IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v216y2023ics0960148123009722.html
   My bibliography  Save this article

LN cooling on mechanical properties and fracture characteristics of hot dry granites involving ANN prediction

Author

Listed:
  • Qu, Hai
  • Li, Chengying
  • Chen, Xiangjun
  • Liu, Xu
  • Guo, Ruichang
  • Liu, Ying

Abstract

Hot dry rock (HDR) development is essential to reduce carbon emission and achieve renewable energy applications. Liquid nitrogen (LN) fracturing can significantly create complex fractures in HDR. Understanding the damage characteristics of heated granites after LN cooling is essential. This study systematically investigates the mechanical properties of heated granites subjected to LN cooling, followed by a two-scale analysis for fracture morphology variation. Increasing rock temperature and cooling cycle cause more complex microcracks and macro fracture networks, leading to higher fragmentation degrees. The degradation of mechanical properties mainly occurs within the first 10 min and sixth cycles. After the six cycles, the failure model transforms from shear failure to a complex composite failure. The feldspar-to-quartz ratio was first proposed to quantitatively describe the relationship between the mechanical strength and granite types. The linear regression method developed two accurate models with four factors to predict the uniaxial compressive strength (UCS) and tensile strength (UTS). Artificial neural network models can precisely predict the UCS and UTS of various granites under different LN cooling parameters based on a comprehensive data set. It provides a novel method to optimize HDR stimulation based on artificial intelligence.

Suggested Citation

  • Qu, Hai & Li, Chengying & Chen, Xiangjun & Liu, Xu & Guo, Ruichang & Liu, Ying, 2023. "LN cooling on mechanical properties and fracture characteristics of hot dry granites involving ANN prediction," Renewable Energy, Elsevier, vol. 216(C).
  • Handle: RePEc:eee:renene:v:216:y:2023:i:c:s0960148123009722
    DOI: 10.1016/j.renene.2023.119058
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148123009722
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2023.119058?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Song, Guofeng & Song, Xianzhi & Ji, Jiayan & Wu, Xiaoguang & Li, Gensheng & Xu, Fuqiang & Shi, Yu & Wang, Gaosheng, 2022. "Evolution of fracture aperture and thermal productivity influenced by chemical reaction in enhanced geothermal system," Renewable Energy, Elsevier, vol. 186(C), pages 126-142.
    2. Zhang, Wei & Wang, Chunguang & Guo, Tiankui & He, Jiayuan & Zhang, Le & Chen, Shaojie & Qu, Zhanqing, 2021. "Study on the cracking mechanism of hydraulic and supercritical CO2 fracturing in hot dry rock under thermal stress," Energy, Elsevier, vol. 221(C).
    3. Kang, Fangchao & Jia, Tianrang & Li, Yingchun & Deng, Jianhui & Tang, Chun'an & Huang, Xin, 2021. "Experimental study on the physical and mechanical variations of hot granite under different cooling treatments," Renewable Energy, Elsevier, vol. 179(C), pages 1316-1328.
    4. Ogliari, Emanuele & Guilizzoni, Manfredo & Giglio, Alessandro & Pretto, Silvia, 2021. "Wind power 24-h ahead forecast by an artificial neural network and an hybrid model: Comparison of the predictive performance," Renewable Energy, Elsevier, vol. 178(C), pages 1466-1474.
    5. Aliyu, Musa D. & Archer, Rosalind A., 2021. "A thermo-hydro-mechanical model of a hot dry rock geothermal reservoir," Renewable Energy, Elsevier, vol. 176(C), pages 475-493.
    6. Kartal, Furkan & Özveren, Uğur, 2022. "Prediction of torrefied biomass properties from raw biomass," Renewable Energy, Elsevier, vol. 182(C), pages 578-591.
    7. Diaz, Melvin B. & Kim, Kwang Yeom, 2020. "Improving rate of penetration prediction by combining data from an adjacent well in a geothermal project," Renewable Energy, Elsevier, vol. 155(C), pages 1394-1400.
    8. Zhu, Zhennan & Kempka, Thomas & Ranjith, Pathegama Gamage & Tian, Hong & Jiang, Guosheng & Dou, Bin & Mei, Gang, 2021. "Changes in thermomechanical properties due to air and water cooling of hot dry granite rocks under unconfined compression," Renewable Energy, Elsevier, vol. 170(C), pages 562-573.
    9. Asai, Pranay & Podgorney, Robert & McLennan, John & Deo, Milind & Moore, Joseph, 2022. "Analytical model for fluid flow distribution in an Enhanced Geothermal Systems (EGS)," Renewable Energy, Elsevier, vol. 193(C), pages 821-831.
    10. Yang, Ruiyue & Hong, Chunyang & Liu, Wei & Wu, Xiaoguang & Wang, Tianyu & Huang, Zhongwei, 2021. "Non-contaminating cryogenic fluid access to high-temperature resources: Liquid nitrogen fracturing in a lab-scale Enhanced Geothermal System," Renewable Energy, Elsevier, vol. 165(P1), pages 125-138.
    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. Li, Mingyao & Sun, Hefeng & Peng, Lei & Zuo, Jianping & Wang, Zhenbo, 2024. "Laboratory investigation on physical and mechanical behaviors of granite after heating and different cooling rates," Energy, Elsevier, vol. 302(C).

    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. Xue, Yi & Liu, Shuai & Chai, Junrui & Liu, Jia & Ranjith, P.G. & Cai, Chengzheng & Gao, Feng & Bai, Xue, 2023. "Effect of water-cooling shock on fracture initiation and morphology of high-temperature granite: Application of hydraulic fracturing to enhanced geothermal systems," Applied Energy, Elsevier, vol. 337(C).
    2. Aliyu, Musa D. & Finkbeiner, Thomas & Chen, Hua-Peng & Archer, Rosalind A., 2023. "A three-dimensional investigation of the thermoelastic effect in an enhanced geothermal system reservoir," Energy, Elsevier, vol. 262(PA).
    3. Shi, Yu & Xu, Fuqiang & Song, Xianzhi & Wang, Gaosheng & Zuo, Yinhui & Li, Xiaojiang & Ji, Jiayan, 2023. "Rock damage evolution in the production process of the enhanced geothermal systems considering thermal-hydrological-mechanical and damage (THM-D)," Energy, Elsevier, vol. 285(C).
    4. Zhao, Peng & Liu, Jun & Elsworth, Derek, 2023. "Numerical study on a multifracture enhanced geothermal system considering matrix permeability enhancement induced by thermal unloading," Renewable Energy, Elsevier, vol. 203(C), pages 33-44.
    5. Xu, Fuqiang & Shi, Yu & Song, Xianzhi & Wu, Wei & Song, Guofeng & Li, Shuang, 2024. "Experimental characterization of damage during geothermal production of hot dry rocks: Comprehensive effects of the damage-elastic deformation on conductivity evolution," Energy, Elsevier, vol. 294(C).
    6. Qiao, Mingzheng & Jing, Zefeng & Feng, Chenchen & Li, Minghui & Chen, Cheng & Zou, Xupeng & Zhou, Yujuan, 2024. "Review on heat extraction systems of hot dry rock: Classifications, benefits, limitations, research status and future prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 196(C).
    7. Wang, Song & Zhou, Jian & Zhang, Luqing & Han, Zhenhua & Kong, Yanlong, 2024. "Numerical insight into hydraulic fracture propagation in hot dry rock with complex natural fracture networks via fluid-solid coupling grain-based modeling," Energy, Elsevier, vol. 295(C).
    8. Qiang Li & Tubing Yin & Xibing Li & Ronghua Shu, 2021. "Experimental and Numerical Investigation on Thermal Damage of Granite Subjected to Heating and Cooling," Mathematics, MDPI, vol. 9(23), pages 1-15, November.
    9. Liu, Ling & Wang, Jujie & Li, Jianping & Wei, Lu, 2023. "An online transfer learning model for wind turbine power prediction based on spatial feature construction and system-wide update," Applied Energy, Elsevier, vol. 340(C).
    10. Mohamed Elgharib Gomah & Guichen Li & Changlun Sun & Jiahui Xu & Sen Yang & Jinghua Li, 2022. "On the Physical and Mechanical Responses of Egyptian Granodiorite after High-Temperature Treatments," Sustainability, MDPI, vol. 14(8), pages 1-22, April.
    11. Oliveira, Augusto Cesar Laviola de & Renato, Natalia dos Santos & Martins, Marcio Arêdes & Mendonça, Isabela Miranda de & Moraes, Camile Arêdes & Lago, Lucas Fernandes Rocha, 2023. "Renewable energy solutions based on artificial intelligence for farms in the state of Minas Gerais, Brazil: Analysis and proposition," Renewable Energy, Elsevier, vol. 204(C), pages 24-38.
    12. Xie, Jingxuan & Wang, Jiansheng, 2022. "Compatibility investigation and techno-economic performance optimization of whole geothermal power generation system," Applied Energy, Elsevier, vol. 328(C).
    13. Zheng, Peng & Xia, Yucheng & Yao, Tingwei & Jiang, Xu & Xiao, Peiyao & He, Zexuan & Zhou, Desheng, 2022. "Formation mechanisms of hydraulic fracture network based on fracture interaction," Energy, Elsevier, vol. 243(C).
    14. Justyna Kujawska & Monika Kulisz & Piotr Oleszczuk & Wojciech Cel, 2023. "Improved Prediction of the Higher Heating Value of Biomass Using an Artificial Neural Network Model Based on the Selection of Input Parameters," Energies, MDPI, vol. 16(10), pages 1-16, May.
    15. Jiansheng, Wang & Lide, Su & Qiang, Zhu & Jintao, Niu, 2022. "Numerical investigation on power generation performance of enhanced geothermal system with horizontal well," Applied Energy, Elsevier, vol. 325(C).
    16. Guo, Tiankui & Zhang, Yuelong & He, Jiayuan & Gong, Facheng & Chen, Ming & Liu, Xiaoqiang, 2021. "Research on geothermal development model of abandoned high temperature oil reservoir in North China oilfield," Renewable Energy, Elsevier, vol. 177(C), pages 1-12.
    17. Haitham M. Ahmed & Hussin A. M. Ahmed & Sefiu O. Adewuyi, 2021. "Characterization of Microschist Rocks under High Temperature at Najran Area of Saudi Arabia," Energies, MDPI, vol. 14(22), pages 1-20, November.
    18. Zhang, Jiansong & Liu, Yongsheng & Lv, Jianguo & Gao, Wenlong, 2024. "The flow and heat transfer characteristics of supercritical mixed-phase CO2 and N2 in a 3D self-affine rough fracture," Energy, Elsevier, vol. 303(C).
    19. Han, Yixiao & Liao, Yanfen & Ma, Xiaoqian & Guo, Xing & Li, Changxin & Liu, Xinyu, 2023. "Analysis and prediction of the penetration of renewable energy in power systems using artificial neural network," Renewable Energy, Elsevier, vol. 215(C).
    20. Jing Wan & Jiehui Huang & Zhiyuan Liao & Chunquan Li & Peter X. Liu, 2022. "A Multi-View Ensemble Width-Depth Neural Network for Short-Term Wind Power Forecasting," Mathematics, MDPI, vol. 10(11), pages 1-20, May.

    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:eee:renene:v:216:y:2023:i:c:s0960148123009722. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.