Energy, Elsevier, vol. 176(C), pages 917-928.
    7. Stoyanov, D.B. & Nixon, J.D. & Sarlak, H., 2021. "Analysis of derating and anti-icing strategies for wind turbines in cold climates," Applied Energy, Elsevier, vol. 288(C).
    8. Wang, Haipeng & Zhang, Bo & Qiu, Qinggang & Xu, Xiang, 2017. "Flow control on the NREL S809 wind turbine airfoil using vortex generators," Energy, Elsevier, vol. 118(C), pages 1210-1221.
    9. Cheng Tao & Tao Tao & Xinjian Bai & Yongqian Liu, 2023. "Wind Turbine Blade Icing Prediction Using Focal Loss Function and CNN-Attention-GRU Algorithm," Energies, MDPI, vol. 16(15), pages 1-15, July.
    10. Valery Okulov & Ivan Kabardin & Dmitry Mukhin & Konstantin Stepanov & Nastasia Okulova, 2021. "Physical De-Icing Techniques for Wind Turbine Blades," Energies, MDPI, vol. 14(20), pages 1-16, October.
    11. Fahed Martini & Adrian Ilinca & Patrick Rizk & Hussein Ibrahim & Mohamad Issa, 2022. "A Survey of the Quasi-3D Modeling of Wind Turbine Icing," Energies, MDPI, vol. 15(23), pages 1-32, November.

    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:13:y:2020:i:22:p:5911-:d:444165. 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.