IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v13y2016i6p594-d72053.html
   My bibliography  Save this article

Generation Mechanism and Prediction Model for Low Frequency Noise Induced by Energy Dissipating Submerged Jets during Flood Discharge from a High Dam

Author

Listed:
  • Jijian Lian

    (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, China)

  • Wenjiao Zhang

    (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, China)

  • Qizhong Guo

    (Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA)

  • Fang Liu

    (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, China)

Abstract

As flood water is discharged from a high dam, low frequency ( i.e ., lower than 10 Hz) noise (LFN) associated with air pulsation is generated and propagated in the surrounding areas, causing environmental problems such as vibrations of windows and doors and discomfort of residents and construction workers. To study the generation mechanisms and key influencing factors of LFN induced by energy dissipation through submerged jets at a high dam, detailed prototype observations and analyses of LFN are conducted. The discharge flow field is simulated using a gas-liquid turbulent flow model, and the vorticity fluctuation characteristics are then analyzed. The mathematical model for the LFN intensity is developed based on vortex sound theory and a turbulent flow model, verified by prototype observations. The model results reveal that the vorticity fluctuation in strong shear layers around the high-velocity submerged jets is highly correlated with the on-site LFN, and the strong shear layers are the main regions of acoustic source for the LFN. In addition, the predicted and observed magnitudes of LFN intensity agree quite well. This is the first time that the LFN intensity has been shown to be able to be predicted quantitatively.

Suggested Citation

  • Jijian Lian & Wenjiao Zhang & Qizhong Guo & Fang Liu, 2016. "Generation Mechanism and Prediction Model for Low Frequency Noise Induced by Energy Dissipating Submerged Jets during Flood Discharge from a High Dam," IJERPH, MDPI, vol. 13(6), pages 1-24, June.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:6:p:594-:d:72053
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/13/6/594/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/13/6/594/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Catherine Marquis-Favre & Julien Morel, 2015. "A Simulated Environment Experiment on Annoyance Due to Combined Road Traffic and Industrial Noises," IJERPH, MDPI, vol. 12(7), pages 1-21, July.
    2. Stéphane Perron & Céline Plante & Martina S. Ragettli & David J. Kaiser & Sophie Goudreau & Audrey Smargiassi, 2016. "Sleep Disturbance from Road Traffic, Railways, Airplanes and from Total Environmental Noise Levels in Montreal," IJERPH, MDPI, vol. 13(8), pages 1-21, August.
    3. Park, Sewan & Park, Sunho & Rhee, Shin Hyung, 2016. "Influence of blade deformation and yawed inflow on performance of a horizontal axis tidal stream turbine," Renewable Energy, Elsevier, vol. 92(C), pages 321-332.
    4. David O. Baloye. & Lobina G. Palamuleni, 2015. "A Comparative Land Use-Based Analysis of Noise Pollution Levels in Selected Urban Centers of Nigeria," IJERPH, MDPI, vol. 12(10), pages 1-22, September.
    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. Jijian Lian & Xiaoqun Wang & Wenjiao Zhang & Bin Ma & Dongming Liu, 2017. "Multi-Source Generation Mechanisms for Low Frequency Noise Induced by Flood Discharge and Energy Dissipation from a High Dam with a Ski-Jump Type Spillway," IJERPH, MDPI, vol. 14(12), pages 1-23, November.

    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. Liu, Zhen & Qu, Hengliang, 2022. "Numerical study on a coupled-pitching flexible hydrofoil under the semi-passive mode," Renewable Energy, Elsevier, vol. 189(C), pages 339-358.
    2. Zhang, Mengjie & Liu, Taotao & Huang, Biao & Wu, Qin & Wang, Guoyu, 2020. "Hydrodynamic characteristics and flow structures of pitching hydrofoil with special emphasis on the added force effect," Renewable Energy, Elsevier, vol. 157(C), pages 560-573.
    3. Modali, Pranav K. & Vinod, Ashwin & Banerjee, Arindam, 2021. "Towards a better understanding of yawed turbine wake for efficient wake steering in tidal arrays," Renewable Energy, Elsevier, vol. 177(C), pages 482-494.
    4. Jördis Wothge & Christin Belke & Ulrich Möhler & Rainer Guski & Dirk Schreckenberg, 2017. "The Combined Effects of Aircraft and Road Traffic Noise and Aircraft and Railway Noise on Noise Annoyance—An Analysis in the Context of the Joint Research Initiative NORAH," IJERPH, MDPI, vol. 14(8), pages 1-19, August.
    5. Irene van Kamp & Sendrick Simon & Hilary Notley & Christos Baliatsas & Elise van Kempen, 2020. "Evidence Relating to Environmental Noise Exposure and Annoyance, Sleep Disturbance, Cardio-Vascular and Metabolic Health Outcomes in the Context of IGCB (N): A Scoping Review of New Evidence," IJERPH, MDPI, vol. 17(9), pages 1-21, April.
    6. Zhang, Mengjie & Wu, Qin & Wang, Guoyu & Huang, Biao & Fu, Xiaoying & Chen, Jie, 2020. "The flow regime and hydrodynamic performance for a pitching hydrofoil," Renewable Energy, Elsevier, vol. 150(C), pages 412-427.
    7. El Fajri, Oumnia & Bowman, Joshua & Bhushan, Shanti & Thompson, David & O'Doherty, Tim, 2022. "Numerical study of the effect of tip-speed ratio on hydrokinetic turbine wake recovery," Renewable Energy, Elsevier, vol. 182(C), pages 725-750.
    8. Peter Lercher & Bert De Coensel & Luc Dekonink & Dick Botteldooren, 2017. "Community Response to Multiple Sound Sources: Integrating Acoustic and Contextual Approaches in the Analysis," IJERPH, MDPI, vol. 14(6), pages 1-34, June.
    9. Guillermo Rey Gozalo & Juan Miguel Barrigón Morillas, 2016. "Analysis of Sampling Methodologies for Noise Pollution Assessment and the Impact on the Population," IJERPH, MDPI, vol. 13(5), pages 1-18, May.
    10. Gabl, Roman & Innerhofer, Daniel & Achleitner, Stefan & Righetti, Maurizio & Aufleger, Markus, 2018. "Evaluation criteria for velocity distributions in front of bulb hydro turbines," Renewable Energy, Elsevier, vol. 121(C), pages 745-756.

    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:jijerp:v:13:y:2016:i:6:p:594-:d:72053. 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.