Numerical Study of the Effect of Splitter Blades on the Flow-Induced Noise of Hydraulic Turbine

Fengxia Shi; Guangbiao Zhao; Yucai Tang; Haonan Zhan; Pengcheng Wang

Numerical Study of the Effect of Splitter Blades on the Flow-Induced Noise of Hydraulic Turbine

Fengxia Shi School of Energy and Power Engineering, Lanzhou University of Technology, Lanzhou, 730050, China; Key Laboratory of Fluid Machinery and Systems of Gansu, Lanzhou, 730050, China
Guangbiao Zhao School of Energy and Power Engineering, Lanzhou University of Technology, Lanzhou, 730050, China
Yucai Tang School of Energy and Power Engineering, Lanzhou University of Technology, Lanzhou, 730050, China
Haonan Zhan School of Energy and Power Engineering, Lanzhou University of Technology, Lanzhou, 730050, China
Pengcheng Wang School of Energy and Power Engineering, Lanzhou University of Technology, Lanzhou, 730050, China

Article ID: 2645

Keywords: Hydraulic turbine; splitter blades; pressure fluctuation; sound field

Abstract

In order to study the effect of splitter blades on the internal and external sound field of the hydraulic turbine, the paper chose a centrifugal pump with a specific speed ns = 33 reversed as a hydraulic turbine as the research object, and added the short blades on the original impeller to form a new splitter impeller. Based on the Re-Normalization Group (RNG) k-ε turbulence model to conduct numerical simulation for the hydraulic turbine, this thesis calculated the internal and external acoustic field by means of the acoustic boundary element (BEM) and finite element (FEM) and analyzed the noise radiation characteristics of the two models under different working conditions. The results show that the blade frequency is the main factor affecting the inlet and outlet sound pressure, and the optimized model decreases the inlet and outlet sound pressure levels by 6.84 and 7.24 dB in optimal working conditions. Rotor-stator interaction is the main reason for the flow-induced noise of hydraulic turbine volute appearing, the optimized model can effectively reduce the impeller and volute rotor-stator interaction and the flow-induced noise of volute. Outfield maximum sound pressure appears at the inlet and the volute tongue, which decreased by 1.84, 6.07, and 5.24 dB at each operating condition. To sum up, splitter blades can improve hydraulic characteristics and flow field noise in the hydraulic turbine.

References

[1]Qi, B., Zhang, D. S., Li, Y., Shen, X., Geng, L. et al. (2021). A comparative study on the reducing flow rate design method for desalination energy recovery pump as turbine. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 43(9), 1–15.

[2]Liu, Z. Q., Xiao, Y. X., Wang, C. P., Zhu, Y., Liu, S. et al. (2021). Hydraulic performance analysis of reverse osmosis seawater desalination turbo energy recovery device. Journal of Hydropower Engineering, 40(2), 131–140.

[3]Lang, T., Liu, Y. T., Chen, K. Q., Xu, E. X., Jin, L. C. et al. (2021). Review of research on hydrodynamic noise of centrifugal pump. Journal of Drainage and Iirrigation Machinery Engineering, 39(1), 8–15.

[4]Dong, L., Dai, C., Kong, F. Y. (2016). Flow-induced noise characteristic and contribution to interior noise for centrifugal pump as turbine. Journal of Mechanical Engineering, 52(18), 184–192.

[5]Parrondo, J., Pérez, J., Barrio, R., González, J. (2011). A simple acoustic model to characterize the internal low frequency sound field in centrifugal pumps. Applied Acoustic, 72, 59–64.

[6]Argarin, J. D., Hambric, S. (2007). Using fluid velocity in lieu of impeller speed for dimensional analysis and a method for estimating fluid-borne noise due to flow turbulence within centrifugal pumps. Proceedings of IMECE, 10, 11–15.

[7]Guo, C., Gao, M., He, S. (2020). A review of the flow-induced noise study for centrifugal pumps. Applied Sciences, 10(3), 1022.

[8]Kato, C., Yamade, Y., Wang, H., Guo, Y., Miyazawa, M. et al. (2007). Numerical prediction of sound generated from flows with a low mach number. Computers & Fluids, 36(1), 53–68.

[9]Si, Q. R., Asad, A., Yuan, J. P., Ibra, J., Yasin, M. et al. (2019). Flow-induced noises in a centrifugal pump: A review. Science of Advanced Materials, 11(6), 1–16.

[10]Cheng, X. R., Li, T. P., Wang, P. (2020). Study on the influence of blade outlet cutting on hydraulic noise of centrifugal pump with low specific speed. Advances in Mechanical Engineering, 12(9), 349–368.

[11]Lu, J. X., Liu, X. B., Zeng, Y. Z., Zhu, B. S., Hu, B. et al. (2020). Investigation of the noise induced by unstable flow in a centrifugal pump. Energies, 13(3), 589.

[12]Paramasivam, K., Rajoo, S., Romagnoli, A. (2015). Suppression of tonal noise in a centrifugal fan using guide vanes. Journal of Sound and Vibration, 357, 95–106.

[13]Guo, R., Li, R. N., Zhang, R. H. (2019). Hydraulic and acoustic performance optimization design of matching between dynamic and static cascades of jet centrifugal pump. Transactions of the Chinese Society of Agricultural Machinery, 50(5), 148–158 (In Chinese).

[14]Dai, C., Dong, L., Kong, F. Y., Fu, L., Bai, Y. X. et al. (2016). Hydrodynamic noise characteristics research in centrifugal pump as turbine. Journal of Basic Science and Engineering, 24(5), 1034–1045.

[15]Dai, C., Ge, Z. P., Dong, L., Liu, H. L. (2020). Research on characteristics of drag reduction and noise reduction on V-groove. Huazhong University of Science & Technology, 48(9), 113–118 (In Chinese).

[16]Dong, L., Pan, Q., Liu, H. L., Dai, C., Xu, J. H. et al. (2019). Influence of impeller with splitter blades on jet self-priming centrifugal pump. Journal of Central South University, 50(8), 2033–2042 (In Chinese).

[17]Yang, S. S., Kong, F. Y., Xue, L., Hu, L. (2012). Effect of splitter blade on the performance of pump as turbine. Transactions of the Chinese Society for Agricultural Machinery, 43(7), 104–107 (In Chinese).

[18]Zhong, S. Y., Huang, X. (2018). A review of the development of aeroacoustics and flow noise, to beginners. Journal of Aerodynamics, 36(3), 363–371.

[19]Zhang, D. S., Zhang, N. S., Xu, B., Zhao, R. J., Gao, X. F. et al. (2021). Numerical study on unsteady flow induced noise of water jet propulsion pump based on lighthill acoustic analogy theory. Journal of Vibration and Shock, 40(10), 278–287.

[20]Guo, R., Li, X. B., Liu, X., Li, T. P. (2023). Effects of trapezoidal cutting at blade outlet on flow-induced noise of centrifugal pump volute. Journal of Vibration and Shock, 42(13), 82–91.

[21]Wang, X. H., Yang, J. H., Guo, Y. L., Xia, Z. (2018). Research on slip phenomenon of pumps as turbines. Journal of Mechanical Engineering, 54(24), 189–196.

[22]Cheng, X. R., Li, T. P., Liu, X., Wang, B. (2021). Research on the effect of blade outlet oblique cutting on centrifugal pump noise under the action of sound and vibration coupling. Technical Acoustics, 40(6), 843–850.

Published

2024-03-11

How to Cite

Shi, F., Zhao, G., Tang, Y., Zhan, H., & Wang, P. (2024). Numerical Study of the Effect of Splitter Blades on the Flow-Induced Noise of Hydraulic Turbine. Sound & Vibration, 58(1), 047082. Retrieved from https://ojs.acad-pub.com/index.php/SV/article/view/2645

Download Citation

Issue

Vol. 58 No. 1 (2024)

Section

Article

Editor-in-Chief

Prof. Jun Yang

Institute of Acoustics, Chinese Academy of Sciences, China

ISSN

1541-0161 (Print)

2693-1443 (Online)

Publication Frequency

Continuously

About the Publisher

Academic Publishing insists on taking academic exchange and publication as the main line, carrying out comprehensive management based on science and technology, and fully exploring excellent international publishing resources. Within 5 years, it will form a strategic framework and scale with science (S), technology (T), medicine (M), education (E), and humanities and arts (H) as the main publishing fields. Academic Publishing is headquartered in Singapore and based in Malaysia, with the United States and China providing the main scientific and academic resources. At the same time, it has established long-term good cooperative relations with other publishing companies, scientific research communities, and academic organizations in more than a dozen countries and regions. Academic Publishing uses English and Chinese as its main publishing languages, mainly publishing books, journals, and conference papers in print and online. The vast majority of publications follow the international open access policy, providing stable and long-term quality and professional publications. With the joint efforts of the expert team and our professional editorial team, our publications will gradually be indexed by international databases in stages to provide convenient and professional retrieval for various scholars. At the same time, manuscripts we accept will be subject to the peer review principle, and cutting-edge and innovative research articles will be preferentially accepted for peer reference and discussion. All kinds of our publications are welcome for peer to contribute, access, and download.

more

Volume Arrangement

Vol 59 Iss 1 (2025)

more issues

Featured Articles

Soundscapes in Arab Cities: A Systematic Review and Research Agenda

In the context of Arab cities, this study explores the intricate interplay between cultural, historical, and environmental elements that shape their unique soundscapes. The paper aims to shed light on this underrepresented field of study by employing a three-fold research approach: systematic review, a comprehensive literature review, and the formulation of a future research agenda. The first part of the investigation focuses on research productivity in the Arab world regarding soundscape studies. An analysis of publication trends reveals that soundscape research in Arab cities is still an emerging area of interest. Critical gaps in the existing body of literature are identified, highlighting the importance of addressing these gaps within the broader context of global soundscape research. The second part of the study delves into the distinctive features that inform the soundscapes of Arab cities. These features are categorized into three overarching groups: (i) cultural and religious life, (ii) daily life, and (iii) heritage and history, by exploring these factors, the study aims to elucidate the multifaceted nature of Arab urban soundscapes. From the resonating calls to prayer and the vibrant ambiance of traditional cafes to the bustling markets and architectural characteristics, each factor contributes to the auditory tapestry that defines Arab cities. The paper concludes with a forward-looking research agenda, proposing sixteen key questions organized into descriptive and comparative categories. These questions emphasize the need for a more profound understanding of sound perception, sources, and the impact of urban morphology on the soundscape. Additionally, they highlight the need for interdisciplinary research, involving fields such as urban planning, architecture, psychology, sociology, and cultural studies to unravel the complexity of Arab urban soundscapes.

Prediction of Sound Transmission Loss of Vehicle Floor System Based on 1D-Convolutional Neural Networks

The Noise, Vibration, and Harshness (NVH) experience during driving is significantly influenced by the sound insulation performance of the car floor acoustic package. As such, accurate and efficient predictions of its sound insulation performance are crucial for optimizing related noise reduction designs. However, the complex acoustic transmission mechanisms and difficulties in characterizing the sound absorption and insulation properties of the floor acoustic package pose significant challenges to traditional Computer-Aided Engineering (CAE) methods, leading to low modeling efficiency and prediction accuracy. To address these limitations, a hierarchical multi-objective decomposition system for predicting the sound insulation performance of the floor acoustic package has been developed based on an analysis of the noise transmission path. This approach involves introducing a 1D-Convolutional Neural Network (1D-CNN) model for predicting the sound insulation performance of the floor acoustic package, thereby avoiding the limitations of conventional CAE approaches that rely solely on “data-driven” methods. The proposed method was applied and tested using specific vehicle models, and the results demonstrated the effectiveness and superiority of the proposed approach relative to those obtained using 2D-CNN and Support Vector Regression (SVR) models.

A Sound Quality Evaluation Method for Vehicle Interior Noise Based on Auditory Loudness Model

When designing and optimizing the hull of vehicles, their sound quality needs to be considered, which greatly depends on the psychoacoustic parameters. However, the traditional psychoacoustic calculation method does not consider the influence of the real human ear anatomic structure, even the loudness which is most related to the auditory periphery. In order to introduce the real physiological structure of the human ear into the evaluation of vehicle sound quality, this paper first carried out the vehicle internal noise test to obtain the experimental samples. Then, the physiological loudness was predicted based on an established human ear physiological model, and the noise evaluation vector was constructed by combining the remaining four psychoacoustic parameters. Finally, the evaluation vector was fitted into the subjective evaluation results of vehicle interior noise by a deep neural network. The results show that our proposed method can estimate the human subjective perception of vehicle interior noise well.

Prediction and Analysis of Vehicle Interior Road Noise Based on Mechanism and Data Series Modeling

Currently, the inexorable trend toward the electrification of automobiles has heightened the prominence of road noise within overall vehicle noise. Consequently, an in-depth investigation into automobile road noise holds substantial practical importance. Previous research endeavors have predominantly centered on the formulation of mechanism models and data-driven models. While mechanism models offer robust controllability, their application encounters challenges in intricate analyses of vehicle body acoustic-vibration coupling, and the effective utilization of accumulated data remains elusive. In contrast, data-driven models exhibit efficient modeling capabilities and can assimilate conceptual vehicle knowledge, but they impose stringent requirements on both data quality and quantity. In response to these considerations, this paper introduces an innovative approach for predicting vehicle road noise by integrating mechanism-driven and data-driven methodologies. Specifically, a series model is devised, amalgamating mechanism analysis with data-driven techniques to predict vehicle interior noise. The simulation results from dynamic models serve as inputs to the data-driven model, ultimately generating outputs through the utilization of the Long Short-Term Memory with Autoencoder (AE-LSTM) architecture. The study subsequently undertakes a comparative analysis between different dynamic models and data-driven models, thereby validating the efficacy of the proposed series vehicle road noise prediction model. This series model, encapsulating the rigid-flexible coupling dynamic model and AE-LSTM series model, not only demonstrates heightened computational efficiency but also attains superior prediction accuracy.