IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i8p6353-d1118117.html
   My bibliography  Save this article

Analysis of Influencing Factors of Gangue Ball Milling Based on Multifractal Theory

Author

Listed:
  • Lei Zhu

    (China Coal Energy Research Institute, Xi’an 710054, China)

  • Wenzhe Gu

    (School of Energy and Mining Engineering, China University of Mining and Technology, Beijing 100083, China)

  • Fengqi Qiu

    (China Coal Energy Research Institute, Xi’an 710054, China)

  • Peng Zhang

    (China Coal Energy Research Institute, Xi’an 710054, China)

Abstract

To study the heterogeneity and local heterogeneity of gangue particle size distribution (PSD) under ball milling, gangue from northern Shaanxi coal mine was taken as a research object. The multifractal pattern of PSD and the variation trend of characteristic parameters of gangue under different ball-to-gangue ratios and grinding times were analyzed by introducing multifractal theory and microscopic research methods such as laser particle size analysis and scanning electron microscopy. The results show that the multifractal characteristics of the gangue particle size distribution with different ball-to-gangue ratios and grinding time periods demonstrate obvious changes. When the ball-to-gangue ratio is 3~9, the multifractal parameters D (0), D (1), Δ α , and Δ f all show linear changes with grinding time. It is demonstrated that due to the phenomenon of particle agglomeration during ball milling, the multifractal characteristics of the particle size distribution of the gangue changes significantly when the ball-to-gangue ratio is 12~15. Furthermore, the results indicate that with the increase in time, D (0), Δ α , and Δ f show a trend of decreasing first and then increasing, and D (1) and D (1)/ D (0) show a trend of first increasing and then decreasing, and both reach their extreme values at 30 min.

Suggested Citation

  • Lei Zhu & Wenzhe Gu & Fengqi Qiu & Peng Zhang, 2023. "Analysis of Influencing Factors of Gangue Ball Milling Based on Multifractal Theory," Sustainability, MDPI, vol. 15(8), pages 1-14, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6353-:d:1118117
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/8/6353/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/8/6353/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiaowei Zhai & Zhuo Cheng & Keyu Ai & Bo Shang, 2020. "Research on Environmental Sustainability of Coal Cities: A Case Study of Yulin, China," Energies, MDPI, vol. 13(10), pages 1-21, May.
    2. Zhao, Zhen-yu & Zhu, Jiang & Xia, Bo, 2016. "Multi-fractal fluctuation features of thermal power coal price in China," Energy, Elsevier, vol. 117(P1), pages 10-18.
    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. Tong, Zhongwen & Chen, Zhanbo & Zhu, Chen, 2022. "Nonlinear dynamics analysis of cryptocurrency price fluctuations based on Bitcoin," Finance Research Letters, Elsevier, vol. 47(PB).
    2. Fernandes, Leonardo H.S. & Silva, José W.L. & de Araujo, Fernando H.A. & Ferreira, Paulo & Aslam, Faheem & Tabak, Benjamin Miranda, 2022. "Interplay multifractal dynamics among metal commodities and US-EPU," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    3. T. Sivageerthi & Bathrinath Sankaranarayanan & Syed Mithun Ali & Ali AlArjani & Koppiahraj Karuppiah, 2022. "Modeling Challenges for Improving the Heat Rate Performance in a Thermal Power Plant: Implications for SDGs in Energy Supply Chains," Sustainability, MDPI, vol. 14(8), pages 1-19, April.
    4. Ding, Lili & Zhao, Zhongchao & Han, Meng, 2021. "Probability density forecasts for steam coal prices in China: The role of high-frequency factors," Energy, Elsevier, vol. 220(C).
    5. Fernandes, Leonardo H.S. & Silva, José W.L. & de Araujo, Fernando H.A., 2022. "Multifractal risk measures by Macroeconophysics perspective: The case of Brazilian inflation dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    6. Gu, Fu & Wang, Jiqiang & Guo, Jianfeng & Fan, Ying, 2020. "How the supply and demand of steam coal affect the investment in clean energy industry? Evidence from China," Resources Policy, Elsevier, vol. 69(C).
    7. Zeng, Lijun & Wang, Jinfeng & Zhang, Jinsuo & Sun, Zhimei & Santibanez Gonzalez, Ernesto D.R., 2021. "A path matching model on new urbanization in mineral resource abundant regions," Resources Policy, Elsevier, vol. 73(C).
    8. Huiyue Diao & Majid Ghorbani, 2018. "Production risk caused by human factors: a multiple case study of thermal power plants," Frontiers of Business Research in China, Springer, vol. 12(1), pages 1-27, December.
    9. Guo, Kun & Kang, Yuxin & Ma, Dandan & Lei, Lei, 2024. "How do climate risks impact the contagion in China's energy market?," Energy Economics, Elsevier, vol. 133(C).
    10. Zhang, Kefei & Cao, Hua & Thé, Jesse & Yu, Hesheng, 2022. "A hybrid model for multi-step coal price forecasting using decomposition technique and deep learning algorithms," Applied Energy, Elsevier, vol. 306(PA).
    11. Han, Chenyu & Wang, Yiming & Ning, Ye, 2019. "Analysis and comparison of the multifractality and efficiency of Chinese stock market: Evidence from dynamics of major indexes in different boards," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 528(C), pages 1-1.
    12. Yujing Liu & Ruoyun Du & Dongxiao Niu, 2022. "Forecast of Coal Demand in Shanxi Province Based on GA—LSSVM under Multiple Scenarios," Energies, MDPI, vol. 15(17), pages 1-16, September.
    13. Wu, Ruirui & Qin, Zhongfeng & Liu, Bing-Yue, 2022. "A systemic analysis of dynamic frequency spillovers among carbon emissions trading (CET), fossil energy and sectoral stock markets: Evidence from China," Energy, Elsevier, vol. 254(PA).
    14. Mhadhbi, Mayssa, 2024. "The interconnected carbon, fossil fuels, and clean energy markets: Exploring Europe and China's perspectives on climate change," Finance Research Letters, Elsevier, vol. 62(PB).
    15. Wu, Siping & Xia, Guilin & Liu, Lang, 2023. "A novel decomposition integration model for power coal price forecasting," Resources Policy, Elsevier, vol. 80(C).
    16. Han, Chenyu & Wang, Yiming & Ning, Ye, 2019. "Comparative analysis of the multifractality and efficiency of exchange markets: Evidence from exchange rates dynamics of major world currencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    17. Wu, Liangpeng & Xu, Chengzhen & Zhu, Qingyuan & Zhou, Dequn, 2024. "Multiple energy price distortions and improvement of potential energy consumption structure in the energy transition," Applied Energy, Elsevier, vol. 362(C).

    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:jsusta:v:15:y:2023:i:8:p:6353-:d:1118117. 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.