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Numerical study of the effect of ultrasound waves on the turbulent flow with chemical reaction

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  • shateri, Amirali
  • jalili, Bahram
  • saffar, Saber
  • Jalili, Payam
  • Domiri Ganji, Davood

Abstract

In this study, a numerical analysis of turbulent flow in a combustion chamber with a Reynolds number of 16700 was conducted, focusing on the application of a 20 kHz ultrasound wave from a bowl-shaped diffusion source for 1 s to reduce process temperature within 5 ms. The study employed the k-ω model, with turbulence-chemistry interaction modeled using the eddy dissipation concept to achieve this. Additionally, the relocation of nozzles was explored, increasing CO2 combustion from 0.31 to 0.34 by decreasing the distance between them. The most optimal distance for locating the nozzles was identified as Di 0.0.1 (Di = 4.58 mm), which exhibited a higher burning rate and increased velocity and temperature during the process. Furthermore, a spray angle of 45° was determined as the optimal angle for minimizing fuel film on the walls and improving combustion. The application of ultrasound waves facilitated the transfer of flame concentration from the walls to the chamber's center, effectively reducing unburnt hydrocarbons on the walls. Notably, the propagation of ultrasound waves significantly accelerated the combustion process by 0.5 ms, setting this study apart from previous investigations.

Suggested Citation

  • shateri, Amirali & jalili, Bahram & saffar, Saber & Jalili, Payam & Domiri Ganji, Davood, 2024. "Numerical study of the effect of ultrasound waves on the turbulent flow with chemical reaction," Energy, Elsevier, vol. 289(C).
    • Handle: RePEc:eee:energy:v:289:y:2024:i:c:s0360544223031018
    DOI: 10.1016/j.energy.2023.129707
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    References listed on IDEAS

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    1. Ehsaniderakhshan, Faeze & Mazaheri, Kiumars & Mahmoudi, Yasser, 2020. "Large eddy simulation on combustion noise in a non-premixed turbulent free flame: Effect of oxygen enhancement," Energy, Elsevier, vol. 210(C).
    2. Naji, Sareh & Keivani, Afram & Shamshirband, Shahaboddin & Alengaram, U. Johnson & Jumaat, Mohd Zamin & Mansor, Zulkefli & Lee, Malrey, 2016. "Estimating building energy consumption using extreme learning machine method," Energy, Elsevier, vol. 97(C), pages 506-516.
    3. Duan, Xiongbo & Liu, Jingping & Yuan, Zhipeng & Guo, Genmiao & Liu, Qi & Tang, Qijun & Deng, Banglin & Guan, Jinhuan, 2018. "Experimental investigation of the effects of injection strategies on cycle-to-cycle variations of a DISI engine fueled with ethanol and gasoline blend," Energy, Elsevier, vol. 165(PB), pages 455-470.
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